bluuebunny/crossref_metadata_2025 huggingface dataset:
Ionizable Lipid Containing Nanocarriers for Antimicrobial Agent Delivery
Authors: Yu Haitao , Sarkar Sampa , Shaw Z. L. , Dyett Brendan , Cai Xudong , Yap Sue Lyn , Conn Charlotte E. , Elbourne Aaron , Drummond Calum J. , Zhai Jiali
Published: August 2024

Antimicrobial resistance (AMR) poses a global health crisis demanding innovative solutions. Traditional antibiotics, though pivotal over the past century in combating bacterial infections, face diminished efficacy against evolving bacterial defense mechanisms, especially in Gram‐negative strains. This study explores self‐assembled ionizable lipid nanoparticles (LNPs) with the incorporation of two ionizable lipid components (one cationic, one anionic) in nanocarriers for advanced antimicrobial drug delivery of the broad‐spectrum antibiotic Piperacillin (Pip). Incorporating cationic ionizable lipid ALC‐0315, recognized as a functional lipid in the Pfizer‐BioNTech mRNA‐based SARS‐CoV‐2 vaccine, into LNPs allowed mesophase transition, pH responsiveness, and ionization behavior in acidic environments found in sites of bacterial infections, to be studied using synchrotron small angle X‐ray scattering, dynamic light scattering, and a 2‐(p‐toluidino)‐6‐naphthalene sulfonic acid assay. Incorporating another anionic ionizable lipid, oleic acid not only modulates the LNPs’ physicochemical properties, such as size, internal phase nanostructure, and surface charge but also synergistically enhances the antimicrobial potency together with ALC‐0315 with a benefit enhancing permeability and fusion with bacterial membranes. This study introduces a strategy for tailoring ionizable lipid compositions in LNPs, providing a new approach to antimicrobial treatment contributing to the fight against AMR.
Total reflection x‐ray fluorescence analysis of trace elements in highly saline samples
Authors: Wiggershaus Bastian , Franke Eric , Vogt Carla
Published: August 2024

The reliable trace analysis of high‐purity chemicals and environmentally relevant samples is more important than ever and has led to the development of novel analytical methods. Total reflection x‐ray fluorescence (TXRF) analysis is an increasingly known method for the determination of heavy metals at low concentration levels in environmental and industrial sample systems. However, there is still a need for optimization to obtain fast and precise results, especially for highly saline samples like brines and salts used in battery production or sea water. In this study, multi‐element standard solutions containing analytes like Co, Cr, Cu, Fe, Mn, Ni, or Zn in a concentration range between 0.1 and 1 mg/L were analyzed in the matrices lithium carbonate (Li2CO3) and artificial seawater (ASW) containing 1000 mg/L Li and 24,000 mg/L NaCl, respectively, leading to matrix‐analyte ratios of up to 240,000:1. Different sample preparation methods were compared in order to achieve the highest possible repeatability (1) and signal‐to‐noise ratios (2) with the least amount of time (3). Various parameters such as sample volume, drying conditions, time, temperature and additive concentration were varied. The relative standard deviation (RSD%) was used as a measure of repeatability for three replicates per sample. For lithium carbonate, a method with a preparation time of only 2 min and a measurement time of 500 s could be developed, which allowed to obtain RSD% well below 5%, a high linearity (R2 > 0.99) and limits of detection (LOD) in the range of 30 μg/L to 60 μg/L for most elements. Seawater analysis could be optimized with respect to signal‐to‐noise ratio, whereby the Kα‐line of the internal standard (Ga) was used for evaluation and the use of a desiccator was found to yield the best results.
Falcon 7b for Software Mention Detection in Scholarly Documents
Authors: Khan AmeerAli , Ramadan Qusai , Yang Cong , Boukhers Zeyd
Published: August 2024

This paper aims to tackle the challenge posed by the increasing integration of software tools in research across various disciplines by investigating the application of Falcon-7b for the detection and classification of software mentions within scholarly texts. Specifically, the study focuses on solving Subtask I of the Software Mention Detection in Scholarly Publications (SOMD), which entails identifying and categorizing software mentions from academic literature. Through comprehensive experimentation, the paper explores different training strategies, including a dual-classifier approach, adaptive sampling, and weighted loss scaling, to enhance detection accuracy while overcoming the complexities of class imbalance and the nuanced syntax of scholarly writing. The findings highlight the benefits of selective labelling and adaptive sampling in improving the model’s performance. However, they also indicate that integrating multiple strategies does not necessarily result in cumulative improvements. This research offers insights into the effective application of large language models for specific tasks such as SOMD, underlining the importance of tailored approaches to address the unique challenges presented by academic text analysis.
Relations between closed string amplitudes and mixed string amplitudes at tree-level
Authors: Yuenyong Aphiwat , Srisangyingcharoen Pongwit
Published: August 2024

Abstract

This paper investigates the relationships between closed and mixed string amplitudes at the tree level in string theory. Through the analytic continuation of complex variables, we establish a factorization of closed string amplitudes into those involving (n − 2) open strings and a single closed string. Expressions for four-, five-, and six-point amplitudes are provided, together with systematic formulations for n-point string amplitudes. The paper addresses possible correction terms arising from integration along infinite tubes during the process of Wick rotations. The implications of our findings are discussed in certain limits.
Reformvorhaben „Gelegenheits-Onkochirurgie“
Authors: Spreider Valesca , Fichtner-Feigl Stefan , Wenz Frederik , Bockelmann Dalibor
Published: August 2024

Hintergrund

Nach wie vor stellen Krebsleiden die zweithäufigste Todesursache in Deutschland dar. Leistungssteuerung und Spezialisierungskonzepte in der Medizin bergen Potenziale, die Versorgung und die Überlebenschancen von Patientinnen und Patienten positiv zu beeinflussen.

