bluuebunny/crossref_metadata_2025_split huggingface dataset:
Arsenic‐contaminated groundwater of the Western Banat (Pannonian basin): Hydrogeochemical appraisal, pollution source apportionment, and Monte Carlo simulation of source‐specific health risks
Authors: Vesković Jelena , Bulatović Sandra , Ražić Slavica , Lučić Milica , Miletić Andrijana , Nastasović Aleksandra , Onjia Antonije 
Published: August 2024

AbstractDue to rapid urbanization and industrial growth, groundwater globally is continuously deteriorating, posing significant health risks to humans. This study employed a comprehensive methodology to analyze groundwater in the Western Banat Plain (Serbia). Using Piper and Gibbs plots, hydrogeochemistry was assessed, while the entropy‐weighted water quality index (EWQI) was used to evaluate groundwater quality. Pollution sources were identified using positive matrix factorization (PMF) accompanied by Pearson correlation and hierarchical cluster analysis, while Monte Carlo simulation assessed health risks associated with groundwater consumption. Results showed that groundwater, mainly Ca–Mg–HCO3 type, is mostly suitable for drinking. Geogenic pollution, agricultural activities, and sewage were major pollution sources. Consumption of contaminated groundwater poses serious non‐carcinogenic and carcinogenic health risks. Additionally, arsenic from geogenic source was found to be the main health risks contributor, considering its worryingly elevated concentration, ranging up to 364 μg/L. These findings will be valuable for decision‐makers and researchers in managing groundwater vulnerability.Practitioner Points
Groundwater is severely contaminated with As in the northern part of the study area.
The predominant hydrochemical type of groundwater in the area is Ca–Mg–HCO3.
The PMF method apportioned three groundwater pollution sources.
Monte Carlo identified rock dissolution as the primary health risk contributor.
Health risks and mortality in the study area are positively correlated.
Hydrogeochemical features, genesis, and quality appraisal of confined groundwater in a typical large sedimentary plain
Authors: Zhang Yuqing , Xiao Yong , Yang Hongjie , Wang Liwei , Wang Jie , Hu Wenxu , Wang Ning , Xu Zhongyuan , Liu Gongxi , Chen Feiyu , Guo Xu 
Published: August 2024

AbstractThe confined groundwater of arid sedimentary plains has been disturbed by long‐term anthropogenic extraction, and its hydrochemical quality is required for sustainable development. The present research investigates the hydrochemical characteristics, formation, potential health threats, and quality suitability of the confined groundwater in the central North China Plain. Results show that the confined groundwater has a slightly alkaline nature in the study area, predominantly dominated by fresh‐soft Cl‐Na and HCO3‐Na types. Water chemistry is governed by water–rock interactions, including dissolution of evaporites and cation exchange. Approximately 97% of the sampled confined groundwaters exceed the prescribed standard for F−. It is mainly due to geological factors such as mineral dissolution, cation exchange, and competitive adsorption of HCO3− and may also be released from compacted soils because of groundwater extraction. Enriched F− in the confined groundwater can pose an intermediate and higher non‐carcinogenic risk to more than 90% of the population. It poses the greatest health threat to the population in the north‐eastern part of the study area, especially to infants and children. For sustainable development, the long‐term use of confined groundwater for irrigation in the area should be avoided, and attention should also be paid to the potential soil salinization and infiltration risks. In the study area, 97% of the confined groundwaters are found to be excellent or good quality for domestic purposes based on Entropy‐weighted Water Quality Index. However, the non‐carcinogenic health risk caused by high contents of F− cannot be ignored. Therefore, it is recommended that differential water supplies should be implemented according to the spatial heterogeneity of confined groundwater quality to ensure the scientific and rational use of groundwater resources.Practitioner Points
The hydrochemistry quality of confined groundwater in an arid sedimentary plain disturbed by long‐term anthropogenic extraction was investigated.
The suitability of confined groundwater for multiple purposes such as irrigation and drinking were evaluated.
The hydrochemical characteristics and formation mechanism of confined groundwater under the influence of multiple factors were revealed.
Harnessing green microbiology for sustainable water management, agriculture, and energy generation: Current advances and future prospects
Authors: Akinsemolu Adenike A. , Onyeaka Helen , Arijeniwa Foluke V. 
Published: August 2024

