bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-Defect-Induced Peculiarities in Inverse Faraday-Based Switching of Superconducting Current-Carrying States near a Critical Temperature
Authors: Croitoru Mihail D. , Buzdin Alexander I.
Published: November 2024

The Inverse Faraday Effect (IFE) is a phenomenon that enables non-thermal magnetization in various types of materials through the interaction with circularly polarized light. This study investigates the impact of single defects on the ability of circularly polarized radiation to switch between distinct superconducting current states, when the magnetic flux through a superconducting ring equals half the quantum flux, Φ0/2. Using both analytical methods within the standard Ginzburg–Landau theory and numerical simulations based on the stochastic time-dependent Ginzburg–Landau approach, we demonstrate that while circularly polarized light can effectively switch between current-carrying superconducting states, the presence of a single defect significantly affects this switching mechanism. We establish critical temperature conditions above which the switching effect completely disappears, offering insights into the limitations imposed by a single defect on the dynamics of light-induced IFE-based magnetization in superconductors.
DurdusTools—An Online Genetic Distance Calculation Tool for Efficient Variety Testing in Durum Wheat (Triticum turgidum L. subsp. durum (Desf.) Husn.)
Authors: Ribarits Alexandra , Bomers Svenja , Zerak Tadej , Alber Oliver , Seereiter Jakob , Escolano García Antonio , Lázaro Somoza Ana , Giulini Anna Pia Maria , Somogyi Ferenc , Kőrösi Sándor , Taferner-Kriegl Jutta
Published: November 2024

The management of variety collections can be supported by integrating molecular data into Distinctness, Uniformity, and Stability (DUS) testing. DurdusTools is a genetic distance (GD) calculation tool that supports planning field trials in durum wheat. A commercially available single-nucleotide polymorphism (SNP) wheat microarray is used to profile varieties and candidate varieties. Their molecular profiles are stored in a database. SNP markers selected based on quality parameters are used to calculate the pairwise genetic distance (GD) between the varieties. Combining molecular and variety information creates a downloadable, user-friendly Excel-based output. The file shows the pairwise GD of the varieties most similar to the candidate variety of interest and selected variety information. After the first year of field trials, the DUS experts use the phenotypic assessment data together with the GD information to select genotypes to be grown in the field for side-by-side comparisons. The principles of DurdusTools allow for an easy integration of molecular data into DUS testing. Using the tool requires neither specific infrastructure nor molecular expert knowledge and was developed by its users for DUS testing purposes. This makes DurdusTools an easily accessible and user-friendly tool that supports variety selection for DUS field trials through an improved data basis.
Light Energy Use Efficiency in Photosystem II of Tomato Is Related to Leaf Age and Light Intensity
Authors: Moustaka Julietta , Sperdouli Ilektra , Moustakas Michael
Published: November 2024

The fundamental key to increase photosynthetic efficiency of crop plants lies in optimizing the light energy use efficiency. In our study, we used tomato to evaluate the allocation of absorbed light energy in young and mature leaves, and to estimate if the extent of photoinhibition and photoprotection can be affected by the leaf age. A reduced efficiency of the oxygen-evolving complex, in young leaves compared to mature ones, resulted in a donor-side photoinhibition, as judged from the significantly lower Fv/Fm ratio, in young leaves. The detected increased 1O2 production in young leaves was probably due to a donor-side photoinhibition. The effective quantum yield of photosystem II (PSII) photochemistry (ΦPSII), at low light intensity (LLI, 426 μmol photons m−2 s−1), was significantly lower in young compared to mature leaves. Moreover, the non-significant increase in non-photochemical energy loss in PSII (ΦNPQ) could not counteract the decreased ΦPSII, and as a result the non-regulated energy loss in PSII (ΦNO) increased in young leaves, compared to mature ones. The significantly lower ΦPSII in young leaves can be attributed to the increased reactive oxygen species (ROS) creation that diminished the efficiency of the open PSII reaction centers (Fv’/Fm’), but without having any impact on the fraction of the open reaction centers. The reduced excess excitation energy, in mature leaves compared to young ones, at LLI, also revealed an enhanced PSII efficiency of mature leaves. However, there was almost no difference in the light energy use efficiency between young and mature leaves at the high light intensity (HLI, 1000 μmol photons m−2 s−1). The ability of mature tomato leaves to constrain photoinhibition is possible related to an enhanced photosynthetic function and a better growth rate. We concluded that the light energy use efficiency in tomato leaves is influenced by both the leaf age and the light intensity. Furthermore, the degrees of photoinhibition and photoprotection are related to the leaf developmental stage.
Influence of Y2O3 Concentration on the Optical Properties of Multicomponent Glasses and Glass–Ceramics
Authors: Beniaiche Akram , Belkhir Nabil , Pérez-Román Berta , Rubio Juan , Rubio Fausto
Published: November 2024