Ziel der Arbeit

Aus der Gesetzesinitiative im Rahmen des KHVVG resultiert aus der Perspektive des UKF eine ganze Reihe medizinstrategischer Implikationen. Diese Arbeit erläutert und diskutiert die Hintergründe, Ziele und Inhalte des Reformvorhabens „Gelegenheits-Onkochirurgie“ und gibt Perspektiven auf strategische Handlungsfelder.

Material und Methoden

Analyse und Interpretation des Entwurfs eines Gesetzes zur Verbesserung der Versorgungsqualität im Krankenhaus und zur Reform der Vergütungsstrukturen (Gesetzentwurf der Bundesregierung).

Ergebnisse

Aus Sicht des UKF sollten Krankenhäuser frühestmöglich und proaktiv Kooperationsgespräche mit benachbarten Krankenhäusern zur Gestaltung der regionalen Gesundheitsversorgung führen mit den Zielen, die lokale Allokation onkologischer Patientinnen und Patienten im Sinne einer bestmöglichen Behandlung abzubilden, den Verlust von Patienten an den betroffenen Standorten abzufedern sowie den Patientenaufwuchs bei den Einrichtungen, die weiterhin onkochirurgisch versorgen werden, vorzubereiten.

Diskussion

Das noch laufende Gesetzgebungsverfahren sowie der Umstand, dass eine belastbare Analyse der relevanten Leistungsbereiche erst im ersten Halbjahr 2025 für Krankenhäuser möglich sein wird, stellt die Einrichtungen vor besondere Herausforderungen in der strategischen Planung ihrer Aktivitäten. Die im Rahmen dieser Arbeit dargestellten Lücken im Gesetzesvorhaben sollten dringend geschlossen werden, um die Ziele des Vorhabens nicht zu konterkarieren und die im System verbleibenden Leistungserbringer bei ihren Vorbereitungen zu unterstützen.
Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening
Authors: Hupatz Henrik , Rahu Ida , Wang Wei-Chieh , Peets Pilleriin , Palm Emma H. , Kruve Anneli
Published: August 2024

Non-targeted screening with liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS) is increasingly leveraging in silico﻿ methods, including machine learning, to obtain candidate structures for structural annotation of LC/HRMS features and their further prioritization. Candidate structures are commonly retrieved based on the tandem mass spectral information either from spectral or structural databases; however, the vast majority of the detected LC/HRMS features remain unannotated, constituting what we refer to as a part of the unknown chemical space. Recently, the exploration of this chemical space has become accessible through generative models. Furthermore, the evaluation of the candidate structures benefits from the complementary empirical analytical information such as retention time, collision cross section values, and ionization type. In this critical review, we provide an overview of the current approaches for retrieving and prioritizing candidate structures. These approaches come with their own set of advantages and limitations, as we showcase in the example of structural annotation of ten known and ten unknown LC/HRMS features. We emphasize that these limitations stem from both experimental and computational considerations. Finally, we highlight three key considerations for the future development of in silico methods.

Graphical Abstract
Modelling analysis of nitrogen removal from paddy water with high infiltration rate
Authors: Saiki Makoto , Egusa Tomohiro , Ohte Nobuhito , Nishida Kei
Published: August 2024

An understanding of nitrogen processes in a paddy field, characterised by large water flux for irrigation and outflows under continuous irrigation, is required to manage adequate nitrogen inputs and outputs. This study identifies the effect of large water flux, especially high infiltration rate, on nitrogen processes in a paddy field under continuous irrigation. The developed nitrogen process model in this study was applied to two paddy fields having different infiltration rates (216 and 106 mm day− 1 on average), and simulated physicochemical and biological nitrogen processes in ponded water, soil water and soil, including whole water flows as well as organic, and inorganic nitrogen forms. In each field, irrigation was found to be the major nitrogen input (153.2–461.5 kg N ha− 1 year− 1), and nitrogen outflow (65.2–284.3 kg N ha− 1 year− 1) found to be smaller than the input from irrigation. The irrigation water was primarily contaminated by dissolved organic nitrogen (DON) and nitrate. Nitrogen transportation from ponded water to soil water was four times greater under high infiltration condition than under low infiltration condition. High nitrogen transport to the soil layer increased air emission via denitrification and decreased outflows. In particular, DON and ammonium transported to soil water are sources of nitrite and nitrate, and denitrification was five times higher under high infiltration than low infiltration. The results of this study imply that paddy fields with high infiltration rates have a greater possibility of nitrogen removal from paddy water, rather than being a pollutant source for the water environment.
Patient perspectives on the use of artificial intelligence in prostate cancer diagnosis on MRI
Authors: Fransen Stefan J. , Kwee T. C. , Rouw D. , Roest C. , van Lohuizen Q. Y. , Simonis F. F. J. , van Leeuwen P. J. , Heijmink S. , Ongena Y. P. , Haan M. , Yakar D.
Published: August 2024

Objectives

This study investigated patients’ acceptance of artificial intelligence (AI) for diagnosing prostate cancer (PCa) on MRI scans and the factors influencing their trust in AI diagnoses.

