Night World Spellbinder Chapter 11 Free Essays

string(23) " A geyser of loathing\." I don’t understand,† Eric said pitifully as Thea towed him toward the bleachers. â€Å"Well, that’s reasonable.† â€Å"Blaise wants to talk to me alone and you want me to do it. We will write a custom essay sample on Night World : Spellbinder Chapter 11 or any similar topic only for you Order Now † â€Å"That’s right.† Thea hadn’t realized it was possible to sound bright and bleak at the same time. â€Å"I told you she’d probably go after you-â€Å" â€Å"And you told me to be careful of her. You made the point very strongly.† â€Å"I know. It’s just†¦Ã¢â‚¬  Thea searched for an explanation that wouldn’t be too much of a lie and clutched her bottle of Evian water. She didn’t need to ask him if he had the protective charm with him- she could smell New Hampshire pine needles. â€Å"It’s just that I think it’s better to get things settled,† she said finally. â€Å"One way or the other. So maybe if you talk to her face-to-face†¦ well, you can decide what you want, and we can get this over with.† â€Å"Thea†¦Ã¢â‚¬  Eric stopped, forcing Thea to stop, too. He looked completely bewildered. â€Å"Thea-I don’t know what you’re thinking, but I don’t need to talk to Blaise to know what I want.† He put his hands gently on her upper arms. â€Å"Nothing she can say could make any difference.† Thea looked at him, at his clean, good features and his expressive eyes. He thought things were so simple. â€Å"Then you can just tell her that,† she said, trying to sound optimistic. â€Å"And the whole thing will be resolved.† Eric shook his head, but allowed her to guide him onward. Blaise was leaning against a concrete dugout by the baseball diamond. When they were about ten feet away, Thea stopped and nodded at Eric to keep going. He walked to Blaise, who slowly straightened with the leisurely grace of a snake uncoiling. Thea put her thumb into the Evian bottle and jiggled it gently. â€Å"Thea said you wanted to talk to me.† Eric’s voice was polite, but not encouraging. He looked back at Thea after he said it. â€Å"I did,† Blaise said in her liquid, persuasive voice. But to Thea’s surprise, she addressed the ground, as if she felt awkward. â€Å"But now†¦ well, I feel so embarrassed. I know what you probably think of me-trying to say something like this while your girlfriend is standing there.† â€Å"Well†¦Ã¢â‚¬  Eric glanced back at Thea again. â€Å"It’s okay,† he added, his voice softer. â€Å"I mean, it’s better to say whatever it is in front of her than behind her back.† â€Å"Yes. Yes, that’s true.† Blaise took a deep breath as if steeling herself and then lifted her head to meet Eric’s eyes. What on earth is she doing? Thea stared at her cousin. Where did this scene come from? â€Å"Eric†¦ I don’t know how to say this, but†¦ I care about you. I know how that sounds. You’re thinking that I have dozens of guys, and the way I treat them I can’t possibly care about any of them. And I don’t blame you if you just want to walk away right now, without even listening to any more.† Blaise fiddled with the zipper at her throat. â€Å"Oh, look, I’m not going to walk away. I wouldn’t do that to you,† Eric said, and his voice was even more gentle. â€Å"Thank you. You’re being so nice-much nicer than I deserve.† Absently, as if it were the most casual of gestures, Blaise reached for the zipper at her throat and pulled it down. The necklace was revealed. Don’t look directly at it, Thea told herself. She stared instead at the back of Eric’s sandy head-which suddenly went very still. â€Å"And you know, this is going to sound strange, but most of those boys don’t really like me.† Blaise’s voice was soft now-seductive but vulnerable. â€Å"They just-want me. They look at the surface, and never even try to see any deeper. And that makes me feel†¦ so lonely sometimes.† In Thea’s peripheral vision, gold stars and moons were shifting and flowing. Yemonja root and other delicious scents wafted toward her. She hadn’t even noticed that the first time; she’d been too deep in the necklace’s spell to analyze it. And a faint, high resonance hung in the air-two or three notes that seemed to shimmer almost above the threshold of hearing. Singing crystals. Of course. Blaise was assaulting every sense, weaving an inescapable golden web†¦ and the whole thing was tuned to Eric’s blood. â€Å"All I’ve ever wanted is a guy who cares enough about me to look deeper than the surface.† Blaise’s voice had a slight catch now. â€Å"And-well, before I knew Thea liked you, I guess I thought you might be that guy. Eric, please tell me-is that completely impossible? Should I just totally give up hope? Because if you say so, I will.† Eric was standing oddly now, as if he were crippled. Thea could see his breath coming faster. She didn’t want to see his face-she knew what it would be like. Like Luke’s. Blank wonder changing into slow adulation for Blaise. â€Å"Just tell me,† Blaise said, raising one hand in a gesture full of pathos. â€Å"And if you say no, I’ll go away forever. But if†¦ if you think you could care about me†¦ even just a little†¦Ã¢â‚¬  She gazed at him with luminous, yearning eyes. â€Å"I†¦Ã¢â‚¬  Eric’s voice was thick and hesitant. â€Å"I†¦ Blaise†¦Ã¢â‚¬  He couldn’t seem to get started on a sentence. And no wonder. He’s lost already. Certainty hit Thea, and she stopped shaking her plastic bottle. Her little Elixir of Abhorrence didn’t stand a chance against Blaise’s magic. Eric was hooked and Blaise was reeling him in. And it wasn’t his fault. Nobody could be expected to hold out against the kind of enchantment Blaise was using. Enchantment and psychology so beautifully mixed that even Thea found herself half believing Blaise’s story. But she had to try anyway. She couldn’t let Eric go without a fight. With one final, violent shake, Thea took her thumb out of the bottle neck. Colorless liquid skyrocketed, spraying up and then raining down on Eric. A geyser of loathing. You read "Night World : Spellbinder Chapter 11" in category "Essay examples" Only one thing went wrong. As soon as the mysterious downpour hit Eric, he turned to see where it was coming from. Instead of looking at Blaise when the elixir soaked into his skin, he was looking at Thea. She stared back into his gray-flecked eyes with a kind of horror. Twice. He’d been twice enchanted now, once to love Blaise and once to hate her. Oh, Eileithyia, it’s over†¦. It was a crisis, and Thea responded instinctively. She reached for Eric, to save him, to be saved herself. She flung out a thought the way she’d fling out a hand to someone going over a cliff. Eric. A connection†¦ Like dosing a circuit-and that was all it took. Thea felt a wave of†¦ something, something hot and sweet, more magical than Blaise’s magic. Distilled lightning, maybe. The air between her and Eric was so charged that she felt as though her skin was being brushed with velvet. It was like being at the intersection of cosmic force lines. And it was all okay. Eric’s face was his ordinary face. Alive, alert, full of warmth-for her. Not zombie worship for Blaise. Thea. It can’t be this simple. But it was. She and Eric were staring at each other in the quivering air and the universe was just one big singing crystal. We’re right together. A yell shattered the silent communion. Thea looked toward the dugout and saw that Blaise the vulnerable had disappeared. â€Å"I’m wet,† Blaise shrieked. â€Å"Are you crazy? Do you have any idea what water drops do to silk?