Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of Psychiatric Comorbidity and Fear of Corona Virus in Patients with Obsessive Compulsive Disorder during Covid-19 Pandemic

Background and objective: The WHO declared the Chinese outbreak of COVID-19 to be health risk of National and International Concern from 30th January 2020. This has significant implications on mental health , especially for patients of OCD in various ways. This study was aimed to study Psychiatric comorbidity and Fear of Corona virus in patients with obsessive-compulsive disorder (OCD) during COVID-19 pandemic and compare socio-demographic & clinical variables between patients of OCD with or without psychiatric comorbidity during COVID-19 pandemic.Methods: In person interview including 96 old and new symptomatic patients of OCD diagnosed as per ICD 10-DCR, who had onset of illness prior to COVID-19 (march 2020), between the age of 18-60 years was conducted. The disease severity was recorded on D-YBOCS, HAM-A and HAM-D. The two groups of OCD, with comorbidity and without comorbidity were compared. Fear of COVID-19 Scale was used to analyse fear of corona virus.Results: Depression was the most common psychiatric comorbidity. The fear of coronavirus in 59.4% OCD patients was observed to be mild in severity and the mean FCV-19S score to be 14.42 ± 4.19. Positive correlation was found between FCV-19S score and the YBOCS obsession subtotal score, YBOCS compulsion subtotal score, YBOCS total score, HAM-D score and HAM-A score. FCV-19S score also had a statistically significant positive correlation with D-YBOCS severity score for contamination and cleaning, severity score for hoarding and collecting, severity score for symmetry and severity score for aggression. Among the OCD patients with comorbidity, a statistically significant higher YBOCS score, D-YBOCS severity score for Contamination and Cleaning and FCV-19S score were observed when compared to OCD patients without comorbidity.Conclusions: Fear of corona virus was seen in majority of the OCD patients and was associated with increased severity of disease. The OCD patients with comorbidity had significantly higher Y-BOCS score mainly for Contamination and Cleaning.
Deep Neural Networks in Power Systems: A Review

Identifying statistical trends for a wide range of practical power system applications, including sustainable energy forecasting, demand response, energy decomposition, and state estimation, is regarded as a significant task given the rapid expansion of power system measurements in terms of scale and complexity. In the last decade, deep learning has arisen as a new kind of artificial intelligence technique that expresses power grid datasets via an extensive hypothesis space, resulting in an outstanding performance in comparison with the majority of recent algorithms. This paper investigates the theoretical benefits of deep data representation in the study of power networks. We examine deep learning techniques described and deployed in a variety of supervised, unsupervised, and reinforcement learning scenarios. We explore different scenarios in which discriminative deep frameworks, such as Stacked Autoencoder networks and Convolution Networks, and generative deep architectures, including Deep Belief Networks and Variational Autoencoders, solve problems. This study’s empirical and theoretical evaluation of deep learning encourages long-term studies on improving this modern category of methods to accomplish substantial advancements in the future of electrical systems.
Research on identification of potential knowledge growth points in information science

The� scientific� system's� complexity� makes� it� impossible� to� solve� social� problems� by� a� single� discipline� independently,� and� interdisciplinary� knowledge� cooperation� and� innovation� become� an� indispensable� research� mode� of� modern� science. � Identifying� the� potential� interdisciplinary� knowledge�association�is�the�key�to�promoting�interdisciplinary�cooperation. �In�this�paper,�based� on�analyzing�the�growth�points�of�science,�"knowledge�growth�point"�is�defined�as�the�growth� point�of�science�that�produces�new�knowledge,�and�its�fundamental�attributes�and�evaluation� indexes� have� been� analyzed. � In� contrast,� the� "interdisciplinary� knowledge� growth� point"� is� defined� as� the� introduction� of� related� interdisciplinary� concepts,� theories,� techniques,� and� methods,� to� conduct� integrated� research� of� key� knowledge� points� of� active� disciplines,� to� generate� growth� point� of� innovative� knowledge,� and� analyze� its� related� research� status. � The� identification� of� "potential� interdisciplinary� knowledge� growth� points"� is� helpful� to� promote� knowledge� innovation. � Therefore,� it� is� intended� to� analyze� the� identification� methods� of� the� generation�of�key�knowledge�nodes�of�the�element�of�disciplines�and� interdisciplinary� related� knowledge,� and� explore� quantitative� and� qualitative� consultation� to� identify� potential� interdisciplinary�knowledge�growth�points. ���
A Comparative Analysis of Transfer Learning Architecture Performance on Convolutional Neural Network Models with Diverse Datasets

