Miracle-dz/UniFAR-FTUs huggingface dataset:
Porous Electropolymerized Films of Ruthenium Complex: Photoelectrochemical Properties and Photoelectrocatalytic Synthesis of Hydrogen Peroxide

The photoelectrochemical cells (PECs) performing high-efficiency conversions of solar energy into both electricity and high value-added chemicals are highly desirable but rather challenging. Herein, we demonstrate that a PEC using the oxidatively electropolymerized film of a heteroleptic Ru(II) complex of [Ru(bpy)(L)2](PF6)2 Ru1 {bpy and L stand for 2,2′-bipyridine and 1-phenyl-2-(4-vinylphenyl)-1H-imidazo[4,5-f][1,10]phenanthroline respectively}, polyRu1, as a working electrode performed both efficient in situ synthesis of hydrogen peroxide and photocurrent generation/switching. Specifically, when biased at −0.4 V vs. saturated calomel electrode and illuminated with 100 mW·cm−2 white light, the PEC showed a significant cathodic photocurrent density of 9.64 μA·cm−2. Furthermore, an increase in the concentrations of quinhydrone in the electrolyte solution enabled the photocurrent polarity to switch from cathodic to anodic, and the anodic photocurrent density reached as high as 11.4 μA·cm−2. Interestingly, in this single-compartment PEC, the hydrogen peroxide yield reached 2.63 μmol·cm−2 in the neutral electrolyte solution. This study will serve as a guide for the design of high-efficiency metal-complex-based molecular systems performing photoelectric conversion/switching and photoelectrochemical oxygen reduction to hydrogen peroxide.
A copula‐based nonstationary frequency analysis for the 2012–2015 drought in California

Using a multicentury reconstruction of drought, we investigate how rare the 2012–2015 California drought is. A Bayesian approach to a nonstationary, bivariate probabilistic model, including the estimation of copula parameters is used to assess the time‐varying return period of the current drought. Both the duration and severity of drought exhibit similar multicentury trends. The period from 800 to 1200 A.D. was perhaps more similar to the recent period than the period from 1200 to 1800 A.D. The median return period of the recent drought accounting for both duration and severity, varies from approximately 667–2652 years, if the model parameters from the different time periods are considered. However, we find that the recent California drought is of unprecedented severity, especially given the relatively modest duration of the drought. The return period of the severity of the recent drought given its 4 year duration is estimated to be nearly 21,000 years.
Effects of Wooden Breast Myopathy on Meat Quality Characteristics of Broiler Pectoralis Major Muscle and Its Changes with Intramuscular Connective Tissue

This study aimed to investigate the effect of wooden breast (WB) myopathy on chemical composition, meat quality attributes and physiochemical characteristics of intramuscular connective tissue (IMCT) of broiler pectoralis major (PM) muscle. Thirty-six fillets were classified into varying degrees of WB condition, including normal, moderate and severe. Results show that WB myopathy altered the collagen profile in PM muscle by increasing total collagen content and decreasing collagen solubility. The composition of macromolecules in IMCT, including hydroxylysyl pyridoxine cross-linking, decorin and glycosaminoglycans, were increased with the severity of WB myopathy. Differential scanning calorimetry analysis indicated higher denaturation temperatures and lower denaturation enthalpy of IMCT for WB. Secondary structures of α-helix and β-sheet in the IMCT of WB were changed to β-turn and random coil. In addition, chemical composition and meat quality attributes showed a correlation with collagen profile and IMCT characteristics. Overall, this study emphasizes the effect of WB myopathy on IMCT and their contributions to meat quality variation.
Robust Cooperative Localization With Failed Communication and Biased Measurements

