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Abstract: The tea tree (Melaleuca alternifolia), a member of the Myrtaceae family, is a valuable medicinal and aromatic plant. Tea Tree essential oil (TTO) has many medical applications, including antibacterial, antifungal, antiviral, antiprotozoal, anti-inflammatory, antioxidant, and anticancer properties. Although the concentration of TTO in a microemulsion is of economic interest, very few studies on this product have been conducted. In this study, we look at how different tea tree oil concentrations in microemulsion formulations affect susceptibility to various bacteria and fungi. TTO susceptibility in a diverse range of microbial species has now been studied using data from a previously published literature review survey. Most bacteria are resistant to TTO at concentrations as low as 1.0 percent, but mucosal skin staphylococci and micrococci, Enterococcus faecalis, and Pseudomonas aeruginosa have minimum inhibitory concentrations much higher than 2 percent. TTO susceptibility in fungi has only recently been scrutinized. Fungicidal dosages range from 0.12 to 2 percent, with minimum inhibitory concentrations ranging from 0.03 to 0.5 percent and the only notable exception is Aspergillus niger, which contains fungicidal concentrations of up to 8%. The review emphasizes the importance of new antibacterial and antifungal formulations, as well as the role of natural essential oils in the discovery of new antibacterial and antifungal agents, and discusses, in brief, all constituents derived from the essential oil (tea tree) that are in preclinical and clinical development. This paper summarizes human and food-borne bacteria and fungi susceptibility to tea tree essential oils and their constituents. Among the many tested, essential oils of spices and herbs (Melaleuca alternifolia) were found to have the strongest antimicrobial properties. This review looks at a wide range of scientific literature, including Sci-hub, Google Scholar, Pub, Chem, NCBI, and web books.

This research aims to prepare microemulsion from Tea Tree and Rosemary essential oil to treat gram-positive and gram-negative bacterial infections. A phase titration has been used to make the proposed microemulsion, which contained 71% water, 23% of a 1:1 mixture of propylene glycol (surfactant), tween 80 (co-surfactant), and 6% of tea tree/rosemary essential oil. In Rosemary essential oil pale yellowish transparent microemulsion, droplet size, zeta potential, and polydispersity index (PDI) of 58.9, 883.6, and 0.678, respectively, showed a stable microemulsion. Tea tree oil loaded in a light, clear microemulsion with zeta potential, droplet size, and polydispersity index (PDI) values of 265.9, 746.8, and 0.987, respectively, indicated a stable microemulsion. The RMO/TTO micro emulsion's viscosity was 1.844/1.933 cps, and its pH ranged from 4.69 to 5.59. The formulation was determined to be a safe, reliable, and effective one in light and good in stability experiments. Escherichia coli, Staphylococcus aureus, and Candida albicans can all be treated using a microemulsion that contains 6% tea tree oil and rosemary oil by agar well diffusion method. Both the EOs-based microemulsion showed more zone of inhibition against Escherichia coli and Candida albicans while Staphylococcus aureus is the less susceptible zone of inhibition. The microemulsion formulation's minimum inhibitory concentration was effective against Staphylococcus aureus, Candida albicans, and E. coli on all physiological parameters. It can be concluded that TTO/RMO essential oil-loaded microemulsion is considered a promising substitute for the current gram-positive and gram-negative regimens.

The present investigation aimed to determine the oxidative potential, sun protection factor value, and half-maximal inhibitory concentration of rosemary essential oil and tea tree essential oil. These two essential oils have gained popularity as active ingredients in many cosmetic preparations due to their antioxidant activity, whether used individually or in combination. Gas chromatography-mass spectroscopy is used to identify the presence of different phytochemical constituents in essential oils. The GC-MS (Gas chromatography-mass spectroscopy) chemical analysis of tea tree oil revealed 34 and rosemary oil revealed 35 volatile chemical components with sesquiterpene hydrocarbon, monoterpenes (42.77%), and alcohols (41.01%) as major detected classes. The 2, 2-diphenylpicrylhydrazyl (DPPH) and nitric oxide-free scavenging activity techniques were used to investigate the antioxidant capacity of these oils. It was found that both tea tree and rosemary oil have the potential to slow down skin aging through their anti-oxidative properties using the approach of free radical scavenging activity. The UV spectroscopy method was used to determine the sun protection factor, and the sun protection values of rosemary and tea tree oil were found to be 8.45 and 6.85, respectively. Rosemary oil was an extremely promising tea tree essential oil for anti-aging and sunburn prevention. The study's findings indicated that rosemary and tea tree essential oil can both offer a synergistic sun protection factor effect, antioxidant property, and anti-aging or extra activity of cosmetic preparations.