Deep learning is a branch of machine learning with many highly successful applications. One application of deep learning is image classification using the Convolutional Neural Network (CNN) algorithm. Large image data is required to classify images with CNN to obtain satisfactory training results. However, this can be overcome with transfer learning architectural models, even with small image data. With transfer learning, the success rate of a model is likely to be higher. Since there are many transfer learning architecture models, it is necessary to compare each model's performance results to find the best-performing architecture. In this study, we conducted three experiments on different datasets to train models with various transfer learning architectures. We then performed a comprehensive comparative analysis for each experiment. The result is that the DenseNet-121 architecture is the best transfer learning architecture model for various datasets.
Intraseasonal Variations of OLR in the Tropics During the FGGE Year

Analyse des donnees satellitaires sur le rayonnement ascendent de grande longueur d'onde (janvier-novembre 1979). L'analyse spectrale des donnees montre la presence de periodicites de 30-60 jours et 15-25 jours. Une confrontation avec l'activite cyclonique tropicale indique qu'elle survient durant la phase active des variations intrasaisonnieres
Improvement of selenium adsorption performance at high temperature by CaO/ZSM-5 composite sorbents

ABSTRACT Selenium in flue gas from coal combustion, released into the atmosphere, will affect the environment and human health greatly. The adsorption method can achieve good control of selenium emission, by using CaO as adsorbent, but CaO is easy to sinter at high temperature, resulting in the decrease of adsorption capacity. Therefore, thermostability ZSM-5 molecular sieve was added to prepare composite adsorbent to improve the adsorption performance for selenium at high temperature. CaO/ZSM-5 composite adsorbent was prepared by impregnation method, and its adsorption performance and mechanism were studied. The results show that the composite adsorbent shows stronger adsorption capacity at high temperatures. The mixing ratio has a great influence on the microstructure of the composite adsorbent influencing the adsorption capacity. When the ratio is 1:1, the adsorption efficiency of the composite adsorbent shows a good performance. At 900°C, the adsorption efficiency of Z1C1(ZSM-5/CaO = 1:1 wt%) can still maintain 67%, which is 32% higher than that of CaO. Si and Al in the composite adsorbent have different effects on the improvement of microstructure. The existence of Si is conducive to maintaining the stable skeleton of the composite adsorbent, improving anti-sintering, while the addition of Al tends to improve the porosity, furtherly ameliorating the structure of the composite adsorbent for high-temperature adsorption.
Maximum Wireless Power Transmission Using Real-Time Single Iteration Adaptive Impedance Matching

Wireless power transfer (WPT) systems’ efficiency is significantly impacted by non-monotonic variations in the coupling coefficient. For very short distances or strong-coupling cases, the WPT efficiency is minimal at the natural resonant frequency, with two peaks around this frequency, known as the frequency splitting phenomenon. On the other hand, WPT capability decreases for long distances or weak coupling cases. Therefore, adaptive matching is required for WPT systems with varying distances, like wireless charging systems for electric vehicles (EVs). This paper first presents a detailed analysis of the frequency splitting phenomenon by studying the root locations of the WPT system’s transfer function. Then, a real-time fixed-frequency adaptive impedance matching (IM) method is proposed, in which the amplitude and phase of the input impedance is estimated using the average active power, the average reactive power, and the amplitude of input voltage. Unlike traditional search-and-find techniques, the proposed method calculates the optimal IM network parameters only in a single iteration, which improves the convergent speed. A scaled-down 20-Watt prototype controlled by the TMSF2812 is fabricated and used to validate the effectiveness of the proposed method over a wide range of coil-to-coil distances.
Organic nitrogen fertilization minimizes requirement of inorganic fertilizers and improves growth and yield attributes of superior grapevines