Cooperative Localization (CL) plays a crucial role in achieving precise localization without relying on localization sensors. However, the performance of CL can be significantly affected by failed communication and biased measurements. This letter presents a robust decentralized CL method that addresses these challenges effectively. To tackle the issue of communication failures, the proposed method adopts a multi-centralized framework that separates the measurement and communication processes. This decoupling allows each robot to utilize measurement information even in the absence of communication. Additionally, an reasonable state estimation method for other robots is proposed by approximating the actual input velocity model of unknown states and then propagating them using the motion model. To handle biased measurements, the method incorporates the M-estimation technique into the measurement update process. This technique weights the received measurements according to their reliability, mitigating the impact of biased measurements on the estimation accuracy. Simulation experiments have been conducted to validate the effectiveness of the proposed method in challenging scenarios.
Durability Improvement of Pumice Lightweight Aggregate Concrete by Incorporating Modified Rubber Powder with Sodium Silicate

To improve the durability of pumice lightweight aggregate concrete applied in cold and drought areas, sodium silicate-modified waste tire rubber powder is used to treat the pumice lightweight aggregate concrete. The pumice lightweight aggregate concrete studied is mainly used in river lining structures. It will be eroded by water flow and the impact of ice and other injuries, resulting in reduced durability, and the addition of modified rubber will reduce the damage. The durability, including mass loss rate and relative dynamic elastic modulus of pumice lightweight aggregate concrete with different sodium silicate dosages and rubber power particle sizes, is analyzed under freeze-thaw cycles, and the microstructure is further characterized by using microscopic test methods such as nuclear magnetic resonance tests, ultra-depth 3D microscope tests, and scanning electron microscopy tests. The results showed that the durability of pumice lightweight aggregate concrete is significantly improved by the addition of modified waste tire rubber powder, and the optimum durability is achieved when using 2 wt% sodium silicate modified rubber power with a particle size of 20, and then the mass loss rate decreased from 4.54% to 0.77% and the relative dynamic elastic modulus increased from 50.34% to 64.87% after 300 freeze-thaw cycles compared with other samples. The scanning electron microscopy test result showed that the surface of rubber power is cleaner after the modification of sodium silicate, so the bonding ability between rubber power and cement hydration products is improved, which further improved the durability of concrete under the freeze-thaw cycle. The results of the nuclear magnetic resonance test showed that the pore area increased with the number of freeze-thaw cycles, and the small pores gradually evolved into large pores. The effect of sodium silicate on the modification of rubber power with different particle sizes is different. After the treatment of 2 wt% sodium silicate, the relationship between the increased rate of pore area and the number of freezing-thawing cycles is 23.8/times for the pumice lightweight aggregate concrete containing rubber power with a particle size of 20 and 35.3/times for the pumice lightweight aggregate concrete containing a particle size of 80 rubber power, respectively.
Quality Indicators and Clinical Outcomes of Acute Stroke: Results from a Prospective Multicenter Registry in Greece (SUN4P)

Aim: The Stroke Units Necessity for Patients (SUN4P) project aims to provide essential data on stroke healthcare in Greece. Herein, we present results on established quality indicators and outcomes after first-ever stroke occurrences. Methods: This prospective multicenter study included consecutive patients admitted to nine hospitals across Greece in 2019–2021. Descriptive statistics were used to present patients’ characteristics, key performance measures and stroke outcomes. Results: Among 892 patients, 755 had ischemic stroke (IS) (mean age 75.6 ± 13.6, 48.7% males) and 137 had hemorrhagic stroke (HS) (mean age 75.8 ± 13.2, 57.7% males). Of those, 15.4% of IS and 8% of HS patients were treated in the acute stroke unit (ASU) and 20.7% and 33.8% were admitted to the intensive care unit (ICU) or high-dependency unit (HDU), respectively. A total of 35 (4.6%) out of 125 eligible patients received intravenous alteplase with a door-to needle time of 60 min (21–90). The time to first scan for IS patients was 60 min (31–105) with 53.2% undergoing a CT scan within 60 min post presentation. Furthermore, 94.4% were discharged on antiplatelets, 69.8% on lipid-lowering therapy and 61.6% on antihypertensives. Oral anticoagulants (OAC) were initiated in 73.2% of the 153 IS patients with atrial fibrillation (AF). Among the 687 IS patients who survived, 85.4% were discharged home, 12% were transferred to rehabilitation centers, 1.2% to nursing homes and 1.3% to another hospital. Conclusions: The SUN4P Registry is the first study to provide data from a prospectively collected cohort of consecutive patients from nine representative national hospitals. It represents an important step in the evaluation and improvement of the quality of acute stroke care in Greece.
Proficiency affects intra- and inter-regional patterns of language control in second language processing