AbstractThis article presents an in‐depth overview of recent developments and prospects in utilizing green microbiology for sustainable water management. It highlights its vital role across various aspects of water management while underscoring its significance for global development. This article delves deep into microbial processes integral to water management, such as degrading pollutants and using biosensors for quality monitoring of drinking water supplies. Furthermore, the article considers microorganisms' potential roles as biofertilizers and biostimulants in agriculture, their involvement in effluent treatment within microbial communities, and the emerging technologies of microbial fuel cells and nanotechnology. Implementation of microbial‐based approaches presents both challenges and opportunities, including regulatory concerns and public acceptance. Finally, this article reviews key findings and emphasizes research needs related to green microbiology to develop solutions towards cleaner, more sustainable water management solutions in the future.
Designing Maneuver Automata of Motion Primitives for Optimal Cooperative Trajectory Planning
Authors: Pedrosa Matheus V. A. , Scheffe Patrick , Alrifaee Bassam , Flaßkamp Kathrin 
Published: August 2024

AbstractTrajectory planning techniques form a central step to enable autonomous driving. The motion primitives method generates an automaton of precomputed maneuvers with structure-exploiting properties. Thereby, the trajectory planning problem can be reduced to finding an admissible/optimal sequence of motion primitives. In this chapter, we present ways to designing maneuver automata based on different system models and on either analytical or data-based approaches for automaton generation. Moreover, numerical methods for computing optimal maneuvers are listed and we discuss graph-based planning techniques. A subsequent chapter shows the evaluation of motion primitives automata in the Cyber-Physical Mobility Lab.
Insulin sensitivity, disposition index and insulin clearance in cystic fibrosis: a cross-sectional study
Authors: Nielsen Bibi U. , Mathiesen Inger H. M. , Krogh-Madsen Rikke , Katzenstein Terese L. , Pressler Tacjana , Shaw James A. M. , Rickels Michael R. , Almdal Thomas P. , Faurholt-Jepsen Daniel , Stefanovski Darko 
Published: August 2024

Abstract
Aims/hypothesis
The aim of this study was to investigate insulin secretion, insulin sensitivity, disposition index and insulin clearance by glucose tolerance status in individuals with cystic fibrosis (CF) and exocrine pancreatic insufficiency.

Methods
In a cross-sectional study, we conducted an extended (ten samples) OGTT in individuals with pancreatic-insufficient CF (PI-CF). Participants were divided into normal glucose tolerance (NGT), early glucose intolerance (EGI), impaired glucose tolerance (IGT) and CF-related diabetes (CFRD) groups. We used three different oral minimal models to assess insulin secretion, insulin sensitivity and insulin clearance during the OGTT. We evaluated insulin secretion using total secretion (Φ total), first-phase secretion (Φ dynamic) and second-phase secretion (Φ static) from the model, and we estimated the disposition index by multiplying Φ total and insulin sensitivity.

Results
Among 61 participants (NGT 21%, EGI 33%, IGT 16%, CFRD 30%), insulin secretion indices (Φ total, dynamic and static) were significantly lower in the CFRD group compared with the other groups. Insulin sensitivity declined with worsening in glucose tolerance (p value for trend <0.001) and the disposition index declined between NGT and EGI and between IGT and CFRD. Those with CFRD had elevated insulin clearance compared with NGT (p=0.019) and low insulin secretion (Φ total) was also associated with high insulin clearance (p<0.001).

Conclusions/interpretation
In individuals with PI-CF, disposition index declined with incremental impairment in glucose tolerance due to a reduction in both insulin secretion and insulin sensitivity. Moreover in CF, reduced insulin secretion was associated with higher insulin clearance.

Graphical Abstract
Irreducible unipotent numerical monoids
Authors: Can Mahir Bilen , Sakran Naufil 
Published: August 2024

AbstractIn our earlier article (Can and Sakran in Port Math 81(1–2): 21–55, 2024) we initiated a study of the complement-finite submonoids of the group of integer points of a unipotent linear algebraic group. In the present article, we continue to develop tools and techniques for analyzing our monoids. In particular, we initiate a theory of ideals for unipotent numerical monoids.
Multicenter and inter-software evaluation of ablative margins after thermal ablation of colorectal liver metastases
Authors: Laimer Gregor , Verdonschot Koen H. M. , Kopf Lina , van der Lei Susan , Scharll Yannick , Hannink Gerjon , Jenniskens Sjoerd F. M. , Meijerink Martijn R. , Bale Reto , Overduin Christiaan G. 
Published: August 2024

Abstract

Purpose
To assess the association between minimal ablative margin (MAM) and local tumor progression (LTP) following CT-guided thermal ablation of colorectal liver metastases (CRLM) in a multicenter cohort and across two confirmation software.

