Miracle-dz/UniFAR-FTUs huggingface dataset:
Saving the Forest from the Trees: Expert Views on Funding Restoration of Northern Arizona Ponderosa Pine Forests through Registered Carbon Offsets

Ponderosa pine forests in the southwestern United States of America are overly dense, increasing the risk of high-intensity stand-replacing wildfires that result in the loss of terrestrial carbon and release of carbon dioxide, contributing to global climate change. Restoration is needed to restore forest structure and function so that a more natural regime of higher frequency, lower intensity wildfires returns. However, restoration has been hampered by the significant cost of restoration and other institutional barriers. To create additional revenue streams to pay for restoration, the National Forest Foundation supported the development of a methodology for the estimation and verification of carbon offsets generated by the restoration of ponderosa pine forests in northern Arizona. The methodology was submitted to the American Carbon Registry, a prominent carbon registry, but it was ultimately rejected. This paper presents a post-mortem examination of that methodology and the reasons it was rejected in order to improve the development of similar methodologies in the future. Using a mixed-methods approach, this paper analyzes the potential atmospheric carbon benefits of the proposed carbon offset methodology and the public and peer-reviewed comments from the associated review of the methodology. Results suggest a misalignment between the priorities of carbon registries and the context-specific ecosystem service benefits of this type of restoration; although findings confirm the potential for reductions in released carbon due to restoration, these results illuminate barriers that complicate registering these reductions as voluntary carbon offsets under current guidelines and best practices, especially on public land. These barriers include substantial uncertainty about the magnitude and timing of carbon benefits. Overcoming these barriers will require active reflexivity by the institutions that register voluntary carbon offsets and the institutions that manage public lands in the United States. Such reflexivity, or reconsideration of the concepts and purposes of carbon offsets and/or forest restoration, will allow future approaches to better align objectives for successfully registering restoration-based voluntary carbon offsets. Therefore, the results of this analysis can inform the development of future methodologies, policies, and projects with similar goals in the same or different landscapes.
Feature Disentanglement For Cross-Domain Retina Vessel Segmentation

Domain shift is regarded as a key factor affecting the robust-ness of many models. Recently, unsupervised auxiliary learning (e.g., input reconstruction) has been proposed to improve the model’s domain transferability and alleviate cross-domain performance degradation; however, in the paradigm of existing approaches, the features extracted from various tasks are shared, which mixes the domain-invariant features from the main task and domain-specific feature from the auxiliary task, leading to an imperfect learning. To solve this problem, we propose a novel unsupervised domain adaptation method - the Disentangled Reconstruction Neural Network (DRNN) - for cross-domain retina vessel segmentation. DRNN leverages two tandem nets and disentangles the domain-invariant features and the domain-specific features in the multi-task learning process. We perform extensive experiments on public retina datasets and our proposed DRNN outperforms the competitors by a significant margin to achieve state-of-the-art results pertaining to retina vessel segmentation.
Selective electrochemical sensor for bisphenol A quantification on carbon electrodes modified with graphitic mesoporous carbon

Owing to the unique electronic properties, high electrical conductivity, and high adsorption capacity of graphitic mesoporous carbon (GMC), a simple strategy was developed to alter the surface of glassy carbon electrodes with a thin layer of GMC. These modified electrodes were applied to detect bisphenol A (BPA) in wastewater samples due to the strong attraction between the GMC-modified surface and BPA. Electrochemical BPA sensing processes were evaluated using different electrochemical techniques, such as differential pulse voltammetry and cyclic voltammetry. For all electrochemical experiments, a distinguished anodic peak at ~ 0.55 V was observed, which was attributed to the enhanced electrochemical BPA oxidation on the surface of the GMC-modified electrode. In addition, the influence of scan rate and electrolyte pH on the electrochemical oxidation of BPA were studied in detail. The electrochemical sensor exhibited a reliable quantification of BPA in a wide range of BPA concentrations (i.e., 20 – 300 μM) and pH (i.e., 5.5 – 8.9) with a sensitivity of 2.93 μA μM−1 cm−2 and a detection limit of 59 nM. Finally, the pre-determined parameters were applied for the quantification of BPA in secondary-treated sewage. The results showed that the developed electrochemical sensor exhibited high BPA recovery in the range of 98.13 – 100.36 %. In summary, the developed electrochemical sensor showed satisfactory reproducibility and sensitivity for accurate BPA detection even in complex matrices, such as sewage.
Interactions and functions of RNA-binding proteins

