Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Multicast Authentication in Energy Automation Environments

— Information security is gaining increasingly more importance for real-time industrial automation networks. Multicast communication is used widely especially on field and process level to cope with performance requirements and to ease the handling of communication peers as the destinations need not to be known by the sender. A security design must not interfere with these communication types. For these reasons, a solution is required allowing to perform an efficient authentication of field level multicast communication.
FutureBody-Finger A Novel Alternative Aid for Visually Impaired Persons

—We have developed a sensory substitution device (SSD), called FutureBody-Finger (FB-Finger) based on a “smart” mechanism with an ecological interface. The primary aim of FB-Finger is to enable visually impaired persons to “recognize” their surrounding environment, specifically in terms of distance. FB-Finger comprises a position-sensitive device (PSD) sensor unit and a small actuator unit and is used to sense the distance as follows: (1) The distance between a (visually impaired) user and an object is measured via ultrasonic waves or infrared rays radiated from the PSD sensor unit; (2) Information on the measured distance is transformed in the actuator unit into haptic stimulation (“somatosensory stimulation”) and then sent to a servo motor incorporated in the actuator unit; and (3) A lever connected to the servo motor catches the stimulation and creates angular motions to convey the information to the user’s finger. In order to afford the device simple use and portability, FB-Finger was designed with a shape such that the forefinger skin/joints receive somatosensory stimulation. In this paper, we outline the concept underlying FB-Finger, describe its underlying mechanism, and report on two psychological experiments conducted. The results of the experiments show that FB-Finger estimates the distance between two objects (i.e., the user and an object) more accurately, and the somatosensory interface enclosed in the device performs better, than commercially available SSDs. On the basis of these findings, we also discuss the effectiveness, possible future improvements, and applicability of FB-Finger to electric travel aids and other assistive aids.
Interdisciplinary Protocols for Timely Assessment and Management of Delirium Symptoms

Purpose: To evaluate a population-based performance improvement pilot project to prevent and better treat acute delirium symptoms. Methods: An interdisciplinary taskforce was convened for protocol development. Protocols and data collection were implemented for three years in three sequential phases. Length of stay, discharge disposition, and frequency of delirium diagnosis were identified as outcome measures. Administrative data was obtained and evaluated for patients pre-and-post protocol phase. Chi-squared tests of independence as well as absolute and relative risk rates were compared between the two cohorts. Results: There was no difference in the relative or absolute risk of delirium diagnosis in either cohort. Statistically and clinically significant differences in length of stay were observed in patients hospitalized with delirium during the 12 months of the project as compared to the 24-month baseline period. The reduction in length of stay was 1.79 days, which correlated to a cost savings of $1033.58 per patient on the orthopedic unit. There was no significant difference in the patient discharge disposition outcome (home, skilled nursing facility, or rehabilitation). Conclusion: The delirium protocols used in the pilot project were associated with reductions length of stay and cost. These findings support more widespread adoption of evidence-based protocols to improve outcomes for patients diagnosed with delirium.
Numerical Calculations of the Cast Solidification with the Complex Shape Including the Movement of the Liquid Phase

The paper presents the results of the computer simulations of solidification with consideration of the liquid phase movement. Simulations were conducted in a real, complex cast. There is a multi-stage resolution to the problem of convection in solidification simulations. The most important resolution concerns the development of the numerical model with the momentum and continuity equations, as well as conditions which are determined by the convection. Simulations were carried out with the use of our authorial software based on stabilized finite elements method (Petroy-Galerkin). In order to solve Navier-Stokes equation (with the convection element), Boussinesq’s approximation were used. Finite Elements Method (FEM) was responsible for the solidification. FEM is close to the heat conduction equation solution (with the internal heat source responsible for the heat released during phase transformation). Convection causes movement in the liquid phase in the solidifying cast and can significantly influence the process of heat transfer from the cast. It may change the distribution of the defects. Results of this article make it possible to assess the conditions in which the influence of the convection on solidification is significant.
Interactive comment on “Long term trends in aerosol optical characteristics in the Po Valley (IT)”

