bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Investigation of a Novel Grinding Device for the One-Pot Production of Ferromagnetic Nanoparticles
Authors: Trofa Marco , Vocciante Marco
Published: February 2024

The use of nanoparticles (NPs) in industrial applications is consistently increasing given their peculiar properties compared to bulk precursor materials. As a result, there is a growing need to develop alternative technical strategies for the synthesis of such NPs using processes that are not only environmentally friendly but also easy and inexpensive to implement on an industrial scale. In this regard, a novel approach has recently been proposed for the safe and sustainable production of metal NPs directly from a bulky solid by magnetically driven low-energy wet milling, which overcomes the limits of applicability to ferromagnetic materials through a unique device configuration. In the present contribution, the understanding of this alternative configuration is deepened by computational investigation. Discrete Element Method (DEM) simulations were used to model the dynamics of the system, highlighting the role of the various parameters involved in the setup and operation of the process. The collisions between grinding and primary particles are analyzed in terms of frequency, impact angle, and energy. Comparing the results with the standard device configuration, the general trend is preserved, though collisions at higher impact angle and energy are also detected.
H2 URESONIC: Design of a Solar-Hydrogen University Renewable Energy System for a New and Innovative Campus
Authors: Joshua Salaki Reynaldo , Park Sanguk , Kwon Kihyeon
Published: February 2024

The necessity to move to sustainable energy solutions has inspired an investigation of innovative technologies for satisfying educational institutions’ sustainable energy needs. The possibility of a solar-hydrogen storage system and its integration into university energy management is investigated in this article. The study opens by providing context, noting the growing relevance of renewable energy in universities as well as the necessity for effective energy storage systems. The goal is to delve into solar-hydrogen technology, outlining its components, operating mechanism, and benefits over typical storage systems. The chapter on Integration Design examines current university energy infrastructure, identifies problems, and provides ways for integrating solar-hydrogen systems seamlessly. This integration relies heavily on technological and economic considerations, such as a cost-benefit analysis and scalability studies. Case studies include real-world examples, performance measurements, and significant insights learned from successful implementations. The chapter Future Prospects investigates new trends in solar-hydrogen technology as well as the impact of government legislation, providing a forward-looking viewpoint for colleges considering adoption. The report concludes with a summary of significant findings, emphasizing the benefits of solar-hydrogen integration and making recommendations for future implementations. The limitation of this research is that it only focuses on design and simulation as a phase of preliminary study.
LM-DeeplabV3+: A Lightweight Image Segmentation Algorithm Based on Multi-Scale Feature Interaction
Authors: Hou Xinyu , Chen Peng , Gu Haishuo
Published: February 2024

Street-view images can help us to better understand the city environment and its potential characteristics. With the development of computer vision and deep learning, the technology of semantic segmentation algorithms has become more mature. However, DeeplabV3+, which is commonly used in semantic segmentation, has shortcomings such as a large number of parameters, high requirements for computing resources, and easy loss of detailed information. Therefore, this paper proposes LM-DeeplabV3+, which aims to greatly reduce the parameters and computations of the model while ensuring segmentation accuracy. Firstly, the lightweight network MobileNetV2 is selected as the backbone network, and the ECA attention mechanism is introduced after MobileNetV2 extracts shallow features to improve the ability of feature representation; secondly, the ASPP module is improved, and on this basis, the EPSA attention mechanism is introduced to achieve cross-dimensional channel attention and important feature interaction; thirdly, a loss function named CL loss is designed to balance the training offset of multiple categories and better indicate the segmentation quality. This paper conducted experimental verification on the Cityspaces dataset, and the results showed that the mIoU reached 74.9%, which was an improvement of 3.56% compared to DeeplabV3+; and the mPA reached 83.01%, which was an improvement of 2.53% compared to DeeplabV3+.
Towards Real-Time Machine Learning-Based Signal/Background Selection in the CMS Detector Using Quantized Neural Networks and Input Data Reduction
Authors: Burazin Mišura Arijana , Musić Josip , Prvan Marina , Lelas Damir
Published: February 2024

The Large Hadron Collider (LHC) is being prepared for an extensive upgrade to boost its particle discovery potential. The new phase, High Luminosity LHC, will operate at a factor-of-five-increased luminosity (the number proportional to the rate of collisions). Consequently, such an increase in luminosity will result in enormous quantities of generated data that cannot be transmitted or stored with the currently available resources and time. However, the vast majority of the generated data consist of uninteresting data or pile-up data containing few interesting events or electromagnetic showers. High-Luminosity LHC detectors, including the Compact Muon Solenoid (CMS), will thus have to rely on innovative approaches like the proposed one to select interesting collision data. In charge of data reduction/selection at the early stages of data streaming is a level 1 trigger (L1T), a real-time event selection system. The final step of the L1T is a global trigger, which uses sub-system algorithms to make a final decision about signal acceptance/rejection within a decision time of around 12 microseconds. For one of these sub-system L1T algorithms, we propose using quantized neural network models deployed in targeted L1T devices, namely, field-programmable gate arrays (FPGA), as a classifier between electromagnetic and pile-up/quantum chromodynamics showers. The developed quantized neural network operates in an end-to-end manner using raw detector data to speed up the classification process. The proposed data reduction methods further decrease model size while retaining accuracy. The proposed approach was tested with simulated data (since the detector is still in the production stage) and took less than 1 microsecond, achieving real-time signal–background classification with a classification accuracy of 97.37% for 2-bit-only quantization and 97.44% for quantization augmented with the data reduction approach (compared to 98.61% for the full-precision, standard network).
Research on 3D Time-Lapse Electric Field Inversion Algorithm for Controlled Source Audio-Frequency Magnetotelluric Method
Authors: Sun Qilong , Tan Handong , Wan Wei , Hu Qixuan
Published: February 2024