Alongside several well-known modifications in DNA and proteins, more than 100 different types of chemical modification are also found in cellular RNAs. RNA modifications can influence the secondary structure and interactions of the RNAs that carry them and they can therefore play important roles in regulating the functions of the RNAs. For many RNA modifications, the enzymes that introduce them are known but the modification targets of several predicted modification enzymes remain to be identified. Interestingly, a particular modification, N6-methyladenosine (m6A), was recently found to be reversible and a group of proteins, termed “readers” that can recognise the modification often via a specialised RNA binding domain (YTH domain), have been identified. Such “reader” proteins have been shown to regulate the fate of RNAs according to their modification status, suggesting that this so called “epitranscriptome” is an additional layer of regulation of gene expression. In this study, cross-linking and analysis of cDNA (CRAC) was used to identify the RNAinteractome of the five human YTH domain-containing proteins, YTHDF1, YTHDF2, YTHDF3, YTHDC1, YTHDC2. To facilitate the mapping of the deep sequencing data obtained from CRAC experiments performed in human cells, a bioinformatic pipeline was adapted and further developed. Analysis of the CRAC data showed that YTHDF1, YTHDF2, YTHDF3 and YTHDC1 predominantly cross-link to mRNAs, which is in line with recently published reports describing functions for these proteins in mRNA degradation, alternative pre-mRNA splicing and enhancing mRNA translation. Interestingly, the CRAC analysis of YTHDC2 revealed a specific cross-linking site on the 18S ribosomal RNA and the association of this protein with ribosomal complexes was confirmed by independent experimental approaches. CRAC analysis using truncated versions of YTHDC2 suggested that the R3H RNA binding domain is required for stable association of this protein with the ribosome and in vitro anisotropy experiments demonstrated that the YTH domain of YTHDC2 has a higher affinity for m6A modifications present in the sequence context found in the ribosomal RNAs than the classical m6A consensus motif found in many mRNAs. Interestingly, immunoprecipitation experiments followed by mass spectrometry identified the cytoplasmic 5’-3’ exonuclease XRN1 as an interaction partner of YTHDC2. These data could suggest a model in which recognition of the m6A modification(s) on the ribosomal RNA by the YTH domain of YTHDC2 promotes RNA degradation by XRN1. Taken together, this study contributes to the understanding of the diverse functions that modification “reader” proteins can play in regulating RNA metabolism.
Job-related stress and tobacco smoking: A systematic review

Abstract Job-related stress may affect smoking initiation, progression, and intensity, therefore, it is important to have a better understanding of these associations to design targeted and effective workplace cessation programs. In this study, we aimed to synthesize existing literature concerning the relationship between job-related stress and tobacco use among adult workers (18 years and older). We searched articles indexed in six major databases (Scopus, PubMed, Embase, Web of Science, EBSCO, and Ovid) between 1997 and March 2020. We included cross-sectional and cohort studies published in English that examined self-reported smoking status or change in smoking status as exposure variables, and job-related status as the outcome variable consistent with the Demand Control Support and Effort-Reward Imbalance models. We searched the databases using combinations of keywords including “occupational stress,” or “job stress” or “work stress” or “job strain” and “smoking” or “tobacco use” or “tobacco consumption” or “cigarettes. ” Of 906 identified articles, 19 (n = 240,787 participants) were included in this review. Findings showed no clear association between job-related stress and smoking status (smoking vs nonsmoking) and smoking cessation. However, the findings suggest an association between job-related stress and changing smoking habits, toward heavier smoking. Our findings indicate that job-related stress may lead to increased smoking intensity.
Video Quality Assessment of User Generated Content: A Benchmark Study and a New Model

Recent years have witnessed an explosion of user-generated content (UGC) shared and streamed over the Internet. Accordingly, there is a great need for accurate video quality assessment (VQA) models for consumer or UGC videos to monitor, control, and optimize this vast content. Here we contribute to advancing the UGC-VQA problem by conducting a comprehensive evaluation of leading blind VQA (BVQA) models. Besides, we also created a new fusion-based BVQA model, which we dub the VIDeo quality EVALuator (VIDEVAL), that effectively balances the trade-off between performance and efficiency. Our experimental results show that VIDEVAL achieves state-of-the-art performance at a lower computational cost. We believe our reliable and reproducible benchmark will facilitate further research on deep learning-based BVQA modeling. An implementation of VIDEVAL has been made available online 1.1https://github.com/vztu/VIDEVAL_release
Comparing the safety and effectiveness of dedicated radiofrequency transseptal wires to electrified metal guidewires

Application of electrocautery to a metal guidewire is used by some operators to perform transseptal puncture (TSP). Commercially available dedicated radiofrequency (RF) guidewires may represent a better alternative. This study compares the safety and effectiveness of electrified guidewires to a dedicated RF wire.
Hermite–Hadamard-Type Inequalities for the Generalized Geometrically Strongly Modified 
 h
 -Convex Functions

