bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Analysis of an Onboard PV System on a Demonstrator Light Commercial Vehicle in Hannover, Germany
Authors: Patel Neel , Sovetkin Evgenii , Pieters Bart , Bittkau Karsten , Ding Kaining , Peibst Robby , Fischer Hilke , Reinders Angèle
Published: January 2025

We present an analysis of the performance data of a monitored PV system onboard a light commercial electric vehicle during parking and driving conditions in the Hannover region of Germany. The PV system's nominal power is 2180 WP with flat silicon modules on the vehicle's roof, rear, left, and right sides and other electronic components needed to charge the vehicle's high‐voltage (HV) battery. The analysis indicated that after 488.92 h of operation, the modules mounted on the vehicle roof produced 133.32 kWh of electricity during parking at the best possible orientation compared to 15.4, 30.67, and 22.99 kWh for the modules mounted on the rear, left, and right sides, respectively. During the trips, after 31.99 h of operation, 6.12, 0.68, 1.08, and 1.86 kWh of electricity were produced by the modules on the roof, rear, left, and right sides, respectively. The overall system efficiency was in the 60%–65% range. The aggregated usable electricity reaching the HV battery after multiple conversion stages generated by the system at the two parking locations was 129.39 kWh. PV electricity generated at the two parking locations enabled a range extension of approximately 530 km, which is 30% of the total distance driven during the measurement period between April and July 2021.
Delay Margin Analysis of Uncertain Linear Control Systems Using Probabilistic μ$$ \mu $$
Authors: Somers F. , Roos C. , Biannic J.‐M. , Sanfedino F. , Preda V. , Bennani S. , Evain H.
Published: January 2025

Monte Carlo simulations have long been a widely used method in the industry for control system validation. They provide an accurate probability measure for sufficiently frequent phenomena but are often time‐consuming and may fail to detect very rare events. Conversely, deterministic techniques such as or IQC‐based analysis allow fast calculation of worst‐case stability margins and performance levels, but in the absence of a probabilistic framework, a control system may be invalidated on the basis of extremely rare events. Probabilistic ‐analysis has therefore been studied since the 1990s to bridge this analysis gap by focusing on rare but nonetheless possible situations that may threaten system integrity. The solution adopted in this paper implements a branch‐and‐bound algorithm to explore the whole uncertainty domain by dividing it into smaller and smaller subsets. At each step, sufficient conditions involving upper bound computations are used to check whether a given requirement–related to the delay margin in the present case–is satisfied or violated on the whole considered subset. Guaranteed bounds on the exact probability of delay margin satisfaction or violation are then obtained, based on the probability distributions of the uncertain parameters. The difficulty here arises from the exponential term classically used to represent a delay , which cannot be directly translated into the Linear Fractional Representation (LFR) framework imposed by ‐analysis. Two different approaches are proposed and compared in this paper to replace the set of delays . First, an equivalent representation using a rational function with unit gain and phase variations that exactly cover those of the original delays, resulting in an LFR with frequency‐dependent uncertainty bounds. Then, Padé approximations, whose order is chosen to handle the trade‐off between conservatism and complexity. A constructive way to derive minimal LFR from Padé approximations of any order is also provided as an additional contribution. The whole method is first assessed on a simple benchmark, and its applicability to realistic problems with a larger number of states and uncertainties is then demonstrated.
Application of artificial intelligence to ultrasound imaging for benign gynecological disorders: systematic review
Authors: Moro F. , Giudice M. T. , Ciancia M. , Zace D. , Baldassari G. , Vagni M. , Tran H. E. , Scambia G. , Testa A. C.
Published: January 2025

Objective

Although artificial intelligence (AI) is increasingly being applied to ultrasound imaging in gynecology, efforts to synthesize the available evidence have been inadequate. The aim of this systematic review was to summarize and evaluate the literature on the role of AI applied to ultrasound imaging in benign gynecological disorders.

Methods

Web of Science, PubMed and Scopus databases were searched from inception until August 2024. Inclusion criteria were studies applying AI to ultrasound imaging in the diagnosis and management of benign gynecological disorders. Studies retrieved from the literature search were imported into Rayyan software and quality assessment was performed using the Quality Assessment Tool for Artificial Intelligence‐Centered Diagnostic Test Accuracy Studies (QUADAS‐AI).

Results

Of the 59 studies included, 12 were on polycystic ovary syndrome (PCOS), 11 were on infertility and assisted reproductive technology, 11 were on benign ovarian pathology (i.e. ovarian cysts, ovarian torsion, premature ovarian failure), 10 were on endometrial or myometrial pathology, nine were on pelvic floor disorder and six were on endometriosis. China was the most highly represented country (22/59 (37.3%)). According to QUADAS‐AI, most studies were at high risk of bias for the subject selection domain (because the sample size, source or scanner model was not specified, data were not derived from open‐source datasets and/or imaging preprocessing was not performed) and the index test domain (AI models were not validated externally), and at low risk of bias for the reference standard domain (the reference standard classified the target condition correctly) and the workflow domain (the time between the index test and the reference standard was reasonable). Most studies (40/59) developed and internally validated AI classification models for distinguishing between normal and pathological cases (i.e. presence vs absence of PCOS, pelvic endometriosis, urinary incontinence, ovarian cyst or ovarian torsion), whereas 19/59 studies aimed to automatically segment or measure ovarian follicles, ovarian volume, endometrial thickness, uterine fibroids or pelvic floor structures.

