bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short‐Term Arsenic Cycling in a Shallow, Polymictic Lake
Authors: Fung Samantha R. , Hull Erin A. , Gawel James E. , Horner‐Devine Alexander R. , Neumann Rebecca B. 
Published: March 2024

AbstractArsenic (As), a harmful contaminant present in many urban lakes, can negatively impact lake ecosystem health when aqueous concentrations are elevated. We observed repeated diel oscillations in As concentrations in the bottom waters of a shallow, temperate lake during a weeklong period. In this work, we explore four mechanistic hypotheses to explain the diel As cycles based on the physical and biogeochemical processes that were investigated during the study. Despite pH being known to control diel As cycles in rivers, we determined that this mechanism was inconsistent with As dynamics observed in Lake Killarney. Instead, we found that iron and manganese concentrations oscillated simultaneously with As concentrations and that redox conditions adjacent to the lakebed likely controlled the near‐bed availability of these three elements. However, based on timescale analysis, we determined that biogeochemical processes at the sediment water interface alone could not have led to the daily oscillations in bottom water concentrations. Rather, turbulence from convective mixing was necessary to transport dissolved species. Notably, we saw that the timing and intensity of peaks in convectively driven turbulence were consistent with observed diel fluctuations in bottom water As. Our results indicate that physical mixing is key in controlling As transport and concentrations on diel timescales within shallow lakes. Understanding the daily cycling of As in shallow lakes is essential for predicting the degree to which lake biota are exposed to this contaminant. Diel oscillations in As concentrations should be considered when designing sampling methods to assess the water quality of contaminated sites.
Assessing genetic diversity in critically endangered Chieniodendron hainanense populations within fragmented habitats in Hainan
Authors: Zhang Li , Zhang Hai-Li , Chen Yukai , Nizamani Mir Muhammad , Wu Tingtian , Liu Tingting , Zhou Qin 
Published: March 2024

AbstractHabitat fragmentation has led to a reduction in the geographic distribution of species, making small populations vulnerable to extinction due to environmental, demographic, and genetic factors. The wild plant Chieniodendron hainanense, a species with extremely small populations, is currently facing endangerment and thus requires urgent conservation efforts. Understanding its genetic diversity is essential for uncovering the underlying mechanisms of its vulnerability and for developing effective conservation strategies. In our study, we analyzed 35 specimens from six different populations of C. hainanense using genotyping-by-sequencing (GBS) and single nucleotide polymorphism (SNP) methodologies. Our findings indicate that C. hainanense has limited genetic diversity. The observed heterozygosity across the populations ranged from 10.79 to 14.55%, with an average of 13.15%. We categorized the six populations of C. hainanense into two distinct groups: (1) Diaoluoshan and Baishaling, and (2) Wuzhishan, Huishan, Bawangling, and Jianfengling. The genetic differentiation among these populations was found to be relatively weak. The observed loss of diversity is likely a result of the effects of natural selection.
Genetic structure and origin of emu populations in Japanese farms inferred from large-scale SNP genotyping based on double-digest RAD-seq
Authors: Koshiishi Yuichi , Wada Kenta 
Published: March 2024

AbstractThe emu is a novel poultry species in Japan. However, Japanese farmed emu populations have reduced genetic diversity owing to inbreeding. We have previously suggested that there are genetic resources in the Tohoku Safari Park (TSP) and Fuji/Kakegawa Kachoen Garden Park (FGP/KGP) to extend the genetic diversity of commercial emu farms based on microsatellite (SSR) and mitochondrial DNA. However, those markers provide relatively poor information. Thus, we investigated the genetic structure of farmed Japanese populations based on a large-scale genotyping system using RAD-seq and verified the usefulness of TSP and FGP/KGP as genetic resources for expanding genetic diversity. Admixture, phylogenetic, and principal component analyses based on 28,676 SNPs showed that TSP individuals were ancestors in the Okhotsk Emu Farm (OEF). FGP/KGP individuals showed a unique genetic component that differed from that of the others. We have previously reported that the mitochondrial haplotypes of FGP/KGP were shared with an isolated wild population in eastern Australia. These results suggest that FGP/KGP individuals originated from an eastern Australia isolated population different from other populations including ancestral of OEF/TSP. Our results would provide information for the development of Japanese emu farms and industry and for the conservation of genetic resources in the Australian wild emu.
Modeling time-varying phytoplankton subsidy reveals at-risk species in a Chilean intertidal ecosystem
Authors: Duckwall Casey , Largier John L. , Wieters Evie A. , Valdovinos Fernanda S. 
Published: March 2024

