Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonpharmacologic and Pharmacologic Treatments of Adult Patients With Major Depressive Disorder: A Systematic Review and Network Meta-analysis for a Clinical Guideline by the American College of Physicians

BACKGROUND Primary care patients and clinicians may prefer alternative options to second-generation antidepressants for major depressive disorder (MDD). PURPOSE To compare the benefits and harms of nonpharmacologic treatments with second-generation antidepressants as first-step interventions for acute MDD, and to compare second-step treatment strategies for patients who did not achieve remission after an initial attempt with antidepressants. DATA SOURCES English-language studies from several electronic databases from 1 January 1990 to 8 August 2022, trial registries, gray literature databases, and reference lists to identify unpublished research. STUDY SELECTION 2 investigators independently selected randomized trials of at least 6 weeks' duration. DATA EXTRACTION Reviewers abstracted data about study design and conduct, participants, interventions, and outcomes. They dually rated the risk of bias of studies and the certainty of evidence for outcomes of interest. DATA SYNTHESIS 65 randomized trials met the inclusion criteria; eligible data from nonrandomized studies were not found. Meta-analyses and network meta-analyses indicated similar benefits of most nonpharmacologic treatments and antidepressants as first-step treatments. Antidepressants had higher risks for discontinuation because of adverse events than most other treatments. For second-step therapies, different switching and augmentation strategies provided similar symptomatic relief. The certainty of evidence for most comparisons is low; findings should be interpreted cautiously. LIMITATIONS Many studies had methodological limitations or dosing inequalities; publication bias might have affected some comparisons. In some cases, conclusions could not be drawn because of insufficient evidence. CONCLUSION Although benefits seem to be similar among first- and second-step MDD treatments, the certainty of evidence is low for most comparisons. Clinicians and patients should focus on options with the most reliable evidence and take adverse event profiles and patient preferences into consideration. PRIMARY FUNDING SOURCE American College of Physicians. (PROSPERO: CRD42020204703).
Edge extraction by FIRE operators

FIRE (fuzzy inference ruled by else-action) operators are a recently proposed family of fuzzy operators for image processing. After an introduction of the generalized structure of the FIRE edge extractor, in this paper it is shown how FIRE operators can be designed in order to comply with the following two requirements: 1) extraction of edges from a noiseless image by means of the simplest possible rule-base; 2) extraction of edges from a noisy image. Some experimental results show the performances of the proposed approach. <<ETX>>
Complex permittivity measurements and mixing laws of porous alumina

The dependence of the permittivity of porous alumina on the microstructure was studied. Three different algebraic mixing laws inaccurately predicted the measured effective permittivity of the three-phase material, which was alumina, air, and water. Finite-difference electrostatic simulations of physically realistic microstructures accurately predicted the experimental results. The electrostatic simulations also provided physical insight into the arrangement of water in the material and its significant effect on the effective permittivity.
Dietary intake of pistachios or mixed nuts results in higher systemic antioxidant capacity with minimal effects on bone in adolescent male rats

Abstract Nutrition is a key determinant of bone health and attainment of peak bone mass. Excess oxidative stress induces bone loss while increasing antioxidant capacity promotes protective effects on bone. Nuts are rich in antioxidants; therefore, we tested the hypothesis that compared to a control diet high in fat (40 % energy) and cholesterol, diets containing isocaloric amounts of pistachios (8·1 % g/g) or mixed nuts (7·5 % g/g) for 8 weeks would result in greater bone health in male adolescent (3 weeks; a state of continued skeletal growth) Sprague-Dawley rats. We found no difference in bone mechanical properties among groups. Tibial apparent density was ~5 % higher in the pistachio and mixed nuts groups v. control (P < 0·05) with no clear difference detected for the femur. Expressions of genes known to impact bone turnover and serum bone turnover biomarkers were unaffected by either diet relative to control. Serum antioxidant capacity was ~2-fold higher in the pistachio and mixed nuts groups compared with control (P < 0·05) but were similar between groups. Therefore, pistachios and mixed nuts may increase tibial density, in part, due to increasing antioxidant capacity. Longer dietary interventions may be necessary to elicit detectable changes in other bones (e.g. femur) and to detect potential mechanisms for the possible bone protective effects of nuts.
Postfire salvage logging alters impacts of recent wildfire on small mammal communities in summer