ABSTRACT This study examines the use of cognitive control during second language (L2) processing by adult language learners. Although cognitive control has been acknowledged as an important component of language processing for years, its conception was as a top-down mechanism of inhibition. Our functional MRI study investigated the correlates of both top-down and bottom-up control as well as semantic decision-making in a group of Spanish learners who varied in proficiency. We observed that multivariate activity patterns were better classified in high proficiency learners during the semantic decision task in regions associated with both top-down and bottom-up control. Additionally, we found that connectivity between these control regions was more organised in high than in low proficiency learners. These findings provide support for the relevance of the distinction between top-down and bottom-up control to language learning. The implications of this distinction are discussed with respect to the current theories of L2 acquisition.
Deciphering the Role of the Gut Microbiota in Exposure to Emerging Contaminants and Diabetes: A Review

Emerging pollutants, a category of compounds currently not regulated or inadequately regulated by law, have recently become a focal point of research due to their potential toxic effects on human health. The gut microbiota plays a pivotal role in human health; it is particularly susceptible to disruption and alteration upon exposure to a range of toxic environmental chemicals, including emerging contaminants. The disturbance of the gut microbiome caused by environmental pollutants may represent a mechanism through which environmental chemicals exert their toxic effects, a mechanism that is garnering increasing attention. However, the discussion on the toxic link between emerging pollutants and glucose metabolism remains insufficiently explored. This review aims to establish a connection between emerging pollutants and glucose metabolism through the gut microbiota, delving into the toxic impacts of these pollutants on glucose metabolism and the potential role played by the gut microbiota.
Optimization of soybean physiochemical, agronomic, and genetic responses under varying regimes of day and night temperatures

Soybean is an important oilseed crop worldwide; however, it has a high sensitivity to temperature variation, particularly at the vegetative stage to the pod-filling stage. Temperature change affects physiochemical and genetic traits regulating the soybean agronomic yield. In this regard, the current study aimed to comparatively evaluate the effects of varying regimes of day and night temperatures (T1 = 20°C/12°C, T2 = 25°C/17°C, T3 = 30°C/22°C, T4 = 35°C/27°C, and T5 = 40°C/32°C) on physiological (chlorophyll, photosynthesis, stomatal conductance, transpiration, and membrane damage) biochemical (proline and antioxidant enzymes), genetic (GmDNJ1, GmDREB1G;1, GmHSF-34, GmPYL21, GmPIF4b, GmPIP1;6, GmGBP1, GmHsp90A2, GmTIP2;6, and GmEF8), and agronomic traits (pods per plant, seeds per plant, pod weight per plant, and seed yield per plant) of soybean cultivars (Swat-84 and NARC-1). The experiment was performed in soil plant atmosphere research (SPAR) units using two factorial arrangements with cultivars as one factor and temperature treatments as another factor. A significant increase in physiological, biochemical, and agronomic traits with increased gene expression was observed in both soybean cultivars at T4 (35°C/27°C) as compared to below and above regimes of temperatures. Additionally, it was established by correlation, principal component analysis (PCA), and heatmap analysis that the nature of soybean cultivars and the type of temperature treatments have a significant impact on the paired association of agronomic and biochemical traits, which in turn affects agronomic productivity. Furthermore, at corresponding temperature regimes, the expression of the genes matched the expression of physiochemical traits. The current study has demonstrated through extensive physiochemical, genetic, and biochemical analyses that the ideal day and night temperature for soybeans is T4 (35°C/27°C), with a small variation having a significant impact on productivity from the vegetative stage to the grain-filling stage.
An investigation of the associations between stigma, self-compassion, and pain outcomes during treatment based on Acceptance and Commitment Therapy for chronic pain

