bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single-cell exploration of active microbiota in solubilizing fixed phosphorus in soils
Authors: Zhu Yong-Guan , Li Hong-Zhe , Peng JingJing , Yang Kai , Zhang Yi-Yue , Chen Qing-Lin , Cui Li 
Published: February 2024

Abstract

Phosphate solubilizing bacteria (PSB) play a crucial role in mobilizing soil fixed phosphorus (P) and mitigating P crisis. However, it is a grand challenge to reveal their in situ P-solubilizing activity and the link between phenotypes and genotypes. Here, single-cell Raman-D2O was employed to discern and quantify soil active PSB. Their abundance and in situ activity differed significantly between soil types and fertilization treatments. Inorganic nutrient input was determined as the key driver for active PSB distributions. Further targeted single-cell sorting and metagenome sequencing of highly active soil PSB revealed novel unculturable genera with a low abundance in bulk soil microbiota. The underlying functional genes and metabolic pathway, especially the previously unrecognized interplay between P and C cycling involved in high P solubilization activity, were elucidated. This study provides a new single-cell approach to exploring PSB from native environments, enabling development of microbial solution for sustainable P utilization in agriculture.
Stress control mechanism by fiber distribution
Authors: Chalermsin Carol Lee , Kanahama Tohya , Sato Motohiro 
Published: February 2024

Abstract
This study aims to determine the optimal design of fibers that can minimize circumferential bending stress from the morphology of “bamboo,” which is considered a “natural functionally graded material (FGM)” because vascular bundles are distributed unevenly across its cross-section. Further, vascular bundles are crucial for determining the mechanical properties of bamboo, and their distribution is not random. This study analyzes bias distribution from the viewpoint of structural mechanics. Longitudinal splitting is a dominant failure mode in both bamboo and fiber composites, it is mainly caused by circumferential bending tensile stress. The bamboo was modelled as a hollow cylinder, and a circumferential bending stress equation was formulated. As a result, the vascular bundles distribution of the bamboo minimized the circumferential bending stress on the inner surface of the cross-section throughout the culm. These suggest that bamboo is a smart plant that can control its distribution based on regions more prone to failure, e.g., where cracks occur first on the inner surface. This study can help obtain the optimal stress-controlled design of fiber-reinforced composites and understand the morphological design of bamboo.
Using Isometric Log-Ratio in Compositional Data Analysis for Developing a Groundwater Pollution Index
Authors: Oh Junseop , Kim Kyoung-Ho , Kim Ho-Rim , Park Sunhwa , Yun Seong-Taek 
Published: February 2024

Abstract

This study introduces a novel Groundwater Pollution Index (GPI) formulated through compositional data analysis (CoDa) and robust principal component analysis (RPCA) to enhance groundwater quality assessment. Using groundwater quality monitoring data from sites impacted by the 2010–2011 foot-and-mouth disease outbreak in South Korea, CoDa uncovers critical hydrochemical differences between leachate-influenced and background groundwater. The GPI was developed by selecting key subcompositional parts (NH4+-N, Cl−, and NO3-−N) using RPCA, performing ilr transformation, and normalizing the results to environmental standards, thereby offering a more precise and reliable pollution assessment. Validated against government criteria, the GPI demonstrated its potential as an alternative assessment tool, confirmed by receiver operating characteristic (ROC) curve analysis. The study underscores the importance of CoDa, especially the isometric log-ratio (ilr) transformation, in overcoming the limitations of traditional statistical methods by focusing on the relative nature of hydrochemical data. By bridging a methodological gap in groundwater assessment, the GPI represents a significant advancement in groundwater quality monitoring and management. Our results emphasize the importance of considering the compositional nature of environmental data and show the utility of multivariate statistical methods in enhancing the precision and reliability of pollution assessments.
Post-stroke seizure (PSS) following intravenous thrombolysis with recombinant tissue plasminogen activator (rtPA): A retrospective study
Authors: Tabatabaee Seyedehnarges , Soleimani Sevim , Eissazade Negin , Abbasi Mohammad Hossein , Esmaeili Sara , Sheibani Fatemeh , Pirouz Mahdi Saberi , Mokhtari Mahisa , Alavi Seyedeh Niloufar Rafiei , Mostafavi Keihan , Khotbehsara Samaneh Tanhapour , Siahpoosh Fateme , Hatam Jaber , Mirzaasgari Zahra 
Published: February 2024

