bluuebunny/crossref_metadata_2025 huggingface dataset:
Diabetic Keratopathy: Redox Signaling Pathways and Therapeutic Prospects
Authors: Buonfiglio Francesco , Wasielica-Poslednik Joanna , Pfeiffer Norbert , Gericke Adrian
Published: January 2024

Diabetes mellitus, the most prevalent endocrine disorder, not only impacts the retina but also significantly involves the ocular surface. Diabetes contributes to the development of dry eye disease and induces morphological and functional corneal alterations, particularly affecting nerves and epithelial cells. These changes manifest as epithelial defects, reduced sensitivity, and delayed wound healing, collectively encapsulated in the context of diabetic keratopathy. In advanced stages of this condition, the progression to corneal ulcers and scarring further unfolds, eventually leading to corneal opacities. This critical complication hampers vision and carries the potential for irreversible visual loss. The primary objective of this review article is to offer a comprehensive overview of the pathomechanisms underlying diabetic keratopathy. Emphasis is placed on exploring the redox molecular pathways responsible for the aberrant structural changes observed in the cornea and tear film during diabetes. Additionally, we provide insights into the latest experimental findings concerning potential treatments targeting oxidative stress. This endeavor aims to enhance our understanding of the intricate interplay between diabetes and ocular complications, offering valuable perspectives for future therapeutic interventions.
Short-Time Alternating Current Electrical Stimulation and Cell Membrane-Related Components
Authors: Buenning Maren E. , Bielfeldt Meike , Nebe Barbara , Staehlke Susanne
Published: January 2024

Electrical stimulation (ES) and its effects on biological systems is an area of research in regenerative medicine. The focus here is on the mechanism of action of ES on cell membrane-related components. A short alternating current (AC) stimulation (10 min) was applied on suspended human MG-63 osteoblasts via a commercially available multi-channel system (IonOptix). The pulsed ES with 1 V or 5 V and frequencies of 20 Hz on cells was performed immediately after cell seeding. The in vitro investigations were conducted by microscopy, flow cytometry, and particle analysis via a Litesizer within 24 h. The short-time ES with the parameter 1 V and 20 Hz was beneficial for the process of cell attachment, which could be related to an enhanced deposition of fibronectin on the glass bottom from the protein-containing medium (10% FBS). The MG-63 cells’ spherical coat hyaluronan remained constant and did not contribute to this AC-triggered adhesion. In this context, the cells’ zeta potential also did not play a role. The membrane potential analyzed via DiBAC4(3) was unchanged. Only the aquaporin channel AQP 8 in the cell membrane was significantly enhanced. Suspended cells in an AC electric field were activated during their settlement, and the fibronectin adsorption on the bottom contributed to this effect but not the membrane-related components.
A Methodology for Knowledge Discovery in Labeled and Heterogeneous Graphs
Authors: Ortega-Guzmán Víctor H. , Gutiérrez-Preciado Luis , Cervantes Francisco , Alcaraz-Mejia Mildreth
Published: January 2024

Graph mining has emerged as a significant field of research with applications spanning multiple domains, including marketing, corruption analysis, business, and politics. The exploration of knowledge within graphs has garnered considerable attention due to the exponential growth of graph-modeled data and its potential in applications where data relationships are a crucial component, and potentially being even more important than the data themselves. However, the increasing use of graphs for data storing and modeling presents unique challenges that have prompted advancements in graph mining algorithms, data modeling and storage, query languages for graph databases, and data visualization techniques. Despite there being various methodologies for data analysis, they predominantly focus on structured data and may not be optimally suited for highly connected data. Accordingly, this work introduces a novel methodology specifically tailored for knowledge discovery in labeled and heterogeneous graphs (KDG), and it presents three case studies demonstrating its successful application in addressing various challenges across different application domains.
Mini-Implant Insertion Using a Guide Manufactured with Computer-Aided Design and Computer-Aided Manufacturing in an Adolescent Patient Suffering from Tooth Eruption Disturbance
Authors: Weismann Christina , Heise Kathrin , Aretxabaleta Maite , Cetindis Marcel , Koos Bernd , Schulz Matthias C.
Published: January 2024

Due to dental diseases, anatomical restrictions, and mixed dentition, the reduction in the number of teeth and the displacement of tooth germs pose challenges in orthodontic treatment, limiting anchorage options. The presented case demonstrates an advanced treatment solution using digital CAD/CAM-technologies and medical imaging for the creation of a mini-implant template. A 12-year-old male patient experiencing delayed tooth eruption, multiple impacted germs, and maxillary constriction underwent intraoral scanning and CBCT. Utilizing coDiagnostiXTM Version 10.2 software, the acquired data were merged to determine the mini-implant placement and to design the template. The template was then manufactured through stereolithography using surgical-guide material. Mini-implants were inserted using the produced appliance, enabling safe insertion by avoiding vital structures. Surgically exposed displaced teeth were aligned using a Hyrax screw appliance anchored on the mini-implants for rapid palatal expansion (RPE) and subsequently used as fixed orthodontics to align impacted teeth. The screw was activated daily for 10 weeks, resulting in a 7 mm posterior and 5 mm anterior maxillary transversal increase. Skeletal anchorage facilitated simultaneous RPE and tooth alignment, ensuring accuracy, patient safety, and appliance stability. The presented case shows a scenario in which computer-aided navigation for mini-implant positioning can enhance precision and versatility in challenging anatomical cases.
Quantitive Assessment of Gustatory Function and Its Association with Demographics, and Systemic Morbidity
Authors: Aframian Doron J. , Zedan Alaa , Agbariah Weaam , Rettman Andra , Almoznino Galit
Published: January 2024

