Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Recognition of Human Emotions Induced by Visual Contents of Digital Images Based on Color Histogram

Using color histograms in automatic emotion recognition systems faces different issues. One of the important challenges is to determine the appropriate number of bins in the color histogram to achieve the highest recognition performance possible with minimal computations. This research focuses on emotion recognition induced by visual contents of images, or REVC for short, using ARTphoto dataset. Twenty-two different classifiers are used with color histograms in both RGB (red, green, blue) and HSV (hue, saturation, value) color spaces across different numbers of bins, and overall performance of each bin size is compared with that of other bin sizes. The research findings show that the performance of REVC system does not improve in terms of overall sensitivity rate, when the number of bins in color histogram is increased. Moreover, this paper identifies the advantage of using HSV color space over RGB in using color histogram for REVC systems. Furthermore, findings recognize the optimum number of bins in both RGB and HSV color spaces, and ANOVA (analysis of variance) is used to analyze experimental data, which identifies the optimum color histogram bin size used for HSV color space is significantly better than that used for RGB color space in REVC systems.
Dynamic instructional planning for an intelligent physiology tutoring system

An intelligent tutoring system (ITS) that will assist first-year medical students in learning the causal relationships between the parameters of the circulatory system and in solving problems of disturbances to the system is discussed. The central component of the ITS, the instructional planner, is responsible for determining what to do next at each point during a tutoring session. The approach taken is to build the planner by combining the capabilities of lesson planning and discourse planning in order to provide globally coherent and adaptive instruction. The planner consists of two parts: a lesson planner and a discourse planner. The lesson planner generates lesson plans, which the discourse planner carries out. A sample dialogue, extracted from the transcript of an actual human tutor-student interaction, is used to provide a framework for the development of the overall system, especially from the planner's point of view. <<ETX>>
A Simple Technique for the Positioning of a Patient with an above Knee Amputation for an Ipsilateral Extracapsular Hip Fracture Fixation

The positioning of the patient on the fracture table is critical to the successful reduction and operative fixation of hip fractures which are fixed using the dynamic hip screw system (DHS). There is a standard setup which is commonly used with relative ease. Yet the positioning of patients with amputations either above or below knee of the affected side can pose a significant challenge. We describe a novel positioning technique used on a 51-year old patient with a right above knee amputation who sustained an intertrochanteric extracapsular hip fracture.
Segmentation and Visualization of the Lungs in Three Dimensions Using 3D Region Growing and Visualization Toolkit in CT Examinations of the Chest

Computed tomography (CT) stands out among the exams used by computeraided diagnosis in medical imaging as it provides the visualization of internal organs such as the lungs and their structures. This paper focuses on the segmentation of lungs using a three-dimensional region growing (3D RG) method and the registration toolkit ITK library. To evaluate the proposed segmentation method, we used 30 exams from a dataset built in previous work with different types of images and diagnosis. The results were compared against two segmentation tools from OsiriX software, one by toolbox and the other by plugin MIA, and a third, by a medical specialist, which was considered as the gold standard. The results are given in a three-dimensional model with the VTK library and show that the lung segmentation, based on the 3D RG method presented here, produce an average segmentation correctness of 98.75%. Therefore, this method could be part of a computeraided medical diagnosis system in Pulmonology.
Combining task‐related activation and connectivity analysis of fMRI data reveals complex modulation of brain networks

Task‐related effects in functional magnetic resonance imaging (fMRI) data are usually analyzed with local activation approaches or integrative connectivity approaches, for example, by psychophysiological interaction (PPI) analysis. While both approaches are often applied to the same data set, a systematic combination of the results with a whole‐brain (WB) perspective is rarely conducted and the relationship between task‐dependent activation and connectivity effects is relatively unexplored. Here, we combined brain activation and graph theoretical analysis of WB‐PPI results in an exemplary episodic memory data set of N = 136 healthy human participants and found regions with congruent as well as incongruent activation and connectivity changes between task and control conditions. A comparison with large‐scale resting state networks showed that in congruent as well as incongruent regions task‐positively modulated connections were mainly between‐network connections, especially with the default mode network, while task‐negatively modulated connections were mainly found within resting state networks. Over all regions, the strength of absolute activation effects was associated with the tendency to exhibit task‐positive connectivity changes, mainly driven by a strong relationship in negatively activated regions. These results demonstrate that task demands lead to a complex modulation of brain networks and provide evidence that task‐evoked activation and connectivity effects reflect separable and complementary information on the macroscale brain level assessed by fMRI. Hum Brain Mapp 38:5726–5739, 2017. © 2017 Wiley Periodicals, Inc.
The lazy lambda calculus in a concurrency scenario