The optical properties and structural characterization of multicomponent silicate glasses of low Al2O3 and different Y2O3 concentrations have been studied. These glasses have also been crystallized to obtain glass–ceramic materials, and their properties have been characterized. The obtained glasses were transparent and their refractive indexes increased with Y2O3 concentration. After a heat treatment at 930 °C for 10 min, these glasses maintained their transparency, but a brown color appeared, and after 30 min, those glasses with high Y2O3 concentrations turned opaque or white in color. These processes of crystallization for obtaining the new glass–ceramics have been studied by means of FTIR and Raman spectroscopies, and the crystallized materials were characterized with XRD and FE-SEM techniques. These glasses and glass–ceramics have also been characterized by means of UV–vis spectroscopy, and the corresponding optical properties (reflectance, color, band-gap) have been determined as a function of the Y2O3 concentrations and the structural properties.
Conductive Hydrogel Materials for Flexible Supercapacitor Electrodes
Authors: Zhang Kun , Chen Zhizhou , Li Jinling , Feng Gaoqiang , Xu Chang , Yang Jizhi , Li Wanwan
Published: November 2024

Flexible supercapacitors (SCs), as promising energy storage devices, have shown great potential for both next-generation wearable electronics and addressing the global energy crisis. Conductive hydrogels (CHs) are suitable electrode materials for flexible SCs on account of their intrinsic characteristics and functional advantages, such as a unique 3D porous structure, remarkable conductivity, tunable chemical and physical properties, and outstanding mechanical properties. Herein, an overview of the fabrication strategies for CHs as electrode materials in flexible SCs, as well as their advantages and disadvantages, and perspectives on CH-based SCs is provided. First, the fabrication strategies for CHs are systematically introduced. Second, various multifunctional CH-based SCs are presented and discussed. Finally, this review concludes with insights into the challenges and opportunities related to CHs or CH-based SCs, indicating future research prospects and application orientations in this field.
Advancements in the Engineering Modification of Sucrose Phosphorylase
Authors: Ma Shuru , Zhang Hongyu , Lou Tingting , Wang Suying
Published: November 2024

Sucrose phosphorylase (SPase) is a member of the glycoside hydrolase family 13, catalyzing the reversible phosphorolysis of sucrose to produce α–glucose–1–phosphate and exhibiting transglycosylation activity toward multiple substrates. Its wide substrate specificity enables the synthesis of various glycosides, which are broadly applied in food, cosmetics, and pharmaceuticals. However, the industrial application of SPase is constrained by its poor thermostability and limited transglycosylation activity. Therefore, current research focuses on enhancing the thermostability and transglycosylation activity of SPase through efficient engineering strategies based on its crystal structure and catalytic mechanism. This paper systematically reviews the crystal structure and catalytic mechanism of SPase, outlines the application of protein engineering and immobilization strategies in improving the thermostability of SPase, and analyzes how modifications at key amino acid sites affect the synthesis of typical glycosylation products. It also summarizes the limitations of SPase engineering modification strategies and explores the potential of diversified approaches for SPase modification, highlighting its broad application prospects in industrial production and laying a solid foundation for further advancements in SPase engineering modification and its industrial application.
Evaluation of Structural Transition Joints Cu-Al-AlMg3 Used in Galvanizer Hangers
Authors: Marônek Milan , Bárta Jozef , Bártová Katarína , Sahul Miroslav , Sahul Martin , Pašák Matej , Nesvadba Petr , Bezdička Petr
Published: November 2024

The paper deals with the evaluation of the quality of Cu-Al-AlMg3 structural transition joints (STJ) made by explosion welding proposed for the renovation of galvanizer hangers. The three-layer joint consisted of electrolytic copper with a thickness of 25 mm, 2 mm of aluminium represented by the AW1050 alloy, and 25 mm of the EN AW 575 aluminium alloy. Light microscopy analysis confirmed the wavy pattern of both interfaces of the welded joint and significant plastic deformation in close proximity to the waves. Microhardness measurement revealed a partial strain hardening of the AW5754 copper-aluminium alloy near the interface and a significant increase in microhardness in the vortex zone of waves, reaching a value of up to 863 HV 0.025. Microcracks were also observed in these places. The intermetallic phase Al2Cu was identified in the vortex zones by XRD analysis. As a continuous layer of intermetallic phase was not observed in the interface of the welded joint, it is possible to consider the used welding parameters as appropriate. A semi-quantitative EDX analysis revealed a diversity of chemical composition in the vortex zones, which does not correspond to the phase composition based on the equilibrium binary Al-Cu diagram due to non-equilibrium conditions in the formation of the welded joint interface. The bond strength of three-layer welded joint evaluated by the strength test ranged from 151 to 171 MPa, which represented approximately a two-fold increase in comparison to the ultimate tensile strength of alloy AW1050, while the failure occurred in all samples at the AW1050-AW5754 alloy interface.
Modification of Ceritinib Crystal Morphology via Spherical Crystallization
Authors: Zokić Iva , Prlić Kardum Jasna , Crnac Lana , Sabol Mirta , Vuić Juraj , Travančić Valentina
Published: November 2024