† Thea opened her mouth, then shut it again. She felt giddy with the sweetness of relief. She had no idea if Blaise really thought the elixir was only water-but one thing was clear. However strong Blaise’s spell had been, it was broken now. And Blaise knew it. Blaise jerked the zipper up and stalked off. â€Å"She’s mad,† Eric said. â€Å"Well†¦Ã¢â‚¬  Thea was still dizzy. â€Å"I told you she likes getting mad.† She took Eric’s arm, very gently, and partly to steady herself. â€Å"Let’s go.† They’d only gone a few steps when Eric said, â€Å"Thank God you hit me with that water.† â€Å"Yes.† Even if the elixir hadn’t worked it had somehow broken Eric’s concentration or distracted Blaise or something. She’d have to see if she could figure out what had happened to disrupt a spell as potent as the one Blaise had created†¦. â€Å"Yeah, because, you know, it was getting really awkward,† Eric went on. â€Å"I kept trying to think of a polite way to tell her there wasn’t a chance, but I couldn’t. And just when I realized I was going to have to say it and hurt her feelings-well, you soaked us.† Thea stopped dead. She stared at him. He was serious. â€Å"I mean-I know I hurt her feelings anyway. Or she wouldn’t have gone away mad. Uh, are you mad now? Thea?† She started walking again. â€Å"Are you saying you didn’t even want to be with her? Not even just a little?† He stopped. â€Å"How could I want to be with her when I want to be with you? I told you that before this whole thing started.† Maybe it’s because we’re soulmates. Maybe it’s because he’s so stubborn. But, whatever, I’d better never tell Blaise. She’ll have a whole new reason for killing him if she finds out her spell bounced off like water off a duck. â€Å"Well, anyway, it’s resolved now,† she murmured-and at that moment she really believed it. She was too happy to think about anything dreadful. â€Å"Is it? Does that mean that we can finally go out? Like on a date?† He sounded so wistful that Thea laughed. She felt light and free and full of energy. â€Å"Yeah. We could go right now. Or†¦ we could go in. Your house, I mean. I’d like to see your sister and Madame Curie again.† Eric made an â€Å"ouch† face. â€Å"Well, Madame Curie would probably like that. But Roz lost her case- the court ruled that the Boy Trekkers are a private organization. And she is not-pardon the pun-a happy camper.† â€Å"All the more reason we should go see her. Poor kid.† Eric looked at her quizzically. â€Å"You’re serious? You have a choice of anywhere in Las Vegas and you’d like to go to my house?† â€Å"Why not?† Thea didn’t mention that a human house was more exotic to her than anywhere else in Vegas. She was happy. It turned out to be a modest frame house, shaded by a couple of honest-to-goodness trees, not palms. Thea felt a twinge of shyness as they went inside. â€Å"Mom’s still at work. And†-Eric checked his watch-â€Å"Roz is supposed to be in her room until five. Home detention. This morning she microwaved her Barbie dolls.† â€Å"That doesn’t sound good for the microwave.† Rosamund’s door was plastered with homemade Signs. DO NOT ENTER. KEEP OUT AND THIS MEANS ERIC. FEMINISM IS THE RADICAL NOTION THAT WOMEN ARE PEOPLE. When Eric opened the door a piggy bank shaped like a skunk came flying toward him. He ducked. It hit the wall and, amazingly, didn’t break. â€Å"Roz-â€Å" â€Å"I hate everybody! And everybody hates me!† A hardback book came soaring. Eric shut the door fast. Bang. â€Å"Everybody doesn’t hate you!† he yelled. â€Å"Well, I hate them! Go away!† Bang. Bang. Crash. â€Å"I think maybe we’d better leave her alone,† Eric said. â€Å"She gets a little moody sometimes. Want to see my room?† His room was nice, Thea decided. Lots of books, some smelling of mildew-â€Å"I get them at the used book stores.† Comparative Vertebrate Anatomy. Development and Structure of the Fetal Pig. The Red Pony. Most of them were about animals in some form or other. And lots of trophies. Baseball trophies, basketball trophies, a few tennis trophies. â€Å"I have to switch between baseball and tennis different years.† Sports equipment was scattered carelessly around, mixed with the books and some dirty socks. Not so different from a teenager’s room in the Night World. Just a person’s room. There was a picture of a man on the desk, a man with sandy hair and a glorious, lightning-bolt smile like Eric’s. â€Å"Who is it?† â€Å"My dad. He died when Roz was little-a plane crash. He was a pilot.† Eric said it simply, but his eyes went dark. Thea said softly, â€Å"My parents died when I was little, too. What’s sad is that I don’t really remember them.† Eric looked at the picture again. â€Å"You know, I never thought about it, but I’m glad I do remember. At least we had him that long.† They smiled at each other. By the bed was a tank that gave off a pleasant percolating sound. Thea sat next to it and watched iridescent blue fish dart around. She turned off the bedside lamp to see the lighted tank better. â€Å"You like it?† â€Å"I like everything,† Thea said. She looked at him. â€Å"Everything.† Eric blinked. He eyed the bed Thea was sitting on, then slowly sat at the desk. He stuck out a casual elbow to lean on and papers showered to the floor. â€Å"Oops.† Thea stifled a laugh. â€Å"Is that the U.C. Davis application?† He looked up hopefully from gathering them. â€Å"It sure is. Want to see it?† Thea almost said yes. She was in such a cheerful mood, ready to agree to anything, be open to anything. But a moment of thought changed her mind. Some things were just going too far. â€Å"Not right now, thanks.† â€Å"Well†¦Ã¢â‚¬ He put the papers back. â€Å"You know, you still might think about transferring to the zoology class at school. Ms. Gasparro is a great teacher. And you’d really like what we’re studying.† Maybe I could, Thea thought. What would it hurt? â€Å"And if you were ever interested. Dr. Salinger is always looking for extra help. It doesn’t pay much, but it’s good experience.