Materials and methods
This multicenter retrospective study included patients who underwent CT-guided radiofrequency or microwave ablation for CRLM between 2009 and 2021 in three institutions. Three-dimensional (3D) MAM was retrospectively assessed using dedicated ablation confirmation software by automatic non-rigid (Ablation-fit) or semi-automatic rigid co-registration (SAFIR) of intraprocedural pre- and post-ablation contrast-enhanced CT scans by two independent reader teams blinded to patient outcomes. LTP was assessed on a per-tumor basis. Factors associated with LTP-free survival were assessed using multivariable Cox regression analysis.

Results
Overall, 113 patients (mean age: 67 ± 10 years; 78 men) who underwent thermal ablation for 189 CRLM (mean diameter: 1.9 ± 1.1 cm) met the inclusion criteria. 173/189 (92%) CRLM could be successfully analyzed using both software. Over a median follow-up of 31 months (IQR: 22–47), 21 of 173 CRLM (12.1%) developed LTP. On multivariable analysis, 3D MAM was independently associated with LTP in both software (Ablation-fit: HR 0.47, 95% CI: 0.36–0.61, p < 0.001; SAFIR: HR 0.42, 95% CI: 0.32–0.55, p < 0.001). No LTP was observed in CRLM ablated with MAM ≥ 4 mm (Ablation-fit) and ≥ 5 mm (SAFIR). The per-tumor median absolute difference in MAM quantification between both software was 2 mm (IQR: 1–3).

Conclusion
MAM was independently associated with LTP after thermal ablation of CRLM across multicenter data and two confirmation software. Ablations achieving a MAM ≥ 5 mm were associated with local control in both software.

Clinical relevance statement
MAMs from intraprocedural contrast-enhanced CT were independently associated with LTP after thermal ablation of CRLM across multicenter data and two confirmation software, with a margin ≥ 5 mm associated with local control in both software.

Key Points

Sufficient ablative margins are critical for local control following thermal ablation of CRLM.

Intraprocedural CT-derived MAM was the only independent factor associated with LTP across two confirmation software.

No LTP was observed in CRLM ablated with a MAM ≥ 5 mm.
Real-world experience with the new pulsed solid-state Thulium: YAG laser (Thulio) for endoscopic enucleation of the prostate
Authors: von Bargen Maximilian Ferry , Glienke M. , Tonyali S. , Sigle A. , Wilhelm K. , Schoenthaler M. , Gratzke C. , Miernik A. 
Published: August 2024

Abstract
Purpose
The solid-state Thulium laser (Tm: YAG) is a novel alternative to the widely used Holmium laser for endoscopic enucleation of the prostate (EEP) due to its relatively high peak power. The aim of this study was to examine the efficacy and safety of a new pulsed Tm: YAG laser in its first application in humans.

Methods
Data were retrospectively collected for the first 103 patients who underwent EEP with a new pulsed solid-state Tm: YAG laser (Thulio®, Dornier MedTech Systems GmbH, Weßling, Germany). Peri- and postoperative data were assessed. Procedure-specific complications were graded using Clavien-Dindo Classifications (CDC). Patients were interviewed 15 months after the surgery to evaluate functional and long-term outcomes. Statistical analysis was performed with Statistical Package for the Social Sciences (SPSS®).

Results
The mean preoperative prostate volume was 105.6 ± 55.0 ml. Median enucleation speed was 4.1 g per minute (range 1.1–9.7). Short-term postoperative complications occurred in 21 patients (20.4%), but no high-grade complications (CDC ≥ IV) were observed. Five patients suffered gross haematuria and required reintervention (CDC IIIb; 4.9%). After 15 months, 76 patients (73.8%) participated in the follow-up interview, where seven patients (9.2%) reported complications, including two reinterventions for urethral strictures (CDC IIIb; 2.6%). Most patients reported an improvement in continence (54.0%) and urine stream (93.4%), but no difference in erectile function (81.6%). No persistent dysuria was reported. Patient satisfaction with the surgery results was very high (96.1%).

