Unveiling Human Values: Analyzing Emotions behind Arguments.

Detecting the underlying human values within arguments is essential across various domains, ranging from social sciences to recent computational approaches. Identifying these values remains a significant challenge due to their vast numbers and implicit usage in discourse. This study explores the potential of emotion analysis as a key feature in improving the detection of human values and information extraction from this field. It aims to gain insights into human behavior by applying intensive analyses of different levels of human values. Additionally, we conduct experiments that integrate extracted emotion features to improve human value detection tasks. This approach holds the potential to provide fresh insights into the complex interactions between emotions and values within discussions, offering a deeper understanding of human behavior and decision making. Uncovering these emotions is crucial for comprehending the characteristics that underlie various values through data-driven analyses. Our experiment results show improvement in the performance of human value detection tasks in many categories.

Evaluation puramatrix as a 3D microenvironment for neural differentiation of human breastmilk stem cells.

The extracellular matrix is recognized as an efficient and determining component in the growth, proliferation, and differentiation of cells due to its ability to perceive and respond to environmental signals. Applying three-dimensional scaffolds can create conditions similar to the extracellular matrix and provide an opportunity to investigate cell fate. In this study, we employed the PuraMatrix hydrogel scaffold as an advanced cell culture platform for the neural differentiation of stem cells derived from human breastmilk to design an opportune model for tissue engineering. Isolated stem cells from breastmilk were cultured and differentiated into neural-like cells on PuraMatrix peptide hydrogel and in the two-dimensional system. The compatibility of breastmilk-derived stem cells with PuraMatrix and cell viability was evaluated by scanning electron microscopy and MTT assay, respectively. Induction of differentiation was achieved by exposing cells to the neurogenic medium. After 21 days of the initial differentiation process, the expression levels of glial fibrillary acidic protein (GFAP), microtubule-associated protein (MAP2), ß-tubulin III, and neuronal nuclear antigen (NeuN) were analyzed using the immunostaining technique. The results illustrated a notable expression of MAP2, ß-tubulin-III, and NeuN in the three-dimensional cell culture in comparison to the two-dimensional system, indicating the beneficial effect of PuraMatrix scaffolds in the process of differentiating breastmilk-derived stem cells into neural-like cells. In view of the obtained results, the combination of breastmilk-derived stem cells and PuraMatrix hydrogel scaffold could be an advisable preference for neural tissue regeneration and cell therapy.

A survey on multi-lingual offensive language detection.

The prevalence of offensive content on online communication and social media platforms is growing more and more common, which makes its detection difficult, especially in multilingual settings. The term "Offensive Language" encompasses a wide range of expressions, including various forms of hate speech and aggressive content. Therefore, exploring multilingual offensive content, that goes beyond a single language, focus and represents more linguistic diversities and cultural factors. By exploring multilingual offensive content, we can broaden our understanding and effectively combat the widespread global impact of offensive language. This survey examines the existing state of multilingual offensive language detection, including a comprehensive analysis on previous multilingual approaches, and existing datasets, as well as provides resources in the field. We also explore the related community challenges on this task, which include technical, cultural, and linguistic ones, as well as their limitations. Furthermore, in this survey we propose several potential future directions toward more efficient solutions for multilingual offensive language detection, enabling safer digital communication environment worldwide.

Toward a Unified Naming Scheme for Thermo-Active Soft Actuators: A Review of Materials, Working Principles, and Applications.

Soft robotics is a rapidly growing field that spans the fields of chemistry, materials science, and engineering. Due to the diverse background of the field, there have been contrasting naming schemes such as "intelligent," "smart," and "adaptive" materials, which add vagueness to the broad innovation among literature. Therefore, a clear, functional, and descriptive naming scheme is proposed in which a previously vague name-Soft Material for Soft Actuators-can remain clear and concise-Phase-Change Elastomers for Artificial Muscles. By synthesizing the working principle, material, and application into a naming scheme, the searchability of soft robotics can be enhanced and applied to other fields. The field of thermo-active soft actuators spans multiple domains and requires added clarity. Thermo-active actuators have potential for a variety of applications spanning virtual reality haptics to assistive devices. This review offers a comprehensive guide to selecting the type of thermo-active actuator when one has an application in mind. In addition, it discusses future directions and improvements that are necessary for implementation.

