bluuebunny/crossref_metadata_2025_split huggingface dataset:
GCI-GGIW-PMBM：An Intelligent Multiple Extended Target Tracking Scheme for Mobile Aquaculture Sensor Networks
Authors: Zhu Jianping , Lv Chunfeng , Peng Zhiguang 
Published: May 2023

Abstract
Poisson multi-Bernoulli Mixture (PMBM) filter, accompanying with its improvements, has been known as an available or practical point and extended multi-target tracking algorithm. This paper presents an improved PMBM scheme carried adaptive detection probability and random birth distributions, coupling with an associated distribution fused scheme for tracking extended multiple targets. Firstly, the augmented state of unknown and changing target detection probability is described by Gamma (GAM) distribution. Then, extended target states are described by Inverse Wishart (IW) distribution on account of the augmented state, besides dynamic states of multiple targets presented by Gaussian distribution. And then, an adaptive newborn distribution is adopted to describe the newborn targets appeared arbitrarily. Consequently, the detailed recursion and closed-form solutions of the proposed filter can be obtained through approximating the intensity of newborn and potential targets to Gamma Gaussian Inverse Wishart (GGIW) pattern. Furthermore, a novel distribution fused scheme Generalized Covariance Intersection (GCI), whose associated states and cardinality are fused by anchors abiding by the respective fused weights, is performed in such an extensive aquaculture tracking sensor system with limited computational and processing capacity. Availability and effectiveness of GCI-GGIW-PMBM filter can be verified by comprehensive simulations. Comparisons with other multiple extended target tracking filters also illustrate that tracking behaviors are improved to a great extent, especially energy efficiency is enhanced largely, and tracking accuracy is relatively improved.
A mixed meal tolerance test predicts onset of type 2 diabetes in Southwestern Indigenous adults.
Authors: Stinson Emma , Chang Douglas , Krakoff Jonathan , Mitchell Cassie 
Published: May 2023

Abstract

Background/Objective: To identify predictors of incident type 2 diabetes using a mixed meal tolerance test (MMTT).

Methods: Adult Indigenous Americans without diabetes (n=501) from a longitudinal cohort underwent at baseline a 4-hour MMTT, measures of body composition, an oral glucose tolerance test, an intravenous glucose tolerance test for acute insulin response (AIR), and a hyperinsulinemic-euglycemic clamp for insulin action (M). Plasma glucose responses from the MMTT were quantified by total and incremental area under the curve (AUC/iAUC).

Results: At follow-up (median time 9.6 [inter-quartile range: 5.6-13.5] years), 169 participants were diagnosed with diabetes. Unadjusted Cox proportional hazards models, glucose AUC180-min (HR: 1.98, 95% CI: 1.67, 2.34, p<0.0001), AUC240-min (HR: 1.93, 95% CI: 1.62, 2.31, p<0.0001), and iAUC180-min (HR: 1.43, 95% CI: 1.20, 1.71, p<0.0001) were associated with an increased risk of diabetes. After adjustment for covariates (age, sex, body fat percentage, M, AIR, Indigenous American heritage) in three subsequent models, AUC180-min (HR: 1.44, 95% CI: 1.10, 1.88, p=0.007) and AUC240-min (HR: 1.41, 95% CI: 1.09, 1.84, p<0.01) remained associated with increased risk of diabetes.

Conclusions: Glucose responses to a mixed meal predicted development of type 2 diabetes. This indicates that a mixed nutritional challenge provides important information on disease risk.
Outcrop analogue constraints on subsurface reservoir properties of the Puga geothermal field, NW Himalaya
Authors: Zimik Horthing V. , Thiele Samuel T. , Khanna Pankaj Khanna 
Published: May 2023

