bluuebunny/crossref_metadata_2025_split huggingface dataset:
BoT-YOLOv8: A high accuracy and stability initial weld position segmentation method for medium-thickness plate
Authors: Liu Zongmin , Li Jie , Zhang Shunlong , Qin Lei , Shi Changcheng , Liu Ning 
Published: January 2024

Abstract

To address the technical bottleneck of autonomous vision guidance for the initial weld position of medium-thickness plate in robot welding. This paper proposes a high accuracy and stability initial weld position segmentation method for medium-thickness plate, this method is developed by integrating the Bottleneck Transformer (BoT) into YOLOv8, termed as BoT-YOLOv8. Firstly, aim to filter out redundant information in the image and enhance the model's capability to express features, the BoT is added behind the last bottleneck layer in the residual module of the YOLOv8 neck structure. Subsequently, in order to obtain the multi-scale information of the target, the atrous convolution is incorporated as the spatial pyramid pooling structure to establish connections between the backbone and the neck of this model. Furthermore, to facilitate the learning of weld position characteristics for the welding robot, the Hue-Saturation-Value (HSV) space region segmentation method is utilized to postprocess the weld seam features. Finally, ablation experiments are conducted on the self-created weld dataset. The results demonstrate that the proposed method achieves a trade-off between detection accuracy (93.1% \({mAP}^{0.5}\)) and detection speed (26.5 \(FPS\)) on a 12GB NVIDIA GeForce RTX 3060 GPU. In addition, compared with the existing methods, the presented method exhibits stronger anti-interference capability.
Do granular shocks generate sizeable aggregate volatility?
Authors: Mandel Antoine , Veetil Vipin 
Published: January 2024

Abstract

Over the last decade, numerous economists have argued that firm-level idiosyncratic productivity shocks can generate much of the observed aggregate volatility if the firms are placed on a production network. We test this hypothesis using granular data on buyer-seller relations between more than half a million firms in the US economy. We find that firm-level shocks within a network setting generate less than a tenth of the observed aggregate volatility. While the network mechanism is capable of amplifying firm-level shocks, the numerical values of the structural properties of the network that generate this amplification are such that the amplification proves to be far from sufficient.
JEL Codes E30, C67, D57.
Modeling with Artificial Neural Networks to estimate daily precipitation in the Legal Amazon
Authors: Gomes Evanice Pinheiro , progenio Mayke feitosa , Holanda Patrícia da Silva 
Published: January 2024

Abstract

Hydrological analyzes carried out from precipitation in the Legal Amazon (AMZ-L) are essential due to their importance in climate regulation, regional and global atmospheric circulation. However, in this region, there are limitations related to data series with short periods and many gaps, especially in the daily scale. Thus, to improve precipitation analyses, a non-parametric stochastic model based on Artificial Neural Networks (ANNs) was used to estimate daily precipitation in AMZ-L. For this, 22 rainfall stations were adopted over a period of 18 years (1998-2016) and with <1% missing data, which were organized considering the complete series and the seasonal periods (rainy and dry). The results obtained demonstrate the good capacity of the model to preserve the precipitation characteristics of the evaluated rainfall stations, mainly those with a more humid climate and with more frequent precipitations during the year, as is the case of those located in the Amazon Biome. However, in regions that suffer prolonged periods of drought, such as the Amazon-Cerrado Ecotone areas, the results were less satisfactory due to the greater recurrence of zeros in the historical series. The seasonal division into dry and rainy periods did not provide better estimates to the model, except for some rainfall gauge stations located at latitudes close to the equator. However, this study may support future research on the estimation of daily precipitation in the region.
Temperature Dependence of the Dielectric Function and Critical Points of Monolayer WSe2
Authors: Nguyen Xuan Au , Le Van Long , Kim Tae Jung , Kim Young Dong 
Published: January 2024

