Miracle-dz/UniFAR-FTUs huggingface dataset:
In silico Prediction of Deleterious Single Nucleotide Polymorphism in S100A4 Metastatic Gene: Potential Early Diagnostic Marker

S100A4 protein overexpression has been reported in different types of cancer and plays a key role by interacting with the tumor suppressor protein Tp53. Single nucleotide polymorphisms (SNP) in S100A4 could directly influence the biomolecular interaction with the tumor suppressor protein Tp53 due to their aberrant conformations. Hence, the study was designed to predict the deleterious SNP and its effect on the S100A4 protein structure and function. Twenty-one SNP data sets were screened for nonsynonymous mutations and subsequently subjected to deleterious mutation prediction using different computational tools. The screened deleterious mutations were analyzed for their changes in functionality and their interaction with the tumor suppressor protein Tp53 by protein-protein docking analysis. The structural effects were studied using the 3DMissense mutation tool to estimate the solvation energy and torsion angle of the screened mutations on the predicted structures. In our study, 21 deleterious nonsynonymous mutations were screened, including F72V, E74G, L5P, D25E, N65S, A28V, A8D, S20L, L58P, and K26N were found to be remarkably conserved by exhibiting the interaction either with the EF-hand 1 or EF-hand 2 domain. The solvation and torsion values significantly deviated for the mutant-type structures with S20L, N65S, and F72L mutations and showed a marked reduction in their binding affinity with the Tp53 protein. Hence, these deleterious mutations might serve as prospective targets for diagnosing and developing personalized treatments for cancer and other related diseases.
Variabilidade temporal (2000 – 2020) da produção de cana-de-açúcar em Alagoa Nova, Brejo Paraibano

A cana-de-açúcar, importante cultura agrícola a nível mundial, é uma espécie de gramínea com boa adaptação a diferentes climas, e matéria-prima base para diversos produtos, com destaque para o etanol e açúcar. No estado da Paraíba, alguns municípios são historicamente ligados ao cultivo e beneficiamento dessa cultura, como, por exemplo, Alagoa Nova, no Brejo Paraibano. Nesse sentido, esse estudo objetivou avaliar a dinâmica produtiva dessa cultura da cana-de-açúcar nesse município, no período de 2000 – 2020. Utilizou-se como fonte de dados o banco de informações da Pesquisa Agrícola Municipal do Instituto Brasileiro de Geografia e Estatística (IBGE). Por meio do Sistema de Recuperação Automática (SIDRA), foram extraídos os dados relativos à área plantada, área colhida, quantidade produzida, rendimento médio e valor da produção dessa cultura em Alagoa Nova. Os resultados evidenciaram elevada variabilidade temporal na produção de cana-de-açúcar em Alagoa Nova, com uma tendência de aumento e recuperação da área plantada e colhida com essa cultura. Ainda, observou-se um aumento temporal do valor da produção. Todavia, baixas produtividades foram observadas durante todo o período amostral. Visto a importância da cana-de-açúcar para o segmento agrícola de Alagoa Nova, ações de incentivo à melhoria dos índices produtivos dessa cultura devem ser incentivadas, buscando-se assim, incrementar essa atividade localmente.
Scientific Narratives in the Study of Student Time Management: A Critical Review

Effective time management plays a major role in the performance society, and not only psychological, but also socio-cultural and pedagogical factors are involved in students' effective organization of time. Mainstream scientific discourse has argued that effective learning depends to a large extent on students' organizational skills. However, researchers have paid scant attention to the socio-cultural and pedagogical aspects that are involved in the development of these skills. The purpose of this article is to critically analyze the dominant scientific narratives on the study of the effective use of time by students. To this end, this study was designed based on a critical review of the literature from 1990 to 2021. The Web of Science and Scopus databases were consulted. A total of 51 papers met the inclusion criteria. The results suggest that learning to organize and optimize academic time is important for social coordination, well-being and achievement of students' academic and life goals. However, the acceleration of instructional time has a major emotional impact on the school population. The conclusion is the need to investigate the subjective and collective experiences of students on the emotional impact that speed, work overload and multitasking have on their academic and personal lives.
Surface decorated Ni sites for superior photocatalytic hydrogen production

