Calf massager: Intervention for body muscle discomfort during prolonged standing

Many occupations require workers to stand for long periods of time without proper interventions, which causes discomfort in the back and lower limbs. Therefore, this study aims to assess the effectiveness in alleviating body muscle discomfort during prolonged standing through the use of a calf massager. This study was conducted among male workers at a manufacturer with production line workers and the list was obtained from the HR Department and simple random sampling was done by number categorization. A total of 100 respondents (50 respondents for both the control and the experimental groups) participated in this study. The experiment took place in a room with a similar setup for the production line. Each respondent was requested to perform the simulated task for 2 hr. For the experimental group, the calf massager was turned on every 15 min. At every 15‐min interval after turning on the calf massager, respondents from both groups were required to evaluate their discomfort level on a Borg's scale CR‐10 questionnaire. The results showed that the level of body discomfort among respondents in the experimental group reduced (20–30%) compared with that of the control group. Multivariate analysis results revealed that the discomfort rating for the lower back, knees, thighs, calves, and feet was significantly lower (p < .05) among the experimental group compared with the control group. For lower body parts, the lower back region was statistically significant (p < .05) at the 90th, 105th, and 120th min; the thigh region was statistically significant (p < .05) at the 120th min; the knee region was statistically significant (p < .05) at the 105th and 120th min; the calf region was statistically significant (p < .05) at all minute intervals except the 15th and 45th min, while the feet region, was statistically significant at the 105th and 120th min. Therefore, this study indicates that calf massage treatment is capable of reducing body muscle discomfort during prolonged standing and highlights the significance of calf massage.     

In vivo clonal expression of T lymphocytes specific for an immunodominant N-terminal myelin basic protein epitope in healthy individuals

The role of myelin basic protein (MBP) T cell recognition in the induction of experimental allergic encephalomyelitis (EAE) has been well established in mice and rats. A remarkable restriction has been observed in T cell receptor (TCR) genes utilized by encephalitogenic T cell lines (TCLs) specific for immunodominant epitopes in these species. Pathological similarities between this animal model and multiple sclerosis (MS) has led to consider MBP as a major candidate autoantigen in this human disorder. Unlike in inbred strains of animals, the T cell response to MBP in humans is quite heterogenous with regard to fine epitope specificity. The existence of V alpha and/or V beta restriction in MBP-specific T cells, from MS patients and healthy controls, is still a matter of debate. In this study we generated 77 MBP-specific TCLs from nine healthy donors and showed that peptide 7-27 is one of the most frequently recognized epitopes. 37% of all epitope-specific TCLs recognized this peptide and p7-27 specific TCLs were generated from seven out of the nine subjects studied. A high level of in vivo clonal expansion was observed in p7-27-specific TCLs in several subjects, which however is not specific of this epitope since this phenomenon was also observed in p85-104- and 149-162-specific TCLs.     

Detection of dental abnormalities using SVM and PSVM

Landmarks needed for detecting dental abnormalities in cephalometric analysis were selected from the digital image, and the angle values needed for dental analysis were calculated and stored in a database which is used for developing training dataset. Principal component analysis was applied for dimension reduction to get the desired feature vectors which are trained and tested using support vector machine and proximal support vector machine classifier to detect the dental abnormalities, the performance of the classifiers were also compared.     

Simple substitution distance and metamorphic detection

To evade signature-based detection, metamorphic viruses transform their code before each new infection. Software similarity measures are a potentially useful means of detecting such malware. We can compare a given file to a known sample of metamorphic malware and compute their similarity—if they are sufficiently similar, we classify the file as malware of the same family. In this paper, we analyze an opcode-based software similarity measure inspired by simple substitution cipher cryptanalysis. We show that the technique provides a useful means of classifying metamorphic malware.     

Probabilistic Health-lnformatics and Bioterrorism

In this article, new probabilistic health-informatics indices connecting probabilities： Pr（A）,Pr（B）,Pr（A IB） and P r（A ]B-） are discovered, where .4 and B denote respectively the ＂ability of a hospital to treat anthrax patients＂ and ＂whether a hospital drilled to be prepared to deal with an adverse bioterrorism＂. These probabilistic informatics are not seen in any textbooks or journal articles and yet, they are too valuable to be unnoticed to comprehend the hospitals＇ preparedness to treat anthrax patients in an outbreak of bioterrorism. A demonstration of this new probabilistic informatics is made in this article with the data in the U.S. Government＇s General Accounting Office＇s report GA0-03-924. Via this example, this article advocates the importance of the above mentioned probabilistic-informatics for health professionals to understand and act swiftly to deal with public health emergencies.     

An Efficient Lossless Telemetry Data Compression and Fault Analysis System Using 2SMLZ and CMOW-DLNN

Wireless Personal Communications - In this paper, the effect of perfect electric conductor (PEC) as a ground plane on antenna array is investigated. Vertical electric dipole which is of...     