The controlled source audio-frequency magnetotelluric method (CSAMT) stands out for its economic efficiency and widespread application in geophysical monitoring. However, the separate inversion of time-lapse monitoring data encounters challenges in comparing and identifying abnormal changes due to variations in data fitting. Furthermore, the utilization of a method akin to Cagniard apparent resistivity for inversion necessitates the simultaneous observation of at least two components of the electromagnetic field, making it unsuitable for extensive three-dimensional observations. This paper proposes a 3D time-lapse electric field inversion algorithm for CSAMT, addressing the complexities in geophysical monitoring. The algorithm introduces two regularization factors and defines an objective function with both temporal and spatial constraints. Synthetic testing reveals the stability of the 3D time-lapse electric field inversion algorithm, demonstrating its effectiveness in delineating underground variations. This solution resolves the challenges posed by the independent inversion of time-lapse monitoring data.
A Machine Learning Multilayer Meta-Model for Prediction of Postoperative Lung Function in Lung Cancer Patients
Authors: Vešović Radomir , Milosavljević Milan , Punt Marija , Radomirović Jelica
Published: February 2024

The goal of this paper is to inform the machine learning community of our results obtained during the development of a system for the assessment of the postoperative lung function of patients suffering from lung cancer. The system is based on a new multilayer regression meta-model, which predicts individual postoperative forced expiratory volume in 1 second (poFEV1) for each patient based on preoperative measurements. The proposed regression models are especially trained to predict this key indicator for the 1st, 4th, and 7th day after surgery. Based on our knowledge, this is the first attempt to obtain poFEV1 in the most critical postoperative period of the first seven days. The high accuracy of the proposed predictive meta-model allows surgeons a number of key insights, starting with whether the patient is suitable for surgical intervention, and ending with the preparation of individualized postoperative treatment. It should be noted that the existing, widely used predictive models, based on functional segments (FC), Juhl-Forst, and Nakahara formulas, give two to three times worse results compared to the proposed new regression meta-model. Based on the SHapley Additive explanations (SHAP) value of the trained meta-model, it is possible to obtain a complete picture of the partial effects of each prognostic factor for each patient preoperatively on the outcome of the surgical intervention. In addition, the global model interpretation by SHAP values reveals some new interdependencies that were not known in medical circles until now. For instance, the influence of age and biomass index on the condition of the patient on the first day after surgery, or the constant significant influence of muscular support for inhalation in the entire seven-day follow-up period.
Intrinsic Safety Risk Control and Early Warning Methods for Lithium-Ion Power Batteries
Authors: Cui Yi , Shen Xueling , Zhang Hang , Yin Yanping , Yu Zhanglong , Shi Dong , Fang Yanyan , Xu Ran
Published: February 2024

Since 2014, the electric vehicle industry in China has flourished and has been accompanied by rapid growth in the power battery industry led by lithium-ion battery (LIB) development. Due to a variety of factors, LIBs have been widely used, but user abuse and battery quality issues have led to explosion accidents that have caused loss of life and property. Current strategies to address battery safety concerns mainly involve enhancing the intrinsic safety of batteries and strengthening safety controls with approaches such as early warning systems to alert users before thermal runaway and ensure user safety. In this paper, we discuss the current research status and trends in two areas, intrinsic battery safety risk control and early warning methods, with the goal of promoting the development of safe LIB solutions in new energy applications.
Design and Control of a Soft Knee Exoskeleton for Pediatric Patients at Early Stages of the Walking Learning Process
Authors: Mansilla Navarro Paloma , Copaci Dorin , Blanco Rojas Dolores
Published: February 2024

Pediatric patients can suffer from different motor disorders that limit their neurological and motor development and hinder their independence. If treated at the very early stages of development, those limitations can be palliated or even removed. However, manual interventions are not completely effective due to the restrictions in terms of time, force, or tracking experienced by the physiotherapists. The knee flexo-extension is crucial for walking and often affected by disorders such as spasticity or lack of force in the posterior chain. This article focuses on the development of a knee exosuit to follow angular trajectories mimicking the maximum and minimum peaks present in the knee flexo-extension profiles of healthy individuals during walking. The proposed exosuit is based on shape memory alloy actuators along with four inertial sensors that close the control loop. The whole device is controlled through a two-level controller and has an hybrid rigid–flexible design to overcome the different issues present in the literature. The device was proven to be feasible for this type of application, with replicable and consistent behavior, reducing the price and weight of existing exosuits and enhancing patient comfort.
From Host Defense to Metabolic Signatures: Unveiling the Role of γδ T Cells in Bacterial Infections
Authors: Nanda Namya , Alphonse Martin P.
Published: February 2024

