bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping Irrigation Methods in the Northwestern US Using Deep Learning Classification
Authors: Nouwakpo S. K. , Bjorneberg D. , McGwire K. , Hoque O.
Published: August 2024

Many agricultural areas of the western United States and other parts of the world practice irrigation using a variety of irrigation methods. Maps of irrigation methods are needed but existing technologies are often unable to distinguish between different irrigation methods when they co‐exist on the same landscape. In this study, we develop a deep learning irrigation methods mapping tool for broad scale application. The technique uses a U‐Net model trained on Landsat 5‐ and 8‐derived input images. Training data consisted in irrigation method classified as Flood, Sprinkler or Other on agricultural fields from the Utah Water Related Land Use data set and additional labeling in selected areas of southern Idaho. An ensemble of 10 trained models had an overall accuracy of 0.78. Precision for Flood, Sprinkler and Other were 0.73, 0.82, and 0.80 while recall values were 0.75, 0.74, and 0.84 respectively. Model performance was generally stable throughout the training years but varied by areas. The best performance was obtained in regions with uniform irrigation method across large patches while small fields of contrasting irrigation method with their surroundings were inadequately predicted. Model prediction in an irrigated watershed of southern Idaho for 2006, 2011, 2013, and 2016 were consistent with previously published survey data. This methodology provides a tool for water resource managers to estimate irrigation methods in agricultural watersheds where natural precipitation is low during the growing season and irrigation methods include center pivots, wheel lines and flood irrigation.
Declining Reservoir Reliability and Increasing Reservoir Vulnerability: Long‐Term Observations Reveal Longer and More Severe Periods of Low Reservoir Storage for Major United States Reservoirs
Authors: Simeone Caelan E. , Hammond John C. , Archfield Stacey A. , Broman Dan , Condon Laura E. , Eldardiry Hisham , Olson Carolyn G. , Steyaert Jen C.
Published: August 2024

Hydrological drought is a pervasive and reoccurring challenge in managing water resources. Reservoirs are critical for lessening the impacts of drought on water available for many uses. We use a novel and generalized approach to identify periods of unusually low reservoir storage—via comparisons to operational rule curves and historical patterns—to investigate how droughts affect storage in 250 reservoirs across the conterminous U.S. (CONUS). We find that the maximum amount of water stored in reservoirs is decreasing, and that periods of unusually low storage are becoming longer, more severe, and more variable in (a) western and central CONUS reservoirs, and (b) reservoirs with primarily over‐year storage. Results suggest that reservoir storage has become less reliable and more vulnerable to larger deviations from desired storage patterns. These changes have coincided with ongoing shifts to the hydroclimate of CONUS, and with sedimentation further reducing available reservoir storage.
Projected Poleward Migration of Western North Pacific Tropical Cyclone Genesis
Authors: Jian Danlei , Zhao Haikun , Klotzbach Philip J. , Raga Graciela B. , Gao Jun , Cao Jian , Wang Chao , Ma Zhanhong
Published: August 2024

The recently‐observed poleward shift in western North Pacific tropical cyclone (TC) genesis has increased the TC threat to East Asia. We find that the poleward shift of TC genesis since 1979 is linked to mega‐ENSO. A downscaling analysis of TC genesis latitude given the constraint of mega‐ENSO using 30 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) show a continued increasing poleward shift with additional warming. We use the dynamic genesis potential index as a TC proxy in future CMIP6 simulations. These simulations show enhanced TC formation in the subtropics and decreased TC formation in the tropics. Modeled TCs in CMIP6 high‐resolution models that well represent mega‐ENSO project future poleward shifts in TC genesis. Both observations and simulations show that extra‐tropical North Pacific sea surface temperature warming associated with mega‐ENSO are the primary driver of the TC genesis poleward shift. Our study provides new insights into climate change‐driven TC migration.
The Coldest and Densest Overflow Branch Into the North Atlantic is Stable in Transport, But Warming
Authors: Larsen Karin Margretha Húsgarð , Hansen Bogi , Hátún Hjálmar , Johansen Guðrið Eriksdóttir , Østerhus Svein , Olsen Steffen Malskær
Published: August 2024

The overflow of cold water through the Faroe Bank Channel (FBC) is the densest water crossing the Greenland‐Scotland Ridge and the densest source for the Atlantic Meridional Overturning Circulation (AMOC). Here, we show that the overflow volume transport remained stable from 1996 to 2022, but that the bottom water warmed at an average rate of 0.1°C per decade, mainly caused by warming of deep waters upstream. The salinity of the overflow water has increased as a lagged and reduced response to the salinity increase seen in the upper‐layer source waters. Therefore, the potential density of the bottom water over the FBC sill shows no statistically significant trend. After entrainment of warmer ambient waters downstream of the FBC, the nonlinear density dependence upon temperature implies, however, that the overflow contributed water of reduced density to the local overturning and the deep limb of the AMOC.
Cloud Radiative Effects Slow Sea Ice Changes During Summer Arctic Dipole Anomaly
Authors: Zhang Haotian , Zhao Chuanfeng , Xia Yan , Chen Annan , Yang Yikun , Yang Jie , Zhao Xin , Chi Yulei , Xu Hongtao , Zhong Shouyi
Published: August 2024