This study aimed to analyze the associations of gustatory dysfunction as measured by validated taste strips with demographics and co-morbidities. This cross-sectional study retrospectively analyzed records of patients who attended the Orofacial Chemosensory Center of Hadassah Medical Center between 2017 and 2020. Taste strips were used as a validated method to determine taste dysfunction. A total of 272 subjects were included, 137 (50.4%) women and 135 (49.6%) men, with a mean age of 53.5 ± 19.3 years and age range of 18–98 years. The total taste score among the study population was 8.53 ± 4.03 (scale range 0–16). Age had a significant negative correlation with the total taste score (p = 0.001), and men exhibited worse total (p < 0.001), salty (p = 0.003), and bitter (p < 0.001) scores. Major trauma was associated with worse total (p < 0.001) and specialized taste assessments (sweet (p = 0.001), sour (p = 0.002), salty (p = 0.016), and bitter (p < 0.001)). Chemotherapy was associated with reduced total (p < 0.001), salty (p = 0.003), and bitter (p = 0.001) taste scores. Zinc deficiency exhibited worse salty (p = 0.027) and total (p = 0.038) taste scores. Patients with burning mouth syndrome (BMS) showed higher salty scores (p = 0.017). Patients who experienced exposure to toxic chemicals exhibited worse salty scores (p = 0.024). We conclude that gustatory dysfunction is associated with older age, male sex, and co-morbidities of major trauma, current chemotherapy, zinc deficiency, BMS, and exposure to toxins. The study highlights the importance of systemic evaluation and quantitive gustatory dysfunction assessment as part of the diagnostic process of patients with subjective complaints of taste disorders.
Moderate-High Blood Eosinophilia Is Associated with Increased Hospitalization and Other Asthma Comorbidities
Authors: Naharro-González Sara , Lorente-Sorolla Clara , Rodrigo-Muñoz José Manuel , Valverde-Monge Marcela , Pinillos-Robles Erwin Javier , Betancor Diana , Fernández-Nieto Mar , Sánchez-Mellado Diana , Gil-Martínez Marta , Santillán-Coello Jessica Mireya , Villacampa-Aubá José Miguel , Mahillo-Fernandez Ignacio , Herrero-González Antonio , Perez-González Alejandro , Rodríguez-Nieto María Jesús , del Pozo Victoria
Published: January 2024

(1) Background: Eosinophilia has traditionally been linked to eosinophilic asthma, for which it is the gold-standard prognostic biomarker. However, the association between eosinophilia and the presence of other diseases and comorbidities is yet unclear. (2) Methods: For this retrospective study, we reviewed the electronic medical records of 49,909 subjects with blood eosinophilia to gather data on the presence of asthma, COPD, sleep apnea, tuberculosis, dyslipidemia, hypertension, and other cardiovascular diseases and severe CRSwNP among these subjects. Demographic features including age, sex, and smoking habits were collected, as well as the number of hospitalizations and emergency department visits. T-tests, ANOVA, Fisher test, and logistic regression models were used. (3) Results: For all age groups studied, eosinophilia was significantly more prevalent among asthmatic subjects than nonasthmatics, especially in patients also presenting CRSwNP, hypertension, and dyslipidemia. The likelihood of developing asthma, COPD, and CRSwNP, and hospitalization, was increased when BEC was above 600 eosinophils/μL. The association between asthma, CRSwNP, and BEC was corroborated by multiple logistic regressions models. (4) Conclusions: We demonstrated the association of having over 600 blood eosinophils/μL with a higher number of hospitalizations and comorbidities (CRSwNP and COPD), which proves that BEC is a highly useful parameter to consider in subjects who present blood eosinophilia.
Selenium-Containing (Hetero)Aryl Hybrids as Potential Antileishmanial Drug Candidates: In Vitro Screening against L. amazonensis
Authors: Fermiano Maria Helena , das Neves Amarith Rodrigues , da Silva Fernanda , Barros Manuella Salustiano Andrade , Vieira Camila Barbosa , Stein André L. , Frizon Tiago Elias Allievi , Braga Antonio Luiz , de Arruda Carla Cardozo Pinto , Parisotto Eduardo Benedetti , Saba Sumbal , Rafique Jamal , Riul Thalita Bachelli
Published: January 2024