Wildfire is a natural ecosystem disturbance in forests in North America, yet fires are often at odds with human activity and affect the timber supply. Postfire salvage logging is common practice globally, but the impacts of salvage logging on wildlife, especially small mammal communities, remain unclear. We livetrapped small mammals to determine their population responses to wildfire and postfire salvage logging in central British Columbia, Canada. Postfire regenerating forest provided habitat for deer mice (Peromyscus maniculatus), southern red-backed voles (Myodes gapperi), and meadow voles (Microtus pennsylvanicus). Postfire salvage logging significantly reduced tree basal area and changed small mammal community structure by reducing southern red-backed vole populations and supporting mainly deer mice, a generalist species. Given the large scale and intensity of postfire salvage logging operations across the province, salvage logging has the potential to decrease vole populations and change small mammal communities across the province.
Computational Challenges and Approaches for Electric Vehicles

Researchers worldwide have become increasingly interested in developing computational approaches to handle challenges facing electric vehicles (EVs) in recent years. This article examines the challenges and future potential of computational approaches for problems such as EV routing, EV charging scheduling (EVCS), EV charging station (CS) placement, CS sizing, and energy or load management. In addition, a summary of the fundamental mathematical models employed to solve the EV computational problems is presented. We cover recent work on computational solutions for various EV problems utilizing single and coupled mathematical models. Finally, we also examine potential research avenues that researchers could pursue to realize the objective of environment-friendly transportation and smart grids (SGs).
Accurately Measuring Contention in Mesh NoCs in Time-Sensitive Embedded Systems

The computing capacity demanded by embedded systems is on the rise as software implements more functionalities, ranging from best-effort entertainment functions to performance-guaranteed safety-related functions. Heterogeneous manycore processors, using wormhole mesh (wmesh) Network-on-Chips (NoCs) as the main communication means, and contention block among applications, are increasingly considered to deliver the required computing performance. Most research efforts on software timing analysis have focused on deriving bounds (estimates) to the contention that tasks can suffer when accessing wmesh NoCs. However, less effort has been devoted to an equally important problem, namely, accurately measuring the actual contention tasks generate each other on the wmesh which is instrumental during system validation to diagnose any software timing misbehavior and determine which tasks are particularly affected by contention on specific wmesh routers. In this article, we work on the foundations of contention measuring in wmesh NoCs and propose and explain the rationale of a golden metric, called task PairWise Contention (PWC). PWC allows ascribing the actual share of the contention a given task suffers in the wmesh to each of its co-runner tasks at packet level. We also introduce and formalize a Golden Reference Value (GRV) for PWC that specifically defines a criterion to fairly break down the contention suffered by a task among its co-runner tasks in the wmesh. Our evaluation shows that GRV effectively captures how contention occurs by identifying the actual core (task) causing contention and whether contention is caused by local or remote interference in the wmesh.
Community Enhanced Link Prediction in Dynamic Networks

