bluuebunny/crossref_metadata_2025_split huggingface dataset:
Activated carbon-supported lanthanum nickel oxide (LaNiO3 ) perovskite nanocomposite supercapacitor electrode material exhibiting superior power-density and life cycle
Authors: Chowdhury Buddhodev , Sahis Amrit , Kuiri Bibhatsu , Patra Ardhendu , Dhak Debasis , Pal Sudipta 
Published: July 2024

Abstract

Perovskite LaNiO3 was synthesized with the help of the sol-gel method and LaNiO3@AC nanocomposite was produced via ultrasonication followed by filtration process keeping LaNiO3 and activated carbon (AC) in an NMP solvent. The prepared electrode material was then coated on Ni foam with a mass loading of 28 mg/cm2. Various well-known characterization techniques such as TGA, FTIR, XRD, FESEM, and XPS were used to characterize the crystal structure and surface morphology of the sample. The electrochemical performance of the prepared electrodes was measured with cyclic voltammetry (CV), galvanometric charge-discharge (GCD), and electrochemical spectroscopy (EIS) using 3 M KOH as an electrolyte solution in two electrode configurations. The pure LaNiO3 electrode exhibits a specific capacitance (Cs) of 177.53 F/g at 5 mV/s, cyclic stability with 73.35% capacitance retention after 3000 cycles, energy density of 24.65 W h/kg, and a power density of 1.48 kW/kg. whereas, The LaNiO3@AC nanocomposite electrode delivered a high Cs of 218.57 F/g at a 5 mV/s scan rate with excellent cyclic stability of about 94.57% specific capacitance retention after 3000 cycles, the outstanding energy density of 30.35 W h/kg with a high-power density of 1.58 kW/kg. Additional investigation on the storage contribution using Dunn's, b-fitting, and Randel Savic models produced superior results with the LaNiO3@AC nanocomposite electrode than with the LaNiO3 electrode. DFT analysis further demonstrated LaNiO3 material's strong electrochemical characteristics and stability. Thus, the LaNiO3@AC composite material can be the newest member of the supercapacitor electrode material with superior electrochemical performance.
Coronary cross-sectional area stenosis severity determined by coronary CT highly correlated with coronary functional flow reserve: a pilot study
Authors: Koumoto Takuto , Kusachi Shozo , Tomiya Takumi , Akagi Takuya , Kawamura Hiroshi , Hirohata Satoshi , Yamaji Hirosuke , Murakami Takashi , Kamikawa Shigeshi , Murakami Masaaki 
Published: July 2024

Abstract

Fractional flow reserve (FFR) is the gold standard for assessing the physiological significance of coronary stenosis. We examined the potential correlation between digitally measured coronary cross-sectional area stenosis by coronary CT angiography, and the FFR. We analyzed 32 consecutive patients with stenoses who underwent invasive FFR determination. The cross-sectional area was assessed using 128-slice coronary detector-based spectral CT angiography. Power analysis revealed that the sample size enabled the detection of an area under the receiver operating characteristic (ROC) curve (AUC) of 0.90. FFR ≤ 0.8 and > 0.8 were defined as FFR-positive and FFR-negative, respectively. Intra- and inter-observer differences were negligible. AUC indicated that cross-sectional area reduction effectively discriminated between FFR-positive and FFR-negative cases, yielding a sensitivity of 0.882 and specificity of 0.933 at the cutoff of 50% area reduction, with an AUC of 0.976. Lesions with less than 45% cross-sectional area reduction on coronary CT angiography were not FFR-positive. When ROC analysis was conducted for lesion characteristics, AUC did not significantly improve. In conclusion, the coronary cross-sectional area stenosis severity from coronary CT angiography distinguished between FFR-positive and FFR-negative lesions with high accuracy. Area reduction on CT angiography is indicated to be clinically useful for predicting the FFR.
The use of pyrophosphate scintigraphy to measure the heart-to-contralateral lung ratio in the presence of rib fractures overlapping the heart
Authors: SUYAMA JUMPEI , Takakuwa Chieko , Kawada Muneyuki , Shirakawa Yuya , Yokoyama Kenichi 
Published: July 2024