Precise construction of isolated reactive centers on semiconductors with well‐controlled configurations affords a great opportunity to investigate the reaction mechanisms in the photocatalytic process and realize the targeted conversion of solar energy to steer the charge kinetics for hydrogen evolution. In the current research, we decorated isolated Ni atoms on the surface of CdS nanowires for efficient photocatalytic hydrogen production. X‐ray absorption fine structure investigations clearly demonstrate the atomical dispersion of Ni sites on the surface of CdS nanowires. Experimental investigations reveal that the isolated Ni atoms not only perform well as the real reactive centers but also greatly accelerate the electron transfer via direct Ni–S coordination. Theoretical simulation further documents that the hydrogen adsorption process has also been enhanced over the semi‐coordinated Ni centers through electronic coupling at the atomic scale.
Analysis of Service Quality for BPJS Health Participants: A Case Study of a Private Hospital in Bandung

Hospitals as one of the health care facilities in general have a very important role in efforts to improve the health status of the Indonesian people. Increasing public awareness about health results in greater demands for improving health services. This study aims at answering the question of how the service is perceived by BPJS health participants at a private hospital in Bandung and what aspects were complained by the BPJS participants. This is a qualitative research with a case study approach. Data was collected by means of semi-structured interviews with 20 BPJS health users. The results of this study indicate that of the 14 elements of service principles, the principle of justice in obtaining services is the element that receives the most complaints. Complaints are addressed not only to service officers but also to medical personnel. Therefore, it is important for hospitals to improve the quality of service by paying attention to the elements of justice for each patient.
Paley's theorem for Hankel matrices via the Schur test

Paley's theorem about lacunary coefficients of functions in the classical space $H^1$ on the unit circle is equivalent to the statement that certain Hankel matrices define bounded operators on $\ell^2$ of the nonnegative integers. Since that statement reduces easily to the case where the entries in the matrix are all nonnegative, it must be provable by the Schur test. We give such proofs with interesting patterns in the vectors used in the test, and we recover the best constant in the main case. We use related ideas to reprove the characterization of Paley multipliers from $H^1$ to $H^2$.
Research on Blended Teaching of Flipped Classroom Based on CNN-SSA-Bi-LSTM Deep Learning Model Computer Media

Aiming at the problem that the influencing factors of computer media flipped classroom hybrid teaching lead to the teaching effect not reaching the expected, this study proposes an ultra-short-term prediction model based on CNN-SSA-Bi-LSTM. CNN-SSA-Bi-LSTM is used to flip the study of mixed teaching in the classroom. This method constructs a one-dimensional convolutional neural network, performs data fusion and feature transformation on multiple key variables, and then constructs a two-way long-term short-term memory network prediction model, which realizes a 45-minute classroom for ultra-short-term prediction of the future. In addition, data optimization is performed through SSA to improve the predictive effect of the CNN-Bi-LSTM model. Experimental results show that compared with the traditional machine learning method, the proposed prediction model can effectively improve the prediction accuracy of the ultra-short-term classroom effect, and the relative variance of the continuous model is increased by 16.22%. High prediction accuracy and low error prove that CNN-SSA-Bi-LSTM deep learning model has strong application prospects in the research of flipped classroom hybrid teaching.
International Journal of Emerging Trends in Health Sciences