AbstractThe allometric trophic network (ATN) framework for modeling population dynamics has provided numerous insights into ecosystem functioning in recent years. Herein we extend ATN modeling of the intertidal ecosystem off central Chile to include empirical data on pelagic chlorophyll-a concentration. This intertidal community requires subsidy of primary productivity to support its rich ecosystem. Previous work models this subsidy using a constant rate of phytoplankton input to the system. However, data shows pelagic subsidies exhibit highly variable, pulse-like behavior. The primary contribution of our work is incorporating this variable input into ATN modeling to simulate how this ecosystem may respond to pulses of pelagic phytoplankton. Our model results show that: (1) closely related sea snails respond differently to phytoplankton variability, which is explained by the underlying network structure of the food web; (2) increasing the rate of pelagic-intertidal mixing increases fluctuations in species’ biomasses that may increase the risk of local extirpation; (3) predators are the most sensitive species to phytoplankton biomass fluctuations, putting these species at greater risk of extirpation than others. Finally, our work provides a straightforward way to incorporate empirical, time-series data into the ATN framework that will expand this powerful methodology to new applications.
An evaluation of the replicability of analyses using synthetic health data
Authors: El Emam Khaled , Mosquera Lucy , Fang Xi , El-Hussuna Alaa 
Published: March 2024

AbstractSynthetic data generation is being increasingly used as a privacy preserving approach for sharing health data. In addition to protecting privacy, it is important to ensure that generated data has high utility. A common way to assess utility is the ability of synthetic data to replicate results from the real data. Replicability has been defined using two criteria: (a) replicate the results of the analyses on real data, and (b) ensure valid population inferences from the synthetic data. A simulation study using three heterogeneous real-world datasets evaluated the replicability of logistic regression workloads. Eight replicability metrics were evaluated: decision agreement, estimate agreement, standardized difference, confidence interval overlap, bias, confidence interval coverage, statistical power, and precision (empirical SE). The analysis of synthetic data used a multiple imputation approach whereby up to 20 datasets were generated and the fitted logistic regression models were combined using combining rules for fully synthetic datasets. The effects of synthetic data amplification were evaluated, and two types of generative models were used: sequential synthesis using boosted decision trees and a generative adversarial network (GAN). Privacy risk was evaluated using a membership disclosure metric. For sequential synthesis, adjusted model parameters after combining at least ten synthetic datasets gave high decision and estimate agreement, low standardized difference, as well as high confidence interval overlap, low bias, the confidence interval had nominal coverage, and power close to the nominal level. Amplification had only a marginal benefit. Confidence interval coverage from a single synthetic dataset without applying combining rules were erroneous, and statistical power, as expected, was artificially inflated when amplification was used. Sequential synthesis performed considerably better than the GAN across multiple datasets. Membership disclosure risk was low for all datasets and models. For replicable results, the statistical analysis of fully synthetic data should be based on at least ten generated datasets of the same size as the original whose analyses results are combined. Analysis results from synthetic data without applying combining rules can be misleading. Replicability results are dependent on the type of generative model used, with our study suggesting that sequential synthesis has good replicability characteristics for common health research workloads.
Physics informed contour selection for rapid image segmentation
Authors: Dwivedi Vikas , Srinivasan Balaji , Krishnamurthi Ganapathy 
Published: March 2024