Abstract

Objective: Tc-99m-pyrophosphate has been used to evaluate amyloid transthyretin (ATTR) cardiac amyloidosis. Quantitative evaluation is widely performed by calculating the heart-to-contralateral lung (H/CL) ratio, but bone lesions may reduce measurement accuracy. We investigated the accuracy of the PYP-ROI software, developed by our group, in addressing the errors caused by bone lesions when measuring the H/CL ratio.
Methods: This retrospective study comprised 17 patients (mean age: 70.7 ± 13.9 years; male:female ratio 13:4) who underwent pyrophosphate scintigraphy to diagnose cardiac amyloidosis during March 2021–November 2021 and in whom cardiac amyloidosis was excluded clinically. None of the participants had rib fractures or other bone lesions. Simulated rib fractures were created, and the H/CL ratio was determined for various pathologies. The differences between these values and the H/CL ratios obtained from the original images were compared.
Results: Based on our findings, which confirmed the software’s utility, we recommend the following steps for imaging analysis. First, the accumulation in the fracture should be eliminated, by manual calculations in the absence of a removal function. Second, compensation for the removed part should be calculated using the average count of the surrounding area. Third, if the fracture accumulation is weaker than the sternal accumulation, the fracture should be included in the measurement. Fourth, if fracture uptake is clearly higher than sternal uptake, the impact is significant.
Conclusions: This study supports the utility of removing or compensating for the accumulation in rib fractures using PYP-ROI software. However, verification in larger clinical studies is required.
HSBP7 Rescue of a Titin Cardiomyopathy Identified by Morphological Profiling
Authors: Chopra Anant , Pei Ruifan , Brydon Elizabeth , Lee Elizabeth , Hill Matthew , Jamali Nasim , Ye Jiangchuan , Roselli Carolina , Verdugo Carmen Diaz , Fleming Stephen , Xiao Ling , Sayed Zeina , Kost-Alimova Maria , Klattenhoff Carla , Hayat Sikander , Carpenter Anne , Cimini Beth , Singh Shantanu , Ellinor Patrick 
Published: July 2024

Abstract

Dilated cardiomyopathy (DCM), a genetic heart disease, is a major contributor to heart failure and cardiac transplantation. Of the many genes underlying DCM, the most common cause is loss of function mutations in the sarcomeric protein titin. In disease, alterations in cardiomyocyte (CM) contractile function are accompanied by morphologic changes. Thus, understanding how genetic and environmental perturbations affect CM morphology may identify new genes or pathways underlying heart failure. Here, we developed CARDIO (Cardiomyocyte Analysis using Robust Cell Painting Imaging and Output), an assay that allows high-content morphological profiling of human stem cell derived CMs (iPS-CMs). After optimization and validation, we applied our CARDIO approach to a CRISPR knockout assay of 39 genes selected from a genome wide association study (GWAS) of cardiac contractile function. We identified a novel role for two genes, YWHAE and HSPB7 with divergent effects in CM morphology and function. Functional validation using engineered heart tissues (EHTs) demonstrated YWHAE knockout (KO) had a similar functional profile as titin KO. In contrast, loss of HSPB7 induced a hypertrophic phenotype and restored contractile function in a titin model of DCM. In sum, our approach demonstrates that the combination of morphological profiling with functional assessment can identify novel genes involved in heart failure at scale, and potentially identify biological mechanisms for therapeutic development.
Predicting mortality in geriatric patients with fever in the Emergency Departments: a prospective validation study
Authors: Akbari Hamideh , Mirfazaelian Hadi , Safaei Arash , Aghdam Hakime Ghafari , Akhgar Atousa , Jalili Mohammad 
Published: July 2024

Abstract

Objective:
Emergency physicians are always faced with the challenge of choosing the appropriate disposition for elderly patients in order to ensure an acceptable care plan and effective use of resources. A clinical decision rule has been proposed but not validated to help ED physicians with decision making. This rule employs leukocytosis, severe coma, and thrombocytopenia as predictors of 30-day mortality. We sought to determine the performance of this clinical prediction rule in a prospective study in a setting different from where it was developed.
Method and Materials:
In this prospective cohort study in a 1200-bed tertiary care, patients older than 65 years old who visited the ED with fever were enrolled. All elements of the rule were collected and the total score was calculated for each patient. Patients were also categorized as low risk (score 0-1) or high risk (score≥2). Thirty-day follow-up was performed to determine the patient outcome (survival or mortality).
Result:
A total of 296 patients were entered our final analysis. The mortality rate by the Geriatric Fever Score was 62.5% for patients with a score of 0, 35.1% for 1, 42.4% for 2, and 60% for 3. When divided into two risk groups low risk group had a mortality of 36.6% and high-risk group had a mortality of 44.2%.
Conclusion:
We concluded that elderly patients who present to ED with fever and have a score of 2 or higher on Geriatric Fever Score are at higher risk of mortality at 30 days.
Differential Association Between Cumulative Dose of 5α-Reductase Inhibitors and Mortality
Authors: Kim Jinhyun , Jang Suk-Yong , Park Eun-Cheol 
Published: July 2024