Leishmaniasis remains a significant global health concern, with current treatments relying on outdated drugs associated with high toxicity, lengthy administration, elevated costs, and drug resistance. Consequently, the urgent need for safer and more effective therapeutic options in leishmaniasis treatment persists. Previous research has highlighted selenium compounds as promising candidates for innovative leishmaniasis therapy. In light of this, a library of 10 selenium-containing diverse compounds was designed and evaluated in this study. These compounds included selenium-substituted indole, coumarin, chromone, oxadiazole, imidazo[1,2-a]pyridine, Imidazo[2,1-b]thiazole, and oxazole, among others. These compounds were screened against Leishmania amazonensis promastigotes and intracellular amastigotes, and their cytotoxicity was assessed in peritoneal macrophages, NIH/3T3, and J774A.1 cells. Among the tested compounds, MRK-106 and MRK-108 displayed the highest potency against L. amazonensis promastigotes with reduced cytotoxicity. Notably, MRK-106 and MRK-108 exhibited IC50 values of 3.97 µM and 4.23 µM, respectively, and most of the tested compounds showed low cytotoxicity in host cells (CC50 > 200 µM). Also, compounds MRK-107 and MRK-113 showed activity against intracellular amastigotes (IC50 18.31 and 15.93 µM and SI 12.55 and 10.92, respectively). In conclusion, the identified selenium-containing compounds hold potential structures as antileishmanial drug candidates to be further explored in subsequent studies. These findings represent a significant step toward the development of safer and more effective therapies for leishmaniasis, addressing the pressing need for novel and improved treatments.
T Cell-Induced Colitis Is Exacerbated by Prolonged Stress: A Comparison in Male and Female Mice
Authors: Maltz Ross M. , Marte-Ortiz Pedro , McClinchie Madeline G. , Hilt Miranda E. , Bailey Michael T.
Published: January 2024

Psychological stress exposure is well recognized to exacerbate inflammatory bowel disease (IBD) but the mechanisms involved remain poorly understood. In this study, chronic T cell-mediated colitis was induced by adoptively transferring CD4+CD45RBhigh splenic T cells from C57BL/6 WT donor mice into Rag1tm1Mom mice. Two weeks after T cell transfer, mice were exposed to a prolonged restraint stressor (RST) for 8 h per day for 6 consecutive days. The colitis phenotype was assessed via histopathology and semi-quantitative rt-PCR at humane endpoints or 10 weeks post-T-cell transfer. Mice that received the T cell transplant developed chronic colitis marked by increases in colonic histopathology and inflammatory cytokines. Colonic histopathology was greater in males than females regardless of RST exposure but RST exposure increased histopathology scores in females such that they reached scores observed in the males. This pattern was consistent with cytokine gene expression and protein levels in the colon (especially for IFN-γ, IL-17A, and TNF-α). Serum cytokine levels were not strongly affected by exposure to the stressor. Using a murine model of chronic T cell-mediated colitis, this study demonstrates that biological sex strongly influences colonic inflammation and exposure to chronic stress has a more pronounced effect in females than in males.
Expression of the Pro-Fibrotic Marker Periostin in a Mouse Model of Duchenne Muscular Dystrophy
Authors: Trundle Jessica , Cernisova Viktorija , Boulinguiez Alexis , Lu-Nguyen Ngoc , Malerba Alberto , Popplewell Linda
Published: January 2024

Duchenne muscular dystrophy (DMD) is characterised by fibrotic tissue deposition in skeletal muscle. We assessed the role of periostin in fibrosis using mdx mice, an established DMD murine model, for which we conducted a thorough examination of periostin expression over a year. RNA and protein levels in diaphragm (DIA) muscles were assessed and complemented by a detailed histological analysis at 5 months of age. In dystrophic DIAs, periostin (Postn) mRNA expression significantly exceeded that seen in wildtype controls at all timepoints analysed, with the highest expression at 5 months of age (p < 0.05). We found Postn to be more consistently highly expressed at the earlier timepoints compared to established markers of fibrosis like transforming growth factor-beta 1 (Tgf-β1) and connective tissue growth factor (Ctgf). Immunohistochemistry confirmed a significantly higher periostin protein expression in 5-month-old mdx mice compared to age-matched healthy controls (p < 0.01), coinciding with a significant fibrotic area percentage (p < 0.0001). RT-qPCR also indicated an elevated expression of Tgf-β1, Col1α1 (collagen type 1 alpha 1) and Ctgf in mdx DIAs compared to wild type controls (p < 0.05) at 8- and 12-month timepoints. Accordingly, immunoblot quantification demonstrated elevated periostin (3, 5 and 8 months, p < 0.01) and Tgf-β1 (8 and 12 months, p < 0.001) proteins in the mdx muscle. These findings collectively suggest that periostin expression is a valuable marker of fibrosis in this relevant model of DMD. They also suggest periostin as a potential contributor to fibrosis development, with an early onset of expression, thereby offering the potential for timely therapeutic intervention and its use as a biomarker in muscular dystrophies.
Current Technologies and Future Perspectives in Immunotherapy towards a Clinical Oncology Approach
Authors: Adhikary Subhamay , Pathak Surajit , Palani Vignesh , Acar Ahmet , Banerjee Antara , Al-Dewik Nader I. , Essa Musthafa Mohamed , Mohammed Sawsan G. A. A. , Qoronfleh M. Walid
Published: January 2024