Retrospective Review of the Efficacy of Lumbar Radiofrequency Ablation for Lumbar Facet Arthropathy: The Influence of Gender and Obesity.

BACKGROUND: Lumbar facet arthropathy is one of the leading causes of back pain. Lumbar radiofrequency lesioning is a therapy for lumbar facet arthropathy that uses heat to ablate the transmission of nerve signals from the medial branches of the spinal nerves associated with the corresponding painful lumbar joints. OBJECTIVES: The present investigation evaluated the outcomes of patients undergoing lumbar radiofrequency ablation at an academic pain program with a special focus on the influence of gender and obesity. STUDY DESIGN: Retrospective chart review. SETTING: Academic tertiary care center. METHODS: We reviewed the charts of 232 patients for age, body mass index, gender, other procedures, and complications, in addition to the primary outcome measurements of Visual Analog Scale pain scores, pain relief percentages, pain relief duration, and functional status improvement per patient report. Associations with outcomes were evaluated with correlations, t tests/analysis of variance, and c2 test. Influences on a change in Visual Analog Scale pain scores before and after treatment were assessed with linear regression. RESULTS: Patients had an average pain reduction of 76.6% (SD = 24.5) from the initial treatment and an average of 30.7 weeks (SD = 21.2) of pain relief from the initial treatment. A total of 83% of the patients reported an improvement in functional status from the initial treatment. Women (mean = 79.8%, SD = 21.4) had a slightly higher pain relief percentage than men (mean = 71.6%, SD = 28.1; P = 0.046). A higher body mass index was associated with less improvement in Visual Analog Scale maximum pain scores from before and after the procedure (b = 0.04; SE = 0.02; P = 0.042). LIMITATIONS: Our study is not a randomized controlled trial; however, based on the number of patients reviewed, our data provide important information regarding lumbar radiofrequency ablations. CONCLUSIONS: This study highlights significant effectiveness for patients undergoing lumbar radiofrequency ablations for lumbar facet joint pain. A variation in effectiveness appears to be influenced by gender and obesity, and therefore additional studies are warranted to further investigate these differences.

Postbiotic as Novel Alternative Agent or Adjuvant for the Common Antibiotic Utilized in the Food Industry.

BACKGROUND: Antibiotic resistance is a serious public health problem as it causes previously manageable diseases to become deadly infections that can cause serious disability or even death. Scientists are creating novel approaches and procedures that are essential for the treatment of infections and limiting the improper use of antibiotics in an effort to counter this rising risk. OBJECTIVE: With a focus on the numerous postbiotic metabolites formed from the beneficial gut microorganisms, their potential antimicrobial actions, and recent associated advancements in the food and medical areas, this review presents an overview of the emerging ways to prevent antibiotic resistance. RESULTS: Presently, scientific literature confirms that plant-derived antimicrobials, RNA therapy, fecal microbiota transplantation, vaccines, nanoantibiotics, haemofiltration, predatory bacteria, immunotherapeutics, quorum-sensing inhibitors, phage therapies, and probiotics can be considered natural and efficient antibiotic alternative candidates. The investigations on appropriate probiotic strains have led to the characterization of specific metabolic byproducts of probiotics named postbiotics. Based on preclinical and clinical studies, postbiotics with their unique characteristics in terms of clinical (safe origin, without the potential spread of antibiotic resistance genes, unique and multiple antimicrobial action mechanisms), technological (stability and feasibility of large-scale production), and economic (low production costs) aspects can be used as a novel alternative agent or adjuvant for the common antibiotics utilized in the production of animal-based foods. CONCLUSION: Postbiotic constituents may be a new approach for utilization in the pharmaceutical and food sectors for developing therapeutic treatments. Further metabolomics investigations are required to describe novel postbiotics and clinical trials are also required to define the sufficient dose and optimum administration frequency of postbiotics.

Alignment behavior of nerve, vascular, muscle, and intestine cells in two- and three-dimensional strategies.