Characterization of cancer diseases and preparation of diagnostic reports after analyzing tissue specimens and several cell samples are provided by pathologists. One of the most successful strategies in pathology is to divide tumors into different subtypes and to adapt the treatment for each tumor. However, this approach has put a big burden on pathologists, who are reviewing tissue samples under the light of the microscope. Because, tumors have about 200 subtypes and pathologies are facing a growing demand for accurate and fast diagnosis and also patient safety. Therefore, digital pathology has been important and growing rapidly. Advances in computer technology such as computing power, faster networks and cheaper storage have enabled pathologists to manage images more easily than in the last decade. Novel pathology tools have a potential for automated and faster diagnosis and also better management of data. Moreover, it enables re -reducibility, validation of results, quality assurance and sharing of new ideas at anywhere and anytime. Advances in digital pathology have been reviewed in this paper. It seems that innovations in technologies will not only provide important improvements in pathology service, but also they will change healthcare and research fundamentally despite some challenges.
Opportunities and Challenges for Rural Broadband Infrastructure Opportunities and Challenges for Rural Broadband Infrastructure Investment Investment

Insufficient internet access is holding back local economies, reducing educational outcomes, and creating health disparities in rural areas of the U.S. At present, federal and state funding is available for rural broadband infrastructure deployment, but existing efforts have not invested in analytical work to maximize efficiency and minimize cost. In this study, we use a state-of-the-art matrix (SAM) to identify key challenges and opportunities facing rural broadband infrastructure from previous research and government reports. We focus on six themes: (1) technology, (2) hardware costs, (3) financing, (4) adoption, (5) regulatory/legal, and (6) management. We highlight key issues to be addressed by both private and public decision-makers to effectively manage broadband investment as well as engage stakeholders to improve access and adoption. Much of the challenge for rural broadband infrastructure is related to a low return on investment due to high capital costs and low population densities. However, there are many innovative approaches to overcoming this barrier from technical, policy, and social perspectives. Unfortunately, adoption and management are understudied and would benefit from additional research to design effective decision-making tools and programs. From a systems perspective, solutions that leverage tools from a diverse set of perspectives, rather than purely focusing on technology deployment, are more likely to be sustainable in the long-term. We outline an agenda for future work based on the needs of rural communities as well as local and state governments.
DESIGN OF WEB-BASED LEARNING SYSTEM

This paper intends to build a web-based learning system by taking the characteristics of learning agent. The system help user in the area of learning environments. The operation of the system includes the study courses of English Grammar and finally the students answer the question of English Grammar exam. Learning agent acting as a tutor to assist the students with specific learning needs, just like a human tutor or a classmate. This learning system is implemented with ASP.Net platform
CMAR_A_279782 11921..11932

*These authors contributed equally to this work Purpose: The liver function index can predict the prognosis of hepatocellular carcinoma and many other non-neoplastic diseases. We aimed to determine whether the preoperative albumin–bilirubin (ALBI) grade could predict the prognosis of patients with gastric cancer (GC). Patients and Methods: Data of 243 patients with GC who underwent radical resection were collected retrospectively. Patients were divided into the high ALBI (>−2.34) and low ALBI (≤−2.34) grade groups. Overall survival was analyzed between the two groups using the Kaplan–Meier curves. Univariate and multivariate analyses identified the independent factors associated with postoperative complications and overall survival. Results: The postoperative complication rates were higher in the high ALBI grade group than in the low ALBI grade group (P=0.005). The high ALBI grade group also had worse overall survival (P<0.001), especially TNM stage II–III patients (stage II, P=0.043; stage III, P<0.001). In the high ALBI grade group, patients with TNM stage III not undergoing chemotherapy had significantly worse survival times (P=0.001). High ALBI grade (P=0.032), Charlson score of 1–2 (P=0.007), and laparotomy surgery (P=0.045) were independent risk factors for postoperative complications. High ALBI grade (P=0.005), age ≥70 years (P=0.002), nutritional risk screening score 2002 score of 5–6 (P=0.019), tumor located in the cardia (P=0.020), diffuse tumor (P<0.001), and TNM stage III (P<0.001) were independent risk factors for overall survival. Conclusion: Preoperative ALBI grade could predict postoperative complications and overall survival of patients with GC, especially those with TNM stages II–III. This grading method has the advantages of preoperative availability, simplicity, and objectivity and aids in improving preoperative prognosis prediction and in achieving better outcomes of postoperative chemotherapy.
40 Years of Pulsars: The Birth and Evolution of Isolated Radio Pulsars

