Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Wavelet Selection for Signal Denoising

Wavelet denoising plays a key role in removing noise from signals and is widely used in many applications. In denoising, selection of the mother wavelet is desirable for maximizing the separation of noise and signal coefficients in the wavelet domain for effective noise thresholding. At present, wavelet selection is carried out in a heuristic manner or using a trial-and-error that is time consuming and prone to error, including human bias. This paper introduces a universal method to select optimal wavelets based on the sparsity of Detail components in the wavelet domain, an empirical approach. A mean of sparsity change (<inline-formula> <tex-math notation="LaTeX">$\mu _{sc}$ </tex-math></inline-formula>) parameter is defined that captures the mean variation of noisy Detail components. The efficacy of the presented method is tested on simulated and experimental signals from Electron Spin Resonance spectroscopy at various SNRs. The results reveal that the <inline-formula> <tex-math notation="LaTeX">$\mu _{sc}$ </tex-math></inline-formula> values of signal vary abruptly between wavelets, whereas for noise it displays similar values for all wavelets. For low Signal-to-Noise Ratio (SNR) data, the change in <inline-formula> <tex-math notation="LaTeX">$\mu _{sc}$ </tex-math></inline-formula> between highest and second highest value is <inline-formula> <tex-math notation="LaTeX">$\approx 8-10\%$ </tex-math></inline-formula> and for high SNR data it is around 5%. The mean of sparsity change increases with the SNR of the signal, which implies that multiple wavelets can be used for denoising a signal, whereas, the signal with low SNR can only be efficiently denoised with a few wavelets. Either a single wavelet or a collection of optimal wavelets (i.e., top five wavelets) should be selected from the highest <inline-formula> <tex-math notation="LaTeX">$\mu _{sc}$ </tex-math></inline-formula> values. The code is available on GitHub and the signalsciencelab.com website.
Effort measurement of support to software products. Learning new tasks through software measurement

Goal-oriented software measurement is an important means to support development teams. Both theory and practice uses the Goal/Question/Metric method (GQM) often to structure measurement efforts. In the context of software process improvement many companies start adopting the GQM method to guide their improvements. In this paper we present a project in which a software development team was supported in their shift from development to maintenance work. This Project team developed a product for a global market, but this product is also customised to national requirements in separate local teams. After the second release of the product, the team that originally developed the product, had to shift to a role in which they give support to the national distributed customisation teams. However, this change implied that the team could no longer plan their activities as usual, because they became more dependent on questions and demands from these customisation teams. To support our target team in the learning process from development to maintenance, we applied the GQM method to measure effort spending to visualise how the change impacted the workload of the team. This paper presents the outline of the measurement programme, the learning process of the team, and contains some of the measurement data. Supported by the measurements presented in this paper, the team learned their new role rather fast, and planning of their new activities became possible because of having ‘real’ data available.
Collaborative filtering using random neighbours in peer-to-peer networks

Traditionally, collaborative filtering (CF) algorithms used for recommendation operate on complete knowledge. This makes these algorithms hard to employ in a decentralized context where not all users' ratings can be available at all locations. In this paper we investigate how the well-known neighbourhood-based CF algorithm by Herlocker et al. operates on partial knowledge; that is, how many similar users does the algorithm actually need to produce good recommendations for a given user, and how similar must those users be. We show for the popular MovieLens 1,000,000 and Jester datasets that sufficiently good recommendations can be made based on the ratings of a neighbourhood consisting of a relatively small number of randomly selected users.
An Analysis of the Low Moving Speed of Landfalling Typhoon In-Fa in 2021

: The movement speed of Typhoon In-Fa (2021) was notably slow, at 10 km h −1 or less, for over 20 hours following its landfall in Zhejiang, China, in contrast to other typhoons that have made landfall. This study examines the factors contributing to the slow movement of Typhoon In-Fa, including the steering flow, diabatic heating, vertical wind shear (VWS), and surface synoptic situation, by comparing it with Typhoons Yagi (2018) and Rumbia (2018) which followed similar tracks. The findings reveal that the movement speed of Typhoons Yagi and Rumbia is most closely associated with their respective 500 hPa environmental winds, with a steering flow of 10–12 m s −1 . In contrast, Typhoon In-Fa’s movement speed is most strongly correlated with the 850 hPa environmental wind field, with a steering flow speed of only 2 m s −1 . Furthermore, as Typhoon In-Fa moves northwest after landfall, its intensity is slightly greater than that of Typhoons Yagi and Rumbia, and the pressure gradient in front of Typhoon In-Fa is notably smaller, leading to its slow movement. Additionally, the precipitation distribution of Typhoon In-Fa differs from that of the other two typhoons, resulting in a weak asymmetry of wavenumber-1 diabatic heating, which indirectly affects its movement speed. Further analysis indicates that VWS can alter the typhoon’s structure, weaken its intensity, and ultimately impact its movement.
Performance implications of context switches no misses to dram.

