bluuebunny/crossref_metadata_2025 huggingface dataset:
Constructive (in)visibility and the trafficking industrial complex: Leveraging borders for exploitation
Authors: Lumley‐Sapanski Audrey , Schwarz Katarina
Published: December 2024

This paper explores the heterogeneity of migrant visibility across space and time, analysing where and how Eritrean forced migrants travelling along the Central Mediterranean Route are made visible or disappeared at various scales and how their (in)visibility is mobilised by other actors for profit. We point to three heterogeneous forms of (in)visibility—hypervisibility, invisibilisation and selective visibility—that frame, justify and help perpetuate a system of migrant exploitation, extortion and human trafficking. Drawing from three tranches of interviews with human trafficking survivors and migrants from Eritrea, government officials, suprastate actors, CSO employees and other stakeholders in Sudan, Libya and Ethiopia conducted between March 2021 and April 2022, we explore the dynamic interplay between representation and policy in the experiences of vulnerable migrants. We develop the term constructive (in)visibility to describe the ways in which migration governance visibilises Eritrean migrants in aggregate as threats, commodities and victims, while simultaneously invisibilising them as individuals and rights bearers. Policy responses to the hypervisibility of the ‘crime’ and ‘magnitude’ of irregular migration leave migrants vulnerable to a chain of predatory actors who see and know irregular migratory routes. Selectively deployed and leveraged borders allow profiteers to benefit from the restrictions on mobility and limitations on protections of irregular migrants, while international investments in restrictionist, externalised migration policies finance actors involved or complicit in migrant smuggling and human trafficking. The mutually reinforcing cycle of constructive (in)visibilisation and repressive policy thus facilitates the establishment of what we define as a trafficking industrial complex—a necrocapitalist market in migrants—that profits from their abandonment, exposing them to abduction, extortion and death.
Improving the Discharge Characteristics of Nonaqueous Lithium-Oxygen Batteries by Constructing Microchannels
Authors: Tang Jiaxing , Gao Yanan , Zhou Wenning , Dou Ruifeng , Fang Juan , Liu Xunliang
Published: December 2024

Non-aqueous lithium-oxygen batteries (NALOBs) are a brand-new variety of recyclable batteries. Its theoretical energy density is very high, and it has enormous potential for use in a variety of industries. However, its cycle performance and discharge capacity still fall short of the scope of its application. Its low performance is mostly a result of the oxygen (O2) transport issues brought on by the cathode microstructure and insoluble discharge products. In response to the challenge of diffusing O2 to the cathode separator side, this work presents a new air cathode structure with microchannels. Experimental testing reveals that electrodes with microchannel structures can enhance specific capacity by around 16.9%, showing the feasibility of this method in enhancing electrode discharge. The material diffusion and discharge processes are simulated using the mesoscale multiphysical field coupling mathematical model using the lattice Boltzmann method after geometric reconstruction of the cathode. According to the study's findings, the construction of microchannels reduces the cathode's diffusion resistance while increasing its O2 concentration during the discharge process. In addition, the study also discusses the influence of the radius, morphology, number, and distribution of microchannels in the electrode on the O2 transport performance in different regions of the electrode.
TNIK: A redox sensor in endothelial cell permeability
Authors: Joachim Justin , Maselli Davide , Petsolari Emmanouela , Aman Jurjan , Swiatlowska Pamela , Killock David , Chaudhry Hiba , Zarban Ali A. , Sarker Mosharraf , Fraser Paul , Cleary Simon J. , Amison Richard , Cuthbert Isabelle , Yang Yue , Meier Magda , Fraternali Franca , Brain Susan D. , Shah Ajay M. , Ivetic Aleksandar
Published: December 2024

Dysregulation of endothelial barrier integrity can lead to vascular leak and potentially fatal oedema. TNF-α controls endothelial permeability during inflammation and requires the actin organizing Ezrin-Radixin-Moesin (ERM) proteins. We identified TRAF2 and NCK-interacting kinase (TNIK) as a kinase directly phosphorylating and activating ERM, specifically at the plasma membrane of primary human endothelial cells. TNIK mediates TNF-α–dependent cellular stiffness and paracellular gap formation in vitro and is essential in driving inflammatory oedema formation in vivo. Unlike its homologs, TNIK activity is negatively and reversibly regulated by H
2
O
2
-mediated oxidation of C202 within the kinase domain. TNIK oxidation results in intermolecular disulfide bond formation and loss of kinase activity. Pharmacologic inhibition of endogenous reactive oxygen species production in endothelial cells elevated TNIK-dependent ERM phosphorylation, endothelial cell contraction, and cell rounding. Together, we highlight an interplay between TNIK, ERM phosphorylation, and redox signalling in regulating TNF-induced endothelial cell permeability.
Airway
Corynebacterium
interfere with
Streptococcus pneumoniae
and
Staphylococcus aureus
infection and express secreted factors selectively targeting each pathogen
Authors: Tamkin Emily , Lorenz Brian P. , McCarty Arianna , Fulte Sam , Eisenmesser Elan , Horswill Alexander R. , Clark Sarah E.
Published: December 2024