Immunotherapy is now established as a potent therapeutic paradigm engendering antitumor immune response against a wide range of malignancies and other diseases by modulating the immune system either through the stimulation or suppression of immune components such as CD4+ T cells, CD8+ T cells, B cells, monocytes, macrophages, dendritic cells, and natural killer cells. By targeting several immune checkpoint inhibitors or blockers (e.g., PD-1, PD-L1, PD-L2, CTLA-4, LAG3, and TIM-3) expressed on the surface of immune cells, several monoclonal antibodies and polyclonal antibodies have been developed and already translated clinically. In addition, natural killer cell-based, dendritic cell-based, and CAR T cell therapies have been also shown to be promising and effective immunotherapeutic approaches. In particular, CAR T cell therapy has benefited from advancements in CRISPR-Cas9 genome editing technology, allowing the generation of several modified CAR T cells with enhanced antitumor immunity. However, the emerging SARS-CoV-2 infection could hijack a patient’s immune system by releasing pro-inflammatory interleukins and cytokines such as IL-1β, IL-2, IL-6, and IL-10, and IFN-γ and TNF-α, respectively, which can further promote neutrophil extravasation and the vasodilation of blood vessels. Despite the significant development of advanced immunotherapeutic technologies, after a certain period of treatment, cancer relapses due to the development of resistance to immunotherapy. Resistance may be primary (where tumor cells do not respond to the treatment), or secondary or acquired immune resistance (where tumor cells develop resistance gradually to ICIs therapy). In this context, this review aims to address the existing immunotherapeutic technologies against cancer and the resistance mechanisms against immunotherapeutic drugs, and explain the impact of COVID-19 on cancer treatment. In addition, we will discuss what will be the future implementation of these strategies against cancer drug resistance. Finally, we will emphasize the practical steps to lay the groundwork for enlightened policy for intervention and resource allocation to care for cancer patients.
Dr. Tetsuro Fujiwara—My Memories from the Early Days of Dr. Fujiwara’s Research
Authors: Jobe Alan H.
Published: January 2024

This brief commentary honors Dr. Tesuro Fujiwara, the first person to treat infants with respiratory distress syndrome by instilling surfactant into their trachea. In the 1960s, mortality from RDS, which could only be treated with oxygen, was about 50 percent. Based on the physiology Fujiwara learned that lung immaturity could be treated with doses of surfactant from animals in sheep models. He then made a surfactant from cow lungs called Servanta and treated 10 infants with RDS, who all had a large improvement in oxygenation. Other new therapies, such as continuous positive airway pressure and newer infant ventilators—in combination with surfactant therapy have decreased infant mortality to less than 1% from RDS in the most recent US infant death statistics.
Automatic Quantitative Assessment for Diagnostic and Therapeutic Response in Rodent Myocardial Infarct Model
Authors: Kim Kangsan , Lee Yong Jin , Kim Min Hwan , Byun Byung Hyun , Woo Sang-Keun
Published: January 2024

The purpose of this study was to investigate the most appropriate methodological approach for the automatic measurement of rodent myocardial infarct polar map using histogram-based thresholding and unsupervised deep learning (DL)-based segmentation. A rat myocardial infarction model was induced by ligation of the left coronary artery. Positron emission tomography (PET) was performed 60 min after the administration of 18F-fluoro-deoxy-glucose (18F-FDG), and PET was performed after injecting 64Cu-pyruvaldehyde-bis(N4-methylthiosemicarbazone). Single photon emission computed tomography was performed 60 min after injection of 99mTc-hexakis-2-methoxyisobutylisonitrile and 201Tl. Delayed contrast-enhanced magnetic resonance imaging was performed after injecting Gd-DTPA-BMA. Three types of thresholding methods (naive thresholding, Otsu’s algorithm, and multi-Gaussian mixture model (MGMM)) were used. DL segmentation methods were based on a convolution neural network and trained with constraints on feature similarity and spatial continuity of the response map extracted from images by the network. The relative infarct sizes measured by histology and estimated R2 for 18F-FDG were 0.8477, 0.7084, 0.8353, and 0.9024 for naïve thresholding, Otsu’s algorithm, MGMM, and DL segmentation, respectively. DL-based method improved the accuracy of MI size assessment.
Microbiota Implications in Endocrine-Related Diseases: From Development to Novel Therapeutic Approaches
Authors: Clemente-Suárez Vicente Javier , Redondo-Flórez Laura , Rubio-Zarapuz Alejandro , Martín-Rodríguez Alexandra , Tornero-Aguilera José Francisco
Published: January 2024

This comprehensive review article delves into the critical role of the human microbiota in the development and management of endocrine-related diseases. We explore the complex interactions between the microbiota and the endocrine system, emphasizing the implications of microbiota dysbiosis for the onset and progression of various endocrine disorders. The review aims to synthesize current knowledge, highlighting recent advancements and the potential of novel therapeutic approaches targeting microbiota-endocrine interactions. Key topics include the impact of microbiota on hormone regulation, its role in endocrine pathologies, and the promising avenues of microbiota modulation through diet, probiotics, prebiotics, and fecal microbiota transplantation. We underscore the importance of this research in advancing personalized medicine, offering insights for more tailored and effective treatments for endocrine-related diseases.
A Cluster-Type Self-Healing Catalyst for Stable Saline–Alkali Water Splitting
Authors: Wang Haiming , Chen Sheng
Published: January 2024