Aerosols properties have been monitored by ground-based in situ and remote sensing measurements at the station for atmospheric research located in Ispra on the edge of the Po Valley for almost one decade. In-situ measurements are performed according to Global Atmosphere Watch recommendations, and quality is assured through the par- 5 ticipation in regular inter-laboratory comparisons. Sunphotometer data are produced by AERONET. Data show signiﬁcant decreasing trends over 2004–2010 for a number of variables including particulate matter (PM) mass concentration, aerosol scattering, backscattering and absorption coe ﬃ cients, and aerosol optical thickness (AOT). In-situ measurement data show no signiﬁcant trend in the aerosol backscatter ratio, 10 but a signiﬁcant decreasing trend of about − 0.7 ± 0.3 % in the aerosol single scattering albedo in the visible light range. Similar trends are observed in the aerosol single scattering albedo retrieved from sunphotometer measurements. Correlations appear between in situ PM mass concentration and aerosol scattering coe ﬃ cient on the one hand, and elemental carbon (EC) and aerosol absorption coe ﬃ cient on the other hand, 15 however, no increase in the EC / PM ratio was observed, which could have explained the decrease in SSA. The application of a simple approximation to calculate the direct radiative forcing by aerosols suggests a signiﬁcant diminution in their cooling e ﬀ ect, mainly due to the decrease in AOT. Applying the methodology we present to those sites where the necessary suite of measurements is available would provide impor- tant information to inform future policies for air quality enhancement and fast climate change mitigation. the trends observed in 2.5 scattering, backscattering and absorption coe ﬃ cients, aerosol optical thickness, and intensive variables (aerosol backscatter ratio and single scattering albedo) calculated from these measurements. These data with decadal trends of in situ aerosol optical properties, because the data series from IPR are still less than 10 years long. However, the consistency between independent remote sensing and in situ data at IPR lend robustness to the observed trends. We estimate their impact on the direct radiative forcing by aerosols and discuss how the application of our methodology to similar datasets obtained across the would lead to important information regarding the impact of current air quality policies on changes in direct radiative forcing.
ISSUES IN MALAYALAM TEXT SUMMARIZATION

: Text Summarization is the process of creates an abridged version of the original text and it covers overall idea about the document. The human summarization requires lot of time and effort. At the same time summarization system produce summary within a short span of time. It generates summaries or abstracts of large documents. Many techniques have been developed for summarization of text in various languages. The techniques may be language dependent or independent. Some techniques may be varies from its discourse structure. The summarization methods can be classified as extractive and abstractive. The abstractive method requires language processing tools. The extractive summarization depends on statistical and linguistic tools. This paper mainly concentrated some of the issues faced by the Malayalam text summarization. The Malayalam summarization faces some difficulties for creating a fruitful summary.
Proceedings of the Workshop on Graphs in Biomedical Image Analysis MICCAI-GRAIL 2017

Human anatomical brain networks derived from the analysis of neuroimaging data are known to demonstrate modular organization. Modules, or communities, of cortical brain regions capture information about the structure of connections in the entire network. Hence, anatomical changes in network connectivity (e.g., caused by a certain disease) should translate into changes in the community structure of brain regions. This means that essential structural differences between phenotypes (e.g., healthy and diseased) should be reflected in how brain networks cluster into communities. To test this hypothesis, we propose a pipeline to classify brain networks based on their underlying community structure. We consider network partitionings into both non-overlapping and overlapping communities and introduce a distance between connectomes based on whether or not they cluster into modules similarly. We next construct a classifier that uses partitioning-based kernels to predict a phenotype from brain networks. We demonstrate the performance of the proposed approach in a task of classifying structural connectomes of healthy subjects and those with mild cognitive impairment and Alzheimer‘s disease.
Not so HOT Triangulations

We propose primal-dual mesh optimization algorithms that overcome shortcomings of the standard algorithm while retaining some of its desirable features. “Hodge-Optimized Triangulations” deﬁnes the “HOT energy” as a bound on the discretization error of the diagonalized Delaunay Hodge star operator. HOT energy is a natural choice for an objective function, but unstable for both mathematical and algorithmic reasons: it has minima for collapsed edges, and its extrapolation to non-regular triangulations is inaccurate and has unbounded minima. We propose a di ↵ erent extrapolation with a stronger theoretical foundation. We propose new objectives, based on normalizations of the HOT energy, with barriers to edge collapses and other undesirable conﬁgurations. We propose mesh improvement algorithms coupling these. When HOT optimization nearly collapses an edge, we actually collapse the edge. Other-wise, we use the barrier objective to update positions and weights. By combining discrete connectivity changes with continuous optimization, we more fully explore the space of possible meshes and obtain higher quality solutions. Labora-tories is a multi-program laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC. , a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. This paper describes objective technical results and anal- ysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.
Using Slang and Emoticon for Sentiment Analysis of Social Media Data

