bluuebunny/crossref_metadata_2025 huggingface dataset:
A First Approach to the Marine Heterobranchia (Mollusca: Gastropoda) Fauna of Marettimo, Egadi Islands, MPA (Western Sicily, Mediterranean Sea)
Authors: Lombardo Andrea , Marletta Giuliana
Published: November 2024

For almost all the Sicilian islands, there are no faunistic data concerning marine Heterobranchia, which is one of the most sought-after groups of marine critters by photographers and diving enthusiasts all over the world. With the present study, carried out through underwater photography at various dive sites and stretches of coastline in the island of Marettimo, we made the first contribution to the knowledge of the marine Heterobranchia fauna present on this island of the Egadi archipelago. Through data collection, it was possible to document the presence of 43 species of marine Heterobranchia. Data analysis showed a remarkable homogeneity in the number of species between the examined sites. This is probably due to the peculiar environmental homogeneity present in the sites of this island, which are almost all rich in the presence of both benthic suspension feeders (the favorite prey of many groups of marine Heterobranchia) and environments full of crevices, grottos, and vertical walls, which are the preferred habitats of the majority of these mollusks. The higher number of marine heterobranch species found in Marettimo compared to the smaller number of species found on the other recently examined Sicilian islands (Pantelleria, Lipari, and Vulcano) is probably due to the massive presence of rich coralligenous biocoenoses and the particular hydrodynamic regime to which Marettimo is subject.
Environmental DNA Detection in Marine Macrophyte Ecosystems as a Potential Blue Carbon Source in Sediments
Authors: Xing Qikun , Kim Samuel J. , Yarish Charles
Published: November 2024

“Blue carbon” refers to the carbon sequestered by the world’s oceanic and coastal ecosystems, particularly through coastal vegetation such as mangroves, salt marshes, seagrasses, and marine macroalgae. These ecosystems play a crucial role in the global carbon cycle by serving as significant carbon sinks, absorbing carbon dioxide from the atmosphere and storing it in biomass and sediments over long periods. This study explores the use of environmental DNA (eDNA) to detect marine macrophytes and microalgae assemblages contributing to blue carbon in sediments across various coastal ecosystems. The research addresses the challenges of traditional monitoring methods by utilizing high-throughput sequencing of the 18S-V9 region amplified using eDNA from sediment samples collected at eight locations in the United States and South Korea. The results reveal a diverse array of taxa, underscoring the variability in community composition across different conditions. Notably, sites with seagrass beds and Ulva blooms showed distinct patterns in microalgal community structure. This study underscores the potential of eDNA analysis in providing comprehensive insights into the biodiversity of marine macrophyte ecosystems, thus informing conservation efforts and enhancing the understanding of marine ecological dynamics.
Adsorption Behavior of Fluorocarbon Surfactants on Polytetrafluoroethylene Surface
Authors: Yan Fei , Ma Cheng , Gong Qingtao , Ma Wangjing , Jin Zhiqiang , Xu Zhicheng , Zhang Lei , Zhang Lu
Published: November 2024

By using the sessile drop method, the wetting properties of nonionic fluorocarbon surfactants (FNS-1 and FNS-2) and anionic fluorocarbon surfactant (FAS) solutions on the surface of polytetrafluoroethylene (PTFE) were investigated. Meanwhile, the effects of surfactant concentration on the contact angle, adhesion tension, PTFE–liquid interfacial tension, and work of adhesion of the fluorocarbon surfactant with different structures were detected. The results demonstrate that the adsorption amount of the three fluorocarbon surfactants at the air–liquid interface is 1.5~2 times higher than their adsorption amount at the PTFE–solution interface. Before critical micelle concentration (CMC), the fluorocarbon surfactant molecules rely on their hydrophobic groups to adsorb on the PTFE surface. The smallest molecular size of FNS-2 results in the largest adsorption amount, while electrostatic repulsion and large steric hindrance result in the smallest adsorption amount for FAS. Above CMC, the fluorocarbon surfactants form semi-micelles to adsorb on the PTFE surface. The hydrophilic modification ability of the three fluorocarbon surfactants for the PTFE surface is stronger than that of reported surfactants, and the contact angle can be reduced to about 20° at high concentrations. The order of the hydrophilic modification ability is FNS-2 > FNS-1 > FAS. Hydrophilic EO groups can effectively enhance the hydrophilicity of FNS-1 and FNS-2. Due to the hydrophobic -CH3 group and the smaller adsorption amount, FNS-1 possesses a weaker hydrophilic modification ability than FNS-2. Investigating the adsorption behavior of fluorocarbon surfactants on the PTFE surface can help us to better utilize fluorocarbon surfactants. This could have broad implications for colloid and interface science.
Impact of Underlying Chronic Medical Conditions on COVID-19 Outcomes Among People Living with HIV: A Retrospective Analysis from the Minnesota Fairview Network
Authors: Aremu Taiwo Opeyemi , Yang Kaifeng , Lu Han , Oluwole Oluwatosin Esther , Adeyinka Kehinde Oluwatosin
Published: November 2024

