nils-herrmann/clean_scirepeval huggingface dataset:
Penglibatan ibubapa sebagai pengurus komite sekolah terhadap kualiti pendidikan
Year: 2016

Komite Sekolah merupakan satu badan yang sah ditubuhkan sebagai penghubung di antara ibubapa, guru, sekolah, masyarakat dan pelajar. Untuk itu perlu diketahui adakah Komite Sekolah telah menjalankan peranannya yang dapat memberi sumbangan terhadap pencapaian kualiti pendidikan. Kajian ini bertujuan untuk mengenalpasti penglibatan ibubapa sebagai Pengurus Komite Sekolah yakni sebagai pemberi nasihat (advisory) pemberi sokongan (supporting) sebagai pengawal (controlling) dan sebagai pengantara (mediator) yang berkaitan terhadap kualiti input, kualiti proses dan kualiti output. Juga untuk mengenal pasti perbezaan yang disebabkan oleh lokasi Sekolah Menengah Atas (SMA) yang berada di bandar di luar bandar dan mengenal pasti "kerangka model" penglibatan ibubapa sebagai Pengurus Komite Sekolah. Kajian ini dijalankan melalui dua fasa iaitu kajian kuantitatif fasa pertama dan kemudian fasa kedua dengan kajian kualitatif. Sampel kajian melibatkan 19 Sekolah Menengah Atas (SMA) Negeri di Kota Batam Provinsi Kepulauan Riau Indonesia, yang terdiri daripada 138 orang sampel kuantitatif dan sebanyak 5 orang informan sampel kualitatif bagi mendalami hasil kajian kuantitatif. Kajian ini menggunakan Model SEM (PLS) untuk menganalisis data kuantitatif dan melalui kaedah triangulasi untuk kualitatif. Hasil dapatan menunjukkan penglibatan ibubapa sebagai Pengurus Komite Sekolah dalam menjalankan peranannya tidak banyak pengaruhnya secara signifikan terhadap kualiti pendidikan. Secara keseluruhan Komite Sekolah di Bandar adalah lebih baik dari di luar bandar. Kajian ini menghasilkan satu model penglibatan Komite sekolah yang menekankan peranan Komite sekolah sebagai rakan kongsi sekolah dengan semua pihak yang disebut Perkongsian Bersepadu (Integrated Partnership) Model ini dapat dijadikan cadangan kajian yang akan datang untuk melihat konsep perkongsian tersebut dengan lebih terperinci.
Reducing Blokchain Size Using Complementary Block
Venue: 2019 International Conference on ICT for Smart Society (ICISS)
Year: 2019

The size, especially the growth rate, of blockchain has been a major problem since its introduction in 2008. A common blockchain scheme will have exponential growth rate that affect the scalability of blockchain. To overcome this problem, complementary block is proposed. The blockchain is split into multiple chain where each block in a chain is a complementary of a block in another chain. The result shows that complementary block have smaller growth rate compared to original blockchain scheme. Despite its small data duplication, the complementary block still retains the same integrity level as the original blockchain.
Experimental study of a 1 kw organic Rankine cycle with a zeotropic mixture of R245fa/R134a
Year: 2015

The performance of a new zeotropic mixture of R245fa 60%/R134a 40% (molar concentration) in small scale ORC (organic Rankine cycle) was proposed and evaluated experimentally. For a range of heat source temperatures, the power output and thermal efficiency of the ORC system with this mixture was analyzed. The experimental data is presented for a 1 kW scroll expander and a heat source temperature between 80 and 120 degC. The results showed that the proposed zeotropic mixture increases the power output compared to an identical ORC with pure R245fa despite working at a lower pressure ratio. With increasing heat source temperature, the pure R245fa ORC becomes increasingly vigorous. Therefore, the best application of this mixture would be in heat sources with temperatures between 80 degC and 100 degC, where the pure R245fa ORC cannot have a high expander inlet pressure; hence, it works at lower pressure ratios.
Hybrid quantum linear equation algorithm and its experimental test on IBM Quantum Experience
Venue: Scientific Reports
Year: 2019

