Miracle-dz/UniFAR-FTUs huggingface dataset:
Leptin Level in Newly Diagnosed Iraqi Acromegaly Patients

Acromegaly is a serious endocrine disease resulting from an increase of growth hormone in the blood. Excessive growth hormone secretion may be caused by an adenoma of the pituitary. This study was designed to assess the effect of serum leptin concentration on acromegaly patients with both gender and its relation with some biochemical analysis. The study conducted 96 subjects (48 acromegaly patients and 48 controls) aged between (30-70) years who were attending the National Diabetic Center/ Al-Mustansirya University and AlYarmuk Teaching Hospital. Fasting blood sugar, lipid profile, growth hormone, insulin like growth factor-1, and serum leptin concentrations were measured for each individual. The results explained a significant increased in body mass index, triacylglycerol and low density lipoprotein cholesterol, (P<0.05) in acromegaly patients when compared with control group. Fasting blood sugar, serum growth hormone and serum insulin like growth factor-1 concentrations explained a highly significant increased, (P<0.01). While serum leptin concentration was significantly decreased. Fasting blood sugar, triacylglycerol, low density lipoprotein, serum growth hormone, serum insulin like growth factor-1, and serum leptin concentrations showed a significant increased in female patients when compared with male acromegaly patients, (P<0.05). This study showed that higher serum leptin levels with higher concentrations of triacylglycerol and low density lipoprotein cholesterol might play a vital function in the progress of acromegaly disease. Also, high serum leptin levels observed in female acromegaly patients when compared with male acromegaly patients, the present study suggested the role of leptin hormone as one of the biomarkers affecting in acromegaly patients.
Source Lithology and Magmatic Processes Recorded in the Mineral of Basalts from the Parece Vela Basin

Since the Early Cenozoic, the Philippine Sea Plate (PSP) has undergone a complex tectonic evolution. During this period the Parece Vela Basin (PVB) was formed by seafloor spreading in the back‐arc region of the proto‐Izu‐Bonin‐Mariana (IBM) arc. However, until now, studies of the geological, geophysical, and tectonic evolution of the PVB have been rare. In this study, we obtained in situ trace element and major element compositions of minerals in basalts collected from two sites in the southern part of the PVB. The results reveal that the basalts from site CJ09‐63 were likely formed via ∼10% partial melting of spinel‐garnet lherzolite, while the basalts from site CJ09‐64 were likely formed via 15%–25% partial melting of garnet lherzolite. The order of mineral crystallization for the basalts from site CJ09‐64 was olivine, spinel, clinopyroxene, and plagioclase, while the plagioclase in the basalts from site CJ09‐63 crystallized earlier than the clinopyroxene. Using a plagioclase‐liquid hygrometer and an olivine‐liquid oxybarometer, we determined that the basalts in this study have high H2O contents and oxygen fugacities, suggesting that the magma source of the Parece Vela basalts was affected by subduction components, which is consistent with the trace element composition of whole rock.
Emotional Functioning in the Context of Health Behaviors During the COVID-19 Pandemic in Health Sciences Students: The Polish Case

Purpose The fear for health, uncertainty, loss of freedom, boredom, and frustration accompanying the COVID-19 pandemic caused mental health burdens. Young people are particularly at a risk of emotional functioning problems. The aim of this manuscript was to verify the relationships between health behaviors and emotional functioning in health sciences students during the third wave of the COVID-19 pandemic in Poland. Patients and Methods The study group comprised 493 Polish health sciences students (314 women, 179 men) aged 21.5 ± 2.25 years. The intensity of health behaviors was examined using the Health Behavior Inventory (HBI). The Hospital Anxiety and Depression Scale (HADS) was carried out to assess symptoms of anxiety and depression. Stress levels were examined with the Perceived Stress Scale (PSS-10). The online versions of psychological scales were created using Google Forms software. Results Mild anxiety symptoms were observed in 21% of examined students and moderate-to-severe in 28%. Mild depressive symptoms were observed in 14% of the study group, and 8% of the examined students suffered from moderate-to-severe depression. The mean perceived stress result was high (22.2 ± 4.1 pts.). The overall intensity of health behavior was, at the mean level, significantly higher in females compared to males. The odds of developing severe symptoms in terms of anxiety, depression, and stress in students with high levels of health-related behaviors were respectively: four times, more than seven times, and nine times lower compared to students with lower levels of these behaviors. Conclusion Undertaking regular pro-health behavior decreased the odds of developing severe symptoms of anxiety, depression, and stress in health sciences students during the COVID-19 pandemic.
A Multiply Connected Belief Network approach for schedule risk analysis of metropolitan construction projects