Over the past 30 years, the Arctic Dipole Anomaly (DA) has repeatedly led to record lows in summer sea ice extent, with cloud radiative effects (CRE) playing a crucial regulatory role. Here, we reveal the CRE variations between positive and negative DA events and elucidate the slowing impacts of CRE on sea ice thickness (SIT) changes. The DA triggers robust meridional winds and transpolar drift, markedly reducing SIT in the Beaufort Sea (BeS), Chukchi Sea (CS), and East Siberian Sea (ESS), while increasing it in the Greenland Sea (GS). CRE significantly slow SIT changes, contributing +14.4, +4.4, +16.4, and −26.7 cm to changes from June to August, against total changes of −55.9, −29.4, −39.8, and +42.8 cm in September over BeS, CS, ESS, and GS, respectively. This study underscores the key impacts of CRE on sea ice variation, emphasizing their significance in the polar climate system.
Synoptic and Mesoscale Dynamics of Cold Surges Over the South China Sea and Their Control on Extreme Rainfall
Authors: Tan I. , Reeder M. J. , Birch C. E. , Peatman S. C. , Webster S.
Published: August 2024

We investigate the synoptic and mesoscale dynamics of two wet and two dry cold surges in January 2021 using a combination of observations, reanalysis, and convective‐scale model forecasts from the Met Office Unified Model (MetUM). We focus on the wet surges, and particularly the wettest days which are locally extreme over Singapore and the surrounding region (i.e., the daily mean and area‐averaged rainfall over 20 years exceeds the 99th percentile). On the large scale, the wet surges are characterized by an anomalously strong anticyclone over Siberia prior to their onset. The anticyclone and resultant surge winds are stronger than those of the dry surges. There is also a relatively moist (dry) environment prior to the onset of the wet (dry) surges, with the Madden‐Julian Oscillation (MJO) being in Phase 3 (Phase 6). On the mesoscale, the combination of the cold surge and a local tropical low produce strong, moist north‐easterly winds and convection over the Singapore region. The equatorward advection of positive anomalies of equivalent potential temperature resembles a weak gravity‐current‐like structure at its head, although the spatial scale is much too large for a gravity current. There is a moist bias in the model forecasts, although the precipitation is underestimated regionally during the wet surges and particularly on the extreme rainfall days. Overall, the model forecasts perform well synoptically but not in the details of mesoscale convection.
Comparing the Upper Mesospheric Temperature Trend and the Response to Solar Activity Derived From the Daily Mean and Nocturnal Na Lidar Observations
Authors: Yuan Tao , Pena Melania , Hsu Chih‐Ting , Qian Liying
Published: August 2024

Over the past decades, various experimental and numerical model studies have indicated cooling trend in the mesosphere and lower thermosphere (MLT), while the magnitude of the trend varies noticeably. Previous studies using the lidar observations derived the temperature trends and solar responses solely from the traditional nocturnal measurements. While these archived results are more or less in agreement with modeling studies, one of the main uncertainties in these studies is the potential biases induced by the trends of the diurnal tide forced in the lower atmosphere, and that of the in situ exothermal reactions involving the photolysis. In the MLT, the diurnal tide has significant seasonal variations, considerable amplitude and is one of the dominant dynamic sources. However, its potential effects in the trend studies have rarely been discussed. In this paper, we present and compare the long‐term temperature trends in the upper mesosphere utilizing the daily mean and nightly mean temperature profiles measured by a Sodium (Na) Doppler lidar at midlatitude. The system was operating routinely in full diurnal cycles between 2002 and 2017, obtaining a unique multi‐year temperature data set. A customized multi‐linear regression (MLR) model is applied to determine the linear trends and the other fitting parameters, such as ENSO and solar F10.7 responses in the upper mesosphere. This study indicates the daily mean cooling trend between 84 and 98 km is larger than that of nightly mean trend by ∼−1 K/decade, while differences in the solar response are within the fitting uncertainties.
Serum neurofilament light at diagnosis: a prognostic indicator for accelerated disease progression in Parkinson’s Disease
Authors: Pedersen Camilla Christina , Ushakova Anastasia , Alves Guido , Tysnes Ole-Bjørn , Blennow Kaj , Zetterberg Henrik , Maple-Grødem Jodi , Lange Johannes
Published: August 2024

Neurofilament light chain (NFL) is elevated in neurodegenerative diseases, including Parkinson’s disease (PD). This study aimed to investigate serum NFL in newly diagnosed PD and its association with cognitive and motor decline over 10 years. Serum NFL levels were measured in PD patients and controls from the ParkWest study at diagnosis (baseline) and after 3 and 5 years. Mixed-effects regression analyzed changes in NFL and the association with annual changes in MMSE and UPDRS-III scores over 10 years. PD patients had elevated serum NFL at all visits and a faster annual increase over 5 years compared to controls (0.09 pg/mL per year; p = 0.029). Higher baseline NFL predicted faster cognitive decline β −0.77 transformed MMSE; p = 0.010), and a 40% NFL increase predicted future motor decline (β 0.28 UPDRS-III; p = 0.004). Elevated serum NFL in early PD is linked to faster cognitive and motor impairment, suggesting its prognostic value in PD biomarker panels.
QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
Authors: Diez Sebastian , Lacy Stuart , Urquiza Josefina , Edwards Pete
Published: August 2024

The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability.
Design strategy and molecular level understanding: hole transport materials with suitable transition dipole orientation for OLEDs
Authors: Kumar Krishan , Kumar Sunil , Karmakar Anirban , Sharma Dipanshu , Chen Feng-Rong , Nagar Mangey Ram , Jou Jwo-Huei , Banik Subrata , Ghosh Subrata
Published: August 2024