By harnessing structural hierarchical insights, plausibly simulate better ones imagination to figure out the best choice of methods for reaching out the unprecedented developments of the tissue engineering products as a next level. Constructing a functional tissue that incorporates two-dimensional (2D) or higher dimensions requires overcoming technological or biological limitations in order to orchestrate the structural compilation of one-dimensional and 2D sheets (microstructures) simultaneously (in situ). This approach enables the creation of a layered structure that can be referred to as an ensemble of layers or, after several days of maturation, a direct or indirect joining of layers. Here, we have avoided providing a detailed methodological description of three-dimensional and 2D strategies, except for a few interesting examples that highlight the higher alignment of cells and emphasize rarely remembered facts associated with vascular, peripheral nerve, muscle, and intestine tissues. The effective directionality of cells in conjunction with geometric cues (in the range of micrometers) is well known to affect a variety of cell behaviors. The curvature of a cell's environment is one of the factors that influence the formation of patterns within tissues. The text will cover cell types containing some level of stemness, which will be followed by their consequences for tissue formation. Other important considerations pertain to cytoskeleton traction forces, cell organelle positioning, and cell migration. An overview of cell alignment along with several pivotal molecular and cellular level concepts, such as mechanotransduction, chirality, and curvature of structure effects on cell alignments will be presented. The mechanotransduction term will be used here in the context of the sensing capability that cells show as a result of force-induced changes either at the conformational or the organizational levels, a capability that allows us to modify cell fate by triggering downstream signaling pathways. A discussion of the cells' cytoskeleton and of the stress fibers involvement in altering the cell's circumferential constitution behavior (alignment) based on exposed scaffold radius will be provided. Curvatures with size similarities in the range of cell sizes cause the cell's behavior to act as if it was in an in vivo tissue environment. The revision of the literature, patents, and clinical trials performed for the present study shows that there is a clear need for translational research through the implementation of clinical trial platforms that address the tissue engineering possibilities raised in the current revision. This article is categorized under: Infectious Diseases > Biomedical Engineering Neurological Diseases > Biomedical Engineering Cardiovascular Diseases > Biomedical Engineering.

Fabrication of a microfluidic device for probiotic drug's dosage screening: Precision Medicine for Breast Cancer Treatment.

Breast cancer is the most common cancer in women; it has been affecting the lives of millions each year globally and microfluidic devices seem to be a promising method for the future advancements in this field. This research uses a dynamic cell culture condition in a microfluidic concentration gradient device, helping us to assess breast anticancer activities of probiotic strains against MCF-7 cells. It has been shown that MCF-7 cells could grow and proliferate for at least 24 h; however, a specific concentration of probiotic supernatant could induce more cell death signaling population after 48 h. One of our key findings was that our evaluated optimum dose (7.8 mg/L) was less than the conventional static cell culture treatment dose (12 mg/L). To determine the most effective dose over time and the percentage of apoptosis versus necrosis, flowcytometric assessment was performed. Exposing the MCF-7 cells to probiotic supernatant after 6, 24 and 48 h, confirmed that the apoptotic and necrotic cell death signaling were concentration and time dependent. We have shown a case that these types of microfluidics platforms performing dynamic cell culture could be beneficial in personalized medicine and cancer therapy.

A new full closed-loop brain-machine interface approach based on neural activity: A study based on modeling and experimental studies.