The use of lambda calculus in richer settings, possibly involving parallelism, is examined in terms of its effect on the equivalence between lambda terms, focusing on S. Abramsky's (Ph.D thesis, Univ. of London, 1987) lazy lambda calculus. First, the lambda calculus is studied within a process calculus by examining the equivalence induced by R. Milner's (1992) encoding into the pi -calculus. Exact operational and denotational characterizations for this equivalence are given. Second, Abramsky's applicative bisimulation is examined when the lambda calculus is augmented with (well-formed) operators, i.e. symbols equipped with reduction rules describing their behavior. Then, maximal discrimination is obtained when all operators are considered; it is shown that this discrimination coincides with the one given by the above equivalence and that the adoption of certain nondeterministic operators is sufficient and necessary to induce it. <<ETX>>
"Welcome!": social and psychological predictors of volunteer socializers in online communities

Volunteer socializers are members of a community who voluntarily help newcomers become familiar with the popular practices and attitudes of the community. In this paper, we explore the social and psychological predictors of volunteer socializers on reddit, an online social news-sharing community. Through a survey of over 1000 reddit users, we found that social identity, prosocial-orientation and generalized reciprocity are all predictors of socializers in the community. Interestingly, a user's tenure with the online community has a quadratic effect on volunteer socialization behaviors -- new and long-time members are both more likely to help newcomers than those in between. We conclude with design implications for motivating users to help newcomers.
Next Generation Ligand Binding Assays—Review of Emerging Real-Time Measurement Technologies

ABSTRACTOver the last few years, numerous ligand binding assay technologies that utilize real-time measurement have been introduced; however, an assemblage and evaluation of these technologies has not previously been published. Herein, we describe six emerging real-time measurement technologies: Maverick™, MX96 SPR™, NanoDLSay™, AMMP®/ViBE®, SoPrano™, and two Lab-on-a-Chip (LoC) microfluidic devices. The development stage gate of these technologies ranges from pre-commercial to commercially available. Due to the novelty, the application and utility of some of the technologies regarding bioanalysis are likely to evolve but it is our hope that this review will provide insight into the direction the development of real-time measurement technologies is moving and the vision of those that are taking us there. Following the technology discussions, a comprehensive summary table is presented.
Group Recommender Model for Boosting and Optimizing Customer Purchases

Group recommender systems generate a set of recommendations that will satisfy a group of customers with potentially competing purchase interests. This paper proposes a research and operational model which effectively enhances Group Recommender Model to boost the customer purchases. For this purpose, it uses the communication and collaboration of two major sources namely Mobile Money Operator and Outlet. MMO proactively monitors the spending pattern of the customers who make purchases using their mobile money. Outlet performs customer segmentation based on RFM (Recency, Frequency and Monetary) score after which a Recursive Cluster Elimination is performed that eliminates customers within the targeted segment. Recursive Frequent Item set Mining and Recursive Market Basket Analysis are performed for the rest of customers in the targeted segment. From the obtained results, the product preferences of the remaining customers in the segment are identified based on which offers are formulated and recommended for the entire segment. It is then communicated to the MMO that intimates these offers to the potential customers among the segment. This model results in boosting customer purchases, expanding customer base and effects in the profitability of the combined source.
Integrating Local Search within neat-GP

There are two important limitations of standard tree-based genetic programming (GP). First, GP tends to evolve unnecessarily large programs, what is referred to as bloat. Second, it uses inefficient search operators that operate at the syntax level. The first problem has been the subject of a fair amount of research over the years. Regarding the second problem, one approach is to use alternative search operators, for instance geometric semantic operators. However, another approach is to introduce greedy local search strategies, combining the syntactic search performed by standard GP with local search strategies for solution tuning, which is a simple strategy that has comparatively received much less attention. This work combines a recently proposed bloat-free GP called neat-GP with a local search strategy. One benefit of using a bloat-free GP is that it reduces the size of the parameter space confronted by the local searcher, offsetting some of the added computational cost. The algorithm is validated on a real-world problem with promising results.
[Protective effects of Aloe vera extract on mitochondria of neuronal cells and rat brain].