- Social media is a copious source of opinionated data. With the increasing number of people using social media website to vocalize their opinions on various subject, it has become viable to automate these opinions on brand, product, news, story via sentiment analysis aka opinion mining. Opinion mining is gaining insights from these user reviews to know the public view as positive or negative about product, service or brand. This helps business organization and individuals to be proactive in decision making. It finds profound application by helping organization to identify potential product advocates or social media influencers. The current manuscript deals with mining of opinions from the Social media site Twitter on “#Me too” movement. Using tweets generates huge data, which need to be processed and then are to be classified as positive, negative or neutral. The main aim of the manuscript is to use diverse features including emoticons and slang other than conventional Bag of Word features and perform effective Sentiment Classification using these features. We apply a feature selection method to find optimal features and these optimal features are classified. I t is evident from this work that integrating emoticons and slang with conventional Bag of Word model improves the accuracy of classification. The manuscript uses Accuracy, Precision and Recall as the performance metric to analyze the opinion of Twitter users.
FORUM Systems Biology and Mode of Action Based Risk Assessment

The applications of systems biology approaches have greatly increased in the past decade largely as a consequence of the human genome project and technological advances in genomics and proteomics. Systems approaches have been used in the medical and pharmaceutical realm for diagnostic purposes and target identiﬁcation. During this same period, the use of mode of action (MOA) for risk assessment has been increasing and there is a need for quantitative risk assessments on an ever-growing number of environmental chemicals. Genome-wide (i.e., global) measurements provide both a discovery engine for identifying MOA and an information base for subsequent evaluation of MOA when conducting a risk assessment. These genome-wide measurements are not chosen based on the hypothesized MOA and therefore represent an unbiased check of the comprehensiveness of an MOA. In addition, optimal design for MOA studies is critical to provide the time and dose dependent data required for quantitative model building. Finally, identiﬁcation of biomarkers and bioindicators of disease in humans provides a viable way to extrapolate from disease outcomes measured at high exposure levels to those at low exposure levels and thus provide the opportunity to reduce or perhaps eliminate in vivo animal testing. To realize the full potential of these approaches, larger integrated projects which include all these individual components are necessary. molecular level changes with measured events at individual or population level. Molecular networks, driven mainly by data from genome-wide assays, are related to key events in disease processes. disease state of each individual can be modeled as perturbations of these underlying networks. A chemical’s MOA can then be deﬁned in terms of the network perturbations in response to exposure.
A Comparison of Regression Models for the Analysis of Ordered Categorical Data

SUMMARY In a clinical trial on the treatment of lung cancer two chemotherapeutic strategies were compared with respect to tumour response, which was assessed under four ordinal categories. Two regression models for the analysis of ordered categorical data, the proportional odds model and the stereotype model, are used to analyse the data. Differences between the models with respect to estimation and significance tests are further investigated using simulation studies. The results indicate that estimates are less biased in the proportional odds model, but in the stereotype model an improvement may be achieved if adjacent categories are amalgamated. Similar behaviour is observed with respect to tests concerning regression coefficients which are of primary interest in most clinical trials. While in the proportional odds model no relevant deviation from the nominal level of significance is observed, comparable results are obtained in the stereotype model only after amalgamation of categories.
Requirements for Extraction of Polyribosomes from Barley Tissue1

The isolation of barley (Hordeum vulgare L.) polyribosomes, showing minimal degradation effects of endogenous RNase, required a buffer adjusted to pH 8.0 and containing 0.40 M KCI in addition to common extraction components. The extracted polyribosomes were characterized in sucrose gradients by their conversion to monosomes when incubated with pancreatic RNase and by their dependence on adequate amounts of Mg2` during extraction and analysis. Factors which contributed to polyribosome stability were evaluated by the rela- tive sedimentation rates of aggregates in sucrose gradients. of larger ribosomes
Collaborative Filtering Based Recommender System Design For E-Commerce: A Case Study