The genus Ipomea contains a wide variety of species that can be found growing along road side in wastelands and along canals. Ipomoea carnea is a plant that grows up to 600 centimetres tall and is straight, woody, bushy and slightly cylindrical in shape with a greenish tint. It is also known as Besharm or bush morning glory, the stem of the Ipomoea carnea plant has different leaves. This plant is utilised as a folk medicine in Ayurveda, Siddha and Unani system of medicine and literature suggest that Ipomoea carnea may have anti-oxidant, immunostimulant, anticancer, hepatoprotective and various other pharmacological activity. T2-ethyl-1,3-dimethylbenzene, 2-(12-pentadecynyloxy) tetrahydro2H-pyran, 3-furanyl[2-hydroxy-4-methyl-2-methyl-2-methylpropyl-cyclopentyl] methanone, 2,2-dideuterooctadecanal, hexadecanoic acid, Linoleic acid are chemical components of Ipomoea carnea. After conducting a thorough examination of the literature. Ipomea Carnea has been shown to be a safe, cost-effective, and potentially therapeutic herb for the treatment of a variety of ailments. Integrating its active components or extracts or fractions in suitable drug delivery system can be used to investigate its therapeutic potential. Keywords: Ipomoea carnea, Chemical Analysis, Pharmacological studies, Pharmacological studies

PurposeBased on the self-determination and affective events theories, the current research examined the mediating role of occupational self-efficacy (OSE) between individualized consideration transformational leadership (ICTL) and affective commitment relationship. Furthermore, this study tests the moderating role of personal growth initiative on the relationship between ICTL and OSE.Design/methodology/approachTo examine the relationship, the authors carried out a time-lagged study spanning over four months for analyzing the indirect effect of ICTL on affective commitment via OSE among 382 Generation Y employees working in Indian IT (information technology) organizations. Results were analyzed using Process macro.FindingsThe study results revealed that OSE significantly mediated the relationship between ICTL and affective commitment. It was also established that the positive relationship between ICTL and OSE was stronger among employees who perceived higher levels of personal growth initiative.Practical implicationsThe findings carry substantial implications for researchers and organizational practitioners. Indeed, the results indicate that human resource management practitioners are required to nurture an ICTL approach for boosting employees' affective commitment levels.Originality/valueThe study proposed a model focusing on the role of ICTL in enhancing employees' OSE and affective commitment. Also, the study contributes to existent research by demonstrating the role of personal growth initiative in understanding the relationship between ICTL and OSE. Moreover, this study provides theoretical and practical implications.

The present study aims to produce nanocomposites of silica based organosilane as sensitive and selective fluorescent sensor for the recognition of 2,4 dichlorophenoxyacetic acid (2,4-D). Hydrazone tethered triazole functionalized organosilane has been synthesized by the condensation reaction of 4-hydroxybenzaldehyde and phenyl hydrazine followed by Cu(I) catalysed cycloaddition of azide with alkyne. The prepared compound has been further grafted over silica surface and the synthesized materials were characterized by FT-IR, NMR (

Background: Automatic Machine Translation (AMT) Evaluation Metrics have become popular in the Machine Translation Community in recent times. This is because of the popularity of Machine Translation engines and Machine Translation as a field itself. Translator is a very important tool to break barriers between communities especially in countries like India, where people speak 22 different languages and their many variations. With the onset of Machine Translation engines, there is a need for a system that evaluates how well these are performing. This is where machine translation evaluation enters. Objective: This paper discusses the importance of Automatic Machine Translation Evaluation and compares various Machine Translation Evaluation metrics by performing Statistical Analysis on various metrics and human evaluations to find out which metric has the highest correlation with human scores. Methods: The correlation between the Automatic and Human Evaluation Scores and the correlation between the five Automatic evaluation scores are examined at the sentence level. Moreover, a hypothesis is set up and p-values are calculated to find out how significant these correlations are. Results: The results of the statistical analysis of the scores of various metrics and human scores are shown in the form of graphs to see the trend of the correlation between the scores of Automatic Machine Translation Evaluation metrics and human scores. Conclusion: Out of the five metrics considered for the study, METEOR shows the highest correlation with human scores as compared to the other metrics.