Background: The bidirectional brain-machine interfaces algorithms are machines that decode neural response in order to control the external device and encode position of artificial limb to proper electrical stimulation, so that the interface between brain and machine closes. Most BMI researchers typically consider four basic elements: recording technology to extract brain activity, decoding algorithm to translate brain activity to the predicted movement of the external device, external device (prosthetic limb such as a robotic arm), and encoding interface to convert the motion of the external machine to set of the electrical stimulation of the brain. New method: In this paper, we develop a novel approach for bidirectional brain-machine interface (BMI). First, we propose a neural network model for sensory cortex (S1) connected to the neural network model of motor cortex (M1) considering the topographic mapping between S1 and M1. We use 4-box model in S1 and 4-box in M1 so that each box contains 500 neurons. Individual boxes include inhibitory and excitatory neurons and synapses. Next, we develop a new BMI algorithm based on neural activity. The main concept of this BMI algorithm is to close the loop between brain and mechaical external device. Results: The sensory interface as encoding algorithm convert the location of the external device (artificial limb) into the electrical stimulation which excite the S1 model. The motor interface as decoding algorithm convert neural recordings from the M1 model into a force which causes the movement of the external device. We present the simulation results for the on line BMI which means that there is a real time information exchange between 9 boxes and 4 boxes of S1-M1 network model and the external device. Also, off line information exchange between brain of five anesthetized rats and externnal device was performed. The proposed BMI algorithm has succeeded in controlling the movement of the mechanical arm towards the target area on simulation and experimental data, so that the BMI algorithm shows acceptable WTPE and the average number of iterations of the algorithm in reaching artificial limb to the target region.Comparison with existing methods and Conclusions: In order to confirm the simulation results the 9-box model of S1-M1 network was developed and the valid "spike train" algorithm, which has good results on real data, is used to compare the performance accuracy of the proposed BMI algorithm versus "spike train" algorithm on simulation and off line experimental data of anesthetized rats. Quantitative and qualitative results confirm the proper performance of the proposed algorithm compared to algorithm "spike train" on simulations and experimental data.

Enhanced balancing GAN: minority-class image generation.

Generative adversarial networks (GANs) are one of the most powerful generative models, but always require a large and balanced dataset to train. Traditional GANs are not applicable to generate minority-class images in a highly imbalanced dataset. Balancing GAN (BAGAN) is proposed to mitigate this problem, but it is unstable when images in different classes look similar, e.g., flowers and cells. In this work, we propose a supervised autoencoder with an intermediate embedding model to disperse the labeled latent vectors. With the enhanced autoencoder initialization, we also build an architecture of BAGAN with gradient penalty (BAGAN-GP). Our proposed model overcomes the unstable issue in original BAGAN and converges faster to high-quality generations. Our model achieves high performance on the imbalanced scale-down version of MNIST Fashion, CIFAR-10, and one small-scale medical image dataset. https://github.com/GH920/improved-bagan-gp.

Nonlinear analysis of postural changes related to the movement interventions during prolonged standing task.

This study assessed the effects of movement-based interventions on the complexity of postural changes during prolonged standing. Twenty participants, equally distributed in gender and standing work experience (SWE), completed three simulated prolonged standing sessions: without movement (control), leg exercise and footrest. The amount and complexity of variability in the centre of pressure (COP) and lumbar curvature angle were quantified using linear and nonlinear tools. Lower leg swelling and back/leg discomfort were also monitored. Participants in the SWE group showed significantly greater postural complexity during the standing. Regular leg exercise resulted in significantly higher postural complexity and lower leg discomfort and swelling. The footrest led to significant changes in amount of COP variability. Both interventions significantly reduced back discomfort. Overall, the nonlinear analysis of postural changes provided different findings compared to linear ones, considering the standing time, interventions and standing job experience. Nonlinear results were consistent with leg discomfort and swelling.Practitioner summary: The effect of movement-based interventions on dynamics of postural alterations over prolonged standing were characterised using nonlinear techniques. The effect of standing work experience was also considered. Previous experience of standing jobs and leg movements increase the complexity of postural behaviour over standing period.

Protective effects of Biebersteinia multifida on sub-chronic toxicity of DZN in male Wistar rats: biochemical, hematological, and oxidative stress indices.

The protective effect of Biebersteinia Multifida on diazinon-induced toxicity in male Wistar rats was investigated over 8 weeks. Impacts of diazinon (10 mg/kg daily), Biebersteinia Multifida (500 mg/kg daily), and coadministration of them on oxidative stress parameters besides hematological and biochemical indices were assessed in various groups. The gas chromatography-mass spectrometry analysis was performed to identify the antioxidant components of plant extract by comparing the mass spectra and retention indices with those given in the literature. Pseudocholinesterase level demonstrated a significant attenuation in the Biebersteinia Multifida+diazinon-treated group in comparison to the diazinon group at the end of the 8th week. Statistical significant differences in hematological and biochemical indices were detectable when the diazinon group was compared to Biebersteinia Multifida+diazinon-treated rats. While diazinon destroyed hepatic and renal functions, Biebersteinia Multifida protected the liver and kidney from diazinon toxic effects by normalizing related function indices at the end of the 8th week. By diminishing malondialdehyde and enhancing the ferric-reducing power, Biebersteinia Multifida minimized the hazardous effect of diazinon-induced oxidative stress. Following these results, the beneficial effects of Biebersteinia Multifida in reducing the toxicity of diazinon should be taken into consideration.