Abstract

Monolayer materials typically display intriguing temperature-dependent dielectric and optical properties, which are crucial for improving the structure and functionality of associated devices. Due to its unique photoelectric capabilities, monolayer WSe2 has recently received a lot of attention in the fields of atomically thin electronics and optoelectronics. In this work, we focus on the evolution of the temperature-dependent dielectric and optical properties of 2D WSe2 over energies from 0.74 to 6.40 eV and temperatures from 40 K to 350 K. We analyze second derivatives with respect to energy to locate the critical points (CP). The dependence of the observed CP energies on temperature is consistent with the alternative domination of the declining exciton binding energy as the temperature increases.
A Comprehensive Analysis of H5N1 Evolution: Phylogenetic Insights and Emerging Mutations in Turkey's Avian Influenza Landscape
Authors: KADI Hamza , COBAN Ahmet Yilmaz , CAGIRGAN Ozge , NOTUROGLU Mehmet , ALBAYRAK Harun 
Published: January 2024

Abstract
Avian influenza (AI) H5N1 viruses, known for their high mortality in humans and poultry, pose a significant public health threat. This study examines seventeen H5N1 isolates from the 2006 outbreak in Turkey and one 2023 isolate for mutations in the hemagglutinin gene's receptor binding domain, which determines host specificity, and the evolutionary changes in the isolates. The hemagglutinin gene region of these isolates was partially amplified using RT-PCR, and critical mutations in the receptor binding domains were examined, alongside the phylogenetic relationships of the isolates in a time- and geography-dependent manner. Our findings showed that key mutations known for altering host selectivity (N224K, G225D, Q226L, S227N, G228S) were absent. However, additional mutations (D110N and S171N), potentially affecting receptor selectivity, were identified. Comprehensive phylogenetic analysis, conducted separately based on geographic regions and temporal distribution, encompassed H5N1 strains isolated from various locations and hosts from 2007 to 2023. This study highlights significant genetic divergence between the 2006 Turkish isolates and the 2023 isolate, highlighting notable evolutionary changes. Distinct clustering of the isolates was observed in both geographic and temporal phylogenetic frameworks, indicating substantial evolutionary shifts within the circulating H5N1 strains in Turkey. Given the global spread potential of H5N1 viruses via migratory birds and the risk of a new pandemic if human-to-human transmission is attained, monitoring H5N1's molecular traits and evolution is crucial for mitigating public health impacts.
Spillover effect of inflation in Indonesia
Authors: Widiarsih Dwi , Taifur Werry Darta , Ridwan Endrizal , Devianto Doddy 
Published: January 2024

Abstract
The economic benefits of inflation analysis are generated after a shock or after the regions interact. This research is spatial panel modeling. The weighting matrix used is Double Power Distance Weights wich gives the best result using Spatial Autoregressive (SAR) model with Fixed Effect Model (FEM). Spatially, inflation in a region has an impact on 2 nearby regions with high correlation. Impact measure is the significant impact of infrastructure, Bank Indonesia Performance (BI performance), Locally-Generated Revenue (PAD), government spending, and energy consumption on inflation, both directly and indirectly. Analysis of the p-value is smaller than the alpha of 5% and 10%, so the direct effect on PAD, government spending, infrastructure, BI performance, and energy consumption is significant on inflation in Indonesia. The findings are interesting because the value of indirect impact is greater than the direct impact, so it can be interpreted that the interaction factor between regions is very strong. Accessibility of infrastructure between regions causes interaction and mobilization to occur. The findings of this research provide recommendations that the government needs to improve physical connectivity (roads, toll roads, bridges, airports, ports, etc.), both for the western and eastern regions of Indonesia. Elements of government fiscal policy with a countercyclical character in managing government finances as well as efficiency in energy management & consumption in creating lower energy intensity values can be recommended because they are determining factors for controlling Indonesia's inflation.
Individual and regional determinants of women’s participation in the European labour market: A Labour Force Survey empirical study
Authors: Lovaglio Pietro Giorgio , Perrelli Adalgisa 
Published: January 2024

Abstract

In line with the existing literature, the primary focus of the present paper is on understanding the multifaceted factors contributing to unequal employment opportunities for women and the potential implications for both individuals and society. Specifically, the objective is to identify meaningful risk factors that affect the probability of being employed for women in the 20–49 age group, exploring possible demographic, educational, social, and family factors, as well as territorial context factors. The analysis is conducted on the three most populous European countries (Italy, France, and Germany) as representatives of different welfare regimes. The analysis exploits the rich information available in the micro-data of the Labour Force Survey (2021) as well as Eurostat regional statistics considering individuals nested in regions (NUTS 2). A deep analysis of empirical findings sheds light on employment determinants and motivations for not working, which appear to be essentially related to family and demographic factors. These results reveal the country-specific profiles that indicate greater risk of non-employment and also provide a basis for suggesting different policy implications.
Classification JEL: F66 J21 J71
Comparison of bacterial species and clinical outcomes in patients with diabetic hand infection in tropical and nontropical regions
Authors: Chen Yan , Liu Bin , Huan Chen , Xie Puguang , Du Chenzhen , Rui Shunli , Hao Mei , Duan Zixiao , Armstrong David G. , Deng Wuquan , Xiao Xiaoqiu 
Published: January 2024

