Miracle-dz/UniFAR-FTUs huggingface dataset:
A method for synthesizing the haptic response of nonlinear deformable objects from data obtained by offline simulation helps create surgical simulators with high-fidelity haptic feedback

cially created tactile sensations. One important use of these displays is to recreate the experience caused by contact between a tool and an object. This capability can be useful in several applications, such as surgical simulators, because users experience an enhanced sense of realism when a haptic simulation is combined with a graphic simulation. Haptic displays require two essential subsystems: a haptic device, which typically has a handle connected to sensors and actuators, and a computational system that interfaces with the device. As shown in Figure 1, the haptic simulator’s function is to reproduce what is felt. Because the physics of light differs from the physics of mechanical interactions, we must recognize that although graphic and haptic simulations can share the encoding of certain properties, such as shape, they must differ in many other aspects, such as models, mathematical techniques, and implementation. One key difference is the need to synthesize a force vector for haptics, as opposed to an illumination field for graphics. If all the components of the simulator are sufficiently accurate, the system can generate a vivid experience of interacting with real objects. The process of computing and generating forces in response to the interaction with virtual objects is sometimes called haptic rendering. For many applications, high fidelity is important. This article proposes a definition for high-fidelity haptic synthesis in terms of four requirements:
Correction in Diagnosis of Parkinson’s Disease with Prediction

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The aim of this work is to fasten the diagnosis of Parkinson's Disease at an early stage considering one of its symptoms which is Dysphonia (abnormal condition of producing speech) to be collected as a dataset from respective voice recordings modulated at different frequencies of respective patients ,then using machine learning model (XGBoost Classifier) predict the diagnosis of the disease with high precision and also Study the recording of muscle response with the aid of the EMG sensor module (Electromyography) with changes in muscle activity (suggested physiotherapy) in the form of an analogue signal. With this implementation we are able to diagnose Parkinson’s Disease at an early stage to reduce the severity level of the disease.
Categorization of seen images from brain activity using sequence models

How do different visual regions of the brain react to an image and are these activities any different when looking at an image of a dog versus a mountain? Are there speciﬁc voxels that are more receptive to living species than to objects? With the release of BOLD5000 data set, we have access to human functional MRI (fMRI) mapped to 5000 distinct images from Scene UNderstanding (SUN), COCO, and ImageNet datasets. Relative to prior datasets, BOLD5000 has signiﬁcantly higher image count and diversity, providing a great opportunity to better understand neuron actives related to vision. In this paper we present an LSTM model for identifying what image a person is looking at from their brain activities over time. First we identify 3 super categories for our problem: Animal, Artifact, and Scene. Then we train an LSTM model on visual region voxel activities over time to predict these super categories and achieve an accuracy of 68%. Our results demonstrate an important step towards better understanding the visual processing systems of the human brain. 1
Development of EEG Data-driven Generative Art Application for Real-time and Dynamic Interaction

Generative art is produced by procedural techniques. It has obtained a lot of attention since the beginning of computer graphics. Many works of art are inspired by nature, among which phyllotaxis is as well. It is a combination of mathematics and the beauty of nature. Not only can it be seen everywhere in nature, but also often appear in man-made objects, becoming part of culture or religion. This paper presents the development of an interactive generative art application that is created from a phyllotaxis pattern by using the user’s Electroencephalogram (EEG) data. When people are using it, it will allow them to more easily relax and achieve the function of art
FULL-WAVE FDTD ANALYSIS OF RECTANGULAR MICROSTRIP ANTENNA ON GRADED COMPOSITE SUBSTRATE