The growth of antibiotic-resistant bacterial infections necessitates focusing on host-derived immunotherapies. γδ T cells are an unconventional T cell subset, making up a relatively small portion of healthy circulating lymphocytes but a substantially increased proportion in mucosal and epithelial tissues. γδ T cells are activated and expanded in response to bacterial infection, having the capability to produce proinflammatory cytokines to recruit neutrophils and clear infection. They also play a significant role in dampening immune response to control inflammation and protecting the host against secondary challenge, making them promising targets when developing immunotherapy. Importantly, γδ T cells have differential metabolic states influencing their cytokine profile and subsequent inflammatory capacity. Though these differential metabolic states have not been well studied or reviewed in the context of bacterial infection, they are critical in understanding the mechanistic underpinnings of the host’s innate immune response. Therefore, this review will focus on the context-specific host defense conferred by γδ T cells during infection with Staphylococcus aureus, Streptococcus pneumoniae, Listeria monocytogenes, and Mycobacterium tuberculosis.
Fulminant Leptospirosis Presenting with Rapidly Developing Acute Renal Failure and Multiorgan Failure
Authors: Liu Yu-Hsien , Chen Yu-Hsuan , Chen Chuan-Mu
Published: February 2024

Leptospirosis, caused by pathogenic spirochetes of the Leptospira genus, is a common zoonosis in tropical and subtropical regions and can lead to an epidemic following heavy rainfall or flooding. The primary reservoirs of Leptospira include rodents, wild animals, dogs, cats, amphibians, and others, but the brown rat (Rattus norvegicus) remains the main source of human Leptospirosis. Humans are often accidental hosts and they can be infected through cuts, abrasions, mucosa, conjunctiva, or by ingesting contaminated water. The clinical manifestation of leptospirosis can vary from mild, nonspecific symptoms to a fatal outcome involving liver and renal failure, pulmonary hemorrhage, meningitis, and septic shock. The severity of fatal outcomes is likely to be due to virulence factors, host susceptibility, and epidemiological conditions. L. interrogans are associated with high-risk individuals, particularly patients older than 60 years of age in clinical settings. The current case study showed a foreign worker who presented with rapidly deteriorating clinical signs of fever, jaundice, impaired consciousness, and oliguric acute renal failure. Drawing from our experience, it is advisable to consider the possibility of leptospirosis diagnosis in patients who show clinical symptoms such as fever, hepatic failure with jaundice, and acute renal failure. This is particularly important for those individuals with a prior history of pathogen exposure. This case study had a strong suspicion of leptospirosis, which was confirmed by the microscopic agglutination test (MAT) and, later, the patient’s recovery following treatment.
HIV-Related Oral Mucosa Lesions: A Cross-Sectional Study on a Cohort of Italian Patients
Authors: Tarozzi Marco , Baruzzi Elisa , Decani Sem , Tincati Camilla , Santoro Andrea , Moneghini Laura , Lodi Giovanni , Sardella Andrea , Carrassi Antonio , Varoni Elena Maria
Published: February 2024

Background: Human immunodeficiency virus (HIV) infection can be associated with oral mucosal diseases, including oral candidiasis and HPV infection, which are putative indicators of the immune status. Aim and Methods: This retrospective cross-sectional study was aimed at assessing the prevalence of HIV-related oral mucosal lesions in a cohort of Italian HIV+ patients regularly attending the Clinics of Infectious Diseases. Results: One hundred seventy-seven (n = 177) patients were enrolled and 30 (16.9%) of them showed HIV-related diseases of the oral mucosa. They were mainly found in male patients over 35 years old, undergoing Combination Antiretroviral Therapy (cART), and with CD4+ count < 500/µL. Oral candidiasis was the most common HIV-related oral lesion. No significant correlations could be detected between the prevalence of HPV infection and other clinical parameters (lymphocyte count, cART treatment and viral load). Conclusions: HIV-related oral mucosal diseases can correlate with immunosuppression. Early diagnosis and management of oral lesions in HIV+ patients should be part of the regular follow-up, from a multidisciplinary perspective of collaboration between oral medicine and infectious disease specialists, in an attempt to reduce morbidity due to oral lesions and modulate antiretroviral therapy according to the patient’s immune status.
Is a Forest Fire a Natural Disaster? Investigating the Fire Tolerance of Various Tree Species—An Educational Module
Authors: Speck Olga , Speck Thomas
Published: February 2024

Wildfires are unplanned conflagrations perceived as a threat by humans. However, fires are essential for the survival of fire-adapted plants. On the one hand, wildfires cause major damage worldwide, burning large areas of forests and landscapes, threatening towns and villages, and generating high levels of air pollution. On the other hand, fire-adapted plants (pyrophytes) in the fire landscapes of the Earth are able to survive exposure to heat (e.g., because of their thick bark, which protects their living tissue) and benefit from fire directly (e.g., fire initiates cone opening and seed release) or indirectly (e.g., fewer competing plants of fire-sensitive species remain, seeds germinate in the ash-fertilized soil). We present the experimental set-up and results of a fire experiment on bark samples used as a basis to assess the fire tolerance of various trees. Fire tolerance is defined as the ability of a tree to survive a surface fire (up to 200 °C and 5 min duration). The measure of the fire tolerance for a tree species is the time taken for the vascular cambium under the insulating bark to reach the critical temperature of 60 °C. Within an educational module, we provide worksheets for teachers and students enabling them to analyze the fire tolerance of various tree barks.
Fear of Sexual Harassment Accusations: A Hidden Barrier to Opposite-Gender Mentoring in Taiwan?
Authors: Tudor Thomas R. , Gapud Stephanie D. , Bajwa Naeem
Published: February 2024