Conclusion
Endoscopic enucleation of the prostate with the new pulsed solid-state Tm: YAG laser is a safe and effective option for surgical BPH treatment.

Trial registration
German Clinical Trials Register number: DRKS00031676. Registration date: 10 May 2023, retrospectively registered.
DOG-EyeTeacher: eine Antwort der Arbeitsgemeinschaft Lehre auf die Umstrukturierungen im Medizinstudium
Authors: Stasik Isabel , Feltgen Nicolas , Plange Niklas , Holz Frank G. , Raupach Tobias ,   die Arbeitsgemeinschaft Lehre, Bartz-Schmidt  , Beyer  , Brandl  , Conrad-Hengerer  , Feltgen  , Flockerzi  , Gabel-Pfisterer  , Hoffmann  , Holz  , Kakkassery  , Lauermann  , Maier  , Mercieca  , Nagel  , Pfau  , Pitz  , Plange  , Raupauch  , Salchow  , Schmack  , Schrittenlocher  , Stahl  , Stasik  , Storp  , Tode  , Vorwerk  , Zimmermann  
Published: August 2024

Zusammenfassung
Hintergrund
Der 2017 verabschiedete Masterplan Medizin 2020 sieht viele Veränderungen im Medizinstudium vor. Auch die Lehrinhalte und Unterrichtsschwerpunkte werden von den Neustrukturierungen betroffen sein. Ein Ziel ist es, die Studierenden kompetenzorientiert auf ihre zukünftige Aufgabe als Ärztinnen und Ärzte vorzubereiten. Der NKLM (Nationaler Kompetenzbasierter Lernzielkatalog Medizin) bildet hierbei die Basis der zukünftig zu unterrichtenden Lehrinhalte.

Methoden
Die Arbeitsgemeinschaft Lehre der DOG hat sich zur Aufgabe gemacht, diese Umstrukturierungen aktiv zu begleiten. In einer standortübergreifenden Zusammenarbeit wurden zur Unterstützung der Lehrenden und auf der Grundlage des NKLM Lehrmaterialien für verschiedene Unterrichtsformate zusammengestellt (z. B. Folien für den Kleingruppenunterricht, Operationsmitschnitte, Bildergalerien, Fallbeispiele) und anschließend in einer Online-Bibliothek, DOG-EyeTeacher genannt, zusammengeführt.

Ergebnisse
Der DOG-EyeTeacher soll die Lehrenden an den Universitäten und ihren Ausbildungskliniken unterstützen, den Qualitätsstandard inhaltlicher Schwerpunkte angleichen, den allseitigen Dialog über die Lehre in der Augenheilkunde fördern und gleichzeitig der Lehre als wichtiger Säule des universitären Dreiklangs in der Medizin mehr Gewicht verleihen. Langfristig soll durch die Bereitstellung ansprechender und zeitgemäßer Lehrmaterialien das Interesse angehender Ärztinnen und Ärzte am Fach Ophthalmologie gesteigert werden.

Schlussfolgerung
Der DOG-EyeTeacher stellt eine Antwort der Arbeitsgemeinschaft Lehre der DOG auf die mit der geplanten Neustrukturierung des Medizinstudiums einhergehenden Herausforderungen dar. Jedes lehrinteressierte DOG-Mitglied kann sich seit Oktober 2023 kostenfrei einen Account erstellen und die Lehrmaterialien nutzen.
Carl Flügge, one of the last holistic hygienists and discoverer of droplet transmission of infectious diseases
Authors: Donald Peter R. , Kaufmann Stefan H.E. , Schaub Dagmar , Thee Stephanie , Lange Christoph 
Published: August 2024

