Miracle-dz/UniFAR-FTUs huggingface dataset:
Using topic modeling for communities clusterization in the VKontakte social network

—Topic modeling is one of the most widely used methods in text analysis. It can be used to select topics as well as to find the topics distributed in each document from the corpus. In this article, we present a method for clustering communities in the social network VKontakte (the most popular Russian social network) using topic modeling. As a communities sample a set of groups for which several students of Tomsk State University are subscribed was selected. There were about 7,000 of them in this set. The article describes the method by which the text corpus was formed, as well as mathematical modeling using two popular classical methods LDA and ARTM. A detailed description of these models, quality assessment criteria, and the main practical techniques used by the authors in training the models are given. The aggregated results of clustering communities by topic are also presented. There are also described a method for expert evaluation of community topics based on visualization of the words that make up the lexical core of the topic.
Data Driven Perspective on Stock Price - Macroeconomic Variables: Indonesia Economy 2016-2020

AbstractThe use of a theory-driven perspective is very common, especially in economics research, and even becomes an inevitable approach. Problems arise when data, as a form of reality, does not synergize with theory. The resulting conclusion is very likely to be different from the theoretical statement. One method that refers to data-driven is the Vector Auto-Regressive (VAR) model, which puts all the variables involved in a position as endogenous variables. This study seeks to identify a statistically more accurate relationship in the relationship between variables, stock prices, consumer price index, Jakarta Inter-Bank Over rate, exchange rate, and Net Balance Trade. Observations were made from January 2016 to December 2020. This study found evidence that there is a recursive relationship between stock price variables and macroeconomic variables. The VAR model identifies the Net Balance Trade variable as an endogenous variable in 3 types of sectoral stocks and only manufacturing sector stocks that resemble it. These results have two theoretical consequences: first, setting stock prices without differentiating sectors carries the risk of generalization errors. Second, setting stock prices as the endogenous variable means assuming that the market is perfect, and efficient and market participants have rational behavior.
An Automated Hyperparameter Tuning Recurrent Neural Network Model for Fruit Classification

Automated fruit classification is a stimulating problem in the fruit growing and retail industrial chain as it assists fruit growers and supermarket owners to recognize variety of fruits and the status of the container or stock to increase business profit and production efficacy. As a result, intelligent systems using machine learning and computer vision approaches were explored for ripeness grading, fruit defect categorization, and identification over the last few years. Recently, deep learning (DL) methods for classifying fruits led to promising performance that effectively extracts the feature and carries out an end-to-end image classification. This paper introduces an Automated Fruit Classification using Hyperparameter Optimized Deep Transfer Learning (AFC-HPODTL) model. The presented AFC-HPODTL model employs contrast enhancement as a pre-processing step which helps to enhance the quality of images. For feature extraction, the Adam optimizer with deep transfer learning-based DenseNet169 model is used in which the Adam optimizer fine-tunes the initial values of the DenseNet169 model. Moreover, a recurrent neural network (RNN) model is utilized for the identification and classification of fruits. At last, the Aquila optimization algorithm (AOA) is exploited for optimal hyperparameter tuning of the RNN model in such a way that the classification performance gets improved. The design of Adam optimizer and AOA-based hyperparameter optimizers for DenseNet and RNN models show the novelty of the work. The performance validation of the presented AFC-HPODTL model is carried out utilizing a benchmark dataset and the outcomes report the promising performance over its recent state-of-the-art approaches.
The temporality of on-street parking – exploring the role of land-use mix and change on parking dynamics

Parking is often overlooked by urban researchers even though parking consumes large proportions of a city’s physical footprint and imposes a significant impediment to more sustainable travel. Underpinning this lack of attention is suitable data and methods capable of capturing the complex dynamics of parking. Here we redress this gap by drawing on an emergent source of parking data and deploying empirical techniques to unpack this complexity. Data from 3542 on-street parking sensors observed over a 9-year period are used to delineate the first typology of parking routines before using a fixed-effects logistic regression model to explain how nearby land-use types and land-use mix shapes tempo and timing of parking utilisation. The benefit of our approach lies in its capacity to discriminate broad types of temporal rhythms associated with parking dynamics at particular places, how these change over time and how these rhythms are associated with different types and mixes of nearby land use. This knowledge is important to inform policies seeking to optimise the use of on-street parking and invoke more sustainable patterns of mobility.
CEO Career Horizon and Corporate Social Responsibility Assurance