Conclusion

The published literature on AI applied to ultrasound in benign gynecological disorders is focused mainly on creating classification models to distinguish between normal and pathological cases, and on developing models to automatically segment or measure ovarian volume or follicles. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
How Do You Ride an Elevator? Passenger In-Cabin Behavior Analysis on a Smart-Elevator Platform
Authors: Robal Tarmo , Reinsalu Uljana
Published: January 2025

Modern elevators came into wide use some 150 years ago. With the advancement of technology, the main task of elevators has remained the same—transport people and goods in between floors—yet elevators have become more sophisticated with a trend toward smart-elevators. While increasing passenger comfort and travel experience, these systems also allow to get an insight into elevator passengers’ behavior during their travels. Have you ever wondered why some people always stand in the same place, or what is your favorite spot to stand in an elevator? This chapter focuses on exploring passengers’ in-cabin behavior while they travel between floors, enabled by a smart-elevator platform. To interpret collected real passengers’ data, a general passenger location analysis model and evaluation methods are developed and several scenarios designed to validate system readiness for behavioral studies. The latter three enablers are used to analyze real elevator passengers’ data to understand how passengers behave in cabins. The results show that passengers tend to choose their favorite position inside the cabin, permitted by the situation, and smart-elevators as a platform can be efficiently used to study passengers’ behavior to enhance cabin environment.
Leuven: A Smart City Experience
Authors: Heyrman Lieve , Guily Tim , Deneckère Rébecca , Kornyshova Elena , Elali Ramona
Published: January 2025

Leuven is the eighth-largest city in Belgium with more than 100,000 inhabitants. It is a leading region in the creation of starts-ups, research centers, and applications on health and climate. Numerous organizations in the Leuven region and the city administration itself are currently cooperating in order to work out advanced ideas around Smart City technology, which is also a crucial step in Leuven’s goal to become climate neutral by 2030. For this particular goal, the organization Leuven 2030 was founded. Leuven 2030 strives for a climate-neutral future for Leuven, representing inhabitants, companies, civil society organizations, knowledge institutions, and public authorities. They do this by combining science (scientific framework), social power (bringing people together around projects), and storytelling (inspiring stories about the steps taken).
Enhancing the Visitor Experience with Immersive Technologies and Gaming: The Monserrate Use Case
Authors: Portugal Carlos , Vaz David , Dias Miguel Sales , Trocado Pedro , Prata Alcina , Abreu Fernando Brito e
Published: January 2025

Immersive technologies, such as augmented reality (AR) and virtual reality (VR), are effective technologies being implemented across diverse fields. We propose an AR/VR-based Web app to be applied in the cultural tourism field with the objective of enhancing the visitors’ experience of the Monserrate Palace, part of a UNESCO cultural landscape located in Sintra, Portugal, managed by Parques de Sintra – Monte da Lua SA.

This chapter overviews the state of the art on immersive technologies in cultural heritage sites and the visitor experience at these sites. Then, it exposes the palace’s historical and cultural significance and some of the challenges it faces in engaging its visitors. The potential applications of immersive technologies in the palace are explored, including interactive storytelling and immersive experiences that allow for a higher level of visitor engagement. Next, it addresses potential challenges and limitations of deploying the proposed solution in the palace, such as technical constraints and preservation concerns. It then concludes with a reflection on the significant potential of AR and VR in enriching the immersive experience of Monserrate Palace, offering new possibilities for engaging with cultural heritages and creating a memorable and enjoyable visit for modern audiences.
Taxonomy of the Scientific Domain of Smart Life
Authors: Deneckère Rébecca , Kornyshova Elena , Sadouki Kaoutar , Brinkkemper Sjaak
Published: January 2025

The field of Smart Life represents a large spectrum of various application domains coming from very established ones as Smart energy and Smart home to very recent ones as Smart environment, Smart airport, or Smart Earth. We observed a substantial growth in the scientific literature with over 126,000 papers containing “Smart” in their titles in 2021. Despite this huge number, we did not identify a detailed classification of these fields in the existing literature. There is still a notable gap in the classification and systematization of these fields. To address this, we developed a generic taxonomy for Smart applications by conducting a systematic mapping study focused on state-of-the-art and research agenda-oriented papers (2341 scientific publications in total).
Evolution of the Scientific Domain of Smart Life
Authors: Deneckère Rébecca , Kornyshova Elena , Brinkkemper Sjaak
Published: January 2025