While legal protections against sexual harassment are crucial, their implementation could have unintended consequences. This study explores the potential downside of these protections—fear of false accusations—and its impact on cross-gender mentoring in Taiwanese workplaces. Drawing on social exchange theory, we investigate how fear of accusations might discourage valuable mentoring relationships between men and women. Through an intercept survey, we examined whether these concerns may lead to reduced mentoring opportunities for women, potentially hindering their career advancement. We proposed new constructs and analyzed the model using SmartPLS 4.1. Our findings reveal a complex dynamic: fear of accusations does appear to decrease cross-gender mentoring, raising concerns about its impact on women’s career trajectories. However, the findings also suggest that men support sexual harassment laws, still believing these laws are needed. We discuss our model and its implications; additionally, we emphasize the need for strategies that balance legal protections while also fostering positive mentoring relationships.
Complexity of the Genetic Background of Oncogenesis in Ovarian Cancer—Genetic Instability and Clinical Implications
Authors: Murawski Marek , Jagodziński Adam , Bielawska-Pohl Aleksandra , Klimczak Aleksandra
Published: February 2024

Ovarian cancer is a leading cause of death among women with gynecological cancers, and is often diagnosed at advanced stages, leading to poor outcomes. This review explores genetic aspects of high-grade serous, endometrioid, and clear-cell ovarian carcinomas, emphasizing personalized treatment approaches. Specific mutations such as TP53 in high-grade serous and BRAF/KRAS in low-grade serous carcinomas highlight the need for tailored therapies. Varying mutation prevalence across subtypes, including BRCA1/2, PTEN, PIK3CA, CTNNB1, and c-myc amplification, offers potential therapeutic targets. This review underscores TP53’s pivotal role and advocates p53 immunohistochemical staining for mutational analysis. BRCA1/2 mutations’ significance as genetic risk factors and their relevance in PARP inhibitor therapy are discussed, emphasizing the importance of genetic testing. This review also addresses the paradoxical better prognosis linked to KRAS and BRAF mutations in ovarian cancer. ARID1A, PIK3CA, and PTEN alterations in platinum resistance contribute to the genetic landscape. Therapeutic strategies, like restoring WT p53 function and exploring PI3K/AKT/mTOR inhibitors, are considered. The evolving understanding of genetic factors in ovarian carcinomas supports tailored therapeutic approaches based on individual tumor genetic profiles. Ongoing research shows promise for advancing personalized treatments and refining genetic testing in neoplastic diseases, including ovarian cancer. Clinical genetic screening tests can identify women at increased risk, guiding predictive cancer risk-reducing surgery.
Metabolic Dysfunction–Associated Fatty Liver Disease (MAFLD) and Thyroid Function in Childhood Obesity: A Vicious Circle?
Authors: Calcaterra Valeria , Degrassi Irene , Taranto Silvia , Porro Cecilia , Bianchi Alice , L’assainato Sara , Silvestro Giustino Simone , Quatrale Antonia , Zuccotti Gianvincenzo
Published: February 2024

Metabolic dysfunction–associated fatty liver disease (MAFLD) is a multisystem disorder characterized by the presence of fatty liver degeneration associated with excess adiposity or prediabetes/type 2 diabetes or metabolic dysregulation. An intricate relationship between the liver and thyroid has been reported in both health and disease. Simultaneously, there is a strong correlation between obesity and both MAFLD and thyroid dysfunction. In this narrative review, we highlighted the relationship between MAFLD and thyroid function in children and adolescents with obesity in order to explore how thyroid hormones (THs) act as predisposing factors in the onset, progression, and sustainability of MAFLD. THs are integral to the intricate balance of metabolic activities, ensuring energy homeostasis, and are indispensable for growth and development. Regarding liver homeostasis, THs have been suggested to interact with liver lipid homeostasis through a series of processes, including stimulating the entry of free fatty acids into the liver for esterification into triglycerides and increasing mitochondrial β-oxidation of fatty acids to impact hepatic lipid accumulation. The literature supports a correlation between MAFLD and obesity, THs and obesity, and MAFLD and THs; however, results in the pediatric population are very limited. Even though the underlying pathogenic mechanism involved in the relationship between MAFLD and thyroid function remains not fully elucidated, the role of THs as predisposing factors of MAFLD could be postulated. A potential vicious circle among these three conditions cannot be excluded. Identifying novel elements that may contribute to MAFLD could offer a practical approach to assessing children at risk of developing the condition.
Recurrent Respiratory Infections in Children with Down Syndrome: A Review
Authors: Ghezzi Michele , Garancini Nicolò , De Santis Raffaella , Gianolio Laura , Zirpoli Salvatore , Mandelli Anna , Farolfi Andrea , D’Auria Enza , Zuccotti Gian Vincenzo
Published: February 2024