ABSTRACT Metropolitan construction projects may be distinguished from other types of projects due to their specific nature. Issues with regard to purchase of property obstacles, a lack of accurate layout drawings for some underground facilities and, therefore, following probable changes in designs make it vital to have specific studies on risk analysis of such engineering projects. However, conventional methods offered in literature of risk analysis fail to consider the interactional mechanisms of risks and their simultaneous occurrence. This paper exploits the Multiply Connected Belief Network approach in MATLAB environment to analyse the simultaneous occurrence of risk factors on schedule delay of a highway project. The method of inference is through Junction Tree Algorithm due to existence of multiply connections in the developed network of the project. The findings for schedule delay were tested in a different space using Monte Carlo simulation and had satisfactory results.
Flight Planning and Procedures

The National Aeronautics and Space Administration (NASA) was founded in 1958 by President Eisenhower as a civilian lead United States federal agency designed to advance the science of space. Over the years, NASA has grown with a vision to "reach for new heights and reveal the unknown for the benefit of humankind" (About NASA). Mercury, Gemini, Apollo, Skylab, and Space Shuttle are just a few of the programs that NASA has led to advance our understanding of the universe. Each of the eleven main NASA space centers located across the United States plays a unique role in accomplishing that vision. Since 1961, Johnson Space Center (JSC) has led the effort for manned spaceflight missions. JSC has a mission to "provide and apply the preeminent capabilities to develop, operate, and integrate human exploration missions spanning commercial, academic, international, and US government partners" (Co-op Orientation). To do that, JSC is currently focused on two main programs, Orion and the International Space Station (ISS). Orion is the exploration vehicle that will take astronauts to Mars; a vessel comparable to the Apollo capsule. The International Space Station (ISS) is a space research facility designed to expand our knowledge of science in microgravity. The first piece of the ISS was launched in November of 1998 and has been in a continuous low earth orbit ever since. Recently, two sub-programs have been developed to resupply the ISS. The Commercial Cargo program is currently flying cargo and payloads to the ISS; the Commercial Crew program will begin flying astronauts to the ISS in a few years.
The Impact of Social Media-Based Collaborative Learning Environments on Students’ Use Outcomes in Higher Education

Abstract Social media has been increasingly utilized by many instructors and students for personal and educational use in higher education. Therefore, this study aims to examine whether and how utilization and usage of social media applications as instructional networking platforms affect use outcomes. This study proposes a research model for assessing the potential use outcomes of social media by conceptualizing three-dimensional factors that capture use outcomes, namely perceived satisfaction, perceived academic performance, and perceived impact on learning. The study collected survey data from 95 undergraduate students from a state college in Palestine reflecting their personal experience on using social media as an educational tool. Partial least square approach using structural equation modelling technique (PLS-SEM) was used for data analysis and research model testing. The results indicate that utilization and educational usage of social media have a positive impact on learning, enhance students’ perception of performance, and produce greater learning satisfaction. This study contributes to the growing body of literature by verifying the benefits of using social media as an educational tool and, in particular, Facebook groups created for educational purposes. Furthermore, this study offers insights into the predictive capabilities of PLS-SEM in the assessment of reflective-formative constructs of the higher-order model.
Assessing the Effects of the COVID-19 Pandemic on M-Commerce Adoption: An Adapted UTAUT2 Approach