We investigate the birth and evolution of isolated radio pulsars using a population synthesis method, modeling the birth properties of the pulsars, their time evolution, and their detection in the Parkes and Swinburne Multibeam (MB) surveys. Together, the Parkes and Swinburne MB surveys have detected nearly 2/3 of the known pulsars and provide a remarkably homogeneous sample to compare with simulations. New proper motion measurements and an improved model of the distribution of free electrons in the interstellar medium, NE2001, also make revisiting these issues particularly worthwhile. We present a simple population model that reproduces the actual observations well, and consider others that fail. We conclude that: pulsars are born in the spiral arms, with the birthrate of 2.8+/-0.5 pulsars/century peaking at a distance ~3 kpc from the Galactic centre, and with mean initial speed of 380^{+40}_{-60} km/s; the birth spin period distribution extends to several hundred milliseconds, with no evidence of multimodality, implying that characteristic ages overestimate the true ages of the pulsars by a median factor >2 for true ages <30,000 yr; models in which the radio luminosities of the pulsars are random generically fail to reproduce the observed P-Pdot diagram, suggesting a relation between intrinsic radio luminosity and (P, Pdot); radio luminosities L Edot^0.5 provide a good match to the observed P-Pdot diagram; for this favored radio luminosity model, we find no evidence for significant magnetic field decay over the lifetime of the pulsars as radio sources ~100 Myr.
Situational and Individual Resources Predict Learning Opportunities and Career Outcomes in VET

Lüthi, F. , & Stalder, B. E. (2018). Situational and individual resources predict learning opportunities and career outcomes in VET. In C. Nägele & B. E. Stalder (Eds.), Trends in vocational education and training research. Proceedings of the European Conference on Educational Research (ECER), Vocational Education and Training Network (VETNET) (pp. 226–237). Abstract Situational and individual resources play a crucial role in learning in vocational education and training (VET). Drawing from the Job Demands-Resources (JD-R) model, we explore work-related and school-related resources of apprentices’ learning environments among 715 learners in Switzerland, and we analyse how resource profiles are related to learning opportunities and career outcomes. Applying latent profile analysis (LPA), we found four groups that are characterised by different patterns and levels of situational resources, including autonomy, instruction quality, and demands. Structure equation modelling (SEM) showed that resource profiles and individual resources (core self-evaluations, CSE) are associated with apprentices’ learning opportunities at both learning locations and, particularly, that having low resources hampers learning. As expected, learning opportunities at work and school positively affect satisfaction with VET and occupational commitment and reduce risks of resignation about VET. The results highlight the importance of providing apprentices with challenging, empowering and support-ive work and school environments to ensure learning and positive career development.
EEG Neurofeedback Brain Training for Epilepsy to Reduce Seizures

To review papers on epilepsy and the use of neurofeedback therapy to reduce seizures. Papers searched were from Pubmed, Proquest, Science Direct, etc. including the review of relevant journals e.g. Annals of Indian Academy of Neurology, HHS Public Script, Basic and Cinical Neuroscience, Current Opinion in Neurology, International Journal of Neurorehabilitation, Neurofeedback and Neuromodulation Techniques and Applications, Measurement Science Review, Journal of Neurotherapy. Common treatments such as surgery, pharmacotherapy, neurostimulation and diet therapy were used for epilepsy but had some limitations. Neurofeedback therapy was found, among those treatments, to be useful for epilepsy. There were two key points of successful protocol used in neurofeedback therapy: sensorimotorrhythm and slowcortical potential enabling a reduction of seizures.
Usability Heuristics for Interactive Digital Television