Materials and methods

A prospective, multicenter study was conducted between January and November 2023. Patients undergoing prostate MRI were surveyed about their opinions on hypothetical AI assessment of their MRI scans. The questionnaire included nine items: four on hypothetical scenarios of combinations between AI and the radiologist, two on trust in the diagnosis, and three on accountability for misdiagnosis. Relationships between the items and independent variables were assessed using multivariate analysis.

Results

A total of 212 PCa suspicious patients undergoing prostate MRI were included. The majority preferred AI involvement in their PCa diagnosis alongside a radiologist, with 91% agreeing with AI as the primary reader and 79% as the secondary reader. If AI has a high certainty diagnosis, 15% of the respondents would accept it as the sole decision-maker. Autonomous AI outperforming radiologists would be accepted by 52%. Higher educated persons tended to accept AI when it would outperform radiologists (p < 0.05). The respondents indicated that the hospital (76%), radiologist (70%), and program developer (55%) should be held accountable for misdiagnosis.

Conclusions

Patients favor AI involvement alongside radiologists in PCa diagnosis. Trust in AI diagnosis depends on the patient’s education level and the AI performance, with autonomous AI acceptance by a small majority on the condition that AI outperforms a radiologist. Respondents held the hospital, radiologist, and program developers accountable for misdiagnosis in descending order of accountability.

Clinical relevance statement

Patients show a high level of acceptance for AI-assisted prostate cancer diagnosis on MRI, either alongside radiologists or fully autonomous, particularly if it demonstrates superior performance to radiologists alone.

Key Points

Prostate cancer suspicious patients may accept autonomous AI based on performance.

Patients prefer AI involvement alongside a radiologist in diagnosing prostate cancer.

Patients indicate accountability for AI should be shared among multiple stakeholders.
Kirchlich getragene Einrichtungen des Gesundheits- und Sozialwesens: Neue Vorlagefrage an den Europäischen Gerichtshof
Authors: Kreß Hartmut
Published: August 2024

Zum kirchlichen Arbeitsrecht liegt dem EuGH ein neues Vorabentscheidungsersuchen des BAG vor. Es
betrifft die Frage, ob eine katholisch getragene Einrichtung einer in der Schwangerenberatung tätigen
Sozialpädagogin aufgrund von Kirchenaustritt kündigen darf, obwohl die Einrichtung auf solchen
Stellen ansonsten auch nichtkatholische Mitarbeiterinnen beschäftigt. Wenn der EuGH die Vorlagefrage
auf der Linie seiner bisherigen Judikatur beantwortet, werden Sonderrechte, die in der Bundesrepublik den
Kirchen als Arbeitgebern gewährt werden, erneut eingegrenzt und die individuellen Grundrechte von kirchlich
Beschäftigten nochmals gestärkt werden.
Rasmussen’s encephalitis: structural, functional, and clinical correlates of contralesional epileptiform activity
Authors: Bauer Tobias , von Wrede Randi D. , Pujar Suresh , Rácz Attila , Hoppe Christian , Baumgartner Tobias , Varadkar Sophia , Held Nina R. , Reiter Johannes T. , Enders Selma , David Bastian , Prillwitz Conrad C. , Brugues Mar , Keil Vera C. W. , Jeub Monika , Borger Valeri , Sander Josemir W. , Kunz Wolfram S. , Radbruch Alexander , Weber Bernd , Helmstaedter Christoph , Vatter Hartmut , Baldeweg Torsten , Becker Albert J. , Cross J. Helen , Surges Rainer , Rüber Theodor
Published: August 2024

Progressive inflammation of one hemisphere characterises Rasmussen’s encephalitis (RE), but contralesional epileptiform activity has been repeatedly reported. We aimed to quantify contralesional epileptiform activity in RE and uncover its functional and structural underpinnings. We retrospectively ascertained people with RE treated between 2000 and 2018 at a tertiary centre (Centre 1) and reviewed all available EEG datasets. The temporal occurrence of preoperative contralesional epileptiform activity (interictal/ictal) was evaluated using mixed-effects logistic regression. Cases with/without contralesional epileptiform activity were compared for cognition, inflammation (ipsilesional brain biopsies), and MRI (cortical and fixel-based morphometry). EEG findings were validated in a second cohort treated at another tertiary centre (Centre 2) between 1995 and 2020. We included 127 people with RE and 687 EEG samples. Preoperatively, contralesional epileptiform activity was seen in 30/68 (44%, Centre 1) and 8/59 (14%, Centre 2). In both cohorts, this activity was associated with younger onset age (OR = 0.9; 95% CI 0.83–0.97; P = 0.006). At centre 1, contralesional epileptiform activity was associated with contralesional MRI alterations, lower intelligence (OR = 5.19; 95% CI 1.28–21.08; P = 0.021), and impaired verbal memory (OR = 10.29; 95% CI 1.97–53.85; P = 0.006). After hemispherotomy, 11/17 (65%, Centre 1) and 28/37 (76%, Centre 2) were seizure-free. Contralesional epileptiform activity was persistent postoperatively in 6/12 (50%, Centre 1) and 2/34 (6%, Centre 2). Preoperative contralesional epileptiform activity reduced the chance of postoperative seizure freedom in both cohorts (OR = 0.69; 95% CI 0.50–0.95; P = 0.029). Our findings question the concept of strict unilaterality of RE and provide the evidence of contralesional epileptiform activity as a possible EEG predictor for persisting postoperative seizures.
Exploring the risk of heat stress in high school pre-season sports training, Johannesburg, South Africa
Authors: Raines Kayleigh , Fitchett Jennifer M.
Published: August 2024