In electrocatalytic processes, traditional powder/film electrodes inevitably suffer from damage or deactivation, reducing their catalytic performance and stability. In contrast, self-healing electrocatalysts, through special structural design or composition methods, can automatically repair at the damaged sites, restoring their electrocatalytic activity. Here, guided by Pourbaix diagrams, foam metal was activated by a simple cyclic voltammetry method to synthesize metal clusters dispersion solution (MC/KOH). The metal clusters-modified hydroxylated Ni-Fe oxyhydroxide electrode (MC/NixFeyOOH) by a facile Ni-Fe metal–organic framework-reconstructed strategy, exhibiting superior performance toward the oxygen evolution reaction (OER) in the mixture of MC/KOH and saline–alkali water (MC/KOH+SAW). Specifically, using a nickel clusters-modified hydroxylated Ni-Fe oxyhydroxide electrode (NC/NixFeyOOH) for OER, the NC/NixFeyOOH catalyst has an ultra-low overpotential of 149 mV@10 mA cm−2, and durable stability of 100 h at 500 mA cm−2. By coupling this OER catalyst with an efficient hydrogen evolution reaction catalyst, high activity and durability in overall SAW splitting is exhibited. What is more, benefiting from the excellent fluidity, flexibility, and enhanced catalytic activity effect of the liquid NC, we demonstrate a self-healing electrocatalysis system for OER operated in the flowing NC/(KOH+SAW). This strategy provides innovative solutions for the fields of sustainable energy and environmental protection.
Correction: Nerdrum Aagaard et al. Significance of Neonatal Heart Rate in the Delivery Room—A Review. Children 2023, 10, 1551
Authors: Nerdrum Aagaard Ellisiv , Solevåg Anne Lee , Saugstad Ola Didrik
Published: January 2024

In the original publication [...]
Trait Anxiety, Emotion Regulation, and Metacognitive Beliefs: An Observational Study Incorporating Separate Network and Correlation Analyses to Examine Associations with Executive Functions and Academic Achievement
Authors: Cécillon François-Xavier , Mermillod Martial , Leys Christophe , Lachaux Jean-Philippe , Le Vigouroux Sarah , Shankland Rebecca
Published: January 2024

Trait anxiety, emotion regulation strategies, and metacognitive beliefs influence executive functions (EFs) and academic achievement. This study examines their interplay and impact on academic success. In total, 275 adolescents (10–17 years) and parents completed an online questionnaire assessing trait anxiety, emotion regulation strategies, metacognition, parent-reported behaviors related to executive functioning, and overall school average. Preliminary analyses confirmed consistency with the existing literature for each variable and their interaction. Furthermore, we conducted a network analysis among the main variables. This analysis supports the need to pay more attention to reflective variables—maladaptive emotion regulation strategies and metacognitive beliefs about worry—when studying trait anxiety. These variables were linked to problematic executive functioning in adolescents, and the latter was negatively linked to academic achievement. This study offers innovative insights by investigating relationships less explored in the scientific literature. It reveals high and significant correlations between metacognitive beliefs, maladaptive emotion regulation strategies, and trait anxiety (r > 0.500, p < 0.001) but also between these variables and both executive functioning and academic achievement. These findings offer new perspectives for research and underscore the importance of holistically examining the psychological factors related to academic success.
Investigating the Association between Serum and Hematological Biomarkers and Neonatal Sepsis in Newborns with Premature Rupture of Membranes: A Retrospective Study
Authors: Hincu Maura-Adelina , Zonda Gabriela-Ildiko , Vicoveanu Petronela , Harabor Valeriu , Harabor Anamaria , Carauleanu Alexandru , Melinte-Popescu Alina-Sînziana , Melinte-Popescu Marian , Mihalceanu Elena , Stuparu-Cretu Mariana , Vasilache Ingrid-Andrada , Nemescu Dragos , Paduraru Luminita
Published: January 2024

(1) Background: Neonatal early-onset sepsis (EOS) is associated with important mortality and morbidity. The aims of this study were to evaluate the association between serum and hematological biomarkers with early onset neonatal sepsis in a cohort of patients with prolonged rupture of membranes (PROM) and to calculate their diagnostic accuracy. (2) Methods: A retrospective cohort study was conducted on 1355 newborns with PROM admitted between January 2017 and March 2020, who were divided into two groups: group A, with PROM ≥ 18 h, and group B, with ROM < 18 h. Both groups were further split into subgroups: proven sepsis, presumed sepsis, and no sepsis. Descriptive statistics, analysis of variance (ANOVA) and a Random Effects Generalized Least Squares (GLS) regression were used to evaluate the data. (3) Results: The statistically significant predictors of neonatal sepsis were the high white blood cell count from the first (p = 0.005) and third day (p = 0.028), and high C-reactive protein (CRP) values from the first day (p = 0.004). Procalcitonin (area under the curve—AUC = 0.78) and CRP (AUC = 0.76) measured on the first day had the best predictive performance for early-onset neonatal sepsis. (4) Conclusions: Our results outline the feasibility of using procalcitonin and CRP measured on the first day taken individually in order to increase the detection rate of early-onset neonatal sepsis, in the absence of positive blood culture.
A Review of Uncertainties in Power Systems—Modeling, Impact, and Mitigation
Authors: Hu Hongji , Yu Samson S. , Trinh Hieu
Published: January 2024