Effects of pressurization on the enthalpy of vaporization for the SiO2 nanofluid.

Using a microchannel heatsink is an advanced cooling technique to meet the cooling needs of electronic devices installed with high-power integrated circuit packages (microchips). These heat sinks utilize microchannel heat exchangers (MCHEs) with boiling-mode cooling (BMC) and nanofluids. Such MCHEs usually have high operating pressures (3-13 bar). In spite of a large number of studies carried out on other thermo-physical properties of nanofluids, few studies have been carried out on the latent heat of evaporation (LHE) of nanofluids. The limited published literature all reports the LHE under atmospheric conditions, which are outside of the operating range of MCHEs. The precise estimation of the LHE is essential for the appropriate design of MCHEs. In the present study, a novel experimental setup is applied for the measurement of LHE under high operating pressure and temperature conditions (90-180 °C and 80-880 kPa) and for investigating the effects of pressure on the LHE. It has been shown that by exposing a nanofluid under pressure some new hydrogen bonds are formed increasing the LHE, which significantly improves the performance of boiling cooling of MCHEs. Based on the obtained results by pressurizing a 2 vol% (4.6 wt%) SiO2 nanofluid, the LHE can be increased by about 17% in comparison with that of a similar non-pressurized sample. On the other hand, pressurization can improve nanofluid stability. Finally, a correlation is proposed for the calculation of enthalpy of evaporation of SiO2 nanofluids.

Recognizing intertwined patterns using a network of spiking pattern recognition platforms.

Artificial intelligence computing adapted from biology is a suitable platform for the development of intelligent machines by imitating the functional mechanisms of the nervous system in creating high-level activities such as learning, decision making and cognition in today's systems. Here, the concentration is on improvement the cognitive potential of artificial intelligence network with a bio-inspired structure. In this regard, four spiking pattern recognition platforms for recognizing digits and letters of EMNIST, patterns of YALE, and ORL datasets are proposed. All networks are developed based on a similar structure in the input image coding, model of neurons (pyramidal neurons and interneurons) and synapses (excitatory AMPA and inhibitory GABA currents), and learning procedure. Networks 1-4 are trained on Digits, Letters, faces of YALE and ORL, respectively, with the proposed un-supervised, spatial-temporal, and sparse spike-based learning mechanism based on the biological observation of the brain learning. When the networks have reached the highest recognition accuracy in the relevant patterns, the main goal of the article, which is to achieve high-performance pattern recognition system with higher cognitive ability, is followed. The pattern recognition network that is able to detect the combination of multiple patterns which called intertwined patterns has not been discussed yet. Therefore, by integrating four trained spiking pattern recognition platforms in one system configuration, we are able to recognize intertwined patterns. These results are presented for the first time and could be the pioneer of a new generation of pattern recognition networks with a significant ability in smart machines.

Predicting Efficacy of 5-Fluorouracil Therapy via a Mathematical Model with Fuzzy Uncertain Parameters.

Background: Due to imprecise/missing data used for parameterization of ordinary differential equations (ODEs), model parameters are uncertain. Uncertainty of parameters has hindered the application of ODEs that require accurate parameters. Methods: We extended an available ODE model of tumor-immune system interactions via fuzzy logic to illustrate the fuzzification procedure of an ODE model. The fuzzy ODE (FODE) model assigns a fuzzy number to the parameters, to capture parametric uncertainty. We used the FODE model to predict tumor and immune cell dynamics and to assess the efficacy of 5-fluorouracil (5-FU) chemotherapy. Result: FODE model investigates how parametric uncertainty affects the uncertainty band of cell dynamics in the presence and absence of 5-FU treatment. In silico experiments revealed that the frequent 5-FU injection created a beneficial tumor microenvironment that exerted detrimental effects on tumor cells by enhancing the infiltration of CD8+ T cells, and natural killer cells, and decreasing that of myeloid-derived suppressor cells. The global sensitivity analysis was proved model robustness against random perturbation to parameters. Conclusion: ODE models with fuzzy uncertain kinetic parameters cope with insufficient/imprecise experimental data in the field of mathematical oncology and can predict cell dynamics uncertainty band.