Abstract

The association between various cumulative doses of 5-ARIs and mortality remains unclear. To examine the absolute and time-averaged cumulative doses of 5-ARIs and their association with all-cause and cause-specific mortality among patients with benign prostatic hyperplasia (BPH) or androgenic alopecia (AGA).
A nested case-control study was conducted. For each patient who died, up to five controls were matched, based on age, sex, follow-up duration, and date of BPH or AGA diagnosis. The cumulative 5-ARI dose was calculated as the cumulative defined daily dose (cDDD) for the absolute and time-averaged doses over the follow-up period.
The study involved 3,084 cases and 14,630 controls. The <365 cDDDs group and 365–730 cDDDs group had higher mortality rates, whereas the >5840 cDDDs group had a significantly reduced mortality risk. A similar result was observed for the duration-averaged cumulative doses. Cause-specific analysis revealed higher suicide rates at lower cumulative doses and lower cardiovascular mortality rates at higher cumulative doses. Other cause-specific mortality rates were not statistically significant.
The findings revealed a complex relationship between cumulative 5-ARI dosage and all-cause mortality, highlighting the need for careful monitoring of patients using 5-ARIs, particularly concerning the elevated risk of suicide.
Short-term Group Venetoclax Combined with Azacitidine for Treating Newly Diagnosed Elderly Acute Myeloid Leukemia: A Retrospective Study
Authors: Yu Zhuruohan , Li Shuangyue , Pei Renzhi , Lu Ying , Wang Yuxiao , Yuan Jiaojiao 
Published: July 2024

Abstract

The induction regimen of venetoclax (VEN) in combination with demethylating agents has improved outcomes in elderly patients with acute myeloid leukemia (AML). However, the optimal course of VEN use during treatment needs further exploration. We conducted a retrospective study to determine the efficacy and safety of VEN in 90 newly diagnosed elderly patients with AML. This included 47 patients who used VEN for 14 days in combination with the azacitidine (AZA) regimen and 43 patients who used VEN for 28 days in combination with the AZA regimen. The rates of clinical remission were similar in the two groups, with a shorter time to neutropenia recovery in the shorter duration group. The short-term group also experienced reduced febrile neutropenia and a trend toward a lower incidence of other adverse events. With a median follow-up time of 494 days, there was a non-significant difference in median overall survival and Event-free survival observed between the two groups. This retrospective study demonstrated that VEN 14 days combined with AZA had similar efficacy to the VEN 28 days regimen combined with AZA. The short-term VEN combined with AZA regimen ensured efficacy with relatively less myelosuppressive effect, shortened blood recovery time, and reduced incidence of infection and fever during treatment. This regimen is suitable for elderly patients who are in poor physical condition and unable to tolerate low-dose chemotherapy and the long-term VEN combined with AZA regimen. It is easier to accept and more regarding the biopsychosocial medicine model.
A qualitative Study on Stress response and Coping of General Practitioners at the Beginning of Independent Duty
Authors: BIAN WEINA , ZHANG YUE , HE JIELING , YANG HONGWEI , MA NINA , CHEN GUANG , QIN SHUMIN , ZHENG QINGHUA 
Published: July 2024

Abstract

Purpose
This study aims to explore the challenges and stresses encountered by general practitioners during standardized residency training while on independent duty, as well as identify effective coping strategies.
Methods
The study adopted qualitative research. We conducted in-depth interviews with 7 trainees who were undergoing standardized training courses for general practitioners and analyzed the obtained information using content analysis.
Results
We extracted three themes, stress and challenges, coping strategies, and the impact of being on duty on one's work or life, from the study.
Conclusions
The qualitative research revealed the psychological state experienced by general practitioners when faced with stresses and challenges, as well as effective coping strategies employed during the initial phase of independent duty.
Major Causes of Accidents in Urban Transportation Network and Methods to Enhance its Safety
Authors: Jafari Mohsen , Amin Reza , Khodaii Ali 
Published: July 2024