Down Syndrome (DS) is the most common chromosomal abnormality compatible with life. The life of patients suffering from DS can be strongly impacted by Recurrent Respiratory tract Infections (RRIs), leading to an increased rate of hospitalisation, a higher need for intensive care and fatality. With a literature review, we summarise here the main etiological factors for RRI in this category of patients, particularly focusing on airway malformations such as tracheomalacia, tracheal bronchus and bronchomalacia, comorbidities associated with the syndrome, like congenital heart diseases, dysphagia, gastroesophageal reflux, musculoskeletal involvement and obesity, and immunologic impairments, involving both innate and adaptive immunity. For these patients, a multidisciplinary approach is imperative as well as some preventive strategies, in particular vaccinations in accordance with their national schedule for immunization.
A Multisource Process Evaluation of a Community-Based Healthy Lifestyle Programme for Child and Adolescent Obesity
Authors: Anderson Yvonne C. , Wild Cervantée E. K. , Gilchrist Catherine A. , Hofman Paul L. , Cave Tami L. , Domett Tania , Cutfield Wayne S. , Derraik José G. B. , Grant Cameron C.
Published: February 2024

Whānau Pakari is a healthy lifestyle assessment and intervention programme for children and adolescents with obesity in Taranaki (Aotearoa/New Zealand), which, in this region, replaced the nationally funded Green Prescription Active Families (GRxAF) programme. We compared national referral rates from the GRxAF programme (age 5–15 years) and the B4 School Check (B4SC, a national preschool health and development assessment) with referral rates in Taranaki from Whānau Pakari. We retrospectively analysed 5 years of clinical data (2010–2015), comparing referral rates before, during, and after the Whānau Pakari clinical trial, which was embedded within the programme. We also surveyed programme referrers and stakeholders about their experiences of Whānau Pakari, analysing their responses using a multiple-methods framework. After the Whānau Pakari trial commenced, Taranaki GRxAF referral rates increased markedly (2.3 pretrial to 7.2 per 1000 person-years), while NZ rates were largely unchanged (1.8–1.9 per 1000 person-years) (p < 0.0001 for differences during the trial). Post-trial, Taranaki GRxAF referral rates remained higher irrespective of ethnicity, being 1.8 to 3.2 times the national rates (p < 0.001). Taranaki B4SC referrals for obesity were nearly complete at 99% in the last trial year and 100% post-trial, compared with national rates threefold lower (31% and 32%, respectively; p < 0.0001), with Taranaki referral rates for extreme obesity sustained at 80% and exceeding national rates for both periods (58% and 62%, respectively; p < 0.01). Notably, a referral was 50% more likely for referrers who attended a Whānau Pakari training half-day (RR = 1.51; p = 0.009). Stakeholders credited the success of Whānau Pakari to its multidisciplinary team, family-centred approach, and home-based assessments. However, they highlighted challenges such as navigating multidisciplinary collaboration, engaging with families with complex needs, and shifting conventional healthcare practices. Given its favourable referral trends and stakeholder endorsement, Whānau Pakari appears to be a viable contemporary model for an accessible and culturally appropriate intervention on a national and potentially international scale.
Correlation between Histopathological Prognostic Tumor Characteristics and [18F]FDG Uptake in Corresponding Metastases in Newly Diagnosed Metastatic Breast Cancer
Authors: Boers Jorianne , Eisses Bertha , Zwager Mieke C. , van Geel Jasper J. L. , Bensch Frederike , de Vries Erik F. J. , Hospers Geke A. P. , Glaudemans Andor W. J. M. , Brouwers Adrienne H. , den Dekker Martijn A. M. , Elias Sjoerd G. , Kuip Evelien J. M. , van Herpen Carla M. L. , Jager Agnes , van der Veldt Astrid A. M. , Oprea-Lager Daniela E. , de Vries Elisabeth G. E. , van der Vegt Bert , Menke-van der Houven van Oordt Willemien C. , Schröder Carolina P.
Published: February 2024