Naturally and synthetically derived hybrid molecules are promising sources for new drug development due to their multiple modes of action and other advantages. Chalcone, two important classes of synthetic chemistry affording diverse pharmacological activities, make themselves ideal blocks for building a chalcone hybrid scaffold as a bioactive agent. Provoked by the promising medicinal applications of such hybrids, the scientific community has reported dozens of chalcone hybrids with a wide spectrum of biological properties including anticancer, antimicrobial, antimalarial, antioxidant, antianxiety and so on, through synthetic hybridization strategy. It is expected to assist medicinal chemists in the effective and successful development of chalcone hybrids. In view of these observations, we herein report the literature review of Chalcone hybrids which possessing antimicrobial, antioxidant and antianxiety potential.

Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user’s expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user’s curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN).

PurposeThis study aims to identify specific human resource management (HRM) practices to overcome destructive deviance among public sector employees. Further, this study aims to rank the identified HRM practices in the order of their impact on destructive deviance.Design/methodology/approachThis study uses the technique of both inductive and quantitative content analyses to identify specific HRM practices and rank them in the order of their impact on destructive deviance. Data was collected from 30 executives employed in Indian public sector via unstructured interviews. Also, Krippendorff’s alpha reliability estimate was calculated to establish the reliability of the content analysis, which was 0.80.FindingsThis study identified ten HRM practices (human resource planning, job design, training and development, reward system, employment security, career advancement opportunities, performance management, employee participation, monitoring and control, work–life balance) in overcoming destructive deviance among public sector employees. Furthermore, based on their frequency distribution, the HRM practices were classified into three categories, i.e. most significant, significant and least significant.Research limitations/implicationsBased on the categorization of HRM practices into three categories, this study implies that to discourage employees from exhibiting deviant behaviour, organizations should focus on the implementation of most significant HRM practices followed by significant and least significant practices. HRM practices that function as a coherent and synergistic system act as a win-win strategy benefitting both employees and the organization.Originality/valueIn spite of the rising research interest in the deviant behaviour in the literature, still there is a dearth of research pertaining to the association between HRM practices and destructive deviance. Moreover, there is no consensus among researchers concerning the specific HRM practices that should be incorporated in the overall construct. Guided by these gaps in the literature, this study identifies ten HRM practices to overcome destructive deviance among public sector employees using qualitative analysis.

Purpose This study aims to provide a review of antecedents of destructive deviance and classify them into three levels, namely, personal, interpersonal and organizational level in the proposed integrated conceptual framework. Furthermore, it proposes three levels of interventions to prevent or modify destructive deviance. Design/methodology/approach Systematic literature review of the past 23 years was carried out for the current study to identify the antecedents of destructive deviance. Findings This study proposes an integrated conceptual framework incorporating three levels of antecedents and interventions for overcoming destructive deviance. Findings classified the antecedents of destructive deviance into three categories, namely, personal, interpersonal and organizational level variables. Similarly, the proposed interventions were classified into three levels, namely, individual (employee resilience, mindfulness), interpersonal (mentoring, peer support) and organizational-level interventions (talent management, internal corporate communication) that organizations should concentrate on to reduce destructive deviance and facilitate health and well-being of employees. Practical implications This study posits three-level interventions to reduce or transform negative characteristics and overcome the negative impact of interpersonal and organizational level antecedents on destructive deviance among employees. The suggested three-level interventions not only reduce the negative characteristics and transform negative behaviors but also lay a significant pavement for fostering positive emotions among employees. Originality/value This study classifies the antecedents of destructive deviance into three categories, namely, personal, interpersonal and organizational-level antecedents. Further, this study offers three-level interventions for overcoming destructive deviance among employees.

The problem of language translation has prevailed in society for so long. However, up to some extent the problem is being reduced by the online available machine translation systems like Google, Bing, Babelfish, etc. But with the emergence of these Machine Translation Systems, there arises the problem of their validation. Can we trust on such translation systems blindly? Is there no scope of improvement? Are these Machine Translation systems not prone to errors? The answer to all these questions is No. So, for this purpose, we need a mechanism that can test or assess these Machine Translation systems. In this paper, we have proposed an algorithm that will evaluate such Machine Translation systems. Our algorithm is being compared with a very well-known BLEU algorithm that works very well for non-Indian languages. The accuracy of the designed algorithm is evaluated using the standard datasets like Tides and EMILLE.