Abstract Purpose: Nitrogen (N) fertilization is the essential nutrient element that limits crop yields before any other element. However, excessive use of N fertilization often leads to economic loss and quality deterioration of the yield. Materials: In the present study, superior grapevines were fertilized with chemical N fertilizer, chicken manure, or biofertilizer (Nitrobeine) over three seasons (2018, 2019, and 2020) to quantify N usage from different sources. Results: The current study’s findings show that N in the mineral form at 60% to 80%, organic and biofertilizers at 20% to 40% was very effective in improving all growth characteristics and yield when compared to using nitrogen completely in mineral form or reducing the percentages of mineral to 40%. Reducing the ratios of mineral nitrogen from 100% to 40% and at the same time increasing the proportions of organic and biofertilizers from 0.0 to 60% caused a gradual increase in the improved berry quality, raising in TSS, % reducing sugars, TSS/acid ratio and decreasing in total % acidity in berries. Conclusions: To improve the yield of Superior grapevines quantitatively and qualitatively with minimum chemical N, it is advisable to supply the vines with the suitable nitrogen (72.0 g N/vine/season) as mineral N (ammonium nitrate) at 60%, organic (chicken manure) at 20% and bio-fertilizers (nitrobeine) at 20%. Thus, replacing 40% of mineral fertilizers with organic and bio-fertilizers can be recommended for producing organic berries.
Ordinary Least Squares with Laboratory Calibrations: A Practical Way to Show Students that This Fitting Model may Easily Yield Biased Results When Used Indiscriminately

Analytical calibration using ordinary least squares (OLS) is the most widely applied response function for calibration in all type of laboratories. However, this calibration function is not always the most adequate and its indiscriminant use can lead to obtain biased estimates of unknowns. Students need to be taught about the practical requirements needed to obtain good results with OLS and when this fitting method is not accurate. Different experimental calibration curves were obtained in laboratory sessions using two common instrumental techniques: chromatography and atomic absorption spectrometry. After discussion seminars evaluating the data obtained by students, they were able to understand that linear fitting was not the most accurate model using atomic absorption spectrometry and a quadratic fitting provided most accurate estimates. Linearity was confirmed in chromatographic calibrations, but data presented heteroscedasticity, which is very common in calibrations done in chemical and biological analyses. A simple experiment was applied to show students how the use of the regression coefficients obtained by OLS with heteroscedastic data lead to highly biased estimates near the quantification limits of the calibration curve. The results obtained allowed to show students that, despite being widely used, OLS is not the most adequate fitting model to obtain accurate and precise results with many calibration methods routinely used in chemical and biological laboratories.
Analysis of microseismic events associated with hydraulic fracture propagation

v Chapter 1: Introduction . 1 1.1 Hydraulic Fracturing . 1 1.2 Assessment of Hydraulic Fracturing Treatment . 6 1.3 Research Goal . 9 1.4 Research Objectives . 9 1.5 Justification . 10 Chapter 2: Theoretical Microseismic Seismograms . 12 2.
A Multi-Parameter Dynamical Diagnostics for Upper Tropospheric and Lower Stratospheric Studies

Ozone trend estimates have shown large uncertainties in the upper troposphere/lower stratosphere (UTLS) region despite multi-decadal observations available from ground-based, balloon, aircraft, and satellite platforms. These uncertainties arise from large natural variability driven by dynamics (reﬂected in tropopause and jet variations) as well as the strength in constituent transport and mixing. Additionally, despite all the community efforts there is still a lack of representative high-quality global UTLS measurements to capture this variability. 5 The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity aims to reduce
Active learning: a case study of student engagement in college Calculus