There is growing concern over the increased risk of heat stress induced by the changing climate, with increased global temperatures expected to exacerbate conditions. Heat stress in school sports is a critically understudied research area in South Africa (SA). As demonstrated by several studies conducted in the global north, the stress elicited by meteorological conditions on students participating in physical education lessons and after-school sports activities could have serious consequences on their health. This paper represents the first research in the region to investigate the risk of heat stress to school students during physical activity. Meteorological data were collected at a school in Johannesburg between March and July, which encompasses the seasons of late summer, autumn, and winter. These were inputted into four heat stress indices: Humidex, Heat Index, Wet Bulb Globe Temperature, and the Universal Thermal Climate Index, together with the measured Wet Bulb Temperature to determine the level of risk of heat stress during physical education lessons and after-school sports activities between March and July. Of the 2700 index scores calculated over this period, 56% indicate some level of heat stress, with almost 6% indicating a high and very high level of risk. Heat stress is calculated to be most likely to occur between 11h00-15h00, and the danger of pre-season training, which takes place in the summer months, is demonstrated by these results. Additionally, this research finds that heat stress is far more likely on artificial surfaces than on natural grass. The findings of this research intimate that school stakeholders should consider the implications of heat stress when considering timetabling and policy-making in the interests of safeguarding their students.
Predictors of discontinuation of osteoporosis treatment: sub-analysis of the Japanese osteoporosis intervention trial-05 (JOINT-05)
Authors: Takeuchi Yasuhiro , Nakatsuka Yuki , Tanaka Shiro , Kuroda Tatsuhiko , Hagino Hiroshi , Mori Satoshi , Soen Satoshi
Published: August 2024

Introduction

To identify predictors of discontinuing treatment with teriparatide (TPTD) and alendronate (ALN), data from a randomized, controlled trial (JOINT-05) involving postmenopausal Japanese women at high risk of fracture were re-analyzed.

Materials and Methods

Participants received sequential therapy with once-weekly TPTD for 72 weeks followed by ALN for 48 weeks (TPTD-ALN group) or monotherapy with ALN for 120 weeks (ALN group). Background data including comorbidities, fracture prevalence, cognitive function, quality of life, activities of daily living, bone metabolism parameters, and nutrient intake were collected. The endpoints were 3 types of discontinuations by the reason: a poor compliance, adverse events (AEs), or any reason including those unrelated to AEs or poor compliance. Odds ratios (ORs) of baseline predictors of discontinuation were evaluated by single or multiple regression analysis.

Results

A total of 234 (49.0%) patients in the TPTD-ALN group and 167 (34.2%) patients in the ALN group discontinued. In the TPTD-ALN group, a lower serum calcium level was a significant predictor of compliance-related discontinuation. Serum 25-hydroxyvitamin D levels were lower in patients with lower serum calcium levels than with higher serum calcium levels. In the ALN group, poor cognitive function was significantly associated with compliance-related discontinuation, and higher body mass index and alcohol intake were predictors of AE-related discontinuation. Predictors of discontinuation were drug-specific. Lower serum calcium levels and poor cognitive function were predictors of discontinuing once-weekly TPTD and ALN, respectively.

Conclusion

When starting TPTD and ALN treatment, careful attention to patients with lower serum calcium levels and poor cognitive function, respectively, may be needed for better treatment continuity.
Prevalence, severity and risk factors for mental disorders among sexual and gender minority young people: a systematic review of systematic reviews and meta-analyses
Authors: O’Shea Jonathan , Jenkins Rebecca , Nicholls Dasha , Downs James , Hudson Lee D.
Published: August 2024