Abstract

Urban accidents are one of the major causes of death and injuries in metropolitan areas. As urbanization continues to accelerate, with more people moving to cities seeking better opportunities and a higher standard of living, the risks associated with urban accidents become more apparent. Investigating the reasons behind this issue and proposing effective solutions is a concern for policymakers. In some cases, the driver is responsible for accidents, while in others, the built environment contributes to the accidents. The aim of this article is to examine factors related to built-environment conditions. Overall, the parameters are divided into four categories: accident, demographic, traffic, and roadway. Relationships between each factor and the occurrence of accidents (in terms of fatalities, injuries, and damages) are examined. The factors in this report focus on external factors related to vehicle activities are the focus of this report. This study focuses on the causes of urban accidents in Tehran, based on aggregate data from 2000 to 2020 in each region. It is concluded that the main causes of this issue include the high number of motorcycles in the city center, excessive speed on congested roads, high vehicle density in certain parts of the city, and unsafe roadways. Effective measures include road repair and renovation, urban development, the implementation of speed limits on highways, the imposition of restrictions on motorcycles on high-speed roads, implementing demand management strategies to reduce traffic on congested roads, establishing feasible options for motorcycle riders, and rigorously enforcing traffic regulations.
Debiased Recommendation Based on Comparative Learning
and Causal Embedding
Authors: Liu Dingyuan , Xun Yaling , Hu Xiaoying , Li Yanfeng Li 
Published: July 2024

Abstract

Biases in recommendation systems significantly reduce recommendation accuracy and user experience. To address the issues in traditional recommendation systems: (1) inaccurate recommendation results due to ineffective modeling of users’ long-term and short-term interests, (2) popularity bias caused by the conformity effect, a debias recommendation method based on contrastive learning and causal embedding (CLACE). CLACE first employs two independent encoders to model users’ long-term and short-term interests separately. Then, a contrastive learning framework is designed to supervise the similarity between the long-term and short-term interest representations and interest proxies. A dynamic attention mechanism is introduced to adaptively adjust the weights of long-term and short-term interests to accurately reflect users’ preference biases. Simultaneously, to fundamentally reduce the popularity bias induced by the conformity effect during the recommendation process, a causal embedding model is introduced to separate user interests from the conformity effect, eliminating the negative impact of the conformity effect on recommendation results and achieving more precise recommendations. The effectiveness of the proposed CLACE is validated on two public datasets, and experimental results demonstrate that CLACE significantly improves recommendation accuracy, recall, and normalized discounted cumulative gain.
PiRPLO: a single-run method for calibrating wildland fire simulations like statistical models
Authors: Waeselynck Valentin , Lautenberger Chris , Saah David 
Published: July 2024

Abstract

We introduce a statistically-inspired class of loss functions for scoring predictive models of wildfire risk, quantifying how well a model fits observed fire occurrence. These loss functions are derived as a weighted generalization of Poisson process deviance; this generalization unifies various existing approaches in the statistical wildfire literature and suggests new approaches, enabling improvements by relaxing requirements of probabilistic independence, using more of the historical information, and giving more importance to the largest fires. Nontrivially, we apply these tools to calibrating the parameters of wildland fire Monte Carlo simulations, and in particular the joint distribution of ignitions and fire durations. We argue that such an integrated approach is more reliable than optimizing the distribution of ignitions in isolation, because it optimizes the end results of simulations. We also describe a fast algorithm for approximating the loss function on candidate distributions of ignitions and durations without having to repeatedly run new simulations: using a sample-reweighting approach, a calibration simulation is run once, and the family of possible ignition distributions is defined and explored after the fact. In particular, distribution mixtures can be used for ensembling fire behavior models, and fire durations can be modeled and calibrated either explicitly via a conditional probability density function, or implicitly via a parametric hazard function that represents containment effectiveness. Furthermore, this method enables the use of gradient-based optimization algorithms for finding the best-fitting parameters. This enables a workflow similar to fitting parametric statistical models. We call this approach Plug-in Reweighted Poisson Likelihood Optimization (PiRPLO).
Internal structure modification of a simple monthly water balance model via incorporation of a machine learning-based nonlinear routing
Authors: Okkan Umut , Ersoy Zeynep Beril , Fistikoglu Okan 
Published: July 2024