Introduction Stigma adversely affects people with chronic pain. The qualities within self-compassion may be particularly useful for buffering the impact of stigma on people with pain. In the context of an Acceptance and Commitment Therapy-based (ACT) treatment for chronic pain, this study investigated the association between changes in stigma and self-compassion and pain outcomes, and the potential moderating role of self-compassion on the association between stigma and pain outcomes. Materials and methods Five-hundred and nineteen patients completed standardized self-report questionnaires of stigma, self-compassion, psychological flexibility, pain intensity and interference, work and social adjustment, and depression symptoms at the start of an interdisciplinary ACT-based treatment for chronic pain. The same measures were completed at post-treatment (n = 431). Results The results indicated that key pain outcomes and self-compassion significantly improved during treatment, but stigma did not. Changes in stigma and self-compassion were significantly negatively correlated and changes in these variables were associated with improvements in treatment outcomes. There were significant main effects of stigma and self-compassion for many of the pre- and post-treatment regression models when psychological flexibility was not controlled for, but self-compassion did not moderate the association between stigma and pain outcomes. Stigma remained significant when psychological flexibility variables were controlled for, while self-compassion did not. Discussion The findings add to our conceptual understanding of the inter-relationships between stigma, self-compassion, and psychological flexibility and can contribute to treatment advancements to optimally target these variables.
SPSO-EFVM: A Particle Swarm Optimization- Based Ensemble Fusion Voting Model for Sentence-Level Sentiment Analysis

Sentiment analysis has received incremental growth in recent years for emerging applications, including human-robot integration, social platforms monitoring, and decision-support systems. Several neural or transformer model-based solutions have been provided in the field of sentiment analysis that relies on the decision of a single classifier or neural model. These are erroneous to encode contextual information into appropriate dialogues and increase extra computational cost and time. Hence, we proposed a compact and parameter-effective Particle Swarm Optimization-based Ensemble Fusion Voting Model (PSO-EFVM) that exploited the combined properties of four ensemble techniques, namely Adaptive-Boost, Gradient-Boost, Random-Forest, and Extremely-Randomized Tree with Particle Swarm Optimization (PSO)-based hyperparameter selection. The proposed model is investigated on five cross-domain datasets after applying the foremost initialization and feature extraction using Information Gain (IG). It employs adaptive and gradient learning to incorporate the automatic attribute selection with the arbitrary loss function optimization. In short, a generalized two-block composite classifier is designed to perform context compositionality and sentiment classification. A population-based meta-heuristic optimization PSO is applied to each base ensemble learner that calculates weights for the best parameter selection. Comprehensive investigations of different domains reveal the superiority of the proposed PSO-EFVM over established baselines and the latest state-of-the-art models.
A STUDY ON THE PREFERRED TRAVEL BEHAVIORS OF OUTBOUND TOURISTS BASED ON PERCEPTION OF TRAVEL RISKS——Case on Beijing Tourists

