Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroprotection for Nonarteritic Central Retinal Artery Occlusion: Lessons from Acute Ischemic Stroke

Abstract Nonarteritic central retinal artery occlusion (NA-CRAO) is a variant of acute ischemic stroke (AIS) and is a cause of sudden severe loss of vision. There are guidelines by the American Heart Association and the American Stroke Association for the care of CRAO patients. This review explores the basis of retinal neuroprotection for CRAO and its potential for improving the outcome of NA-CRAO. Recently, there have been significant advances in research into the use of neuroprotection to treat retinal diseases, including retinal detachment, age-related macular degeneration, and inherited retinal diseases. Also, neuroprotective research in AIS has been extensive, and newer drugs tested, including Uric acid, Nerinetide, and Otaplimastat, with promising results. Progress in cerebral neuroprotection after AIS offers hope for retinal neuroprotection after CRAO; and a possibility of extrapolating research findings from AIS into CRAO. Combining neuroprotection and thrombolysis can extend the therapeutic window for NA-CRAO treatment and potentially improve outcomes. Experimented neuroprotection for CRAO includes Angiopoietin (Comp Ang1), KUS 121, Gene therapy (XIAP), and hypothermia. Efforts in the field of neuroprotection for NA-CRAO should focus on better imaging to delineate the penumbra after an acute episode of NA-CRAO (using a combination of high-definition optical coherence angiography and electrophysiology). Also, research should explore details of pathophysiologic mechanisms involved in NA-CRAO, allowing for further neuroprotective intervention, and closing the gap between preclinical and clinical neuroprotection.
Pengaruh Pelatihan Ai Chi Terhadap Peningkatan Performa Dual Task Pada Lansia

Aktifitas yang dilakukan seseorang dalam kesehariannya tidak lepas dari aktifitas multitasking dimana pada aktifitas tersebut minimal seseorang harus mampu melakukan dua aktifitas sekaligus (dualtask), lansia dengan gangguan kognitif atau tidak mampu melakukan aktifitas ganda atau dualtask mempunyai resiko jatuh yang tinggi. Salah satu tindakan untuk meningkatkan kemampuan kognitif dan dualtask pada lansia adalah dengan latihan Ai Chi. Ai Chi merupakan metode latihan yang terbukti mampu meningkatkan kualitas hidup lansia dimana mengurangi resiko jatuh salah satunya. Tujuan penelitian untuk membuktikan apakah pelatihan Ai Chi dalam meningkatkan performa dual task pada lansia.
WEIBULL SEMIPARAMETRIC REGRESSION MODELS UNDER RANDOM CENSORSHIP

Semiparametric regression is concerned with the flexible combination of non-linear functional relationships in regression analysis. The main advantage of the semiparametric regression models is that any application benefits from regression analysis can also benefit from the semiparametric regression. In this paper, we derived a consistent estimator of parametric portion and nonparametric portion in Weibull semi-parametric regression models under random censorship.
The Ontology of Velocity

Special relativity formulates a world partitioned into frames in relative motion; absolute motion is prohibited by axiom: no preferred frame, with consequences for the ontology of velocity. The best guide to physical reality is experiment, so ontology of velocity is investigated in the context of primordial field theory in terms of three experiments: Michelson-Morley, Michelson-Gale and Hafele-Keating experiments
Design of non-delayed full link high precision internal calibration scheme for radar system

A non-delayed full link high precision internal calibration scheme of radar system based on built-in calibration module is introduced in this paper. By adding internal calibration module and necessary calibration signal coupling and separation circuit to the existing radar system, this scheme can realize the transmitting, receiving and reference calibration of the radar system in working condition with low cost and low system complexity. It has the characteristics of simple system composition, comprehensive calibration mode, large dynamic range of calibration signal, high precision calibration in full temperature range. It can be used as a feasible scheme for non-delayed calibration of radar system.
A critical review of machine learning for lignocellulosic ethanol production via fermentation route