A combined experimental and theoretical study on a group of phenothiazine-substituted pyridine is reported.
Role of water in vapor permeation through graphene oxide membranes
Authors: Kim Choonsoo , Lee Byeongho
Published: August 2024

This study demonstrates that GO membranes enable efficient separation of aqueous and alcoholic vapor mixtures and discusses the critical vapor-permeation mechanism.
Constructing Cu0/Cu+ interfaces on Cu-based MOF derivatives to promote the adsorption stability of intermediates in the process of CO2 electroreduction to C2 products
Authors: Hong Jingwei , Li Wanli , Shang Jin , Yamashita Hiromi , Hu Yun
Published: August 2024

The unique Cu0/Cu+ interface of Cu-MOF74/Cu2O-350 enhances the adsorption of reaction intermediates and provides more active sites, thereby increasing the faradaic efficiency (FE) of CO2 reduction to C2H4.
Innovative on-site colorimetric assay of tetracyclines by smartphones in waters and milks based on a synergistic co-catalyst FeMoO4@Fe7S8 with strong interactions and complexation
Authors: Gu Jingjing , Gong Hailong , Li Yuhao , Ma Qinqin , Hou Xiaofeng , Shen Siyu , Liu Tingting , Wang Xuedong
Published: August 2024

The synthesis of co-catalyst FeMoO4@Fe7S8 with strong interactions and complexation and the application of innovative on-site colorimetric assay of tetracyclines by smartphones in waters and milks.
Detection and infectivity of SARS-CoV-2 in Korean municipal wastewater facilities and characterization of environmental factors influencing wastewater-bound SARS-CoV-2
Authors: Kim Jayun , Kim Yoon-ji , Lee Sook-young , Oem Jae-Ku , Kim Subin , Kim Keugtae , Jung Woosik , Kim Sungpyo , Jeong Dong-Hwan , Lee Minjoo , Lee Soo-Hyung , Kim Hyunook , Park Joonhong
Published: August 2024

Nationwide wastewater was analyzed during COVID-19 surges. Sample processing and SARS-CoV-2 detection were optimized. Virus non-infectivity was validated. Rose with local COVID-19 spikes. Temperature and water quality impact modeling.
Comprehensive investigation of multifunctional polyaniline/reduced graphene oxide nanocomposites synthesized from deep eutectic solvents: experimental, RSM, ANN and computational studies
Authors: Boublia Abir , Guezzout Zahir , Haddaoui Nacerddine , Badawi Michael , Lakikza Imane , Belkhettab Ilyas , Moumeni Ouahiba , Aouni Saoussen Imene , Alam Manawwer , Benguerba Yacine
Published: August 2024

This work reports a comprehensive investigation into the synthesis, modeling, and characterization of multifunctional polyaniline/reduced graphene oxide (PANI/rGO) nanocomposites, with a focus on their synthesis using deep eutectic solvents (DES).
Cornulacin: a new isoflavone fromCornulaca monacanthaand its isolation, structure elucidation and cytotoxicity through EGFR-mediated apoptosis
Authors: Badawy Ahmed M. , Eltamany Enas E. , Hussien Rodina M. , Mohamed Osama G. , El-Ayouty Mayada M. , Nafie Mohamed S. , Tripathi Ashootosh , Ahmed Safwat A.
Published: August 2024

Cornulacin, a new isoflavone, was isolated fromCornulaca monacanthawith structural elucidation and cytotoxicity against ovarian A2780 cancer through apoptosis induction.
Computational-assisted molecular design, synthesis and application of benzobisthiadiazole-based near-infrared dye in electrowetting displays
Authors: Chen Junheng , Lin Haoteng , Wang Xintong , He Dinggui , Luo Baoyi , Guo Yuanyuan , Chen Wangqiao , Zhou Guofu
Published: August 2024

Computational-assisted molecular design of benzobisthiadiazole-based donor–acceptor–donor type near-infrared dyes, their synthesis and application as colored inks in electrowetting displays.
Multifunctional microwave absorption materials: construction strategies and functional applications
Authors: Xiao Junxiong , He Mukun , Zhan Beibei , Guo Hua , Yang Jing-liang , Zhang Yali , Qi Xiaosi , Gu Junwei
Published: August 2024

Classification and multifunctional scalability of advanced microwave absorbing materials.
Biopolymeric and lipid-based nanotechnological strategies for the design and development of novel mosquito repellent systems: recent advances
Authors: Nwagwu Chinekwu , Onugwu Adaeze , Echezona Adaeze , Uzondu Samuel , Agbo Chinazom , Kenechukwu Frankline , Ogbonna John , Ugorji Lydia , Nwobi Lotanna , Nwobi Obichukwu , Mmuotoo Oluchi , Ezeibe Ezinwanne , Loretz Brigitta , Tarirai Clemence , Mbara Kingsley Chimaeze , Agumah Nnabuife , Nnamani Petra , Ofokansi Kenneth , Lehr Claus-Micheal , Attama Anthony
Published: August 2024

This review critically examines the recent advances in the innovative use of biopolymeric and lipid-based nanomaterials in developing safer and more effective mosquito-repellent formulations to prevent mosquito-transmitted diseases.
Activating S surfaces by reversing the electron supply direction for fast hydrogen sensing
Authors: Jia Xin , Li Musen , Li Yurou , Qiao Panzhe , Wang Xiaowu , Jiang Yi , Guo Mengmeng , Hu Pengfei , Lu Bo , An Bao-Li , Xue Zhenggang , Xu Jiaqiang
Published: August 2024