A comprehensive review of uncertainties in power systems, covering modeling, impact, and mitigation, is essential to understand and manage the challenges faced by the electric grid. Uncertainties in power systems can arise from various sources and can have significant implications for grid reliability, stability, and economic efficiency. Australia, susceptible to extreme weather such as wildfires and heavy rainfall, faces vulnerabilities in its power network assets. The decentralized distribution of population centers poses economic challenges in supplying power to remote areas, which is a crucial consideration for the emerging technologies emphasized in this paper. In addition, the evolution of modern power grids, facilitated by deploying the advanced metering infrastructure (AMI), has also brought new challenges to the system due to the risk of cyber-attacks via communication links. However, the existing literature lacks a comprehensive review and analysis of uncertainties in modern power systems, encompassing uncertainties related to weather events, cyber-attacks, and asset management, as well as the advantages and limitations of various mitigation approaches. To fill this void, this review covers a broad spectrum of uncertainties considering their impacts on the power system and explores conventional robust control as well as modern probabilistic and data-driven approaches for modeling and correlating the uncertainty events to the state of the grid for optimal decision making. This article also investigates the development of robust and scenario-based operations, control technologies for microgrids (MGs) and energy storage systems (ESSs), and demand-side frequency control ancillary service (D-FCAS) and reserve provision for frequency regulation to ensure a design of uncertainty-tolerance power system. This review delves into the trade-offs linked with the implementation of mitigation strategies, such as reliability, computational speed, and economic efficiency. It also explores how these strategies may influence the planning and operation of future power grids.
Improving the Communication of Dental Findings in Pediatric Dentistry by Using Intraoral Scans as a Visual Aid: A Randomized Clinical Trial
Authors: Schulz-Weidner Nelly , Gruber Marina , Schraml Eva May , Wöstmann Bernd , Krämer Norbert , Schlenz Maximiliane Amelie
Published: January 2024

The aim of this first randomized clinical trial (RCT) was to determine whether intraoral scans (IOS) can be used as a visual aid to improve the communication of dental findings in pediatric dentistry. Therefore, 60 children (mean age 10.1 ± 3.3 years) and their accompanying parents/primary caregivers (PGs) were examined between July 2022 and February 2023. Patients were randomly allocated to two groups: half of the participants were informed of the children’s dental findings including treatment plans by verbal explanation alone (control group, n = 30), while the other half were informed using IOS (Trios 4, 3Shape) as a visual aid to support the verbal explanation (study group, n = 30). Both groups then completed a questionnaire regarding their children’s diagnosis, treatment needs, planned therapy, and oral hygiene. Statistical analysis was performed using a t-test (p < 0.05). Overall, there was a significant difference between the two groups (p < 0.001) in terms of understanding the current oral situation of their children. While 85.5 ± 17.3% (mean ± standard deviation) of the answers were correct in the study group, only 57.2 ± 17.8% of the participants in the control group were capable of answering the questions correctly. In particular, the control group had difficulties answering the questions about treatment needs and therapy correctly. Within the limitations of this first pilot study, IOS can be clearly recommended as a visual aid to improve the communication of dental findings with PGs in pediatric dentistry.
Agricultural Produce Supply Chain Network of Capsicum: Empirical Evidence from India
Authors: Thakur Pankaj , Mehta Piyush , Lal Priyanka , Chaudhary Rashmi , Pani Saswat Kumar , Singh Akash Gaurav , Devi Chhaya , Verma Kamlesh , Sharma Prashant
Published: January 2024

Vegetables are important for both nutritional and economic stability and contribute significantly to the agricultural landscape of India. The demand for vegetables is rising, driven by population growth and increased awareness of their benefits. This empirical study highlights the dynamics of agricultural production supply chain networks of capsicum crops in the northwestern Himalayan region, specifically Himachal Pradesh, India. The study employs the Acharya approach to analyse the various marketing channels utilized by farmers in the capsicum supply chain. This methodology sheds light on the economic nuances at each stage and examines marketing channels, costs, margins, price spread and marketing efficiency. Simultaneously, the Garrett ranking method is applied to discern and prioritize constraints faced by farmers. This comprehensive approach ensures a nuanced understanding of the economic and logistical intricacies of capsicum marketing. The analysis of marketing channels reveals five distinct pathways employed by farmers, with Channel-C (Producer–Commission Agent–Retailer–Consumer) standing out as the most dominant, representing 47.25% of the total quantity. Moreover, Channel-A (Producer–Consumer) proves to be the most cost-effective for producers and boasts the highest producer price, while Channel-C, involving commission agents, incurs higher costs. This suggests a preference for intermediaries, emphasizing factors like market access and negotiation skills, whereas Channel-D (Producer–Local Trader–Wholesaler–Retailer–Consumer) has the highest gross marketing margin, emphasizing the trade-offs between efficiency and transaction volume. The results indicate that while Channel-A is the most efficient, it is not the preferred choice due to the lower transaction quantity. Further, the absence of market consultation services, inadequate road infrastructure, high commission charges, nonremunerative prices and untimely availability of vehicles are the major constraints in marketing. The findings of the study call for targeted interventions to create a more robust and farmer-friendly marketing environment for capsicum crops in the region. The study proposes targeted recommendations, emphasizing collaborative efforts between stakeholders, government bodies and farmers. This research contributes to the academic discourse and also offers actionable insights for researchers and policymakers, fostering sustainability, profitability and equity within the capsicum supply chain.
Nonintrusive Load Monitoring (NILM) Using a Deep Learning Model with a Transformer-Based Attention Mechanism and Temporal Pooling
Authors: Irani Azad Mohammad , Rajabi Roozbeh , Estebsari Abouzar
Published: January 2024