OBJECTIVE To investigate the effects of Aloe vera extract (AV) on mitochondria in rat pheochromocytoma (PC12) cells and rat brain and to study the mechanism of its neuroprotection. METHOD After treatment, the morphology of PC12 cells was observed under microscope, the activity of mitochondria in PC12 cells was measured by MTT method, and the mitochondrial membrane potential (MMP) in PC12 cells was detected by JC-1 method. The mitochondrial function in rat brain was detected by resazurin method. The production of malondialdehyd (MDA) in rat brain mitochondria was tested by thiobarbaturic acid (TBA) assay. RESULT AV could improve mitochondrial damage induced by azide sodium (NaN3) in PC12 cells. The viability of PC12 cells treated with NaN364 mmol x L(-1) for 4 h decreased by 47.8%, and AV at 1 and 10 mg x L(-1) could respectively increase the viability of NaN3-treated cells by 16.7% (P < 0.05) and 22.3% (P < 0.01). MMP in PC12 cells in AV 1 and 10 mg x L(-1) group was significantly higher than that of NaN3-treated group (P < 0.05). AV also protected the structure and function of mitochondria in rat brain. AV at 10 mg x L(-1) had protective effect on mitochondria function impair induced by NaN3 (P < 0.01). AV 1 and 10 mg x L(-1) markedly inhibited the lipid peroxidation of brain mitochondria induced by Fe2+ -cysteine (P < 0.05, P < 0.01). CONCLUSION AV has protective effects on mitochondria of neuronal cells and rat brain.
Protein network inference from multiple genomic data: a supervised approach

MOTIVATION An increasing number of observations support the hypothesis that most biological functions involve the interactions between many proteins, and that the complexity of living systems arises as a result of such interactions. In this context, the problem of inferring a global protein network for a given organism, using all available genomic data about the organism, is quickly becoming one of the main challenges in current computational biology. RESULTS This paper presents a new method to infer protein networks from multiple types of genomic data. Based on a variant of kernel canonical correlation analysis, its originality is in the formalization of the protein network inference problem as a supervised learning problem, and in the integration of heterogeneous genomic data within this framework. We present promising results on the prediction of the protein network for the yeast Saccharomyces cerevisiae from four types of widely available data: gene expressions, protein interactions measured by yeast two-hybrid systems, protein localizations in the cell and protein phylogenetic profiles. The method is shown to outperform other unsupervised protein network inference methods. We finally conduct a comprehensive prediction of the protein network for all proteins of the yeast, which enables us to propose protein candidates for missing enzymes in a biosynthesis pathway. AVAILABILITY Softwares are available upon request.
Opiate Receptor Antagonism in Right-Sided Congestive Heart Failure. Naloxone Exerts Salutary Hemodynamic Effects Through Its Action on the Central Nervous System

Opiate receptor inhibition causes adrenergic receptor-mediated increases in aortic pressure, cardiac output, and left ventricular contractile function in right heart failure. To study whether the effects of opiate receptor inhibition are mediated by means of an action on the central opiate system, we administered equimolar doses of naloxone hydrochloride and naloxone methobromide (MeBr) and normal saline to heart failure dogs. Chronic stable right heart failure was produced by progressive pulmonary artery constriction and tricuspid valve avulsion. Naloxone hydrochloride caused an increase in mean aortic pressure, cardiac output, left ventricular dP/dt and dP/dt/P, plasma catecholamines, and regional blood flows to the myocardium, quadriceps muscle, kidneys, and splanchnic beds. Plasma β-endorphin and adrenocorticotropin also increased. In contrast, neither normal saline nor naloxone MeBr (which does not cross the blood-brain barrier) affected the systemic or regional hemodynamics or neurohormones. Naloxone hydrochloride was also administered to anesthetized heart failure dogs. Pentobarbital anesthesia removed cortical perception of nociceptive stimulation, reduced the increase in plasma epinephrine, and abolished vasodilation in skeletal muscle that occurred in conscious dogs after naloxone hydrochloride administration but had no major effects on responses of plasma norepinephrine, systemic hemodynamics, or other regional blood flows to opiate receptor inhibition. Naloxone hydrochloride had no effect in sham-operated dogs. The results indicate that the hemodynamic effects of naloxone are mediated by an action within the central nervous system. Furthermore, since pentobarbital anesthesia did not markedly alter the hemodynamic responses to naloxone hydrochloride, the acute salutary effects of opiate receptor inhibition probably are not caused by removal of the antinociceptive effect of endogenous opiolds in heart failure. {Circulation Research 1989;65:103–114)
Visualization and Computer Graphics on Isotropically Emissive Volumetric Displays