The nature of a built-in electric field within supported metal catalysts plays a crucial role in regulating gas adsorption and electron transfer during the gas-sensing process.
Thermally stable NIR broad emission of Cr3+ doping phosphor with a high output power
Authors: Chen Zhishan , Zhang Shaoan , Li Zhenzhang , Ye Huacong , Yan Haoran , Xu Jialong , Gao Ling , Li Yang , Zhang Shizhen
Published: August 2024

The anti-thermal quenching of Cr3+ is determined by the attribution of the defect level, which originates from the coupling between the doped ion Cr3+ and the VO. NIR pc-LED achieves an NIR output power of 59.67 mW with working current of 150 mA.
Aromatic side chain manipulation in A–DA′D–A type acceptors for organic photovoltaics
Authors: Wen ChengLong , Yuan Jun , Zhang Zhiguo , Li Dongxu , Zhou Yuqian , Liu Wanqiang , Zhou Zaichun , Li Yungui , Jiang Lihui , Zou Yingping
Published: August 2024

Three acceptors with different aromatic side chains were synthesized and the photovoltaic performance effects of steric hindrances were studied. BTP-1-iPr better matches the energy level of PM6, obtaining higher VOC, FF and PCE of 17.19%.
Biomimetic mineralization: construction and biomedical applications of biohybrid materials
Authors: Chen Tiantian , Wang Yingjie , Wang Keheng , Dai Min , Duan Yu , Mao Chun , Wan Mimi
Published: August 2024

Construction of biomineralized biohybrid materials and their biomedical applications.
Electrochemical synthesis of selenyl imidazo[2,1-b]thiazinones via three-component reactions
Authors: Yue Yuancheng , Chen Ziren , Xue Fei , Wang Bin , Zhang Yonghong , Xia Yu , Wu Shaofeng , Jin Weiwei , Liu Chenjiang
Published: August 2024

In this paper, we have developed an efficient strategy for the concise synthesis of diverse selenyl imidazo[2,1-b]thiazinones via electrochemical oxidative three-component tandem reactions in the absence of transition metals, and oxidants.
Computational investigation of the effects of polymer grafting on the effective interaction between silica nanoparticles in water
Authors: Singh Yuvraj , Choudhury Chandan K. , Ghosh Rikhia , Singh Rakesh S.
Published: August 2024

Altering solvent-mediated effective interaction between silica nanoparticles in water through polymer grafting.
Correction: Construction of energy transfer channels from [SbCl6]3− to Ln3+ (Ln3+ = Ho3+, Er3+) in Cs2NaGdCl6 for advanced anti-counterfeiting materials
Authors: Li Yanyang , Du Huimin , Ma Yue , Liu Meifang , Zou Jian , Wang Shentang , Yang Jun , Hu Shanshan , Lin Jun
Published: August 2024

Correction for ‘Construction of energy transfer channels from [SbCl6]3− to Ln3+ (Ln3+ = Ho3+, Er3+) in Cs2NaGdCl6 for advanced anti-counterfeiting materials’ by Yanyang Li et al., J. Mater. Chem. C, 2024, 12, 12589–12597, https://doi.org/10.1039/D4TC02186J.
Multi-Class Imbalance Classification of Diabetes Cases Using Light Gradient Boosting Machine
Authors: Manfaati Nur Indah , Rosadi Dedi , Abdurakhman
Published: August 2024

Diabetes is the third leading cause of death in Indonesia. Diabetes is considered a silent killer because it kills slowly and triggers various complications of chronic diseases in the body of the sufferer. Early detection of diabetes is very important to reduce the risk of more serious health problems and reduce the country's socio-economic losses in diabetes management. Machine learning classification is an alternative method that can be used for early detection of diabetes by predicting category labels from observed data. This study aims to classify diabetes using the Light Gradient Boosting Machine (LGBM) method with Synthetic Minority Oversampling Technique of Nominal and Continuous (SMOTENC). The SMOTENC oversampling method is used to handle the imbalance problem in the dataset used, while the LGBM method is used for multi-class classification of diabetes. The results showed that by applying the SMOTENC technique, a more balanced data distribution was obtained, so that when used in the classification process using LGBM, it resulted in high model performance. Based on the confusion matrix, the accuracy value is 90%.
Mathematics research in India: A scientometrics and complex network analysis
Authors: Chin Jia Hou , Balasubramaniam Pagavathi G. , Ratnavelu Kuru
Published: August 2024

Over the past three decades, there has been a noticeable growth in both the quantity and quality of scientific research in India. In recent years, India’s growing prominence on the global map of research productivity has become highly visible. Numerous scientometrics studies have been reported for various fields in India such as computer science, nanoscience, nanotechnology, artificial intelligence, solar cells, and dentistry among others. However, there is a lack of scientometric research in the domain of mathematics within India, despite its crucial role in propelling advancements across various disciplines. Furthermore, research collaboration has emerged as an important factor in accelerating the progress of mathematics research in a country since the 20th century. Therefore, studying collaboration trends becomes an essential component of scientometrics. In this paper, we comprehensively analyze the state of mathematics research in India, including collaboration trends, using methods from scientometrics and complex network analysis. Scientometrics offers an overview of the nature of mathematics research being undertaken, while complex network analysis reveals the dynamics and structural variation of research collaborations at the country and institutional level across various temporal periods. The findings provide insights into the development and collaboration trends of mathematics research in India from 2001 to 2021. There has been an exponential increase in publications since 2015, with approximately 20% of mathematics research conducted in India appearing to be associated with physics research. In terms of research collaborations, there has been a notable increase in collaborations between India and several countries including the USA, China, Saudi Arabia, and Turkey. However, an analysis of institutional collaboration networks suggests that these collaborations tend to be small-scale research.
Performance of Brownian-motion Process Generated Universal Portfolio in Times of COVID-19 Pandemic
Authors: Pang Sook Theng , Liew How Hui , Khor Wei Sheng
Published: August 2024

