Miracle-dz/UniFAR-FTUs huggingface dataset:
FREQUENCY FEATURES OF THE NUMERICAL METHOD SAMPLING OF DIGITAL CONTROL SYSTEMS

Context. The studies of the frequency properties of the explicit multistep numerical integrators which use for sampling of continuous transfer function in the digital control systems, are conducted in this article. Numerical integrators in such systems implement as an integral parts of the digital regulators. Objective. The goal of this research is an analysis of the behavior of explicit numerical integrators of different orders, which areused to discretize continuous systems, in order to study their impact on the properties of the synthesized digital system. Method. Numerical methods of integration are considered as digital filters, the behavior of which is studied by the frequency characteristics method. To do this, the z-transform apparatus was used. Integrators’ discrete transfer functions were found for frequency analysis using the Control Systems Toolbox package of the mathematical application MATLAB. For further analysis, two closed feedback test structures were used: with integrators in the forward channel and in the feedback loop. Both variants of structures were studied by the frequency characteristics method for sampling using numerical integrators of 1st–6th orders. Results. The inefficiency of using high-order numerical integrators for continuous systems’ discretization is shown. Given the behavior of the frequency characteristics of test systems, the most rational is the use of low-order integrators, namely – the first and second orders. Establishing the cause of this phenomenon requires additional research, in particular, to identify the possible impact of additional zeros and poles of discrete transfer functions of the numerical integrators. Conclusions. The use of low-order integrators, namely the first and second orders, is the most rational for sampling of digital control systems and the inefficiency of using high-order numerical integrators to sample continuous systems is proven.
Indigestible cellulose and lignin in determining feces production and apparent digestibility in horses - doi: 10.4025/actascianimsci.v34i3.10577

Four crossbred geldings were used in a randomized blocks experimental design. The objective was to study the use of the internal markers indigestible cellulose (iCEL) and indigestible lignin (iLIG), obtained in situ (cattle) or in vivo (equine) to predict nutrient apparent digestibility in horses. Treatments consisted of different methodologies to determine digestibility: direct method with total feces collection (TC), and indirect method using internal markers iCEL and iLIG obtained either by in situ incubation in bovine rumen or in vivo (IV) using the mobile nylon bag (MNB) technique in horses. Feces production was 2.80 kg in DM, and average recovery rate (p > 0.05) was 101%. Nutrient digestibility coefficient (p > 0.05) estimates were adequately predicted by iCEL and iLIG, obtained in situ or in vivo, with average values of 52.63, 54.17, 64.90, 43.73 and 98.28% for dry matter, organic matter, crude protein, neutral detergent fiber and starch, respectively. It can be concluded that iCEL and iLIG may be obtained in vivo by MNB in horses consuming a forage-concentrate diet, to predict nutrient digestibility coefficients.
CUYASHE: Computação sobre dados cifrados em GPGPUs

Em tempos de computação em nuvem, há interesse em se utilizar criptossistemas que não apenas garantam a segurança dos dados no transporte e armazenamento, mas também durante o processamento, de forma a preservar a privacidade dos contratantes e detentores dos dados. Esquemas de cifração homomórfica são candidatos promissores para computação sobre dados cifrados, satisfazendo novos requisitos de segurança. Neste trabalho, é apresentada CUYASHE, uma implementação em GPGPUs do criptossistema completamente homomórfico em nível, YASHE. A implementação emprega a plataforma CUDA, o Teorema Chinês do Resto e a Transformada de Fourier para obter ganhos significativos de desempenho. Quando comparada com a implementação estado da arte em CPUs, foram obtidos ganhos de 20% de velocidade na adição e 58% na multiplicação homomórfica, operações críticas do ponto de vista de desempenho para se avaliar qualquer função sobre dados cifrados. Isso demonstra que GPGPUs são uma tecnologia adequada para se implementar serviços de computação em nuvem que preservam a privacidade.
Development of a Web Application for Historical Building Management through BIM Technology