ABSTRACT Framing on the premise of upper echelons theory, this study explores the relationship between a chief executive officer’s career horizon and corporate social responsibility assurance in an emerging market. Using a 9-year (2010–2018) unique sample of A-share listed firms in China, we found that the chief executive officer’s age is an important determinant of corporate social responsibility assurance and is significantly negatively associated with corporate social responsibility assurance, indicating that the chief executive officer’s age increase experienced a significant decline in corporate social responsibility assurance. These findings are consistent with our expectation that as CEOs grow older their rigidity increase with their age and this cause to decrease their interest to engage in corporate social responsibility assurance. Further, the negative relationship between the chief executive officer’s age and corporate social responsibility assurance is significantly positively moderated by both state-owned enterprises and heavily polluted firms. Our results contribute to the existing literature and have implications for potential policymakers.
An Optimized Structure for Enhancing Optical Absorption of Solar Energy in Elliptical GaAs Nanowire Array Solar Cell

The enhanced optical absorption of solar energy in a solar cell using nanostructured materials is a very demanding and important research area. Hence, an optimized structure to increase the optical absorption of solar energy in an elliptical GaAs (Gallium Arsenide) nanowire array solar cell was proposed in this paper. The influence of geometric parameters on the optical absorption of elliptical GaAs nanowire solar cells was investigated by exploiting the finite difference in time domain simulations. Based on the design and analysis, the elliptical GaAs nanowire array performed better than any circular GaAs nanowire. It was found that the enhanced performance was due to the reduced reflection from the top surface and a reduced transmission from the bottom surface of the elliptical GaAs nanowire array. The structural parameters of the elliptical GaAs nanowire were optimized by calculating the short circuit current density (Jsc) for different geometries over the solar spectrum. It was demonstrated that there was an increase of 9.4% in the Jsc compared with the circular GaAs nanowire under the optimized conditions.
The complete chloroplast genome sequence of Lithocarpus longinux (Fagaceae)

Abstract Lithocarpus longinux (Hu) Chun ex Y.C. Hsu & H.Wei Jen is a Critically Endangered tree distributed in Ma-li-po county in the Southeastern Yunnan Province China. Less than ten individuals have been found since the species was established 70 years ago. In this study, we assembled and annotated the complete chloroplast genome of L. longinux. The complete chloroplast genome of the species is 161,420 bp in length and has a GC content of 36.8%, including one large single-copy region (LSC, 90,409 bp), one small single-copy region (SSC, 19,255 bp), and two copies of inverted repeat regions (IRs, 25,878 bp). A total of 112 unique genes were detected, including 81 protein-coding genes, 29 tRNA genes, and 4 rRNA genes. Phylogenetic analysis of 31 representative chloroplast genomes of the Fagales suggests Lithocarpus is monophyletic with strong bootstrap support and that L. longinux is closely related to L. balansae.
SiamGauss: Siamese region proposal network with Gaussian head for visual object tracking

Abstract. We propose SiamGauss, a Siamese region proposal network with a Gaussian head for single-target visual object tracking for aerial benchmarks. Visual tracking in aerial videos faces unique challenges due to the large field of view resulting in small size objects, similar looking objects (confusers) in close proximity, occlusions, and fast motion due to simultaneous object and camera motion. In Siamese tracking, a cross-correlation ration is performed in the embedding space to obtain a similarity map of the target within a search frame, which is then used to localize the target. The proposed Gaussian head helps suppress the activation produced in the similarity map on confusers present in the search frame during training while boosting the confidence on the target. This activation suppression improves the confuser awareness of our tracker. In addition, improving the activation on the target helps maintain tracking consistency in fast motion. Our proposed Gaussian head is only applied during training and introduces no additional computational overhead during inference while tracking. Thus, SiamGauss achieves fast runtime performance. We evaluate our method on multiple aerial benchmarks showing that SiamGauss performs favorably with state-of-the-art trackers while rating at a frame rate of 96 frames per second.
The negative secondary transfer effect: Comparing proposed mediation theories

The secondary transfer effect proposes that contact with an outgroup impacts attitudes towards another, secondary outgroup. For positive contact, three pathways have been identified for the effect: attitude generalization, multiculturalism, and ingroup reappraisal (deprovincialization hypothesis, operationalized here as national pride). Research on negative secondary transfer effects is still scarce. Using data from a German nationally representative survey, we investigated negative secondary transfer effects from foreigners to refugees. The three pathways were compared while considering positive and refugee contact. Negative and positive secondary transfer effects both occurred (partially) mediated via attitude generalization and multiculturalism but not via national pride. We conclude there might be a risk of generalizing prejudice from unrelated negative experiences via these two mechanisms. Research on forced migration and intergroup contact should further explore them with the ultimate goal of preventing negative secondary transfer effects. Longitudinal or experimental research is needed to address causality, ideally involving various outgroups.
Case Report on the role of physiotherapy in improving the quality of life of a patient with Amyotrophic lateral sclerosis