The composition of the respiratory tract microbiome is a notable predictor of infection-related morbidities and mortalities among both adults and children. Species of
Corynebacterium,
which are largely present as commensals in the upper airway and other body sites, are associated with lower colonization rates of opportunistic bacterial pathogens such as
Streptococcus pneumoniae
and
Staphylococcus aureus
. In this study,
Corynebacterium
-mediated protective effects against
S. pneumoniae
and
S. aureus
were directly compared using
in vivo
and
in vitro
models. Pre-exposure to
Corynebacterium pseudodiphtheriticum
reduced the ability of
S. aureus
and
S. pneumoniae
to infect the lungs of mice, indicating a broadly protective effect. Adherence of both pathogens to human respiratory tract epithelial cells was significantly impaired following pre-exposure to C.
pseudodiphtheriticum
or
Corynebacterium accolens
, and this effect was dependent on live
Corynebacterium
colonizing the epithelial cells. However,
Corynebacterium
-secreted factors had distinct effects on each pathogen.
Corynebacterium
lipase activity was bactericidal against
S. pneumoniae
, but not
S. aureus
. Instead, the hemolytic activity of pore-forming toxins produced by
S. aureus
was directly blocked by a novel
Corynebacterium
-secreted factor with protease activity. Taken together, these results suggest diverse mechanisms by which
Corynebacterium
contribute to the protective effect of the airway microbiome against opportunistic bacterial pathogens.
Comparative performances of the Qvella FAST system and conventional methods for rapid identification and antibiotic susceptibility testing on monomicrobial positive blood cultures
Authors: Penven Malo , Louazon Manon , Freret Charlotte , Sauron Alexandra , Pilard Meghane , Creignou Elisa , Gardan Ophélie , Haumont Maryne , Zouari Asma , Lorre Stéphane , Cattoir Vincent
Published: December 2024

Rapid and accurate diagnosis of sepsis is of paramount importance to reduce associated morbidity and mortality. The Qvella FAST System is a new instrument that concentrates and purifies bacteria from positive-flagged blood culture bottles (PFBCBs) to produce a “liquid” colony comparable to a subcultured colony in less than 40 min for rapid ID and calibrated antibiotic susceptibility testing (AST). In this study, we evaluated performances of the FAST System workflow and our rapid routine manual workflow (bacterial pellet obtained after lysis, cleaning, washing, and centrifugation for ID; AST by disc diffusion by direct inoculation after dilution) by comparison to the reference method based on 24-h bacterial subcultures. Two panels of PFBCBs were studied: panel A (including 107 prospective BCs from septic patients, October–November 2022) and panel B (including 102 BCs spiked with difficult-to-identify bacteria [mostly streptococci] and multidrug-resistant isolates), resulting in a total of 209 evaluable samples. The FAST System provided a correct ID to the species level in 178/209 (85.2%) of cases. For AST, the categorical agreement (CA) of the FAST System was 99.4%, with rates of very major (VME), major (ME), and minor (mE) errors of 0.59%, 0.20%, and 0.26%, respectively. Our rapid routine workflow based on manual methods show similar results for ID (86.2%) and AST (CA, 99.6%; VME, 0.50%; ME, 0.16%; mE, 0.13%). In conclusion, the Qvella FAST system, a promising tool that can reduce diagnostic time by approximately 1 day, shows excellent performances for rapid ID and AST.
Erratum to: Condensates of the Magnetoexcitations in Quantum Hall Dielectrics
Authors: Gorbunov A. V. , Larionov A. V. , Kulik L. V. , Timofeev V. B.
Published: December 2024

An Erratum to this paper has been published: https://doi.org/10.1134/S1062873824110029
Erratum to: The Polarization Jet/SAID and Plasma Irregularities of Different Scales
Authors: Sinevich A. A. , Chernyshov A. A. , Chugunin D. V. , Miloch W. J. , Mogilevsky M. M.
Published: December 2024

An Erratum to this paper has been published: https://doi.org/10.1134/S1062873824110030
Age against the machine—susceptibility of large language models to cognitive impairment: cross sectional analysis
Authors: Dayan Roy , Uliel Benjamin , Koplewitz Gal
Published: December 2024

Objective

To evaluate the cognitive abilities of the leading large language models and identify their susceptibility to cognitive impairment, using the Montreal Cognitive Assessment (MoCA) and additional tests.

Design

Cross sectional analysis.

Setting

Online interaction with large language models via text based prompts.

Participants

Publicly available large language models, or “chatbots”: ChatGPT versions 4 and 4o (developed by OpenAI), Claude 3.5 “Sonnet” (developed by Anthropic), and Gemini versions 1 and 1.5 (developed by Alphabet).

Assessments

The MoCA test (version 8.1) was administered to the leading large language models with instructions identical to those given to human patients. Scoring followed official guidelines and was evaluated by a practising neurologist. Additional assessments included the Navon figure, cookie theft picture, Poppelreuter figure, and Stroop test.

Main outcome measures

MoCA scores, performance in visuospatial/executive tasks, and Stroop test results.

Results

ChatGPT 4o achieved the highest score on the MoCA test (26/30), followed by ChatGPT 4 and Claude (25/30), with Gemini 1.0 scoring lowest (16/30). All large language models showed poor performance in visuospatial/executive tasks. Gemini models failed at the delayed recall task. Only ChatGPT 4o succeeded in the incongruent stage of the Stroop test.

