Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALISIS KINERJA KEUANGAN PEMERINTAH DAERAH SE-PROVINSI JAWA TENGAH SEBELUM DAN SAAT PANDEMI COVID19

Penelitian ini bertujuan untuk menganalis perbedaan rasio kemandirian keuangan, fleksibilitas keuangan, solvabilitas operasional, solvabilitas jangka pendek, solvabilitas jangka panjang, dan solvabilitas layanan pemerintah daerah se-Provinsi Jawa Tengah Sebelum dan Saat Pandemi Covid19. Dalam penelitian ini, terdapat 35 Pemerintah Kabupaten dan Kota di Provinsi Jawa Tengah yang menjadi sampel penelitian dengan menggunakan teknik pengambilan sampel sensus atau sampel jenuh. Alat analisis yang digunakan dalam penelitian ini adalah Uji Beda. Hasil penelitian ini menunjukkan bahwa terdapat perbedaan rata-rata rasio kemandirian keuangan dan solvabilitas operasional Pemerintah Daerah Kabupaten dan Kota di Provinsi Jawa Tengah sebelum dan saat pandemi Covid19. Sedangkan untuk rasio fleksibilitas keuangan, solvabilitas jangka pendek, solvabilitas jangka panjang dan solvabilitas layanan tidak terdapat perbedaan rata-rata sebelum dan saat pandemi Covid19. Kata Kunci: Kemandirian Keuangan, Fleksibilitas Keuangan, Solvabilitas Operasional, Solvabilitas Jangka Pendek, Solvabilitas Jangka Panjang, Solvabilitas Layanan, Kinerja Keuangan Daerah, Pandemi COVID19, Jawa Tengah.
An investigation of English student-teachers’ constraints during teaching internship program

The teaching internship is designed to smooth the transition from teacher to student. At the same time the teaching internship assignment gives the teachers training institutions an opportunity to evaluate the students teaching capabilities. It is one of the most important components of the teacher training program. It is an opportunity for student teachers to put their theoretical studies into practice. The objective of this study is to investigate the constraints faced by student teachers during teaching internship program. The qualitative method was employed in this study. The study involved 26 students who participated in the teaching internship program in 2016/2017 session, Faculty of Teacher Training and Education, University of Syiah Kuala. Covenience sampling technique was used to select the sample. The instruments used to collect data was questionnaire. The data collected was analyzed by using Miles and Huberman’s qualitative data analysis. Based on the questionnaire the result showed that there were fourteen constraints faced by student teachers during teaching internship program. The constraints were mainly in the domains of personal, class participation, class management, instructional, emotional, adjusting to students, and supervision. As teaching practice is an important component of teachers training program, considerable attention must be given to make it more effective and fruitful. Therefore, this study suggests that the cooperation of the faculty and schools in terms of supervision need to be improved in order to optimize the outcome of the program.
Assimilation of Images via Dictionary Learning-Based Sparsity Regularization Strategy: An Application for Retrieving Fluid Flows

In this work, we propose a structure sparsity regularization strategy in the framework of 4-D variational data assimilation (4-D Var). In meteorology and oceanography, the number of unknown model variables is far fewer than that of image observations, often leading to solve an underdetermined nonlinear inverse problem. In recent years, the $\ell ^{1}$ -norm-based sparsity regularization approach has attracted great attention in the field of 4-D Var because of its data structure preservation and noise suppression. To avoid little underlying physical priors considered, we introduce a widely used dictionary learning (DL) method to adaptively derive an efficient sparse approximation via learning a basis from a given dataset. For our target application of estimating sea surface flows, we consider a DL sparsity constraint on the variable of flow vorticity due to its rich spatial variation related to flows evolution. A novel anisotropic regularization method combined with fluid dynamics characteristics could overcome magnitude underestimation and staircase artifacts appearing in the gradient regularization-based 4-D Var method. The split Bregman iteration with fast convergence property is employed to solve the $\ell ^{1}+\ell ^{2}$ nonsmooth minimization problem. The promising fluid flows estimation performance in real test cases (assimilation of image sequences collected from CORIOLIS experimental turntable) demonstrates the efficiency of our approach.
‘Just like breathing’: A portrait of an 85-year-old veteran teacher