The COVID-19 pandemic has impacted consumers’ lives and their shopping patterns, leading them towards mobile commerce. To address current shopping circumstances, an adapted UTAUT2 model aims to integrate trust and perceptions of the effects of the COVID-19 pandemic on consumers’ behavioral intention to rely on m-commerce during this period. The study proposes a research model which is investigated with the help of structural equation modelling in AMOS. Using the framework of a cross-sectional study, data were collected from an emerging market in Romania, where internet speed ranks 4th worldwide and where the yearly increase in internet and social media users is approximately 10%. By using confirmatory factor analysis and structural equation modelling, the research validates the applicability of UTAUT2 in examining consumers’ behavioral intent of using m-commerce during a pandemic. Hedonic motivation is the strongest predictor of consumers’ behavioral intentions to continue using m-commerce. The findings contribute to understandings of consumers’ behavior with m-commerce in an emerging market, extending knowledge based on the adapted UTAUT2 model and allowing for comprehension of the key role of trust and social influences in affecting consumers’ perceptions of the COVID-19 outbreak in relation to shopping patterns.
Comparison of Clinical Features and Outcomes between SARS-CoV-2 and Non-SARS-CoV-2 Respiratory Viruses Associated Acute Respiratory Distress Syndrome: Retrospective Analysis

Although a few studies comparing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and non-SARS-CoV-2 respiratory viruses have been reported, clinical features and outcomes comparing SARS-CoV-2 and non-SARS-CoV-2 respiratory viruses associated acute respiratory distress syndrome (ARDS) are still lacking. We retrospectively identified patients with SARS-CoV-2 (November 2020 to January 2022) and non-SARS-CoV-2 respiratory viruses associated ARDS (February 2015 to November 2020) at a single tertiary hospital. Their clinical data were obtained by medical record review. All viral infections were confirmed by RT-PCR. Thirty-one SARS-CoV-2 and seventy-one patients with non-SARS-CoV-2 respiratory viruses associated ARDS patients were identified. Influenza (62%) was the most common in non-SARS-CoV-2 respiratory viruses associated ARDS patients. Patients with SARS-CoV-2 were more likely to be female and had higher body mass index, lower clinical frailty, APACHE II, and SOFA score than those with non-SARS-CoV-2 respiratory viruses. All patients with SARS-CoV-2 were treated with corticosteroids and used more high-flow nasal oxygen than those with non-SARS-CoV-2 respiratory viruses. The concomitant respiratory bacterial infection was significantly higher in non-SARS-CoV-2 respiratory viruses than SARS-CoV-2. Although there were no significant differences in the 28-, 60-day, and in-hospital mortality rates between SARS-CoV-2 and non-SARS-CoV-2 respiratory viruses associated ARDS, the duration of mechanical ventilation and length of hospital stay were significantly longer in patients with SARS-CoV-2 than those with non-SARS-CoV-2 respiratory viruses. Although the severity of illness and the concomitant bacterial infection rate were lower in patients with SARS-CoV-2 associated ARDS, mortality rates did not differ from non-SARS-CoV-2 respiratory viruses associated ARDS.
Highly Fast Innovative Overcurrent Protection Scheme for Microgrid Using Metaheuristic Optimization Algorithms and Nonstandard Tripping Characteristics

The incorporation of renewable energy microgrids brings along several new protection coordination challenges due to the new and stochastic behaviour of power flow and fault currents distribution. An optimal coordination scheme is a potential solution to develop an efficient protection system to handle the microgrid protection challenges. In this paper, new optimal Over Current (OC) relays coordination schemes have been developed using nonstandard tripping characteristics for a power network connected to renewable energy resources. The International Electrotechnical Commission (IEC) microgrid and IEEE-9 bus systems have been used as benchmark networks to test and evaluate the coordination schemes. The proposed OC relays coordination approach delivers a fast and more reliable performance under different OC faults scenarios compared to traditional approaches. In addition, to improve and evaluate the performance of the proposed coordination approach, four modern and novel metaheuristic optimization algorithms are developed and employed to solve the OC relay coordination problem, namely: Modified Particle Swarm Optimization (MPSO), Teaching Learning (TL), Grey Wolf Optimizer (GWO) and Moth-Flame Optimization Algorithm (MFO). In this paper, the modern metaheuristic algorithms have been employed to handle the impact of renewable energy on the grid, and enhance the sensitivity and selectivity of the protection system. The test cases, consider the impact of integrating the different levels of renewable energy resources (with a capacity increment of 25% and 50%) in the microgrid on the OC relays protection performance by using nonstandard and standard tripping characteristics. In addition, a comparison analysis for the modern metaheuristic algorithms with Particle Swarm Optimization (PSO) algorithm as a common and standard technique in solving coordination problems under different fault scenarios considering also the higher impedance faults are introduced. The results in all cases showed that the proposed optimal nonstandard approach successfully reduced the overall tripping time and improve the performance of the protection system in terms of sensitivity and selectivity.
Lipopolysaccharide Modifies Sodium Current Kinetics through ROS and PKC Signalling in Induced Pluripotent Stem-Derived Cardiomyocytes from Brugada Syndrome Patient