The Finite Difference Time Domain (FDTD) full wave analysis technique is applied to microstrip antenna designed on LDPE/titania graded dielectric substrates. The FDTD simulation generates data which helps in visualizing the time progression of vector fields throughout the three-dimensional solution space. It gives a physical insight of complex field interactions at different stages of field propagation. The radiation response of the microstrip antenna is analysed by finding the scattering parameters by taking Fourier transformation of the transient E field component. The S11 obtained using this method for the graded substrate antenna is compared with the measured and simulated (using CST Microwave Studio) results which shows proximity.
Variational inverse modelling within the Community Inversion Framework to assimilate δ13C(CH4) and CH4: a case study with model LMDz-SACS

Framework to assimilate δC(CH4) and CH4 : a case study with model LMDz-SACS Joël Thanwerdas1,*, Marielle Saunois1, Antoine Berchet1, Isabelle Pison1, Bruce H. Vaughn2, Sylvia Englund Michel2, and Philippe Bousquet1 1Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ, IPSL, Gif-sur-Yvette, France. 2INSTAAR University of Colorado, Boulder, CO, United States Correspondence: J. Thanwerdas (joel.thanwerdas@lsce.ipsl.fr)
Feature Selection using Graph based Clustering methods - A Review

------------------------------------------------------------------- Abstract - Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. A feature selection algorithm may be evaluated from both the efficiency and effectiveness points of view. Based on these criteria, clustering-based feature selection algorithms have been given. In which a minimum spanning tree (MST) is used for representation of the graph and solve the cluster identification problem using this representation. Due to their ability to detect clusters with irregular boundaries, minimum spanning tree-based clustering algorithms have been widely used in practice. Here we have study some graph clustering methods.
Histopathological assessment of nano n-acetyl cysteine effect on postoperative adhesion in rats

Department of Clinical Science, Faculty of Specialized Veterinary Sciences, Science and Research Branch, Islamic Azad University, Universal Scientific Education and Research Network (USERN), Department of Pathobiology, Faculty of Specialized Veterinary Sciences, Science and Research Branch, Islamic Azad University, Tabriz, Department of Food Hygiene, Faculty of Veterinary Medicine, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
Openspace Sonification: Complementing Visualization of the Solar System with Sound

Data visualization software is commonly used to explore outer space in a planetarium environment, where the visuals of the software is typically accompanied with a narrator and supplementary background music. By letting sound take a bigger role in these kinds of presentations, a more informative and immersive experience can be achieved. The aim of the present study was to explore how sonification can be used as a complement to the visualization software OpenSpace to convey information about the Solar System, as well as increasing the perceived immersiveness for the audience in a planetarium environment. This was investigated by implementing a sonification that conveyed planetary properties, such as the size and orbital period of a planet, by mapping this data to sonification parameters. With a user-centered approach, the sonification was designed iteratively and evaluated in both an online and planetarium environment. The results of the evaluations show that the participants found the sonification informative and interesting, which suggest that sonification can be beneficially used as a complement to visualization in a planetarium environment.
Final Report Summary-WATBIO ( Development of improved perennial non-food biomass and bioproduct crops for water stressed environments )

Executive Summary: The over-arching aim of WATBIO was to develop new and improved germplasm for non-food perennial feedstock crops suitable for the emerging bioeconomy in Europe. Three perennial crops were chosen: Populus, Miscanthus and Arundo, and their ability to tolerate droughted environments and to maintain biomass production in water-scarce and droughted conditions was investigated. Excellent progress was made to deliver all aspects of the project and in several areas the project has moved significantly beyond the original workplan. This includes in particular, the extended development of genomic resources where a reduction in sequencing costs enabled additional research on (i) RNAseq analysis of WATBIO RNAi lines,
Equine osteoarthritis: An overview of different treatment strategies.