From the view of perceived risks of outbound tourists, the social security issues are the war, the terrorism, politics, war crimes and so on;the public health issues are tourism and infectious diseases, public health incidents and so on;the natural disasters are earthquakes, floods, volcanoes, tsunamis and so on;the measure of travel prices, the price of foreign exchange and the fluctuations of the exchange rate.All these pose threat to the security of the outbound tourists.All the factors together constitute the risks of tourism;furthermore any of the factors will affect the tourist perception of security of the tourism destination.Due to the lack of travel risk perception and understanding, tourism industry often makes errors in dealing with the travel risks.The investigation of this study is conducted among Beijing residents who are above 18 years old, mainly from group tourism and individual tourism.The group tourism survey is conducted among the outbound tourists through Beijing International Travel Agency, and the individual tourism survey is conducted randomly among individual tourists at Beijing International Airport during waiting time.The survey lasted 50 days from January 10 to February 29, 2008.Through empirical investigation, this study analyzed the relationship between travel risk perception and preferred travel behavior.The results revealed that factor analysis extracted 3 travel risk perception factors(terrorism war risk factor, public health risk factor, natural disaster financial risk factor);4 preferred travel behavior factors(preferred exotic culture, preferred similar culture, preferred tourism service, preferred popularization). Multi-regression analysis tested that travel risk factor has a negative impact on preferred travel behavior, it means when tourists perceive the tourism risks, they will cancel the tourism activities for self-safety.In the end, the study limitation and future research recommendations were discussed.
Is ChatGPT an Effective Tool for Providing Dietary Advice?

The chatbot Chat Generative Pretrained Transformer (ChatGPT) is becoming increasingly popular among patients for searching health-related information. Prior studies have raised concerns regarding accuracy in offering nutritional advice. We investigated in November 2023 ChatGPT’s potential as a tool for providing nutritional guidance in relation to different non-communicable diseases (NCDs). First, the dietary advice given by ChatGPT (version 3.5) for various NCDs was compared with guidelines; then, the chatbot’s capacity to manage a complex case with several diseases was investigated. A panel of nutrition experts assessed ChatGPT’s responses. Overall, ChatGPT offered clear advice, with appropriateness of responses ranging from 55.5% (sarcopenia) to 73.3% (NAFLD). Only two recommendations (one for obesity, one for non-alcoholic-fatty-liver disease) contradicted guidelines. A single suggestion for T2DM was found to be “unsupported”, while many recommendations for various NCDs were deemed to be “not fully matched” to the guidelines despite not directly contradicting them. However, when the chatbot handled overlapping conditions, limitations emerged, resulting in some contradictory or inappropriate advice. In conclusion, although ChatGPT exhibited a reasonable accuracy in providing general dietary advice for NCDs, its efficacy decreased in complex situations necessitating customized strategies; therefore, the chatbot is currently unable to replace a healthcare professional’s consultation.
Macroecological correlates of richness, body size, and species range size in terrestrial vertebrates across the world

Species richness, body size, and range size are among key subjects in animal macroecology and biogeography. To date, the species richness–body size–range size nexus remains largely understudied at a global scale and for large taxonomic groups. Here we examine the relative role of species richness and body size in determining species range size among terrestrial vertebrates across spatial and taxonomic scales. We then test related hypotheses in the context of Rapoport’s rule, latitude, and climate variation. To do this, we used simultaneous autoregressive analysis and structural equation modeling to test for statistical relationships among species richness, body size, and range size for all terrestrial vertebrates and for each continent. We then investigated the relative contributions of richness, body size, latitude, climate variation, and their combinations in the variations in species range sizes. We found that species richness consistently shows strong negative correlations with range size at global, regional, and within-region levels, and for all terrestrial vertebrates, and for each of the four classes (i.e., birds, mammals, amphibians, and reptiles). The strength of the relationships increased with richness and with spatial and taxonomic scales. Globally, species richness explained more variation in species range size than did latitude and climates. Body size contributed significantly to the range sizes of all four classes but especially reptiles and amphibians. However, the relative contributions of these factors varied substantially among the continents and terrestrial vertebrate classes. Comparison with the findings of a previous study shows that there were also significant differences in regional patterns between terrestrial vertebrates and plants and the relative contributions of diversity vs. latitude. Our findings show clear relationships among species richness, body size, and range size, but the strength of the relationships varies among regions and taxonomic groups. In general, species richness could predict species range size better than body size, latitude, and climate. These results have important theoretical and applied implications.