Abstract

Purpose: Hand infection is a rare complication in patients with diabetes. Its clinical outcomes depend on the severity of hand infection caused by bacteria, but the difference in bacterial species in the regional disparity is unknown. The purpose of this study was to explore the influence of tropical and nontropical regions on bacterial species and clinical outcomes for diabetic hand.
Patients and Methods: A systematic literature review was conducted using PubMed,
EMBASE, Web of Science, and Google Scholar. Moreover, the bacterial species and clinical outcomes were analyzed with respect to multicenter wound care in China (nontropical regions).
Results: Both mixed bacteria (31.2% vs. 16.6%, p=0.014) and fungi (7.5% vs. 0.8%, p=0.017) in the nontropical region were significantly more prevalent than those in the tropical region. Staphylococcus and Streptococcus spp. were dominant in gram-positive bacteria, and Klebsiella, Escherichia coli, Proteus and Pseudomonas in gram-negative bacteria occupied the next majority in the two regions. The rate of surgical treatment in the patients was 31.2% in the nontropical region, which was significantly higher than the 11.4% in the tropical region (p=0.001). Although the overall mortality was not significantly different, there was a tendency to be increased in tropical regions (6.3%) compared with nontropical regions (0.9%). However, amputation (32.9% vs. 31.3%, p=0.762) and disability (6.3% vs. 12.2%, p=0.138) were not significantly differentbetween the two regions.
Conclusion: Similar numbers of cases were reported, and the most common bacteria were similar in tropical and nontropical regions in patients with diabetic hand. There were more species of bacteria in the nontropical region, and their distribution was basically similar, except for fungi, which had differences between the two regions. The present study also showed that surgical treatment and mortality were inversely correlated because delays in debridement and surgery can deteriorate deep infections, eventually leading to amputation and even death.
Pretransplant Desensitization of Donor-Specific Anti-HLA Antibodies with Plasmapheresis and Immunoglobulin Produces Equivalent Outcomes to Patients with No Donor Specific Antibodies in Haploidentical Hematopoietic Cell Transplant
Authors: Cochran Hunter , Slade Michael , Gao Feng , Godbole Sonia , Pruitt Aaron , De Togni Elisa , Liu Chang , Grossman Brenda , Abboud Ramzi 
Published: January 2024

Abstract
In patients requiring haploidentical hematopoietic cell transplant (haplo-HCT), the presence of donor specific anti-HLA antibodies (DSAs) is associated with high rates of primary graft failure and poor overall survival (OS). There is limited data regarding the effect of desensitization.
Adult patients undergoing haplo-HCT at Washington University School of Medicine from 2009- 2021 were identified. Patients were divided into three cohorts: no DSA, untreated DSA or treated DSA. DSA testing was performed. Desensitization therapy using plasmapheresis and IVIg (immunoglobulin) was performed.
We retrospectively identified 304 patients for study inclusion. 14 of 30 patients with DSAs underwent desensitization. By day +2, 57% of patients cleared all DSAs. OS was expectedly worse in patients with untreated DSAs. There were similar results between treated DSA and patients without DSA (OS median: control: 352 days vs. treated: 1331 days vs. untreated: 137 days, p = 0.02). RFS was also significantly different between the groups however with similar RFS in treated DSA and control groups (RFS median: control: 248 vs. treated: 322 v. untreated: 119, p = 0.03).
Desensitization before haplo-HCT produces similar outcomes to patients without DSAs. While the optimal desensitization protocol has not been established, all patients received a backbone of plasmapheresis and immunoglobulin.
Pan-cancer multi-omics analysis reveals the prognostic value of RGS gene family
Authors: Wu Yawen , Lin Fanfeng , Zhang Jie , Li Guanghao , Xie Li 
Published: January 2024