Nonintrusive load monitoring (NILM) is an important technique for energy management and conservation. In this paper, a deep learning model based on an attention mechanism, temporal pooling, residual connections, and transformers is proposed. This article presents a novel approach for NILM to accurately discern energy consumption patterns of individual household appliances. The proposed method entails a sequence of layers, including encoders, transformers, attention, temporal pooling, and residual connections, offering a comprehensive solution for NILM while effectively capturing appliance-specific energy usage in a household. The proposed model was evaluated using UK-DALE, REDD, and REFIT datasets in both seen and unseen cases. It shows that the proposed model in this paper performs better than other methods stated in other papers in terms of F1-score and total error of the results (in terms of SAE). This model achieved an F1-score equal to 92.96 as well as a total SAE equal to −0.036, which shows its effectiveness in accurately diagnosing and estimating the energy consumption of individual home appliances. The findings of this research show that the proposed model can be a tool for energy management in residential and commercial buildings.
One-Stage Small Object Detection Using Super-Resolved Feature Map for Edge Devices
Authors: Huynh Xuan Nghia , Jung Gu Beom , Suhr Jae Kyu
Published: January 2024

Despite the achievements of deep neural-network-based object detection, detecting small objects in low-resolution images remains a challenging task due to limited information. A possible solution to alleviate the issue involves integrating super-resolution (SR) techniques into object detectors, particularly enhancing feature maps for small-sized objects. This paper explores the impact of high-resolution super-resolved feature maps generated by SR techniques, especially for a one-stage detector that demonstrates a good compromise between detection accuracy and computational efficiency. Firstly, this paper suggests the integration of an SR module named feature texture transfer (FTT) into the one-stage detector, YOLOv4. Feature maps from the backbone and the neck of vanilla YOLOv4 are combined to build a super-resolved feature map for small-sized object detection. Secondly, it proposes a novel SR module with more impressive performance and slightly lower computation demand than the FTT. The proposed SR module utilizes three input feature maps with different resolutions to generate a super-resolved feature map for small-sized object detection. Lastly, it introduces a simplified version of an SR module that maintains similar performance while using only half the computation of the FTT. This attentively simplified module can be effectively used for real-time embedded systems. Experimental results demonstrate that the proposed approach substantially enhances the detection performance of small-sized objects on two benchmark datasets, including a self-built surveillance dataset and the VisDrone2019 dataset. In addition, this paper employs the proposed approach on an embedded system with a Qualcomm QCS610 and demonstrates its feasibility for real-time operation on edge devices.
Fast and Energy-Efficient Oblique Decision Tree Implementation with Potential Error Detection
Authors: Lim Chungsoo
Published: January 2024

In the contemporary landscape, with the proliferation of cyber-physical systems and the Internet of Things, intelligent embedded systems have become ubiquitous. These systems derive their intelligence from machine learning algorithms that are integrated within them. Among many machine learning algorithms, decision trees are often favored for implementation in such systems due to their simplicity and commendable classification performance. In this regard, we have proposed the efficient implementations of a fixed-point decision tree tailored for embedded systems. The proposed approach begins by identifying an input vector that might be classified differently by a fixed-point decision tree than by a floating-point decision tree. Upon identification, an error flag is activated, signaling a potential misclassification. This flag serves to bypass or disable the subsequent classification procedures for the identified input vector, thereby conserving energy and reducing classification latency. Subsequently, the input vector is alternatively classified based on class probabilities gathered during the training phase. In comparison with traditional fixed-point implementations, our proposed approach is proven to be 23.9% faster in terms of classification speed, consuming 11.5% less energy without compromising classification accuracy. The proposed implementation, if adopted in a smart embedded device, can provide a more responsive service to its users as well as longer battery life.
Over-Current Capability of Silicon Carbide and Silicon Devices for Short Power Pulses with Copper and Phase Change Materials below the Chip
Authors: Bhadoria Shubhangi , Dijkhuizen Frans , Zhang Xu , Ran Li , Nee Hans-Peter
Published: January 2024

An increasing share of fluctuating and intermittent renewable energy sources can cause over-currents (OCs) in the power system. The heat generated during OCs increases the junction temperature of semiconductor devices and could even lead to thermal runaway if thermal limits are reached. In order to keep the junction temperature within the thermal limit of the semiconductor, the power module structure with heat-absorbing material below the chip is investigated through COMSOL Multiphysics simulations. The upper limits of the junction temperature for Silicon (Si) and Silicon Carbide (SiC) are assumed to be 175 and 250 ∘C, respectively. The heat-absorbing materials considered for analysis are a copper block and a copper block with phase change materials (PCMs). Two times, three times, and four times of OCs would be discussed for durations of a few hundred milliseconds and seconds. This article also discusses the thermal performance of a copper block and a copper block with PCMs. PCMs used for Si and SiC are LM108 and Lithium, respectively. It is concluded that the copper block just below the semiconductor chip would enable OC capability in Si and SiC devices and would be more convenient to manufacture as compared to the copper block with PCM.
Membrane CO2 Separation System Improvement for Coal-Fired Power Plant Integration
Authors: Alabid Maytham , Dinca Cristian
Published: January 2024