Advances in microprocessor technology have resulted in the situation where CPU performance is improving faster than DRAM main memory performance. While it is true that current differences between CPU and DRAM speeds are not yet at the point where DRAM should be considered a slow peripheral, it is worthwhile considering the possibility o f current trends continuing long enough that DRAM does resemble a slow peripheral. Eventually, a cache miss to DRAM could resemble a main memory page fault to disk an expensive delay being experienced while the miss is handled. The logical approach may be to handle the miss as a page fault to disk is typically handled to perform a context switch. A basic requirement for context switching on DRAM accesses is a fast context switch. The RAMpage memory hierarchy, which handles the 1 2 cache as a paged memory and main memory as secondary storage, is the ideal platform for evaluating this idea. The reasons for this are twofold. Firstly, the RAMpage model, in treating the secondary cache as main memory, allows context-switching code to be pinned in SRAM, meaning that this code cannot cause references to DRAM once in SRAM. This ensures a faster context switch on average and avoids the complications o f recursion in the miss handler when switching on a miss causes a miss itself. Secondly, although the RAMpage hierarchy has been shown to substantially reduce the number o f references to DRAM, this benefit is offset by an increase in the time needed to handle a DRAM access. Thus there exists good potential for improved CPU utilization and therefore performance improvement through context switching. This is particularly true for large page sizes, in which fewer but more expensive misses occur. The objective o f this study is to investigate the feasibility of context switching as an approach to dealing with the increasing gap between CPU and DRAM performance and to evaluate the scalability o f this approach as the speed gap widens. This objective is achieved by using tracedriven simulation to model the performance o f the RAMpage hierarchy with context switching on page faults to DR, *M. Overall results show context switching on page faults improves RAMpage performance from a previous maximum of 17% over the standard hierarchy, to 25%. A secondary result shows that pinning code used to perform context switches in SRAM under the RAMpage hierarchy substantially improves average context switching time, particularly when large pages are used. Although a more detailed study would be needed to verify the merits o f this approach fully, this work demonstrates that context switching on a DRAM access is an approach worthy of consideration, particularly when looked at in the context o f the RAMpage model.
Bayesian View Synthesis and Image-Based Rendering Principles

In this paper, we address the problem of synthesizing novel views from a set of input images. State of the art methods, such as the Unstructured Lumigraph, have been using heuristics to combine information from the original views, often using an explicit or implicit approximation of the scene geometry. While the proposed heuristics have been largely explored and proven to work effectively, a Bayesian formulation was recently introduced, formalizing some of the previously proposed heuristics, pointing out which physical phenomena could lie behind each. However, some important heuristics were still not taken into account and lack proper formalization. We contribute a new physics-based generative model and the corresponding Maximum a Posteriori estimate, providing the desired unification between heuristics-based methods and a Bayesian formulation. The key point is to systematically consider the error induced by the uncertainty in the geometric proxy. We provide an extensive discussion, analyzing how the obtained equations explain the heuristics developed in previous methods. Furthermore, we show that our novel Bayesian model significantly improves the quality of novel views, in particular if the scene geometry estimate is inaccurate.
LipidWrapper: An Algorithm for Generating Large-Scale Membrane Models of Arbitrary Geometry

As ever larger and more complex biological systems are modeled in silico, approximating physiological lipid bilayers with simple planar models becomes increasingly unrealistic. In order to build accurate large-scale models of subcellular environments, models of lipid membranes with carefully considered, biologically relevant curvature will be essential. In the current work, we present a multi-scale utility called LipidWrapper capable of creating curved membrane models with geometries derived from various sources, both experimental and theoretical. To demonstrate its utility, we use LipidWrapper to examine an important mechanism of influenza virulence. A copy of the program can be downloaded free of charge under the terms of the open-source FreeBSD License from http://nbcr.ucsd. edu/lipidwrapper. LipidWrapper has been tested on all major computer operating systems.
Modestly Overweight Women Have Vascular Endothelial Dysfunction