† And†¦ what would that hurt? It’s not as if I would be breaking any laws. I wouldn’t have to use any powers, either, I could just be close to the animals. â€Å"I’ll think about it,† she said. She could hear the suppressed excitement in her own voice. She looked at Eric, who was sitting with his elbows on his knees, leaning forward, watching her earnestly. â€Å"And- thanks,† she said softly. â€Å"For what?† â€Å"For†¦ wanting the best for me. For caring.† The light from the fish tank threw wavering blue patterns on the walls and ceiling. It made the bedroom seem like its own little underwater world. It danced over Thea’s skin. Eric stared at her. Then he swallowed and shut his eyes. With his eyes still shut, he said in a muted voice, â€Å"I don’t think you know how much I care.† Then he looked at her. That connection again. It seemed to be drawing them together-an almost physical feeling of attraction. It was exciting, but scary. Eric got up very slowly and crossed the room. He sat by Thea. Neither of them looked away. And then things just seemed to happen by themselves. Their fingers were intertwined. Thea was looking up and he was looking down. They were so close that their breath mingled. Thea shivered with the electricity. Everything seemed wrapped in a golden haze. Crash. Something hit the other side of the wall. â€Å"Ignore it; it’s poltergeists,† Eric murmured. His lips were an inch from hers. â€Å"It’s Rosamund,† Thea murmured back. â€Å"She feels bad-and it’s not really fair. We should try and make her feel better.† She was so happy that she wanted everyone else to be happy, too. Eric groaned. â€Å"Thea†¦Ã¢â‚¬  â€Å"Let me just go see if I can cheer her up. I’ll come back.† Eric shut his eyes, opened them, and turned on the lamp. He gave her a pained smile. â€Å"Okay. I have to water Mom’s outside plants and feed the rabbits and stuff, anyway. Let me know when she’s cheered up enough. I’ll be waiting.† Thea knocked and ducked as she entered Rosamund’s room. â€Å"Roz? Can I just talk to you for a minute?† â€Å"Don’t call me that. I want you to call me Fred.† â€Å"Uh, how come Fred?† Thea sat cautiously on the edge of the bed-or not the bed, actually, the box springs. The mattress was across the room, standing on its side in a corner. The entire room looked as if it had been hit simultaneously by a hurricane and an earthquake, and it smelled strongly of guinea pig. Slowly, part of a sandy head appeared above the mattress. One green eye regarded Thea directly. â€Å"Because,† Rosamund said with terrible maturity, â€Å"I’m not a girl anymore. Things have always been this way for girls and they will always be this way and they are never going to change. And don’t give me any of that B.S. about how females hear better and do better in submarines and have better fine motor skills, because I don’t care. I’m going to be a boy now.† â€Å"You’re a smart kid,† Thea said. She was surprised at how smart Roz was, and at how much she wanted to comfort her. â€Å"But you need to study your history. Things haven’t always been this way. There were times when women and men were equals.† Rosamund just said, â€Å"When?† â€Å"Well-in ancient Crete, for one thing. They were all children of Eileithyia, the Great Goddess, and boys and girls both did dangerous stuff, like acrobatics on wild bulls. Of course†¦Ã¢â‚¬  Thea paused, struck by a thought. â€Å"The Greeks did come and conquer them.† â€Å"Uh-huh.† â€Å"But, um†-Thea wracked her brain for human history-â€Å"Well, the ancient Celts were okay-until the Romans came and conquered them. And†¦ and†¦Ã¢â‚¬  Human history was a problem. â€Å"I told you,† Rosamund said bitterly. â€Å"It always turns out the same. Now go away.† â€Å"Well†¦Ã¢â‚¬  Thea hesitated. It was the excitement that did it. The giddy feeling of everything being right with the world. It made her overconfident, made her feel as if Night World law were a little thing that could be dispensed with if necessary. Don’t, a part of her mind whispered. Don’t or you’ll be sorry. But Rosamund was so miserable. And the golden glow was still around Thea, making her feel protected. Invulnerable. â€Å"Look,† she said. â€Å"This may not help much, but I’ll tell you a story, a story that always made me feel better when I was a little girl. Only you have to keep it a secret.† There was a flicker of interest in Rosamund’s green eyes. â€Å"A true story?† â€Å"Well-I can’t really say it’s true.† And that’s true-I can’t. â€Å"But it’s a good story, and it’s about a time when women were leaders. About a girl called Hellewise.† How to cite Night World : Spellbinder Chapter 11, Essay examples

Self Defense free essay sample

Self-Defense means to fight or struggle, and take effective realistic measures to defend oneself. The course is designed to help people with no previous experience and all fitness levels in the shortest possible time. All kinds of people of different age groups are encouraged to take this training. Through this, people have learned effective street-proven self-defense techniques in the light of modern military defensive tactics, first-aid, CPR, applied anti-rape and anti-hijacking techniques, adrenal response and rear management, firefighting and mind control and meditation. It provides the highest level of training to deal with stressful situations and how to overcome fear and be able to utilize various safety and protective measures to ensure ones safety and survival. And also teaches those many tricks and helps them to be more aware of their surroundings thereby engendering confidence in females so that they can move around more independently without feeling totally helpless. SD is different from all other self defense techniques because it keeps the real life context in mind, situations such as carjacking, hijacking, kidnappings, sexual assault, armed robbery, criminal attacks, gang violence, school and workplace massacres, child abductions are just to name a few. We will write a custom essay sample on Self Defense or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page There are many self defense programs which claim to be reality based, however they are not, they simply see themselves as training realistically, abandoning all traditional customs but they fail to provide the key ingredients to a complete self defense. This training puts emphasis on gross motor skills and adrenaline rush. Fear and stress that is due to high adrenal rush or similar confrontational situations will enhance once speed, reflex and reactions to assault, that is the key to this self defense program. And will also help the trainees learn the warning signals of an impending attack and the typical rhythm, plans and tactics of an attacker.