Research in “Smart” domains has proliferated over recent decades, branching into various subfields including Smart energy, Smart cities, and Smart homes and, more recently, Smart farming, Smart universities, and Smart tourism. Building on a bibliographic study of 2341 literature reviews and state-of-the-art papers, this chapter addresses the research question: How have Smart applications evolved through time? We show the growth of the Smart Life scientific domain reflecting a rising interest among researchers and society and provide an analysis of the increasing diversity of the research concepts in Smart Life. Finally, we present the evolution of four key Smart domains: Smart applications for enterprises, persons, environment, and society. Therefore, this chapter illustrates the surge in publications over the past decade underscoring the expanding relevance and impact of Smart Life in contemporary technological and societal contexts.
A Review of Social, Behavioral, and Ethical Considerations for SmartLife Engineering
Authors: Murray John
Published: January 2025

Smart Life (SL) systems do not exist in a technological vacuum; they are embedded in a social ecosystem and have rich and complex interactions with their surroundings. It is important to recognize that their design and implementation will have an impact on the individuals and communities around them. This chapter examines the social, behavioral, and ethical issues to be considered in a holistic systems approach to SL engineering, to help practitioners and stakeholders to design the strategies needed for successful SL deployments. It addresses these topics from several disciplinary viewpoints and provides a comprehensive set of references for those requiring further detailed information.
Stakeholders in Smart City Standardization
Authors: Jakobs Kai
Published: January 2025

The chapter suggests a way to better integrate the expertise of societal stakeholders into the earliest possible stage of the development of technologies with significant non-technical ramifications, e.g., societal, environmental, or ethical. Based on a thorough analysis of the current situation, the chapter suggests a modified standards setting process for such technologies. Specifically, it describes how the diverse stakeholders and their different forms of knowledge may be integrated into this process and how it may be managed.
Smart-Viticulture and Deep Learning: Challenges and Recent Developments on Yield Prediction
Authors: Mohimont Lucas , Hollard Lilian , Steffenel Luiz Angelo
Published: January 2025

Smart agriculture is a trendy topic as it has a clear impact in both productivity, ecological impact, and improvement of working conditions. Smart viticulture is one of the domains that can benefit both from wireless sensor networks and mobile devices embarked in vineyard labor tools (e.g., on a straddler tractor). One important use case is related to the yield estimation, an invaluable information to drive the harvest organization, plant management, and business’s economy. Traditional methods rely on destructive sampling and manual counting, resulting in error rates sometimes greater than 30%. In this chapter, we review existing techniques for the automation of yield estimation and, focusing on deep learning methods, propose some strategies and preliminary results obtained in a production environment.
Introduction
Authors: Hollnaicher Simon
Published: January 2025

This chapter introduces the book's research question and explains its relevance. The book is concerned with the concept of feasibility and how scientific assessments in the climate context engage with it. Feasibility is a central concept in political philosophy and has been prominently featured in recent climate discourse. Integrated Assessment Models are scientific models that project various climate futures for given climate goals and thereby provide scenario evidence on the feasibility of climate goals and different mitigation strategies. The central philosophical problem of the book is introduced as the value problem in assessing feasibility. The question is how we can assess the seemingly empirical concept of feasibility with value-laden models, which inherently and deeply depend on a range of value assumptions. The book attempts to explain how the models can contribute to assessing feasibility, while at the same time critically discussing their normative basis and evaluating modeling practices in light of a principal solution to the value problem. This chapter outlines the content and argument the book makes and what it contributes to the existing literature.
The Value-Dimension of Feasibility
Authors: Hollnaicher Simon
Published: January 2025

This chapter argues that feasibility judgments are inherently value-laden and that recognizing this value dimension helps address two key conceptual challenges in the feasibility debate. It begins by introducing the widespread assumption that feasibility is a purely descriptive concept and that this notion helps separate scientific facts from values. The chapter then surveys conceptual contributions that challenge this separation and argues for a “thick” conception of feasibility, building on Wiens’ account. The proposed thick conception integrates value judgments in three ways: by excluding unacceptable means, rejecting measures with unacceptable side effects, and setting value-laden thresholds for acceptable levels of uncertainty. This value-laden understanding of feasibility addresses the first challenge of distinguishing feasibility from mere practical possibility. The chapter argues that the normative role of feasibility as ruling out proposals can be refined as demarcating options that are worthy of deliberation. This sense of ruling out is compatible with thick feasibility. Finally, it recovers the comparative sense of feasibility through related, value-laden concepts—such as options being “more challenging” or “more realistic”—thereby addressing the second challenge.
CFS/ME als ideale Fassade für das Münchhausen-by-Proxy-Syndrom? – „Auch Ausruhen kann anstrengend sein …“
Authors: Melfsen Siebke , Lucas Torsten
Published: January 2025

Vorgestellt wird die 9‑jährige Mara mit progressiver körperlicher Schwäche bei Kachexie, Licht- und Lärmempfindlichkeit, Kopfschmerzen und Konzentrationsstörungen sowie seit Monaten auf die Kernfamilie reduzierten sozialen Kontakten. Mara lebte in einem reizabgeschirmten Raum. Die Mutter hatte eine vergleichbare Symptomatik, die – wie anfangs die von Mara – als Chronic Fatigue Syndrome/Myalgic Encephalitis (CFS/ME) eingeordnet worden war.