We propose a hybrid quantum algorithm based on the Harrow Hassidim Lloyd (HHL) algorithm for solving a system of linear equations. In this paper, we show that our hybrid algorithm can reduce a circuit depth from the original HHL algorithm by means of a classical information feed forward after the quantum phase estimation algorithm, and the results of the hybrid algorithm are identical to those of the HHL algorithm. In addition, it is experimentally examined with four qubits in the IBM Quantum Experience setups, and the experimental results of our algorithm show higher accurate performance on specific systems of linear equations than that of the HHL algorithm.
Vaccine designers take first shots at COVID 19.
Venue: Science
Year: 2020

The race to develop a vaccine against the novel coronavirus is unprecedented in speed, scale, and scope. Two companies already have launched clinical trials, one in the United States, the other in China. According to the World Health Organization, 54 other vaccine "candidates" are in the works by researchers from academia, biotechs, big pharma, and the military. One effort, by Johnson Johnson, potentially has $1 billion in backing, including half from the U.S. government. The Coalition for Epidemic Preparedness Innovations is financing eight other projects and may invest up to $2 billion itself. The vaccines are being made with both old and new technologies; the "platforms" include inactivated and attenuated viruses, protein subunits, harmless viral vectors, messenger RNA, DNA, and viruslike particles. Many researchers are optimistic that the scientific hurdles are not that high, noting that there9s durable immunity seen in humans infected with closely related coronaviruses, as well as success in vaccine studies in animal models against those diseases. If several vaccines prove their worth which will take at least 1 year in an ideal world that will also mean there is a greater supply, and there9s little question that the demand will be exceedingly high.
Characterization of body composition and definition of sarcopenia in patients with alcoholic cirrhosis: A computed tomography based study
Venue: Liver international official journal of the International Association for the Study of the Liver
Year: 2017

Alterations in body composition (BC) as loss of fat and muscle mass (sarcopenia) are associated with poor outcome in alcoholic cirrhosis (ALC) Prevalence of sarcopenia depends upon the method of assessment. Computed Tomography (CT) is a gold standard tool for assessing BC.
Wesley J. Thompson (1947 2019)
Venue: Frontiers in Molecular Neuroscience
Year: 2020

Wesley Jay (Wes) Thompson, known for his seminal contributions to the studies of neuromuscular synapses and glial cells, passed away on March 26, 2019, at the age of 71. Surviving family, friends, trainees, colleagues, and others who hold Wes in fond memory gathered at the campus of Texas A&M University in College Station, TX, for a memorial service in his honor some weeks later. All of the speakers recounted with fondness their interactions withWes that exemplified the impact his approaches to life and work had on the lives of many others. Most who knewWes would agree that he never liked to talk about himself much except in performing self deprecating humor and voicing his displeasure with the current political climate. Wes abhorred any public recognition of his accomplishments (or good deeds) and only begrudgingly tolerated those accompanied by research funds.We are certainWes would have protested the production of this article that pays him tribute. There are aspects of his life, however, that were readily apparent to those who have spent any meaningful amount of time with Wes his generosity, drive and integrity as a scientist, affinity for history and simpler things in life such as his vegetable garden and backyard barbeque with friends that brought him joy, and love for his daughter. Jeff Lichtman, a fellow towering contemporary figure in the study of neuromuscular synapses, once called Wes "a gem of a human being," a much deserved compliment that sweetly sums up the warm character of the man we all knew. Wes was born on December 10, 1947, in Alice, TX, to Jay and Harriett Thompson from whom Wes inherited many of his endearing traits: rough around the edges Texan charm, a desire/willingness to fix any mechanical instruments (often with mixed results) from his inventor/oilman father, and a deep belief in the value of education from his mother, a school teacher. The family relocated to Crawford, TX, where Wes spent a large part of his childhood. In 1966, Wes graduated from Crawford High School, and in 1970, earned a Bachelor of Science degree with High Honors from North Texas State University (since renamed the University of North Texas) a short 2 h drive away. Perhaps as a preview of what lay ahead in his long and respected scientific career punctuated with honors, a survey of his high school and college yearbooks  provides hints that fellow students had already recognized Wes's academic accomplishments and potential. As his career progressed, clearly,Wes did not fall victim to enemies of promise. In addition to receiving several postdoctoral fellowships, he was named a Searle Scholar in 1981 (Searle Scholars Program, Chicago Community Trust) and received a National Institutes of Health (NIH) Research Career Development Award in 1984 and a Javits Neuroscience Investigator award in 2001. He maintained a research program that was continuously funded by the NIH until his death. As a testament to his long standing dedication to educate undergraduate students, Wes was also recognized with a University of Texas at Austin Teaching Excellence Award in 2000.
Effect of mold opening on the properties of PLA samples obtained by foam injection molding
Year: 2018