ABSTRACT Through a phenomenological lens of portraiture methodology, this article explores the career experiences of a veteran acting teacher who, at the age of 85 years, remains highly passionate and dedicated to his work with younger aspiring actors. The article reveals how for this veteran teacher, his strong teacher identity characterised by a quest for challenge and a commitment to career-long professional development are significant to maintaining relevance and passion for teaching. As many countries grapple with issues surrounding the retention of veteran teachers, understanding the ways in which he maintains his passion and commitment over succumbing to stress and burn out like so many teachers in the performing arts is timely.
Biomass Production of Microalgae using Agricultural and Industrial Wastewater

Growing wastewater microalgae contributes to the elimination of nutrients and pollutants present in wastewater because they need N and P for the synthesis of proteins, nucleic acid, and phospholipids. The most sustainable approach for achieving high biomass and high lipid build-up, along with environmental protection. In the current research, nine microalgae were cultivated on two variations of wastewater (agricultural and industrial dyes wastewater) and compared to the synthetic medium. The results indicated that after three weeks of the incubation period, the ability of microalgae to grow in sterilized synthetic medium and wastewater and gave greater biomass and chlorophyll (a) than in non-sterilized ones. Out of the tested nine microalgae, four microalgae (Nostoc muscorum, Anabeana oryzae, Spirulina platensis and Anabeana fertilissima) were selected which gave the highest significant values of dry weight, biomass productivity and chlorophyll (a) content. The selected microalgae showed the highest significant values of the chemical composition, i.e. total carbohydrate, protein and lipid when cultivated in agricultural wastewater more than those cultivated in both industrial dyes wastewater and synthetic broth medium. Among four microalgae, two microalgae of A. oryzae HSSASE6 (KT277789), and S. platensis NIES-39 (A00800) were chosen where the chemical composition contents ranged from 1.17 to 1.21-fold and 1.03 to 1.06-fold of carbohydrate, 1.06 to 1.09-fold and 1.88 to 1.93-fold of protein and 1.41 to 1.52-fold and 1.76 to 1.90-fold of lipid more than those of other microalgae, respectively. The agriculture wastewater was inoculated with a single culture of A. oryzae HSSASE6 (KT277789) or S. platensis NIES-39 (A00800) individually with 10 % of inoculum size, which more preferred than was inoculated with consortia culture. Results also showed that A. oryzae HSSASE6 (KT277789) was more efficient strain for giving biomass and productivity in agricultural wastewater than S. platensis NIES-39 (A00800) (about 28% more ).
Model-Robust Inference for Clinical Trials that Improve Precision by Stratified Randomization and Covariate Adjustment

Abstract Two commonly used methods for improving precision and power in clinical trials are stratified randomization and covariate adjustment. However, many trials do not fully capitalize on the combined precision gains from these two methods, which can lead to wasted resources in terms of sample size and trial duration. We derive consistency and asymptotic normality of model-robust estimators that combine these two methods, and show that these estimators can lead to substantial gains in precision and power. Our theorems cover a class of estimators that handle continuous, binary, and time-to-event outcomes; missing outcomes under the missing at random assumption are handled as well. For each estimator, we give a formula for a consistent variance estimator that is model-robust and that fully captures variance reductions from stratified randomization and covariate adjustment. Also, we give the first proof (to the best of our knowledge) of consistency and asymptotic normality of the Kaplan–Meier estimator under stratified randomization, and we derive its asymptotic variance. The above results also hold for the biased-coin covariate-adaptive design. We demonstrate our results using data from three trials of substance use disorder treatments, where the variance reduction due to stratified randomization and covariate adjustment ranges from 1% to 36%. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
A life-threatening reverse Takotsubo syndrome in a young breastfeeding woman: a case report