Vascular endothelial dysfunction occurs early in the atherosclerotic process and is predictive of cardiovascular prognosis. However, the association between specific cardiovascular risk factors and endothelial dysfunction in women has not been well characterized. This study examined the relationship between endothelial dysfunction and cardiovascular risk factors (body mass index [BMI] ≥ 25 kg/m2, current smoking, age, diabetes, hypertension, hypercholesterolemia, and family history of early coronary heart disease) in a population of women that included those already being treated for risk factors.
Diabetes Mellitus as a Risk Factor for Open-Angle Glaucoma: A Systematic Review and Meta-Analysis

Objective To determine the association between diabetes mellitus (DM) and primary open-angle glaucoma (POAG). Methods This is a systematic review and meta-analysis of case-control and cohort studies. The literature search included two databases (PubMed and Embase) and the reference lists of the retrieved studies. Separate meta-analyses for case-control studies and cohort studies were conducted using random-effects models, with results reported as adjusted odds ratios (ORs) and relative risks (RRs), respectively. Results Thirteen studies—seven case-control studies and six population-based cohort studies—were included in this meta-analysis. The pooled RR of the association between DM and POAG based on the risk estimates of the six cohort studies was 1.40 (95% CI, 1.25–1.57). The pooled OR of the association between DM and POAG based on the risk estimates of the seven case-control studies was 1.49 (95% CI, 1.17–1.88). There was considerable heterogeneity among the case-control studies that reported an association between DM mellitus and POAG (P<0.001) and no significant heterogeneity among the cohort studies (P = 0.377). After omitting the case-control study that contributed significantly to the heterogeneity, the pooled OR for the association between DM and POAG was 1.35 (95% CI, 1.06–1.74). Conclusions Individuals with DM have an increased risk of developing POAG.
Comprehensive Utilization Technology of Aronia melanocarpa

Aronia melanocarpa fruit contains a variety of active ingredients, such as phenolic acids, anthocyanins, proanthocyanidins, etc. Relevant in vivo and in vitro studies have concluded that it has beneficial effects in terms of treating dyslipidemia, hypertension, glucose metabolism disorders, etc. This article discusses the nutritional value and food processing of Aronia melanocarpa and reviews the chemical components of Aronia melanocarpa and the pharmacological activities of related substances in order to summarize the chemical characteristics of the fruit and its development prospects. The process optimization of juice production, the impact of antioxidant capacity, and the comprehensive utilization of pomace in feed are discussed. This article provides a reference for future comprehensive application research and product development of Aronia melanocarpa.
Alu repeat analysis in the complete human genome: trends and variations with respect to genomic composition

MOTIVATION Transposon-derived Alu repeats are exclusively associated with primate genomes. They have gained considerable importance in the recent times with evidence of their involvement in various aspects of gene regulation, e.g. alternative splicing, nucleosome positioning, CpG methylation, binding sites for transcription factors and hormone receptors, etc. The objective of this study is to investigate the factors that influence the distribution of Alu repeat elements in the human genome. Such analysis is expected to yield insights into various aspects of gene regulation in primates. RESULTS Analysis of Alu repeat distribution for the human genome build 32 (released in January 2003) reveals that they occupy nearly one-tenth portion of the sequenced regions. Huge variations in Alu frequencies were seen across the genome with chromosome 19 being the most and chromosome Y being the least Alu dense chromosomes. The highlights of the analysis are as follows: (1). three-fourth of the total genes in the genome are associated with Alus. (2). Alu density is higher in genes as compared with intergenic regions in all the chromosomes except 19 and 22. (3). Alu density in human genome is highly correlated with GC content, gene density and intron density with GC content being major deterministic factor compared with other two. (4). Alu densities were correlated more with gene density than intron density indicating the insertion of Alus in untranslated regions of exons.
The effect of intervention based on Health Action Model to promote workers’ safe behavior in Isfahan Steel Company

Background: The worldwide concern for safety has created the need for new and effective methods to improve safety in the workplace. This study was designed to determine the effect of educational intervention based on Health Action Model on the safe behavior among workers in Isfahan Steel Company. Materials and Methods: This study was designed as a quasi-experimental research with experimental and control groups with pre- and post- intervention measurements. The experimental group received intervention based on the Health Action Model. The control group did not receive any intervention except that they participated in the current safety courses of the company. The sample size was 270 workers who were randomly selected and divided into two groups: Experimental (n = 135) and control (n = 135). Data were collected using a questionnaire and a checklist after and before the intervention and were analyzed. Based on the distribution of variables, parametric (t-test, paired t-test) or nonparametric (Chi-square, Wilcoxon) tests were utilized to analyze data. P value less than 0.05 was considered significant. Results: The results indicated that before intervention, the experimental and control groups were similar in model structures. After intervention, the mean scores of knowledge, attitude, and behaviors in relation to safety in the experimental group increased statistically significantly and the observed difference in the control group was not significant. The results also indicated that unsafe behaviors in the experimental group decreased following the educational intervention. This difference also was not statistically significant in the control group. Conclusion: The results showed that application of Health Action Model has an acceptable and positive influence on promoting safe behaviors, knowledge, normative system, and facilitating factors among workers in Isfahan Steel Company. It is, therefore, recommended that Health Action Model based intervention be used for other and similar industries.
SIRT1 activation confers neuroprotection in experimental optic neuritis.