ABSTRACT This paper presents a case study for strategic engagement of students in a Calculus course in order to produce increased learning in the classroom. Since it has been shown that active learning can promote greater comprehension for students in science, technology, engineering, and mathematics (STEM) courses, the researcher utilized many types of active learning techniques to enhance classroom instruction. The key components implemented are presented as a model of enhanced learning through developed classroom engagement. This course redesign model entitled, Strategic Engagement for Increased Learning (SEIL), has the potential to (1) contribute to the body of knowledge on ways to improve mathematics skills for college students, (2) identify successful teaching strategies and technologies that will promote the retention of STEM students, (3) increase the success rate of students taking Calculus, and (4) help produce more STEM graduates needed for the STEM workforce in the United States of America.
MODEL REGRESI LOGISTIK PADA FAKTOR-FAKTOR YANG MEMPENGARUHI IMUNISASI LENGKAP BALITA

Imunisasi merupakan upaya pemberian vaksin pada balita supaya balita terhindar dari penyakit infeksi berbahaya. Penelitian ini bertujuan mendapatkan model untuk mengetahui faktor yang paling berhubungan dengan kelengkapan imunisasi balita usia 1-26 bulan di wilayah Puskesmas Desa Kalanganyar. Analisis data menggunakan metode regresi logistik dengan bantuan software SPSS 16.0. Dari analisis yang menggunakan regresi logistik, diperoleh model : Y = -13,278 + 0,103 X 1 – 3,117 X 2 + 1,846 X 3 + 5,034 X 4 + 3,018 X 5 . Berdasarkan model yang diperoleh faktor-faktor yang mempengaruhi imunisasi lengkap balita adalah usia ibu, pekerjaan ibu, pendidikan ibu, pengetahuan ibu, peran kader posyandu. Dari kelima faktor tersebut yang paling mempengaruhi model tersebut adalah faktor pengetahuan ibu. Dari persamaan regresi logistik, maka peneliti mengambil sebuah contoh pada salah satu responden yang telah melengkapi imunisasi balita, maka diperoleh peluang seorang balita mendapatkan imunisasi lengkap balita sebesar 0,746.
Supercontinuum generation in photonic crystal fibres with core filled with toluene

A photonic crystal fibre with hollow core filled with toluene is considered as a new system for coherent supercontinuum generation. The dispersion characteristics are studied for various geometrical parameters of photonic crystal fibres. Two structures with lattice constant 2 μm, filling factors d/Λ 0.3 and 0.35 and toluene core of diameters of 3.34 and 3.23 μm have flat dispersion in the near infrared range. The structure with d/Λ = 0.3 has all-normal dispersion characteristics in whole near-infrared wavelength range, while the second structure (d/Λ = 0.35) has anomalous dispersion for wavelengths longer than 1.5 μm. Although confinement losses in the considered structures are as high as 0.4 dB cm−1, we show that the generation of coherent supercontinuum in the range 1.0–1.7 μm with the pulse energy conversion of 16% is feasible in 4 cm long fibre samples with standard fibre femtosecond lasers.
Modelling the climate change impacts on river discharge and inundation extent in the Magdalena River basin – Colombia

ABSTRACT Climate change may have significant impacts on water balance and may considerably influence flooding dynamics of river systems by increasing extreme precipitation. This study evaluates the potential effects of climate change on river discharge and inundation in the Magdalena River basin, the main river in Colombia, using the synergy between the MGB (Modelo de Grandes Bacias) hydrological–hydrodynamic model and downscaled Eta-regional climate model (RCM) projections based on four global climate models (GCMs): BESM (Brazilian Earth System Model), CanESM2 (Canadian Earth System Model), MIROC5 (Model for Interdisciplinary Research on Climate Version Five), and HadGEM2-ES (Hadley Centre Global Environment Model version 2). We used two different greenhouse gas scenarios (RCP4.5 and RCP8.5 (Representative Concentration Pathway)) for the “historical” (1986–2005) and “mid-term prospective” (2046–2065) periods. Model results for the “mid-term prospective” period under scenarios RCP4.5 and RCP8.5 indicate increase in mean river discharges in the east portion of the basin, decreased river discharges (mainly in the dry season) in the upper Magdalena basin, and increased inundation extent. By coupling hydrological–hydrodynamic and GCMs/RCMs models, modelling frameworks like the one used in this study provide an effective management tool for stakeholders interested in potential climate change impacts on tropical river basins.
Numerical modelling of open channel junctions using the Riemann problem approach