Nowadays the built heritage has been recognized as one of the main sectors that can support the economic and sustainable development of countries. In the last years, the built heritage has been subject to several levels of interventions, being now clear its need for a proper maintenance and conservation management. However, in several cases, the maintenance faces lack of building records, which makes the maintenance a harsh, long, and expensive process. Therefore, there is an opportunity and need to apply new technologies, like Building Information Modelling (BIM), as supporting tool to the management of historical heritage. By so, the aim of this work was the development of a management system to be used as a supporting tool to the maintenance and conservation of the existent buildings, in historical context, facilitating to the interested parties the automated and digitized information needed to carry out the most varied tasks, with the particularity to be directly connected to the 3D-BIM model of the building. But in order to test the developed system (its applicability and functionality), it was in an early phase, applied to a pilot project with the significant heritage value. This work follows a development methodology applied to the case study and had different phases: (1) the case study was modelled in Autodesk Revit software, in whose model was inserted all the parametric information and associated metadata; (2) then, a support database of the management system was developed in Microsoft SQL Server, which will support all the information exported from the BIM model; (3) a web application was developed in C# through Visual Studio 2015, which works through and application programming interface (API) allowing the communication between the web application and the BIM model, allowing not only the interaction with the parametric information of this one, but also, a persistent access to a data management system (drawings, inspection reports, specifications, etc.) that has been created. The development of the management system and its application to the case study allows us to show its potential as a tool for the historical heritage management, contributing to its permanent and constantly updated management and cross off the fragmentation and loss of information therefore reducing the consequent investment in data collection.
Aalborg Universitet Heroes today-but what about tomorrow

Young high-growth firms, or gazelles, have been investigated predominantly with respect to their outstanding short-term performance. The paper at hand adopts a different approach by analyzing the long-term performance of such firms to shed light on the sustainability of these job-creating machines. Using the Danish Integrated Database for Labour Market Research, we find that former gazelles are not able to sustain their headstart in terms of performance in the long run. We demonstrate that gazelles are often outperformed by initially slower growing competitors, as high initial growth negatively affects a firm’s long-term survival. We also find that high-growth start-ups ultimately achieve lower employment growth and higher employee turnover. We explain these counterintuitive findings by arguing that an initial period of rapid employment growth impedes the emergence of a stable and efficient routine structure within the newly founded venture if expansion is undertaken too hastily. In turn, this impediment decreases these firms’ long-term performance, as the initial set of structures and routines or the lack thereof has a long-lasting effect on the organization’s development. Acknowledgments: This project was funded by the Danish Social Science Research Council at the Danish Agency for Science, Technology and Innovation. We are grateful for discussions with Michael S. Dahl, Olav Sorenson, Michael Hannan, Glenn Carroll, and seminar participants at the Stanford Graduate School of Business and Scandinavian Consortium for Organizational Research.
Estruturas Virtuais e Diferenciação de Vértices em Grafos de Dependência para Detecção de Malware Metamórfico

Este artigo apresenta uma metodologia de identificação de malware metamórfico baseada na comparação de grafos de dependência armazenados numa base de referência. Em função da diferenciação estrutural dos vértices e da adição de estruturas virtuais, a metodologia proposta é capaz de identificar e eliminar os elementos não relevantes do grafo de referência original, reduzindo o tamanho da base de referência e melhorando a variância nos resultados obtidos durante a comparação entre os grafos. Para validar isto, é apresentada a comparação dos resultados obtidos com aqueles gerados por uma metodologia de referência, na identificação dos malware metamórficos W32.Evol e W32.Polip.
Trajectory Tracking Control for Differential-Drive Mobile Robot by a Variable Parameter PID Controller