Abstract
There has been a large barrier in geothermal energy production in India due to the knowledge gap in understanding the subsurface uncertainties. In Puga, Ladakh, a significant amount of research has been done that estimates the availability of >5000 MWh of geothermal energy, but it remains untapped. It is largely due to a limited understanding of reservoir characteristics. In addition to the comprehensive review of literature, this study includes outcrop analogue studies to develop a better understanding of the subsurface geothermal system. Observing the geological settings, the lithologies and structures exposed in the cliffs adjacent to Puga valley are analogous to the subsurface, to depths of at least a few kilometres. A 3-D model of the outcrop is developed from aerial imagery collected using drone (quadcopter), that has been utilized to interpret fracture sets and foliation planes. Areas with intensely developed fabrics demonstrate the mechanical significance of these fabrics. The distinctive relationship between faults in the outcrop and the valley fill provides evidence for recent movement on the faults. Further, a variety of mineral fillings were observed in fractures across the outcrop which includes quartz±tourmaline veins, hydrothermal biotite, vuggy sub- and euhedral quartz, finegrained iron oxides and iron-rich travertine. Several exposures near the base of the cliffs show clear advanced argillic and sulfuric alteration. This study integrates digital outcrop mapping techniques along with constraints provided by the literature to derive a conceptual model of the Puga geothermal system. It provides an understanding of the structural architecture of the reservoir, which is an important parameter in developing the ‘Integrated reservoir model’.
Spatial temporal analysis of vehicle routing problem from online car-hailing trajectories
Authors: Yang Xue , Yu Jianhua , Kan Zihan , Zhou Lin , Guan Qingfen , Tang Luliang 
Published: May 2023

Abstract
A range of vehicle routing problems, from routing planning that vehicles will apply to the actual route that drivers selected in their environment, depend on many factors including travel length, traffic condition, or personalized experience, etc., raising a fundamental question: To what degree is planned route align with the actual route. Here we explore the spatial temporal differences between the planned route and actual route by studying the popular roads which are avoided by drivers (denoted as: PRAD) from car hailing trajectories. By matching the raw trajectories based on an improved HMM map-matching algorithm, we obtain the OD (origin-destination) matrix and their corresponding actual route that vehicles traveled, and planned route generated by A* routing algorithm. We used the Jaccard index to quantify the similarity between the actual route and the planned route of the same OD pair. The PRAD is detected and further analyzed from the aspects of traffic condition. By using car-hailing trajectories provided by DiDi company, we analyzed drivers' routing behavior in workday and weekend in Wuhan. The relation of PRAD with traffic condition in workday and weekend is discussed and results shown that about 65% PRAD are occurred with a serious traffic jam especially in workday.
A Lightweight Traffic Sign Recognition Model Based on Improved YOLOv5
Authors: Yang Jie , Sun Ting , Zhu Wenchao , Li Zonghao 
Published: May 2023

Abstract
Traffic sign detection and recognition is a key technology for achieving automatic vehicle driving and maintaining road safety. The paper proposes a lightweight recognition algorithm based on YOLOv5 to address the problems of large model size, complex computation, low detection accuracy and high computational cost of existing traffic sign recognition algorithms. The algorithm is based on YOLOv5, replacing the convolutional structure in the original YOLOv5 neck network with Ghost Module and C3Ghost Module, thus reducing the redundant features in the feature fusion process, lowering the computational cost and the number of parameters; improving the PAN structure of the network and introducing the hybrid attention mechanism module CBAM, which ignores the unimportant information and capturing key information in traffic signs; adding cross-layer connections to the feature pyramid network shortens the path of information transfer, fuses more features, and improves the network feature recognition accuracy. In addition, the EIoU_Loss function is used as the bounding box regression loss function to improve the localization accuracy of the algorithm. The performance of the improved algorithm is also verified on the Chinese traffic sign dataset. The experimental results show that the improved algorithm improves the detection accuracy by 1.2% over the existing YOLOv5 algorithm, mAP@0.5 and mAP@0.5:0.95 by 1.5% and 3.4% respectively, and the overall number of parameters and computational cost of the model are reduced by 14.5% and 16%. The proposed algorithm has enhanced recognition capability for targets in multiple environments and can meet the requirements for real-time traffic sign recognition.
Advancing Prosthetic Arm Technology with Enhanced Aesthetics Integrating EMG Based Signals, 3D Printing and Tactile Sensors
Authors: Palthi Rusesh , Arug Lalith Sree Jayanth , Gugulothu Gopichand Naik , Singh Shashank Kumar , Pal Prashant , Bansod Saurabh , Kumar Yogesh 
Published: May 2023