In this work, machine learning (ML) applications in lignocellulosic bioethanol production were reviewed. First, the pretreatment-hydrolysis-fermentation route, the most commonly studied alternative, was summarized. Next, a bibliometric analysis was performed to identify the current trends in the field; it was found that ML applications in the field are not only increasing but also expanding their relative share in publications, with bioethanol seeming to be the most frequently researched topic while biochar and biogas are also receiving increased attention in recent years. Then, the implementation of ML for lignocellulosic bioethanol production via this route was reviewed in depth. It was observed that artificial neural network (ANN) is the most commonly used algorithm (appeared in almost 90% of articles), followed by response surface methodology (RSM) (in about 25% of articles) and random forest (RF) (in about 10% of articles). Bioethanol concentration is the most common output variable in the fermentation step, while fermentable sugar and glucose concentration are studied most in hydrolysis. The datasets are usually small, while the fitnesses of the models (R2) are usually high in the papers reviewed. Finally, a perspective for future studies, mostly considering improving data availability, was provided.
An unsupervised transfer learning bearing fault diagnosis method based on depthwise separable convolution

Bearings are an essential component of rotating mechanical equipment. Traditional signal processing-based fault diagnosis methods usually require a massive labeled data for training, but bearings generally operate in the equipment under normal fault-free conditions. This paper proposes an improved adaptive batch normalization (AdaBN) transfer learning bearing fault diagnosis method for batch normalization (BN) in traditional deep learning architecture. The AdaBN network preprocesses the raw vibration signals, and then the preprocessed features are input to a depthwise sparable convolution neural model for training. Features are extracted by depthwise convolution and point convolution in the network. AdaBN can freeze all the parameters in the network except the BN layer. Finally, a small amount of labeled data is classified using transfer learning methods. A laboratory data set was used for validation, and the experimental validation showed that the accuracy of the bearing fault diagnosis method using AdaBN reached 85%.
Mechanisms of knowledge translation in the conditions of modern culture digitalization

This article deals with the problem of digitalization of cultural mechanisms of knowledge translation. The study clarifies the terms digitization and digitalization, considers their comparison, as well as differences from digital technologies. In addition, the positive and negative consequences of these processes on society as a whole are considered. Since a modern person prefers to receive information in a finished form, therefore, digitalization is of great importance. The history of the emergence of digitalization as a separate process is also considered. Now most areas of our lives increase technological involvement, that has led to a large-scale convergence of various areas and processes. The article examines the influence of convergence on the processes of social and political integration at the level of interaction between groups, associations of individuals in the implementation of civil initiatives, as well as at the level of states and peoples. Digitalization processes have significantly changed the world and human interaction.
Impact of different data processing methods on model diagnostic performance

During fault diagnosis of rolling bearings of rotating machinery in nuclear power plant, there are different data processing methods for original vibration signals, and different data processing methods have different diagnostic accuracy under the same diagnosis model. [Purpose] When the performance of the model is limited, in order to improve the diagnostic accuracy of the model, it is necessary to study the data processing method. [Methods] Therefore, the original vibration signal is processed into five ways: time-domain diagram(TD), time grayscale diagram(TGS), fast Fourier transform frequency-domain diagram(FFT), short-time Fourier transform time-frequency diagram(STFT) and continuous wavelet transform time-frequency diagram(CWT) for the initial feature extraction of the original vibration signal, and the five methods are compared and analyzed in the original data, data with added noise and data with less sample size. [Result] The experimental results show that the FFT data processing methods has a more obvious test accuracy under the noisy data and small sample size, and its accuracy is 1.9% and 6.7%(data under 50 sample size) higher than the suboptimal methods in both cases. [Conclusions] Therefore, in the case of noisy data and small sample size, the diagnostic performance of the model can be further improved by adopting the FFT data processing.
Strategic Management Accounting for Village-Owned Enterprises in Indonesia

