Miracle-dz/UniFAR-FTUs huggingface dataset:
Expert systems as a tool supporting the assessment of the financial condition of business units

The ubiquitousness of information systems means that more and more areas of the company's activity are moving into the virtual sphere. IT systems take over most of the complicated tasks performed by people, which has a positive impact on time and costs incurred for the implementation of these tasks. One of the areas in which IT systems are used is the area of financial management, and thus the management of the financial condition of the unit. This article aims to test the suitability of expert systems as tools that can support the analysis and assessment of the financial condition of business units. The theoretical part discusses the essence of IT systems, theoretical foundations of expert systems and their advantages and disadvantages. The research part shows the use of an expert system to conduct the analysis of the financial condition of selected enterprises based on data from the financial statements of these units from 2015. The expert system provided information on the financial condition of selected companies. These results were compared with the results of the analysis carried out in the traditional way. This confirmed the author's assumption that it is possible to replace the financial analysis carried out with traditional methods by using a properly prepared expert system.
Two cases with avoidant/restrictive food intake disorder (ARFID): Effectiveness of EMDR and CBT combination on eating disorders (ED)

Traumatic life events are among the etiological factors that may trigger eating disorders (ED). In the present study, we examined the effects of Eye Movement Desensitization and Reprocessing (EMDR) therapy and Cognitive Behavioral Therapy (CBT) therapies combined on two young girls, who had symptoms of ED as a consequence of their traumatic experiences. Two Caucasian female patients arrived at the clinic with highly similar complaints about eating. They both were mutually holding the fear that food would get stuck in their throat, breathing would be impeded and their heart rate would increase; creating an inability to swallow while eating. This culminated in a fear of death through asphyxiation while eating. In the initial interviews, the clients revealed past traumatic events in which a food blockage in the throat led to a temporary inability to breathe. Therefore, we conducted EMDR therapy combined with CBT. Both were treated with seven sessions of EMDR therapy and nine sessions of CBT, after which symptoms were reduced to minimum. In this case study, EMDR therapy combined with CBT proved to be effective by neutralizing the impact of previous trauma on ED symptomatology.
Motors and Mitosis: Characterizing the Role of Dynein in Mammalian Epithelial Spindle Positioning Phenomena

Reproduction distinguishes living organisms from inanimate objects, as cells cannot be made except by division from preexisting cells. Despite the importance of proper cell division for growth, aging, healing, and the prevention of diseases such as cancer, many of the complicated protein interactions involved remain a mystery. Mitosis, the segregation of replicated chromosomes to two new daughter cells, is central to the process of cell division. The forces generated by motor proteins, a special class of proteins able to convert chemical energy from ATP into mechanical energy, are necessary for the movements of the cytoskeleton during mitosis. Dynein is a motor protein that walks along the microtubules of the mitotic spindle, performing several essential roles throughout the phases of mitosis. Research in budding yeast and other model systems has implicated dynein located at the cell cortex as a key player in spindle positioning (Kozlowski et al., 2007; Carminati and Stearns, 1997). The regulation and mechanics of spindle positioning are poorly understood yet critical for both asymmetric and symmetric cell divisions. The characterization of spindle positioning phenomena in a line of mammalian epithelial cells revealed a pattern of asymmetric spindle position at anaphase onset followed by unequal movement of each set of sister chromatids in a significant subpopulation of cells. In addition to phase contrast observation of spindle positioning, microscopic observation of mammalian epithelial cells expressing fluorescent gamma tubulin revealed asymmetric movement of each spindle pole during anaphase. Immunofluorescent fixing and staining of mammalian epithelial cells suggested that dynein localized to the cell cortex plays a role in spindle positioning phenomena.
Managed Stock Recommendations