Elhussein E. Mahmoud, Ahmed S. A. Hassaneen, Mohammed A. Noby, Amany S. Mawas, Abdel-Nasser A. Abdel-Hady Department of Surgery, Anaesthesiology, and Radiology, College of Veterinary Medicine, South Valley University, Qena 83523, Egypt, Department of Theriogenology, Obstetrics, and Artificial Insemination, College of Veterinary Medicine, South Valley University, Qena 83523, Egypt, Department of Pathology & Clinical Pathology, College of Veterinary Medicine, South Valley University, Qena 83523, Egypt.
Supplementary Material: Modeling Probability Forecasts via Information Diversity

Denote the set of all coherent information structures with QN . Consider Σ22 ∈ QN and its associated Borel sets {Bi : i = 1, . , N}. Given that Σ22 is coherent, its information can be represented in a diagram such as the one given by Figure 1 in the main manuscript. Keeping the diagram representation in mind, partition the unit interval S into 2 disjoint parts Cv := ∩i∈vBi \ ∪i/ ∈vBi, where v ⊆ {1, . , N} denotes a subset of forecasters and each Cv represents information used only by the forecasters in v. Given that ∑ v |Cv| = 1, it is possible to establish a linear function L from the probability simplex
Swift Automated System for Distinguishing Blue-White Colonies Post Bacterial Transformation on Agar Plates Using Computer Vision Techniques

The manual selection of transformed bacterial colonies from non-transformed ones grown on agar plate post-blue-white screening – despite chromogenic difference – is cumbersome, owing to their small size and large cell number. The present study offers a lucrative solution to this problem by the design of an automated system that is not only fast and less laborious but also low priced and user-friendly. The image masking technique was used to distinguish plated transformed colonies. This method uses computer vision techniques to detect the number of blue and white colonies post bacterial transformation on agar plates and calculate the transformation efficiency. To assess the proposed model with the manual counting method, we have validated the model by comparing the manual counting of colonies with the automated system count. Hence, a model was developed that would be an added advantage to biotechnologists as it would minimize the time required for counting and help in productive research.
Association of Platelet Lymphocyte Ratio (PLR) and Neutrophil Lymphocyte Ratio (NLR) with Global Registry of Acute Coronary Events (GRACE) Score in Acute Coronary Syndrome

Introduction: Acute Coronary Syndrome (ACS) has morbidity and mortality significantly increase, it requires risk stratification for the assessment and selection of initial invasive strategies. The Global Registry of Acute Coronary Events (GRACE) scores recommended as risk stratification of ACS. Some of studies found that the combination of GRACE scores with other clinical and laboratory parameters can increase predictive value of ACS. Platelet Lymphocyte Ratio (PLR) and Neutrophil Lymphocyte Ratio (NLR) act as parameter of systemic inflammation in ACS. Aims of the study to determine the association between PLR and NLR with risk stratification GRACE score. Method: This study is analytical with a cross-sectional retrospective design. This study included 70 patients with a diagnosis of ACS based on medical record data. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS) 22.0. P-value <0.05 was considered statistically significant. Results: This study was found a positive correlation between PLR and NLR with the GRACE score of patients ACS (r=0.485, p<0.001; r=0.570, p<0.001). The PLR and NLR were both found the significantly higher in the high risk GRACE score respectively (188 ± 47, p < 0.001; 7.9± 2.7, p<0.001). The ROC curve analysis, cutt-off PLR of 123 and above (sensitivity of 72.7 %; specificity of 70.3), while cutt-off NLR of 4 and above (sensitivity of 78.8%; specificity of 70.3%) to detect high risk GRACE score. Conclusion: There is a significant association between PLR and NLR with GRACE score
Global Computing Project IST-2001-32222 Mobile Calculi Based on Domains Type Systems for Open Networks , using the MIKADO core programming models