Abstract
Enhancing prosthetic arm technology by integrating electromyography (EMG) signals, 3D printing, and tactile sensors to improve aesthetics, accuracy, and latency. The combination of these technologies has the potential to revolutionize prosthetic arm functionality by providing a more intuitive and responsive experience for users. The EMG-based signals enable high accuracy control over the prosthetic arm, allowing complex movements such as grasping and releasing objects. 3D printing technology allows for customized prosthetic arms that fit the user's unique physical characteristics with low latency, providing better comfort and functionality while allowing for aesthetically pleasing designs. Tactile sensors provide valuable feedback to the user with low latency, improving control and interaction with the surrounding environment. Our research shows that this system is effective in improving prosthetic arm functionality and appearance with high accuracy and low latency. The potential for further development and integration of these technologies to create more aesthetically pleasing prosthetic devices with improved accuracy and low latency is discussed. Integrating EMG-based signals, 3D printing, and tactile sensors with a focus on aesthetics, high accuracy, and low latency holds significant promise for advancing prosthetic arm technology. Future research should focus on enhancing these technologies for real-world applications.
Association of Dengue Case Load and Environmental Factors in Four Potentially Disease Risk Areas of Pakistan
Authors: Mufeeza Hafiza , AKRAM WASEEM , Munir Rizwan , Khan Hafiz Azhar Ali , Tayyib Muhammad , Lee Hee Il 
Published: May 2023

Abstract
Dengue is a crucial public health dilemma. Scarce water supply, population density, inadequate solid waste management, poor socio-economic level and climatic variations are recognized as key factors in Aedes breeding and later on in the transmission of Dengue Fever (DF). Dengue incidence (cases) is strongly associated with climatic tiers such as relative humidity, temperature and rainfall. Our findings on values of the bivariate correlation analysis have revealed positive correlation between rainfall and dengue incidences (r = 0.75**, r = 0.913**, r = 0.948**, r = 0.961** P < 0.01) as rainfall was the main cause of increase in number of cases in all districts. Moreover r = 0.613* P < 0.05, has depicted a moderate positive association between monthly average humidity and number of incidences, and r = 0.648* P < 0.05, suggested that there is a moderately positive relationship between monthly average temperature and number of incidences Moreover, high amount of monsoon rainfall 400.93mm in the year 2019 and post-monsoon seasons strongly contributed in the dengue virus outbreak.
Socioeconomic differences in nutrition in Italy before and during COVID-19 pandemic: a nationwide cross-sectional study
Authors: Dolcini Jacopo , Ponzio Elisa , D’Errico Marcello Mario , Barbadoro Pamela 
Published: May 2023