Foam injection molding is a process by which complex, thick parts with a cellular core and a compact solid skin can be manufactured. The addition of a physical blowing agent under high pressure allows the decrease of the viscosity and the glass transition temperature of the gas/polymer melt. These features of the foam injection molding are very beneficial for biodegradable polymers, in which the processability window is very narrow. In this study, morphology, rheological, and mechanical properties of parts with a complex shape, obtained by foam injection molding, were analyzed. In particular, two commercial grades of poly(lactic acid) having different rheological behavior were adopted to obtain foamed parts by injection molding process with nitrogen as a physical blowing agent. For both resins, the effect of the mold opening on morphology and mechanical properties was assessed.
SOSIAL MEDIA SEBAGAI UPAYA PENINGKATAN PENJUALAN PRODUK UKM (Studi Kasus di SMESCO Jakarta)
Year: 2020

Tujuan penelitian ini adalah 1) untuk mengetahui sosial media dalam upaya peningkatan penjualan produk produk UKM 2) seberapa besar kontribusi sosial media dalam upaya peningkatan penjualan produk UKM. Berdasarkan tujuan yang ingin dicapai dalam penelitian ini, yaitu mengetahui tentang hubungan antara variabel yang diteliti, maka penelitian ini merupakan penelitian korelasional yaitu mengukur kekuatan hubungan antara variabel yang menunjukkan hubungan sebab akibat Adapun pendekatan yang digunakan dalam penelitian ini adalah menggunakan metode kuantitatif. Subjek penelitian ini adalah pelaku usaha yang terdaftar di SMESCO Jakarta dengan jumlah sampel 28 responden. Teknik analisis data menggunakan statistik deskriptif dengan regresi linear. Analisis regresi linear diperoleh Y 23,83 0,43X artinya nilai b 0,43 ternyata positif, maka tiap pertambahan atau peningkatan penggunaan media sosial yang efektif akan diimbangi dengan pertambahan penjualan. Hasil dari penelitian ini adalah 1) terdapat pengaruh sosial media terhadap peningkatan penjualan, 2) terdapat kontribusi penggunaan sosial media sebesar 19 dalam meningkatkan penjualan.
Thriving at the Top in the Digital Era: The Impact of ICT on TMT Agility
Year: 2018

Top management teams (TMT) have been argued to thrive in an environment characterized by continuous change and uncertainty, where the classical office space has been partly and in some cases even entirely replaced by the virtual space. Given this increased need for connectivity, in this conceptual paper we shed light on the role of information and communication technologies (ICT) in shaping the agility of TMTs. We extend recent TMT research to disentangle the concept of agility and provide novel insights into the nature of the relationship between ICT and TMT agility. In doing so, we emphasize the role of TMT level and environmental level contingencies in altering the interplay between the two constructs. We develop propositions suggesting that at best, the net effect of ICT on TMT agility is positive, while at worst the net effect is neutral, negative and positive effects canceling each other out.
Integration of Wit API with Python Coded Terminal Bot
Year: 2019

This research paper consists of the development of a python chatbot integrated with specific packages and dependencies having capabilities to perform various real life applications which can also be packaged with some integrated systems as a personal assistant. Various Web services are used using their APIs so as to make it more powerful and less dependent on python packages. It operates completely on Linux (Ubuntu) terminal. Python command with the __main__.py file has been used to run it. Terminal then becomes a live Web based chatbot service with STT and TTS services. Natural language processing is further done by Wit.ai API which token key is set in the code. Each NLP is done by the API and then processed, and crunched text is sent from the wit engine direct to display terminal.
Emodin Ameliorates Renal Damage and Podocyte Injury in a Rat Model of Diabetic Nephropathy via Regulating AMPK/mTOR Mediated Autophagy Signaling Pathway
Venue: Diabetes, metabolic syndrome and obesity targets and therapy
Year: 2021