In the last decade, several foundational formalisms for global computing have appeared in literature to improve the understanding of the complex mechanisms underlying such new computational scenario. In their design, the integration of security mechanisms is a major challenge and great efforts have been recently devoted to embed such mechanisms within standard programming features. In this deliverable, we shall focus on the security mechanisms put forward by type systems, that are used for expressing and checking behavioural properties concerning mobility, resource access, security, etc. Moreover, when dealing with distributed and mobile computing in wide-area “open” systems, one is often confronted with a scenario where interaction may take place between parties whose respective properties are unknown or only partially known to each other. If stopping the execution for re-checking is to be avoided, each component must dynamically carry with it sufficient behavioural information that can be checked at runtime by the other ones interacting with it. We present here three typing approaches focussed on security properties of open systems, and on their enforcement mechanisms. The solutions proposed do not rely on a single process calculus but encompass three successfull models for global computing systems: Dπ, Ambient and KLAIM.
Effects of Different Solvent Polarity on the Quality Characteristics of Conophor Nut Oil

This study investigated the effect of different extraction solvents on physico-chemical and fatty acid compositions of conophor nut oil (Tetracarpidiumconophorum). Solvent extraction was done using Soxhlet and physico-chemical properties and fatty acid profiles of the oils were carried out using standard procedure. The oil yields of conophor nut oil ranged from 43.77% (ethanol) to 46.72% (n-hexane). The physico-chemical properties values such as iodine number; refractive index; saponification value; acid value; peroxide value; viscosity at 25°C and colour were 23.46-28.31 g I2/100g; 1.52-1.66; 190.90-199.16 mg KOH/g; 2.41-2.62 mg NaOH/g; 3.47 to 4.28 meq O2/g; 11.43-13.98 mPa. ; light yellow to deep yellow, respectively. The fatty acid compositions of the oil showed that saturated and unsaturated components ranged from 5.18-7.81% and 83.1-93.13%, respectively. Some of the saturated components of conophor nut oil include palmitic; cerotic; melissic; valeric and tridecyclic while its unsaturated components are oleic; isooleic; petroselinic; linolenic; alpha-linolenic and eicosatrienoic. In conclusion, the results showed that different solvents used in extraction of the conophor nut oil affected some physico-chemical properties of the oil. Similarly, fatty acid compositions were also affected. The properties investigated showed that the oil can find its usage food formulation and chemical industries.
The corrosion behaviors of multilayer diamond-like carbon coatings: influence of deposition periods and corrosive medium

Electrochemical measurements, salt spray tests and immersion tests were employed to investigate the influence of deposition periods and corrosive medium (NaCl, H2SO4, HCl, NaOH) on the corrosion behaviors of silicon doped multilayer diamond-like carbon (DLC) coatings. The results showed that the corrosion resistance of the multilayer DLC coatings was significantly improved with the increase of deposition periods. Interestingly, the coating with the highest deposition periods provided good corrosion protection in neutral and acidic solutions while poor corrosion protection in alkaline and acidic chloride solutions.
Improving the Representative Concatenated Frame Images Base on Convolutional Neural Network for Thai Lip Reading Recognition

—Lip reading could be improved by providing more training data with deep learning techniques. This work aims to improve the concatenated frame images for use as input in deep learning processes by reducing the number of frames and image size for visual speech recognition in Thai. The developed model could be used the Convolutional Neural Network to detect and classify the lip motion from speakers on videos in Thai. The experimental result showed that the developed model with concatenated five frame images gave a training accuracy at 95.67% and training loss was 4.23%, where the validation accuracy was 87.12%, and validation loss was 8.79%. It could be said that the concatenated five frame images were represented as input data and improved Thai lip-reading recognition using the convolutional neural network.
Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors

We propose well-calibrated null preference priors for use with one-sided hypothesis tests, such that resulting Bayesian and frequentist inferences agree. Null preference priors mean that they have nearly 100% of their prior belief in the null hypothesis, and well-calibrated priors mean that the resulting posterior beliefs in the alternative hypothesis are not overconfident. This formulation expands the class of problems giving Bayes-frequentist agreement to include problems involving discrete distributions such as binomial and negative binomial oneand two-sample exact (i.e., valid) tests. When applicable, these priors give posterior belief in the null hypothesis that is a valid p-value, and the null preference prior emphasizes that large p-values may simply represent insufficient data to overturn prior belief. This formulation gives a Bayesian interpretation of some common frequentist tests, as well as more intuitively explaining lesser known and less straightforward confidence intervals for two-sample tests.
Studies in History and Philosophy of Modern Physics