AbstractEffective training of deep image segmentation models is challenging due to the need for abundant, high-quality annotations. To facilitate image annotation, we introduce Physics Informed Contour Selection (PICS)—an interpretable, physics-informed algorithm for rapid image segmentation without relying on labeled data. PICS draws inspiration from physics-informed neural networks (PINNs) and an active contour model called snake. It is fast and computationally lightweight because it employs cubic splines instead of a deep neural network as a basis function. Its training parameters are physically interpretable because they directly represent control knots of the segmentation curve. Traditional snakes involve minimization of the edge-based loss functionals by deriving the Euler–Lagrange equation followed by its numerical solution. However, PICS directly minimizes the loss functional, bypassing the Euler Lagrange equations. It is the first snake variant to minimize a region-based loss function instead of traditional edge-based loss functions. PICS uniquely models the three-dimensional (3D) segmentation process with an unsteady partial differential equation (PDE), which allows accelerated segmentation via transfer learning. To demonstrate its effectiveness, we apply PICS for 3D segmentation of the left ventricle on a publicly available cardiac dataset. We also demonstrate PICS’s capacity to encode the prior shape information as a loss term by proposing a new convexity-preserving loss term for left ventricle. Overall, PICS presents several novelties in network architecture, transfer learning, and physics-inspired losses for image segmentation, thereby showing promising outcomes and potential for further refinement.
Risk factors for hypoactive delirium in patients with nontraumatic ARDS: a prospective observational study
Authors: Lian Fuyan , Li Fei , Tang Xuemei , Yuan Yuan 
Published: March 2024

AbstractTo investigate the incidence, characteristics and risk factors for hypoactive delirium in patients with nontraumatic acute respiratory distress syndrome (ARDS) and to explore the independent risk factors associated with hypoactive delirium and provide new ideas for early prediction and treatment. Hypoactive delirium is a known serious complication in ARDS patients, and currently, there are no effective early detection models or clinical prediction tools, and there is a lack of clinical treatment. This study included nontraumatic ARDS patients who stayed in the intensive care unit (ICU) for more than 24 h and were older than 18 years. A total of 205 ARDS patients admitted to the ICU of Gansu Provincial People's Hospital between December 2021 and February 2023 were selected. Demographic data, clinical characteristics and laboratory test results were collected within 24 h after the patients entered the ICU. Multivariate logistic regression analysis was used to investigate risk factors, evaluate the clinical prediction effect of the model and construct a nomogram for visual display. The incidence of hypoactive delirium among the patients included in the study was 41%. Patients with hypoactive delirium had hypertension; diabetes mellitus; Acute Physiology and Chronic Health Evaluation II (APACHE II) scores ≥ 15; and increased procalcitonin, C-reactive protein (CRP), lactic dehydrogenase and interleukin-6 (IL-6) levels compared with those without hypoactive delirium. Logistic regression analysis revealed that diabetes mellitus (OR 3.305, 95% CI: 1.866–12.616; p = 0.047), CRP level (OR 1.002, 95% CI: 1.001–1.023; p = 0.044), and IL-6 level (OR 1.045, 95% CI: 1.017–1.063; p = 0.001) were independent risk factors for hypoactive delirium. After receiver operating characteristic (ROC) curve analysis, calibration plot and decision curve analysis (DCA) confirmed that the clinical prediction ability of this study model was satisfactory, and a nomogram was drawn for visual display. Hypoactive delirium is a common serious complication in nontraumatic ARDS patients. Our logistic regression model not only effectively predicts hypoactive delirium early but also reveals potential clinical therapeutic targets.
Highly efficient catalytic degradation of organic dyes using iron nanoparticles synthesized with Vernonia Amygdalina leaf extract
Authors: Jara Yohannes Shuka , Mekiso Tilahun Tumiso , Washe Alemayhu Pawulos 
Published: March 2024