Conclusions

With the exception of ChatGPT 4o, almost all large language models subjected to the MoCA test showed signs of mild cognitive impairment. Moreover, as in humans, age is a key determinant of cognitive decline: “older” chatbots, like older patients, tend to perform worse on the MoCA test. These findings challenge the assumption that artificial intelligence will soon replace human doctors, as the cognitive impairment evident in leading chatbots may affect their reliability in medical diagnostics and undermine patients’ confidence.
On the role of soft and non-perturbative gluons in collinear parton densities and parton shower event generators
Authors: Mendizabal M. , Guzman F. , Jung H. , Taheri Monfared S.
Published: December 2024

The Parton Branching method offers a Monte Carlo solution to the DGLAP evolution equations by incorporating Sudakov form factors. In this approach, the Sudakov form factor can be divided into perturbative and non-perturbative components, with the non-perturbative part being analytically calculable under specific conditions. We first examine forward evolution and demonstrate that including soft and non-perturbative gluons (through the non-perturbative Sudakov form factor) is essential for the proper cancellation of divergent terms in parton density evolution. This non-perturbative component is also important for Transverse Momentum Dependent (TMD) parton distributions, and within the Parton Branching framework, it is constrained by fits to inclusive collinear parton densities. Additionally, we explore the impact of this non-perturbative Sudakov form factor on backward parton evolution and its effects on parton and hadron spectra originating from initial state showers. Our results show that soft and non-perturbative gluons significantly influence inclusive distributions, such as Drell–Yan transverse momentum spectra. However, we found that soft and non-perturbative gluons have a minimal impact on final state hadron spectra and jets.
Black hole information, replica wormholes and macroscopic entanglement
Authors: Calmet Xavier , Hsu Stephen D. H.
Published: December 2024

In this invited review, we discuss the evaporation of a black hole, with emphasis on the resulting macroscopically distinct patterns of Hawking radiation. The density matrix of this radiation can approach a pure final state in the form of a highly entangled macroscopic superposition state. We note that this exact property is exhibited in replica wormhole calculations, and also in quantum hair effects on Hawking radiation amplitudes. Finally, we revisit the information paradox (Mathur’s theorem and firewalls), showing that it can be resolved by macroscopic entanglement.
Relativistic configuration–interaction density functional theory
Authors: Wang Y. K. , Meng J.
Published: December 2024

This paper is about the relativistic configuration–interaction density functional theory and is dedicated to the memory of Thomas T.S. Kuo who has made great contributions to the field of nuclear physics. The relativistic configuration–interaction density functional theory is a novel nuclear many-body method that combines the advantages of the configuration–interaction shell model and the relativistic density functional theory. In this paper, we briefly review its basic concepts and recent applications on nuclear spectroscopic properties, chiral rotation, two-neutrino double-[Formula: see text] decay, and neutrinoless double-[Formula: see text] decay, as well as some perspectives on its future development.
Robust Enhanced Ridge-Type Estimation for the Poisson Regression Models: Application to English League Football Data
Authors: Lukman Adewale F. , Owolabi Abiola T. , Akanni Olukunmi O. , Kporxah Charles , Farghali Rasha
Published: December 2024

This study delves into the intricacies of addressing multicollinearity and outliers in Poisson regression modeling. Our examination encompasses a comprehensive survey of well-established methodologies, such as the ridge estimator and MT-estimator, and recent innovations like the enhanced ridge-type estimator. These approaches bolstered the robust estimation of the Poisson regression modeling with the development of a robust method. Through a series of numerical studies, including simulations and a meticulous analysis of the English League Football data, we empirically validate the efficacy of these methods. This research contributes to the evolving toolkit for effectively handling count data in the dynamic field of statistics.
UNEMPLOYMENT DYNAMICS USING MULTI-ORDER FRACTIONAL MATHEMATICAL MODEL: A CASE STUDY OF NORTHERN STATES OF INDIA
Authors: RATHEE SAVITA , NARWAL YOGEETA
Published: December 2024

The continuous increase in unemployment rates and their significant economic impact necessitate the rapid updating and modification of present models and policies implemented by governmental entities. To successfully handle the timely transmission of employment within the workforce, many contemporary models still need the incorporation of an individual’s job history. Consequently, in order to study the unemployment problem, this research presents a multi-order fractional nonlinear mathematical model that takes into account the Caputo fractional order derivative and three important variables: the number of skilled unemployed individuals, the number of employed individuals, and the number of open positions. The existence and uniqueness of the proposed model’s solution are demonstrated by using generalization of Picard fixed point theorem. The solution of the proposed model is bounded and non-negative. The reproduction number has been analyzed to determine the factors that would help create new job vacancies. The multi-order model utilizes real data to make predictions regarding the unemployed as well as the employed population for the Northern states of India (J&K, HP, Punjab, Haryana) with an average absolute error less than 21% and 3%, respectively. When compared to the actual data, the fractional order model better captures the characteristics of the unemployed population than the integer order model. The fractional-order model exhibits lower RMSE, MAE and MAPE values and higher correlation coefficient (r) value.
STRONG TIES BETWEEN ACADEMIC AND CORPORATE RESEARCHERS: FOCUS ON TRIGGERS FOR TIE FORMATION
Authors: MURAKMI YUKIKO
Published: December 2024