— Differential-drive mobile robots are most commonly used in industrial applications among wheeled mobile robots. Therefore, this paper presents a method to design a variable parameter PID controller for a differential-drive mobile robot following NURBS trajectory with a desired time-varying velocity. First, the robot's nonlinear kinematic error model is established, from which linearized around the desired angular velocity to obtain a linear error equation. Then, the variable parameter PID controller is designed to control the robot to follow the NURBS trajectory with minor error under the condition of time-varying velocity. The controller coefficients are selected through simulation and experiment to achieve the minor kinematic error. A platform robot is designed and built to demonstrate the proposed controller. Simulation and experimental results are presented to illustrate the effectiveness of the proposed controller. Therefore, it is possible to apply this result to control mobile robots in industrial applications.
Polygenic Scores of Alzheimer's Disease Risk Genes Add Only Modestly to APOE in Explaining Variation in Amyloid PET Burden.

BACKGROUND Brain accumulation of amyloid-β is a hallmark event in Alzheimer's disease (AD) whose underlying mechanisms are incompletely understood. Case-control genome-wide association studies have implicated numerous genetic variants in risk of clinically diagnosed AD dementia. OBJECTIVE To test for associations between case-control AD risk variants and amyloid PET burden in older adults, and to assess whether a polygenic measure encompassing these factors would account for a large proportion of the unexplained variance in amyloid PET levels in the wider population. METHODS We analyzed data from the Mayo Clinic Study of Aging (MCSA) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Global cortical amyloid PET burden was the primary outcome. The 38 gene variants from Wightman et al. (2021) were analyzed as predictors, with PRSice-2 used to assess the collective phenotypic variance explained. RESULTS Known AD risk variants in APOE, PICALM, CR1, and CLU were associated with amyloid PET levels. In aggregate, the AD risk variants were strongly associated with amyloid PET levels in the MCSA (p = 1.51×10-50) and ADNI (p = 3.21×10-64). However, in both cohorts the non-APOE variants uniquely contributed only modestly (MCSA = 2.1%, ADNI = 4.4%) to explaining variation in amyloid PET levels. CONCLUSION Additional case-control AD risk variants added only modestly to APOE in accounting for individual variation in amyloid PET burden, results which were consistent across independent cohorts with distinct recruitment strategies and subject characteristics. Our findings suggest that advancing precision medicine for dementia may require integration of strategies complementing case-control approaches, including biomarker-specific genetic associations, gene-by-environment interactions, and markers of disease progression and heterogeneity.
Feature Extraction and Intelligent Text Generation of Digital Music

Because the current network music operation mechanism is constantly improving and the matching of music platforms and users is poor, in this paper, the characteristics of digital music are analyzed, and the music features, rhythm, tune, intensity, and timbre with the MIDI format are extracted. Then, a music feature information extraction algorithm based on neural networks is proposed, and according to the extracted information of the music style, the B2T model is adopted for intelligent text generation. Finally, test results are given by the style matching rate and ROUGE value, which show that the model is accurate and effective for classification of music and description of related text, and the extraction of music feature information has a certain influence on its intelligent text generation.
Therapeutic Potential of a Vasopressin V2 Receptor Antagonist for Calcium Channel Blocker-Associated Edema with Vasospastic Angina

Calcium channel blocker- (CCB-) associated peripheral edema does not resolve without CCB discontinuation or dose reduction. However, renin–angiotensin system (RAS) inhibitors have been reported to be effective for CCB-associated edema. We report a case of vasospastic angina with refractory CCB-associated edema. A 78-year-old man had refractory edema induced by a CCB. It was successfully treated with tolvaptan, an active vasopressin V2 receptor antagonist. The aim of this case report is to understand the mechanism and treatment of CCB-associated peripheral edema and how tolvaptan affects peripheral edema.
A Sensor Fault Diagnosis Method for a Lithium-Ion Battery Pack in Electric Vehicles