Abstract Background Takotsubo syndrome (TTS) is characterized by transient left ventricular (LV) dysfunction and is usually triggered by emotional, physical, or combined stress. This syndrome has been increasingly recognized, although it remains a challenging and often misdiagnosed disorder. Case summary A 36-year-old breastfeeding woman was admitted with sudden dyspnoea and oppressive chest pain. On admission, she was lethargic, hypotensive, and tachycardic. The electrocardiogram showed rapid atrial fibrillation and diffuse ST-segment depression. The transthoracic echocardiogram (TTE) revealed severe LV systolic dysfunction, with midventricular and basal akinesis, compensatory apical hyperkinesia, and without intraventricular gradient. Emergent coronary angiogram showed normal coronary arteries. A presumptive diagnosis of reverse TTS with cardiogenic shock (CS) was made. The patient was transferred to the intensive care unit after intubation and inotropic and vasopressor support was initiated. During hospitalization, rapid clinical improvement was observed. In 3 days, the patient was weaned from haemodynamic support and extubated. Furthermore, β-blocker and angiotensin receptor blocker were initiated and tolerated. Cabergoline was also administered to inhibit lactation. The presumptive diagnosis was further strengthened by cardiac magnetic resonance and all triggering factors were excluded. At hospital discharge she was asymptomatic and the follow-up TTE was normal, which confirmed the diagnosis of reverse TTS. Discussion We present a case of a young woman, 8 months after delivery, which developed a life-threatening reverse TTS without triggering factor identified. Reverse TTS is a rare variant of TTS with different clinical features and is more likely to be complicated by pulmonary oedema and CS.
Cognitive reserve as a moderator of outcomes in five clusters of first episode psychosis patients: a 10-year follow-up study of the PAFIP cohort

Abstract Background Cognitive reserve (CR) has been associated with the development and prognosis of psychosis. Different proxies have been used to estimate CR among individuals. A composite score of these proxies could elucidate the role of CR at illness onset on the variability of clinical and neurocognitive outcomes. Methods Premorbid intelligence quotient (IQ), years of education and premorbid adjustment were explored as proxies of CR in a large sample (N = 424) of first-episode psychosis (FEP) non-affective patients. Clusters of patients were identified and compared based on premorbid, clinical and neurocognitive variables at baseline. Additionally, the clusters were compared at 3-year (N = 362) and 10-year (N = 150) follow-ups. Results The FEP patients were grouped into five CR clusters: C1 (low premorbid IQ, low education and poor premorbid) 14%; C2 (low premorbid IQ, low education and good premorbid adjustment) 29%; C3 (normal premorbid IQ, low education and poor premorbid adjustment) 17%; C4 (normal premorbid IQ, medium education and good premorbid adjustment) 25%; and C5 (normal premorbid IQ, higher education and good premorbid adjustment) 15%. In general, positive and negative symptoms were more severe in the FEP patients with the lowest CR at baseline and follow-up assessments, while those with high CR presented and maintained higher levels of cognitive functioning. Conclusions CR could be considered a key factor at illness onset and a moderator of outcomes in FEP patients. A high CR could function as a protective factor against cognitive impairment and severe symptomatology. Clinical interventions focused on increasing CR and documenting long-term benefits are interesting and desirable.
Appraising the Impact of Pressure Control on Leakage Flow in Water Distribution Networks

Water losses in Water Distribution Networks (WDNs) are inevitable. This is due to joints interconnections, ageing infrastructure and excessive pressure at lower demand. Pressure control has been showing promising results as a means of minimising water loss. Furthermore, it has been shown that pressure information at critical nodes is often adequate to ensure effective control in the system. In this work, a greedy algorithm for the identification of critical nodes is presented. An emulator for the WDN solution is put forward and used to simulate the dynamics of the WDN. A model-free control scheme based on reinforcement learning is used to interact with the proposed emulator to determine optimal pressure reducing valve settings based on the pressure information from the critical node. Results show that flows through the pipes and nodal pressure heads can be reduced using this scheme. The reduction in flows and nodal pressure leads to reduced leakage flows from the system. Moreover, the control scheme used in this work relies on the current operation of the system, unlike traditional machine learning methods that require prior knowledge about the system.
Pindrop Labs' Submission to the ASVspoof 2021 Challenge