— Usability evaluation for applications based on emerging information technology brings new challenges. Interactive Digital Television (iDT) is considered as the convergence of television and computer technologies. The main iDT feature is that the user may interact with the application; therefore usability should be a main concern when designing iDT applications. Current research usually focuses on iDT applications from a technical point of view, rather than a user– centered approach. There is a need for new usability evaluation methods or at least for the use of traditional evaluations in novel ways. A set of heuristics is proposed, in order to help the usability evaluations of iDT applications.
Fractal superconducting resonators for the interrogation of two-level systems

In this thesis we use high-Q superconducting thin-film microwave resonators to interact with several types of quantum mechanical two-level systems. Such a resonator is used as the central building block in a cryogenic near-field scanning microwave microscope (NSMM) to reach a completely new regime of NSMM operation. In this regime where the superconducting resonator is only populated with a small number of photons, we demonstrate a capacitance sensitivity down to 64x10^(-21) Farad/rtHz and nanoscale resolution, which is sufficient to apply this scanning probe technique to quantum coherent objects. Such a 'coherent'-NSMM enables several new applications: for example to study the interaction of the NSMM probe with two-level defects in samples and to characterize artificial two-level systems (qubits), which eventually could lead to better understanding of decoherence mechanisms in superconducting quantum circuits. We demonstrate the ability to reach this regime in a sample consisting of a Cooper-pair box (CPB) weakly coupled to a superconducting resonator. In the strong driving regime we observe Landau-Zener-Stuckelberg interference and we discover a new type of relaxation mechanism in the strongly driven CPB that involves pair breaking and quasiparticle tunneling. It results in a recovered parity of the CPB and a population inversion of the dressed states. Not only does this demonstrate the applicability of NSMM for qubit characterization, but the quasiparticle mediated population inversion also becomes suitable for robust charge sensing in a scanning probe setup. To integrate the superconducting resonator onto our NSMM probe we develop a new type of resonator design - the fractal design - that have a very small external dipole moment allowing for a compact resonator. Another advantage of the fractal resonator is its resilience to magnetic fields. We show that the fractal resonator, after further optimization, can maintain quality factors above 10^5 in applied fields of more than 400 mT, something that becomes particularly useful for the interrogation of spin ensembles coupled to the resonator. We demonstrate that it is possible to detect down to 5x10^5 spins/rtHz in a very small volume coupled to a fractal resonator. Furthermore, the low dipole moment of the fractal resonator allows us to also introduce DC bias into the resonator without degrading its Q-factor. This is an important technological step that allows us to interact with new materials where spins can be quickly and locally manipulated using electric fields and we demonstrate the first steps in this direction with ensembles of manganese doped ZnO nanowires and frustrated molecular Cu spin triangles. The measurements achieve a very high sensitivity thanks to the Pound-Drever-Hall locking technique used. We develop this technique such that both resonance frequency and quality factor can be monitored with very high accuracy in real time. The demonstrated stability is ~30 Hz/rtHz for frequency readout and we can determine the Q-factor with a precision of 34 dB/rtHz.
League Adjusted Salary Model using Local Polynomial Regression

- Since the 2012 National Hockey League (NHL) Lockout, there have been many economic trends in the league that one might argue inconsistent. While many players’ salaries were significantly altered as results of buy-outs or extravagant contract signings, the salary cap has fluctuated dramatically in the following years due to these chaotic activities. To understand the seemingly contradicting NHL economic trends, in this paper, we discuss League Adjusted Salary Model (LASM) applying Local Polynomial Regression Modeling to properly gauge a player’s monetary vs. production feasibility value. The League Adjusted Salary Model is a approach that is dependent on a player’s League-Relative Salary Percentages and his Individual Production. The League Relativity is emphasized to account for the different payrolls of all 30 NHL teams and to understand the year-by-year economic trend. The Individual Production is a user flexible element of the individual level model that can be improved with utilizations of “Enhanced Statistics” such as Unblocked Shot Attempt Relative Percentage values. Combining these two data sets, we apply the Local Polynomial Regression Modeling to compute the feasibility of cost and production.