Abstract
Background Recombinant tissue plasminogen activator (rtPA), the gold standard treatment of acute ischemic stroke, can reportedly result in seizures, known as post-stroke seizure (PSS). PSS is categorized as early PSS (EPSS), occurring within the first week of stroke onset, and late PSS (LPSS), occurring after the first week of stroke onset. Therefore, we aimed to evaluate the incidence of PSS after intravenous thrombolysis (IVT) with rtPA and to identify the potentially associated risk factors.
Methods This retrospective cohort study included 955 patients who were admitted between January 2017 and October 2018. Demographics, medical records, and paraclinical data were recorded and analyzed.
Results Out of the 955 patients included, 176 (18.42%) had received rtPA, of which 93 (69.88%) were male. Focal to bilateral tonic-clonic seizure was the most frequent seizure type in our study. We found that the use of rtPA was not significantly associated with the incidence of PSS. EPSS was significantly associated with a positive history of ischemic stroke (P = 0.019), cortical involvement (P = 0.002), cardioembolic stroke (P = 0.013), and HT (P = 0.009). LPSS was significantly associated with DM (P = 0.021), cortical involvement (P = 0.049) and higher mRS scores (P = 0.007). Conclusions rtPA did not significantly impact the incidence of PSS. Further research is needed to strengthen the body of evidence for the relationship between IVT with rtPA and PSS and to identify the associated risk factors.
Rice Production in Tamilnadu Using Bayesian Predictive Models
Authors: Saranyadevi M. , Mohideen A. Kachi 
Published: February 2024

Abstract
In this paper, prediction for Rice production in Tamilnadu using Bayesian model average and model selection with Zellner's g-prior approach. The methods were performed through MCMC sampling procedures for Bayesian Model Selection and Model Average, Bayesian Predictive Model and Markov Chain Monte Carlo Sampling Method. This posterior distribution can be used to simply select the “best” model BMA performs better than adopting a single best model for prediction. The results in discussed in rice production inclusion Probabilities and p-value normalizing this product, one can infer the PMPs and model weighted posterior distribution for any coefficients.
Targeted protein editing with an antibody-based system
Authors: Vendruscolo Michele , Rimon Oded , Konc Juraj , Ali Montader , Chowdhury Vaidehi Roy , Sormanni Pietro , Bernardes Gonçalo 
Published: February 2024

Abstract
The chemical modification of proteins is one of the major mechanisms used to regulate the properties and functions of these macromolecules in the cell. It is therefore of great interest to develop tools to exploit this type of modifications for applications in molecular biology, medicine and biotechnology. Here we present a method of using antibodies to perform post-translational covalent modifications of endogenous proteins in complex environments by exploiting proximity-driven chemistry. The method is based on the ability of antibodies to hold a weakly reactive group close to its intended site of reaction by binding the target protein on a nearby epitope. We characterise this approach by modifying the green fluorescent protein in increasingly complex environments, and illustrate its applicability by targeting the disease-associated protein beta-2 microglobulin.
Psychological, social, and health-related factors predict risk for financial exploitation
Authors: Smith David , Yang Yi , Hackett Katherine , Katta Srikar , Ludwig Rita , Jarcho Johanna , Giovannetti Tania , Fareri Dominic 
Published: February 2024

Abstract
People lose tens of billions of dollars a year to financial exploitation in the United States alone. Few studies have examined how preferences for trust and fairness in economic activities may contribute to risk for financial exploitation. Furthermore, few studies have examined the interaction between risk factors. In three studies, we attempt to address these gaps by surveying 1918 demographically and socioeconomically diverse participants to examine putative risk factors for self-reported financial exploitation. We focused on: 1) how trust in others and fairness preferences during economic games are associated with self-reported financial exploitation; and 2) how sociodemographic and health-related factors interact with psychosocial factors to confer risk for financial exploitation. We found participants with lower socioeconomic status and poor emotion regulation skills were at the greatest risk for financial exploitation. We also found associations between greater risk for financial exploitation and poorer physical health, more severe cognitive decline, increased persuadability, and increased insensitivity to trustworthiness cues. Our findings suggest that risk for financial exploitation is dependent upon a combination of psychosocial, sociodemographic and health factors, which may lead to interventions that protect vulnerable individuals.
Risk factors associated to a positive screening for Postpartum Depression in Mexican women with elective cesarean delivery: an analytical cross-sectional study during the early postoperative stage
Authors: Hernández-Muñoz Adrián Enrique , Fletes-Reyes Ana Lilia , López-Jiménez José de Jesús , Cuevas-Gómez Gloria Noemí , Herrera-Godina Melva Guadalupe , Cabrera-Pivaral Carlos Enrique , Rangel Miguel A. 
Published: February 2024