Convexity theory becomes a hot area of research due to its applications in pure and applied mathematics, especially in optimization theory. The aim of this paper is to introduce a broader class of convex functions by unifying geometrically strong convex function with h convex functions. This new class of functions is called as generalized geometrically strongly modified h -convex functions. We established Hermite–Hadamard-type inequalities for the generalized geometrically strongly modified h -convex functions. Our results can be considered as generalization and extension of literature.
Influence of Selected Working Conditions on Electricity Generation in Bifacial Photovoltaic Modules in Polish Climatic Conditions

This paper discusses the conversion of solar irradiance energy into electricity. Double-sided (bifacial) panels are gaining increasing popularity in commercial applications due to the increased energy yield with a constant occupied mounting surface. However, the value of the additional energy yield produced by the back of the panel depends on several important factors. This paper presents the influence of working conditions on electricity generation in bifacial modules. This paper also investigates the influence of weather conditions, the module inclination angle, and the substrate beneath the panel surface on electricity generation. Fill factor and efficiency were calculated for each case included in the study scope. Based on the current voltage, power characteristics, and calculations, the module operation for different conditions was compared. It was observed that the optimal inclination angle to the surface is higher for the bifacial modules compared to the unilateral modules. The type of surface under the module has also been indicated to impact the amount of electricity generated. The additional energy yield associated with the panels’ rear side accounts for 2% to more than 35% of the total power generated by a photovoltaic (PV) module. The unit cost of electricity generation in the analyzed cases was also determined.
qTSL: A Multilayer Control Framework for Managing Capacity, Temperature, Stress, and Losses in Hybrid Balancing Systems

This work deals with the design and validation of a control strategy for hybrid balancing systems (HBSs), an emerging concept that joins battery equalization and hybridization with supercapacitors (SCs) in the same system. To control this system, we propose a two-layer model predictive control (MPC) framework. The first layer determines the optimal state-of-charge (SoC) reference for the SCs considering long load forecasts and simple pack-level battery models. The second MPC layer tracks this reference and performs charge and temperature equalization, employing more complex module-level battery models and short load forecasts. This division of control tasks into two layers, running at different time scales and model complexities, enables us to reduce computational effort with a small loss of control performance. Experimental validation in a small-scale laboratory prototype demonstrates the effectiveness of the proposed approach in reducing charge, temperature, and stress in the battery pack.
Highly Localized Point-by-Point Fiber Bragg Grating for Multi-Parameter Measurement

A three-parameter sensor based on a point-by-point fiber Bragg grating (PBP-FBG) is proposed. The fabricated sensor is 40 mm long. The spectrum loss at 1336.15 nm is selected to measure the surrounding liquid level. The sensitivity for liquid level sensing is −0.046 dB/mm. The temperature is measured using the Bragg dip shifts with sensitivity of 10.06 pm/ °C. The cut-off mode shift is used to measure the surrounding refractive index with sensitivity of 535.14 nm/RIU. As a benefit of femtosecond laser direct inscription fabrication, the grating length is controllable and the liquid level sensing range is expandable. This sensor provides a simple, reliable method for accurate liquid level, temperature and refractive index measurements in hazardous environments.
Forcing responsibility? Examining earnings management induced by mandatory corporate social responsibility: evidence from India

Purpose This study aims to investigate the impact of mandatory corporate social responsibility (CSR) spending legislation on the earnings management strategies of firms. Design/methodology/approach The authors use panel data regression models to analyze the data for this study. This study covers the post-legislation period, which spans over five years from the financial year ending March 2015 to the financial year ending March 2019. Findings The results show that firms manipulate accounting measures to avoid breaching the cut-off criteria for mandatory CSR. In particular, the results show that firms operating around the operating revenue threshold misclassify operating revenue as non-operating revenue. In contrast, firms operating around the net worth and net profit thresholds do downward real and accrual earnings management. These results are consistent with several robustness measures. Originality/value To the best of the authors’ knowledge, this is the first study that examines the impact of mandatory CSR spending on earnings management.
Drug Repurposing Against SARS-CoV-2: Targeting NSP16-NSP10 Interaction

Drug repurposing studies have played a crucial role in fighting the Covid-19 pandemic. Discovering a new drug molecule for disease takes a very long time. However, repurposing a drug molecule developed for another disease can accelerate new treatments for a disease. Thus, several drug repurposing studies were carried out targeting essential proteins for SARS-CoV-2. Nsp16-Nsp10 interaction was targeted in this work since this interaction is needed for SARS-CoV-2 to evade the human immune system. Therefore, docking calculations of approved 2126 drug molecules obtained from the Drugbank database were performed using the AutoDock Vina program. These docking calculations, drugs Ledipasvir Elbasvir, Venetoclax, Digitoxin, Irinotecan, Dexamethasone, Acetyldigitoxin, Dactinomycin, Lumacaftor, and Simeprevir, have the highest docking scores. Significant interactions for these drug molecules were presented. © 2021, Turkish Chemical Society. All rights reserved.
The Relationships Among Perceived Medical Quality, Well-Being Perception, And Behavioral Intention: A Comparison Between Domestic And Overseas Medical Destinations