This study reveals that the strength of ties among academic and corporate researchers who are subject to institutional distance depends on the triggers for tie formation through trust. As strong ties are suitable for the exchange of complex knowledge, they are expected to contribute to knowledge transfer and subsequent innovative knowledge creation. With data from 508 researchers in Japan, this study reveals that the most common trigger is meeting at academic conferences, but ties formed through this trigger are weak. In contrast, ties formed during school days or past work are long-lasting strong ties, and introductions by peer researchers form strong ties from the short-term perspective. Interestingly, ties formed through introductions by industry–academia intermediary organisations are found to be strong in the short term but weak in the long term. Based on these results, this study suggests management and policy that contribute to the formation of strong ties.
WHAT DRIVES CROWDFUNDING SUCCESS? AN EXPLORATION OF KEY INFLUENCING FACTORS
Authors: KHADHRAOUI FERIEL , AJINA AYMEN
Published: December 2024

This study investigates how project-specific factors, the project creator, and campaign signals influence crowdfunding success in France. Analysing 424 projects from the KissKissBankBank platform, the research employs Generalised Linear Models to identify significant success factors. The findings reveal that signals such as publications, geographical location, project category, the creator’s past experience, the number of backers, and the funds raised positively affect campaign success. Contrary to our research hypotheses, signals related to factors such as video, the length of the project description, fundraising duration, and goal amount negatively impact success. Additionally, signals related to factors such as comments, readability of the project description, facial trust, and gender were found to be insignificant. This study provides valuable insights for young entrepreneurs, helping them identify crucial signals for crafting effective crowdfunding strategies, thereby enhancing the likelihood of their campaign success. It also serves as a resource for potential backers, enabling them to make informed investment choices before committing to crowdfunding projects.
Performance analysis of dates and acacia hybrid filler reinforced natural polymer composite
Authors: Vengatesh Maharajan Prasanna , Stalin Balasubramaniam , Nagaprasad Nagaraj , Sethu Suresh , Krishnaraj Ramaswamy , Raj Vijilius Helena , Somaiah A. , Gupta Manish
Published: December 2024

In recent years, the shift toward renewable materials has been driven by the environmental and economic implications of synthetic alternatives. Bio-filler reinforced polymer composites, particularly our Date seed and Acacia filler reinforced vinyl ester (DSF/AF-VE), provide multifaceted advantages like ecological sustainability, cost-effectiveness, biocompatibility, reduced carbon footprint, and enhanced processability for diverse applications, including automotive components, biodegradable packaging, and lightweight construction materials. This study explores using Date seed and Acacia fillers, known for their sustainability, recyclability, and bio-degradability, in polymer composites. By incorporating these fillers with vinyl ester, we aimed to enhance properties like mechanical strength, thermal stability, and wear resistance. A standard compression molding process was chosen for this experiment due to its proven effectiveness in achieving uniform filler distribution, reproducibility of composite properties, and its suitability for large-scale industrial applications. DSF/AF-VE composites were produced with filler loadings ranging from 10% to 40%, maintaining a 50% filler/filler ratio. Our findings indicate that an optimal filler proportion significantly enhances the structural properties of the composite. A filler concentration of 15w% yielded the best tensile and flexural strength, while 20w% was optimal for impact strength. The DSF/AF-VE hybrid filler showed considerable improvements in tensile, flexural, and impact strength compared to the clear matrix, with increases of 1.53 times, 1.48 times, and 1.93 times, respectively. This study underscores the potential of Date seed and Acacia fillers in enhancing the mechanical properties of natural polymer composites, suggesting their suitability for low-load applications, such as switchboards, panels, wheel arches, and air spoilers.
Magnetic Tape Storage Technology
Authors: Lantz Mark A. , Furrer Simeon , Petermann Martin , Rothuizen Hugo , Brach Stella , Kronig Luzius , Iliadis Ilias , Weiss Beat , Childers Ed R. , Pease David
Published: December 2024

Magnetic tape provides a cost-effective way to retain the exponentially increasing volumes of data being created in recent years. The low cost per terabyte combined with tape’s low energy consumption make it an appealing option for storing infrequently accessed data and has resulted in a resurgence in use of the technology. Magnetic tape as a digital data storage technology was first commercialized in the early 1950’s and has evolved continuously since then. Despite its long history, tape has significant potential for continued capacity and data rate scaling. This article strives to provide an overview of linear magnetic tape technology, usage, history, and future outlook. After a short introduction, the article delves into the details of how modern tape drives and media operate, including the basic mechanism and physics of magnetic recording, current tape media technology, state-of-the-art tape head technology, tape layout and encoding, data retrieval, timing-based servo and mechatronics of a tape drive, and the capabilities of current drives. This is followed by a discussion of tape libraries, an overview of tape library performance modeling research, operating system-level and application-level tape support, tape use cases, and the future scaling potential and outlook of tape. The article concludes with a history of tape hardware, media, usage and software.
Neuro-Symbolic Embedding for Short and Effective Feature Selection via Autoregressive Generation
Authors: Gong Nanxu , Ying Wangyang , Wang Dongjie , Fu Yanjie
Published: December 2024