Evidence suggests heightened prevalence and severity of mental disorders among sexual minority (SM) and gender minority (GM) young people. Several risk factors have been associated with these disparities. A systematic review of systematic reviews and meta-analysis was conducted to provide a comprehensive overview of the literature and to determine the field’s current position. MEDLINE, PsycInfo, Scopus and Web of Science were searched in March 2022 and updated January 2024. Eligibility criteria were systematic reviews or meta-analyses assessing contemporaneous prevalence, severity and/or risk factors of mental disorders among SM or GM young people aged 25 and under. 42 reviews were included, all of which were low quality. The prevalence of depression among SM was 26% (95% CI 21–32%), and among GM was 46% (95% CI 36–56%). Greater depression severity was found among SM compared to heterosexual young people, with a significant albeit small effect size (Hedges’ g = 0.38, 95% CI = 0.25 to 0.50); effect sizes were similar when separating by gender. GM also reported greater symptom severity compared to cisgender young people. Other mental disorders were more prevalent compared to those reported in the general population, and of greater severity compared to heterosexual/cisgender young people. Several proximal and distal risk factors were focused upon within the systematic reviews identified. Past systematic reviews consistently indicate a heightened risk of mental disorders among SM and GM young people. Services need to be aware of these disparities and adapt their care accordingly.
The effects of laser acupuncture on metabolic syndrome in obese postmenopausal women: a randomized controlled study
Authors: Kamal Wafaa M. , Maged Ahmed M. , AbdelAziz Suzi , Mahmoud Safaa I. , Mohsen Reham A.
Published: August 2024

To study the laser acupuncture (LA) effects on postmenopausal obese women’s metabolic syndrome. Randomized controlled trial. Benha university hospital. Thirty postmenopausal women were randomized into two equal groups. Group A received a diet regimen and Group B received LA treatment for 30 min three times a week for two months beside the diet regimen. Included weight (W), body mass index (BMI), waist (WC), hip (HC), waist-hip ratio (WHR), systolic blood pressure (SBP), diastolic blood pressure (DBP), serum level of total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), fasting blood glucose (FBG), fasting blood insulin (FBI), homeostatic model assessment-insulin resistance (HOMA-IR) before and after the end of treatment. The study’s findings showed that both groups experienced a highly statistically significant decrease in the post-testing mean value of W, BMI, WC, HC, WHR, SBP, DBP, TC, TG, LDL, FBG, FBI, and HOMA-IR, while both groups experienced a significant increase in the post-treatment mean value of HDL (p 0.0001). The posttreatment SBP, DBP, TC, TG, LDL, FBS, FBI and insulin resistance were significantly lower while HDL was significantly higher in women who received combined LA and diet regimen compared to those who received dietary regimen only. LA beside the nutritional intervention is a physical therapy technique that may be used safely, easily, and effectively to minimize metabolic syndrome features during menopause.
SYZ mirror symmetry of solvmanifolds
Authors: Bedulli Lucio , Vannini Alessandro
Published: August 2024

We present an effective construction of non-Kähler supersymmetric mirror pairs in the sense of Lau, Tseng and Yau (Commun. Math. Phys. 340:145–170, 2015) starting from left-invariant affine structures on Lie groups. Applying this construction we explicitly find SYZ mirror symmetric partners of all known compact 6-dimensional completely solvable solvmanifolds that admit a semi-flat type IIA structure.
Use of weather types to analyze the simultaneous abundance of ozone, PM2.5 and allergenic tree pollen: focusing on the potential impact on asthma hospitalization in Montreal, Canada
Authors: Robichaud Alain
Published: August 2024

Air pollution, aeroallergens, and weather conditions can worsen health symptoms such as asthma. While studying the impact of these factors, the use of weather types (WTs) rather than individual meteorological variables (such as temperature, relative humidity, wind, cloudiness, or precipitation) is more appropriate since it is holistic and integrative. Moreover, several studies have shown that the human body responds to WTs, rather than to individual meteorological variables. In this study, the use of Sheridan’s WTs is adopted and compared with a so-called “In-House” WTs. The analysis presented here deals with the links between asthma hospitalization and the synergy among air pollution, birch tree pollen and WTs. Knowing the daily WT in a region can provide valuable information for health planning and management of asthma hospitalization, emergency visits and sub-clinical symptoms in the population. This is because air pollution and birch pollen both occur within only a few specific WTs, such as the TROWAL (trough of warm air aloft) or tropical airmasses. These specific WTs need to be more scrutinized since, in Montreal, these are often linked with higher daily mean hospitalization. The findings of this study emphasize the importance of specific WTs in determining the maximum daily concentrations of ozone, fine particles, Betula pollen concentrations and health effects such as asthma hospitalization. Moreover, the use of data filters in the analysis (for temperature and total count of hospitalization) also reveals new insights in the complex nature of asthma disease and its relationship with environmental factors.
Composition and diversity of ground beetles within wooded pastures and alternative land-use systems in Swiss Jura mountains
Authors: Zimmermann Erwan Edgar , Chittaro Yannick , Wider Sandrine , Zemp Delphine Clara
Published: August 2024