This study examines whether analysts actively “manage” their recommendation distributions and how such behavior influences the informativeness of their recommendations. We define a potentially managed recommendation as one that appears to be driven by distributional properties of an individual analyst’s portfolio of recommendations, rather than solely by changes in firm fundamentals. We find that analysts are more likely to issue sell recommendations with concurrent buy recommendations and that such behavior is more pronounced when analysts’ recommendations deviate from an internally set target distribution. Recommendation management increases after the Global Settlement, which required analysts to disclose the distribution of outstanding recommendations. Such behavior is also more pronounced among more visible analysts (i.e., All Star analysts and analysts employed by large brokerage houses). Finally, managed recommendations exhibit more muted stock market reactions. Our results provide initial evidence on how incentives across an analyst’s portfolio can compromise analyst objectivity. Preliminary draft: please do not cite or distribute without permission.
Leading-order relativistic corrections to the rovibrational spectrum of $\text{H}_2\,\!^+$ and ${\rm HD}^+$ molecular ions

D. T. Aznabayev,1,2,3 A. K. Bekbaev,1,4 and Vladimir I. Korobov1,5 1Bogoliubov Laboratory of Theoretical Physics, Joint Institute for Nuclear Research, Dubna 141980, Russia 2The Institute of Nuclear Physics, Ministry of Energy of the Republic of Kazakhstan, 050032 Almaty, Kazakhstan 3L. N. Gumilyov Eurasian National University, 010000 Astana, Kazakhstan 4Al-Farabi Kazakh National University, 050038 Almaty, Kazakhstan 5Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St., Moscow 117198, Russia
Taxonomy of the Bacteroides I. Deoxyribonucleic Acid Homologies Among Bacteroides fragilis and Other Saccharolytic Bacteroides Species

Strains of the “Bacteroides fragilis group” and other saccharolytic intestinal bacteroides were delineated by deoxyribonucleic acid homology. Of the 340 strains studied, about 90% belonged to any 1 of 10 major homology groups: The named species B. fragilis, B. vulgatus, B. distasonis, B. thetaiotaomicron, B. ovatus, B. uniformis, and B. eggerthii, a described group temporarily designated “subsp. a,” and groups “3452-A” and “T4-1. ” Organisms belonging to the two latter groups had phenotypic similarities with and had not been previously differentiated from B. distasonis. Thirty more strains had no homology with the above-mentioned groups and appeared to be very heterogeneous when compared among themselves. There were two subgroups within the B. fragilis homology group. These subgroups had about 65 to 70% intergroup homology and about 80 to 90% intragroup homology. The B. ovatus and B. thetaiotaomicron homology groups had similar levels of heterogeneity, but they were more complex in that they appeared to have greater numbers of subgroups. The rest of the homology groups were quite homogeneous, usually having 80 to 90% intragroup homology.
LEGHEMOGLOBIN AND RHIZOBIUM RESPIRATION

INTRODUCTION 444 LEGHEMOGLOBIN 445 Occurrence, Purification, Sequence Analysis 445 Biosynthesis and its Control; Genetic Origin 446 Maintenance, Turnover, and Degradation 448 Leghemoglobin Structure in Relation to Oxygen Reactivity 449 lntracellular Location of Leghemoglobin 451 LEGUME BACTEROIDS AND THE OXYGEN PARADOX 452 Nitrogenase Location and Oxygen Lability: Possible Protective Mechanisms . 452 Cytochrome Variation Among Free-living Rhizobia and Bacteroids 453 Periplasmic Location of Bacteroid Oxidases? 455 LEGHEMOGLOBIN A D RHIZOBIUM RESPIRATION EFFICIENCY 457 Oxygen Delivery and Other Possible Leghemoglobin Functions 457 The Soybean Symbiosis: Recognition of Efficient and Inefficient Phases of Bacteroid Respiration 459 Other Legume Symbioses: Evidence for Increasing Oxygen Tolerance 461 Respiration Substrate in Relation to Symbiotic Efficiency 466 Hemoglobin Nonlegume Symbioses 468 Rhizobium Nitrogen Fixation Without Leghemoglobin 470 CONCLUSIONS 471
Setting the record straight: The office of technology assessment report—pharmaceutical R&D costs, risks, and rewards