Studies have suggested a connection between inflammation and arrhythmogenesis of Brugada syndrome (BrS). However, experimental studies regarding the roles of inflammation in the arrhythmogenesis of BrS and its underlying mechanism are still lacking. This study aimed to investigate the influence of inflammation on BrS-phenotype features using human-induced stem cell-derived cardiomyocytes (hiPSC-CMs) from a BrS-patient carrying an SCN10A variant (c.3749G > A). After LPS treatment, the peak sodium current decreased significantly in SCN10A-hiPSC-CMs, but not in healthy donor-hiPSC-CMs. LPS also changed sodium channel gating kinetics, including activation, inactivation, and recovery from inactivation. NAC (N-acetyl-l-cysteine), a blocker of ROS (reactive oxygen species), failed to affect the sodium current, but prevented the LPS-induced reduction of sodium channel currents and changes in gating kinetics, suggesting a contribution of ROS to the LPS effects. Hydrogen peroxide (H2O2), a main form of ROS in cells, mimicked the LPS effects on sodium channel currents and gating kinetics, implying that ROS might mediate LPS-effects on sodium channels. The effects of H2O2 could be attenuated by a PKC blocker chelerythrine, indicating that PKC is a downstream factor of ROS. This study demonstrated that LPS can exacerbate the loss-of-function of sodium channels in BrS cells. Inflammation may play an important role in the pathogenesis of BrS.
Comparative performance of different rice planting methods under Nagarjuna Sagar Project Left Canal Command Area (Sri Lal BahadurShastri Canal) of Nalgonda district

A field study was conducted at Agricultural Research Station, Kampasagar, Nalgonda district of Andhra Pradesh during the kharif season of 2008-09 to evaluate the different planting methods of rice under Nagarjuna Sagar Project Left Canal Command Area (Sri Lal Bahadur Shastri Canal) of Nalgonda district. The experiment was laid out in large plots with seven methods of establishment (Yangi eight row transplanter, semidry rice cultivation (sowing of dry seed behind small plough, sowing of dry seed with gorru and sowing of dry seed with national seed drill), system of rice intensification, puddled direct seeded rice and random transplanting (farmer practice). Out of which, sowing of dry seed behind the small plough recorded highest grain yield (6475 kg/ha) than other methods. Sowing of dry seed with national seed drill produced almost equal grain yield to that of sowing of dry seed behind small plough (6416 kg/ha). Transplanting with Yangi eight row transplanter recorded grain yield of 5600 kg/ha when compared to random transplanting (5250 kg/ha). The water productivity was higher in semi-dry rice sown behind small plough (5.39 kg/ha-mm) followed by semi-dry rice sown with national seed drill (5.03 kg/ha-mm). Highest gross and net returns were obtained in semi-dry rice sown behind small plough (Rs. 84175 and 62900) followed by semi-dry rice sowing with national seed drill (Rs. 83408 and 62058). Though higher investment for cultivation in Yangi eight row transplanter (Rs. 36950), higher gross returns were obtained (Rs. 72800) as compared to random transplanting (Rs. 68250).
ANALISIS PENGARUH FAKTOR PAJAK, INVESTMENT OPPORTUNITY SET (IOS), PROFITABILITY, DAN NON PERFORMING LOAN (NPL) TERHADAP TINGKAT UTANG PADA PERUSAHAAN PERBANKAN YANG TERDAFTAR DI BURSA EFEK INDONESIA