Wooded pastures combine trees and pastures in a land-use system resulting from traditional silvopastoral practices. With their sparse tree cover, wooded pastures represent an ecotone between open area pastures and forests with potentially high species diversity, although this is poorly tested for animal groups especially insects. In this study, we aimed to characterise and compare species communities in terms of species composition and diversity indices, biomass and ecological traits of ground beetles in wooded pastures, forests and non-wooded pastures. Pitfall traps were set up in 29 study sites located in the Swiss Jura mountains. Ground beetle communities in wooded pastures largely encompass those in open pastures and forests, although some species are found only in forests or open areas. Wooded pastures and open pastures have an equivalent species diversity level, which is significantly higher than the one in forests. Ground beetle diversity is positively correlated with the surfaces of Biodiversity Promotion Areas within a 100 m radius. Areas with high tree cover (70–100%) favour brachypterous and hygrophilic species, whereas areas with reduced tree cover (0–20%) favour xerophilic and winged species. Ground beetles’ size and biomass increase with tree cover. Wooded pastures are an important ecotone, ensuring a gradual change of land-use systems between open areas and forests, where a wide range of species from both land-use systems are found. These semi-natural systems are important for the conservation of ground beetles.
Effect of minocycline on changes in affective behaviors, cognitive function, and inflammation in breast cancer survivors undergoing chemotherapy: a pilot randomized controlled trial
Authors: Melink Zihan , Lustberg Maryam B. , Schnell Patrick M. , Mezzanotte-Sharpe Jessica , Orchard Tonya S.
Published: August 2024

Purpose

Minocycline suppresses chemotherapy-induced neuroinflammation in preclinical models, but its effects in cancer survivors are unknown. This study evaluated the longitudinal effects of minocycline on affective behaviors, cognitive functions, and inflammation in women with breast cancer (BC) undergoing chemotherapy.

Methods

This is a pilot, double-blind, randomized controlled trial of oral minocycline (100 mg BID) versus placebo for chemotherapy-induced affective disorders in women initiating chemotherapy for stage I–III BC. Participants received minocycline or placebo up to one week before chemotherapy, continuing through cycle 4 (C4). Epidemiologic Studies Depression Scale (CES-D) and State-Trait Anxiety Inventory (STAI) were assessed at baseline, each cycle of chemotherapy (C1–C4), 2–3-week post-chemotherapy (end of chemotherapy), and 6-month post-chemotherapy (6 M) as the primary outcomes. Sub-group analysis of CES-D and STAI based on the severity of symptoms was also performed. Changes in self-reported cognition and serum inflammatory markers were also evaluated.

Results

Fifty-seven women enrolled and 55 completed the study. Except for Interleukin-8 (p ≤ 0.03), changes in inflammatory markers, cognitive function, CES-D, and STAI were not significantly different between groups from baseline to any cycle or post-chemotherapy time point (all p > 0.05), adjusting for baseline scores. Increases in serum Interleukin-8 from baseline to C4 and 6 M were ameliorated by minocycline (p < 0.05). The sub-group symptomatic for depression (CES-D > = 16 at baseline) treated with minocycline had a greater reduction in CES-D score compared to placebo from baseline to 6 M (p = 0.01).

Conclusion

Despite attenuation of IL-8, minocycline did not alter self-reported affective symptoms or cognition in this cohort of BC survivors undergoing chemotherapy. The effect of minocycline on BC survivors symptomatic for depression before chemotherapy warrants further investigation.
Tiramisù: making sense of multi-faceted process information through time and space
Authors: Alman Anti , Arleo Alessio , Beerepoot Iris , Burattin Andrea , Di Ciccio Claudio , Resinas Manuel
Published: August 2024

Knowledge-intensive processes represent a particularly challenging scenario for process mining. The flexibility that such processes allow constitutes a hurdle as they are hard to capture in a single model. To tackle this problem, multiple visual representations of the same processes could be beneficial, each addressing different information dimensions according to the specific needs and background knowledge of the concrete process workers and stakeholders. In this paper, we propose, describe, and evaluate a framework, named , that leverages visual analytics for the interactive visualization of multi-faceted process information, aimed at supporting the investigation and insight generation of users in their process analysis tasks. is based on a multi-layer visualization methodology that includes a visual backdrop that provides context and an arbitrary number of superimposed and on-demand dimension layers. This arrangement allows our framework to display process information from different perspectives and to project this information onto a domain-friendly representation of the context in which the process unfolds. We provide an in-depth description of the approach’s founding principles, deeply rooted in visualization research, that justify our design choices for the whole framework. We demonstrate the feasibility of the framework through its application in two use-case scenarios in the context of healthcare and personal information management. Plus, we conducted qualitative evaluations with potential end users of both scenarios, gathering precious insights about the efficacy and applicability of our framework to various application domains.
An Analysis of Prospective Responsibilities
Authors: Whittle Ann
Published: August 2024

In this paper, I offer an analysis of prospective responsibilities. I begin by surveying recent accounts of prospective responsibilities and positioning my view within that literature. Then I offer a more detailed analysis of a shared component of these accounts, namely the claim that S is prospectively responsible for φ only if S has to ‘see to it that φ'.
Facial Expression Recognition for Probing Students’ Emotional Engagement in Science Learning
Authors: Tang Xiaoyu , Gong Yayun , Xiao Yang , Xiong Jianwen , Bao Lei
Published: August 2024