The commonest type of motor neuron disease is ALS. Amyotrophic lateral sclerosis (ALS), which is also known as Lou Gehrig's disease, is a degenerative disease that affects the neurons and includes features of gradually increasing motor neurons degeneration that controls voluntary muscles functions. Early signs of ALS include gradual onset of stiffness of muscles, muscular spasms, progressive weakness, and muscle wasting. C9orf72 (chromosome 9 open reading frame 72) is the commonest gene that undergoes mutation in ALS, promoting the loss of motor neurons in multiple ways. This case is of a 47 years old male patient who presented with complaints of asthenia in the lower limb for 2 years, asthenia in the upper limbs for 1½ years, dyspnea for the last 5 months, and dysphasia, dysphagia, sialorrhea for the last 3 months. He underwent various interventions like MRI, CT scans, EMG (Electromyography), and NCV (Nerve Conduction Velocity). He was then diagnosed with Motor neuron disease after ruling out another probable diagnosis like upper and lower motor neuron disease, Syringomyelia. The disease-specific outcome measures for ALS are ALSFRS and ALSAQ-5. Physiotherapy treatment that is modulated according to the patient’s need plays a vital role in improving the quality of life and helps in delaying the worsening of symptoms henceforth helping in increasing the life span of the patients diagnosed with Amyotrophic Lateral Sclerosis. underwent a cervical spine MRI. On 21/04/2020, NCV and EMG were carried out: Motor nerve conduction showed slightly reduced Compound Motor action potential (CMAP) amplitude from the right ulnar nerve and right peroneal nerve. NEE (Needle examination) showed increased insertion activity with widespread fibrillation potentials, and positive waves from distal and proximal muscles of all four limbs, cervical, thoracic, and lumbosacral paraspinal mentalis. Long duration, high amplitude Motor unit action potentials (MUAPs) was seen with reduced recruitment pattern from proximal and distal muscles of upper and lower limbs bilaterally. The conclusion was widespread AHC lesion with active chronic denervation in muscles involving lumbosacral, thoracic, and cervical segments and so he was also diagnosed with an anterior horn cell lesion. On 26/12/2021, he underwent a few more investigations like a Brain MRI that had the impression of mild cerebral and cerebellar atrophy and screening of the whole spine that divulged findings of early degenerative spondylotic changes in the spine with marginal endplate osteophytes and desiccated intervertebral discs that displayed hypointense signal on T2 weighted images at all cervical and 2-3 lumbar level. Posterior disc bulge was noted at C3-4 to C5-6 levels indenting the thecal sac without overt compression of nerve root without notice of any compressive or non-compressive myelopathy. The posterior disc bulge was divulged at the L2-3 level without nerve roots compression (Figure 1).
FT-IR SPECTROSCOPIC APPROACH FOR THE QUANTITATIVE ANALYSIS OF FEW COMMERCIAL DRUGS IN BULK AND PHARMACEUTICAL FORMULATIONS

Simple, environment-friendly, rapid, accurate and cost effective Fourier Transform Infrared Spectroscopic (FT-IR) methods have been developed for the quantification of Bosentan (BSN), Desloratadine (DSD) and Flunarizine (FNZ) in bulk and marketed formulations. These drugs were estimated by several techniques and a new method has been developed by using FT-IR technique. The methods were developed on the basis of sample concentration influences the intensity of the vibrational bands and linearity is expected between concentration and optical density. The quantity of the drug present in commercial tablets with no interference of the excipients was estimated by applying this proposed method. This method has been validated in terms of LOD, LOQ, precision, accuracy, % RSD, robustness and ruggedness. A factor affecting the absorbance viz., concentration of drug is optimized. The presence of excipients has also been examined and found no significant effect. The calibration curves are found effective for the assessment of pure drug and pharmaceuticals. These curves also can be applied in bulk drug and pharmaceutical industries.
Journal Pre-proofs The Open-Access European Prevention of Alzheimer’s Dementia (EPAD)

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer’s Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features — i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features — Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER) , and Image Quality Rate (IQR) — were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.
Bedrohungsanalyse eines Smart-Home-Szenarios zur Visualisierung von Energieverbrauchsdaten im Vorfeld einer Steuerentscheidung