The activation of autophagy has potential protective effect on diabetic nephropathy (DN) podocyte injury, and the AMPK/mTOR signaling pathway is an important regulatory pathway of autophagy. Emodin has been reported to effectively delay DN progression; however, the therapeutic mechanisms involved in vivo remain ambiguous. The present study aimed to elucidate the mechanism of emodin in improving renal tissue and podocyte injury in DN by regulating the AMPK/mTOR autophagy signaling pathway.  All rats were divided into 4 groups: a Sham group, a Vehicle group, a low dose emodin (LD Emo) group (20 mg/kg/day) and a high dose emodin (HD Emo) group (40 mg/kg/day) The different doses of Emo and distilled water were daily administrated for 8 weeks after the induction of DN by the unilateral nephrectomy combined with intraperitoneal injections of streptozotocin (STZ) The rats' general status, blood glucose, biochemical parameters, urinary protein excretion, renal histological changes and cell apoptosis in renal tissue, as well as the key protein expressions in the AMPK/mTOR signaling pathway and apoptosis related proteins were examined, respectively.  Emodin ameliorated the general condition, kidney weight and urinary protein excretion of the rats, but has little influence on serum biochemical parameters and did not lower blood glucose; emodin attenuated renal fibrosis including the cell numbers, extracellular matrix rate and collagen area in glomerulus, simultaneously relieved podocyte foot process fusion, up regulated the expression of nephrin protein and suppressed glomerular and tubular epithelial cell apoptosis. In addition, emodin can induce and enhance autophagy in podocytes including increased expression of LC3 II/I, Beclin 1, p AMPK protein and decreased expression of p62, p mTOR protein, as well as increased autophagosomes in podocytes.  We have demonstrated that emodin, as a natural regulator in vivo, reduced proteinuria and alleviated renal fibrosis without affecting hyperglycemia in DN rats. The potential mechanisms by which emodin exerts its renoprotective effects in vivo are through suppressing cell apoptosis and enhancing autophagy of podocytes via the AMPK/mTOR signaling pathway in the kidney.
Down regulation of Glutathione Peroxidase 4 in Oral Cancer Inhibits Tumor Growth Through SREBP1 Signaling
Venue: AntiCancer Research
Year: 2021

This study aimed to elucidate the role of glutathione peroxidase 4 (GPX4) on the sterol regulatory element binding proteins (SREBPs) proliferation pathway in oral cancer cells, and determine its protein expression in oral cancer tissues.  Quantitative RT PCR and immunoblot analysis were carried out. Cell viability assay, apoptosis detection assay, immunohistochemistry and GPX4 knockdown were performed.  The levels of both GPX4 mRNA and protein were highest in SAS cells. GPX4 knockdown in SAS cells, a human oral squamous cell carcinoma cell line, using GPX4 siRNA resulted in a reduction in cell number, which appeared to be due to non apoptotic cell death such as ferroptosis. Furthermore, SREBP was clearly down regulated by GPX4 knockdown in SAS cells. Immunopositivity for GPX4 was revealed on the membrane of human oral squamous cell carcinoma cells, and this was correlated with p53 immunoreactivity.  GPX4 appears to play an important role in oral cancer proliferation.
Mean Variance Analysis in Bayesian Optimization under Uncertainty
Venue: AISTATS
Year: 2021

We consider active learning (AL) in an uncertain environment in which trade off between multiple risk measures need to be considered. As an AL problem in such an uncertain environment, we study Mean Variance Analysis in Bayesian Optimization (MVA BO) setting. Mean variance analysis was developed in the field of financial engineering and has been used to make decisions that take into account the trade off between the average and variance of investment uncertainty. In this paper, we specifically focus on BO setting with an uncertain component and consider multi task, multi objective, and constrained optimization scenarios for the mean variance trade off of the uncertain component. When the target blackbox function is modeled by Gaussian Process (GP) we derive the bounds of the two risk measures and propose AL algorithm for each of the above three problems based on the risk measure bounds. We show the effectiveness of the proposed AL algorithms through theoretical analysis and numerical experiments.
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Venue: ICML
Year: 2017