Enteral and Parenteral Nutrition Essay Example

Enteral and Parenteral Nutrition Essay Which critically ill patients should receive TPN? Prof R D Griffiths in conjunction with Fresenius-Kabi Why are these guidelines required? In the critical care setting, nutritional support influences the outcome for critically ill patients. This guideline seeks to outline the important role of parenteral nutrition in the critically ill patient. Enteral and parenteral nutrition The enteral route for nutrition delivery is preferred where it can be safely delivered in the absence of gastrointestinal intolerance. For a small proportion of patients enteral feeding is not possible but in addition for a larger proportion of patients research consistently shows that enteral nutrition does not always cover the total nutritional needs of intensive care unit patients. There has been a reluctance to use parenteral nutrition (PN) or to supplement enteral (EN) or oral nutrition with parenteral nutrition (PN) for the perceived risk that to do so increases the infection and mortality risk. Systematic review evidence acquired from studies in the critically ill shows that while there may be an increased risk of infection there is no added mortality risk [ 1 ]. Parenteral nutrition has changed considerably over the last forty years and many of the complications were a feature of historical PN practice associated with its inappropriate use, unbalanced formulations and liberal overfeeding. Even the risk of infection may be more related to the underlying patient disease and indication for PN rather than modern PN formulations and delivery in ICU. We will write a custom essay sample on Enteral and Parenteral Nutrition specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Enteral and Parenteral Nutrition specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Enteral and Parenteral Nutrition specifically for you FOR ONLY $16.38 $13.9/page Hire Writer Malnourishment It has been estimated that around 40% of all patients in hospital are undernourished and this is associated with further complications. Acute critically ill patients lose on average approximately 5-10% of skeletal muscle mass per week during their ICU stay [ 3 ]. Complications such as septicaemia in these patients are to a large extent caused by malnutrition and impaired immunological function [ 2 ]. Complications versus choice of nutrition route When correctly applied, the complications of PN are less likely to result in death compared with those of EN. Recent studies conclude that PN compared with early EN is risk-neutral overall [ 3 ]. It is reassuring that in critically ill patients, when used with EN in the ICU as a supplement, PN has been confirmed to be risk-neutral or may even offer benefits. However from current data it is not possible to justify the extra cost of supplemental PN when started concurrently with EN at the start of an ICU admission [ 1 ] but more importantly there are no studies where it has been started in the more appropriate situation after EN has been shown to fail in already malnourished ICU patients. It has been demonstrated that nutritional goals were reached in 22% of ICU patients fed via EN compared with 75% with PN [ 2 ]. It must be remembered that under nutrition is a debt that must eventually be repaid and this is also worse if it is compounded! The ACCEPT study showed that survival from intensive care was improved when an evidence based guideline for nutrition was followed and more nutrition delivered more consistently. This was achieved by earlier introduction and more complete enteral nutrition delivery without any decline in the use of PN alone or in supplementation. Using the guidelines These guidelines have been developed using a step-by-step approach as follows: Step 1ASSESSMENTDoes the patient require nutritional support? Step 2ADMINISTRATIONWhich route(s) should be used? Step 3ACHIEVEMENT (REVIEW)Are nutrition goals being met? Step 1 Nutritional Risk Screening (adapted from NRS 2002 ESPEN) Does this patient require nutritional support? Initial screening of patients is recommended in these guidelines but it is assumed that ALL patients fulfill the criteria for requiring a final screening assessment which follows. The adaptation assumes an affirmative answer to the question â€Å"Is the patient severely ill? (e. g. in intensive care) Impaired nutritional statusSeverity of disease (increase in requirements) Score 0Normal nutritional statusScore 0Normal nutritional requirements Score 1 Wt loss 5% in 3 months or foodScore 1Hip fracture. Chronic patients in (Mild)intake below 50-75% of normal particular acute complications of requirements in preceding weekcirrhosis, COPD. Chronic diabetes haemodialysis, oncology. Score 2Wt loss 5% in 2 months or BMIScore 2Major abdominal surgery, stroke, (Moderate)18. -20. 5 + impaired general condition orsevere pneumonia, haematologic food intake 25-60% of normal requirement malignancy. in preceding week. Score 3Wt loss 15% in 3 months or BMI Score 3Head injury, Bone marrow transplant (Severe)18. 5 + impaired general condition orIntensive Care Patients (APACHE 10) food intake 0-25% of normal requirement in preceding week SCORE+ SCORE= TOTAL SCORE AGE ADJUSTMENT (IF PATIENT ? 70 YRS ADD 1 TO TOTAL SCORE)= TAAS SCORE INTERPRETATION SCORE ? 3The patient is nutritionally at risk and a nutritional plan should be initiated. SCORE 3Weekly re-screening of the patient. If the patient is scheduled for a major operation a preventative nutrition plan should be considered to avoid associated risk status. Step 2Administration route(s) Nutritional support does influence the outcome of critically ill patients and evidence suggests that the consistent achievement of nutritional goals is important and this should if feasible be through the enteral route [ 7 ]. Evidence suggests that for most patients this is just as effectively and safely delivered through a naso-gastric tube compared to tubes sited after the stomach [ 1 ]. It must be recognized that problems do occur with all forms of enteral delivery and that delivery is more often attained by the parenteral route3 and this is apparent in critically ill patients where enteral nutrition is inappropriate, contraindicated or has failed. Parenteral nutrition should be used when the GI tract is not functional or cannot be accessed or when the patient’s nutrient needs are greater than those which can be met through the GI tract. However it should not be commenced in the non-malnourished as a supplement until approaches to enteral delivery have been optimized [ 1 ]. Assess the integrity and function of the bowel using the following prompts: IF THE ANSWER IS â€Å"NO† TO EITHER QUESTION – TIME TO CONSIDER PN Is the digestive tract functioning? Is the patient well nourished and recovery of gut function expected within 3 days? IF THE ANSWER IS â€Å"YES† TO EITHER QUESTION – TIME TO CONSIDER PN While using an enteral feeding protocol does the presence of excess gastric aspirates (e. g. persistently 150mls after measures to improve gastric emptying) lead to reduced enteral intake. Does the nutrition equirements of the disease or injury exceed that which can be delivered safely via the enteral route? Some patients with an intact GI tract do not tolerate enteral feeds or do not receive sufficient intake enterally or orally to meet their energy and protein requirements. The reasons for poor gastric emptying should be considered. Simple measures such as turning to the right side or reducing opiate intake may be tried along w ith short trials of either Metoclopramide or Erythromycin if other causes have been excluded. However gastrointestinal intolerance is an important and worrying sign and is associated with increased pneumonia and risk of death independently of illness severity . The supine posture is also associated with increased risk of aspiration pneumonia and if patients cannot be nursed in the semi-erect position parenteral nutrition may be a safer option whether it is used as a supplement or as the sole source of nutrition in these patients [ 6 ]. Choice of feed and amounts In the critical care setting estimation or measurement of precise requirements is fraught with error. A target of 25 kcal/kg/day for the first week is acceptable. Protein intake is the central component as this cannot be stored metabolically. Most evidence supports 1. 5 gm/kg/day as a reasonable target. Requirements change during an illness and generally increase in the second week and when patients become more active. Simple methods using patient size bands based upon accessible measures of body size (height or weight) should be used to calculate target amounts. More sophisticated individual patient calculations have not been shown to be any more accurate. Polymeric complete enteral feeds should be used for most patients and infused continuously. Evidence for the use of specific formulations is lacking, except that the immunonutrition cocktails that contain extra arginine should NOT be given [ 1 ] outside of the peri-operative setting where evidence exists. An all-in-one complete balanced parenteral formulation should be used and evidence based recommendations suggests where practical these should contain glutamine [ 1 ]. They should be delivered continuously through a dedicated lumen that should not be used for any other access. Some of the energy should come from lipid sources but there is paucity of evidence to suggest any particular lipid formulations although this may change as more advanced formulations come on the market. Caution should be applied when other lipid containing infusions are also in use (e. g. propofol). Lipid infusion is safe at rates up to 1. 5 gm/kg/day, and glucose should be given at 3-4 gm/kg/day. Use simple standardized regimens for most patients. Within ICU acute electrolyte management (e. g. potassium and phosphate) is more readily managed by separate infusions if safe systems exist. Patients on renal support will have increased nutritional losses so maintain on full feeding. Important when using either EN or PN Nutrition should be commenced at reduced rates especially in the malnourished until metabolic tolerance established. Increase to full target over a 3 day period and monitor for re-feeding syndrome. It is possible to overfeed with PN but unless glucose intake exceeds 4-5 gm/kg/day hyperglycaemia indicates peripheral insulin resistance and the need for additional insulin and not reduction in feed volume. Step 3 Are nutrition goals being achieved? Set targets and check nutrition intake daily and act upon the findings. It is recommended that calorie (and nitrogen) intake is calculated daily in addition to the fluid balance. Has the patient received the amount of nutrition prescribed over previous days? Nutritional support, once instigated, should be monitored to confirm the safety of treatment. The following guide illustrates the type of monitoring required. The tests required will depend upon duration and method of feeding. The frequency of testing will vary depending on the illness severity. Fluid balance and calorie intake and if possible weight. Urea and electrolytes daily (watch K+ as feeds may have only a modest K+ content) Blood glucose monitored frequently and preferably as part of a tight glycaemic control. Phosphate (This should be monitored closely especially when starting feeds in the malnourished) Plasma lipid clearance or triglycerides Full blood count Liver function tests, Calcium Magnesium Calculation or measurement of nitrogen balance is not reliable in the routine setting. Nutrition support algorithm summary ASSESS Is nutritional support required? 40% of patients admitted to hospital are undernourished REASSESS Supplemental PN? ADMINISTER Which route? Is enteral feeding practical and safe? If not consider PN ACHIEVE and REVIEW Are you satisfying the nutrient needs of the patient? N Y WEANING STRATEGY If on EN can oral intake be started? If on PN can EN be started?