Background: In metastatic breast cancer (MBC), [18F]fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) can be used for staging. We evaluated the correlation between BC histopathological characteristics and [18F]FDG uptake in corresponding metastases. Patients and Methods: Patients with non-rapidly progressive MBC of all subtypes prospectively underwent a baseline histological metastasis biopsy and [18F]FDG-PET. Biopsies were assessed for estrogen, progesterone, and human epidermal growth factor receptor 2 (ER, PR, HER2); Ki-67; and histological subtype. [18F]FDG uptake was expressed as maximum standardized uptake value (SUVmax) and results were expressed as geometric means. Results: Of 200 patients, 188 had evaluable metastasis biopsies, and 182 of these contained tumor. HER2 positivity and Ki-67 ≥ 20% were correlated with higher [18F]FDG uptake (estimated geometric mean SUVmax 10.0 and 8.8, respectively; p = 0.0064 and p = 0.014). [18F]FDG uptake was lowest in ER-positive/HER2-negative BC and highest in HER2-positive BC (geometric mean SUVmax 6.8 and 10.0, respectively; p = 0.0058). Although [18F]FDG uptake was lower in invasive lobular carcinoma (n = 31) than invasive carcinoma NST (n = 146) (estimated geometric mean SUVmax 5.8 versus 7.8; p = 0.014), the metastasis detection rate was similar. Conclusions: [18F]FDG-PET is a powerful tool to detect metastases, including invasive lobular carcinoma. Although BC histopathological characteristics are related to [18F]FDG uptake, [18F]FDG-PET and biopsy remain complementary in MBC staging (NCT01957332).
A Novel Method for Assessing Risk-Adjusted Diagnostic Coding Specificity for Depression Using a U.S. Cohort of over One Million Patients
Authors: Glass Alexandra , Melton Nalander C. , Moore Connor , Myrick Keyerra , Thao Kola , Mogaji Samiat , Howell Anna , Patton Kenneth , Martin John , Korvink Michael , Gunn Laura H.
Published: February 2024

Depression is a prevalent and debilitating mental health condition that poses significant challenges for healthcare providers, researchers, and policymakers. The diagnostic coding specificity of depression is crucial for improving patient care, resource allocation, and health outcomes. We propose a novel approach to assess risk-adjusted coding specificity for individuals diagnosed with depression using a vast cohort of over one million inpatient hospitalizations in the United States. Considering various clinical, demographic, and socioeconomic characteristics, we develop a risk-adjusted model that assesses diagnostic coding specificity. Results demonstrate that risk-adjustment is necessary and useful to explain variability in the coding specificity of principal (AUC = 0.76) and secondary (AUC = 0.69) diagnoses. Our approach combines a multivariate logistic regression at the patient hospitalization level to extract risk-adjusted probabilities of specificity with a Poisson Binomial approach at the facility level. This method can be used to identify healthcare facilities that over- and under-specify diagnostic coding when compared to peer-defined standards of practice.
A Preliminary Approach towards Rotor Icing Modeling Using the Unsteady Vortex Lattice Method
Authors: Samad Abdallah , Villeneuve Eric , Morency François , Béland Mathieu , Lapalme Maxime
Published: February 2024

UAV rotors are at a high risk of ice accumulation during their operations in icing conditions. Thermal ice protection systems (IPSs) are being employed as a means of protecting rotor blades from ice, yet designing the appropriate IPS with the required heating density remains a challenge. In this work, a reduced-order modeling technique based on the Unsteady Vortex Lattice Method (UVLM) is proposed as a way to predicting rotor icing and to calculate the required anti-icing heat loads. The UVLM is gaining recent popularity for aircraft and rotor modeling. This method is flexible enough to model difficult aerodynamic problems, computationally efficient compared to higher-order CFD methods and accurate enough for conceptual design problems. A previously developed implementation of the UVLM for 3D rotor aerodynamic modeling is extended to incorporate a simplified steady-state icing thermodynamic model on the stagnation line of the blade. A viscous coupling algorithm based on a modified α-method incorporates viscous data into the originally inviscid calculations of the UVLM. The algorithm also predicts the effective angle of attack at each blade radial station (r/R), which is, in turn, used to calculate the convective heat transfer for each r/R using a CFD-based correlation for airfoils. The droplet collection efficiency at the stagnation line is calculated using a popular correlation from the literature. The icing mass and heat transfer balance includes terms for evaporation, sublimation, radiation, convection, water impingement, kinetic heating, and aerodynamic heating, as well as an anti-icing heat flux. The proposed UVLM-icing coupling technique is tested by replicating the experimental results for ice accretion and anti-icing of the 4-blade rotor of the APT70 drone. Aerodynamic predictions of the UVLM for the Figure of Merit, thrust, and torque coefficients agree within 10% of the experimental measurements. For icing conditions at −5 °C, the proposed approach overestimates the required anti-icing flux by around 50%, although it sufficiently predicts the effect of aerodynamic heating on the lack of ice formation near the blade tips. At −12 °C, visualizations of ice formation at different anti-icing heating powers agree well with UVLM predictions. However, a large discrepancy was found when predicting the required anti-icing heat load. Discrepancies between the numerical and experimental data are largely owed to the unaccounted transient and 3D effects related to the icing process on the rotating blades, which have been planned for in future work.
The Work Environment of the School Leader in Australia: The Case for Sustained Change in Role and Practice
Authors: Caldwell Brian J.
Published: February 2024

The questions addressed in this essay are (1) how has the work environment of school leaders changed in the early years of the 21st century, (2) how have these changes affected the role of the school leader, (3) what is the association between an evident deterioration in the work environment and the trend to more autonomy for schools and their leaders, and (4) how can school systems be more effective in supporting school leaders? The essay is organised into three domains that emerged from a review of the literature on changes in the work environment: intensification–intimidation, autonomy–accountability and system–support. Six recommendations are derived from the evidence: principals should have greater control over their work environment, system leaders should remove many reporting requirements from schools, there should be “organised abandonment” of outdated practices, the potential benefits of AI should be realised, there should be more engagement in planning for the future, and there should be further research on processes and outcomes through randomised controlled trials of new practices. It is not so much new theories in leadership but rather new roles and new practices within different arrangements for governance, informed by ongoing research as the context changes, amid evidence of deterioration in professional wellbeing.
From Research to Retweets—Exploring the Role of Educational Twitter (X) Communities in Promoting Science Communication and Evidence-Based Teaching
Authors: Déchène Monica , Lesperance Kaley , Ziernwald Lisa , Holzberger Doris
Published: February 2024