PurposeThe purpose of this paper is to investigate the impact of perceived abilities-motivation-opportunity (AMO framework) enhancing human resource management practices on destructive and constructive deviance through employee engagement.Design/methodology/approachData were collected from 350 middle-level information technology employees. Structural equation modeling was applied to examine the proposed hypotheses.FindingsResults revealed significant relationships between perceived AMO framework and destructive and constructive deviance, except for the relationship between perceived ability and destructive deviance. Furthermore, perceived AMO framework exhibited a significant positive relationship with employee engagement. Utilizing social exchange theory, results proposed partial mediation of employee engagement between perceived AMO framework and constructive and destructive deviance except for the relationship between perceived ability and destructive deviance, for which employee engagement exhibited full mediation.Research limitations/implicationsThis study implies that contemporary organizations must take initiatives to enhance employee engagement through the implementation of abilities, motivation and opportunities-enhancing human resource management (HRM) practices (AMO framework). Results of the study infer that motivation-enhancing HRM practices contribute highest in generating employee engagement followed by opportunity and abilities-enhancing HRM practices.Originality/valueThis study empirically investigates the impact of HRM bundles on both destructive and constructive deviance. Additionally, this study explores the underlying mechanism between HRM bundles and workplace deviance by assessing the mediating role of employee engagement.

Purpose In a world of fast-changing markets, corporate brand is the heart and soul of a company. A company’s employees are crucial in nourishing a successful corporate image. Eventually, organizations require committed employees who orient their energy and drive the company toward a shared vision. However, employees’ deviant behavior can cripple the organization’s brand image. Given this fact, the purpose of this study is to offer strategies that can play a vital role in overcoming destructive deviance and in turn fostering the pavement for building a strong corporate brand image. Design/methodology/approach Given the purpose, this study used systematic review of literature to analyze the newspaper articles that reported the cases of deviant behaviors exhibited by employees of “Air India” and were published between 2015 and 2017. Further, this study used document analysis to identify and categorize the various forms of deviant behaviors exhibited by employees of Air India. Findings The current study asserted four chief interventions, namely, talent management strategies, resilience, workplace spirituality and mindfulness to overcome destructive deviance and promote constructive behavior among employees of Air India. Research limitations/implications The present study offers vital implications for organizations to curb the escalating deviant behavior among employees in the hospitality industry. These interventions might lay a significant pavement for fostering positive emotions among employees, which in turn could play a crucial role in enhancing service quality and building a strong brand image. Originality/value Given the mounting cases of deviant behavior among employees, the present study draws attention to the necessity for a shift in the generic organizational strategies and instigates organizations to integrate the study’s strategies to curb deviant behavior and in turn build a strong corporate image.

PurposeThe purpose of this paper is to propose a conceptual framework associating globalization, workforce diversity, and deviance and suggest micro-macro HRM strategies to overcome challenges associated with the workforce diversity and workplace deviance.Design/methodology/approachA systematic review of literature of past 25 years was carried out with the key word “globalization, workforce diversity, and deviance” from several electronic databases.FindingsFindings propose micro-macro HRM strategies to be adopted by HR practitioners in Association of Southeast Asian Nations (ASEAN) organizations to manage workforce diversity and deviance in the age of globalization.Research limitations/implicationsThe challenges due to workforce diversity may get worse because ASEAN is more incongruent in terms of phases of economic, social, cultural, and political advancement. Therefore, proposed model can be tested and compared in different ASEAN organizations.Originality/valueThere is a dearth of literature associating globalization, workforce diversity, and deviance. This paper bridges this gap by proposing a conceptual framework in the ASEAN context and suggests micro-macro HRM strategies to be adopted by HRM practitioners to overcome associated challenges with workforce diversity and deviance.