Stress Reduction of 3D Printed Compliance‐Tailored Multilayers

Multilayered multi‐material interfaces are encountered in an array of fields. Here, enhanced mechanical performance of such multi‐material interfaces is demonstrated, focusing on strength and stiffness, by employing bondlayers with spatially‐tuned elastic properties realized via 3D printing. Compliance of the bondlayer is varied along the bondlength with increased compliance at the ends to relieve stress concentrations. Experimental testing to failure of a tri‐layered assembly in a single‐lap joint configuration, including optical strain mapping, reveals that the stress and strain redistribution of the compliance‐tailored bondlayer increases strength by 100% and toughness by 60%, compared to a constant modulus bondlayer, while maintaining the stiffness of the joint with the homogeneous stiff bondlayer. Analyses show that the stress concentrations for both peel and shear stress in the bondlayer have a global minimum when the compliant bond at the lap end comprises ≈10% of the bondlength, and further that increased multilayer performance also holds for long (relative to critical shear transfer length) bondlengths. Damage and failure resistance of multi‐material interfaces can be improved substantially via the compliance‐tailoring demonstrated here, with immediate relevance in additive manufacturing joining applications, and shows promise for generalized joining applications including adhesive bonding.     

Evaluation of potential anti‐cancer activity of cationic liposomal nanoformulated Lycopodium clavatum in colon cancer cells

Research dealing with early diagnosis and efficient treatment in colon cancer to improve patient''s survival is still under investigation. Chemotherapeutic agent result in high systemic toxicity due to their non‐specific actions on DNA repair and/or cell replication. Traditional medicine such as Lycopodium clavatum (LC) has been claimed to have therapeutic potentials against cancer. The present study focuses on targeted drug delivery of cationic liposomal nanoformulated LC (CL‐LC) in colon cancer cells (HCT15) and comparing the efficacy with an anti‐colon cancer drug, 7‐ethyl‐10‐hydroxy‐camptothecin (SN38) along with its nanoformulated form (CL‐SN38). The colloidal suspension of LC was made using thin film hydration method. The drugs were characterised using ultraviolet, dynamic light scattering, scanning electron microscopy, energy, dispersive X‐ray spectroscopy. In vitro drug release showed kinetics of 49 and 89% of SN38 and LC, whereas CL‐SN38 and CL‐LC showed 73 and 74% of sustained drug release, respectively. Studies on morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis of Bcl‐2, Bax, p53 by real‐time polymerase chain reaction and western blot analysis of Bad and p53 protein were performed. Nanoformulated LC significantly inhibited growth and increased the apoptosis of colon cancer cells indicating its potential anti‐cancer activity against colon cancer cells.Inspec keywords: cancer, biological organs, cellular biophysics, drug delivery systems, drugs, nanomedicine, genetics, DNA, molecular biophysics, biochemistry, lipid bilayers, toxicology, suspensions, colloids, light scattering, X‐ray chemical analysis, solvation, enzymes, nanostructured materialsOther keywords: energy dispersive X‐ray spectroscopy, in vitro drug release, morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis, Bcl‐2, Bax, real‐time polymerase chain reaction, western blot analysis, Bad protein, p53 protein, scanning electron microscopy, dynamic light scattering, ultraviolet scattering, thin film hydration method, colloidal suspension, nanoformulated form CL‐SN38, 7‐ethyl‐10‐hydroxy‐camptothecin, anticolon cancer drug, colon cancer cells HCT15, cationic liposomal nanoformulated LC, targeted drug delivery, therapeutic potentials, Lycopodium clavatum, traditional medicines, cell replication, DNA repair, nonspecific actions, high systemic toxicity, chemotherapeutic agents, patient survival, colon cancer treatment, colon cancer diagnosis, CL‐LC, potential anticancer activity     

Automatic classification of Tamil documents using vector space model and artificial neural network

Automatic text classification based on vector space model (VSM), artificial neural networks (ANN), K-nearest neighbor (KNN), Naives Bayes (NB) and support vector machine (SVM) have been applied on English language documents, and gained popularity among text mining and information retrieval (IR) researchers. This paper proposes the application of VSM and ANN for the classification of Tamil language documents. Tamil is morphologically rich Dravidian classical language. The development of internet led to an exponential increase in the amount of electronic documents not only in English but also other regional languages. The automatic classification of Tamil documents has not been explored in detail so far. In this paper, corpus is used to construct and test the VSM and ANN models. Methods of document representation, assigning weights that reflect the importance of each term are discussed. In a traditional word-matching based categorization system, the most popular document representation is VSM. This method needs a high dimensional space to represent the documents. The ANN classifier requires smaller number of features. The experimental results show that ANN model achieves 93.33% which is better than the performance of VSM which yields 90.33% on Tamil document classification.