Abstract
Background: Several socioeconomic conditions may influence subjects’ adherence to healthy eating habits. Food consumption may be influenced by external stress during crisis periods; however, the effects of these events on food habits are difficult to predict. Also, a pandemic crisis like the recent COVID-19 pandemic may have influenced dietary habits and food consumption. The objective of this study was to compare dietary habits in Italian people one year before the COVID-19 pandemic with those belonging to the year 2020 in a nationwide population sample.
Materials and methods: Information on dietary habits has been obtained from the multi-purpose survey on families “Aspects of daily life”, carried out in Italy by the Italian National Statistics Institute (ISTAT). We analyzed data coming from 2016 and 2020 editions of the survey (43000 subjects each year). We used population attributable factor (PAF) adjusted for age, defined as the proportional reduction in unhealthy diet that would occur if all participants had had a higher education, assuming higher educated individuals as more socially advantaged. Prevalence association for each dietary exposition has been calculated through logistic regression.
Results: both men and women show high prevalence of unhealthy dietary habits. Regarding men, excessive consumption of eggs, pork meat, and bovine meat is characterized by a PAF attributable to socioeconomic conditions to an extent greater than 30%. Women show the same trend. During COVID-19 pandemic men and women show unhealthy profiles of food consumption since men increased consumption of eggs, cooked fats, snacks, sweets, and reduced consumption of fruits and vegetables. Both sexes registered an increase in overweight and obese subjects in 2020.
Conclusions: To our knowledge, this study is the first in our country to use a validate yearly questionnaire to analyze dietary habits looking at single kind of different foods at nationwide level and to put in relationship these habits with COVID-19 pandemic. Our results show unbalanced dietary habits of Italian population. Socioeconomic differences influence food choices but in a complex way. Outside stressors like a crisis period as COVID-19 pandemic seem to have an important role in both men and women regarding assumption of so-called “junk food”.
Effects of temporal and spatial continuity of grasslands on butterfly communities
Authors: INOUE Taiki , KENTA Tanaka 
Published: May 2023

Abstract
Semi-natural grasslands have high biodiversity, but they are declining worldwide, and desperately need to be prioritized for conservation. Recently, numerous papers have concluded that vegetation history may influence biodiversity. We targeted three vegetation types in ski-run grasslands in central Japan: "old grasslands" that have been in existence for 300 to several thousand years, "new grasslands" that have been deforested for 43 to 72 years, and forests adjacent to those ski-runs. We established transects at six to seven sites for each vegetation type and surveyed butterfly communities visually. Plant communities were also surveyed along the same transects. Species composition, numbers of species, and total abundance of butterflies did not vary with grassland age; however, the area of old grasslands within 100 m of transects affected species composition. Minois dryas (Nymphalidae) and Eurema mandarina (Pieridae) were identified as indicator species of large, old grasslands (>8000 m2 within 100 m), whereas no indicator species were detected at other sites. Abundances of Minois dryas, Brenthis daphne (Nymphalidae), and Curetis acuta (Lycaenidae) were greater where old grassland areas occurred within 100 m of observed sites. Sanguisorba officinalis (Rosaceae), the host plant of B. daphne, and Lespedeza bicolor, the main host plant of E. mandarina and C. acuta, was identified as an indicator of old grassland, explaining the dependence of these three butterfly species on old grasslands. Previous studies have also shown that M. sinensis, the main host plant of M. dryas, is an indicator for the entire grassland, suggesting that the butterfly's distribution was restricted to a narrower area than that of host plants. Our results suggest that large, old grasslands should have high conservation priority to maintain grassland butterfly diversity.
Effects of temporal grassland continuity on plant diversity and species composition in geographically diverse communities
Authors: INOUE Taiki , YAIDA Yuki A. , UEHARA Yuki , KATSUHARA Kouki R. , KAWAI Jun , SEKI Takeharu , TAKASHIMA Keiko , MIYAMOTO Nodoka , YAMAMOTO Yuka , SHIMONO Ayako , USHIMARU Atushi , KENTA Tanaka 
Published: May 2023

Abstract

Semi-natural grasslands, which support high biodiversity, are declining worldwide, underscoring an urgent need to identify high biodiversity grasslands that should be prioritised for conservation. We previously reported that grasslands with longer temporal continuity in a single region in Japan have higher plant diversity. To confirm the generality of this finding, we targeted three regions (40 to 90 km apart) in central Japan, including the previously-studied area. We first traced vegetation changes since the 1910s to the present in and around ski-run grasslands, and then examined the effects of vegetation history on plant communities. We surveyed plant communities using transects at five to eight sites in each of three vegetation types: "old grasslands", which are estimated to have persisted for 110 to several thousand years, "new grasslands", which were created by deforestation 45 to 89 years ago, and forests adjacent to those ski runs, in each region (total, 58 sites). The number of rare grassland species and native grassland species were highest in old grasslands. Species composition differed markedly between old and new grasslands, with the beta diversity as high as nearly half of that across all three regions. Numbers of indicator species were 21 and 4 for old and new grasslands, respectively, indicating that many plant species depend on old grasslands. Indicator species that were more frequent in old grassland were perennials, had purple flower color, and tended to have well-developed rhizomes. The strong effect of vegetation history across these three regions clearly verified the high conservation priority of grasslands with long temporal continuity.
Validation of a viable delirium detection test performed by nurses and physicians during routine patient care
Authors: Soboh Rashad , Gino-Moor Sharon , Jiris Nizar , Ginsberg Shira , Oliven Ron 
Published: May 2023