Feature selection aims to identify the optimal feature subset for enhancing downstream models. Effective feature selection can remove redundant features, save computational resources, accelerate the model learning process, and improve the model overall performance. However, existing works are often time-intensive to identify the effective feature subset within high-dimensional feature spaces. Meanwhile, these methods mainly utilize a single downstream task performance as the selection criterion, leading to the selected subsets that are not only redundant but also lack generalizability. To bridge these gaps, we reformulate feature selection through a neuro-symbolic lens and introduce a novel generative framework aimed at identifying short and effective feature subsets. More specifically, we found that feature ID tokens of the selected subset can be formulated as symbols to reflect the intricate correlations among features. Thus, in this framework, we first create a data collector to automatically collect numerous feature selection samples consisting of feature ID tokens, model performance, and the measurement of feature subset redundancy. Building on the collected data, an encoder-decoder-evaluator learning paradigm is developed to preserve the intelligence of feature selection into a continuous embedding space for efficient search. Within the learned embedding space, we leverage a multi-gradient search algorithm to find more robust and generalized embeddings with the objective of improving model performance and reducing feature subset redundancy. These embeddings are then utilized to reconstruct the feature ID tokens for executing the final feature selection. Ultimately, comprehensive experiments and case studies are conducted to validate the effectiveness of the proposed framework. The associated data and code are publicly available (
https://github.com/NanxuGong/feature-selection-via-autoregreesive-generation
).
Effect of Sugarcane Bagasse Ash and Lime on Physico‐Mechanical Properties of Clayey Soil
Authors: Vengala Jagadish , Dharek Manish S. , Pramod K. , Thejaswi Poornachandra , Poudel Arjun
Published: December 2024

Soil stabilization is critical in construction, impacting the stability and longevity of infrastructure. Traditional materials such as cement, lime and fly ash have long been used for this purpose. Previous research has demonstrated the effectiveness of cement and lime for stabilizing clayey soils. This study builds on that foundation by investigating the innovative use of sugarcane bagasse ash (BA), an agricultural by‐product, as a sustainable alternative for soil improvement. BA and lime were added to clayey soil in varying proportions (0%, 4%, 8% and 12% by dry weight) to assess their impact. Geotechnical tests, including Proctor compaction, unconfined compressive strength (UCS) and California Bearing Ratio (CBR) tests, were performed on both unstabilized and stabilized soil samples, with each test repeated three times for accuracy. The results showed that adding BA and varying lime contents significantly improved the soil’s maximum dry density (MDD) and UCS, with specific mixtures yielding peak values. The UCS of the stabilized soil increased by 300% to 400% compared to unstabilized soil, while CBR values improved by 61.32% in soaked conditions and 50% in unsoaked conditions. These enhancements suggest that BA and lime mixtures can effectively improve the performance of clayey soils in construction, potentially reducing dependence on conventional materials. The chemical interaction between lime and BA likely contributes to this improvement through pozzolanic reactions, forming cementitious compounds that enhance soil strength and stability. Of all the combinations, the combination of 8% BA and 12% lime provided the greatest improvements in MDD, optimum moisture content (OMC), CBR and UCS. This research not only addresses environmental concerns regarding waste disposal but also aims to optimize soil properties, contributing to safer, more durable infrastructure while promoting sustainability.
Energy Detector–Based Spectrum Sensing in Cognitive Radios Over α−κ−F Fading Channel
Authors: Kumar Rahul , M. Jagadeesh Chandra Prasad , Singh Shweta , Malathkar Nithin Varma
Published: December 2024

Cognitive radios (CRs) are envisioned as a potential solution, to provide spectrum‐efficient communication for futuristic wireless communication systems like the Internet of Things (IoT) and others. This article examines the efficiency of CR’s detection performance over the fading channel. The fading model is a generalized fading model intended to collectively quantify channel nonlinearity and shadowing effects. Therefore, the effect of channel nonlinearity and shadowing together on CR detection performance has been studied. New analytical formulas for the average probability of detection (APOD) for a single user and cooperative detection are obtained for energy detection (ED)–based spectrum sensing (SS). Additionally, to provide a deeper understanding of detection characteristics, expression for the area under the receiver operating characteristics is also obtained. The effectiveness of CR detection under various nonlinearity and shadowing effects is investigated using the developed analytical expressions, and the results indicate that performance degrades as channel impairments increase. At last, Monte Carlo simulations are employed to demonstrate that the obtained analytical expressions are valid.
Identifying Promising Immunomodulators for Type 1 Diabetes (T1D) and Islet Transplantation
Authors: Ajmal Nida , Bogart Maislin C. , Khan Palwasha , Max-Harry Ibiagbani M. , Healy Amber M. , Nunemaker Craig S.
Published: December 2024

Type 1 diabetes (T1D) is an autoimmune chronic disorder that damages beta cells in the pancreatic islets of Langerhans and results in hyperglycemia due to the loss of insulin. Exogenous insulin therapy can save lives but does not stop disease progression. Thus, an effective therapy may require beta cell restoration and suppression of the autoimmune response. However, currently, there are no treatment options available that can reverse T1D. Within the National Clinical Trial (NCT) database, a majority of over 3000 trials to treat T1D are devoted to insulin therapy. This review focuses on noninsulin pharmacological therapies, specifically immunomodulators. Many investigational new drugs fall under this category, such as the recently FDA‐approved CD3 monoclonal antibody teplizumab to delay the onset of T1D. In total, we identified 39 different immunomodulatory investigational drugs. FDA‐approved teplizumab for Stage 2 T1D is discussed along with other immunomodulators that have been tested in Phase 3 clinical trials or higher, including otelixizumab (another anti‐CD3 monoclonal antibody), daclizumab (an anti‐CD25 monoclonal antibody), ladarixin (CXCR1/2 inhibitor), and antithymocyte globulin (ATG). Immunomodulators also play roles in islet transplantation and cellular therapies like FDA‐approved Lantidra. Several immunomodulators involved in Phase 3 clinical studies of islet transplantation are also discussed, including alemtuzumab, basiliximab, etanercept, and reparixin, some already FDA‐approved for other uses. These include alemtuzumab, basiliximab, etanercept, and reparixin, some of which have been FDA‐approved for other uses. This review provides background, mechanism of action, results of completed trials, and adverse effects as well as details regarding ongoing clinical trials for each of these immunomodulators.