The growth and development of BUMDes in Indonesia is very rapid, but it has not been able to contribute to optimally increasing the income and welfare of rural communities. Strategic management accounting is an approach to management accounting techniques that can support the achievement of organizational goals and objectives. This research is based on contingency theory that there is not universally applicable approach. The development of strategic management accounting needs to consider the characteristics of the organization, including the organizational environment. The object of this research is Village Owned Enterprises in Indonesia. Respondents in this study were: administrators (managers) of Village-Owned Enterprises in Indonesia. The data analysis technique used a qualitative description. The results show that most village-owned enterprises in Indonesia have always and often applied strategic management accounting techniques, however, there are still many BUMDes managers who sometimes even rarely apply strategic management accounting techniques. This condition may be one of the factors that not yet optimal function and role of BUMDes in encouraging economic improvement and community welfare.
Fock-Goncharov coordinates and rank $n$ swapping algebra

In our previous paper arXiv:math/1411.2796, we introduce the rank $n$ swapping algebra, which is a Poisson algebra associated to an affine variety defined by pair of points on a circle and their determinant relations. In this paper, we show how the rank $n$ swapping algebra is related to a naturally generalized Weil-Petersson form. More precisely, let the rank $n$ swapping multifraction algebra $\mathcal{B}_n(\mathcal{P})$ be the sub fraction algebra of the rank $n$ swapping algebra generated by "cross ratios". Given a generic configuration space $\operatorname{Conf}_{k,n}$ of $k$ flags in $\mathbb{RP}^{n-1}$ and its associated triangulation, we give a Poisson algebra monomorphism from the fraction algebra generated by the Fock-Goncharov coordinates for $\operatorname{Conf}_{k,n}$ into $\mathcal{B}_n(\mathcal{P})$ with respect to the Fock-Goncharov's Poisson bracket and the swapping Poisson bracket. This gives a geometric interpretation of the natural Poisson structure described by Fock and Goncharov in arXiv:math/0311149 via pairs of points on a circle. As a consequence, we reprove that the Poisson structure of Fock-Goncharov does not depend on triangulations.
The use of time/area closures to reduce bycatches of harbour porpoises: lessons from the Gulf of Maine sink gillnet fishery

In 1994, the United States National Marine Fisheries Service (NMFS) implemented a series of time/area closures for the Gulf of Maine sink gillnet fishery to reduce the bycatch of harbour porpoises (Phocoena phocoena). The present study evaluates the effectiveness of the Mid-Coast closure area, implemented during November 1994. Rates of porpoise bycatches are analysed prior to, during and after the closure. In addition, individual vessels are tracked and the spatial distribution of fishing effort examined to determine how fishermen responded to the closure. The highest bycatch rate occurred in September in the Mid-Coast region, well before the closure. During November, fishermen concentrated much of their effort adjacent to the closed area in unrestricted waters, where bycatch occurred. The Mid-Coast closure was not in place for a long enough period, nor was it large enough, to be effective in reducing bycatch rates of harbour porpoises. The failure of the Mid-Coast closure is attributed to temporal and spatial variation in patterns of bycatch rates, and to the displacement of fishing effort and porpoise bycatch outside the closed area.
Vertebrate and Invertebrate Animal and New In Vitro Models for Studying Neisseria Biology

The history of Neisseria research has involved the use of a wide variety of vertebrate and invertebrate animal models, from insects to humans. In this review, we itemise these models and describe how they have made significant contributions to understanding the pathophysiology of Neisseria infections and to the development and testing of vaccines and antimicrobials. We also look ahead, briefly, to their potential replacement by complex in vitro cellular models.
Genetic Variants Associated with Drug Resistance of Cytomegalovirus in Hematopoietic Cell Transplantation Recipients