Deep neural networks (DNNs) have achieved unprecedented performance on a wide range of complex tasks, rapidly outpacing our understanding of the nature of their solutions. This has caused a recent surge of interest in methods for rendering modern neural systems more interpretable. In this work, we propose to address the interpretability problem in modern DNNs using the rich history of problem descriptions, theories and experimental methods developed by cognitive psychologists to study the human mind. To explore the potential value of these tools, we chose a well established analysis from developmental psychology that explains how children learn word labels for objects, and applied that analysis to DNNs. Using datasets of stimuli inspired by the original cognitive psychology experiments, we find that state of the art one shot learning models trained on ImageNet exhibit a similar bias to that observed in humans: they prefer to categorize objects according to shape rather than color. The magnitude of this shape bias varies greatly among architecturally identical, but differently seeded models, and even fluctuates within seeds throughout training, despite nearly equivalent classification performance. These results demonstrate the capability of tools from cognitive psychology for exposing hidden computational properties of DNNs, while concurrently providing us with a computational model for human word learning.
Variable neighbourhood search for dual resource constrained flexible job shop scheduling
Year: 2014

Dual resource constrained flexible job shop scheduling problem (FJSP) is considered and an effective variable neighbourhood search (VNS) is presented, in which the solution to the problem is indicated as a quadruple string of the ordered operations and their resources. Two neighbourhood search procedures are sequentially executed to produce new solutions for two sub problems of the problem, respectively. The search of VNS is restarted from a slightly perturbed version of the current solution of VNS when the determined number of iterations is reached. VNS is tested on some instances and compared with methods from literature. Computational results show the significant advantage of VNS on the problem.
Impact of Trivalent Metal Ion Doping on Structural, Photoluminescence and Electric Properties of NiFe2O4 Thin Films
Venue: Journal of Electronic Materials
Year: 2019

Nickel aluminum ferrite thin films of chemical formula NiFe2 xAlxO4 (0.0 x 1.0 in the step 0.2) were deposited on glass substrate using the spray pyrolysis deposition technique. The x ray diffraction patterns exhibited single phase cubic spinel structure with space group Fd 3m. The Fourier transform infrared spectroscopy (FTIR) spectra shows fundamental absorption bands related to octahedral and tetrahedral sites. The average surface roughness of all the thin films was estimated from AFM study, and is found on the order of 13 52 nm. The grain size is in nanosize dimensions and distributed homogeneously over the surface of the thin film to analyze by the FE SEM. The PL spectra obtained at room temperature showed the characteristic near band edge emission at around 680 nm and 780 nm. The DC electrical resistivity (rdc) as the function of temperature was studied for various Al3+ substitutions that indicated the decreasing trend with the increasing temperature, which exhibited a semiconducting nature of thin film. The dielectric properties decreased with increase in the Al3+ ions. The dielectric behavior of Al3+ substituted nickel ferrite thin films was explained by using Koop's phenomenological model. The dielectric parameters, such as the dielectric constant (e' dielectric loss (e' and loss tangent (tan d) decreased with increase in the Al3+ ions substitution as well as showing normal behavior with frequency.
Identity Aware Deep Face Hallucination via Adversarial Face Verification
Venue: 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS)
Year: 2019

In this paper, we address the problem of face hallucination by proposing a novel multi scale generative adversarial network (GAN) architecture optimized for face verification. First, we propose a multi scale generator architecture for face hallucination with a high up scaling ratio factor, which has multiple intermediate outputs at different resolutions. The intermediate outputs have the growing goal of synthesizing small to large images. Second, we incorporate a face verifier with the original GAN discriminator and propose a novel discriminator which learns to discriminate different identities while distinguishing fake generated HR face images from their ground truth images. In particular, the learned generator cares for not only the visual quality of hallucinated face images but also preserving the discriminative features in the hallucination process. In addition, to capture perceptually relevant differences we employ a perceptual similarity loss, instead of similarity in pixel space. We perform a quantitative and qualitative evaluation of our framework on the LFW and CelebA datasets. The experimental results show the advantages of our proposed method against the state of the art methods on the 8x downsampled testing dataset.