Studi ini bertujuan untuk menentukan pengaruh pajak (perusahaan tarif pajak dan non-debt pajak perisai ), investasi kesempatan set (IOS), profitabilitas yang meningkat non-performing pinjaman kredit bermasalah (NPL) pada tingkat utang (pengaruh). Penduduk dalam studi ini secara perbankan perusahaan yang terdaftar di bursa saham dan aktif sampai 2013. Contoh adalah 31 perbankan perusahaan dengan pengamatan sebanyak 28 laporan keuangan. Pengamatan dilakukan selama empat tahun, ie 2010-2013. Data yang digunakan adalah data sekunder, antara lain berasal dari laporan keuangan dari the banking company didaftarkan dan aktif pada bursa saham yang ditentukan melalui purposive sampel. Analisis data yang dilakukan dengan asumsi dan hipotesis pengujian klasik dengan beberapa regresi linier metode. Hasil studi ini menunjukkan bahwa faktor (perusahaan pajak tarif pajak dan non tarif pajak) pajak, kredit bermasalah (NPL) dan kesempatan investasi (IOS) tidak memiliki efek dalam tingkat utang (leverage) , sementara keuntungan tingkat dampak kenaikan utang ( leverage ). Kata Kunci: Perusahaan tarif pajak, non tariff pajak, kesempatan investasi (IOS) , profitabilitas, kredit bermasalah (NPL), kenaikan utang
Effects of Plasticity on Elevational Range Size and Species Richness

Elevational ranges within many taxa are greater in the north temperate region than the tropics. Two hypotheses to explain the pattern are, first, that large elevational ranges in the temperate region arise because species have evolved broad tolerance curves in response to seasonality and, second, that a low diversification rate in the temperate region (speciation minus extinction) has led to relatively few species, each of which occupies a large elevational range in the absence of competitors (character release). We build a quantitative genetic model of selection on a phenotypic trait, whereby increased tolerance is modeled as arising from plasticity in the trait. We show that broad tolerances result in evolution of large elevational ranges because they induce shallower genotypic clines and hence reduced maladaptive gene flow. The evolution of large elevational ranges results in relatively few competing species arranged along the elevational gradient at a species carrying capacity. In such saturated communities, species have much elevational overlap. In contrast, in similar-sized communities that could accommodate many more species, the resulting character release is associated with smaller elevational overlaps. Empirical assessment of these predictions should contribute to assessing any role for ecological limits in driving the latitudinal diversity gradient in species richness.
Comparison of transfer learning method for COVID-19 detection using convolution neural network

Currently, one of the most dangerous diseases is Coronavirus disease 2019 (COVID-19). COVID-19 is a threat to the whole world, and almost all countries are experiencing the COVID-19 pandemic, including Indonesia. Various ways to detect COVID-19 sufferers have been carried out, such as swab tests, rapid tests, and antigens. One way that can be done to detect COVID-19 infection is to look at X-ray images of the patient's lungs because someone infected with COVID-19 has a different lung shape from normal people. Many studies have been carried out to detect COVID-19, using either machine learning (ML) or deep learning (DL). In this study, we propose to use transfer learning as an extraction feature in the classification of the covid dataset. The study was conducted four times using four different methods, namely ResNet 50, MobileNet V2, Inception V3, and DensNet-201. After experimenting, we compared the results to find out which method has the best results in detecting COVID-19. From this research, it was found that the ResNet 50 model has the best results with 92.3% accuracy, 93% precision, 93% F1-Score, 99% sensitivity, and 90.7% specificity.
Pan-Sharpening via Deep Locally Linear Embedding Residual Network

The goal of pan-sharpening tasks is to fuse panchromatic (PAN) images and low spatial-resolution (LR) multi-spectral (MS) images for the purpose of aggregating texture and spectral information. Although traditional embedding-based pan-sharpening methods achieve competitive results, they are limited by the shallow network and not suitable for large-scale datasets. In this study, we design a novel multi-scale locally linear embedding residual network (LLERN) that consists of two phases: the spectral preservation phase and the structural preservation phase. As the pretreatment of the structural preservation network, the spectral preservation network aims to up-scale the LR MS image while retaining spectral information. The proposed locally linear embedding residual block (LLERB) in the structural preservation phase can search for similar sparse patches from the PAN image space and embed the corresponding local geometric relationship into the residual space to enhance the MS image. Extensive experiments suggest that the proposed LLERN outperforms state-of-the-art methods from visual and quantitative perspectives and confirm the assumption that LR image patches and residual image patches in a local region share a similar manifold structure which can be used to guide deep-learning modeling with improved interpretability. The source code is available at https://github.com/jiaming-wang/LLERN.