Trial Registration: ClinicalTrials.gov identifier: NCT03875729, NCT01030861, NCT00129259, NCT00385697, NCT01280682; NCT03929601, NCT04598893, NCT05757713, NCT00678886, NCT01123083, NCT00064714, NCT00468117, NCT04628481, NCT01106157, NCT02215200, NCT00331162, NCT00679042, NCT01220856, NCT01817959
Influence of Nanosilica on Mechanical Performance in Woven Carbon/Kevlar/Epoxy Hybrid Composites
Authors: K. G. Pranesh , Manjunath Attel , K. C. Nagaraja , Bhat Raghavendra , D. Prajwal , Bhowmik Abhijit , Prakash Chander
Published: December 2024

The study focus on fiber‐reinforced polymer composite materials, which are widely used in the mechanical industries for various applications. While using the composite materials, mechanical properties such as tensile, flexural, and interlaminar shear strength plays vital role in selection of composite materials. The current work aims to investigate the influence of adding nanosilica at varying weight percentages (0, 2, and 4) to the epoxy matrix on the tensile, flexural, and interlaminar shear strengths of the fiber‐reinforced polymer hybrid nanocomposite. The five carbon and four Kevlar layer hybrid polymer nanocomposites are made with woven fibers. The method used to improve the dispersion of nanosilica in the epoxy resin was high‐speed shearing. The hand lay‐up process was used to manufacture hybrid polymer nanocomposite laminates, which were then effectively postcured. The tests for tensile strength, flexural strength, and interlaminar shear strength were carried out in accordance with ASTM standards D3039, D790, and D2344, respectively. According to the tested specimens, a hybrid composite including 2 wt.% of nanosilica with epoxy provides better tensile strength of 6.83%, flexural strength of 10.13%, and interlaminar shear strength of 13.54% more than a hybrid composite without nanosilica. At 4 wt.% of nanosilica addition to epoxy matrix, the tensile, flexural, and interlaminar shear strength decreased when compared to 2 wt.% of nanosilica due to agglomeration. The addition of 2 wt.% nanosilica to the epoxy matrix in carbon/Kevlar fiber‐reinforced polymer hybrid composites yields superior tensile, flexural, and interlaminar shear strength compared to other weight percentages.
Effect of CFRP Sheets Strengthening Method on Behaviour of Modified Lightweight Foamed Concrete Beams
Authors: Jaffal Angham Nassar , Hilal Ameer A. , Mahmoud Akram S.
Published: December 2024

This study has been adopted to examine the effect of carbon fibre‐reinforced polymer (CFRP) sheet strengthening methods on the flexural behaviour of modified foamed concrete beams reinforced with different steel reinforcement ratios, and it deals with the enhancement in flexural behaviour of conventional nonstrengthened FC beams. Twelve modified foamed concrete beams were produced in three groups depending on the reinforcement ratio (under, balanced and over) and strengthened with externally bonded CFRP sheets applied in different methods (bottom layer, U jacket and hybrid). The examined flexural variables in four‐point bending were ultimate load, fracture mode, crack width, ductility, stiffness and deflection. The results showed an increase in the carrying capacity of foamed concrete beams strengthened with CFRP sheets by (2.5%–109%) compared to the reference nonstrengthened foamed concrete beams. The stiffness of the concrete samples reinforced with CFRP sheets were improved by 13%–306% compared to nonstrengthened foamed reference beams. For a given reinforcement ratio, it was found that the best CFRP sheets strengthening method was by applying the CFRP sheets in hybrid (wrap 0° + 90°).
Thymoquinone‐Loaded Nanoemulsion Against 5‐Fluorouracil–Induced Cytotoxicity In Vitro and In Vivo
Authors: Alimoradi Fatemeh , Mansoori Razieh , Ale-Ahmad Atiyeh , Arabameri Motahare , Almasi Darya , Moghadamnia Ali Akbar , Kazemi Sohrab , Hosseini Seyed Mohammad
Published: December 2024

Chemotherapy is an effective cancer treatment but may be limited by its harmful effects on normal cells. Thymoquinone (TQ) is a natural antioxidant. This study investigates the protective effects of TQ‐loaded nanoemulsion (TQ‐NE) against 5‐fluorouracil (5‐FU) cytotoxicity in vitro and in vivo. The cytotoxic impacts of 5‐FU and its combination with TQ‐NE were measured on HepG2 cells and human fibroblasts. Subsequently, TQ‐NE and 5‐FU were administered to rats, and body weight, serum biomarkers of liver and kidney injury, and histopathologic alterations in hepatorenal tissues were measured. TQ‐NE ameliorated 5‐FU cytotoxicity in both HepG2 cells and human fibroblasts. TQ‐NE and 5‐FU combination showed a more substantial suppression on the HepG2 cell line than 5‐FU alone (p < 0.001). In vivo experiments in rats showed that TQ‐NE improved body weight gain and reduced the elevated levels of serum biomarkers of 5‐FU‐induced hepatic and renal injury. Histopathological examination showed that TQ‐NE significantly reduced 5‐FU‐induced pathological changes in hepatic and renal tissues (p < 0.001). TQ‐NE as a co‐treatment with 5‐FU may have several advantages over conventional chemotherapy, including improved efficacy, reduced toxicity, and enhanced bioavailability. These findings suggest that TQ‐NE could be a promising adjunct therapy in cancer treatment protocols.
Application of Eccentricity‐Based Topological Indices to the Design and Optimization of Blood Cancer Drugs
Authors: S. Puneeth , Mathad Veena , K. Shalini , Senan Mahde Sultan
Published: December 2024