Der akute Rückgang der Symptomatik bei Aufnahme auf unsere psychosomatische Station mit Trennung von der Mutter sowie die detaillierte (Beziehungs‑)Anamnese und Einordnung der auffälligen Interaktions- und Verhaltensmuster führten nach dem Ausschluss einer organischen Ursache zur Diagnose Münchhausen-by-Proxy-Syndrom (MbpS) und ermöglichten es, Mara erfolgreich zu behandeln.
Role of membrane porosity in passive sampling of aquatic contaminants for stable isotope analysis: enhancement of analyte accumulation rates and selectivity
Authors: Tafa Armela , Bernstein Anat , Elsner Martin , Bakkour Rani
Published: January 2025

Compound-specific isotope analysis (CSIA) is a potent method for illustrating the in situ degradation of aquatic contaminants. However, its application to surface and groundwater is hindered by low contaminant concentrations, typically in the nanogram-per-litre range, requiring the processing of large water volumes. Polar organic chemical integrative samplers (POCIS) have shown promising results when combined with CSIA, yet their extended deployment time to accumulate sufficient analyte mass remains a major limitation. In our study, we addressed this issue by increasing the pore size of the polyethersulfone membrane (PES) from 0.1 to 8

$$\upmu $$

μ

m. This resulted in significant increases in the mass accumulation rates of atrazine (3.5-fold), S-metolachlor (3.4-fold), and boscalid (3.0-fold). Importantly, the larger pore sizes did not compromise isotopic integrity, with

$$\Delta \delta ^{13}$$

Δ

δ
13

C

$$\le +0.4\pm 0.1$$

≤
+
0.4
±
0.1

‰ and

$$\Delta \delta ^{15}$$

Δ

δ
15

N

$$\le -0.6\pm 0.4$$

≤
-
0.6
±
0.4

‰, both within accepted uncertainties. Additionally, we observed an enhanced selectivity of the larger pores towards the target analytes over humic acids, whereas no significant increase in (bio)fouling potential was detected for the 8

$$\upmu $$

μ

m membrane, as demonstrated by gravimetric analysis, SEM measurements, mass accumulation rates, and isotope ratios of fouled and unfouled POCIS. Our findings show that increasing the membrane pore size from 0.1 to 8

$$\upmu $$

μ

m reduces deployment time and expedites the accumulation of analyte mass required for gas chromatography isotope ratio mass spectrometry, offering a promising method to expand CSIA for low-concentration pesticide analysis in the field.

Graphical abstract
Intracellular enhancement technique for gadoxetic acid-enhanced hepatobiliary-phase magnetic resonance imaging: evaluation of hepatic function
Authors: Fonseca Dara , Nakamura Yuko , Higaki Toru , Maeda Shogo , Nishihara Takashi , Bito Yoshitaka , Takizawa Masahiro , Kondo Shota , Higashino Ryo , Morishita Shintaro , Akiyama Yuji , Fukuma Shingo , Kawaoka Tomokazu , Tsuge Masataka , Oka Shiro , Awai Kazuo
Published: January 2025

Purpose

To investigate the utility of intracellular enhancement (ICE) technique which suppresses signals from the extracellular space for the evaluation of hepatic function on gadoxetic acid-enhanced hepatobiliary-phase (HBP) images.

Methods

We subjected 67 patients with suspected neoplastic hepatic lesions to gadoxetic acid-enhanced HBP imaging with and without ICE [i-HBP, conventional-HBP (c-HBP)]. A radiologist calculated the liver/spleen contrast (LSC) [LSC = signal intensity (SI) of liver/SI of spleen]. Receiver-operating analysis was used to evaluate the diagnostic value of the LSC on i-HBP- (i-LSC) and c-HBP images (c-LSC) to differentiate between Child-Pugh classes A and B.

Results

Of the 67 patients, 57 were in Child-Pugh class A and 10 were in class B. For their differentiation, the area under the curve value of i-LSC was higher than of c-LSC (0.81 vs. 0.68).

Conclusions

ICE technique can improve the accuracy of estimating hepatic function on HBP images.