The growing popularity of online social networks is quite evident nowadays and provides an opportunity to allow researchers in finding solutions for various practical applications. Link prediction is the technique of understanding network structure and identifying missing and future links in social networks. One of the well-known classes of methods in link prediction is a similarity-based method, which uses local and global topological information of the network to predict missing links. Some methods also exist based on quasi-local features to achieve a trade-off between local and global information on static networks. These quasi-local similarity-based methods are not best suited for considering community information in dynamic networks, failing to balance accuracy and efficiency. Therefore, a community enhanced framework is presented in this paper to predict missing links on dynamic social networks. First, a link prediction framework is presented to predict missing links using parameterized influence regions of nodes and their contribution in community partitions. Then, a unique feature set is generated using local, global, and quasi-local similarity-based as well as community information-based features. This feature set is further optimized using scoring-based feature selection methods to select only the most relevant features. Finally, four machine learning-based classification models are used for link prediction. The experiments are performed on six well-known dynamic networks and three performance metrics, and the results demonstrate that the proposed method outperforms the state-of-the-art methods.
Weak-type estimates for the modified Hankel transform

where Jα is the Bessel function of the first kind of order α. For any bounded functionm on R+ the multiplier operator Tm is defined by Hα(Tmf) = mHαf. We will obtain a multiplier theorem in terms of the spaces WBVs,λ of functions of weak bounded variation which were introduced by Gasper and Trebels [4]. The condition which defines these spaces is an extension of the Hörmander condition [8] for fractional derivatives. For 1 ≤ s <∞, λ > 0 a bounded continuous function m on R+ belongs to WBVs,λ if it satisfies
SIMO detection schemes for underwater optical wireless communication under turbulence

In underwater optical wireless communication (UOWC), a channel is characterized by abundant scattering/absorption effects and optical turbulence. Most previous studies on UOWC have been limited to scattering/absorption effects. However, experiments in the literature indicate that underwater optical turbulence (UOT) can cause severe degradation of UOWC performance. In this paper, we characterize an UOWC channel with both scattering/absorption and UOT taken into consideration, and a spatial diversity receiver scheme, say a single-input–multiple-output (SIMO) scheme, based on a light-emitting-diode (LED) source and multiple detectors is proposed to mitigate deep fading. The Monte Carlo based statistical simulation method is introduced to evaluate the bit-error-rate performance of the system. It is shown that spatial diversity can effectively reduce channel fading and remarkably extend communication range.
Modeling and analysis of reverse-fixed piezoelectric tube fiber scanner for two-photon endomicroscopy

Miniature two-photon microscopy combines the two-photon excitation principle and is more lightweight and flexible, allowing it to be applied to freely behaving animals. The piezoelectric tube (PZT) fiber scanner is the key actuated component in miniature fiber-scanning two-photon endomicroscopy (TPEM). In this paper, we use multi-physics field finite element simulation to model and analyze a reverse-fixed PZT fiber scanner for TPEM. The simulation results show that the first two resonant frequencies of the PZT fiber scanner are 163.6 Hz and 757.9 Hz, respectively. At the first two resonant points, the PZT fiber scanner scan range are 0.078 mm and 0.68 mm, respectively. Theoretical guidance for frequency selection of the reverse-fixed PZT fiber scanner is provided by these simulation results.
A scanning target profile monitor for the slow extracted beam at the AGS

The purpose of this new instrument is for probing beam halo and obtaining beam profiles of the resonant extracted beam at the AGS. The device described is a prototype version, to obtain data and prepare for a more permanent device. The goals of the permanent device are to allow emittances of low current, but high intensity slowly extracted beams to be accurately measured and to have a diagnostic for probing the wings of the beam distribution. The device works on secondary emission from thin targets as well as scattering into two scintillator telescopes. The targets are movable over the entire aperture at the device.
A review of underwater digital hologram systems

With the development of underwater resources and underwater exploration, there is an urgent need for high-precision, real-time, and three-dimensional observation of underwater detection methods. As one of the new technologies of underwater detection, underwater digital holographic technology can fill the gap in underwater high-precision three-dimensional observation and detection, so the research and development teams have successively carried out the research and development of underwater digital holographic systems. This paper briefly introduces the application and types of underwater digital holographic technology, and reviews the design and algorithm of different underwater digital holographic systems.
Research on spectral confocal displacement measurement method based on machine learning