ABSTRACT

Among various monthly water balance models, one of the models that has the simplest structure and offers a well-behaved conceptual platform is the GR2M. Despite the widespread use of the model with two-free parameters, the fact that it tends to produce relatively large errors in peak flow months necessitates some modifications to the model. The reason for the mentioned simulation deficiencies could be that the relationship between the routing reservoir and the external environment of the basin is controlled by a single parameter, making the storage–discharge relationship linear. Therefore, in this study, least squares support vector regression, one of the nonlinear data-driven models, has replaced the routing part of the GR2M to enhance the monthly runoff simulation. The performance of the three-parameter hybrid model (GR3M), which was developed by considering the parameter parsimony point of view and including a machine learning (ML)-based nonlinear routing scheme, was examined in some locations in the Gediz River Basin in western Turkey. Statistical performance measures have shown that GR3M, which both leverages the capabilities of an ML model and blends conceptual outputs within a nested scheme, clearly outperforms the original GR2M. The proposed modification has brought significant improvements, especially to high-flow simulations.
Multiple conceptual hydrological models for simulating streamflow in data-sparse river basins: an application of the Vietnamese Cau river basin
Authors: Tran Tuan Thach 
Published: July 2024

ABSTRACT

Streamflow plays a critical role in water resources management, requiring precise estimation, especially in data-sparse river basins. In this study, multiple hydrological models (HYMOD, GR4J, and NAM) are presented and employed to simulate streamflow in the data-sparse Vietnamese Cau river basin at the Thac Rieng station, providing an illustrative example. Four indices named Nash–Sutcliffe efficiency (NSE), correlation coefficient (r), Kling–Gupta efficiency (KGE), and root mean square error (RMSE) are implemented to quantitatively assess model performance. Firstly, using the available hydrometeorological data from 1 January 1960 to 31 December 1981, parameters in each model are determined using the Shuffled Complex Evolution University of Arizona optimization method. The results show that three models reproduced acceptably observed streamflow, with NSE ranging from 0.65 to 0.75, r and KGE varying between 0.72 and 0.87, and RMSE is less than 6.5% of the observed streamflow magnitude. Secondly, the NAM model was found as the most suitable for simulating observed streamflow in the studied river basin. Thirdly, three models were applied to simulate streamflow in the period from 1 January 1982 to 31 December 2022, revealing similar magnitudes of four statistical indicators of observed and estimated streamflow. The capability of the three models in simulating streamflow in data-sparse river basins is finally discussed.
Assessing the environmental impacts of reclaimed and conventional water in hydroponics based on a life cycle assessment approach
Authors: Nadeem Abdullah , Tariq Muhammad Atiq Ur Rehman , Sarwar Kaleem , Iqbal Mudassar , Ahmad Khalil , Ahmed Khalil 
Published: July 2024

ABSTRACT

As the global population approaches 9 billion by 2050, challenges of food and water scarcity intensify. Hydroponics, an innovative and eco-friendly technology, has gained prominence in addressing these challenges. This study employs Life Cycle Assessment (LCA) to comprehensively evaluate the environmental and economic impacts of utilizing reclaimed water in a hydroponic system. Results from midpoint, endpoint, and normalized analyses reveal key contributors to the hydroponic system's environmental burden, including water, substrates, fertilizers, and energy sources. Significant impacts have been observed in marine and terrestrial ecotoxicity, as well as photochemical ozone formation. Reclaimed water consistently demonstrates lower environmental impacts compared to conventional water across various indicators, such as climate change (131 kg CO2 eq.), fine particulate matter formation (0.108 kg PM2.5 eq.), and freshwater consumption (0.291 cubic meters). The study emphasizes the potential of hydroponics with reclaimed water to offer sustainable and environmentally friendly agricultural practices. The detailed LCA results provide valuable insights for policymakers and stakeholders, promoting the adoption of hydroponics to address food and water scarcity challenges. From the findings, reclaimed water in hydroponics lowers the environmental impacts as compared to conventional water and PVC (Polyvinyl chloride) along with electricity is the major contributor in environmental burden.