The U.S. Office of Technology Assessment (OTA) report on pharmaceutical research and development (R&D)—costs, risks, rewards—has generated a range of often heated responses, both for and against the industry. The purpose of this commentary is to clarify two points of confusion that repeatedly appear about the report: First, it is not a new and definitive study of the cost of pharmaceutical R&D (although certain related studies were commissioned by OTA). Second, the report is not unexpected, given the political‐economic context in which drug prices have historically been discussed. © 1993 wiley‐Liss, Inc.
Mining Twitter Data for Improving Lexicon-Based Election Predictions and Candidate Analysis on Political Issues: Hybrid Topic-Based Sentiment Analysis with Issue Filtering

Twitter data mining techniques have been used in the run-up to elections to predict their outcomes and perform analysis to explain results. Due to the popularity of the social media platform it is possible to collect large amounts of data with which often lexicon-based sentiment analysis has been used to accomplish these tasks, mostly because of its efficiency and simplicity. More recently, hybrid techniques, which in addition to calculating tweet sentiment also incorporate topic modelling methods to extract the main “topics” from a corpus of text, have been applied independently for both election prediction and analysis. It is possible to use hybrid methods to analyse different political issues (e.g. economic, social, etc) and the public opinion for candidates in respect to them; and other hybrid methods have been shown to outperform baseline sentiment analysis approaches for election prediction. A mining solution which can accomplish both of these tasks non-exhaustively is desirable for better predictions and a greater understanding of election outcomes. This report will present a novel approach to mining Twitter data, Hybrid Topic-Based Sentiment Analysis with Issue Filtering (HTBSA*), which will not only pose as a potential improvement upon state-of-the-art techniques for election prediction; but can be abstracted to perform candidate analysis on any individual political issue, proposing a baseline methodology for doing this. This research approach has effectively outperformed all of the well-established methods in the realm of lexicon-based election prediction, giving a mean average error as low as 2.20% from true vote share. This technique was performed on data collected on the run up to the UK General Election 2019 and in an addition to this, it has successfully been black box tested on an unseen dataset. Based on the empirical evidence given by our results, HTBSA* can be relied upon to predict elections occurring in the future, but analysis results in respect to individual political issues may be inconsistent, suggesting further work is required. Lines of research that come as a result of this study have the potential to tackle election mining problems in new ways, which are more sophisticated than what has been done previously.
Molecular Characterization and Genetic Relatedness Among Pecan Cultivars Based on RAPD Markers

Understanding the genetic similarity of frequently used germplasm is vital to any breeding program attempting to increase the genetic diversity of new cultivars. An accurate knowledge of the origin and parentage of parental germplasm may also lead to a better understanding of the inheritance of important genetic traits. In many crops, this information is can be obtained by pedigree analysis. In pecan this is problematic because many cultivars were developed in the late 19 and early 20 centuries by nurserymen with sometimes inadequate record keeping and protection against cross pollination, resulting in many cultivars where only the maternal parent or neither parent has been established. In addition, most cultivars represent at most two generations of controlled crosses and many are seedling selections. Because of these limitations, it is often difficult to predict those crosses most likely to increase genetic diversity.
Convolution Neural Network based Fire Detection in Surveillance Videos

: Surveillance has many applications in Intrusion detection, theft detection, and event monitoring. During surveillance, many abnormal events can occur such as fire, accidents, and disasters. Among such abnormal events, fire is one of the most commonly happening events. This necessity the existence of effective fire alarming systems for surveillance. The existing flame detection systems rely on visible light from surveillance cameras. The existing methods can be categorized into three categories: pixel-level, blob-level, and patch-level methods. But overall these methods don’t work on small fires and color-based methods are sensitive to fire-colored objects, brightness, and shadows. As a result, the number of false warnings produced by these methods is high. In this paper, a Convolutional Neural Network based on a pre-trained GoogLeNet model which won the ImageNet Challenge in 2014, this model is trained on the mivia dataset of Fire and Not-Fire videos. The model is tweaked until maximum accuracy is achieved. This paper is focused on a solution to provide fire detection with existing infrastructure of CCTVs and surveillance systems.
Affect-sensitive Dialogue Response Generation for Positive Emotion Elicitation