ABSTRACT The solution of an extended Riemann problem is used to provide the internal boundary conditions at a junction when simulating one-dimensional flow through an open channel network. The proposed approach, compared to classic junction models, does not require the tuning of semi-empirical coefficients and it is theoretically well-founded. The Riemann problem approach is validated using experimental data, two-dimensional model results and analytical solutions. In particular, a set of experimental data is used to test each model under subcritical steady flow conditions, and different channel junctions are considered, with both continuous and discontinuous bottom elevation. Moreover, the numerical results are compared with analytical solutions in a star network to test unsteady conditions. Satisfactory results are obtained for all the simulations, and particularly for Y-shaped networks and for cases involving variations in channels' bottom and width. By contrast, classic models suffer when geometrical channel effects are involved.
Creative Leadership Affecting Organizational Performance according to the Balanced Scorecard: A Case Study of Public Limited Companies in Bangkok, Thailand

This paper aims to analyze a relationship and the effect of creative leadership on organizational performance according to the Balanced Scorecard of Public Limited Companies in Bangkok. The samples used in this study were 370 participants who were administrators, general managers, department heads and employees working in Public Limited Companies located in Bangkok metropolitan areas. The research questionnaire was used as a tool to collect data. Statistics used in this study consisted of percentage, mean, standard deviation, Pearson Correlation and Multiple Regression Analysis (MRA). The research results indicated that creative leadership was positively related to organizational performance of Public Limited Companies in Bangkok. Creative leadership also had an effect on organizational performance of Public Limited Companies. The variable of creative leadership which had the highest effect on organizational performance was creativity (Beta = .528, p < .01), followed by vision (Beta = .524, p < .01), inspiration (Beta = .428, p < .01), problem solving (Beta = .178, p < .01), flexibility (Beta = .168, p < .01), and trustworthiness (Beta = .128, p <.05). Creativity is considered as the most important characteristic of organizational leaders; therefore, the company leaders should be encouraged to have creativity in order to create innovation, find new ways to solve problems and drive organization to achieve sustainable growth and development. In addition, this research provides detailed concepts, theories and new findings about creative leadership and organizational performance according to Balanced Scorecard, which can be used as references for further study.
Linear stability analysis of steady‐state tropical cyclones with single or double eyewalls

The structure of an eyewall within an intense tropical cyclone is known to influence its intensity strongly. Furthermore, intense tropical cyclones often undergo an eyewall replacement cycle, a process in which an outer eyewall forms, contracts and replaces an inner eyewall. During this process, two concentric eyewalls will exist. To examine the effects of such structures, analytical solutions of the transverse circulation equation associated with a balanced vortex model have been proposed in the literature. For a single eyewall, the analytical solution is defined over three regions–the eye, eyewall and far‐field–while in the case of concentric or double eyewalls one subdivides the domain into five regions–the eye, inner eyewall, moat, outer eyewall and far‐field. The goal of the present article is to present a stability analysis for steady‐state vortex solutions corresponding to tropical cyclones with either single or double eyewalls. We first obtain general steady‐state solutions and a general approach for the stability or instability of such states involving a perturbation analysis (which makes use of small perturbations to the vortex structure in each of the three or five regions). We then make several simplifying assumptions on the form of the stationary solutions, so as to make the stability analysis tractable while maintaining physical relevance. The stability criteria obtained depend on the model parameters as well as on the structure of the perturbations undergone by the steady‐state solutions. Making use of parameter values calibrated from the literature, we then provide bifurcation diagrams giving regions of stability or instability. Such analytical stability results for steady‐state vortex solutions of the transverse circulation equation complement existing numerical stability results in the literature.