PurposeThis paper aims to propose an integrated conceptual framework depicting the antecedents of workplace deviance. This framework demonstrates three broad categories of antecedents of workplace deviance incorporating individual, interpersonal and organizational antecedents. The identified antecedents were later ranked in the order of their impact on workplace deviance.Design/methodology/approachPRISMA diagram was used to conduct the systematic literature review and identify the antecedents of workplace deviance. The identified antecedents were later ranked using analytic hierarchy process (AHP). For AHP, data were collected from 20 HR managers and academicians employed in various Indian organizations and institutes.FindingsThis study identified three categories of antecedents of workplace deviance, namely, organizational, interpersonal and individual antecedents. Results of AHP indicated that organizational antecedents have the most significant role in overcoming workplace deviance (18.92 per cent), which was followed by individual (1.47 per cent) and interpersonal level antecedents (1.28 per cent).Practical implicationsThis study posits that organizations should avoid unfavorable exchange with its employees by providing suitable organizational and interpersonal practices and by conducting ethical programs and workshops to discourage deviant practices. Moreover, organizations should conduct integrity tests, personality assessment tests to avoid individuals with negative personality characteristics.Originality/valueThis study adds to the literature on workplace deviance by identifying and classifying all the proposed antecedents of literature in an integrated framework. Moreover, this study used techniques of PRISMA and AHP, which represents novelty in the literature of workplace deviance.

Using a cavity assisted two-photon Raman process, we demonstrate the deterministic generation and storage of fast photons (pulse width < atomic excited-state lifetime) in an atomic system coupled to a high-bandwidth cavity (k > 7).

Machine learning is the key solution to many AI issues, but learning models rely heavily on specific training data. While a Bayesian setup can be used to incorporate some learning patterns with previous knowledge, those patterns can not access any organized world knowledge on requirements. The primary objective is to enable human-capable machines in ordinary everyday circumstances to estimate and make presumptions. In this paper we propose to respond to such common sense issues through a textual inference system with external, organized common sense graphs for explanatory inferences. The framework is based on a schematic map as a pair of questions and answers, a linked subgraph from the semantine to the symbolic space of knowledge-based external information. It displays a schematic map with a new network graphic module for information knowledge and performance with graph representations. LSTMs and graphical networks with a hierarchical attention-based direction are the basis of our model. It is flexible and understandable from the intermediate attention scores, leading to confident results. We also achieved state-of-the-art reliability on CommonsenseQA, a broad database of common sense reasoning utilizing ConceptNet as the only external tool for BERT-based models.

Assessment of the Translation done by machines has always been a major topic of interest for the Natural Language Researchers. Every day, a new translator is out there in the market claiming to be the best one. But to challenge such claims, one needs to have a powerful assessment tool that can judge the output of any translator on different parameters like fluency of the language, adequacy as well as the accuracy of the output generated. In this paper, we have discussed the major issues with the algorithms used for the evaluation of Machine translation. We have also presented a brief description and comparative study of different metrics used to evaluate the outcome of a machine translator over English to Hindi Language parallel sentences.

Machine Translation, sometimes referred by the acronym MT, is one of the important fields of study of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. At its basic level, MT performs simple substitution of atomic words in one natural language for words in another language. Around the world, numerous systems are available in the market for the assessment of the translation being done by the various translation systems. Even within India, a large number of such evaluation systems are available and a lot of research is still going on to develop a better evaluation system which can beat the results produced by Human Evaluators. Even the main challenge before Indian Researchers is that the evaluation systems which are giving unbeatable results for the translation of Foreign languages (such as German, French, Chinese, etc.) are not even giving considerable results for the translation of Indian Languages (Hindi, Tamil, Telugu, Punjabi, etc.). So at par these evaluation systems cannot be applied as it is to evaluate Machine Translations of Indian Languages. Indian languages require a novel approach because of the relatively unrestricted order of words within a word group. In this paper, we are presenting an algorithm (by incorporating different modules of language models like synonym replacement, root word extraction and shallow parsing) which when applied upon the translation of English to Hindi text gives better evaluation results as compared to those algorithms which do not incorporate all these modules. Moreover, our study is limited to English to Hindi language pair and the testing is being with the corpora of agriculture domain.

The servers utilize a major proportion of the energy utilized in the cloud-based companies. Through this paper, we are proposing a group of methodologies and approaches via which it would be possible to attain an energy conservation of more than 80 % of the total energy consumed by the cluster. We are using an integrated mechanism in between the servers and the jobs, consisting of combination of optimization approaches: beginning from ant colony optimization in the cloud cluster to bee colony optimization in load balancing to queueing theory in solving different job arrival patterns and some intermediate optimization algorithms like PowerNap and more. We have designed this approach without degrading the quality of service of the datacenters/clusters.