Die Integration von vernetzter Sensorik, Gebaudeautomationstechnik und fernsteuerbaren Haushaltsgeraten zu einem intelligenten Haushalt (Smart-Home), welches seinerseits in einem Smart-Grid vernetzt ist, ermoglicht vielfaltige Ansatze zur intelligenteren Nutzung von verfugbaren Energieressourcen und Steigerung des Wohnkomforts. Diese verteilten IT-Systeme eroffnen neue Angriffsmoglichkeiten auf Privathaushalte und mussen besonders sicher und privatspharengerecht konzipiert sein. In diesem Dokument untersucht daher die KASTEL-Arbeitsgruppe „Intelligente Infrastrukturen und Energie“ Bedrohungen auf die IT-Sicherheit einer Smart-Home-Architektur.
Operational flexibility in hospitals: Scale development and validation

The purpose of this paper is to develop and validate an operational flexibility construct that can serve as a general theory in operations management in the context of the hospital industry. The effects of management capability and competitive intensity on operational flexibility and performance relationships are also explored. We used data collected from a sample of 152 administrators of hospitals in the mid-west region of the USA and performed a systematic series of analyses. Following the transformation model, grounded in the fundamental and powerful concept of operations management, we develop a psychometrically validated, 11-item, three-dimensional (input, process, output) scale of operational flexibility (OF) construct for the hospital industry. As the degree of operational flexibility allowed in any transformation system is influenced by management capability, it is established as a complementary mediator in strengthening the OF-performance relationship in the presence of competitive intensity (i.e. moderator). The paper concludes with limitations and directions for future research.
A Compact Wideband Circularly Polarized Crossed-Dipole Antenna with Broad Beamwidth

In this paper, a compact wideband circularly polarized (CP) crossed-dipole antenna with wide half-power beamwidth (HPBW) and broad 3 dB axial ratio beamwidth (ARBW) is proposed. The antenna is composed of crossed bowtie dipoles, four pentagonal parasitic elements and eight vertical metallic plates. A double vacant-quarter printed ring with orthogonal bowtie dipoles is designed for CP radiation and broadband characteristics of impedance and 3 dB axial ratio (AR) bandwidths. Parasitic elements and vertical metallic plates are utilized to increase bandwidth and broaden beamwidth further. The total size of the proposed antenna is 0. 4λ× 0. 4λ× 0. 16λ. Simulated results are in good agreement with the measured ones which demonstrate an impedance bandwidth 88.4% and a 3 dB AR bandwidth 73.1% The HPBW of more than 120◦ is 70.0%. The 3 dB ARBWs of more than 120◦ in E-plane and H-plane are 63.1% and 37.5%, respectively. With both the excellent CP performance and compact size, the proposed antenna is attractive for modern wireless communications.
Semi-Automatic Task Planning of Virtual Humans in Digital Factory Settings

Introduction: Digital factory planning and digital commissioning are important tools for process and production planning. Their main objective is to minimize costs by optimizing the factory layout in terms of process time and material ow. The focus of these planning methods recently has changed from the simulation of machine and material movements to a human factor oriented viewpoint especially considering an aging workforce. In this process ergonomic methods are used for the evaluation and the identi cation of potential problem areas. At the moment, production simulations involving digital humans are mainly used in major enterprises, operating in the automotive and engineering sector. The high operational costs of available software systems, e.g. for necessary sta training, in combination with the enormous expenditure of time for creating a simulation, are substantial shortcomings which make this approach nearly inaccessible for small and medium-sized companies [9] [5]. To improve the usability of digital humans in simulations, methods are needed that avoid the time consuming process of manual programming by automatically creating work plans, actions and movements for digital humans. In this paper we present a software system The Smart Virtual Worker (SVW) [6] that has been developed as an experimental platform to demonstrate the feasibility of such an approach. The SVW is capable of performing ve di erent types of elementary actions (walkto, transport, align, assemble and disassemble) and for any particular action that is performed our software calculates ergonometric scores based on Method Time Measurement (MTM, [3]) and Rapid Upper Limb Assessment (RULA, [4]) for their evaluation. An Autodesk® Inventor® plugin [1] to our system is used to create a realistic virtual environment for the SVW. A task description for the SVW can either be imported with this plugin or created with the GUI of our software. Tasks for the SVW are internally represented as objectives. This means that any task is de ned by criteria that must be met (the terminal objectives), rather than a speci c action sequence to reach it. The actions to achieve the terminal objectives are generated by the planning algorithm that intends to minimize an objective function speci ed as a convex combination of the MTM and RULA scores of the movements of the virtual worker. The user can in uence the optimization by providing the weights to the convex combination. The task of nding optimal action sequences can be modeled as a shortest path problem in an abstract state space. However, the state space is fairly large and unstructured (to keep generality and extensibility)