The formulation process for some drugs can be challenging, due to their unfavorable physical and mechanical properties and poor water solubility. Powder technology has made a significant impact in regard to the modification of the particles in active pharmaceutical ingredients (APIs) to produce high-quality granules. Spherical particles are preferred over other shapes, due to their high tap and bulk density, reduced dustiness, better flowability, strong anti-caking properties, and better mechanical performance during tableting. The present study investigates the possibility of obtaining spherical crystals of ceritinib, a drug used for the treatment of anaplastic lymphoma kinase (ALK)-positive advanced non-small cell lung cancer, which belongs to BCS class IV drugs and has a platy crystal shape. Ceritinib spheres were prepared by spherical agglomeration, in a ternary system, and quasi-emulsion solvent diffusion, with the addition of polyvinylpyrrolidone, as well as a combination of these two methods. With the combined method of spherical crystallization, crystals with the most favorable morphology and the narrowest distribution of particle sizes were obtained, which was the reason for further optimization. The influence of different impeller geometries and mixing rates on the morphology of the obtained crystals was examined and the optimal conditions for the process were selected. Using empirical correlations and a visual criterion, the process was scaled up from a 0.1 L to a 1 L batch crystallizer. The obtained crystals were characterized by light and scanning electron microscopy. The addition of a bridging liquid and/or a polymer additive did not change the internal structure of the ceritinib crystals, which was confirmed by X-ray powder diffraction.
Disability and Participation in Colorectal Cancer Screening: A Systematic Review and Meta-Analysis
Authors: Ricciardi Giovanni Emanuele , Cuciniello Rita , De Ponti Emanuele , Lunetti Carlo , Pennisi Flavia , Signorelli Carlo , Renzi Cristina
Published: November 2024

Background: The aim of this study is to assess the impact of disability on participation in CRC screening and to determine the overall effect size. Methods: We conducted a systematic review and meta-analysis to compare CRC screening participation in individuals with and without disabilities. The search encompassed five databases (PubMed, EMBASE, Scopus, Google Scholar, medRxiv). Pooled estimates were calculated for each type of CRC screening and disability categories to synthesize the findings. The participation in CRC screening was derived using a random effects model. Results: A total of 20 articles were included, most of them from the USA. Based on pooled estimates, individuals with disabilities have lower odds of undergoing CRC screening versus those without disabilities (OR = 0.80, 95%CI 0.73–0.87). Analysis by screening type indicated that individuals with a disability have lower odds of a fecal occult blood test or a fecal immunochemical test (OR: 0.72, 95%CI 0.65–0.81), with no significant difference for a colonoscopy. Individuals with intellectual disabilities had significantly lower rates of CRC screening participation (OR = 0.65, 95%CI 0.53–0.79), especially for FOBT/FIT (OR = 0.58, 95%CI 0.49–0.69). Conclusions: Disparities exist for CRC screening participation in people with disabilities. Further research and coordinated efforts are essential to develop interventions for improving early cancer diagnosis for this non-negligible patient group.
Evaluating the Efficacy of Immunotherapy in Fragile Hospitalized Patients
Authors: Rajadurai Charles Vincent , Gagnon Guillaume , Allard Catherine , Malick Mandy , Pavic Michel
Published: November 2024

Background: Immunotherapy is the cornerstone of treatment for many cancers. The effectiveness of immunotherapy in hospitalized patients is unknown due to the exclusion of this fragile population from clinical trials. This study evaluates the efficacy of immunotherapy in fragile hospitalized patients. Method: We conducted a single-center retrospective study involving 49 patients who started an immunotherapy (IO) during a hospitalization or within 3 months after a hospitalization at the Centre Hospitalier de l’Université de Sherbrooke (CHUS). Efficacy analysis included objective response rate (ORR), overall survival (OS), and progression-free survival (PFS). Results: Immunotherapy resulted in 30.6% of all grades combined and 18.4% of grade three to four immune-related adverse events (irAE). Efficacy outcomes were inferior in the fragile cohort of patients with ORR of 38.9%, PFS of 2.8 months (95% CI [2.17–3.35]), and OS of 3.2 months (95% CI [1.60–4.84]). Performance status of ECOG three to four compared to ECOG zero predicts poor OS (HR 5.666 [1.207–26.594]; p = 0.028) and PFS (HR 4.136 [0.867–19.733]; p = 0.075). Fitness to receive four to six cycles (HR 0.335 [0.152–0.0.738]; p < 0.007) or more predicts greater OS compared to one to three cycles of immunotherapy. Low levels of serum albumin (HR 0.917 [0.852–0.987]; p = 0.021) and elevated levels of serum LDH (HR 2.224 [1.469–3.367]; p < 0.001) are associated with a reduced OS. Conclusion: The effectiveness of immunotherapy in fragile hospitalized patients is compromised, although they exhibit significant irAE. Excellent performance status, fitness to receive many IO treatments, and normal levels of serum LDH and albumin may be useful in selecting patients who will benefit from immunotherapy.
Spatial Distribution and Temporal Variation of Megafauna in Circalittoral and Bathyal Soft Bottoms of the Westernmost Biodiversity Hotspot of the Mediterranean Sea: The Alboran Ridge
Authors: García-Ruiz Cristina , Hidalgo Manuel , Ciércoles Cristina , González-Aguilar María , Torres Pedro , Urra Javier , Rueda José L.
Published: November 2024