PURPOSE Axonal damage and loss of neurons correlate with permanent vision loss and neurologic disability in patients with optic neuritis and multiple sclerosis (MS). Current therapies involve immunomodulation, with limited effects on neuronal damage. The authors examined potential neuroprotective effects in optic neuritis by SRT647 and SRT501, two structurally and mechanistically distinct activators of SIRT1, an enzyme involved in cellular stress resistance and survival. METHODS Experimental autoimmune encephalomyelitis (EAE), an animal model of MS, was induced by immunization with proteolipid protein peptide in SJL/J mice. Optic neuritis developed in two thirds of eyes with significant retinal ganglion cell (RGC) loss detected 14 days after immunization. RGCs were labeled in a retrograde fashion with fluorogold by injection into superior colliculi. Optic neuritis was detected by inflammatory cell infiltration of the optic nerve. RESULTS Intravitreal injection of SIRT1 activators 0, 3, 7, and 11 days after immunization significantly attenuated RGC loss in a dose-dependent manner. This neuroprotective effect was blocked by sirtinol, a SIRT1 inhibitor. Treatment with either SIRT1 activator did not prevent EAE or optic nerve inflammation. A single dose of SRT501 on day 11 was sufficient to limit RGC loss and to preserve axon function. CONCLUSIONS SIRT1 activators provide an important potential therapy to prevent the neuronal damage that leads to permanent neurologic disability in optic neuritis and MS patients. Intravitreal administration of SIRT1 activators does not suppress inflammation in this model, suggesting that their neuroprotective effects will be additive or synergistic with current immunomodulatory therapies.
Effects of Embryo Culture on Angiogenesis and Morphometry of Bovine Placentas During Early Gestation1

Abstract The objective of this study was to determine the effects of undefined and semidefined culture systems for in vitro embryo production on angiogenesis and morphometry of bovine placentas during early gestation. Blastocysts produced in vivo were recovered from superovulated Holstein cows and served as controls. Blastocysts produced in vitro were exposed to either serum-supplemented medium with cumulus cell coculture (in vitro-produced with serum; IVPS) or modified synthetic oviductal fluid medium without serum or coculture (mSOF). Single blastocysts from each production system were transferred into heifers. Fetuses and placentas were recovered on Day 70 of gestation. Cotyledonary tissues were obtained for quantification of vascular endothelial growth factor (VEGF) and peroxisome proliferator-activated receptor-gamma (PPARG) mRNA and protein. Samples of placentomes were prepared for immunocytochemistry and histological analysis. Placentas from the mSOF group were heavier and had the fewest placentomes, least placental fluid, and lowest placental efficiency (fetal weight/placental weight) compared with the in vivo and IVPS groups. There was no effect of embryo culture system on volume densities of fetal villi or maternal endometrium within placentomes. The volume density of fetal pyknotic cells was increased in placentomes in the mSOF group compared with the in vivo and IVPS groups. Placentomes in the mSOF group had decreased densities of blood vessels and decreased levels of VEGF mRNA in cotyledonary tissue. In conclusion, compared with placentas from embryos produced in vivo or in vitro using an undefined culture system, placentas from embryos produced in vitro using a semidefined culture system exhibited a greater degree of aberrant development of the placenta during early gestation.
Accuracy of Local Conduction Velocity Determination from Non-Fractionated Cardiac Activation Signals

Local velocity and direction of cardiac excitation spread can be estimated from four extra-cellular electric potential waveforms recorded simultaneously by closely-spaced electrodes. In this work, three methods for the determination of these parameters in case of non-fractionated electrograms were compared. Waveforms recorded during in-vitro experiments were analyzed in terms of their noise components. Noise according to the experimental environment was generated and added to noise-free waveforms obtained from computer simulations. For each of the three investigated methods the accuracy of the determined parameters velocity and direction was evaluated for three different noise levels and three types of propagation.