Abstract
Background. It has been reported that the Postpartum Depression (PPD)’s symptomatology increases during the first 72 hours after delivery. Although PPD’s screening is recommended during this period, there is few evidence about the associated Risk Factors (RF) that determine this disorder in women who exclusively underwent an Elective Cesarean Delivery (ECD). Hence, our objective was to determine the RF for PPD’s positive screening in the early postoperative stage after an ECD.
Methods. An analytical cross-sectional study was conducted in 123 women, rooming-in at Guadalajara’s Civil Hospital Fray Antonio Alcalde, during the average hospital length of stay after an ECD (2.1±1.02 days). To screen the PPD’s symptomatology, we applied the Edinburgh Postpartum Depression Scale (EPDS). To identify possible RF, we checked the women’s sociodemographic characteristics, obstetric/pregnancy complications, and neonatal comorbidities in their Medical Records. Subsequently, we carried out Odds Ratio (OR) analysis, followed by logistic regression that determined adjusted OR (aOR) and 95% Confidence Intervals (95% CI).
Results. By applying the EPDS, we identified 32.5% of PPD’s positive screening, significantly associated with miscarriages (OR 2.6, 95% CI: 1.06-6.30), multiparity (OR 2.6, 95% CI: 1.08-6.43) and age ≥30 years (OR 2.3, 95% CI: 1.04-5.20). Other associations were found with less than four prenatal visits (OR 2.4, 95% CI: 1.10-5.35), unplanned pregnancy (OR 2.7, 95%CI: 1.29-5.98), newborn comorbidities (OR 2.7, 95% CI: 1.18-6.03), and obstetric complications (OR 3.1, 95% CI: 1.37-7.07). Nevertheless, the logistic regression determined that previous history of depression (aOR 8.8, 95% CI: 1.62-13.8), obstetric complications (aOR 8.8, 95% CI: 1.58-9-43), and newborn comorbidities (aOR 9.9, 95% CI: 1.86-14.7) were RF for PPD.
Conclusions. Newborn and obstetric complications, along with previous depression, were main causes for the presence of depressive symptoms in women with an ECD. By considering not only the latter, but also that the prevalence for PPD’s positive screening that we found was higher than the results from national reports, we suggest that clinical and surgical professionals seek these RF during this early postoperative period, in order to treat and prevent any negative long-term effects on the mother’s mental well-being.
A Mendelian randomization study suggests that human skin color is an intermediate factor in the influence of mental disorders
Authors: Cao Junhua , Xu Xiaoyu , Zhao Jingru , Liu Jiuming , Chen Yanyan , Pu Youwei , Yang Zhaohui 
Published: February 2024