Twitter has evolved from its initial purpose as a microblogging social network to a pivotal platform for science communication. Equally, it has gained significant popularity among teachers who utilize communities like the German #twitterlehrerzimmer (TWLZ; Twitter teachers’ lounge) as a digital professional learning network. (1) Background: To date, no studies examine how science communication is conducted on Twitter specifically tailored to teachers’ needs and whether this facilitates evidence-based teaching. (2) Methods: Answering the three research questions involved a comprehensive mixed methods approach comprising an online teacher survey, utility analysis using Analytical Hierarchy Process (AHP) models, and machine learning-assisted tweet analyses. (3) Results: Teachers implement research findings from the TWLZ in their teaching about twice a month. They prefer interactive tweets with specific content-related, communicative, and interactive tweet features. Science communication in the TWLZ differs from everyday communication but notably emphasizes the relevance of transfer events for educational practice. (4) Conclusions: Findings highlight that dialogue is essential for successful science communication. Practical implications arise from new guidelines on how research findings should be communicated and encourage teachers to reflect on their Twitter usage and attitude toward evidence-based teaching. Recommendations for further research in this emerging field are also discussed.
Prediction of Arabic Legal Rulings Using Large Language Models
Authors: Ammar Adel , Koubaa Anis , Benjdira Bilel , Nacar Omer , Sibaee Serry
Published: February 2024

In the intricate field of legal studies, the analysis of court decisions is a cornerstone for the effective functioning of the judicial system. The ability to predict court outcomes helps judges during the decision-making process and equips lawyers with invaluable insights, enhancing their strategic approaches to cases. Despite its significance, the domain of Arabic court analysis remains under-explored. This paper pioneers a comprehensive predictive analysis of Arabic court decisions on a dataset of 10,813 commercial court real cases, leveraging the advanced capabilities of the current state-of-the-art large language models. Through a systematic exploration, we evaluate three prevalent foundational models (LLaMA-7b, JAIS-13b, and GPT-3.5-turbo) and three training paradigms: zero-shot, one-shot, and tailored fine-tuning. In addition, we assess the benefit of summarizing and/or translating the original Arabic input texts. This leads to a spectrum of 14 model variants, for which we offer a granular performance assessment with a series of different metrics (human assessment, GPT evaluation, ROUGE, and BLEU scores). We show that all variants of LLaMA models yield limited performance, whereas GPT-3.5-based models outperform all other models by a wide margin, surpassing the average score of the dedicated Arabic-centric JAIS model by 50%. Furthermore, we show that all scores except human evaluation are inconsistent and unreliable for assessing the performance of large language models on court decision predictions. This study paves the way for future research, bridging the gap between computational linguistics and Arabic legal analytics.
Statement-Grained Hierarchy Enhanced Code Summarization
Authors: Zhang Qianjin , Jin Dahai , Wang Yawen , Gong Yunzhan
Published: February 2024

Code summarization plays a vital role in aiding developers with program comprehension by generating corresponding textual descriptions for code snippets. While recent approaches have concentrated on encoding the textual and structural characteristics of source code, they often neglect the global hierarchical features, causing limited code representation. Addressing this gap, our paper introduces the statement-grained hierarchy enhanced Transformer model (SHT), a novel framework that integrates global hierarchy, syntax, and token sequences to automatically generate summaries for code snippets. SHT is distinctively designed with two encoders to learn both hierarchical and sequential features of code. One relational attention encoder processes the statement-grained hierarchical graph, producing hierarchical embeddings. Subsequently, another sequence encoder integrates these hierarchical structures with token sequences. The resulting enriched representation is then fed into a vanilla Transformer decoder, which effectively generates concise and informative summarizations. Our extensive experiments demonstrate that SHT significantly outperforms state-of-the-art approaches on two widely used Java benchmarks. This underscores the effectiveness of incorporating global hierarchical information in enhancing the quality of code summarizations.
A Comprehensive Review on Space Vector Based-PWM Techniques for Common Mode Voltage Mitigation in Photovoltaic Multi-Level Inverters
Authors: Ben Mahmoud Zouhaira , Khedher Adel
Published: February 2024