Sparse representation of brain signals offers effective computation of cortico-muscular coupling value to predict the task-related and non-task sEMG channels: A joint hdEEG-sEMG study.

Cortico-muscular interactions play important role in sensorimotor control during motor task and are commonly studied by cortico-muscular coherence (CMC) method using joint electroencephalogram-surface electromyogram (EEG-sEMG) signals. As noise and time delay between the two signals weaken the CMC value, coupling difference between non-task sEMG channels is often undetectable. We used sparse representation of EEG channels to compute CMC and detect coupling for task-related and non-task sEMG signals. High-density joint EEG-sEMG (53 EEG channels, 4 sEMG bipolar channels) signals were acquired from 15 subjects (30.26 ± 4.96 years) during four specific hand and foot contraction tasks (2 dynamic and 2 static contraction). Sparse representations method was applied to detect projection of EEG signals on each sEMG channel. Bayesian optimization was employed to select best-fitted method with tuned hyperparameters on the input feeding data while using 80% data as the train set and 20% as test set. K-fold (K = 5) cross-validation method was used for evaluation of trained model. Two models were trained separately, one for CMC data and the other from sparse representation of EEG channels on each sEMG channel. Sensitivity, specificity, and accuracy criteria were obtained for test dataset to evaluate the performance of task-related and non-task sEMG channels detection. Coupling values were significantly different between grand average of task-related compared to the non-task sEMG channels (Z = -6.33, p< 0.001, task-related median = 2.011, non-task median = 0.112). Strong coupling index was found even in single trial analysis. Sparse representation approach (best fitted model: SVM, Accuracy = 88.12%, Sensitivity = 83.85%, Specificity = 92.45%) outperformed CMC method (best fitted model: KNN, Accuracy = 50.83%, Sensitivity = 52.17%, Specificity = 49.47%). Sparse representation approach offers high performance to detect CMC for discerning the EMG channels involved in the contraction tasks and non-tasks.

Agent-based Modeling of Tumor and Immune System Interactions in Combinational Therapy with Low-dose 5-fluorouracil and Dendritic Cell Vaccine in Melanoma B16F10.

This study is designed to present an agent-based model (ABM) to simulate the interactions between tumor cells and the immune system in the melanoma model. The Myeloid-derived Suppressor Cells (MDSCs) and dendritic cells (DCs) are considered in this model as immunosuppressive and antigen-presenting agents respectively. The animal experiment was performed on 68 B16F10 melanoma tumor-bearing C57BL/6 female mice to collect dynamic data for ABM implementation and validation. Animals were divided into 4 groups; group 1 was control (no treatment) while groups 2 and 3 were treated with DC vaccine and low-dose 5- fluorouracil (5-FU) respectively and group 4 was treated with both DC Vaccine and low-dose of 5-FU. The tumor growth rate, number of MDSC, and presence of CD8+/CD107a+ T cells in the tumor microenvironment were evaluated in each group. Firstly, the tumor cells, the effector immune cells, DCs, and the MDSCs have been considered as the agents of the ABM model and their interaction methods have been extracted from the literature and implemented in the model. Then, the model parameters were estimated by the dynamic data collected from animal experiments.  To validate the ABM model, the simulation results were compared with the real data. The results show that the dynamics of the model agents can mimic the relations among considered immune system components to an emergent outcome compatible with real data. The simplicity of the proposed model can help to understand the results of the combinational therapy and make this model a useful tool for studying different scenarios and assessing the combinational results. Determining the role of each component helps to find critical times during tumor progression and change the tumor and immune system balance in favor of the immune system.

Modelling System of Two Insulin-Glucose Delays to Achieve the Dynamics of Glucose Changes.