An emotionally-competent computer agent could offer valuable assistance in various affective tasks. For example caring for the elderly, low-cost ubiquitous chat therapy, and providing emotional support in general. In this paper, we build an end-to-end chat-oriented dialogue system that can dynamically mimic affective human interactions by utilizing a hierarchical neural network architecture. End-to-end approaches have been reported to show promising results for non-goal oriented dialogue systems. However, application of this approach towards incorporating emotion in the dialogue is still very lacking. Our contributions in this paper are 1) a neuralnetwork based chat-oriented dialogue system that captures user’s emotional state and considers it in generating a dialogue response, trained to elicit positive emotion through the interaction, 2) a dialogue corpus that reflects a positive emotion elicitation strategy for model training to influence its affective tendency. This allows positive emotion elicitation without any elaborate dialogue strategy.
ANTIBACTERIAL ACTIVITY OF SILVER NANOPARTICLES BIOSYNTHESIZED BY OLIVE OIL

Silver nanoparticles (AgNPS) were synthesized using olive oil as reducing and stabilizing agent. AgNPS prepared in non-aqueous solution, where the start material was dissolved in acetone as a solvent and to be miscible with olive oil. After heating at 110 C, the color turned into brown colloidal. AgNPS characterized by UV–visible spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), atomic force microscopy (AFM), dynamic light scattering (DLS) and scanning electron microscopy (SEM). All techniques showed the formation of spherical AgNPS of metallic sliver in crystalline phase with narrow particle size distribution. Estimation of minimum inhibitory concentration of AgNPS and The antibacterial activity of Silver nanoparticles was evaluated by agar well diffusion method . Several kinds of bacteria were studied like Proteus mirabilis, Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Vibrio cholera, Vibrio paraheamolyticus, Klebsiella pneumonia, and Salmonella enteritidicus, where AgNPS showed broad spectrum antibacterial activity.
Hierarchical sphere-based DEM for simulating particles of arbitrary shape

Particle shape is a key factor which affects both the statics and dynamics of granular matter. Appreciating this, many methods have been proposed for simulating non-spherical particle shapes in discrete element method (DEM) simulations [1]. One of the most common, adopted in the popular commercial codes EDEM and PFC, is multi-sphere clumps. Although convenient because of its basis on simple spheres, a disadvantage of the multi-sphere approach is that many spheres may be required to approximate a real particle’s shape with reasonable fidelity [2] which can be computationally expensive. In this research, we introduce a hierarchy into the multi-sphere approach, with the aim of reducing the computational cost for simulating arbitrarily shaped particles at high resolution. The hierarchy consists of two levels. Firstly, large spheres are used to roughly approximate the particle’s shape. Secondly, each of these spheres contains a large number of points or small spheres, sufficient to give the required level of accuracy. The potential performance improvement comes from the fact that the detailed representation of the particle’s shape only becomes relevant at possible contact points. This hierarchical approach was implemented in LAMMPS [3] by adapting an existing body/nparticle pair style [4]. The efficiency of the implementation is compared with the multi-sphere approach without using the hierarchy for both dense cases with many, long-duration contacts and dilute cases with few, short-lived contacts. The optimal balance between the number of large spheres and the number of points within each large sphere is explored. Finally, the limitations of the current implementation are discussed and sources of performance improvement are suggested.
EGGS: Sparsity‐Specific Code Generation

Sparse matrix computations are among the most important computational patterns, commonly used in geometry processing, physical simulation, graph algorithms, and other situations where sparse data arises. In many cases, the structure of a sparse matrix is known a priori, but the values may change or depend on inputs to the algorithm. We propose a new methodology for compile‐time specialization of algorithms relying on mixing sparse and dense linear algebra operations, using an extension to the widely‐used open source Eigen package. In contrast to library approaches optimizing individual building blocks of a computation (such as sparse matrix product), we generate reusable sparsity‐specific implementations for a given algorithm, utilizing vector intrinsics and reducing unnecessary scanning through matrix structures. We demonstrate the effectiveness of our technique on a benchmark of artificial expressions to quantitatively evaluate the benefit of our approach over the state‐of‐the‐art library Intel MKL. To further demonstrate the practical applicability of our technique we show that our technique can improve performance, with minimal code changes, for mesh smoothing, mesh parametrization, volumetric deformation, optical flow, and computation of the Laplace operator.
Effects of Shear Flow on the Stability of Tokamak Plasmas