In this study, we apply QSPR analysis to some potent drugs used in blood cancer treatment using eccentricity‐based topological indices, which are structural descriptors capturing the shape and size of the molecules as well as their branching and symmetry. These index values are computed by partitioning the corresponding molecular graphs of the drugs for both vertex and edge sets based on their degrees and eccentricities. Then, cubic regression analysis is incorporated into the structural property relational models with these indices and their corresponding physical properties. This work also deals with the various statistical parameters that affect the goodness of the model, and their error analysis is discussed, thereby producing impactful regression models through the graphical depiction of their curve fits.
Valuating Households’ Willingness to Pay for Conservation of Forest Coffee (Coffea arabica) Application of Contingent Valuation Technique: Evidence From the Kafa Zone Southwest of Ethiopia
Authors: Temam Nesru , Ordofa Gemechu , Teshome Wubishet
Published: December 2024

This research is driven by the rapid degradation of Ethiopia’s native forest coffee due to agricultural expansion and limited community engagement in conservation efforts, threatening both biodiversity and local livelihoods. The primary objective is to assess the factors influencing households’ willingness to pay (WTP) for conserving Coffea arabica, a vital genetic resource. Using a contingent valuation method (CVM), data were collected through structured questionnaires from 164 households in the Kafa Zone, where forest coffee has deep cultural and economic significance. The bivariate probit model was employed to analyze how various socioeconomic factors (income from coffee, age, gender, property rights, and education) and institutional influences (customary laws and property rights) affect WTP for conservation. Key findings indicate that income from forest coffee, customary laws, traditional institutions, and extension contacts positively impact households’ WTP, while age and sex also play significant roles. Younger household heads, increased extension contact, and stronger property rights were associated with higher WTP. The average annual WTP per household was calculated as 430 Ethiopian Birr. The study recommends enhancing community involvement through policies that integrate economic incentives with customary governance systems, promote equitable benefit‐sharing, and strengthen property rights. By aligning conservation policies with local socioeconomic contexts, the findings underscore the potential for sustainable forest management and improved community livelihoods in Ethiopia’s coffee‐producing regions.
Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma
Authors: Kader Tanjina , Lin Jia-Ren , Hug Clemens B. , Coy Shannon , Chen Yu-An , de Bruijn Ino , Shih Natalie , Jung Euihye , Pelletier Roxanne J. , Lopez Leon Mariana , Mingo Gabriel , Omran Dalia K. , Lee Jong Suk , Yapp Clarence , Satravada Baby A. , Kundra Ritika , Xu Yilin , Chan Sabrina , Tefft Juliann B. , Muhlich Jeremy L. , Kim Sarah H. , Gysler Stefan M. , Agudo Judith , Heath James R. , Schultz Nikolaus , Drescher Charles W. , Sorger Peter K. , Drapkin Ronny , Santagata Sandro
Published: December 2024

High-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC. Our findings reveal immune modulating mechanisms within precursor epithelium, characterized by chromosomal instability, persistent interferon (IFN) signaling, and dysregulated innate and adaptive immunity. FT precursors display elevated expression of MHC-class I, including HLA-E, and IFN-stimulated genes, typically linked to later-stage tumorigenesis. These molecular alterations coincide with progressive shifts in the tumor microenvironment, transitioning from immune surveillance in early STICs to immune suppression in advanced STICs and cancer. These insights identify potential biomarkers and therapeutic targets for HGSOC interception and clarify the molecular transitions from precancer to cancer.
Questionnaire-Based Global Prevalence of Hidradenitis Suppurativa: A Systematic Review and Meta-Analysis
Authors: Zahid Jawad Ahmad , Henning Mattias A.S. , Bouazzi Dorra , Jemec Gregor B.E.
Published: December 2024

Background: Hidradenitis suppurativa (HS), a chronic inflammatory skin disease affecting intertriginous areas, presents a recurring and debilitating challenge. Even though recent efforts have been made to estimate the overall HS prevalence, variations in screening modalities and missing data from the Global South warrant further investigation. Understanding the HS prevalence is crucial for treatment approaches and pathogenesis. Thus, we aimed to estimate a global HS prevalence based on studies using homogeneous validated questions. Methods: This systematic review was prospectively registered on PROSPERO and adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Searches in PubMed, Embase, and CINAHL were performed on August 9, 2023. Original reports assessing the HS prevalence in adults using the following two questions were included: “Do you have recurrent boils of the skin?” and “Have you for the past 6 months had 2 or more boils/abscesses in any of the below locations: in the axilla, in the groin, around your genitals, on the buttocks, several locations i.e., first the buttocks then the axilla, etc.?” A pooled prevalence with 95% confidence interval (CI) was calculated with a random-effects model. Results: Eight studies qualified for inclusion, of which the prevalence estimate ranged from 0.7% to 6.4%. The meta-analysis encompassing 49,971 participants revealed a global HS prevalence of 2.5% (95% CI, 1.8–3.5%). Conclusion: This meta-analysis suggests a global HS prevalence of 2.5% using a validated questionnaire. Due to heterogeneity and sparse data from the Global South, this estimate should be interpreted with caution.
Effectiveness of Machine Learning Based Adjustments to an eHealth Intervention Targeting Mild Alcohol Use
Authors: Derksen Marloes , van Beek Max , Blankers Matthijs , Nasri Hamed , de Bruijn Tamara , Lommerse Nick , van Wingen Guido , Pauws Steffen , Goudriaan Anna E.
Published: December 2024