The Alboran Sea is the westernmost sub-basin of the Mediterranean Sea, and it is connected to the Atlantic Ocean through the Strait of Gibraltar. The Alboran Ridge is located in the middle of the Alboran Sea and represents a hotspot of biodiversity in the Mediterranean Sea. Besides their critical importance, there are few studies on the communities and changes in biodiversity, and they mostly concentrate on infralittoral and circalittoral bottoms. In this work, the composition, structure and bathymetric and temporal changes of megafauna of the Alboran Ridge were examined. Samples were collected from MEDITS surveys carried out between 2012 and 2022 at depths ranging from 100 to 800 m. Analyses were performed separately for each of the taxonomic groups: osteichthyes, chondrichthyes, crustaceans, molluscs, echinoderms and “other groups”. There was no common spatial organization for each of the faunistic groups studied, although most of them displayed differences between the shelf and the slope. The continental shelf was characterized by the highest values of community metrics such as abundance, biomass, species richness and mean weight of species for all groups except for chondrichthyes and crustaceans. Decreasing trends of some community metrics were detected in some of the faunistic groups throughout the study period.
Seaweed-Associated Diatoms (Bacillariophyta) in Dokdo of South Korea: I. Subphyla Melosirophytina, Coscinodiscophytina, and Class Mediophyceae
Authors: Park Joon Sang , Lee Kyun-Woo , Jung Seung Won , Kim Han Jun , Lee Jin Hwan
Published: November 2024

Dokdo is an island located in the easternmost part of Korea, which has high levels of biodiversity of birds and fish, especially marine invertebrates. However, the biodiversity of microalgae, especially diatoms (Bacillariophyta), is relatively unknown, despite their ecological importance as primary producers of the marine food web and bioindicators of environmental conditions associated with climate change. To understand the biodiversity of seaweed-associated diatoms from Dokdo, we collected macroalgae present at a depth 5–15 m by SCUBA diving on 17 October 2017. There were a large number of diatoms (over 130 species), even though it was a one-time survey. As it includes too many taxa to cover at once, voucher flora for other taxonomic groups will be provided through the continuous serial papers. This is the first series of seaweed-associated diatoms, with 26 species belonging to the subphyla Melosirophytina and Coscinodisophytina, and the class Mediophyceae. Among these, seven species including one new taxon were reported for the first time in Korea, which, along with the geopolitical characteristics of the survey area, proved that there is no domestic interest in seaweed-related diatoms. In particular, the appearance of species that have been reported in subtropical waters, such as the order Ardissoneales, requires continuous monitoring of marine seaweed-associated diatoms to confirm whether their colonization in Dokdo waters was due to climate change or species-specific water temperature tolerance.
Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms
Authors: Muhsen Dhiaa Halboot , Haider Haider Tarish , Al-Nidawi Yaarob
Published: November 2024

Identifying the parameters of a triple-diode electrical circuit structure in PV modules is a critical issue, and it has been regarded as an important research area. Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the mutation stage to enhance the reliability and efficiency of the DEA. A new formula is presented to adapt the control parameters (mutation factor and crossover rate) of the DEA. Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). The results of the proposed PV modeling method are evaluated with other state-of-the-art approaches. According to different statistical criteria, the DEIMA demonstrates superiority in terms of root mean square error and main bias error by at least 5.4% and 10%, respectively, as compared to other methods. Furthermore, the DEIMA has an average execution time of 27.69 s, which is less than that of the other methods.
Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI
Authors: Jeon Insu , Kim Minjoong , So Dayeong , Kim Eun Young , Nam Yunyoung , Kim Seungsoo , Shim Sehoon , Kim Joungmin , Moon Jihoon
Published: November 2024

Background: As the demand for early and accurate diagnosis of autism spectrum disorder (ASD) increases, the integration of machine learning (ML) and explainable artificial intelligence (XAI) is emerging as a critical advancement that promises to revolutionize intervention strategies by improving both accuracy and transparency. Methods: This paper presents a method that combines XAI techniques with a rigorous data-preprocessing pipeline to improve the accuracy and interpretability of ML-based diagnostic tools. Our preprocessing pipeline included outlier removal, missing data handling, and selecting pertinent features based on clinical expert advice. Using R and the caret package (version 6.0.94), we developed and compared several ML algorithms, validated using 10-fold cross-validation and optimized by grid search hyperparameter tuning. XAI techniques were employed to improve model transparency, offering insights into how features contribute to predictions, thereby enhancing clinician trust. Results: Rigorous data-preprocessing improved the models’ generalizability and real-world applicability across diverse clinical datasets, ensuring a robust performance. Neural networks and extreme gradient boosting models achieved the best performance in terms of accuracy, precision, and recall. XAI techniques demonstrated that behavioral features significantly influenced model predictions, leading to greater interpretability. Conclusions: This study successfully developed highly precise and interpretable ML models for ASD diagnosis, connecting advanced ML methods with practical clinical application and supporting the adoption of AI-driven diagnostic tools by healthcare professionals. This study’s findings contribute to personalized intervention strategies and early diagnostic practices, ultimately improving outcomes and quality of life for individuals with ASD.
Can Radiological Renal Artery Parameters Predict Acute Kidney Injury in Infective Endocarditis Surgery?—From Imaging to Outcomes
Authors: Dinges Christian , Boxhammer Elke , Kremser Iris , Gansterer Katja , Steindl Johannes , Schörghofer Nikolaos , Knapitsch Christoph , Kaufmann Reinhard , Hoppe Uta C. , Hammerer Matthias , Hergan Klaus , Scharinger Bernhard
Published: November 2024