The chromatic confocal technology (CCT) uses the dispersion principle to establish an accurate encoding relationship between the spatial position and the axial focus point of each wavelength to achieve non-contact measurement. The accuracy of the measurement results is affected by the peak wavelength extraction accuracy. The flexible and adaptable characteristics of machine learning techniques are used to model the spectral wavelength and light intensity nonlinearly, establish the response relationship between input wavelength and output normalized light intensity, and refit the spectral curve distribution. In this paper, we apply the network of regression aspect of machine learning, Extreme Learning Machine (ELM), Back Propagation Neural Network (BPNN), and Genetic Algorithm optimized Back Propagation Neural Network(GA-BPNN) to fit the spectral response of the system to accurately locate the peak wavelength and compare it with the traditional peak extraction methods of Gaussian fitting, polynomial fitting, and center of the mass method to verify that the machine learning method used is significantly better than the traditional peak extraction methods in terms of peak extraction accuracy. The ELM network is the best among the three networks, with a peak extraction error of only 0. 04μm and a Root Mean Square Error(RMSE) of only 6.8×10-4. The analysis of calibration experiments, resolution, and stability experiments found that the ELM algorithm was found to have the shortest calculation time, and the system measurement resolution was explored through the ELM algorithm to be about 2μm. The research results of this paper have contributed to the improvement of the system measurement accuracy and measurement efficiency.
A Visual Diagnostic Tool for Causal Inference

Abstract:Rosenbaum and Rubin (1983) suggested a visual representation, that can be used as a diagnostic tool, for examining whether the relationships between confounders and outcomes are sufficiently controlled, or whether there is a more complex relationship that requires further adjustment. This short commentary highlights this simple tool, providing an example of its utility along with relevant R code.
Thermal Performance Enhancement of Thermosyphon Heat Pipe with Binary Working Fluids

Thermal performance of a thermosyphon heat pipe using ethanol-water and TEG-water with variations of parameters such as the mixture content, the pipe diameter, and the working temperature have been studied in this research work. From the experiments, it is found that at low temperature of heat source (less than 80oC), the ethanol-water mixture has a higher heat transfer rate than that of water and close to that of pure ethanol. In the case of TEG-water mixture, the heat transfer rate of the thermosyphon varies with the content of TEG in the mixture, and it is found that TEG in the mixture can increase the critical heat flux due to the flooding limit in a small thermosyphon. The boiling equation of Rohsenow and the condensation equation of Nusselt are modified to predict the heat transfer coefficients inside the thermosyphon. For the mixtures, the weighted average of the heat transfer coefficient of each component can be used to predict the total heat transfer coefficient. Furthermore, it is found that Fag.
Ionic behaviours in silicone oil

Transient currents in silicone oils with various kinematic viscosities were measured by a thin film tunnel emitter method. A current peak or shoulder which showed the carrier transit time was observed after application of a rectangular pulse voltage to a tunnel emitter. The carrier mobility calculated from these transit times varied from 10-3 to 10-7 cm2 V-1 s-1 with temperature and kinematic viscosity. In the viscous range lower than 100 cSt Walden's rule held good in the relation of carrier mobility and viscosity, while over the viscous range higher than 100 cSt the carrier mobility and its activation energy were nearly constant in spite of variation of viscosity.
Variance component estimates, phenotypic characterization, and genetic evaluation of bovine congestive heart failure in commercial feeder cattle