Abstract

Background
Mental disorders are a group of clinical diseases that result in varying degrees of impairment of a person's cognitive, emotional, volitional and behavioral mental activities. Previous studies have demonstrated variations in disease susceptibility among different groups. In addition to differences in disease pathogenesis, differences in human phenotypes among populations may also be intermediate factors affecting disease development, such as the diversity of human skin color. Whether there is a genetic link between skin color and mental disorders remains unknown. Therefore, our aim is to investigate whether skin color is associated with the risk of mental disorders.
Methods
We conducted two-sample Mendelian randomization study to analyze the effect of skin color on eight prevalent mental disorders (schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, anxiety, depression, anorexia nervosa, obsessive-compulsive disorder, autism spectrum disorder) as well as a closely related trait (insomnia). Analyses were conducted using the "TwoSampleMR" and "MRPRESSO" packages in R.
Results
MR results suggest that higher genetically predicted skin color was associated with an increased risk of schizophrenia by the IVW method [odds ratios (OR) = 1.132; 95% confidence interval (CI): 1.046–1.225; P = 0.002]. We also observed that skin color was positively associated with bipolar disorder by the weighted median method [OR = 1.176; 95% CI: 1.028–1.345; P = 0.0147]. However, higher genetically predicted skin color was significantly associated with a decreased risk of attention deficit hyperactivity disorder [IVW: OR = 0.840, 95% CI: 0.730–0.966, P = 0.014; weighted median: OR = 0.797, 95% CI: 0.648–0.980, P = 0.034].
Conclusion
Our study establishes a relationship between skin color and mental disorders, such as schizophrenia, bipolar disorder and attention deficit hyperactivity disorder. These findings provide new evidence that human common phenotypes have an impact on mental disorders.
Synthesis, structural elucidation, DNA-binding and anti-oxidant activities of centrosymmetric paddlewheel copper carboxylate complexes
Authors: Mushtaq Afifa , Iqbal Muhammad , Rashid Zahid , Shahid Khadija , Tahir Muhammad Nawaz , Ali Saqib 
Published: February 2024

Abstract
Synthesis, structural characterization and preliminary biological relevance of four new copper carboxylate complexes (1-4) has been presented here. The complexes have been synthesized by direct treatment of the substituted phenyl acetate and pyridine ligands in aqueous medium. The complexes were stable indefinitely with excellent yield and were characterized using spectroscopic and single crystal XRD techniques. FTIR spectroscopy revealed the bridging bidentate coordination mode for the carboxylate moiety in accordance to the actual structure revealed by XRD. Moreover, UV-Visible spectroscopic and cyclic voltammetric studies helped in their characterization and yielded signals which were typical of the copper(II) complexes. Successfully solved single crystal XRD data showed binuclear paddlewheel structures for all the complexes with both copper ions linked through four OCO bridges of ortho-methoxy phenyl acetate (1-3) and ortho-methyl-meta-nitrophenyl acetate (4). The geometry around each copper was distorted square pyramidal where the apical positions are occupied by meta-bromopyridine (1), meta-methylpyridine (2) and DMSO (3 and 4) molecules. The complexes exhibited excellent DNA-binding activity majorly via intercalation as revealed by four experimental techniques in line with the in silico studies. Their anti-oxidant activity was also comparable to that of the ascorbic acid. Complexes 1 and 4 exhibited significant anti-bacterial activity against Micrococcus luteus and Staphylococcus aureus. These preliminary findings indicated the biological potential of the synthesized complexes.
Density of Limnoperna fortunei larval stages in a subtropical basin: spatiotemporal variation and environmental influences
Authors: Lopes M. N. , Pinheiro-Silva L. , Ribolli J. , Ávila-Simas S. , Lopes C. A. , Cardoso G. F.M. , Guereschi R. M. , Kavaguichi-Leite N. , Petrucio M. M. , Nuñer A. P.O. 
Published: February 2024

Abstract

The golden mussel (Limnoperna fortunei) is an invasive bivalve that has established itself in several South American river systems, impacting ecosystem functioning. Reservoir cascades provide their larvae with the means of rapid dispersal, but the relationship between environmental variables and larval stage structure remains unclear. In this study, the density of four L. fortunei larval stages was assessed in a cascade of five reservoirs in the upper Uruguay River Basin and associated with spatiotemporal variation in environmental parameters. Larval density increases were more related to fluctuating environmental parameters than to the expected effect of a cascade system, as the highest larval densities did not occur in the downstream reservoirs. Smaller D-shaped larvae predominated, suggesting that larger umbonated larvae either attempted to settle on the substrate (prior to metamorphosis to pediveligers) or were naturally preyed upon. The relationships between environmental parameters were evaluated using a multivariate model. Water temperature and dissolved oxygen had a significant effect on larval density, but did not respond to density variations independently. However, during winter, larval density decreased significantly. Other variables also contribute to species activity and survival in the upper Uruguay River Basin reservoirs and may be considered limiting factors. The interaction between basin area and rainfall strongly influenced the increase in larval density because runoff enriched the reservoirs with nutrients essential for the leading development of larval phases. Our findings provide insights on larval development in golden mussels, which can be used as a tool to manage further dispersal of this invasive species.
Carbon sequestration potential of Qimbaba forest; Implications of managing forests for climate change mitigation
Authors: Kassa Getachew , Molla Eyayu 
Published: February 2024