Favorite person essays

Favorite person essays Do you know the baseball player who has been in both the Hall of Fame and on the All-Century Team while also playing in 15 All-star games? Well, I do, hes Lawrence Peter Berra, known to many as Yogi Berra. Lawrence was born on May 12, 1925, in St. Louis, Missouri. He grew up on Elizabeth St., in a neighborhood called The Hill. His father worked in a shoe factory, and young Lawdie, as he was called by his friends, decided he didnt want to do that kind of work so he picked up sports. He found out that he was actually good at it and could play as well as or better than any kid in the neighborhood. He got his nickname Yogi from his friend Bobby Hofman when they went to a movie about India. They saw this old swami who was called Yoga and so his friends started to call him Yoga and it soon turned into Yogi. For the record Yogi Bear (the cartoon) got its name from Yogi Berra, not the other way around. Yogi only went to school through the 8th grade. In 1942 Yogi was playing minor league ball. Yogis friend Joe Garagiola was offered $500 dollars to sign with the Cardinals, and Yogi figured that he would get a $500 dollar contract too. The Cardinals decided that one $500 dollar kid was enough, and only offered Yogi $250, which he turned down. The Yankees felt that he was worth the money so they signed him for $500 in 1943. The Giants manager, Mel Ott, saw him play and tried to offer the Yankees $50,000 for Yogis contract. The Yankees manager decided if Mel Ott thought he was worth that much money he had better keep him. Yogi played for Norfolk in 1943, then entered the Navy at age 18. He was assigned to a rocket launcher during the Normandy Invasion at Omaha Beach, and in North Africa and Italy, and was finally stationed back in the States. After his discharge he reported to the Yankees in his Navy uniform and was looked at like some kind of clown. He was...

Reading discussion facilitation assignment Essay

Reading discussion facilitation assignment - Essay Example ies such as crime and violence due to lack of parental guidance. In addition, the Philippine media also inclined to infer that the absence of motherly care can be liken to abandonment (Parrenas et al. 44), which could give rise to the supposition that all children, deficient of familiar reinforcement, will become social burdens (44). In The Care Crisis in the Philippines: Children and Transnational Families in the New Global Economy, Parrenas et al. describes how the existing society view women migration. They contend that the modern day standpoint on the migration of women workers, that is, to create a significant emotional hardship to the children in transnational households and the postulated solution that is to call for the migration of the women workers to return to nuclear family do not sufficiently address the problem. Parrenas et al. argues that there are other factors that threaten the well-being of children i.e. domestic violence and male infidelity (53); and it should not exclusively be cast on the migration of women workers. The prevalent gender ideology that is commonly accepted in most civilizations retains the importance of the role of the mothers in the welfare of the children. And while many people believe that fathers too have the responsibility to provide care of their children, primary care is almost entirely linked to women. Therefore, this predating ideology on gender strains the recent development in the labour force, that is, more and more women are taking the roles of men as provider. Particularly, in the Philippines, â€Å"care is now the country’s primary export† (41); and since women are deemed to be the primary care provider, many Filipina workers are migrating every year to other countries to work as domestic helpers and nannies, sacrificing their children, in order to afford them with better opportunities in life. They care for other people’s children while leaving their own children to kinship care. Whether i t is a culturally-shaped societal stance on gender ideology, migration of women has been always criticized by the media because it jeopardizes the conventional structure of a nuclear family. Transnational household arrangements are often viewed by critics as focal point for the proliferation of juvenile delinquency and the increase of social liabilities for the government. However, in a survey conducted by Parrenas, it has been found out that not all children belonging to a transnational family develop the feeling of resentment more than indebtedness toward their mothers. Most of them, if not all of them, places more importance on the â€Å"outcome† of the sacrifice rather than the care that they are supposed to receive from their mothers. Seen this way, it can somehow be inferred that migration of women workers does not necessarily equate to emotional burden among children in transnational families; although, it does not also mean that they do not feel any negative feelings at all. Personally, there is an element of inevitability to feeling negatively towards the

International comparisons of stock market volatility Essay

International comparisons of stock market volatility - Essay Example Even researchers and practitioners have made modeling of stock volatility a subject of empirical and theoretical study. Historically, stock market volatility is approximately 20% per annum and 5.8% per month even though periods of high and low volatilities are experienced. During the financial crisis, there was a 50 percent drop in stock prices. The effects of the crisis are still being felt due to increased public and private debt, levels of unemployment and global capitalism. The governments are doing their best to prevent and contain the situation buy formulating new policies and reforming major sectors. Volatility measures the degree of variability between stock prices. In other words, it determines the degree of deviation between the current price of an asset and the average past price. To understand volatility, it is important to take a look at the nature and trends of global markets and the correlation of the stock market returns. For many investors, volatility is a risk, thus , it is to be taken into consideration in analyzing their portfolios. Some of the factors that lead to volatility include changes in technology, new financial instruments such as derivatives and the increased integration of global markets. Volatility is measurable, and the commonly used measure is Chicago Board Options Exchange Index (CBOE) of implied (VIX) volatility. In this paper, we will use a sample of 19 emerging markets economies (EMEs) and developed market in Europe, Latin America, Middle East and Asia as a basis of comparison on the stock market’s volatility. Most of the previous research papers focused on regional and local stock markets but due to the national integration that is linking markets globally, we use will compare countries from different continents (Beirne et al 2008). Nature of stock markets in emerging and developed markets Global markets consist of emerging and developed stock markets. A few studies have been done to examine the characteristics of em erging markets. According to these studies, emerging markets are characterized by higher average returns, low correlations with developed markets, higher volatility and more predictability of returns (Chukwuogor 2008). Their main argument was that volatility in emerging markets is high and difficult especially in the segmented markets. Segmented markets are influenced by local factors. Their returns tend to be skewed and highly non-normally distributed. Volatility in emerging markets has been declining following capital market capitalization. The correlation in emerging markets is quite higher than in the developed markets due to lack of diversification and trading depths (Chukwuogor 2008). The volatility in these markets is highly influenced by social, political, economic factors. Data and methodology The studies also focused only on the emerging markets and not developed markets. We will use daily returns and volatilities of such returns for the 19 countries using data from 2001 t o 2009. We use the GARCH model to determine the means and variances of stock returns in these countries. The Standard and Poor (S & P) index is used to rank the countries. Below is a table showing the emerging and developed markets. TABLE 1 Country Index USA S&P 500 UK FTSE 100 France CAC 40 Germany DAX 30 Xetra Australia All Ordinaries China/Hong kong Hang Seng Singapore Strait Times Malaysia Kuala Lumpur Composite Thailand stock exchange of Thailand China Shanghai

Social Media in Business and Society