The increasing incidence of bovine congestive heart failure (BCHF) in feedlot cattle poses a significant challenge to the beef industry due to economic loss, reduced performance, and reduced animal welfare attributed to cardiac insufficiency in growing animals. Changes to cardiac morphology as well as abnormal pulmonary arterial pressure (PAP) in purebred cattle of mostly Angus ancestry have been extensively characterized over the past 30 years. However, congestive heart failure affecting cattle late in the feeding period has been an increasing problem over time and tools are needed for the industry to address the rate of mortality in the feedlot. At harvest, a population of 32,763 commercial fed cattle was phenotyped for cardiac morphology with associated production data collected from feedlot processing to harvest at a single feedlot and packing plant in the Pacific Northwest. A sub-population of 5,001 individuals were selected for low-pass genotyping to estimate variance components and genetic correlations between heart score and the production traits observed during the feeding period. At harvest, the incidence of a heart score of 4 or 5 in this population was approximately 4.14%, indicating a significant proportion of feeder cattle are at an increased risk of cardiac mortality before harvest. The heart scores were also significantly and positively correlated with the percentage Angus ancestry observed by genomic breed percentage analysis. The heritability of heart score measured as a binary (scores 1 and 2 = 0, scores 4 and 5 = 1) trait was 0.356 in this population, which indicates the development of a selection tool to reduce the risk of congestive heart failure in the form of an EPD (expected progeny differences) is feasible. Genetic correlations of heart score with growth traits and feed intake were moderate and positive (0.289 to 0.460). Genetic correlations between heart score and backfat and marbling score were -0.120 and -0.108, respectively. Significant genetic correlation to traits of high economic importance in existing selection indexes may explain the increased rate of congestive heart failure observed over time. These results indicate there is potential to implement heart score observed at harvest as a phenotype under selection in genetic evaluation in order to reduce feedlot mortality due to cardiac insufficiency and improve overall cardiopulmonary health in feeder cattle.
The more, the merrier: multivariate phase synchronization methods excel pairwise ones in estimating functional brain connectivity from reconstructed neural sources

The estimation of functional connectivity (FC) from electro-(EEG) or magnetoencephalographic (MEG) recordings suffers from low spatial resolution, being one of the reasons for the reduced number of sensors compared to the number of reconstructed sources of activity. This problem can be avoided by estimating FC between larger regions instead of individual sources. However, combining all the sources in each area to produce a single time series per region is far from trivial. We have used simultaneous EEG/MEG data from 11 participants and compared the FC estimates from both techniques by using different multivariate approaches. Since the underlying generators are identical for EEG and MEG, the more similar the FC estimation from both techniques is, the more accurate it is likely to be. The results show that using either the average or the root-mean-square of the bivariate source-to-source FC estimates consistently outperforms the use of a representative time series from each area. We concluded that the reconstructed activity in each brain region is too complex to be reduced to a single representative time series and that full multivariate approaches must be used to describe between-area FC from electrophysiological recordings accurately. Moreover, the high correlation between the FC values estimated from EEG and MEG suggests that the results found in the high-sensitivity, low-noise MEG can be transferable to the more affordable EEG, at least when high-quality source reconstruction is used.
Defining the contribution of microRNA-specific slicing Argonautes in animals

microRNAs regulate gene expression through interaction with an Argonaute protein family member. While some members of this protein family retain an enzymatic activity capable of cleaving RNA molecules complementary to Argonaute-bound small RNAs, the role of the slicing activity in the canonical microRNA pathway is still unclear in animals. To address the importance of slicing Argonautes in animals, we created Caenorhabditis elegans strains, carrying catalytically dead endogenous ALG-1 and ALG-2, the only two slicing Argonautes essential for the miRNA pathway in this animal model. We observe that the loss of ALG-1 and ALG-2 slicing activity affects overall animal fitness and causes phenotypes, reminiscent of miRNA defects, only when grown and maintained at restrictive temperature. Furthermore, the analysis of global miRNA expression shows that the catalytic activity of ALG-1 and ALG-2 differentially regulate the level of specific subsets of miRNAs in young adults. We also demonstrate that altering the slicing activity of those miRNA-specific Argonautes does not result in any defect in the production of canonical miRNAs. Together, these data support that the slicing activity of miRNA- specific Argonautes function to maintain the levels of a set of miRNAs for optimal viability and fitness in animals particularly exposed to specific growing conditions.