Graphical abstract
Trends and Gaps in Prescribed Burning Research
Authors: Gordon Luke , Evans Maldwyn John , Zylstra Philip , Lindenmayer David B.
Published: January 2025

Prescribed burning is a key tool in land management globally used to reduce wildfire risks and achieve ecological, cultural and resource management objectives across both natural and human systems. Despite its widespread application, research on prescribed burning is marked by significant gaps. Subsequently, we posed the following research questions: (1) What are the key research topics that define international, peer-reviewed literature on prescribed burning? (2) What are the temporal and spatial trends of these topics? (3) What are the relationships between the national income of a given country and the trends in research topics? And, (4) What are the most salient knowledge gaps in peer-reviewed prescribed burning research, and how can they be addressed? We used structural topic modelling and geoparsing to conduct a detailed text analysis of 7878 peer-reviewed articles on prescribed burning. We revealed that research on prescribed burning is dominated by studies from high-income countries, particularly the United States. This highlights a geographical bias that may skew global understanding and application of prescribed burning practices. Our topic modelling revealed the most prevalent topics to be Fire Regimes and Landscape Biodiversity Management, whilst topics such as Air Pollution & Health, and Wildfire Risk Management gained prominence in recent years. Our analysis highlighted a disconnect between forestry-related research and broader landscape management topics. This finding emphasises the need for more interdisciplinary research, and research on the use and effects of prescribed burning in diverse ecosystems and underrepresented regions, particularly in the context of climate change.
Cost-utility analysis of ropeginterferon alfa-2b to manage low-risk patients with polycythemia vera as compared to phlebotomy only in the Austrian healthcare system
Authors: Walter Evelyn , Torelli Francesca , Barbui Tiziano
Published: January 2025

Treatment of polycythemia vera (PV) aims to maintain hematocrit on target to reduce risk of thrombotic complications, while preventing disease progression to myelofibrosis (MF) and acute myeloid leukemia (AML). This analysis evaluated cost-effectiveness of adding ropeginterferon alfa-2b (ropegIFNα) to phlebotomy in patients with low-risk PV (those younger than 60 years without prior thrombosis), compared to phlebotomy alone. We combined a 12-month decision tree with a semi-Markov cohort model comparing ropegIFNα to the standard treatment from the Austrian healthcare system perspective over 30 years. Outcomes were quality adjusted life years (QALYs), costs, and incremental cost-utility ratio (ICUR). Model inputs were obtained from the phase 2 Low-PV study, additional published literature and from Austrian-specific cost databases. One-way and probabilistic sensitivity analyses (SA) assessed the robustness of findings. RopegIFNα led to 1,43 higher QALYs and 50.960 EUR overall higher costs compared to phlebotomy alone, with an ICUR of 35.525 EUR/QALY. Thrombosis, MF, and AML costs decreased for the ropegIFNα group by 12%, 30% and 16% respectively, due to the delayed complications onset and disease progression. In the one-way SA, ropegIFNα costs and discount rates had the greatest impact on results. The probabilistic SA showed a 100% probability of cost-effectiveness at willingness-to-pay threshold aligned to the Austrian GDP per capita. RopegIFNα is a cost-effective treatment option for patients with low-risk PV. These findings suggest that early treatment with ropegIFNα could ensure optimal resource allocation by preventing costly thrombotic events and progression to MF whilst increasing patient quality of life.
Robustness of radiomics within photon-counting detector CT: impact of acquisition and reconstruction factors
Authors: Zhang Huan , Lu Tingwei , Wang Lingyun , Xing Yue , Hu Yangfan , Xu Zhihan , Lu Junjie , Yang Jiarui , Chu Jingshen , Zhang Benyan , Zhong Jingyu
Published: January 2025

Objectives

To assess the impact of acquisition and reconstruction factors on the robustness of radiomics within photon-counting detector CT (PCD-CT).

Methods

A phantom with twenty-eight texture materials was scanned with different acquisition and reconstruction factors including reposition, scan mode (standard vs high-pitch), tube voltage (120 kVp vs 140 kVp), slice thickness (1.0 mm vs 0.4 mm), radiation dose level (0.5 mGy, 1.0 mGy, 3.0 mGy, 5.0 mGy, vs 10.0 mGy), quantum iterative reconstruction level (0/4, 2/4, vs 4/4), and reconstruction kernel (Qr40, Qr44, vs Qr48). Thirteen sets of virtual monochromatic images at 70-keV were reconstructed. The regions of interest were drawn with rigid registrations. Ninety-three radiomics features were extracted from each material. The reproducibility of radiomics features was evaluated using the intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). The variability of radiomics features was assessed by coefficient of variation (CV) and quartile coefficient of dispersion (QCD).

Results

The percentage of features with ICC > 0.90 and CCC > 0.90 were high when repositioned (88.2% and 88.2%) and tube voltage was changed (87.1% and 87.1%), but none of the features with ICC > 0.90 and CCC > 0.90 when high-pitch scan and different slice thickness were used. The percentage of features with CV < 10% and QCD < 10% were high when repositioned (47.3% and 68.8%) and tube voltage was changed (64.2% and 71.0%), but that with CV < 10% and QCD < 10% were low between standard and high-pitch scans (16.1% and 26.9%) and slice thickness (19.4% and 29.0%).

Conclusions

The PCD-CT radiomics was robust to tube voltage, radiation dose, reconstruction strength level, and kernel, but brittle to high-pitch scan and slice thickness.