This study aimed to evaluate effects of three machine learning based adjustments made to an eHealth intervention for mild alcohol use disorder, regarding a) early dropout, b) participation duration, and c) success in reaching personal alcohol use goals. Additionally, we aimed to replicate earlier machine learning analyses. We used three cohorts of observational log data from the Jellinek Digital Self-help intervention. First, a cohort before implementation of adjustments (T0; n=320); second, a cohort after implementing two adjustments (i.e., sending daily emails in the first week and nudging participants towards a ‘no alcohol use’ goal; T1; n=146); third, a cohort comprising the prior adjustments complemented with eliminated time constraints to reaching further in the intervention (T2; n=236). We found an increase in participants reaching further in the intervention, yet an increase in early dropout after implementing all adjustments. Moreover, we found that more participants aimed for a quit goal, whilst participation duration declined at T2. Intervention success increased, yet not significantly. Lastly, machine learning demonstrated reliable for outcome prediction in smaller datasets of an eHealth intervention. Strong correlates as indicated by machine learning analyses were found to affect goal setting and use of an eHealth program for alcohol use problems.
Adjuvant sequential chemotherapy for salivary duct carcinomas: a retrospective comparative analysis
Authors: Kim Younghac , Choi Nayeon , Kim Eun-Hye , Chung Man Ki , Son Young-Ik , Oh Dongryul , Ahn Yong Chan , Lee Se-Hoon , Jung Hyun Ae , Park Sehhoon , Kim Jinyong , Jeong Han-Sin , Ahn Myung-Ju
Published: December 2024

Introduction: This study aimed to report the efficacy and safety of adjuvant sequential chemotherapy after definitive treatment of salivary duct carcinoma (SDC) compared with the standard treatment alone (surgery with postoperative radiation therapy). Methods: This was a retrospective study of pathologically confirmed 135 SDC patients (study period 2009 to 2022). After curative surgery and adjuvant radiation therapy, 55 of 135 patients decided to receive additional chemotherapy (OP+RT+Chemo group), while 80 opted for surgery and radiation (OP+RT group). Treatment outcomes of overall survival (OS), disease-free survival (DFS), and distant-metastasis-free survival (DMFS) were compared using a propensity score matching (PSM) analysis. Results: Adjuvant chemotherapy consisted of three cycles of cisplatin-based regimen, which was well tolerated in most patients with minimal adverse events. Multivariable analyses indicated that the addition of chemotherapy did not improve OS (p = 0.05), DFS (p = 0.386), and DMFS (p = 0.735), although there was a trend toward favoring adjuvant chemotherapy in terms of OS. With PSM analysis, OS (OP+RT+Chemo to OP+RT, Hazard ratio [HR] = 0.40, 95% confidence interval [95%CI] = 0.12-1.29, p = 0.126), DFS (HR = 0.69, 95% CI = 0.30-1.56, p = 0.367) and DMFS (HR = 0.96, 95% CI = 0.46-1.99, p = 0.903) were not statistically different. Conclusions: Current cisplatin-based adjuvant chemotherapy did not significantly improve treatment outcomes of SDC patients over the surgery and adjuvant radiation. Further development or clinical studies are required to improve the outcomes of SDC, including chemotherapeutic, biomarkers, immune checkpoint inhibitors, or treatment strategies.
A comparative analysis of ANFIS and fuzzy controllers for a dynamic hybrid model
Authors: Kaltoum Laoufi , Mouloudi Youssef , Hazzab Abdeldjebar , Abdelkader Abdallah Ben
Published: December 2024

Transitioning from combustion engines to electric motors is essential to reduce CO₂ emissions and combat climate change. This study presents a dynamic hybrid model combining a fuel cell and battery for electric vehicles, emphasizing simplified parameter extraction from battery datasheets. The model integrates two energy storage systems: batteries for electrochemical storage and hydrogen for chemical storage, converted into electricity via a fuel cell stack. This dual approach enables flexible refueling options with electricity or hydrogen. An air compressor in the proton exchange membrane (PEM) fuel cell stack optimizes performance across varying driving conditions. The research aims to minimize fuel cell consumption and enhance energy storage efficiency using Sim Power Systems software. It employs traditional proportional integral derivative (PID) controllers and advanced optimization techniques, including fuzzy and ANFIS, to achieve optimal power distribution between the fuel cell system (FCS) and the energy secondary source (ESS) for specific road scenarios. The proposed ANFIS-based approach demonstrates superior control in balancing energy efficiency and driving dynamics, surpassing both PID and fuzzy logic controllers in key metrics. This innovative closed-loop control system offers a promising solution for hybrid electric vehicles, ensuring optimal performance and energy management.