Social Media in Business and Society Most organizations tend to look upon social media as a threat, where some even opt to ban the usage from the workplace altogether. The idea behind it being that employees would be given the opportunity to waste time online, chat, and possibly pose as a security threat to the organization. (Turban, 2011) (Smith, 2010) outlines risk of employees social media use at work, these can be both intentional or not and they could lead to legal and reputational risks for organisations. These have been categorised as three main problems: Use of social media cannot be fully regulated, monitored or controlled thus organisations are giving up control. Social media is a worldwide means of communication, once a negative post is online its only a matter of time till it goes viral thus reaching competitors, regulators and customers. Social media is emotional and employees can express their feelings of happiness and/or frustration. Furthermore, (Flynn, 2012) identifies the risks of having employees participating in social media by causing reputational damage, trigger lawsuits, cause humiliation, crush credibility, destroy careers, create electronic business records, and lead to productivity losses. (Dreher, 2014) argues that social media is not to be feared, but rather embraced and seen as an opportunity where employees can act as corporate advocates and brand ambassadors. If anything, it helps employees keep up to date with latest news related to the industry together with continuous knowledge development. Nonetheless, even though there are many studies that point out the benefits of social media, there is still no clear-cut decision whether it can influence work performance or whether it can fuel the social capital of the employees and help in knowledge transfer (Zhang, 2016). However, it cannot be denied that every organisation allowing social media at work will always have its fair deal of challenges to overcome. (Eliane Bucher, 2013) speaks about the health issues that can be encountered. Starting off with stating that there is so much information available on social media that professionals may face information overload. Not to mention the mix of work life with private life overlapping with social media. New technologies should improve workers efficiency and reduce stress levels however often the opposite occurs (Eliane Bucher, 2013). Technostress as referred to by (Brod, 1984). To be successful in the social media environment one needs to overcome the below 3 points otherwise technostress is formed: Techno-overload Increase in workload which could be actual or perceived. Techno-invasion Social media enables people to be constantly connected from almost every device. This can lead to the feeling of the need to be connected or online causing reduction in family time allowing work issues to invade the private life (Eliane Bucher, 2013). Techno-uncertainty Social media is constantly changing and therefore brings with it uncertainty as regards to what technologies and skills are needed to perform the job and what will they be in the future. Social media comes with many legal issues tied to it. These range from pre-employment to post employment. Wrong usage of social media will for sure lead to waste of time, inefficiency, reputation issues and negative image for the organisation. Some of the laws are outlined below by (Lieber, 2011): Employment Laws by tagging co-workers in certain provocative photos or videos, Defamation and Libel Laws by stating certain comments on co-workers or employers thus effecting their reputation., As stated in (Trott, 2009) a Microsoft Survey found that 41% of employers based their decision of not hiring an applicant based on what they found online in relation to their reputation. This is also known as Netrep. This constitutes a legal risk of discrimination in itself if the recruiter is basing decision on the netrep. Fair Credit Reporting Act by having interviewers friending an applicant on Facebook to acquire more information than is required for the job applied. Health Insurance Portability and Accountability Act by having a medical professional LinkIn with a patient. Uniform Trade Secrets Act by having employees discussing or commenting on social media about company internal only discussions or non-public projects. Employers can monitor the use of social media at work if the employees are informed in advance. Disciplinary actions can be taken once any abuse is being noticed. Policies should include what is allowed and what is considered as abuse (Trott, 2009). If the employees post on their personal accounts outside of office hours and such posts are in relation to work having a negative impact in some way to the employer or the organisation then there is still grounds for disciplinary action even though employees try to advocate for respect for private and family life, home and correspondence (article 8) or freedom of expression (article 10) from the Human Rights Act 1998. As discussed above, social media has its advantages and disadvantages and seeing that social media is here to stay organisations have little choices but to accept the new reality, address it and learn how to make good use of it. (Lieber, 2011), among others, identifies the following criteria that any organisation willing to harness social media must address: The creation and enforcement of solid social media policies within the organisations personnel addressing fair use, access during work time and general behaviour on social media (even during personal time). Directly using social media for the benefit of the organisation such as for recruitment, marketing and investigating competing organizations. Monitoring of key social networks to data mine information regarding your organisation (and potentially others as well), possibly using automated algorithms and software for maximum efficiency and accuracy. From the above-mentioned criteria, the first two deal with human resource aspect of social media where organizations lay out guidelines to their employees on how to use them, and they as the organizations can use social media directly for recruitment, marketing etc. However, as the third criteria suggests, to make most use of social networks organizations must make sure that any information/data being released on such platforms, is gathered and used effectively. It is important that an organization is always aware of what the average user is saying about their brand, effectively getting the general feel or mood while analysing the trends across time. The same principle could be applied to monitor competitors; possibly for example identifying any weak products which the competitors have and having your own similar product take advantage of the situation. Effective monitoring comes from generating good data. Data mining involves the following steps to make data meaningful for monitoring: (Raghav Bali, 2016) Removing unwanted data and noise Transformation of the raw data into data that can be used for further processing Study the data and come up with patterns that can give further insight to our data Represent the data in a way that is useful to companies or to who the data intended for. There are different data mining techniques which can be used to monitor social media use. Social media is a form of real time communication therefore an effective monitoring tool needs to monitor and provide alerts as things happen. Most text mining tools make use of search engines to go through social media sites and collect information related to the keywords or interests. (Mark My Words article) Text Analytics (Text/Data Mining)   Ã‚   Text analytics involves a complex and elaborate number of steps to strip down conversations into separate words and analyse the way these words are being used, positive or negative and even derive patterns from collected data. When we search for a movie and receive some other movie recommendations that technique is using text mining. Text Mining is made up of Data Mining (Information retrieval, Natural Language Processing Machine learning) + Text Data (Emails, Tweets, News Articles, Websites, Blogs etc.) Figure 1: Text Mining (Charu C. Aggarwal, 2012) As indicated in Figure 1, Stop Word Removal and Stemming eliminate the generic and less meaningful words form a phrase, this helps categorizing different words with same meaning as see, seen and being seen. Bag of Words (BOW) is having words separated from the sentence and each word having a numerical value which represents its importance. Limitations (Charu C. Aggarwal, 2012) outlines several limitations that can be observed and future in-depth research is required: The real-time posts on social media are a very important resource as mining data in real time as it is being posted can yield many advantages. This however remains a challenge for when these posts are not conducted from work computers or from outside work. Social media is very unstructured and some applications like twitter even limit the amount of characters per post. This brings about problems of text recognition when short length words are used like gnite gr8 etc. Social media allows different ways to express opinions or emotions these could be through images, videos