Tearing modes may be a major performance limiting player in tokamak magnetic confinement. The linear evolution of the classical tearing mode is investigated here with a numerical modelling single helicity reduced MHD code. Results are compared to the theoretical predictions for dispersion relations, the stabilizing effect of perfectly conducting walls at the boundaries, as well as the stabilizing effect of finite viscosity. Shear flow is found to have either stabilizing or destabilizing effect, depending on the ratio of rotation shear layer width to the current density layer width. Below a certain threshold ratio, which depends on the Prandtl number, shear flow is stabilizing and above that threshold, the opposite is observed. Furthermore, the stabilizing/destabilizing effect is much more notorious in the two limiting cases: inviscid and strongly viscous regimes. The results suggest that shear flow has a destabilizing effect in the outer layer and a stabilizing effect on the inner layer. Marginally stable modes fail to be destabilized in the presence of shear flow when shear is supposedly a destabilizing effect.
A VISUAL SURFACE DEFECT DETECTION METHOD BASED ON LOW RANK AND SPARSE REPRESENTATION

Surface defect detection is very crucial for product quality control. A visual detection method based on low rank and sparse representation for surface defect detection of the wind turbine blade is brought forward in this paper. Two terms, which are the Laplacian regularization term and the noise term, were added into robust principal component analysis (RPCA). The noise term deﬁned by F-norm is used to suppress un-even illumination and Gaussian noise, and the Laplacian regularization term is utilized to constrain the spatial relationship of superpixels. The defect image is considered to consist of a low rank matrix, a sparse matrix and a noise matrix, which corresponds with non-defect portion, defect portion and the noise portion of the image. At ﬁrst, the proposed method segments the input image into a number of non-overlapping superpixels and extracts their features. Then, the optimal salient map is generated via the proposed method. Finally, the binary image is obtained by Otsu method. By quantitative and qualitative evaluation, experimental results illustrate that the proposed method is superior in terms of robustness and accuracy compared with 10 state-of-the-art methods on the synthetic and real images.
The determinants of α-amylase pH–activity profiles

The glycosyl hydrolases present a large family of enzymes that are of great significance for industry. Consequently, there is considerable interest in engineering the enzymes in this family for optimal performance under a range of very diverse conditions. Until recently, tailoring glycosyl hydrolases for specific industrial processes mainly involved stability engineering, but lately there has also been considerable interest in engineering their pH-activity profiles. We mutated four neutral residues (N190, F290, N326 and Q360) in the chimeric Bacillus Ba2 alpha-amylase to both charged and neutral amino acids. The results show that the pH-activity profile of the Ba2 alpha-amylase can be changed by inserting charged residues close to the active site. The changes in the pH-activity profile for these neutral --> charged mutations do not, however, correlate with the predictions from calculations of the p K(a) values of the active site residues. More surprisingly, the neutral --> neutral mutations change the pH-activity profile as much as the neutral --> charged mutations. From these results, it is concluded that factors other than electrostatics, presumably the dynamic aspects of the active site, are important for the shape of the pH-activity profiles of the alpha-amylases.
Growth Promotion in Ayu (Plecoglossus altivelis) by Gene Transfer of the Rainbow Trout Growth Hormone Gene

method. Hatching and survival rates of ayu into which the gene was transferred were lower than those of the control, and about 10% of ayu were raised from 105 treated fertilized eggs. The persistence of transferred DNA was detected using polymerase chain reaction (PCR) with specific primers in genomic DNA from caudal fin tissue after 5 mo. PCR and restriction enzyme digestion analyses showed that the success of gene transfer was as high as 55%. Mosaic expressions of the transgene could be detected in gill, caudal fin, liver, brain, and muscle, but not in the heart. Two-fold growth enhancement in body weight and 1.3-fold in body length were measured. http://www.sinica. edu.tw/zool/zoolstud/41.3/303.pdf