Cytomegalovirus (CMV) infection is a serious complication in hematopoietic cell transplantation (HCT) recipients. Drug-resistant strains make it more challenging to treat CMV infection. This study aimed to identify variants associated with CMV drug resistance in HCT recipients and assess their clinical significance. A total of 123 patients with refractory CMV DNAemia out of 2271 HCT patients at the Catholic Hematology Hospital between April 2016 and November 2021 were analyzed, which accounted for 8.6% of the 1428 patients who received pre-emptive therapy. Real-time PCR was used to monitor CMV infection. Direct sequencing was performed to identify drug-resistant variants in UL97 and UL54. Resistance variants were found in 10 (8.1%) patients, and variants of uncertain significance (VUS) were found in 48 (39.0%) patients. Patients with resistance variants had a significantly higher peak CMV viral load than those without (p = 0.015). Patients with any variants had a higher risk of severe graft-versus-host disease and lower one-year survival rates than those without (p = 0.003 and p = 0.044, respectively). Interestingly, the presence of variants reduced the rate of CMV clearance, particularly in patients who did not modify their initial antiviral regimen. However, it had no apparent impact on individuals whose antiviral regimens were changed due to refractoriness. This study highlights the importance of identifying genetic variants associated with CMV drug resistance in HCT recipients for providing appropriate antiviral treatment and predicting patient outcomes.
MAP3D: An explorative approach for automatic mapping of real-world eye-tracking data on a virtual 3D model

Mobile eye tracking helps to investigate real-world settings, in which participants can move freely. This enhances the studies’ ecological validity but poses challenges for the analysis. Often, the 3D stimulus is reduced to a 2D image (reference view) and the fixations are manually mapped to this 2D image. This leads to a loss of information about the three-dimensionality of the stimulus. Using several reference images, from different perspectives, poses new problems, in particular concerning the mapping of fixations in the transition areas between two reference views. A newly developed approach (MAP3D) is presented that enables generating a 3D model and automatic mapping of fixations to this virtual 3D model of the stimulus. This avoids problems with the reduction to a 2D reference image and with transitions between images. The x, y and z coordinates of the fixations are available as a point cloud and as . csv output. First exploratory application and evaluation tests are promising: MAP3D offers innovative ways of post-hoc mapping fixation data on 3D stimuli with open-source software and thus provides cost-efficient new avenues for research.
Pulsed Laser Diode Based Wireless Power Transmission Application: Determination of Voltage Amplitude, Frequency, and Duty Cycle

Laser power transfer (LPT) is one of the leading technologies in long-distance power transmission with its advantages such as enabling high power transmission and suitability for mobile applications. The transmitter part, which includes the laser diode (LD) and the driving circuit, directly affects system efficiency. Continuous wave (CW) lasers are used in studies due to their high power and continuous radiation. However, one of the main disadvantage of the mentioned system is the high cost of LD. In this study, the use of pulsed LDs in LPT applications is proposed because of their small size and low cost. On the other hand, appropriate operating point of pulsed LD is missing information in the literature. In order to contribute literature with this information, pulsed LD is used for LPT, and the effects of driving voltage amplitudes, frequencies, and duty cycles are analyzed to demonstrate the importance of determining the appropriate operating point of the pulsed LD and the potential use of pulsed LDs in LPT.
Preprocessing and Reduction for Semidefinite Programming via Facial Reduction: Theory and Practice

Semidefinite programming is a powerful modeling tool for a wide range of optimization and feasibility problems. Its prevalent use in practice relies on the fact that a (nearly) optimal solution of a semidefinite program can be obtained efficiently in both theory and practice, provided that the semidefinite program and its dual satisfy the Slater condition. This thesis focuses on the situation where the Slater condition (i.e., the existence of positive definite feasible solutions) does not hold for a given semidefinite program; the failure of the Slater condition often occurs in structured semidefinite programs derived from various applications. In this thesis, we study the use of the facial reduction technique, originally proposed as a theoretical procedure by Borwein and Wolkowicz, as a preprocessing technique for semidefinite programs. Facial reduction can be used either in an algorithmic or a theoretical sense, depending on whether the structure of the semidefinite program is known a priori. The main contribution of this thesis is threefold. First, we study the numerical issues in the implementation of the facial reduction as an algorithm on semidefinite programs, and argue that each step of the facial reduction algorithm is backward stable. Second, we illustrate the theoretical importance of the facial reduction procedure in the topic of sensitivity analysis for semidefinite programs. Finally, we illustrate the use of facial reduction technique on several classes of structured semidefinite programs, in particular the side chain positioning problem in protein folding.
Injection Flow Past a Porous Plate: Solution to an Unsolved Problem