ABSTRACT The niche market of medical tourism is growing in response to medical advancements and enhanced well-being. This research aims to examine the relationships among perceived quality of medical services, well-being perception, and behavioral intention between residents’ domestic country and in overseas medical destinations. It further compares these variables based on residents’ age groups. Convenience sampling was applied to invite Hong Kong residents at the aging center as well as members of associations and social media groups (e.g., Facebook) to participate in this study. An online questionnaire was sent to participants who have medical experiences in Hong Kong (domestic country) and/or overseas medical destinations. Results showed that residents had different perceptions of medical quality between domestic and overseas medical destinations. The factors of perceived staff and management quality and perceived facility quality influence well-being perception and consequently improve residents’ behavioral intention. However, no mean difference was found between perceived quality of medical services and well-being perception and behavioral intention by different age groups of residents. The theoretical contributions to the service quality perception literature and managerial implications were further discussed for future development.
PFC Single-Phase AC/DC Boost Converters: Bridge, Semi-Bridgeless, and Bridgeless Topologies

Power Factor Correction (PFC) single-phase AC/DC converters are used in several power electronics applications as full wave control rectifiers improving power quality and providing high standards of efficiency. Many papers dealing with the description or use of such topologies have been published in recent years; however, a review that describes and organizes their specific details has not been reported in the technical literature. Therefore, this paper presents an extensive review of PFC single-phase AC/DC converters operating with the Boost converter topology for low and medium voltage as well as and power appliances. A categorization of bridge, semi-bridgeless, and bridgeless, in accordance with the construction characteristics, was carried out in order to unify the technical terminology. Benefits and disadvantages are described and analyzed in detail. Furthermore, a comparison performance in terms of PFC, Total Harmonic Distortion (THD), power capacity, electromagnetic compatibility (EMC), number of elements, and efficiency is included.
Identification of the most effective muscles in landing impact forces

The aim of this study was to evaluate the role of the main lower limb muscles in increasing or decreasing each lower limb joint impact force during drop landing. To do so, the body was modeled by a four-link musculoskeletal model consisting of eight main Hill-type muscles. Different drop landing scenarios were modeled by changing the activation levels of the considered muscles. In each landing simulation, the impact GRF and impact joint forces were obtained. In order to compare and rank the muscles with respect to their effect on each impact force, a computationally feasible zero-one (off-on) muscle activation analysis was proposed. The proposed approach revealed important features regarding the relation between different impact forces and muscle activations. Specifically, the results can be interpreted in terms of the role that each muscle potentially plays in causing or preventing certain injuries. Moreover, the results obtained from the analysis were further used to classify the muscles into four categories, depending on the effect they have on each impact force. The proposed theoretical analysis is seen to be a promising tool in predicting the role of muscles and their order of importance in the generation of lower limb impact forces in landing, without the need for experimental tests.
rPPG-Based Spoofing Detection for Face Mask Attack using Efficientnet on Weighted Spatial-Temporal Representation

Face spoofing detection against paper attack and video-replay attack has been well studied, whereas detecting 3D face mask attack remains challenging. Remote photoplethysmography (rPPG) signal is a recently developed liveness clue for face-spoofing detection. The main challenge of existing rPPG-based methods is that the signal can be easily distorted by background noise or object motion. To address this problem, in this work, we propose an rPPG-based face-spoofing detection method using multiple regions of interests (ROIs) covering entire face, and emphasize the regions containing richer rPPG signals using larger weights. The rPPG signals of these regions form a weighted spatial-temporal map. In view of the discriminant power of EfficientNet over other deep convolutional neural networks, we propose a domain-specific EfficientNet as the classification method. Extensive experiments on two databases namely 3DMAD and HKBU-Mars V2 demonstrate the superior performance of the proposed method over state-of-the-art rPPG-based face-spoofing-detection algorithms.
Orthonormal Ultraspherical Operational Matrix Algorithm for Fractal–Fractional Riccati Equation with Generalized Caputo Derivative

Herein, we developed and analyzed a new fractal–fractional (FF) operational matrix for orthonormal normalized ultraspherical polynomials. We used this matrix to handle the FF Riccati differential equation with the new generalized Caputo FF derivative. Based on the developed operational matrix and the spectral Tau method, the nonlinear differential problem was reduced to a system of algebraic equations in the unknown expansion coefficients. Accordingly, the resulting system was solved by Newton’s solver with a small initial guess. The efficiency, accuracy, and applicability of the developed numerical method were checked by exhibiting various test problems. The obtained results were also compared with other recent methods, based on the available literature.