Key Points

Question

The stability of radiomics features against acquisition and reconstruction factors within PCD-CT should be fully determined before academic research and clinical application.

Findings

The radiomics features are robust against tube voltage, radiation dose, reconstruction strength level, and kernel within PCD-CT but brittle to high-pitch scan and slice thickness.

Clinical relevance

The high-pitch scan and slice thickness that influence voxel size should be set with careful attention within PCD-CT, to allow a higher robustness of radiomics features before the implementation of radiomics analysis in clinical routine.
Neobladder saving caesarean section in a pregnant woman with congenital bladder exstrophy
Authors: Granieri Chiara , D’Ippolito Silvia , Foresta Aniello , Gui Benedetta , Foschi Nazario , Esposito Giovanni , Scambia Giovanni
Published: January 2025

Purpose

To propose an obstetric management model for patients with congenital bladder exstrophy (BE) and multiple previous surgeries, recognizing the unique anatomical variations of each patient and emphasizing the importance of personalized treatment approaches.

Methods

We present the obstetric management and delivery of a 32-year-old pregnant woman with congenital BE, focusing on antenatal anatomical assessment, accurate delivery planning and key surgical steps during an elective caesarean section. Additionally, we conduct a comprehensive review of the current literature to enhance understanding of the reproductive implications associated with this exceptionally rare condition.

Results

Following urological magnetic resonance imaging and intraoperative ultrasound, a successful neobladder-saving caesarean section was performed at 37 weeks, resulting in the delivery of a healthy infant with no maternal complications.

Conclusion

Obstetric management in women with congenital BE presents unique challenges due to its significant impact on urinary and reproductive functions. Careful delivery planning and antenatal anatomical assessment are crucial for optimizing both maternal and fetal outcomes. A personalized, multidisciplinary approach can help minimize potential complications.
Iron-sulfur clusters: the road to room temperature
Authors: Skeel Brighton A. , Suess Daniel L. M.
Published: January 2025

Iron-sulfur proteins perform a wide variety of reactions central to the metabolisms of all living organisms. Foundational to their reaction chemistry are the rich electronic structures of their constituent Fe-S clusters, which differ in important ways from the active sites of mononuclear Fe enzymes. In this perspective, we summarize the essential electronic structure features that make Fe-S clusters unique, and point to the need for studies aimed at understanding the electronic basis for their reactivity under physiological conditions. Specifically, at ambient temperature, both the ground state and a large number of excited states are thermally populated, and thus a complete understanding of Fe-S cluster reactivity must take into account the properties, energies, and reactivity patterns of these excited states. We highlight prior research toward characterizing the low-energy excited states of Fe-S clusters that has established what is now a consensus model of these excited state manifolds and the bonding interactions that give rise to them. In particular, we discuss the low-energy alternate spin states and valence electron configurations that occur in Fe-S clusters of varying nuclearities, and finally suggest that there may be unrecognized functional roles for these states.

Graphical abstract
Sparsity and proximity transference in integer programming
Authors: Aliev Iskander , Celaya Marcel , Henk Martin
Published: January 2025

We obtain new transference bounds that connect the additive integrality gap and sparsity of solutions for integer linear programs. Specifically, we consider the integer programs

$$\min \{{\varvec{c}}\cdot {\varvec{x}}: {\varvec{x}}\in P\cap \mathbb {Z}^n\}$$

min
{

c

·

x

:

x

∈
P
∩

Z

n

}

, where

$$P=\{{\varvec{x}}\in \mathbb {R}^n: \varvec{A}{\varvec{x}}={\varvec{b}}, {\varvec{x}}\ge {\varvec{0}}\}$$

P
=
{

x

∈

R

n

:

A

x

=

b

,

x

≥

0

}

is a polyhedron in the standard form determined by an integer

$$m\times n$$

m
×
n

matrix

$$\varvec{A}$$

A

and an integer vector

$${\varvec{b}}$$

b

. The main result of the paper gives an upper bound for the integrality gap that drops exponentially in the size of the support of the optimal solutions corresponding to the vertices of the integer hull of P. Additionally, we obtain a new proximity estimate for the

$$\ell _2$$

ℓ
2

-distance from a vertex of P to its nearest integer point in P. We also strengthen previously known bounds for the integer Carathéodory rank, a key sparsity characteristic which estimates the minimum size of the support of an integer point in P in terms of the matrix

$$\varvec{A}$$

A

. The proofs make use of the results from the geometry of numbers and convex geometry.
Reconstruction of paleo-environments by two aquatic plants: eDNA analysis in lake sediment cores
Authors: Yamagishi Satoshi , Nakamura Yasuhide , Seto Koji , Ando Takuto , Katsuki Kota , Takahara Teruhiko
Published: January 2025