It is widely believed that the solution of Navier-Stokes equations for a steady flow at velocity (at y ~ ) past an infinite porous plate in the case of, injection does not exist since the solution becomes unbounded (White 1991, p-143). However, interestingly, no theoretical justification has been provided to support this "non-existence". Hence it had remained an unsolved problem for the mathematicians for a long time. The present work provides a highly accurate solution to this problem that is valid both for suction as well as injection. The homotopy perturbation method (HPM) is used to solve the problem analytically.
A novel strategy employing the flavonoid fisetin to halt the progression of renal fibrosis in obstructive nephropathy

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial and No Derivatives License (http:// creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted non-commercial use, distribution of the material without any modifications, and reproduction in any medium, provided the original works properly cited. Ureteral obstruction (UO) has a significant impact on renal function by altering hemodynamics, decreasing glomerular filtration, and inducing renal transcriptomic and metabolomic changes. It can also cause structural changes in the kidney parenchyma, most notably hydronephrosis and renal fibrosis. Renal fibrosis, a common feature of chronic kidney disease (CKD), is a complex process characterized by loss of capillary networks, progressive accumulation of fibrous collagens, and activation of myofibroblasts and inflammatory cells. The process results in a substantial decline in renal blood flow and tissue perfusion, impaired tubular handling of water and electrolytes, and an increase in urinary protein excretion. CKD can be caused by many diseases, including diabetic nephropathy, hypertensive nephrosclerosis, glomerulonephritis, chronic obstructive nephropathy, and others. Globally, the prevalence of CKD is increasing, which poses a significant clinical challenge as CKD can progress to end-stage renal disease (ESRD), which requires dialysis and kidney transplantation. Approximately 9.1% of the world’s population, or 700 million individuals, have CKD. Chronic obstruction of the urinary tract and urine flow leads to obstructive nephropathy and ESRD. Animal modA novel strategy employing the flavonoid fisetin to halt the progression of renal fibrosis in obstructive nephropathy
Gerenciamento de workflows cientificos em bioinformatica

Atividades em bioinformatica estao crescendo por todo o mundo, acompanhadas por uma proliferacao de dados e ferramentas. Isto traz novos desafios, por exemplo, como entender e organizar esses recursos, como compartilhar e re-usar experimentos bem sucedidos (ferramentas e dados), e como prover interoperabilidade entre dados e ferramentas de diferentes locais e utilizados por usuarios com perfis distintos. Esta tese propoe uma infra-estrutura computacional para resolver tais problemas. A infra-estrutura permite projetar, re-usar, anotar, validar, compartilhar e documentar experimentos de bioinformatica. Workflows cientificos sao os mecanismos utilizados para representar tais experimentos. Combinando pesquisa em bancos de dados, workflows cientificos, inteligencia artificial e Web semântica, a infra-estrutura se beneficia do uso de ontologias para permitir a especificacao e anotacao de workflows de bioinformatica e para servir como base aos mecanismos de rastreabilidade. Alem disso, ela usa tecnicas de planejamento em inteligencia artificial para prover as composicoes automatica, iterativa e supervisionada de tarefas para satisfazer as necessidades dos diferentes tipos de usuarios. Os aspectos de integracao de dados e interoperabilidade sao resolvidos combinando o uso de ontologias, mapeamento entre estruturas e algoritmos de casamento de interfaces. A infra-estrutura foi implementada em um prototipo e validada com dados reais de bioinformatica Abstract