In electric vehicles, a battery management system highly relies on the measured current, voltage, and temperature to accurately estimate state of charge (SOC) and state of health. Thus, the normal operation of current, voltage, and temperature sensors is of great importance to protect batteries from running outside their safe operating area. In this paper, a simple and effective model-based sensor fault diagnosis scheme is developed to detect and isolate the fault of a current or voltage sensor for a series-connected lithium-ion battery pack. The difference between the true SOC and estimated SOC of each cell in the pack is defined as a residual to determine the occurrence of the fault. The true SOC is calculated by the coulomb counting method and the estimated SOC is obtained by the recursive least squares and unscented Kalman filter joint estimation method. In addition, the difference between the capacity used in SOC estimation and the estimated capacity based on the ratio of the accumulated charge to the SOC difference at two nonadjacent sampling times can also be defined as a residual for fault diagnosis. The temperature sensor which is assumed to be fault-free is used to distinguish the fault of a current or voltage sensor from the fault of a battery cell. Then, the faulty current or voltage sensor can be isolated by comparing the residual and the predefined threshold of each cell in the pack. The experimental and simulation results validate the effectiveness of the proposed sensor fault diagnosis scheme.
Active event sport tourism experience: the role of the natural environment, safety and security in event business models

The connection between tourism development and the natural environment is more intense in outdoor sport tourism than in many other forms of tourism. Natural settings (space), sport activities undertaken and the motivations of the people who participate in them interact to create sport tourism experiences. Tourist safety and security are also proved to be important elements of a tourist experience and it seems that sport tourists may be more sensitive to safety issues than non-sport tourists. This paper therefore aims to analyse the importance of the natural environment and safety and security issues, as constitute event business model elements, in providing sport tourism experiences. The natural setting is also examined as a motivation to participate in sport tourism travel. On the basis of 464 questionnaires gathered from active participants of 16 small-scale sport events in four different outdoor sports, exploratory factor analysis was conducted on motivational statements and revealed a conceptually clear sevenfactor structure. One of them, titled ‘Nature’, was the second most important motivational dimension for participants but differences between particular sports were considerable. In terms of business model elements included in the survey, participants gave high importance to all elements related to the natural environment and safety and security. Scenic destination, scenic and interesting course, course safety and event safety were the most important elements of event business models for participants in all four sports. Environmental management and proper implementation of security and crowd control measures were also singled out as important event processes. However, results of ANOVA indicate statistically significant differences between the sports in seven out of nine business model elements. These findings shed some light on the managerial aspects of sport tourism practice, helping managers to better serve sports and tourism needs at a particular event and in the destination.
Analisis Sentimen Twitter Berbahasa Indonesia Terhadap Aplikasi PeduliLindungi dengan Algoritma SVM, KNN, dan Regresi Logistik

PeduliLindungi merupakan aplikasi mobile yang diluncurkan oleh KOMINFO, bekerjasama dengan Kementerian Kesehatan dan Kementerian Badan Usaha Milik Negara (BUMN) sesuai dengan Keputusan Menteri Komunikasi dan Informatika Nomor 171 Tahun Aplikasi PeduliLindungi dibuat untuk membantu pelacakan kasus COVID-19, di mana pengguna aplikasi ini berpartisispasi aktif membagikan data lokasi saat bepergian, sehingga dapat dilakukan pelacakan riwayat kontak dengan pasien positif COVID-19. Masyarakat Indonesia memiliki berbagai opini terhadap aplikasi PeduliLindungi, baik opini yang bersifat negatif maupun positif. Opini-opini mengenai aplikasi PeduliLindungi banyak disampaikan melalui media sosial Twitter, yang menjadi aplikasi dengan pengguna harian aktif terbanyak di Indonesia. Penelitian ini bertujuan untuk menganalis sentimen masyarakat Indonesia mengenai aplikasi PeduliLindungi dari data yang bersumber dari media sosial Twitter dan menentukan apakah sentimen masyarakat terhadap aplikasi ini bersifat negatif atau positif menggunakan algoritma SVM, KNN, dan Regresi Logistik. Data yang digunakan untuk analisis sentimen merupakan data Twitter berbahasa Indonesia, yang berkaitan dengan aplikasi PeduliLindungi. Data berjumlah 1000 baris diperoleh dari media sosial Twitter menggunakan kode akses Twitter API dari periode Oktober 2021 – November 2021. Berdasarkan analisis, didapatkan bahwa klasifikasi sentimen menggunakan algoritma Regresi Logistik dengan parameter C = 10 dan penalty = L2 menjadi model terbaik untuk klasifikasi data Twitter mengenai aplikasi Pedulilindungi. Didapatkan nilai matriks evaluasi untuk akurasi sebesar 81.5%, recall sebesar 96.6%, precision sebesar 81.5%, dan f-1 score sebesar 88.4%.
Value of Residential Investment in Photovoltaics and Batteries in Networks: A Techno-Economic Analysis