Here we are proposing a framework that will help reliable and fault tolerant data center using dynamic allocation VM's in distributed environment using prior allocations in case failure of VM's. The datacenter sub-module will be working closely with VMTD, TVM and QoSC. We focus to invent a framework which could solve the problem of optimizing number of servers to run for a given load. We seek novelty on developing assignment of jobs in the Cloud environment.

The task of the Evaluation of Machine Translation (MT) is very difficult and challenging too. The difficulty comes from the fact that translation is not a science but it is more an art; most of the sentences can be translated in many acceptable forms. Consequently, there is no such fix standard against which a particular translation can be evaluated. If it has been possible to make an independent algorithm that would be able to evaluate a specific Machine Translation, then the belief is that this evaluation algorithm will be a better algorithm than the translating algorithm itself. Initially, MT evaluation used to be done by human beings which was a time-consuming task and highly subjective too. Also evaluation results may vary from one human evaluator to another for the same sentence pair. Therefore we need automatic evaluation systems, which are quick and objective. Different methods for Automatic Evaluation of Machine Translation have been projected in recent years, out of which many of them have been accepted willingly by the MT community. In the proposed work, we have checked the applicability of BLEU metric and of its modified versions for English to Hindi Machine Translation(s) particularly for Agriculture Domain. Further, we have incorporated some additional features like synonym replacement and shallow parsing modules and after that we have calculated the final score by using BLEU and M-BLEU metrics. The sentences which have been tested are taken from Agriculture Domain. The BLEU metric does not consider the synonym problem and it considers synonym as different words thereby lowering down the final calculated score while comparing the human translations with the machine translations. To overcome this drawback of BLEU, we have incorporated a synonym replacement module in our algorithm. For this, first of all the word is replaced by its synonym present in any of the reference human translations and then it is compared with the reference human translation.

Aim: The purpose of this study was to assess skeletal age and establish relationship between mandibular canine calcification and skeletal age. Materials and methods: The study included 147 females aged 10 to 13 years. The subjects were divided into three groups: Group I—comprising of 10 to 11 years old female; Group II—comprising of 11 to 12 years old female; Group III—12 to 13 years female. OPG and hand and wrist radiographs of left side for each subject were taken with prior consent of their parents. The calcification status of canine was evaluated from orthopantomograms according to scores given in Demirjian’s method. The stages of ossification of various carpal bones were evaluated using radiographic atlas of Greulich-Pyle and skeletal age was calculated. Results: Data collected was statistically analyzed. Conclusion: The results drawn from this study showed that a strong correlation was observed for canine calcification stage F for 10 to 11 years and for stage G in 11 to 12 years and 12 to 13 years respectively. How to cite this article: Malik P, Rana V, Rehani U. To Evaluate the Relationship between Mandibular Canine Calcification Stages and Skeletal Age. Int J Clin Pediatr Dent 2012;5(1): 14-19.

Increasing crime rates and global security crises have necessitated the employment of forensic techniques for tackling such situations. Crime scene investigation forms an essential part of forensic science protocol, which involves collection and examination of the physical evidences present in various forms (chemical, biological and physical) and their subsequent examination in the laboratory. Interaction of the crime scene investigating personnel with such materials is expected and may pose occupational health hazards to the individuals involved, e.g., investigation of clandestine drug laboratories, physical contact with harmful biological agents, and exposure to latent fingerprint developing chemicals and materials, etc. Occupational hazards to the personnel involved in the crime scene investigation are of primary importance when keeping in view the health of the individuals involved and the dynamic nature of the cases they come across. In the present paper, the major health considerations asso...

Osteopetrosis is a rare metabolic disease.1 Dental abnormalities may be attributed to the pathological changes in osteopetrosis. Patients with osteopetrosis are especially susceptible to osteomyelitis of mandible.1 A 13-year-old girl presented with complaint of jaw swelling on left side. The radiograph of left mandible (lateral oblique view) showed small sequestrum with irregularity and erosions of the man-dibular cortical margins. This case report aims at diagnosis and treatment of osteopetrosis with superadded mandibular osteomyelitis―a are entity.