The universal portfolio is a portfolio investment strategy which theoretically achieves good return. Brownian motion is a stochastic process which is heavily applied in various financial derivative pricing. The goal of this study aims to investigate the performance of finite order Brownian motion process generated universal portfolio (BMPGUP) using 3 independent stocks during COVID-19 pandemic. The research will include 3 daily traded stocks from respective countries, Malaysia KLCI, Singapore STI and Thailand SET 50 from January 2020 to June 2022. The performance is benchmark against Equally Weighted portfolio (EWP). According the investigation, BMPGUP performed better than the benchmark (compare with respective listed index within each country), especially in term of Sharpe ratio and Sortino ratio. This suggests that BMPGUP is a good alternative strategy for investors adopting the universal portfolio strategies.
Smallest Cubic Graphs with Given Girth and Skewness
Authors: Ng Chii Liang , Chia Gek L. , Wong Denis Chee-Keong
Published: August 2024

The skewness of a graph is the minimum number of its edges whose deletion results in a planar graph. We determine the minimum orders of cubic graphs with girth no more than 6 and skewness no more than 4. In passing, we also determine the skewness of all cubic cages whose girth is no more than 8.
Investigating the feature extraction capabilities of non-negative matrix factorisation algorithms for black-and-white images
Authors: Liew How Hui , Ng Wei Shean , Chen Huey Voon
Published: August 2024

Nonnegative matrix factorisation (NMF) is a class of matrix factorisation methods to approximate a nonnegative matrix as a product of two nonnegative matrices. To derive NMF algorithms, the optimisation problems for NMF are developed and the divergence used in the optimisation problems can have many forms. The β-divergence is the most popular and is used in this research. The NMF algorithms derived from the β-divergence have a few hyperparameters including the rank and the initial conditions. This paper surveyed on the software implementations of the NMF algorithms and then applied the open source software implementations of Frobenius norm based NMF algorithm, KL divergence based NMF algorithm and binary matrix factorisation (BMF) with fixed ranks to three classes of black-and-white images. For black-and-white images with a lot of common features (like MNIST), KL divergence NMF with appropriate initial guess is empirically found to be best NMF algorithm for black-and-white image feature extraction compare to other NMF algorithms. All NMF algorithms for data with little to no common features are useful in generating feature images which can be used to inspire art design as well as in the realm of computer vision.
Fish grades identification system with ensemble-based key feature learning
Authors: Akhyar Fityanul , Novamizanti Ledya , Wijayanto Inung , Wirawan Cahaya Irham , Wijaya Dede Chandra , Fredigo Agno , Ramdhon Ferdi , Lin Chih-Yang
Published: August 2024

Indonesia has already contacted the maritime nations due to its 5.8 million km2 of coastline. Consequently, fish products are among the most important commodities. Moreover, fish grading is a crucial step in the process of exporting fisheries products. Currently, in Indonesia, the process itself is manually inspected by an expert. In addition, this paper proposes to assist the industry by suggesting a method for grading fish. This method involves combining two essential fish parts with different resolutions: the high-level feature (the body) and the low-level feature (the eye) serve as defining characteristics. These two main parts are accurately localized using a deep learning-based object detection model, specifically YOLOv7, and extracted with an efficient and adaptive learned classification model, namely EfficientnetV2S. In the final stage, the two extracted features are combined and learned with Dense Layers to generate three distinct fish grades. Based on the experimental results, the proposed work achieved an accuracy, F1 Score, and recall of 96.88%, 97%, and 97%, respectively. The proposed model outperformed the baseline model, which relies solely on deep learning-based classification, by a significant margin.
Probability of Informed No-Tradings: A Copula-Based PIN Model with Zero-Inflated Poisson Distributions
Authors: Kao Chu-Lan Michael , Lin Emily , Wu Shan-Chi
Published: August 2024

Classical probability of informed trading (PIN) models assume that, given the information scenario, the number of buy and sell order flows are independently Poisson distributed, which imposes an assumption on the probability of no-trades. However, empirical data shows that the implied probabilities of no-trades do not match the aforementioned Poisson and independent assumptions. Therefore, we propose a new PIN model that better fits the data by using zero-inflated Poisson distributions and copula functions, which allow us to match the probability of no-trades. The expectation conditional maximization (ECM) is further proposed to tackle the parameter fittings, which is verified by simulation studies. The empirical studies show that this model outperforms the original PIN models, with significant parameters on the zero-inflations as well as copulas. In particular, we find that it is possible for an information to simultaneously increase the probability of no trade and boost up the average number of transactions, which contradicts the intuition.
A Rare Cause of Gastric Ulcer in a Treated Case of Diffuse Large B-Cell Lymphoma of Stomach—Cytomegalovirus-Associated Gastric Ulcer
Authors: Mahajan Akhil , Sundaram Sridhar , Mane Kiran , Puri Rahul , G.H Shravan
Published: August 2024