AbstractCarl Flügge is best known for the promotion of studies demonstrating the transmission of all manner of infections, but particularly tuberculosis, by coughed droplets. But it is seldom recognised that Flügge was also influential in a number of other fields comprising the practice of hygiene. One-hundred years following his death in 1923, we review literature related to the studies of Flügge and his colleagues and students and illustrate the particular emphasis he laid upon the environment within which disease and its transmission might be fostered or prevented, embracing and studying aspects essential to the health of any community ranging from fundamental microbiology in the laboratory to subjects as disparate as housing, clean water supply, nutrition, sanitation, socio-economic circumstances and climate. Very early in his career he promoted breast feeding for the prevention of seasonal gastro-enteritis and later the sheltering of cough as a means of preventing the transmission of infected respiratory droplets, not only as regards tuberculosis, but also concerning all manner of other respiratory infections. By the time of Flügge’s death the complexification of available scientific methodologies comprising hygiene made it difficult for any individual to comprehend and study the wide range of hygiene-related subjects such as Flügge did. Carl Flügge was one of the last holistic hygienists and an originator of the study of environmental health as a pillar of hygiene.
Advancing horizons in remote sensing: a comprehensive survey of deep learning models and applications in image classification and beyond
Authors: Paheding Sidike , Saleem Ashraf , Siddiqui Mohammad Faridul Haque , Rawashdeh Nathir , Essa Almabrok , Reyes Abel A. 
Published: August 2024

AbstractIn recent years, deep learning has significantly reshaped numerous fields and applications, fundamentally altering how we tackle a variety of challenges. Areas such as natural language processing (NLP), computer vision, healthcare, network security, wide-area surveillance, and precision agriculture have leveraged the merits of the deep learning era. Particularly, deep learning has significantly improved the analysis of remote sensing images, with a continuous increase in the number of researchers and contributions to the field. The high impact of deep learning development is complemented by rapid advancements and the availability of data from a variety of sensors, including high-resolution RGB, thermal, LiDAR, and multi-/hyperspectral cameras, as well as emerging sensing platforms such as satellites and aerial vehicles that can be captured by multi-temporal, multi-sensor, and sensing devices with a wider view. This study aims to present an extensive survey that encapsulates widely used deep learning strategies for tackling image classification challenges in remote sensing. It encompasses an exploration of remote sensing imaging platforms, sensor varieties, practical applications, and prospective developments in the field.
A novel methodology for offline English handwritten character recognition using ELBP-based sequential (CNN)
Authors: Humayun Muniba , Siddiqi Raheel , Uddin Mueen , Kandhro Irfan Ali , Abdelhaq Maha , Alsaqour Raed 
Published: August 2024

AbstractHandwritten character recognition falls under the domain of image classification, which has been under research for years. But still, specific gaps need to be highlighted as offline handwritten character recognition (OHCR) with the limitation of the unstructured hierarchy of character classification. However, the idea is to make the machine recognize handwritten human characters. The language focused on in this research paper is English, using offline handwritten character recognition for identifying English characters. There are many publicly available datasets, of which EMNIST is the most challenging. The key idea of this research paper is to recommend a deep learning-based ELBP-CNN method to help recognize English characters. This research paper proposes a deep learning CovNet with feature extraction and novel local binary pattern-based approaches, LBP (AND, OR), that is tested and compared with renowned pre-trained models using transfer learning. These parametric settings address multiple issues and are finalized after experimentation. The same hyperparametric settings were used for all the models under test and E-Character, with the same data augmentation settings. The proposed model, named the E-Character recognizer, produced 87.31% accuracy. It was better than most of the tested pre-trained models and other proposed methods by other researchers. This research paper further highlighted some problems, like misclassification due to the similar structure of characters.
Advances in remote sensing based soil moisture retrieval: applications, techniques, scales and challenges for combining machine learning and physical models
Authors: Abbes Ali Ben , Jarray Noureddine , Farah Imed Riadh 
Published: August 2024

AbstractSoil Moisture (SM) monitoring is crucial for various applications in agriculture, hydrology, and climate science. Remote Sensing (RS) offers a powerful tool for large-scale SM retrieval. This paper explores the advancements in RS techniques for SM estimation. We discuss the applications of these techniques, along with the advantages and limitations of traditional physical models and data-driven Machine Learning (ML) based approaches. The paper emphasizes the potential of combining ML and physical models to leverage the strengths of both approaches. We explore the challenges associated with this integration and future research directions to improve the accuracy, scalability, and robustness of RS-based SM retrieval. Finally, the paper also discusses a few issues such as input data selection, data availability, ML complexity, the need for public datasets for benchmarking, and analysis.