Voice spooﬁng has become a great threat to automatic speaker veriﬁcation (ASV) systems due to the rapid development of the speech synthesis and voice conversion techniques. How to effectively detect these attacks has become a crucial need to those systems. The ASVspoof 2021 challenge provides a unique opportunity to foster the development and evaluation of new techniques to detect logical access (LA), physical access (PA) and Deepfake (DF) attacks covering a wide range of techniques and audio conditions. The Pindrop Lab participated to both the LA and DF detection tracks. Our submissions to the challenge consist of a cascade of an embedding extractor and a backend classiﬁer. Instead of focusing on an extensive feature engineering and complex score fusion methods, we focus on improving the generalization of the embedding extractor model and the backend classiﬁer model. We use log ﬁlter banks as the acoustic features in all our systems. Different pooling meth-ods and loss functions are studied in this work. Additionally, we investigated the effectiveness of stochastic weight averaging, further improved the robustness of the spooﬁng detection system. Overall, three different variants of the same system have been submitted to the challenge. They all achieved a very competitive performance on both LA and DF tracks, and their combination achieved a min-tDCF of 0.2608 on the LA track and an EER of 16.05% on the DF track.
Drought Impact on Carbon Assimilation of A Zelkova Serrata Plantation

Background: As anthropogenic greenhouse gas emissions intensify global climate change, plantations have become an important tool to mitigate atmospheric CO2. Our aim in this study was to estimate carbon assimilation and clarify the impact of environmental factors on the photosynthesis of Zelkova serrata, an important plantation species, which extensively planted in low altitude of East Asia.Results: We measured monthly gas exchange parameters and leaf area to estimate carbon assimilation. The results showed that gas exchange was significantly affected by vapor pressure deficit and temperature, especially in the dry season, and both photosynthetic rate and carbon assimilation decreased. However, drought led to lower daytime assimilation and higher night-time respiration, which caused a 43% decrease in carbon assimilation. Additionally, the poor site quality and environmental stress may impact the growth and carbon assimilation of this species.Conclusions: Z. serrata may not be suitable for planting in a tropical monsoon climate area. Therefore, the effects of extreme weather on the forest carbon budget may be stronger in the future. Leaf area showed seasonal variation and serious defoliation caused by a typhoon in the summer. The monthly leaf assimilation rate was 0.88–4.17 μmol CO2 m-2 s-1, which was estimated to assimilate 3.50 Mg C ha-1 yr-1 in the study area.
Revealing the Correlation between Altered Skin Lipids Composition and Skin Disorders

Human skin layers serve as a barrier between the body and the environment, by preventing water loss and blocking the entry of chemicals, allergens, and microbes. Recent data showed that skin lipids are vital ‘key players’ of several functions and mechanisms performing in the skin, such as, barrier function and microbiome composition. Abnormalities in lipid composition have been observed in inflammatory cutaneous diseases with a disrupted skin barrier. This review aims to demonstrate the fundamental role of keratinocytes, sebocytes, and microbiome-derived lipids in the maintenance of the skin barrier. Furthermore, it would reveal the correlation between altered skin lipids’ composition, microbiome, and the occurrence of certain dermatological disorders such as acne vulgaris, atopic dermatitis, psoriasis, and rosacea.
A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE

Universities benefit from the merging of classroom lecturing and the use of technological resources to provide an innovative environment for their students. E-learning resources facilitate the process of teaching and learning. Although students use these resources widely, their usage behaviours and the factors the dominate the instructor-students learning resources usage still need to be investigated further due to the fast growing technological changes and the advance features of e-learning, which affect the dominant prioritization and the significances of these factors. In order to facilitate this research, a research model was derived from the modified Technology Acceptance Model (TAM) in order to observe the factors that influence the instructors-students utilization of learning resources within universities in the United Arab Emirates (UAE). The research model was assessed based on an analysis of 520 students who participated in the study. Thus, it can be inferred that both peer influence and student’s capability to use technology have no relevant effect on perceived usefulness and students’ usage behaviour. However, instructor contributions, course content and design do indeed have a significant correlation with student usage behaviour. The findings from this research advance the understanding of the factors that have a more dominant influence on instructor-students learning resources usage in the context of UAE universities.
The rare Case of Cystic Adenoid Carcinoma of the Larynx Treated by Post Operative Radiation Therapy