AbstractToday, nanoscience explores the potential of nanoparticles due to their extraordinary properties compared to bulk materials. The synthesis of metal nanoparticles using plant extracts is a very promising method for environmental remediation, which gets global attention due to pollution-led global warming. In the present study, iron nanoparticles (FeNPs) were successfully synthesized by the green method using Vernonia amygdalina plant leaf extract as a natural reducing and capping agent. Biosynthesized FeNPs were characterized with different analytical techniques such as UV–visible, FT-IR, XRD, and SEM. The analysis revealed the formation of amorphous FeNPs with an irregular morphology and non-uniform distribution in size and shape. The average particle size was approximately 2.31 µm. According to the catalytic degradation investigation, the FeNPs produced via the green approach are highly effective in breaking down both CV and MB into non-toxic products, with a maximum degradation efficiency of 97.47% and 94.22%, respectively, when the right conditions are met. The kinetics study exhibited a high correlation coefficient close to unity (0.999) and (0.995) for the degradation of MB and CV, respectively, for the zero-order pseudo-kinetics model, which describes the model as highly suitable for the degradation of both dyes by FeNPs compared to other models. The reusability and stability of biosynthesized nano-catalysts were studied and successfully used as efficient catalysts with a slight decrease in the degradation rate more than four times. The results from this study illustrate that green synthesized FeNPs offer a cost-effective, environmentally friendly, and efficient means for the catalytic degradation of organic dyes.
Effects of the addition of short straight steel fibers on the strength and strains of high-strength concrete during compression
Authors: Kaźmierowski Maciej , Jaskulski Roman , Drzazga Michał , Nalepka Marek , Kordasz Michał 
Published: March 2024

AbstractThe article presents the effect of the addition of short straight steel fibers on the behavior of high-strength concrete (HSC) under compression (σ–ε curves). Deformations of cylindrical samples were measured simultaneously with the use of linear variable differential transformers (LVDT), strain gauges and the method of digital image correlation (DIC). The study showed that as the content of short straight steel fibers increases, both the composite compressive strength (fc) and strains (ε0), which correspond to the stress equal to the compressive strength, increase as well. To a lesser extent, the effect of short straight fibers on the descending part of the σ–ε curve was observed. An increase in the density and toughness ratio of the compressive strength of high-strength concrete with fibers compared to concrete without fibers was also observed. Moreover, compressive strength of the composite was estimated using the ultrasonic method. Based on the obtained results, a statistical analysis and an estimation of parameters fc and ε0 were carried out, and an analytical model was proposed to describe σ–ε relationship for HSC reinforced with short straight fibers under compressive loading. The results obtained for compressed fiber-reinforced concrete were compared with data available in literature.
Antibacterial and hemocompatibility potentials of nano-gold-cored alginate preparation against anaerobic bacteria from acne vulgaris
Authors: Abbas Hanan A. , Taha Ali A. , Sulaiman Ghassan M. , Al Ali Amer , Shmrany Humood Al , Stamatis Haralambos , Mohammed Hamdoon A. , Khan Riaz A. 
Published: March 2024

AbstractAcne is a prevalent dermatological disease, with high global incidence, and is a health menace. The current study aimed to isolate and characterize the anaerobic bacteria responsible for the condition. Causes of a total of 70 acne-based bacterium isolates obtained from patients of mild, moderate, and severe acne, 24 were Clostridium innocuum, 21 were Lactobacillus plantarum, 13 were Anaerococcus prevotii, and 12 were Peptoniphilus asaccharolyticus. Nearly 69% of males were suffering, while the rest were females at 31%. The 15–30 years old age group was the most affected. The gold/alginate nanoparticles’ nanopreparation (GANPs) produced from chloroauric acid and sodium alginate was an effective treatment against the acne conditions under the experimental conditions. The nanopreparation exhibited significant inhibitory activity against anaerobic bacterial isolates, with a minimum inhibitory concentration of 200 µg/ml for A. prevotii and P. asaccharolyticus, and 400 µg/ml for C. innocuum and L. plantarum. The in vitro efficacy of the GANPs on human blood parameters was also assessed. The concurrent results suggested potential antibacterial activity and hemocompatibility of the product, which has promise to be used as a successful antibacterial agent for acne.
Assessing anatomical variations of the inferior mesenteric artery via three-dimensional CT angiography and laparoscopic colorectal surgery: a retrospective observational study
Authors: Ding Yuanyi , Zhao Botian , Niu Wenbo , Hu Xuhua , Li Chenhui , Liu Zining , Yu Bin 
Published: March 2024