Background: Infective endocarditis (IE) poses significant challenges in cardiovascular medicine, often necessitating valvular surgery to manage severe complications. Postoperative acute kidney injury (AKI) is a notable complication affecting patient outcomes. While clinical and procedural factors have been well studied, the role of radiological renal artery parameters in AKI risk remains underexplored. Methods: This retrospective study analyzed 80 patients with IE who underwent valvular surgery from 2013 to 2021, focusing on postoperative AKI as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Radiological parameters, including renal artery calcification, renal ostial calcification, the presence of renal infarctions, and additional arteries, were assessed using preoperative computed tomography (CT). Statistical analyses included binary logistic and linear regression models, Kaplan–Meier survival curves, and Cox proportional hazard regression to explore associations between these parameters and AKI incidence, creatinine levels, and mortality. Results: Out of 80 patients, 31 (38.8%) developed AKI. No significant differences were found in baseline characteristics or radiological parameters between the AKI+ and AKI− groups. Binary logistic and linear regression analyses revealed no substantial relationship between anatomical factors and AKI risk or creatinine levels. However, Cox regression identified “additional renal artery” as a significant predictor of 1-month mortality (HR: 1.747, 95% CI: 1.024–2.979, p = 0.041) but not for 6- or 12-month mortality. Conclusions: Radiological anatomical factors, including calcifications and additional arteries, did not significantly impact AKI risk in IE patients undergoing valvular surgery. However, the presence of additional arteries was associated with increased short-term mortality. These findings suggest the need for further research to elucidate factors contributing to AKI and mortality in this context.
Comment on Uzun Ozsahin et al. COVID-19 Prediction Using Black-Box Based Pearson Correlation Approach. Diagnostics 2023, 13, 1264
Authors: Graña Manuel , Badiola-Zabala Goizalde , Cano-Escalera Guillermo
Published: November 2024

The declaration of the COVID-19 pandemic by the World Health Organization (WHO) in March 2020 has triggered the publication of thousands of papers covering a plethora of aspects of the pandemic, from epidemiology models [...]
Reply to Graña et al. Comment on “Uzun Ozsahin et al. COVID-19 Prediction Using Black-Box Based Pearson Correlation Approach. Diagnostics 2023, 13, 1264”
Authors: Uzun Ozsahin Dilber , Precious Onakpojeruo Efe , Bartholomew Duwa Basil , Usman Abdullahi Garba , Isah Abba Sani , Uzun Berna
Published: November 2024

Dr [...]
Feasibility of Using 18F-FDG PET/CT Radiomics and Machine Learning to Detect Drug-Induced Interstitial Lung Disease
Authors: Smith Charlotte L. C. , Zwezerijnen Gerben J. C. , Wiegers Sanne E. , Jauw Yvonne W. S. , Lugtenburg Pieternella J. , Zijlstra Josée M. , Yaqub Maqsood , Boellaard Ronald
Published: November 2024

Background: Bleomycin is an oncolytic and antibiotic agent used to treat various human cancers because of its antitumor activity. Unfortunately, up to 46% of the patients treated with bleomycin develop drug-induced interstitial lung disease (DIILD) and potentially life-threatening interstitial pulmonary fibrosis. Tools and biomarkers for predicting and detecting DIILD are limited. Therefore, we aimed to evaluate the feasibility of 18F-FDG PET/CT, PET radiomics, and machine learning in distinguishing DIILD in an explorative pilot study. Methods: Eighteen Hodgkin’s lymphoma (HL) patients, of whom 10 developed DIILD after treatment with bleomycin, were retrospectively included. Five diffuse large B-cell lymphoma (DLBCL) patients were included as a control group since they were not treated with bleomycin. All patients underwent 18F-FDG PET/CT scans before (baseline) and during treatment (interim). Structural changes were assessed by changes in Hounsfield Units (HUs). The 18F-FDG PET scans were used to assess metabolic changes by examining the feasibility of 504 radiomics features, including the mean activity of the lungs (SUVmean). A Random Forest (RF) classifier evaluated the identification and prediction of DIILD based on PET radiomics features. Results: HL patients who developed DIILD showed a significant increase in standard SUV metrics (SUVmean; p = 0.012, median increase 37.4%), and in some regional PET radiomics features (texture strength; p = 0.009, median increase 101.6% and zone distance entropy; p = 0.019, median increase 18.5%), while this was not found in HL patients who did not develop DIILD and DLBCL patients. The RF classifier correctly identified DIILD in 72.2% of the patients and predicted the development of DIILD correctly in 50% of the patients. There were no significant differences in HUs over time within all three patient groups. Conclusions: Our explorative longitudinal pilot study suggests that certain regional 18F-FDG PET radiomics features can effectively identify DIILD in HL patients treated with bleomycin, as significant longitudinal increases were observed in SUVmean, texture strength, and zone distance entropy after the development of DIILD. The metabolic activity of these features did not significantly increase over time in DLBCL patients and HL patients who did not develop DIILD. This indicates that 18F-FDG PET radiomics, with and without machine learning, might serve as potential biomarkers for detecting DIILD.
Evaluating Various Methods Used by Direct-to-Consumer Products Promising Personalized Nutrition
Authors: Gimpfl Sebastian , Steinle Kseniia , Gedrich Kurt
Published: November 2024