and tags making the text analytics much more complex and difficult in its pre-processing stage. Method 1: Keyword Search (Rappaport, 2010) Organisations can decide which keywords they want to monitor, these may be chosen based on what is important for that company, it could be their products or emotional states. Social media is a very unstructured place containing noise and unwanted data for our data mining process. This form of search is good to capture keywords and try and form a meaning of these words and the frequency used however its very hard to come up with what is the users intent. For that reason, we then consider a more complex search method called Sentiment Analysis. Method 2: Sentiment Analysis and Emotion Analysis Sentiment Analysis is the process of identifying sentiment in text and analyse it. There are three types of sentiment analysis (Walaa Medhat, 2014): Document Level Analyse the entire document as one topic and form an opinion or sentiment on the entire document Sentence Level Analyse sentiment in each sentence Aspect Level Analyse sentiment in respect to entities as you can have more than one aspect in a sentence for the same entity. For this study, we are focusing our research on Sentence Level analysis using Semantic search. Semantic Search: Semantic search goes beyond the traditional keyword search by providing a meaning to a phrase and makes use of a wide range of resources to interpret the phrase and thus providing a more accurate result. Some examples of semantic search in our daily lives: Conversational searches:   Figure 2: Conversational Search (Google, 2017) Auto Correct spelling mistakes: Figure 3: Auto Correct (Google, 2017) Display information in graphics format: Figure 4: Information in graphics format (Google, 2017) (Charu C. Aggarwal, 2012) outlines some challenges that are encountered when going through mining. These are the difficulty in recognising opinions, subjective phrases and emotions. Opinion mining challenges. When using semantic search method on a post one needs to understand that the post can contain all the following: Positive opinions I like the computer I bought, it has a very clear screen Negative opinions however my wife thinks its too expensive Different targets The targets in the positive opinions relate to the computer and the screen whereas the targets in the negative opinions are the price Different opinion holders The positive opinions are mine however the negative opinions are of my wife Subjectivity mining challenges Posts are also made up of objective and subjective comments. Subjective expressions like opinions, desire, assumptions amongst others may not contain opinions or may not express any positive or negative comments. Emotions mining challenges Emotions (love, joy, anger, fear, sadness, happiness and more) fall under a form of subjective expression. Sometimes emotions give no opinions in a phrase. To observe the usefulness and ideal approach towards the analysis of social media related posts and messaging, a software algorithm was designed and partially developed to illustrate this scenario. The idea behind this software is to have the user write inside a textbox, mimicking an actual employee typing using a company machine, while the system monitors such text and acts per what it registers. Therefore, this tool will be presented as a standalone software/algorithm concept, emulating an actual activity of a possible employee, and as such must be adapted accordingly to make use of it in a real-life situation. The basic principle of the solution proposed is made up of three modules: The key logger that monitors the users input at runtime and effects certain rules The keyword and semantic analysis on the data gathered The storage of produced analysis and log The following flowchart outlines the lifecycle of said solution, followed by a detailed analysis of each component mentioned above, as well as possible ways on how it can be further enhanced to produce even more accurate results. The flow of the proposed solution. Created using draw.io (https://www.draw.io/) Collecting and Processing Data In this solution, key logging is used to monitor the data inputted by the user, which is a constant monitoring of the keystrokes registered by ones activity, and registered as a stream of text ready to be dissected and analysed as required. The main advantage of using such a strategy is that data is collected and used in real-time, making it ideal for scenarios where an alarm (for example a negative post related to work) needs to be raised as quickly as possible to the relevant personnel, providing a detailed log of what the employee has typed (through the key logger) eliminating the need to monitor and access the relevant social media to check what has been posted. Note: there are other strategies one can pursuit to monitor the users activity, such as firewall policies or general network surveillance, however in real-life situations such solutions can prove rather difficult to setup due to the expertise required; while web encryption and proxy services makes it even harder to effectively monitor the traffic generated by the users. A key logger, even if effective, generates a lot of unneeded garbage beyond the scope of social media. For example, an employee working on his station would be constantly registering keystrokes which the logger is then adding them up to its own text stream. This could prove to be very problematic for three main reasons: The logger would begin to amass a significant amount of storage space, unless the key logger is given a limit of how much information it can hold and removing old data to make up space for the new data, but than some information can get permanently lost. The analysis of the text stream generated can be quite intensive, which can significantly affect the performance of the machine doing the analysis, especially when considering that the analysis is assumed to be processed on the users machine which most probably isnt very well suited for such intensive work. Furthermore, following the previous point, the garbage log is being analysed too needlessly. The chances are that an employee would spend very little time on social media, thus logging and analysing the work-related activity is quite pointless for such a scope. To overcome the above-mentioned issues, the proposed solution makes use of predefined social media trigger keywords i.e. a list of social media websites such as Facebook, Twitter, LinkedIn etc., where depending on such triggers being hit or not, the key logger will have two states, passive monitoring and active monitoring. When the tool is running normally, the key logger is in a passive state keeping only the last 30 characters in its memory, without processing the stream. The only thing it does however, is to constantly check the stream read from the textbox in the tool against the trigger keywords, and if any of the keywords is found to have been registered then the key logger would go into active state. While in this state the key logger would increase its maximum capacity, and begin to log every keystroke while constantly analysing the feed. The key logger will go back to passive state when the predefined character limit is reached or enough time has passed. Following this logic, only a set of keystrokes would be registered, reducing the chance of collecting and processing unneeded information while maintaining the workload and storage use of the machine to a minimum. Note: in this approach once the key logger goes into active state, it is monitoring and analysing the feed at runtime locally, and this could prove to be quite intensive depending on the parameters set and the overall performance of the users machines. Organizations implementing this solution can opt to have the log analysed after the key loggers goes back into passive state and therefore analysing the data only once. Better yet, since the solution assumes that the key logger is analysing the data locally, instead the logs can be sent to a common server and be analysed as a scheduled task. Once this data is captured through the key logger the feed can be processed by means of the methods discussed earlier (Method 1 and 2). Based on the outcome we store the data in our information system and align the data based on the organisations social policy. Approaching data analysis using keyword and semantic methods The designed software makes use of two different types of analysis algorithms, keyword based and semantic based, and are used together to try and cancel each others limitations and thus providing much more accurate results. Keyword based analysis The more traditional keyword analysis algorithm consists of having a list of keywords i.e. a predefined set of texts, and hit the data to be analysed against that list to determine whether any keywords have been hit and at what frequency. For example, having a text (representing the data) analysed against