Even though there are numerous CO2 capture technologies (such as chemical and physical absorption), investigators are still trying to come up with novel methods that can minimize the energy requirements for their integration into thermal power plants, as well as the CAPEX and OPEX expenses. In this work, the technical and financial aspects of integrating two-stage polymeric membranes into a coal-fired power plant with a capacity of 330 MW were examined. The study researched the membrane post-combustion CO2 capture process utilizing CHEMCAD version 8.1 software with several parameters and an expander to decrease the total cost. The simulation showed promising results regarding reducing power consumption after using an expander for both a high capture rate (>90%) and a CO2 concentration of more than 95%. Thus, the CO2 captured cost decreased from 58.4 EUR/t (no expander) to 48.7 EUR/t (with expander).
DC Active Damper Control Strategy Based on Resonance Suppression Effectiveness Evaluation Method
Authors: Zhang Huaying , Wang Yingxin , Zhu Xinyi , Xu Yonghai , Tao Shun
Published: January 2024

With the complication of the power system, features of the resonance interaction behave diversely and pose a threat to the effectiveness of the resonance suppression strategies. Existing resonance suppression strategies are usually designed for specific scenarios which are in close correlation with the impedance frequency-amplitude distribution, and their adaptability under different scenarios is hard to evaluate. In this paper, the resonance suppression domain of a DC distribution network is derived based on the node impedance variation before/after the resonance is suppressed. The derived criterion takes the admittance change of the resonance suppression strategies as variables, and the conservative/ideal suppression domain criteria are defined. On this basis, a method for evaluating the effectiveness of resonance suppression strategies is proposed, which simplifies the evaluation process and avoids a complicated matrix inverse process to each resonance suppression strategy during the system impedance calculation. Furthermore, a DC active damper control strategy based on the resonance suppression strategy evaluation is proposed, and the proposed strategy could suppress resonances under different scenarios by a targeted design of the reshaping admittance parameters. Time domain simulations with a 5-node distribution network are carried out to verify the proposed method.
A Parametric 3D Model of Human Airways for Particle Drug Delivery and Deposition
Authors: Geronzi Leonardo , Fanni Benigno Marco , De Jong Bart , Roest Gerben , Kenjeres Sasa , Celi Simona , Biancolini Marco Evangelos
Published: January 2024

The treatment for asthma and chronic obstructive pulmonary disease relies on forced inhalation of drug particles. Their distribution is essential for maximizing the outcomes. Patient-specific computational fluid dynamics (CFD) simulations can be used to optimize these therapies. In this regard, this study focuses on creating a parametric model of the human respiratory tract from which synthetic anatomies for particle deposition analysis through CFD simulation could be derived. A baseline geometry up to the fourth generation of bronchioles was extracted from a CT dataset. Radial basis function (RBF) mesh morphing acting on a dedicated tree structure was used to modify this baseline mesh, extracting 1000 synthetic anatomies. A total of 26 geometrical parameters affecting branch lengths, angles, and diameters were controlled. Morphed models underwent CFD simulations to analyze airflow and particle dynamics. Mesh morphing was crucial in generating high-quality computational grids, with 96% of the synthetic database being immediately suitable for accurate CFD simulations. Variations in wall shear stress, particle accretion rate, and turbulent kinetic energy across different anatomies highlighted the impact of the anatomical shape on drug delivery and deposition. The study successfully demonstrates the potential of tree-structure-based RBF mesh morphing in generating parametric airways for drug delivery studies.
Exploring Rice Consumption Habits and Determinants of Choice, Aiming for the Development and Promotion of Rice Products with a Low Glycaemic Index
Authors: Cabral Diva , Moura Ana P. , Fonseca Susana C. , Oliveira Jorge C. , Cunha Luís M.
Published: January 2024

Current consumption drivers, particularly those related to health and wellbeing, have been influencing trends for the lower consumption of cereals, particularly rice, due to their typical high glycaemic index (GIs) and consequent impacts on obesity. To satisfy this consumer concern, more food innovations that promote healthy eating habits are required. Such innovations must be consumer-oriented to succeed, understanding the dynamics of consumer habits and responding to consumer expectations. This study explored these habits, from acquisition to consumption practices, and the expectations of the European market from the perspective of the major European consumer, Portugal, to obtain insights that support the development of low glycaemic index (GI) rice products. A mixed-methods approach was applied. For the first quantitative questionnaire, 256 Portuguese rice consumers aged 18–73 years were recruited. Twenty-four individuals were selected according to their gender and rice consumption profiles for in-depth interviews. The results confirmed that rice was the main side dish for the participants and was mainly consumed at home, cooked from raw milled rice. The drivers of consumption differ according to the provisioning process stage. In the acquisition stage, participants reported benefits from the rice’s dynamic market by comparing products on price, brand, and rice types. In the preparation stage, participants reported the adequacy of the recipe and occasion, while in the consumption stage, participants enhanced their sensory preferences, depending on the rice dish. Although the GI concept was unknown to half of the participants, it was perceived as interesting and positive for healthy eating. Consumers showed concern about the taste and naturalness of the product, preferring it to be as close to a homemade dish as possible. The negative perceptions we verified were interpreted to be due to a lack of knowledge about the GI concept. Therefore, awareness actions and informative campaigns are recommended to promote low-GI rice products.