Student engagement in science classroom is an essential element for delivering effective instruction. However, the popular method for measuring students’ emotional learning engagement (ELE) relies on self-reporting, which has been criticized for possible bias and lacking fine-grained time solution needed to track the effects of short-term learning interactions. Recent research suggests that students’ facial expressions may serve as an external representation of their emotions in learning. Accordingly, this study proposes a machine learning method to efficiently measure students’ ELE in real classroom. Specifically, a facial expression recognition system based on a multiscale perception network (MP-FERS) was developed by combining the pleasure-displeasure, arousal-nonarousal, and dominance-submissiveness (PAD) emotion models. Data were collected from videos of six physics lessons with 108 students. Meanwhile, students’ academic records and self-reported learning engagement were also collected. The results show that students’ ELE measured by MP-FERS was a significant predictor of academic achievement and a better indicator of true learning status than self-reported ELE. Furthermore, MP-FERS can provide fine-grained time resolution on tracking the changes in students’ ELE in response to different teaching environments such as teacher-centered or student-centered classroom activities. The results of this study demonstrate the validity and utility of MP-FERS in studying students’ emotional learning engagement.
Development of a holistic framework for the description and characterization of company-individual Manufacturing Change Management processes
Authors: Rammo Jan-Philipp , Arifagic Almin , Agyekum Ellen , Zaeh Michael F.
Published: August 2024

In today’s manufacturing industry, companies operate in a complex and rapidly changing environment, resulting in an increasing number and variety of Manufacturing Changes (MCs). To ensure long-term competitiveness, companies must respond quickly, flexibly, and effectively to various types of MCs. While many companies have established processes to manage MCs, these processes often lack flexibility and a comprehensive methodological and digital support. Existing approaches to support these processes are often generic and difficult to transfer to a company’s unique Manufacturing Change Management (MCM) process. For this purpose, a framework and an associated application method have been developed in which MCM processes are abstracted and mathematically modeled using descriptive and characterizing attributes. To achieve a comprehensive view of the processes, the holistic framework intends to model people’s activities involved in the process, process steps, and the occurrence of information inside the process. The framework was developed through a three-phase approach, with attributes derived from the literature, case studies, and expert interviews. The framework and the associated application method were tested in a first industrial use case. In conclusion, the framework developed in this contribution supports practitioners and researchers to consistently describe and to flexibly adapt generally valid theoretical and practical approaches to company-individual MCM processes.
Experiences of unemployed and/or work-disabled cancer survivors who have pursued to return to paid employment: a focus group study
Authors: Greidanus M. A. , van Ommen F. , de Boer A. G. E. M. , Coenen P. , Duijts S. F. A.
Published: August 2024

Purpose

To explore experiences of unemployed and/or work-disabled cancer survivors who have pursued to return to paid employment.

Methods

Four digital focus group interviews were conducted with 16 cancer survivors (< 10 years post-diagnosis) who have pursued to return to work within the last 2 years. Interview topics included motivations, facilitators of and barriers to job seeking, and returning to and maintaining paid employment. Interview audio recordings were transcribed verbatim and analyzed using conventional content analyses.

Results

Participants were mostly female (94%), and the majority had successfully returned to paid employment (56%). Both intrinsic factors (e.g., sense of purpose, social interactions) and extrinsic factors (e.g., financial necessity) motivated their return to paid employment. During job seeking, participants experienced facilitators including support, personal qualities (e.g., life experience), and trial workplaces. Barriers included inadequate support, perceived employer discrimination, and work ability uncertainty. Returning to and maintaining employment was facilitated by flexible work, supportive colleagues, and intrinsic drive, while barriers included side effects (e.g., fatigue) and overly demanding work.

Conclusions

Unemployed and/or work-disabled cancer survivors are generally motivated to return to paid employment by both intrinsic and extrinsic factors, but uncertainty about their ability and inadequate support may hinder this. These findings highlight the need for trial workplaces, support during every phase of return to paid employment, and a flexible, supportive workplace.

Implications for Cancer Survivors

Tailored interventions addressing the needs identified in this study are urgently needed. The recommendations provided offer strategies for various stakeholders to enhance support for unemployed and work-disabled cancer survivors.
Inquiry into the validity of the Digital Services Act and the role of the representative associations under that regulation
Authors: Pacuła Krzysztof
Published: August 2024

The Digital Services Act (DSA) tackles challenges arising from the evolution of online intermediary services and inevitably brings forth a multitude of legal issues regarding its operation. While the first rulings of the EU courts, delivered in incidental proceedings, have to be read in the specific context in which they were rendered, these decisions could serve as a noteworthy reference point for future discussions on the broader understanding of the DSA. An intriguing aspect of these rulings is their potential to illustrate two prospective approaches that may emerge in future case law concerning the DSA at both EU and national levels.
Life Project Scale: a new measure to assess the coherence of the intended future
Authors: Coscioni Vinicius , Teixeira Marco Antônio Pereira , Sacramento Adriana Malheiros , Paixão Maria Paula
Published: August 2024

This article identifies different types of validity and reliability evidence of the Life Project Scale (LPS), a new psychometric measure to assess the coherence of the intended future. It comprises three studies involving five samples that accounted for 2,808 participants from Brazil and Portugal. The final version of the LPS contains two factors with four items each. The factors assess identification (i.e., awareness of one’s intended future) and involvement (i.e., enactment of plans and actions in favor of one’s intended future). The two factors are indicators of the coherence of life projects’ intentional structures and action. Altogether, the three studies provide validity and reliability evidence based on exploratory and confirmatory factor analyses, the assessment of ceiling and floor effects, four types of reliability coefficients, relations to other measures (authenticity and meaning in life), and measurement invariance models. Therefore, the LPS is ready for further use, development, and testing in other research and practice contexts.
Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy
Authors: Takagi Hisamichi , Takeda Ken , Kadoya Noriyuki , Inoue Koki , Endo Shiki , Takahashi Noriyoshi , Yamamoto Takaya , Umezawa Rei , Jingu Keiichi
Published: August 2024

Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dose-volume histogram of prostatic urethra has been associated with such toxicities in previous reports. Previous research has focused on estimating the prostatic urethra, which is difficult to delineate in CT images; however, these studies, which are limited in number, mainly focused on cases undergoing brachytherapy uses low-dose-rate sources and do not involve external beam radiation therapy (EBRT). In this study, we aimed to develop a deep learning-based method of determining the position of the prostatic urethra in patients eligible for EBRT. We used contour data from 430 patients with localized prostate cancer. In all cases, a urethral catheter was placed when planning CT to identify the prostatic urethra. We used 2D and 3D U-Net segmentation models. The input images included the bladder and prostate, while the output images focused on the prostatic urethra. The 2D model determined the prostate’s position based on results from both coronal and sagittal directions. Evaluation metrics included the average distance between centerlines. The average centerline distances for the 2D and 3D models were 2.07 ± 0.87 mm and 2.05 ± 0.92 mm, respectively. Increasing the number of cases while maintaining equivalent accuracy as we did in this study suggests the potential for high generalization performance and the feasibility of using deep learning technology for estimating the position of the prostatic urethra.
Low-light enhancement method with dual branch feature fusion and learnable regularized attention
Authors: Sun Yixiang , Ni Mengyao , Zhao Ming , Yang Zhenyu , Peng Yuanlong , Cao Danhua
Published: August 2024

Restricted by the lighting conditions, the images captured at night tend to suffer from color aberration, noise, and other unfavorable factors, making it difficult for subsequent vision-based applications. To solve this problem, we propose a two-stage size-controllable low-light enhancement method, named Dual Fusion Enhancement Net (DFEN). The whole algorithm is built on a double U-Net structure, implementing brightness adjustment and detail revision respectively. A dual branch feature fusion module is adopted to enhance its ability of feature extraction and aggregation. We also design a learnable regularized attention module to balance the enhancement effect on different regions. Besides, we introduce a cosine training strategy to smooth the transition of the training target from the brightness adjustment stage to the detail revision stage during the training process. The proposed DFEN is tested on several low-light datasets, and the experimental results demonstrate that the algorithm achieves superior enhancement results with the similar parameters. It is worth noting that the lightest DFEN model reaches 11 FPS for image size of 1224×1024 in an RTX 3090 GPU.

Graphical Abstract
The Child Factor in Child–Robot Interaction: Discovering the Impact of Developmental Stage and Individual Characteristics
Authors: Rudenko Irina , Rudenko Andrey , Lilienthal Achim J. , Arras Kai O. , Bruno Barbara
Published: August 2024

Social robots, owing to their embodied physical presence in human spaces and the ability to directly interact with the users and their environment, have a great potential to support children in various activities in education, healthcare and daily life. Child–Robot Interaction (CRI), as any domain involving children, inevitably faces the major challenge of designing generalized strategies to work with unique, turbulent and very diverse individuals. Addressing this challenging endeavor requires to combine the standpoint of the robot-centered perspective, i.e. what robots technically can and are best positioned to do, with that of the child-centered perspective, i.e. what children may gain from the robot and how the robot should act to best support them in reaching the goals of the interaction. This article aims to help researchers bridge the two perspectives and proposes to address the development of CRI scenarios with insights from child psychology and child development theories. To that end, we review the outcomes of the CRI studies, outline common trends and challenges, and identify two key factors from child psychology that impact child-robot interactions, especially in a long-term perspective: developmental stage and individual characteristics. For both of them we discuss prospective experiment designs which support building naturally engaging and sustainable interactions.
A user study of visualisations of spatio-temporal eye tracking data
Authors: Claus Marcel , Hermens Frouke , Bromuri Stefano
Published: August 2024

Eye movements have a spatial (where people look), but also a temporal (when people look) component. Various types of visualizations have been proposed that take this spatio-temporal nature of the data into account, but it is unclear how well each one can be interpreted and whether such interpretation depends on the question asked about the data or the nature of the dataset that is being visualised. In this study, four spatio-temporal visualization techniques for eye movements (chord diagram, scan path, scarf plot, space-time cube) were compared in a user study. Participants

$$(N = 25)$$

(
N
=
25
)

answered three questions (what region first, what region most, which regions most between) about each visualization, which was based on two types of datasets (eye movements towards adverts, eye movements towards pairs of gambles). Accuracy of the answers depended on a combination of the dataset, the question that needed to answered, and the type of visualization. For most questions, the scan path, which did not use area of interest (AOI) information, resulted in lower accuracy than the other graphs. This suggests that AOIs improve the information conveyed by graphs. No effects of experience with reading graphs (for work or not for work) or education on accuracy of the answer was found. The results therefore suggest that there is no single best visualisation of the spatio-temporal aspects of eye movements. When visualising eye movement data, a user study may therefore be beneficial to determine the optimal visualization of the dataset and research question at hand.

Graphical abstract