The increasing availability of direct-to-consumer personalized nutrition products has raised questions about their scope of personalization and added value compared to general dietary guidelines. This study evaluated eleven personalized nutrition products across six distinct methodologies, including DNA analysis, blood marker analysis, microbiome testing, blood glucose monitoring, questionnaire-based personalization, and consultation with a dietitian, comparatively evaluating their consistency and added value compared to general dietary guidelines. A 24-year-old obese male with no pre-existing illnesses was chosen as the case participant to represent a typical individual seeking personalized nutrition advice for weight loss. Significant variability and inconsistency were observed across and within the different methodologies, particularly in recommendations for energy intake and macronutrient distribution. Most advice was generic and aligned closely with existing dietary guidelines, with a notable lack of behavioral change strategies. This study underscores the challenges in personalized nutrition, highlighting the problem that current practices often fall short of delivering truly tailored recommendations. There is a critical need for clearer definitions, evidence-based guidelines, and more comprehensive approaches to fully realize the potential of personalized nutrition in improving individual health.
Co-Extraction of DNA and RNA from Candida albicans Using a Chemical Method in Conjunction with Silicon Carbide with Few Cells
Authors: Freitas Elizabeth Cristina Vieira de , Santos Francisca Alves dos , Lopes Maria Raíssa Vieira , Sousa Júnior Dárcio Luiz de , Yafawi Tássia Thaís Al , Araújo Ana Carolina Ferreira , Freitas Priscilla Ramos , Menezes Irwin Rose Alencar de , Coutinho Henrique Douglas Melo , Leandro Maria Karollyna do Nascimento Silva
Published: November 2024

Objective: The study aimed to optimize protocols for the joint extraction of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from 0.025 × 106 CFU of Candida albicans, targeting to overcome the challenges in the extraction of these genetic materials. Materials and methods: From this, treated silicon carbide (SiC) granules were added to fungal samples from methods 1, 2, and 3 obtained from aliquots of BHI or Sabouraud medium to cause cell lysis and enable the isolation of these macromolecules by phenol and chloroform. The concentration and integrity of the extracted nucleic acids were analyzed, respectively, by spectrophotometry using the A260/A280 ratios and 1% agarose gel electrophoresis. Results: Therefore, method 3 is the one that most comprises samples considered pure of both DNA and RNA, simultaneously. Furthermore, the presence of intact RNAs corresponding to the base pair size such as 5.8 S rRNA and tRNA was verified during electrophoresis, considering the particularities of RNA, which makes it very unstable and easily degraded. Conclusions: Thus, it results in a faster and simpler method in addition to obtain promising results using minimal amounts of biological sample and offering a valuable alternative for small laboratories to work with molecular biology.
Distributed Model Predictive Control Cooperative Guidance Law for Multiple UAVs
Authors: Huang Hanqiao , Dong Yue , Cui Haoran , Zhou Huan , Du Bo
Published: November 2024

Aiming at the problem of multiple unmanned aerial vehicles (UAVs) cooperatively intercepting a maneuvering target, this paper proposes a cooperative guidance law with less energy consumption and a newly accurate time-to-go estimation algorithm in the two-dimensional (2D) plane. Firstly, based on the relative motion equations between UAVs and the target on the 2D plane, the line-of-sight (LOS) direction and the LOS normal direction models are established. Then, based on the distributed model predictive control (DMPC) theory, DMPC cooperative guidance laws are designed in two directions. This guidance law can ensure that all UAVs intercept the maneuvering target at the expected LOS angle at the same time and reduce the energy consumption during the guidance process. Then, a new time-to-go estimation algorithm is designed, which can reduce the time-to-go estimation error and improve the cooperative accuracy. Finally, the simulation results show that the DMPC cooperative guidance law reduces energy consumption by more than 50% compared to other guidance laws and the proposed time-to-go estimation algorithm improves the accuracy by 200% compared to traditional methods.
Novel Design and Computational Fluid Dynamic Analysis of a Foldable Hybrid Aerial Underwater Vehicle
Authors: Chen Guangrong , Yan Lei , Cao Ao , Zhu Xinyuan , Ding Hongbo , Lin Yuxiang
Published: November 2024

Hybrid Aerial Underwater Vehicles (HAUVs), capable of operating effectively in both aerial and underwater environments, offer promising solutions for a wide range of applications. This paper presents the design and development of a novel foldable wing HAUV, detailing the overall structural framework and key design considerations. We employed fluid simulation software to perform comprehensive hydrodynamic and aerodynamic analyses, simulating the vehicle’s behavior during aerial flight, underwater navigation, water entry and exit, and surface gliding. The motion characteristics under different speed and angle conditions were analyzed. Additionally, a physical prototype was constructed, and experimental tests were conducted to evaluate its performance in both aerial and underwater environments. The experimental results confirmed the vehicle’s ability to seamlessly transition between air and water, demonstrating its viability for dual-environment operations.
Entropy of Neuronal Spike Patterns
Authors: Luczak Artur
Published: November 2024