Adenoid cystic carcinoma (C.A.K.) is a malignant tumor most commonly developing in the main or accessory salivary glands. The most frequent sites of C.A. K are located in the salivary glands of the oral cavity, in particular in the hard palate and with less frequency in the nasal cavity, paranasal sinuses and pharynx. The laryngeal localization of C.A. K is extremely rare. The cervical scanner is the imaging of choice for the early diagnosis of CAK of the larynx. Diagnosis is made by pathology examination of the biopsy specimen supplemented by immunohistochemistry. We report the case of a 26-years-old patient, who presented for 18 months, progressive dysphagia to solids, and then laryngeal dyspnea requiring emergency tracheotomy. Surgery followed by postoperative radiotherapy was used for treatment.
Applicability of the 500°C isotherm method in determining the strength of reinforced concrete beams after fire

Abstract A procedure to estimate the residual bending moment and the shear load capacity after fire in reinforced concrete beams was evaluated. The calculation method is based on the 500ºC Isotherm Method, adopting the reduction coefficients proposed by Van Coile et al. (2014) for the steel yield strength. The proposed method validation was done from experimental results of 62 reinforced concrete beams available in the literature. It was possible to observe a good approximation of the analytical method with the experimental data. For the bending moment an average ratio M r ana / M r exp of 1.04 and standard deviation of 0.15 was found. For the shear force an average ratio V r ana / V r exp of 0.85 and standard deviation of 0.23 was found.
An empirical investigation of socio-economic impacts of agglomeration economies in major cities of Punjab, Pakistan

Abstract Agglomeration economies are the external benefits earned from clustering of industries and people in cities. The study assumes unbridled clustering of population in emerging urban agglomerations turning economies into diseconomies. This study empirically investigates the heterogeneous socioeconomic impacts of agglomeration economies in selected cities of Punjab, Pakistan, from 1998 to 2018, using the Pooled Mean Group and the Mean Group techniques of Panel ARDL. Agglomeration economies are determined by population density, number of registered factories, employment size, and housing, in the cities of Punjab. The study designed four indices for socioeconomic conditions using principal component analysis. These include: education-index, healthcare-index, water & sanitation-index, and economic conditions-index. Research findings reveal pressures of high population density, unemployment, and costly housing on educational & healthcare facilities, poor sanitation & waste management, in cities of Punjab, Pakistan. The study suggests that policy makers and urban planners to develop short term and long term policies and development plans for villages and secondary cities to uplift wellbeing of the local population. Nonetheless, cities need to decentralize for sustainable development and management.
Ferroptosis and its emerging role in tumor

Ferroptosis is a novel form of programmed cell death characterized by iron-dependent lipid peroxidation accumulation. It is morphologically, biochemically, and genetically distinct from other known cell death, such as apoptosis, necrosis, and pyroptosis. Its regulatory mechanisms include iron metabolism, fatty acid metabolism, mitochondrial respiration, and antioxidative systems eliminating lipid peroxidation, such as glutathione synthesis, selenium-dependent glutathione peroxidase 4, and ubiquinone. The disruption of cellular redox systems causes damage to the cellular membrane leading to ferroptotic cell death. Recent studies have shown that numerous pathological diseases, like tumors, neurodegenerative disorders, and ischemia-reperfusion injury are associated with ferroptosis. As such, pharmacological regulation of ferroptosis either by activation or by suppression will provide a vast potential for treatments of relevant diseases. This review will discuss the advanced progress in ferroptosis and its regulatory mechanisms from both the antioxidative and oxidative sides. In addition, the roles of ferroptosis in various tumorigenesis, development, and therapeutic strategies will be addressed, particularly to chemotherapy and immunotherapy, as well as the discoveries from Traditional Chinese Medicine. This review will lead us to have a comprehensive understanding of the future exploration of ferroptosis and cancer therapy.