Peripheral giant cell granuloma is a benign reactive lesion of gingiva. It manifests as a firm, soft, bright nodule or as a sessile or pedunculate mass. This article reports the management of peripheral giant cell granuloma in a 12-year-old boy by surgical excision.

In fact, Gartner projected global revenue for cloud computing to reach almost $150 billion by 2014. However, the 2011 market is already approximately $68 billion globally. With increase in web technologies and internet, a proportional increase in cloud computing technologies has been cited. Cloud computing has been emerging as a flexible and powerful computational architecture to offer ubiquitous services to users. A variety of hardware and software resources are integrated together as a resource pool, the software is no longer resided in a single hardware environment, it is utilized according to the schedule of the resource pool for optimized resource utilization. The optimization of energy consumption in the cloud computing environment is the question how to use various energy conservation strategies to efficiently allocate resources. The need of different resources in cloud environment is unpredictable. It is observed that load management in cloud is utmost needed in order to provide QoS (Quality of Service). The jobs on over-loaded physical machine are shifted to under-loaded physical machine and turning the idle machine off, in order to provide green cloud. For energy optimization, DVFS and Power-Nap are good strategies. As good amount of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still consume 60% of their peak power. In this paper, we have proposed an algorithm for energy optimization having the constraint QoS and SLA.

The Doha Round of negotiations held during November 2001, have set an Agenda, for development, Trade and Intellectual Property compliances, by discussing the TRIPS Agreement. This was followed by Ministerial discussions held in Cancun in 2003, Geneva in 2004, in Honkong in 2005 and again in Geneva in 2006 and 2008.Subsequently, Annual Conference of WTO was held on 11th and 12th September 2008 in Geneva, Switzerland. This meet failed largely due to the fact that modalities for Agricultural and Non-Agricultural Market Access (NAMA) did not succeed. This is a continuation of Doha discussions. However, Doha round of discussions provided for Special Safeguard Mechanism (SSM) by countries to protect the Tariff - for farmers. The WTO has plans to conclude the negotiation relating to Doha in 2010. This has been expressed by the Director General of WTO in his informal discussions with the member countries. It is therefore, considered that evaluating the Doha discussions and TRIPS provisions regarding thereto, will be a proper step, since it is being concluded soon. This Article thus analysis the provisions of Doha Round Discussions and TRIPS evaluations in these periods of time.

To evaluate the evidence for the use of probiotics in the prevention of acute diarrhoea, we did a meta-analysis of the available data from 34 masked, randomised, placebo-controlled trials. Only one trial was community based and carried out in a developing country. Most of the remaining 33 studies were carried out in a developed country in a health-care setting. Evaluating the evidence by types of acute diarrhoea suggests that probiotics significantly reduced antibiotic-associated diarrhoea by 52% (95% CI 35-65%), reduced the risk of travellers' diarrhoea by 8% (-6 to 21%), and that of acute diarrhoea of diverse causes by 34% (8-53%). Probiotics reduced the associated risk of acute diarrhoea among children by 57% (35-71%), and by 26% (7-49%) among adults. The protective effect did not vary significantly among the probiotic strains Saccharomyces boulardii, Lactobacillus rhamnosus GG, Lactobacillus acidophilus, Lactobacillus bulgaricus, and other strains used alone or in combinations of two or more strains. Although there is some suggestion that probiotics may be efficacious in preventing acute diarrhoea, there is a lack of data from community-based trials and from developing countries evaluating the effect on acute diarrhoea unrelated to antibiotic usage. The effect on acute diarrhoea is dependent on the age of the host and genera of strain used.

Heralded entanglement between distant quantum memories is the key resource for quantum networks. Based on quantum repeater protocols, these networks will facilitate efficient large-scale quantum communication and distributed quantum computing. However, despite vast efforts, long-distance fibre based network links have not been realized yet. Here we present results demonstrating heralded entanglement between two independent, remote single-atom quantum memories generated over fibre links with a total length up to 33 km. To overcome the attenuation losses in the long optical fibres of photons initially emitted by the Rubidium quantum memories, we employ polarization-preserving quantum frequency conversion to the low loss telecom band. The presented work represents a milestone towards the realization of efficient quantum network links., Comment: 6 pages and 4 figures + 5 pages and 4 figures