a list of negative texts (the keywords) would provide a set of statistical information which could be used to evaluate how negative the text is, which is conceptually what a social media monitoring tool should be trying to achieve. However, the major flaw of this analysis algorithm within the context of social media monitoring, is that keyword based analysis is far too broad and prone to false alarms if not controlled. Having the data gathered from the key logger (therefore filtered to social media activity) analysed against a set of negative texts, the statistical information produced may not be relevant to the organizations interest. An employee could simply be posting a feed about how bad the weather is and how much s/he hates it, which the keyword analysis algorithm would recognize as negative and report accordingly. In the proposed solution, the keyword based algorithm uses two different sets of keywords against the gathered data, with the aim to filter the batches of logged texts by relevance. The first set consists of a list of works related text, such as work, job, company, [company name] etc. i.e. every keyword that could somehow link the user to the organization implementing the solution. In the second set, a list of keywords/texts associated with negativity are stored, such as bored, unhappy, hate, dull, sick and tired etc. When the data passed along through the key logger reaches the keyword analysis module, it would first check the log against the first set and therefore determine whether the data fed is of any relevance to work, and if not simply do nothing. On the other hand, if any of the keywords from the first set is hit, it means that the data inputted is relevant and therefore must be analysed further. In this case, the tool would analyse the entire log within the key logger (which is currently in an active state as described in the previous section) and extract the statistical information with regards to the second set. The flow of the full keyword based algorithm adapted in the tool Created using draw.io (https://www.draw.io/) Examples Keywords to assume: First Set (work): WORK, JOB Second Set (negative): BORED, UNHAPPY, SAD, HATE, DULL, TIRED, SICK AND TIRED, ANNOYED, FED UP Example 1: Input Hate this weather, its severely effecting my mood. Constantly feeling tired and sad. Output None Example 2: Input At work and bored. Wish I could find a better job, this one is just so annoying. Output BORED x 1 [full log] Example 3: Input Never a dull moment at work. At the end of the day, the management brought in pizzas, fresh doughnuts and beer. In a couple of hours, the food was gone leaving everyone too tired to move. Got to love this company, always making sure their employees are never bored and unhappy. Output DULL x 1 TIRED x 1 BORED x 1 UNHAPPY x 1 [full log] From the examples above one can note a few limitations concerning the keyword based analysis algorithm. In example 2 the logged text is alarming, which most probably would require the full attention of the responsible personnel, but due to the limited keywords, only a single piece of text was hit which would make the output seem not so alarming. Furthermore, the logged text had the word annoying which in the negative keyword set is listed as annoyed, but still this was not captured. Therefore, this means that this algorithm is highly dependent on the keywords lists and possible deviations of each text. In example 3 the output looks very alarming since the negative keywords list was hit 4 times, but the input is very positive. The algorithm was unable to take into consideration the context of how the negative words were used and simply counted the number of times they were encountered within the log, hence raising a false alarm. To overcome such limitations, other algorithms must be used in conjunction with the keyword based, where in this solution the semantic based approach is used to compliment the algorithm and try to provide more accurate results. Semantic based analysis As explained in previous sections, semantic analysis introduces a certain degree of understanding when analysing a given text, and this is achieved by giving meaning to what it is fed. In this proposed software algorithm, this type of analysis is used to evaluate the sentiment and emotion behind the fed input, and therefore can determine whether the users work related activity on social media is negative or positive, which by extension may be able to overcome the limitations of keyword based approach. Basic forms of semantic based algorithms used to analyse text in relation to sentiment and emotion, often providing a single value output denoted by a percentage, where 0% means that the text is absolutely negative and a 100% would indicate that without a doubt it is positive. However, semantic analysis is capable to go beyond a simple value, where some of which can produce a fully detailed report indicating the level of emotions for multiple types, such as anger, fearfulness and joy. The following is an example of such a report produced by the tool Tone Analyser offered by (Cloud, 2017). Example report of a semantic based algorithm offered by IBM Watson Developer Cloud Applying such an algorithm which produces a very detailed report, may be well beyond the scope of monitoring work related activity on social media. In the end, what the proposed solution is trying to achieve is to detect negative activity which would harm said organizations, that when detected, the log of that activity is passed along to the corresponding personnel with perhaps a brief report of the analysis. Another drawback to be considered in this scenario, is that light weight semantic algorithms are much less intensive than algorithms which consider different types of emotions when analysing a text, and given that in the solution such an analysis will be triggered almost constantly, having a heavy algorithm being triggered would result in a very negative experience to said users. This is why in the proposed solution a lighter semantic analysis is considered, that is the API provided by (ParallelDots, 2017). Note: one could argue that using a semantic analysis algorithm which produces a detailed report, could replace the entire algorithm which is using both the keyword based analysis and the light weight semantic based analysis. However, performance wise the latter would operate much smoother, and from a technical point of view considerably easier to setup. Note: in the proposed solution, the semantic analysis will be conditional to whether the keyword based algorithm is triggered or not, and therefore subject to the filter which is detecting whether the activity on social media is related to work or not. Examples using the sentiment analysis demo provided by (ParallelDots, 2017), which outputs single value percentages 0% being negative, while 100% being positive. Example 1: Input Hate this weather, its severely effecting my mood. Constantly feeling tired and sad. Output 0% Example 2: Input At work and bored. Wish I could find a better job, this one is just so annoying. Output 6% Example 3: Input Never a dull moment at work. At the end of the day, the management brought in pizzas, fresh doughnuts and beer. In a couple of hours, the food was gone leaving everyone too tired to move. Got to love this company, always making sure their employees are never bored and unhappy. Output 79% Classifying severity based on score and frequency of words Thus far, the algorithm detected negative activity on social media relating to work, using both keywords and semantic analysis. However, the term negative can be rather broad and it may be the case that the organization would not want to be alerted for every minor negative activity, since that will become counterproductive. As such the proposed algorithm has a threshold mechanism which determines whether to send in alerts or not. The threshold settings are two. The minimum number of negative words the activity must contain, and the minimum percentage of negativity to be considered. Right after the key logger is finished monitoring the social media activity, if work related activity is logged, the system evaluates the log based on the threshold set by the administrators of the system, and proceed accordingly. Using same parameters of previous example for keyword and semantic based approaches. The thresholds are set as follows: Minimum Keywords 1, Minimum Semantic Percentage 30%. Example 1: Input Hate this weather, its severely effecting my mood. Constantly feeling tired and sad. Output None (not work related) Alert No Example 2: Input At work and bored. Wish I could find a better job, this one is just so annoying. Output Keywords hit: 1 Semantic: 6% Alert Yes Example 3: Input Never a dull moment at work. At the end of the day, the management brought in pizzas, fresh doughnuts and beer. In a couple of hours, the food was gone leaving everyone too tired to move. Got to love this comp