Abstract

Background: The regulator of G-protein signaling (RGS) family, regulating cellular signaling events downstream of G-protein coupled receptors (GPCRs), is of great significance for diagnostic and prognostic prediction in cancer. At present, the comprehensive studies of RGS family genes in pan-cancer and specifically in Kidney renal clear cell carcinoma (KIRC) are rare.Methods: The performance of RGS genes in pan-cancer was assessed using the multi-omics dataset including genomic, transcriptomic, epigenetic and clinical data obtained from The Cancer Genome Atlas (TCGA). Subsequently, we conducted an in-depth exploration of RGS family genes in KIRC. Univariate cox regression and lasso regression were used to construct the risk model based on the five RGS genes. Independent prognostic factors for OS of KIRC patients were validated via univariate and multivariate COX analyses, and a nomogram was then developed. Finally, tumor mutation burden, immune infiltration, drug sensitivity and functional enrichment were analyzed and compared between the low- and high-risk groups.Result:We comprehensively found out that the abnormal expression, somatic mutations and methylation of RGS genes were associated with tumorigenesis and survival rates in pan-cancer. Interestingly, much more highly expressed RGS genes induced significantly higher risk and poorer survival in KIRC than those in other tumors. A prediction model for the prognosis based on five RGS genes (RGS2, RGS17, RGS10, RGS20 and RGS7BP) was established using univariable cox regression and lasso regression. The functional enrichment, tumor microenvironment, and immune infiltration were statistically different between the low-risk and high-risk groups. Clinically, our risk score model was effective in predicting the sensitivity of KIRC patients to chemotherapy and immune checkpoint blockade therapy.Conclusions:A five-gene risk-score signature was constructed and validated, which is of great clinical value and contributes to better clinical decision making and personalized treatment strategies associated with the benefits of KIRC patients.
Optimal Rank-based Procedures for Testing Randomness against Panel Bilinear Dependence
Authors: Lmakri Aziz , Akharif Abdelhadi , Mellouk Amal 
Published: January 2024

Abstract

Based on the local asymptotic normality (LAN) property, we are proposing parametric and nonparametric locally and asymptotically optimal (in the Le Cam-Hájek sense) procedures for the problem of testing white noise against the general panel super-diagonal bilinear dependence. The proposed rank-based tests are asymptotically most stringent and valid under a wide class of densities. The asymptotic relative efficiencies (AREs), with respect to the corresponding pseudo-Gaussian procedure, are computed under various densities. Simulation studies are conducted to illustrate the finite-sample performance of the proposed tests.
Women at Risk: A Comparative Study on Socioeconomic Status, Lifestyle, Brain, and Cognition Among Older Females in Japan and Sweden
Authors: Liu Yingxu , Tatewaki Yasuko , Boraxbekk Carl-johan , Thyreau Benjamin , Cui Yuehua , Zhang Ye , Hidaka Yosuke , Kajitani Naoto , Yuki Seiji , Takebayashi Minoru , Ninomiya Toshiharu , Taki Yasuyuki , Karalija Nina 
Published: January 2024

Abstract

Objective
Determine and compare lifestyle risks addressing the effects of socioeconomic status (SES) on brain and cognitive variations among females in two community-dwelling cohorts across Japan and Sweden.
Method
We included 576 (73.7 ± 6.0 years) and 195 (63.9 ± 13.4 years) cognitively healthy females from the Arao (AC, Japan) and Betula (BC, Sweden) cohorts, respectively. SES was defined by educational and occupational categories. Lifestyle-related diseases included obesity, diabetes, hypertension, and depressive disorder; habits including exercise, social activity, sleep, alcohol habits, and smoking status. Brain structural outcomes were derived from T1 weighted magnetic resonance imaging scans. A priori regions of interest included volumes of the hippocampus, amygdala, thalamus, and caudate; thickness of the superior frontal gyrus, inferior temporal gyrus, and middle temporal gyrus. General cognitive performance was evaluated by the Mini-Mental State Examination score. The relationships between SES-lifestyle with the brain and cognition were assessed by structural equation models.
Results
Positive associations were found between SES and volumetric brain measures and cognition (MMSE) in both cohorts, but not between SES and cortical thickness. Lifestyle-related diseases (including obesity, diabetes, hypertension, and depressive disorder), but not habits such as exercise or sleep, partially explained the positive association between SES and brain volumes (up to 18.6% in the AC). A similar, but non-significant trend, was seen in the SES-cognition association that could be explained by lifestyle-related diseases.
Discussion
Although statements of causality cannot be made from the current work, our findings suggest management of the lifestyle-related disease is particularly important for females for compensating the maladaptive effects of SES on brain atrophy.
RIS-Aided MmWave Hybrid Relay Network Based on Multi-Agent Deep Reinforcement Learning
Authors: Zhao Yifeng , Liu Xuanhui , Liu Haoran , Wang Xiaoqi , Huang Lianfen 
Published: January 2024