— Recommender Systems (RS) are one of the core engagement functions for e-commerce industry. In a typical recommender system, customer and product data is analyzed and a prediction model is generated, which evaluates products for prospective customers. In terms of business value, it helps individuals identify their interest among an overwhelming variety of products. In this paper, a collaborative filtering based recommender system framework is proposed for Turkey’s leading e-commerce platform hepsiburada. First of all, implicit feedback and customer-product prediction pairs are prepared from collected data. Second, a regularized Singular Value Decomposition (SVD) based matrix factorization model is established for Collaborative Filtering (CF). Customers and products are represented with latent factor vectors. This model is trained with implicit feedback, as the SVD problem is solved with Alternating Least Squares (ALS). Third, predictions are gathered from the CF model. Then, predictions are limited to ten-product recommendation sets. Finally, recommendations are evaluated by behavioral data generated by prospective customers. The initial results show that 19% of recommendations match customers’ interests.
Serine racemase interaction with N-methyl-D-aspartate receptors antagonist reveals potential alternative target of chronic pain treatment: Molecular docking study

Serine racemase (SR) catalyzes L-serine racemization to activate the N-methyl-D-aspartate receptor (NMDAR). NMDAR activation is associated with the progression of acute-to-chronic neuropathic pain. This study aimed to investigate NMDAR antagonist interactions with SR to obtain potential chronic pain target therapy. Several NMDAR antagonist drugs were obtained from the drug bank, and malonate was used as a control inhibitor. Ligands were prepared using the open babel feature on PyRx. The SR structure was obtained from Protein data bank (PDB) (3l6B) and then docked with ligands using the AutoDock Vina. Haloperidol had a lower binding affinity than malonate and other ligands. Ethanol had the highest binding affinity than other drugs but could bind to the Adenosine triphosphate (ATP)-binding domain. Haloperidol is bound to reface that function for reprotonation in racemization reaction to produce D-serine. Halothane bond with Arg135 residues aligned negatively charged substrates to be reprotonated properly by reface. Tramadol is bound to amino acid residues in the triple serine loop, which determines the direction of the SR reaction. Several NMDAR antagonists such as haloperidol, halothane, ethanol, and tramadol bind to SR in the specific binding site. It reveals that SR potentially becomes an alternative target for chronic pain treatment.
Optimization of microspheres containing virgin coconut oil and hydrolyzed virgin coconut oil as antimicrobial

Virgin Coconut Oil (VCO) with potential fatty acid content has a strong antibacterial effect for drug and cosmetics. VCO was hydrolyzed as hydrolyzed VCO (HVCO) to increase its activity. This study aims to optimize VCO and HVCO microspheres. Examination was included fatty acid content, density, and organoleptic. VCO and HVCO microspheres were characterized by yield, moisture content (MC), morphology, and size. Fatty acid content was done through gas chromatography mass spectrometry whereas for microspheres, effect of alginate concentration (1%–2%), and addition of poly ethylene glycol (PEG) were studied. VCO and HVCO microspheres formulas showed that an increase in polymer concentration, increasing yield, and improving MC. The most optimal 2% alginate with the addition of PEG increased yield up to 59% and reduced size. F4 microspheres resulted the highest yield, low MC, and high fatty acids. Morphology was spherical and smooth with small size. Optimization of HVCO microspheres showed its potential which recommend for antibacterial and antifungal activity.
Diabetic Cardiomyopathy and Ischemic Coronary Heart Disease: Prevention and Therapy by Exercise and Conditioning

: Metabolic syndrome, diabetes and ischemic heart disease are among the leading causes of death and disability in Western countries. Diabetic cardiomyopathy is responsible for the most severe signs and symptoms. An important strategy for reducing the incidence of cardiovascular disease is regular exercise. Remote ischemic conditioning has some similarity with exercise, and can be induced by short periods of ischemia and reperfusion of a limb, and it can be performed in people who cannot exercise. There is abundant evidence that exercise is beneficial in diabetes and ischemic heart disease, but there is a need to elucidate the specific cardiovascular effects of emerging and unconventional forms of exercise in people with diabetes. Also, remote ischemic conditioning may be considered among the options to induce beneficial effects in these patients. The characteristics and interactions of diabetes and ischemic heart disease, and the known effects of exercise and remote ischemic conditioning in the presence of metabolic syndrome and diabetes, are analyzed in this brief review.