AbstractTo assess the anatomy of the inferior mesenteric artery (IMA) and its branches by reviewing laparoscopic left-sided colorectal cancer surgery videos and comparing them with preoperative three-dimensional computed tomography (3D-CT) angiography, to verify the accuracy of 3D-CT vascular reconstruction techniques. High-definition surgical videos and preoperative imaging data of 200 patients who underwent laparoscopic left-sided colorectal cancer surgery were analysed, and the alignment of the IMA and its branches in relation to the inferior mesenteric vein (IMV) was observed and summarized. The above two methods were used to measure the length of the IMA and its branches. Of 200 patients, 47.0% had the sigmoid arteries (SAs) arise from the common trunk with the superior rectal artery (SRA), and 30.5% had the SAs arise from the common trunk with the left colic artery (LCA). In 3.5% of patients, the SAs arising from both the LCA and SRA. The LCA, SA, and SRA emanated from the same point in 13.5% of patients, and the LCA was absent in 5.5% of patients. The range of D cm (IMA length measured by intraoperative silk thread) and d cm (IMA length measured by 3D-CT vascular reconstruction) in all cases was 1.84–6.62 cm and 1.85–6.52 cm, respectively, and there was a significant difference between them. (p < 0.001). The lengths between the intersection of the LCA and IMV measured intraoperatively were 0.64–4.29 cm, 0.87–4.35 cm, 1.32–4.28 cm and 1.65–3.69 cm in types 1A, 1B, 1C, and 2, respectively, and there was no significant difference between the groups (p = 0.994). There was only a significant difference in the length of the IMA between the 3D-CT vascular reconstruction and intraoperative observation data, which can provide guidance to surgeons in preoperative preparation.
Changes in Cabernet Sauvignon yield and berry quality as affected by variability in weather conditions in the last two decades in Lebanon
Authors: Ghantous G. , Popov K. , El Sebaaly Z. , Sassine Y. N. 
Published: March 2024

AbstractCabernet Sauvignon is the most planted cultivar in Lebanese vineyards. This study investigated the variation of its production at two vineyards ‘Kanafar’ (West Bekaa at 1020 m.a.s.l) and ‘Taanayel’ (Central Bekaa at 800 m.a.s.l) and their interactions with weather conditions from 2006 till 2018. Evaluation of climate records denoted interannual variability in weather conditions occurring in 2015 in Kanafar and in 2008 in Taanayel. Average yield peaked in 2009 in Kanafar (19,187.0 kg ha−1) and in 2011 in Taanayel (14,279.0 kg ha−1), both years marked a turning point after which values of average yield shifted downwards (by 31–67% in Kanafar, and 14–82% in Taanayel). At Kanafar, after 2015, averages of yield, weight of 200 berries (W200B), potential alcohol (PA), and total polyphenolic richness (TPR) decreased by 35%, 1.5%, 36.2 g, and 50%, respectively. In Taanayel, only TPR content in berries was significantly affected by varying weather conditions (decrease by 20%). Also, TPR values followed a progressive decreasing pattern starting from 2006 at both vineyards with minor exceptions. Multiple regression analysis assessed the relationship between various indicators and weather variables at each vineyard. It showed that the decrease in yield at Kanafar correlated with higher temperature during the growing season (by 0.6 °C), higher solar radiation from early-spring to early-summer (by 13.9–27.1 W m−2), and lower values of maximum wind speed during mid to late summer (by 0.4 m s−1), occurring during 2016, 2017, and 2018 at Kanafar. The model explained 60% of yield variations at this vineyard. Further, weather variables accounted for 61% (R2 = 0.61) of changes in PA and for 58% (R2 = 0.58) of TPR of berries at Kanafar. Conclusively, interannual variability in weather conditions had more serious negative influence on Cabernet Sauvignon production at Kanafar than at Taanayel, but had a similar negative influence on polyphenols accumulation in berries, and thus on potential wine quality produced at both vineyards.