Abstract
Climate change poses one of the most significant challenges humanity has ever encountered, potentially underpinning the ongoing global warming phenomenon. Tropical forests play a crucial role in mitigating climate change by absorbing and storing carbon from the atmosphere. However, there has been limited research on carbon sequestration and emission reduction in Ethiopia. This study aimed to assess the carbon stock of the Qimbaba forest non-destructively, utilizing 40 circular sample plots and an allometric equation. The results indicated that the total carbon stock of the plantation forest was estimated at 24.98 t/ha-1, with 20.34 ± 0.18 t/ha-1 attributed to natural trees and 4.64 ± 0.1 t/ha-1 to nurse trees. Above-ground carbon was calculated at 16.01 ± 0.14 t/ha-1 for natural forest and 3.65 ± 0.08 t/ha-1 for nurtured trees in the plantation forest. Below-ground carbon values were determined to be 4.32 ± 0.04 t/ha-1 for natural forests and 0.99 ± 0.21 t/ha-1 for nurse trees in plantation forests. The findings suggest that the Qimbaba forest significantly contributes to climate change mitigation. To capitalize on this potential and receive financial incentives, it is recommended to integrate the forest into programs such as REDD+ and CDM of the Kyoto Protocol.
Triple Band Diamond-shaped Polarization Insensitive Plasmonic Nano Emitter for Thermal Camouflage and Radiative Cooling
Authors: Şanlı Atıf Kerem , Tabaru Timuçin Emre , Kılıç Veli Tayfun 
Published: February 2024

Abstract

This study proposes the design of a novel Metal-Insulator-Metal (MIM) nano-infrared emitter that uses a unique diamond-shaped grating to achieve selective infrared absorption. Diamond-shaped nano emitter (DNE) structure exhibits four narrow resonant peaks within key absorption windows such as short-wave infrared (SWIR) and mid-wave infrared (MWIR), alongside a wide absorption band in the Non-Transmissive Infrared Range (NTIR) for thermal camouflage applications compatible with radiative cooling. Moreover, the proposed DNE is polarization insensitive as it has an in-plane symmetric design. Using the 3D Finite-Difference Time-Domain (FDTD) simulations, we demonstrate the nano emitter's superior performance characterized by its high absorption rates and tuned effective impedance matching. As of our knowledge, the findings suggest that this is the first time that a MIM structure achieved multiple narrow resonance peaks, located in SWIR and MWIR simultaneously, with a wide absorption range in the NTIR. Represented DNE stands as a significant innovation in the field of stealth technology, providing a tunable, high-efficiency solution for managing and controlling thermal emissions across diverse applications.
Centralized Smart Energy Monitoring System for Legacy Home Appliances
Authors: Ahmad Shahed S. , Almasalha Fadi , Qutqut Mahmoud H. , Hijjawi Mohammad 
Published: February 2024

Abstract

As people increasingly rely on electrical devices for their daily tasks. As a result, energy consumption rates have sharply risen, leading to higher household electricity bills. This has produced a growing demand for energy monitoring systems that can accurately estimate energy usage, especially for older residential appliances that are difficult or expensive to update with monitoring sensors. However, current energy monitoring systems have some drawbacks, such as the inability to detect different types of appliances and the deployment complexity accurately. Moreover, such systems are too costly to use in older power infrastructures. To address this issue, we propose a centralized smart energy monitoring system that utilizes prediction algorithms to calculate the power consumption of legacy home appliances. The primary goal of our proposed system is to overcome the limitations of legacy home appliances that require infrastructure upgrades. The system consists of two layers: a hardware layer that includes an Emontx device, Analog-to-Digital Converters (ADC), and Current Transformer (CT) sensors, and a software layer that includes Artificial Intelligence (AI) proposed predictors using a pre-defined set of rules and K Nearest Neighbours (KNN) algorithms. We conducted experiments on real home appliances to evaluate the proposed model. The accuracy of the proposed models showed positive results after several modifications and hard tuning of several parameters in the hardware devices, specifically for Jordanian power plants.