The availability of commodity volumetric displays provides ordinary users with a new means of visualizing 3D data. Many of these displays are in the class of isotropically emissive light devices, which are designed to directly illuminate voxels in a 3D frame buffer, producing x-ray-like visualizations. While this technology can offer intuitive insight into a 3D object, the visualizations are perceptually different from what a computer graphics or visualization system would render on a 2D screen. This paper formalizes rendering on isotropically emissive displays and introduces a novel technique that emulates traditional rendering effects on isotropically emissive volumetric displays, delivering results that are much closer to what is traditionally rendered on regular 2D screens. Such a technique can significantly broaden the capability and usage of isotropically emissive volumetric displays. Our method takes a 3D data set or object as the input, creates an intermediate light field, and outputs a special 3D volume data set called a lumi-volume. This lumi-volume encodes approximated rendering effects in a form suitable for display with accumulative integrals along unobtrusive rays. When a lumi-volume is fed directly into an isotropically emissive volumetric display, it creates a 3D visualization with surface shading effects that are familiar to the users. The key to this technique is an algorithm for creating a 3D lumi-volume from a 4D light field. In this paper, we discuss a number of technical issues, including transparency effects due to the dimension reduction and sampling rates for light fields and lumi-volumes. We show the effectiveness and usability of this technique with a selection of experimental results captured from an isotropically emissive volumetric display, and we demonstrate its potential capability and scalability with computer-simulated high-resolution results.
Informative Census Transform for Visual Object Representation

Our paper newly presents unsupervised feature representation method for images called informative census transform (ICT) based on statistical analysis of CT binary features and submodular optimization. A new cost function is designed to measure the informativeness of each binary feature by considering (1) an individual informativeness of features and (2) relative informativeness between binary features. Moreover, two constraints are designed by considering sub-modular characteristics to guarantee theoretical performance and fast optimization via simple greedy algorithm. Experimental results show that the proposed ICT features with two constraints outperforms the traditional CT features in terms of recognition performance and computational cost.
Maximizing profit using recommender systems

Traditional recommendation systems make recommendations based solely on the customer’s past purchases, product ratings and demographic data without considering the profitability of the items being recommended. In this work we consider the question of how a vendor can directly incorporate the protability of items into its recommendation system so as to maximize expected prot while still providing accurate recommendations. Our approach uses the output of any traditional recommender system and adjusts it according to item protability. Our approach is parametrized so the vendor can control the amount of deviation between the recommendation incorporating prots and the traditional recommendation. We study our approach under two settings and show that it can achieve signicantly more prot than traditional recommendations.
Evidence of a synergistic association between heart rate, inflammation, and cardiovascular mortality in patients undergoing coronary angiography.

AIMS Both elevated inflammatory activity and sustained tachycardia reflect unfavourable cardiovascular risk profiles, and there is evidence to suggest the deleterious effects of inflammation are amplified by increased heart rate. The purpose of this study was to assess the interaction between resting heart rate and inflammation in cardiovascular mortality. METHODS AND RESULTS A total of 3267 patients (2283 men), aged 18-95 years, scheduled for coronary angiography, were followed prospectively. By principle component analysis, we developed an overall multi-marker index of inflammation weighting the respective coefficients of five inflammatory markers including: interleukin-6, C-reactive protein, serum amyloid A, neutrophils, and fibrinogen. Cox proportional hazard regression models were employed to evaluate the relationship between inflammation and heart rate with cardiovascular mortality. Across 29,940 person years of follow-up, there were 546 (17%) deaths due to cardiovascular disease (CVD). Significantly, we observed a strong synergistic effect of inflammatory activity and concurrent elevated heart rate. For CVD mortality, patients in the highest quartile of inflammation had an adjusted hazard ratio (95% confidence interval) of 1.84 (1.31-2.57), P < 0.0001 if their resting heart rate was <75 b.p.m. Substantially, patients had a greater adjusted HR of 7.50 (3.21-17.50), P < 0.0001 if their resting heart rate was ≥75 b.p.m. CONCLUSION The present analyses underline elevated inflammation as a risk factor for cardiovascular mortality. The effects of inflammation appeared to be strongly amplified by a faster resting heart rate. If confirmed by additional studies, this association may prove a useful adjunct for therapeutic approaches to alleviate symptoms and prolong survival.
Evaluation of macroseismic intensities in Mexico from recent earthquakes using ¿Sintió un sismo? (Did you feel it?)

Las investigaciones macrosismicas utilizando datos recolectados a partir de encuestas en linea han adquirido un gran auge en los ultimos anos. Su facil acceso y bajo costo permiten realizar evaluaciones de la severidad del sismo a partir de los efectos observados por la poblacion. Ademas es posible generar curvas de atenuacion para una region en particular, visualizar el estado de las construcciones y los posibles efectos de sitio. En regiones donde no se tiene una buena cobertura de redes sismicas, las intensidades macrosismicas han demostrado ser un gran sustituto de datos instrumentales. En este trabajo se presentan mapas de intensidades macrosismicas para cuatro sismos en distintos puntos del pais. Los datos se obtuvieron de la base de datos del programa ? Sintio un sismo? , una encuesta en linea implementada en el 2014. Encontramos que la atenuacion es menor en zonas consideradas tectonicamente estables que en regiones activas