Environmental DNA (eDNA) analysis using lake sediment cores can be used to assess populations, dynamics, and historical changes in ecosystems and environments, based on the DNA composition of micro-organisms and plants. While this method has shed light on past environments, a more detailed understanding of past ecosystems requires targeted sediment core eDNA analysis focusing on specific species. Here, we focused on the salt-tolerant aquatic plants Stuckenia pectinata and Potamogeton pusillus, which are abundant in Lake Shinji and serves as a model system for Japanese brackish lakes, conducted species-specific DNA analysis on nine sediment cores 64–379 cm collected from water depth of 4.6–5.1 m. Additionally, we performed CNS elemental analysis on these sediment cores to reconstruct the paleoenvironment of Lake Shinji. Our findings revealed the presence of S. pectinata and P. pusillus DNA from approximately 2000 years ago, and a clear relationship was observed between DNA detection and historical salinity levels in the lake. Stuckenia pectinata tended to have a higher DNA detection frequency than that of P. pusillus, possibly related to the different salinity tolerance levels between the two species. Based on the relationship between the horizontal–vertical distributions of sedimentary eDNA of aquatic plants and their salinity tolerances, the paleoenvironment associated with salinity in Lake Shinji could also be reconstructed. Therefore, it is possible to elucidate the long-term dynamics of these plants associated with past environmental change as water pollution, using the time-series data on eDNA of macro-organisms, such as aquatic plants, in the sediment cores.
Predictors of higher pain in possible open globe injury emergency medical services activations
Authors: Choudhry Hassaam S. , Mothy David , Reddy Aneesh , Patel Aman M. , Peterson Skyler , Fisher Benjamin , Dastjerdi Mohammad H.
Published: January 2025

Purpose

To determine predictors of high pain in open globe injury (OGI) cases treated and transported by Emergency Medical Services.

Methods

The National Emergency Medical Services Information System database was queried for activations of OGI between 2017 and 2021. Demographic, location, medication, and date and time information was collected. Cases were divided based on the intensity of maximum pain reported (low pain: below 5/10, high pain: above 5/10). Logistic regression was used to identify significant predictors of high maximum pain.

Results

Of 53,589 cases of OGI, 20,766 reported high levels of pain. Females were more likely to report high pain than males (OR 1.24, CI 1.195–1.285). All age groups between 16 and 75 years old were more likely to report high pain than patients below 15, while all age groups above 75 were less likely. American Indians/Alaska Natives, Black, and Hispanic Americans were all more likely to report high pain than White Americans (American Indian, OR 1.249, CI 1.067–1.461; Black, OR 1.332, CI 1.277–1.390; Hispanic, OR 1.133, CI 1.064–1.207). OGI cases in the Midwest and South regions were less likely to report high pain than those in the West (Midwest, OR 0.868, CI 0.807–0.933; South, OR 0.800, CI 0.748–0.855). Compared to low pain patients, a greater percentage of high pain patients received opioid analgesia (10.04% vs. 0.44%).

Conclusions

Demographic factors and location may contribute to higher pain in OGI patients. This information may prove useful in the management of OGI and may warrant further investigation into the nature of open globe trauma.Kindly check and confirm the inserted city is correct for affiliation 3.Correct
How Pannah Gahs (shelter homes) are helping the homeless people in Lahore, Pakistan
Authors: Hameed Rizwan , Aslam Atif Bilal , Khan M Sana Ullah
Published: January 2025

Urban homelessness is a problem faced by both developed and developing countries due to various causes requiring contextualized responses. Governments have used temporary housing like shelter homes to combat homelessness, but providing adequate facilities and ensuring their use by the homeless remain significant challenges. This research article investigates the efficacy of shelter homes (locally known as Pannah Gahs) in Lahore. The objective is to explore the migration purposes of occupants contributing to urban homelessness, evaluate their satisfaction with shelter home facilities and understand their future migration intentions. Unstructured key informant interviews with Pannah Gah officials and semi-structured interviews of selected homeless people staying in the Panah Gahs were conducted. The finding reveals that, unlike in other developing countries, the government’s compassionate approach to treating homeless people with dignity, the security measures in place, and the staff training at Pannah Gahs have encouraged the homeless to use these facilities more frequently. However, most seemingly urban homeless people are economic migrants with homes elsewhere thus exhibiting a multilocality character. Employed homeless individuals often seek their own housing, while job-seeking homeless individuals tend to stay in their current situations due to financial constraints. The study highlights policy implications, advocating for a nuanced definition of homelessness considering economic migrants and spatially split households. It emphasizes the need for government support, such as affordable housing, and stresses that successful shelter home programs require government commitment, stakeholder collaboration, and comprehensive support services to restore the dignity and self-respect of the homeless.
Pregnant Turkish Muslim Women’s Perspectives and Experiences on Religion and Spirituality during Pregnancy
Authors: Yilmaz Figen Alp , Uzunçakmak Tuğba
Published: January 2025