Cytomegalovirus (CMV), a double-stranded deoxyribonucleic acid virus, belongs to the Herpesviridae family. The seroprevalence of CMV varies from 40 to 100% depending on the population studied or detection method used. Infection by CMV is not a rare disease and is frequently observed in immunocompromised hosts with hematological or immunological diseases or under treatment with glucocorticoids or immunosuppressants. CMV infection can manifest as asymptomatic, constitutional symptoms or tissue-invasive diseases. The gastrointestinal (GI) tract is one of the most commonly involved systems and associated with 30% of tissue-invasive diseases among immunocompetent patients. GI involvement in CMV infection most commonly involves the colon. Upper GI tract involvement, especially CMV gastritis, has rarely been recognized or reported.
Impact of Candidemia on Survival Rates in Major Burn Patients: A Retrospective Study from the South of Türkiye
Authors: Kılıç Çil Merve , Özlü Özer , Başaran Abdülkadir
Published: August 2024

Objective In severely burned patients, fungal infections are among the most devastating complications. Candidemia is an important cause of mortality with an increasing incidence despite advances in burn care management. Higher affected body surface area, long intensive care unit (ICU) stay, flame burn, third-degree burn, and previous bacterial infections were associated with the development of candidemia. Candidemia in patients with major burns admitted to an ICU of a tertiary burns center is investigated.

Methods Patients hospitalized in the ICU of Adana City Training and Research Hospital from July 1, 2017, to November 10, 2020, were included. The demographic and clinical variables, the Candida species isolated from blood cultures and their antifungal susceptibilities, need for grafting, complications, and rate of mortality are evaluated retrospectively. Patients were grouped as “candidemia” or “noncandidemia” according to whether or not they experienced Candida bloodstream infection.

Results A total of 371 patients were included; the mean age was 22.02 ± 20.9 years. Most patients were male (69.5%). The percentage of burned surface area was 25.93 ± 17.6. The mean ICU stay was 16.95 ± 16.3 days. There were 90 candidemia episodes in 69 patients. The most commonly isolated Candida species were C. parapsilosis, C. tropicalis, and C. albicans. The mortality rates in the candidemia and noncandidemia groups were 24.6 and 5.6%, respectively (p < 0.001).

Conclusion Adhering to isolation rules, early wound debridement and closure, avoidance of catheters where possible, and avoidance of the early use of broad-spectrum antibiotics are important measures in reducing candidemia in patients with major burns. Candidemia was associated with greater burn surface areas, duration of hospital stay, and larger numbers of interventional procedures. However, previous bacterial infection receiving prolonged antibiotic therapy was the greatest risk factor of candidemia. Culture results are important to select the antifungal agent with high susceptibility, but results are not rapidly available. There is need for early clinical prediction measures to inform early and effective antifungal treatment.
Effect of Palivizumab Prophylaxis on Respiratory Syncytial Virus Hospitalizations in Preterm Infants Born to 290/7 to 316/7 Weeks of Gestational Age
Authors: Zamur Elifcan , Uygur Ozgun , Karadag-Oncel Eda , Gunes Sezgin , Sahin Suzan , Kefeli Demirel Melike , Engur Defne , Oncel Mehmet Yekta
Published: August 2024

Objective In 2020, in-line with the recommendations of the Turkish Neonatal Society, a new palivizumab indication was added for preterm infants with 290/7 to 316/7 weeks of gestational age. This study aimed to determine the risk factors of hospitalizations due to lower respiratory tract infections (LRTIs) and respiratory syncytial virus (RSV) in preterm infants (290/7–316/7 weeks of gestational age) who were or were not within the scope of palivizumab indication during the first two RSV seasons (2018–2019 and 2019–2020) and the next two RSV seasons (2020–2021 and 2021–2022) to evaluate the validity of the new indication of palivizumab reimbursement scope.

Methods This study was a two-center retrospective and prospective cohort study and included all preterm infants (290/7–316/7 weeks) aged 90 days and younger during the RSV season (October–March). The primary outcome was to compare the hospitalization rates between patients who received palivizumab and those who did not. The secondary outcome was to identify the risk factors for patients hospitalized due to LRTIs.

Results Of the 122 preterm infants included in the study, 48.3% (n = 59) were in the prophylaxis group (Group 1) and 51.7% (n = 63) were in the non-prophylaxis group (Group 2). It was noteworthy that 53.8% (n = 14) of the 26 infants hospitalized due to LRTIs were in Group 1 and 46.2% (n = 12) were in Group 2 (p = 0.682). Of the RSV PCR-positive infants, 62.5%(n = 5) were in Group 1 and 37.5% (n = 3) were in Group 2 (p = 0.30). The median length of hospitalization was similar in the groups (p = 0.123).

Conclusion The indication for palivizumab prophylaxis can be determined more clearly for our country in light of national multicenter studies with an increased sample size.
Electrophysiological features of cortical 3D networks are deeply modulated by scaffold properties
Authors: Callegari Francesca , Brofiga Martina , Tedesco Mariateresa , Massobrio Paolo
Published: August 2024