Australia has one of the highest rates of residential photovoltaics penetration in the world. The willingness of households to privately invest in energy infrastructure, and the maturing of battery technology, provides significant scope for more efficient energy networks. The purpose of this paper is to evaluate the scope for promoting distributed generation and storage from within existing network spending. In this paper, a techno-economic analysis is conducted to evaluate the economic impacts on networks of private investment in energy infrastructure. A highly granular probabilistic model of households within a test area was developed and an economic evaluation of both household and network sectors performed. Results of this paper show that PV only installations carry the greatest private return and, at current battery prices, the economics of combined PV and battery systems is marginal. However, when network benefits arising from reducing residential evening peaks, improved reliability, and losses avoided are considered, this can more than compensate for private economic losses. The main conclusion of this paper is that there is significant scope for network benefits in retrofitting existing housing stock through the incentivization of a policy of a more rapid adoption of distributed generation and residential battery storage.
MRI Radiogenomics in Precision Oncology: New Diagnosis and Treatment Method

Precision medicine for cancer affords a new way for the most accurate and effective treatment to each individual cancer. Given the high time-evolving intertumor and intratumor heterogeneity features of personal medicine, there are still several obstacles hindering its diagnosis and treatment in clinical practice regardless of extensive exploration on it over the past years. This paper is to investigate radiogenomics methods in the literature for precision medicine for cancer focusing on the heterogeneity analysis of tumors. Based on integrative analysis of multimodal (parametric) imaging and molecular data in bulk tumors, a comprehensive analysis and discussion involving the characterization of tumor heterogeneity in imaging and molecular expression are conducted. These investigations are intended to (i) fully excavate the multidimensional spatial, temporal, and semantic related information regarding high-dimensional breast magnetic resonance imaging data, with integration of the highly specific structured data of genomics and combination of the diagnosis and cognitive process of doctors, and (ii) establish a radiogenomics data representation model based on multidimensional consistency analysis with multilevel spatial-temporal correlations.
Near Future Projection of Indian Summer Monsoon Circulation under 1.5 °C and 2.0 °C Warming

The Indian summer monsoon’s (ISM) response to low (1.5 °C) and medium (2.0 °C) warming scenarios are examined during the period 2021–2050 using 11 member ensembles of the state-of-the-art Community Earth System Model, version 1 (CESM1-CAM5) datasets. We find that in the near-term period an increase in warming by 0.5 °C will strengthen the monsoon circulation and precipitation over the Indian landmass and east Asia. Under the 1.5 °C warming scenario, the ISM circulation will weaken, and precipitation will exhibit a decreasing trend, while the ISM precipitation and circulation will strengthen under the 2.0 °C warming scenario. The strengthening of ISM under the 2.0 °C warming scenario is due to the strengthening of the South China Sea (SCS) anticyclone and a high-pressure center near the Philippine Island. This high-pressure center over the SCS will facilitate a cross-basin strengthening of the easterly wind from the western Pacific Ocean/SCS to the equatorial Indian Ocean, which will, in turn, strengthen the transport of the Pacific-origin moisture to the Indian subcontinent and East Asia. This increase in moisture content over the Indian subcontinent will strengthen the monsoonal circulation and precipitation under the 2.0 °C warming scenario.