Neuronal spike patterns are the fundamental units of neural communication in the brain, which is still not fully understood. Entropy measures offer a quantitative framework to assess the variability and information content of these spike patterns. By quantifying the uncertainty and informational content of neuronal patterns, entropy measures provide insights into neural coding strategies, synaptic plasticity, network dynamics, and cognitive processes. Here, we review basic entropy metrics and then we provide examples of recent advancements in using entropy as a tool to improve our understanding of neuronal processing. It focuses especially on studies on critical dynamics in neural networks and the relation of entropy to predictive coding and cortical communication. We highlight the necessity of expanding entropy measures from single neurons to encompass multi-neuronal activity patterns, as cortical circuits communicate through coordinated spatiotemporal activity patterns, called neuronal packets. We discuss how the sequential and partially stereotypical nature of neuronal packets influences the entropy of cortical communication. Stereotypy reduces entropy by enhancing reliability and predictability in neural signaling, while variability within packets increases entropy, allowing for greater information capacity. This balance between stereotypy and variability supports both robustness and flexibility in cortical information processing. We also review challenges in applying entropy to analyze such spatiotemporal neuronal spike patterns, notably, the “curse of dimensionality” in estimating entropy for high-dimensional neuronal data. Finally, we discuss strategies to overcome these challenges, including dimensionality reduction techniques, advanced entropy estimators, sparse coding schemes, and the integration of machine learning approaches. Thus, this work summarizes the most recent developments on how entropy measures contribute to our understanding of principles underlying neural coding.
Efficient Search Algorithms for Identifying Synergistic Associations in High-Dimensional Datasets
Authors: Hourican Cillian , Li Jie , Mishra Pashupati P. , Lehtimäki Terho , Mishra Binisha H. , Kähönen Mika , Raitakari Olli T. , Laaksonen Reijo , Keltikangas-Järvinen Liisa , Juonala Markus , Quax Rick
Published: November 2024

In recent years, there has been a notably increased interest in the study of multivariate interactions and emergent higher-order dependencies. This is particularly evident in the context of identifying synergistic sets, which are defined as combinations of elements whose joint interactions result in the emergence of information that is not present in any individual subset of those elements. The scalability of frameworks such as partial information decomposition (PID) and those based on multivariate extensions of mutual information, such as O-information, is limited by combinational explosion in the number of sets that must be assessed. In order to address these challenges, we propose a novel approach that utilises stochastic search strategies in order to identify synergistic triplets within datasets. Furthermore, the methodology is extensible to larger sets and various synergy measures. By employing stochastic search, our approach circumvents the constraints of exhaustive enumeration, offering a scalable and efficient means to uncover intricate dependencies. The flexibility of our method is illustrated through its application to two epidemiological datasets: The Young Finns Study and the UK Biobank Nuclear Magnetic Resonance (NMR) data. Additionally, we present a heuristic for reducing the number of synergistic sets to analyse in large datasets by excluding sets with overlapping information. We also illustrate the risks of performing a feature selection before assessing synergistic information in the system.
Complexity and Variation in Infectious Disease Birth Cohorts: Findings from HIV+ Medicare and Medicaid Beneficiaries, 1999–2020
Authors: Williams Nick
Published: November 2024

The impact of uncertainty in information systems is difficult to assess, especially when drawing conclusions from human observation records. In this study, we investigate survival variation in a population experiencing infectious disease as a proxy to investigate uncertainty problems. Using Centers for Medicare and Medicaid Services claims, we discovered 1,543,041 HIV+ persons, 363,425 of whom were observed dying from all-cause mortality. Once aggregated by HIV status, year of birth and year of death, Age-Period-Cohort disambiguation and regression models were constructed to produce explanations of variance in survival. We used Age-Period-Cohort as an alternative method to work around under-observed features of uncertainty like infection transmission, receiver host dynamics or comorbidity noise impacting survival variation. We detected ages that have a consistent, disproportionate share of deaths independent of study year or year of birth. Variation in seasonality of mortality appeared stable in regression models; in turn, HIV cases in the United States do not have a survival gain when uncertainty is uncontrolled for. Given the information complexity issues under observed exposure and transmission, studies of infectious diseases should either include robust decedent cases, observe transmission physics or avoid drawing conclusions about survival from human observation records.
Monitoring Hazards in Dam Environments Using Remote Sensing Techniques: Case of Kulekhani-I Reservoir in Nepal
Authors: Rimal Bhagawat , Tiwary Abhishek
Published: November 2024

Maintaining the operability of a hydroelectric power station at a scale originally designed is being compromised by continuous reservoir sedimentation. The underlying factors include a complex mix of landscape alterations owing to natural and anthropogenic activities around dam areas, such as gully erosion, landslides, floods triggered by heavy rainfall, climate change, and construction activities. The hydropower projects in the low-to-mid mountain regions of Nepal are witnessing a combination of these phenomena, affecting their optimal performance in meeting long-term sustainable power supply targets. This paper presents a combination of geo-spatial analysis and field evaluations to identify the trends from Kulekhani-I, one of the oldest storage-type hydropower projects in Nepal, using long-term time series remote sensing satellite imagery from 1988 to 2020. Our analysis shows an expansion of the surface water content area over time, attributed mainly to high sedimentation deposition owing to multiple factors. This study has identified an urgent need for addressing the following two key contributory factors through an effective control mechanism to avoid rapid sedimentation in the reservoirs: natural—landslides and floods leading to mainly silt deposition during heavy rainfalls; and anthropogenic—road construction materials dumped directly in the reservoir. Effective implementation of a remote sensing monitoring scheme can safeguard future damages to dam environments of more recently built storage-type hydropower projects.
The Effect of Diabetes Mellitus Severity on Foot & Ankle Burn Recovery
Authors: McCown Sheldon A. , Walters Elliot T. , Palackic Alen , Franco-Mesa Camila , Davis Ashton R. , Keys Phillip H. , Song Juquan , Wolf Steven E.
Published: November 2024