Three-dimensionality (3D) was proven essential for developing reliable models for different anatomical compartments and many diseases. However, the neuronal compartment still poses a great challenge as we still do not understand precisely how the brain computes information and how the complex chain of neuronal events can generate conscious behavior. Therefore, a comprehensive model of neuronal tissue has not yet been found. The present work was conceived in this framework: we aimed to contribute to what must be a collective effort by filling in some information on possible 3D strategies to pursue. We compared directly different kinds of scaffolds (i.e., PDMS sponges, thermally crosslinked hydrogels, and glass microbeads) in their effect on neuronal network activity recorded using micro-electrode arrays. While the overall rate of spiking activity remained consistent, the type of scaffold had a notable impact on bursting dynamics. The frequency, density of bursts, and occurrence of random spikes were all affected. The examination of inter-burst intervals revealed distinct burst generation patterns unique to different scaffold types. Network burst propagation unveiled divergent trends among configurations. Notably, it showed the most differences, underlying that functional variations may arise from a different 3D spatial organization. This evidence suggests that not all 3D neuronal constructs can sustain the same level of richness of activity. Furthermore, we commented on the reproducibility, efficacy, and scalability of the methods, where the beads still offer superior performances. By comparing different 3D scaffolds, our results move toward understanding the best strategies to develop functional 3D neuronal units for reliable pre-clinical studies.
Somatic mutations in tumor-infiltrating lymphocytes impact on antitumor immunity
Authors: Mukohara Fumiaki , Iwata Kazuma , Ishino Takamasa , Inozume Takashi , Nagasaki Joji , Ueda Youki , Suzawa Ken , Ueno Toshihide , Ikeda Hideki , Kawase Katsushige , Saeki Yuka , Kawashima Shusuke , Yamashita Kazuo , Kawahara Yu , Nakamura Yasuhiro , Honobe-Tabuchi Akiko , Watanabe Hiroko , Dansako Hiromichi , Kawamura Tatsuyoshi , Suzuki Yutaka , Honda Hiroaki , Mano Hiroyuki , Toyooka Shinichi , Kawazu Masahito , Togashi Yosuke
Published: August 2024

Immune checkpoint inhibitors (ICIs) exert clinical efficacy against various types of cancers by reinvigorating exhausted CD8
+
T cells that can expand and directly attack cancer cells (cancer-specific T cells) among tumor-infiltrating lymphocytes (TILs). Although some reports have identified somatic mutations in TILs, their effect on antitumor immunity remains unclear. In this study, we successfully established 18 cancer-specific T cell clones, which have an exhaustion phenotype, from the TILs of four patients with melanoma. We conducted whole-genome sequencing for these T cell clones and identified various somatic mutations in them with high clonality. Among the somatic mutations, an
SH2D2A
loss-of-function frameshift mutation and
TNFAIP3
deletion could activate T cell effector functions in vitro. Furthermore, we generated CD8
+
T cell–specific
Tnfaip3
knockout mice and showed that
Tnfaip3
function loss in CD8
+
T cell increased antitumor immunity, leading to remarkable response to PD-1 blockade in vivo. In addition, we analyzed bulk CD3
+
T cells from TILs in additional 12 patients and identified an
SH2D2A
mutation in one patient through amplicon sequencing. These findings suggest that somatic mutations in TILs can affect antitumor immunity and suggest unique biomarkers and therapeutic targets.
Binding adaptability of chemical ligands to polymorphic α-synuclein amyloid fibrils
Authors: Liu Kaien , Tao Youqi , Zhao Qinyue , Xia Wencheng , Li Xiang , Zhang Shenqing , Yao Yuxuan , Xiang Huaijiang , Han Chao , Tan Li , Sun Bo , Li Dan , Li Ang , Liu Cong
Published: August 2024

α-synuclein (α-syn) assembles into structurally distinct fibril polymorphs seen in different synucleinopathies, such as Parkinson’s disease and multiple system atrophy. Targeting these unique fibril structures using chemical ligands holds diagnostic significance for different disease subtypes. However, the molecular mechanisms governing small molecules interacting with different fibril polymorphs remain unclear. Here, we investigated the interactions of small molecules belonging to four distinct scaffolds, with different α-syn fibril polymorphs. Using cryo-electron microscopy, we determined the structures of these molecules when bound to the fibrils formed by E46K mutant α-syn and compared them to those bound with wild-type α-syn fibrils. Notably, we observed that these ligands exhibit remarkable binding adaptability, as they engage distinct binding sites across different fibril polymorphs. While the molecular scaffold primarily steered the binding locations and geometries on specific sites, the conjugated functional groups further refined this adaptable binding by fine-tuning the geometries and binding sites. Overall, our finding elucidates the adaptability of small molecules binding to different fibril structures, which sheds light on the diagnostic tracer and drug developments tailored to specific pathological fibril polymorphs.
Lipid-associated macrophages’ promotion of fibrosis resolution during MASH regression requires TREM2
Authors: Ganguly Souradipta , Rosenthal Sara Brin , Ishizuka Kei , Troutman Ty D. , Rohm Theresa V. , Khader Naser , Aleman-Muench German , Sano Yasuyo , Archilei Sebastiano , Soroosh Pejman , Olefsky Jerrold M. , Feldstein Ariel E. , Kisseleva Tatiana , Loomba Rohit , Glass Christopher K. , Brenner David A. , Dhar Debanjan
Published: August 2024