Abstract

In millimeter wave (mmWave) communication, the utilization of multi-hop relay technology has been regarded as a promising approach to overcome the significant path loss encountered during signal transmission. However, the traditional active relay network suffers from low energy efficiency (EE) and uneven resource distribution. To address these challenges, we introduce Reconfigurable Intelligent Surface (RIS) as a passive relay to the mmWave communication system and create a hybrid relay system that combines passive and active relays, which aims to improve EE through the multi-hop relay. Additionally, with the development of Artificial Intelligence, deep Q-learning (DQN) is applied to optimize the hybrid relay system in this paper, where every transmitted signal of the base station (BS) is considered an agent. In this approach, the network is trained based on the interaction between the collected environment information and the users' relay allocation strategy. Considering competition-cooperation relationships of multiple users, we propose a multi-agent DQN (MADQN) algorithm to allocate the relay resource where the primary goal is maximizing EE. Simulation results demonstrate that our proposed scheme can effectively converge to the optimal relay link, further improving EE and reducing energy consumption in comparison with conventional schemes.
Rapid classification of epidemiologically relevant age categories of the malaria vector, Anopheles funestus
Authors: Mwanga Emmanuel P. , Siria Doreen J. , Mshani Issa H. , Mwinyi Sophia H. , Abbas Said , Jimenez Mario Gonzalez , Wynne Klaas , Baldini Francesco , Babayan Simon A. , Okumu Fredros O. 
Published: January 2024

Abstract
Background
Accurately determining the age and survival probabilities of adult mosquitoes is crucial for understanding parasite transmission, evaluating the effectiveness of control interventions and assessing disease risk in communities. This study was aimed to demonstrating rapid identification of epidemiologically relevant age categories of Anopheles funestus, a major Afro-tropical malaria vector, through the innovative combination of infrared spectroscopy and machine learning, instead of the cumbersome practice of dissecting mosquito ovaries to estimate age based on parity status.
Methods
An. funestus larvae were collected in rural south-Eastern Tanzania and reared in the insectary. Emerging adult females were sorted by age (1–16 day-olds) and preserved using silica gel. PCR confirmation was conducted using DNA extracted from mosquito legs to verify the presence of An. funestus and eliminate undesired mosquitoes. Mid-infrared spectra were obtained by scanning the heads and thoraces of the mosquitoes using an ATR FT-IR spectrometer. The spectra (N = 2084) were divided into two epidemiologically relevant age groups: 1–9 days (young, non-infectious) and 10–16 days (old, potentially infectious). The dimensionality of the spectra was reduced using principal component analysis, then a set of machine learning and multi-layer perceptron (MLP) models were trained using the spectra to predict the mosquito age categories.
Results
The best performing model, XGBoost, achieved an overall accuracy of 87%, with classification accuracies of 89% for young and 84% for old An. funestus. When the most important spectral features influencing the model performance were selected to train a new model, the overall accuracy increased slightly to 89%. The MLP model, utilising the significant spectral features, achieved higher classification accuracies of 95% and 94% for the young and old An. funestus, respectively. After dimensionality reduction, the MLP achieved 93% accuracy for both age categories.
Conclusion
This study shows how machine learning can quickly classify epidemiologically relevant age groups of An. funestus based on their mid-infrared spectra. Having been previously applied to An. gambiae, An. arabiensis and An. coluzzii, this demonstration on An. funestus underscore the potential of this low-cost, reagent-free technique for widespread use on all the major Afro-tropical malaria vectors. Future research should demonstrate how such machine-derived age classifications in field collected mosquitoes correlate with malaria in human populations.