Abstract
Background
Delirium is a frequent mental impairment in geriatric patients hospitalized in acute care facilities. It carries a high risk of complications and is often the first symptom of acute illness. It is clearly important to identify the development of delirium at an early stage, and several short and effective diagnostic tests have been developed and validated for this purpose. Despite this, patients on hospital wards are seldom monitored for signs of emergent delirium, suggesting that compliance with guidelines would be improved by introducing a simpler and more user-friendly test.
Methods
We recently implemented a simple delirium assessment tool, called R&M, that can be introduced into the daily routine of ward staff without significantly adding to their workload. The nurses noted their impression of the patient's cognitive state in the electronic medical record, and during the morning round the ward physician administered a short attention test to any patients suspected of cognitive impairment. In this study, we compared R&M test against the widely used and well validated 4AT.
Results
R&M performed daily by the ward staff was found to be non-inferior to 4AT performed by an experienced rater. Compared to 4AT, R&M had a sensitivity of 93.9% and a specificity of 98.3%. An Altman-Bland plot indicated that both tests can be used interchangeably.
Conclusions
The R&M test is reliable, easy to administer, likely to boost compliance with guidelines, and is expected to raise awareness of delirium among the nurses and physicians directly involved in the diagnostic process.
Trial registration
NCT05836714, Apr. 28, 2013 (retrospectively registered).
Utility of pneumonia severity assessment tools for mortality prediction in healthcare-associated pneumonia: a systematic review and meta-analysis
Authors: Noguchi Shingo , Katsurada Masahiro , Yatera Kazuhiro , Xu Dongjie , Nakagawa Natsuki , Fukuda Yosuke , Shindo Yuichiro , Senda Kazuyoshi , Tsukada Hiroki , Miki Makoto , Mukae Hiroshi 
Published: May 2023

Abstract

Accurate prognostic tools for mortality in patients with healthcare-associated pneumonia (HCAP) are needed to provide appropriate medical care. Tools like PSI, A-DROP, I-ROAD, and CURB-65, widely used for predicting mortality in community-acquired and hospital-acquired pneumonia cases, remain controversial. We identified articles evaluating either PSI, A-DROP, I-ROAD, or CURB-65 and the mortality outcome in patients with HCAP and calculated the pooled sensitivities, specificities, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratios, and the overall summary area under the curves (AUCs) for mortality prediction. Additionally, the differences in prognostic power among these four assessment tools were evaluated using the mean differences of AUCs. Using a cut-off value of moderate, sensitivity, specificity, PLR, and NLR were found to be 0.91-0.97, 0.15-0.53, 1.14-1.66, and 0.18-0.33. respectively. Upon using a cut-off value of severe, sensitivity, specificity, PLR, and NLR were 0.63-0.70, 0.53-0.66, 1.49-2.03, and 0.47-0.58, respectively. Overall AUCs were 0.70 (0.68-0.72), 0.71 (0.63-0.78), 0.68 (0.63-0.73), and 0.67 (0.63-0.71), respectively, for PSI, A-DROP, I-ROAD, and CURB-65 (p=0.63). In conclusions, these severity assessment tools do not have enough power to predict mortality in HCAP patients. Furthermore, there are no significant differences in predictive performance among these four severity assessment tools.