While macrophage heterogeneity during metabolic dysfunction-associated steatohepatitis (MASH) has been described, the fate of these macrophages during MASH regression is poorly understood. Comparing macrophage heterogeneity during MASH progression vs regression, we identified specific macrophage subpopulations that are critical for MASH/fibrosis resolution. We elucidated the restorative pathways and gene signatures that define regression-associated macrophages and establish the importance of TREM2+macrophages during MASH regression. Liver-resident Kupffer cells are lost during MASH and are replaced by four distinct monocyte-derived macrophage subpopulations.Trem2is expressed in two macrophage subpopulations: i) monocyte-derived macrophages occupying the Kupffer cell niche (MoKC) and ii) lipid-associated macrophages (LAM). In regression livers, no new transcriptionally distinct macrophage subpopulation emerged. However, the relative macrophage composition changed during regression compared to MASH. While MoKC was the major macrophage subpopulation during MASH, they decreased during regression. LAM was the dominant macrophage subtype during MASH regression and maintainedTrem2expression. Both MoKC and LAM were enriched in disease-resolving pathways. Absence of TREM2 restricted the emergence of LAMs and formation of hepatic crown-like structures. TREM2+macrophages are functionally important not only for restricting MASH-fibrosis progression but also for effective regression of inflammation and fibrosis. TREM2+macrophages are superior collagen degraders. Lack of TREM2+macrophages also prevented elimination of hepatic steatosis and inactivation of HSC during regression, indicating their significance in metabolic coordination with other cell types in the liver. TREM2 imparts this protective effect through multifactorial mechanisms, including improved phagocytosis, lipid handling, and collagen degradation.
Efficiency boosting of 236 nm AlGaN-based micro-LEDs
Authors: Li Hongbo , Lu Shunpeng , Zhu Licai , Sun Wenchao , Bai Jiangxiao , Hao Jialong , Zhang Shanli , Jiang Ke , Shi Zhiming , Jia Yuping , Chen Yang , Ben Jianwei , Liu Mingrui , Zang Hang , Wu Tong , Li Dabing , Sun Xiaojuan
Published: August 2024

In this study, 236 nm AlGaN-based deep ultraviolet (DUV) micro-LEDs with different sized P-contact areas are designed and fabricated, and the sidewalls are restored by a wet chemical treatment method with KOH solution. The results reveal that proper KOH treatment can effectively remove plasma damaged materials and clearly show the formation of m-plane facets. Compared with untreated micro-LEDs, the reverse leakage current of the treated micro-LEDs under −10 V decreases by up to 91.7% and the specific contact resistivity (SCR) reduces from 6.94 Ω cm2 to 0.07 Ω cm2. The underlying mechanism is that the KOH treatment removes the sidewall defects which lead to surface nonradiative recombination sites and surface leakage. Moreover, KOH treatment also removes contamination on the P+-GaN surface and leads to lower SCR. However, a much longer treatment also destructs the 20 nm P+-GaN layer, which results in higher voltage but less DUV light absorption. As a result, the peak light output power density increases from 2.12 W cm−2 to 4.01 W cm−2, representing an 89.2% increase. Efficient enhancement of micro-LEDs is anticipated to facilitate the development of DUV micro-LEDs for maskless lithography and high-capacity DUV non-line-of-sight communication.
Analyzing the physical properties of Half-Heusler RNiSb (R = Sc, Y) for optoelectronic and thermoelectric applications based on first-principles theories
Authors: Tarekuzzaman Md , Babu Md Sayedul Islam , Rayhan M A , Ahmad Sohail , Rasheduzzaman Md , Choudhury M S H , Moazzam Hossen M , Nasrin Shamima , Hasan Md Zahid
Published: August 2024

In this study, we investigated the RNiSb (R = Sc, Y) half-Heusler material for various properties including structural, electronic, mechanical, elastic anisotropic, optical, and thermal properties using Density Functional Theory (DFT) with the Cambridge Serial Total Energy Package (CASTEP) code. Our analysis of the lattice parameters closely aligns with previous theoretical and experimental findings. The positive phonon dispersion curve confirms the dynamical stability of RNiSb (R = Sc, Y). The elastic constants meet the Born criteria, indicating the mechanical stability and brittleness of the RNiSb (R = Sc, Y) solids. While ScNiSb displays elastic isotropy, YNiSb exhibits elastic anisotropy. Electronic band structure and Density of states (DOS) calculations reveal that ScNiSb and YNiSb have indirect band gaps of 0.44 eV and 0.589 eV, respectively. We also determined key optical properties such as absorption coefficient, dielectric function, conductivity, reflectivity, refractive index, and loss function. The optical properties calculations revealed strong photoconductivity, and high reflectivity, all of which show given the materials use in the microelectronics, and optoelectronics application. Furthermore, the Debye temperature and minimum thermal conductivity of ScNiSb decrease with the replacement of Sc by Y, highlighting its potential as a material for thermal barrier coating (TBC). Finally, we computed the Helmholtz free energy (F), internal energy (E), entropy (S), and specific heat capacity (C

v
) based on the phonon density of states.
A high order multi step method for solving system of fractional differential equations
Authors: Azin Hadis , Iloon Kashkooly Ali
Published: August 2024

The primary objective of this research paper is to present an advanced method utilizing quadratic interpolation to address the challenges encountered in solving a system of fractional initial value problems. By employing this high-order technique, we aim to improve the accuracy and efficiency of numerical computations associated with fractional differential equations. In our proposed methodology, we strive to enhance the conventional block-by-block approach by mitigating the interdependence of unknown solutions at each block iteration, except for the initial two steps. This modification aims to maintain the favorable stability characteristic inherent in block-by-block schemes, while effectively reducing coupling effects. We meticulously examine the convergence properties of the proposed method and conduct a rigorous analysis of the associated errors that prove that the numerical solution convergence to the true solution with an order of 3 + β when the parameter 0 < β ≤ 1. To substantiate the theoretical claims put forth in our research, we present a series of numerical examples. These examples serve as empirical evidence to demonstrate the effectiveness and practical applicability of the proposed method. The presented method superiority over alternative approaches is highlighted through a comprehensive comparison of the numerical results.