Nowadays, transformer-less photovoltaic (PV) multi-level inverters (MLIs) are commonly employed in both industrial and residential settings. This structure has attracted increased attention due to its unique advantages, such as higher efficiency, lower cost and size, better waveform quality, and inherent fault tolerance. However, due to the removal of the transformer, the common mode voltage (CMV) becomes one of the crucial issues in transformer-less PV MLIs. The high-frequency variation in CMV results in a leakage current that deteriorates the line current quality, increases the PV power system losses, leads to severe electromagnetic emissions (EMI), reduces the PV array lifespan, and causes personal safety problems. In this regard, this paper presents a review of the existing and recent research on modulation techniques based on space vector pulse width modulation (SVPWMs) that overcome this issue in transformer-less three-level NPC-MLIs (3L-NPC-MLIs). The reduced CMV-SVPWM (RCMV-SVPWM) can be mainly categorized as an RCMV-SVPWM based on the vector type, based on virtual vectors, and based on the two-level SVPWM (2L-SVPWM). Their features and their limitations in terms of several main criteria are discussed. In the final section of this paper, some challenges and future trends for this research area are projected.
Partial Replacement of Fish Meal with Protein Hydrolysates in the Diet of Penaeus vannamei (Boone, 1934) during the Nursery Phase
Authors: Negrini Celma , Nascimento Ferreira Caio Henrique do , Kracizy Rafael Ortiz , Ferreira Rosane Lopes , Costa Luana , Mauerwerk Marlise Teresinha , Retcheski Milena Cia , Cazarolli Luisa Helena , Boscolo Wilson Rogério , Cupertino Ballester Eduardo Luis
Published: February 2024

The objective was to evaluate the effects of partial replacement of fish meal with protein hydrolysates and a commercial product in the diets of Penaeus vannamei post-larvae on zootechnical performance, proximate chemical composition, digestive enzyme activity, and total hemocyte count. The experiment was conducted in a clear water recirculation system comprising 24 experimental units, each with 30 shrimp with an average weight of 0.2 g. The treatments were control, chicken protein hydrolysate (CPH), enzymatic hydrolysate of chicken feathers, Aquabite®, CPH + maltodextrin, and CPH + yeast, with four replicates each. The inclusion level of the different protein sources evaluated was 6%. At the end of the experiment, all shrimp were counted, weighed, and measured to determine the zootechnical performance. The body and feed chemical compositions, as well as the enzymatic activities of the hepatopancreas and the total hemocyte count in the hemolymph, were analyzed. The data obtained were subjected to ANOVA and Tukey’s test. There was no statistical difference between the treatments in any of the analyzed parameters. The results showed that all the evaluated protein hydrolysates can be used as partial substitutes for fish meal in P. vannamei diets during the nursery phase, maintaining equivalent and adequate digestive enzyme activities, health, growth, and body composition of the shrimp, in addition to being ecologically sustainable ingredients.
Polyphenols and CRISPR as Quorum Quenching Agents in Antibiotic-Resistant Foodborne Human Pathogens (Salmonella Typhimurium, Campylobacter jejuni and Escherichia coli 0157:H7)
Authors: Higuera-Ciapara Inocencio , Benitez-Vindiola Marieva , Figueroa-Yañez Luis J. , Martínez-Benavidez Evelin
Published: February 2024

Antibiotic resistance in foodborne pathogens is an increasing threat to global human health. Among the most prevalent antibiotic-resistant bacteria are Salmonella enterica serovar Typhimurium, Campylobacter jejuni and E. coli 0157:H7. Control of these and other pathogens requires innovative approaches, i.e., discovering new molecules that will inactivate them, or render them less virulent without inducing resistance. Recently, several polyphenol molecules have been shown to possess such characteristics. Also, the use of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) approaches has recently been proposed for such purpose. This review summarizes the main findings regarding the application of both approaches to control the above-mentioned foodborne pathogens by relying on Quorum Sensing interference (Quorum Quenching) mechanisms and highlights the avenues needed for further research.
Exploring Technological, Safety and Probiotic Properties of Enterococcus Strains: Impact on Rheological Parameters in Fermented Milk
Authors: Sakoui Souraya , Derdak Reda , Pop Oana Lelia , Vodnar Dan Cristian , Jouga Fatimazahra , Teleky Bernadette-Emőke , Addoum Boutaina , Simon Elemér , Suharoschi Ramona , Soukri Abdelaziz , El Khalfi Bouchra
Published: February 2024

Enterococci, known for their resilience, are commonly found in food, the environment, and the gastrointestinal tracts of humans and animals. In recent research, six strains of enterococcus were isolated from bat guano. These include Enterococcus mundtii SRBG1, Enterococcus gallinarum SRBG3, Enterococcus faecium SRBG2, Enterococcus casseliflavus EC1, and Enterococcus devriesei CAU 1344. Identification was done using 16S DNA analysis. Each strain underwent evaluation for its technological properties (such as tolerances to various NaCl concentrations and temperatures, as well as amylolytic, β-galactosidase, lipolytic, and proteolytic activities, and EPS production) and selected probiotic properties (including safety profile, resistance to 0.3 percent bile salts and gastric juice with a pH of 2.5, lysozyme tolerance, and antibacterial and antibiofilm activities against four foodborne pathogens). The results were analyzed using Principal Component Analysis. This analysis revealed that E. mundtii SRBG1 and E. gallinarum SRBG3, followed by E. faecium SRBG2, were most closely associated with a broad range of technological characteristics and were subsequently used for fermenting skimmed milk. The rheological properties of the samples indicated a shear-thinning or non-Newtonian behavior. Furthermore, during storage of the fermented milk at 4 °C over periods of 1, 7, 14, and 21 days, there were no significant changes in bacterial count (at around 7 log10 CFU/mL) and pH when fermented with the three evaluated strains.