Background: Due to the increased prevalence of diabetes and the irreparable complications of this disease, it is important to measure and monitor the blood glucose levels of diabetic patients. The only way to treat type 1 diabetes is monitoring insulin, and in this type of diabetes, insulin should be injected into the body in order to reduce the patient's blood glucose as prescribed by the physician at certain times. In addition, the only way to treat type 2 diabetes is through diet and exercise daily. Objective: We aim to use an ordinary differential equation model with two-delays to control the rate of changes in blood glucose levels throughout the day, based on the amount of food that the person consumes. Material and Methods: In this analytical study, we extended an ODE model which is parameterized by data collected in this study to capture dynamics of glucose and insulin. We used global sensitivity analysis method to assess model robustness with respect to parameter perturbations. Results: Our results have shown that utilizing the dynamics of changes in blood glucose levels throughout the day can be used to prevent hypoglycemia and hyperglycemic in the diabetic patients. Conclusion: Dynamic modeling can help us to prevent hypoglycemia and hyperglycemia in the diabetic patients.

Design and ergonomic assessment of a passive head/neck supporting exoskeleton for overhead work use.

Overhead work is an important risk factor associated with musculoskeletal disorders of the neck and shoulder region. This study aimed to propose and evaluate a passive head/neck supporting exoskeleton (HNSE) as a potential ergonomic intervention for overhead work applications. Fourteen male participants were asked to perform a simulated overhead task of fastening/unfastening nut in 4 randomized sessions, characterized by two variables: neck extension angle (40% and 80% of neck maximum range of motion) and exoskeleton condition (wearing and not wearing the HNSE). Using the HNSE, significantly alleviated perceived discomfort in the neck (p-value = 0.009), right shoulder (p-value = 0.05) and left shoulder (p-value = 0.02) and reduced electromyographic activity of the right (p-value = 0.005) and left (p-value = 0.01) sternocleidomastoid muscles. However, utilizing the exoskeleton caused a remarkable increase in right (p-value = 0.04) and left (p-value = 0.05) trapezius electromyographic activities. Performance was not significantly affected by the HNSE. Although the HNSE had promising effects with respect to discomfort and muscular activity in the static overhead task, future work is still needed to investigate its effect on performance and to provide support for the generalizability of study results.

A complete, evidence-based review on novichok poisoning based on epidemiological aspects and clinical management.

Background: The whole world has learned about the existence of a highly toxic neuro-paralytic substance called Novichok. A wide range of neuro-paralytic toxins were used during the wars of decades ago, which also had harmful and irreversible effects. Fortunately, the establishment of conventions prohibiting the use of these weapons prevented the adverse clinical consequences of these compounds. What we did in the present study was to evaluate the clinical features of Novichok, how to manage exposure to it, and to evaluate the prognostic aspects associated with this poisoning agent. Methods: The manuscript especial databases including Medline, Web of knowledge, Google scholar, and Scopus were deeply searched by the two blinded investigators for all eligible studies based on the considered keywords. Initially 98 articles were initially collected by database searching that considering eligibility criteria, 83 articles were finally eligible for the final assessment. There is a lack of clinical trials and case-cohort studies on general population about treatment and side effects when it comes to human nerve agents and most of the data in our search is based on animal studies. Results: In evaluating various clinical, auto physiological and prognostic aspects of exposure to these substances, special attention was necessary to the following points. First, Novichok agents are considered more potent than other toxic agents. Pathophysiologically, these agents irreversibly bind acetylcholinesterase and produce a rapid cholinergic toxidrome which is responsible for the clinical manifestations as well as the potential dangerous and life threatening side effects caused by these agents. Uniquely, these agents are thought to also target every neuron in the central and peripheral nervous system. As a managerial and therapeutic approach, early and timely treatment of its related complication along with prevents massive exposure and decontamination in addition to rapid resuscitation can prohibit debilitating neuropathy and death due to facing it. Conclusion: The present review highlights the importance of recognizing the potential acute toxic effects of Novichok agents, diagnostic and therapeutic approaches (life-saving antidotal therapy) to complications and ultimately the application of guidelines to improve the prognosis of exposure to these agents for both victims and medical community.