The aim of this study is to determine the views and experiences of pregnant Muslim women about religion and spirituality during pregnancy. A descriptive, phenomenological design was used, and the study was conducted with 16 pregnant Muslim women living in Türkiye. The thematic analysis method was used. The main themes created in the study were pregnant women’s motivation to have children, changes during pregnancy, faith and spirituality during pregnancy, support for the moment of birth, and motherhood. Pregnant women also need moral support in addition to routine practices and follow-ups during this difficult and distressing process. Religious practices provide psychological comfort for pregnant women in coping with the symptoms they experience and having a healthy birth and a healthy baby. Spiritual care should be given importance in raising health professionals and spirituality-based topics should be included in the education process.
Developing robust incomplete Cholesky factorizations in half precision arithmetic
Authors: Scott Jennifer , Tůma Miroslav
Published: January 2025

Incomplete factorizations have long been popular general-purpose algebraic preconditioners for solving large sparse linear systems of equations. Guaranteeing the factorization is breakdown free while computing a high quality preconditioner is challenging. A resurgence of interest in using low precision arithmetic makes the search for robustness more important and more challenging. In this paper, we focus on ill-conditioned symmetric positive definite problems and explore a number of approaches for preventing and handling breakdowns: prescaling of the system matrix, a look-ahead strategy to anticipate breakdown as early as possible, the use of global shifts, and a modification of an idea developed in the field of numerical optimization for the complete Cholesky factorization of dense matrices. Our numerical simulations target highly ill-conditioned sparse linear systems with the goal of computing the factors in half precision arithmetic and then achieving double precision accuracy using mixed precision refinement. We also consider the often overlooked issue of growth in the sizes of entries in the factors that can occur when using any precision and can render the computed factors ineffective as preconditioners.
Resilience as a professional competence: a new way towards healthy teachers?
Authors: Baatz Judith , Wirzberger Maria
Published: January 2025

Considering teachers’ poor state of health, we conducted a literature review to investigate, whether resilience, as a professional competence, has a health-promoting effect on teachers. Re-directing the seemingly inevitable trajectory from stress to illness towards health, the effects should be reflected in the improvement of teachers’ negative strain ratios. Hence, our review investigated the effect of resilience and specific resilience resources regarding teachers’ risk of burnout, stress perception and coping, general well-being, attrition rates, and effectiveness. Our results indicate that resilience supports teachers’ health, by consistently showing a positive impact on the investigated aspects. Furthermore, our catalog of identified resilience resources supports the concept of teacher-specific resilience. As effective programs for promoting teachers’ resilience are lacking, this informs new intervention approaches to promote teachers’ health.
A community detection-based parallel algorithm for quantum circuit simulation using tensor networks
Authors: Pastor Alfred M. , Badia Jose M. , Castillo Maribel
Published: January 2025

Quantum computing holds significant promise for solving complex problems, but simulating quantum circuits on classical computers remains essential due to the current limitations of quantum hardware. Efficient simulation is crucial for the development and validation of quantum algorithms and quantum computers. This paper explores and compares various strategies to leverage different levels of parallelism to accelerate the contraction of tensor networks representing large quantum circuits. We propose a new parallel multistage algorithm based on communities. The original tensor network is partitioned into several communities, which are then contracted in parallel. The pairs of tensors of the resulting network can be contracted in parallel using a GPU. We use the Girvan–Newman algorithm to obtain the communities and the contraction plans. We compare the new algorithm with two other parallelisation strategies: one based on contracting all the pairs of tensors in the GPU and another one that uses slicing to cut some indexes of the tensor network and then MPI processes to contract the resulting slices in parallel. The new parallel algorithm gets the best results with different well-known quantum circuits with a high degree of entanglement, including random quantum circuits. In conclusion, the results show that the main factor that limits the simulation is the space cost. However, the parallel multistage algorithm manages to reduce the cost of sequential simulation for circuits with a high number of qubits and allows simulating larger circuits.
KubePipe: a container-based high-level parallelization tool for scalable machine learning pipelines
Authors: Suárez Daniel , Almeida Francisco , Blanco Vicente , Toledo Pedro
Published: January 2025

As the complexity and scale of machine learning applications continue to grow, the need for efficient training methodologies becomes increasingly critical. Traditional training processes can be time-intensive, often limiting rapid development and deployment. In response to this challenge, we present KubePipe, a high-level tool that abstracts parallelism and containerization from the user, allowing non-expert users to leverage advanced parallel architectures without requiring deep knowledge of parallel computing or container orchestration. KubePipe enables the concurrent execution of multiple machine learning workflows within a Kubernetes cluster, optimizing computational resources and significantly reducing training times. By leveraging containerized environments, KubePipe ensures a high degree of modularity, scalability, and portability, making it adaptable to various machine learning frameworks and tasks. Our experimental results demonstrate substantial performance improvements when using KubePipe compared to conventional pipeline implementations. This paper explores the architecture and functionality of KubePipe, providing insights into its integration with existing machine learning systems and highlighting its potential to streamline the training process in high-performance computing environments.