In recent years a growing number of philosophers of science have come to realise that the philosophical foundations of statistical mechanics are not as secure as was once thought. Conceptual problems that had been swept under a carpet of technicalities, or simply ignored, have surfaced, solutions that were accepted are being questioned, and new routes are being explored. Thus, central issues such as the origins of time asymmetry, Maxwell’s demon, and the compatibility of statistical and classical mechanics, are as urgent and intriguing today as they were when statistical mechanics took shape at the end of the nineteenth century. Research in the foundations of the theory of relativity and quantum mechanics has deepened our understanding of these fields. This special issue is motivated by recognition of the need for similar research in the foundations of thermodynamics and statistical mechanics. The analogy between thermodynamics and other fundamental physical theories is itself a matter of controversy. On the one hand, thermodynamics has been recognised as a particularly profound theory, indispensable for our understanding of the physical world. Those who see it in this light are fond of quoting Einstein’s celebrated remark regarding the impression made on him by classical thermodynamics. It was the only physical theory, he said, that he was convinced would never (within the limits of the applicability of its concepts) be overthrown. On the other hand, we frequently hear it said that with the emergence of statistical mechanics, the laws of thermodynamics, and the second law in particular, having been reduced to the law of large numbers, have been explained away. This latter view is often taken to indicate, further, that statistical mechanics is merely a second-order theory, a probabilistic
New morphological data on the rare sigmodontine Mindomys hammondi (Rodentia, Cricetidae), an arboreal oryzomyine from north-western Andean montane forests

The monotypic rodent Mindomys Weksler, Percequillo & Voss, 2006 (Cricetidae, Sigmodontinae) is one of the rarest members of the speciose tribe Oryzomyini. As this species is restricted to the Chocó forests of the western Andean slope in northern Ecuador, our knowledge is based on a few specimens collected decades ago. Here we add the first data on some aspects of external anatomy (cheiridia examined in fresh, ears, rhinarium), genital anatomy (penis), soft anatomy (palate, stomach, caecum) and postcranial skeleton retrieved from a full adult male, recently trapped in Reserva Drácula, Carchi, Ecuador. Several features of this specimen, paradoxically the first to be added to Ecuadorian mammal collections, reinforce the view that Mindomys is an arboreal sigmodontine.
REDUCED INTEGRATION IN THE FINITE ELEMENT ELASTOPLASTIC-DAMAGE ANALYSIS OF ANCIENT MASONRY CONSTRUCTIONS

Structural analysis of ancient masonry constructions under earthquake-like demands is a complicated task due to their irregular geometry and to the mechanical characteristics of masonry. Most solution strategies are based on the use of numerical methods, such as the finite element method, and an ad hoc material constitutive models. As this strategy generally involves high computational costs, its application has to rely on the use of simplifying assumptions regarding the overall behaviour of the problem, which may, nevertheless, drastically impact the accuracy of the results. In this work, the advantages of using solid finite elements based on the use of a sub-integration scheme with hourglass control in nonlinear analysis of historical masonry constructions and of an elastoplastic-damage constitutive model, are investigated. Considering that the high computational cost involved in the calculation of a stiffness matrix of a nonlinear solid element caused by the evaluation of a constitutive model for each loading step, is proportional to the number of integration points employed, using a low-order integration rule is optimal, especially for fine meshes. To represent the nonlinear mechanical behaviour of masonry, an elastoplastic-damage model is implemented within this sub-integration scheme. Also, in order to have a full and computationally efficient strategy to determine the performance of these structures, involving its evolution to collapse, a homogenization technique with a macro-modelling approach is used. Finally the conclusions of this work, derived from the formulation of the method proposed and the analysis of the results obtained from illustrative examples, are given.