Background: Diabetic patients often present with complex limb pathology, resulting in impaired sensation in the distal extremities making tactile injuries such as burns difficult to notice. We posit that poorly controlled diabetes mellitus, evidenced by increasing elevations in hemoglobin A1c, is associated with delayed wound healing and increased complications in burn patients. Methods: The TriNetX Network, a database of 89 million patients across the U.S., was queried for diabetic patients with foot and ankle burns. Patients were divided into four groups based on A1c: properly controlled (<7%), moderately controlled (7–9%), poorly controlled (>9%), and propensity-matched non-diabetic controls. Evaluated outcomes included split-thickness skin grafting, infections, amputations, acute kidney failure (AKF), and mortality within one month of the burn. Results: When comparing the poorly controlled A1c cohort with the properly controlled and moderately controlled A1c cohorts, we found a significant increase in amputations (p = 0.042) and cutaneous infections (p = 0.0438), respectively. When evaluating non-diabetics to diabetic patients, significantly increased rates of amputations (p < 0.0001), cutaneous infections (p = 0.0485), systemic infections (p = 0.0066), and AKF (p = 0.0005) were noted in the latter. Conclusions: Poorly controlled diabetes shows a significant correlation with increased complications following foot and ankle burns, including amputations, infections, and AKF.
Forecasting Wind–Photovoltaic Energy Production and Income with Traditional and ML Techniques
Authors: Masala Giovanni , Schischke Amelie
Published: November 2024

Hybrid production plants harness diverse climatic sources for electricity generation, playing a crucial role in the transition to renewable energies. This study aims to forecast the profitability of a combined wind–photovoltaic energy system. Here, we develop a model that integrates predicted spot prices and electricity output forecasts, incorporating relevant climatic variables to enhance accuracy. The jointly modeled climatic variables and the spot price constitute one of the innovative aspects of this work. Regarding practical application, we considered a hypothetical wind–photovoltaic plant located in Italy and used the relevant climate series to determine the quantity of energy produced. We forecast the quantity of energy as well as income through machine learning techniques and more traditional statistical and econometric models. We evaluate the results by splitting the dataset into estimation windows and test windows, and using a backtesting technique. In particular, we found evidence that ML regression techniques outperform results obtained with traditional econometric models. Regarding the models used to achieve this goal, the objective is not to propose original models but to verify the effectiveness of the most recent machine learning models for this important application, and to compare them with more classic linear regression techniques.
Pop Culture Media as Curricular Text: Designing an Interdisciplinary Undergraduate Seminar Using Abbott Elementary
Authors: Jones Sara , Some Kountiala J.
Published: November 2024

Abbott Elementary, the Emmy-award winning mockumentary-style comedy television show, chronicles the day-to-day efforts of a group of teachers in a Philadelphia public elementary school who, despite the odds stacked against them, are determined to help their students succeed. With humor and heart, the show also uncovers some of the larger policy issues at play in U.S. urban public education, such as teacher shortages, school funding, and school choice. This essay describes the development of an interdisciplinary Honors seminar for undergraduate students at a large, public university in the Midwest U.S. that used episodes of Abbott Elementary as a central curricular text to support students in analyzing current policy issues in urban education. Drawing on Giroux’s concept of media as public pedagogy, this essay details how the course design employed a critical intersectional multiculturalism cultural studies approach to create opportunities for students to engage in a multiperspectival analysis, including (1) an understanding of political culture, (2) textual analysis, and (3) audience reception. Implications and recommendations are made for selecting and integrating popular culture media as curricular text in interdisciplinary coursework.
Addressing the Sense of School Belonging Among All Students? A Systematic Literature Review
Authors: Štremfel Urška , Šterman Ivančič Klaudija , Peras Igor
Published: November 2024

The sense of school belonging plays an important role in students’ academic, behavioural, and psychological outcomes. Based on a systematic review, following the PRISMA 2020 guidelines and examining 86 studies conducted between 1990 and February 2023, the article addresses two research questions: (a) what are the predictors of the sense of school belonging at the individual, micro, meso, exo, macro, and chrono levels of the bioecological model of human development; (b) do these predictors differ based on students’ individual characteristics, and if so, how. The findings reveal individual factors as important predictors of school belonging and indicate the lack of studies that take into consideration the interplay of different (micro, meso, exo, macro, chrono) levels in addressing the sense of school belonging. Considering the complexity and multi-factorial nature of the sense of school belonging, it calls upon further research, which would support the development of evidence-based interventions for fostering school belonging among different groups of students, particularly those who are at risk of feeling alienated from school, and thus promote equity in education.