(1) Background: The Coronavirus Disease 2019 (COVID-19) pandemic has raised concerns about the impact of underlying medical conditions on the health outcomes of people living with HIV (PLWH). This study aimed to assess how pre-existing chronic medical conditions affect the health outcomes of PLWH infected with COVID-19. (2) Methods: A retrospective study using data from the Minnesota Fairview network (1 January 2020–31 December 2022) was conducted. Fisher’s exact test, the Kruskal–Wallis rank-sum test, and ordinal logistic regressions with a Benjamini–Hochberg (BH) adjustment on p-values were used to assess the influence of chronic conditions on COVID-19 severity, adjusting for age and gender. (3) Results: Among 216 records, significant associations were found for a stroke, chronic kidney disease, lung disease, and neurologic conditions (p < 0.05). Type 1 diabetes was marginally significant (0.05 < p < 0.1). After adjusting for age and sex, a stroke (p = 0.0008, BH-adjusted p = 0.0044) and chronic kidney disease (p = 0.0003, BH-adjusted p = 0.0033) significantly increased the risk of severe COVID-19 outcomes. (4) Conclusions: Pre-existing medical conditions should be considered in the clinical management and public health interventions for PLWH infected with COVID-19. Tailored strategies are essential to mitigate the higher risk of severe outcomes in PLWH with specific chronic comorbidities.
Mind–Body Health in Crisis: A Survey of How Students Cared for Themselves Amidst the COVID-19 Pandemic
Authors: Winter Emily L. , deLeyer-Tiarks Johanna , Bellara Aarti P. , Bray Melissa A. , Schreiber Samantha
Published: November 2024

The focus on college students’ mental and physical health is steadily increasing with more students reporting concern and need for services. This study investigates the results of college students’ utilization of mind–body health activities and services in the wake of COVID-19. As part of a larger research study on college wellbeing, a survey completed by 557 college students between May and August of 2020 assessed student’s use of mind–body health strategies. To examine differences in mind–body health (MBH) service and activity usage before and during COVID-19 campus closures, paired t-tests were used, while one-way ANOVAs were used to determine differences based on demographic variables. Findings across MBH service and activity use during campus closures were variable, with use differing based on a variety of factors including gender, socioeconomic background, age, and race, as well as the participant’s personal prior history of services. These findings provide insight into what services students accessed during the lockdown period to aid university health systems with recommended guidance and resources.
Investigating Exchange Efficiencies of Sodium and Magnesium to Access Lithium from β-Spodumene and Li-Stuffed β-Quartz (γ-Spodumene)
Authors: Gamage McEvoy Joanne , Thibault Yves , Duguay Dominique
Published: November 2024

After the high-temperature pretreatment of α-spodumene to induce a phase transition to β-spodumene, a derivative of the silica polymorph keatite, often coexisting with metastable Li-stuffed β-quartz (γ-spodumene), the conventional approach to access lithium is through ion exchange with hydrogen using concentrated sulfuric acid, which presents drawbacks associated with the production of low-value leaching residues. As sodium and magnesium can produce more interesting aluminosilicate byproducts, this study investigates Na+ ↔ Li+ and Mg2+ ↔ 2 Li+ substitution efficiencies in β-spodumene and β-quartz. Thermal annealing at 850 °C of the LiAlSi2O6 silica derivatives mixed with an equimolar proportion of Na endmember glass of equivalent stoichiometry (NaAlSi2O6) indicates that sodium incorporation in β-quartz is limited, whereas the main constraint for not attaining complete growth to a Na0.5Li0.5AlSi2O6 β-spodumene solid solution is co-crystallization of minor nepheline. For similar experiments in the equimolar LiAlSi2O6-Mg0.5AlSi2O6 system, the efficient substitution of Mg for Li is observed in both β-spodumene and β-quartz, consistent with the alkaline earth having an ionic radius closer to lithium than sodium. Ion exchange at lower temperatures was also evaluated by exposing coexisting β-spodumene and β-quartz to molten salts. In NaNO3 at 320 °C, sodium for lithium exchange reaches ≈90% in β-spodumene but less than ≈2% in β-quartz, suggesting that to be an efficient lithium recovery route, the formation of β-quartz during the conversion of α-spodumene needs to be minimized. At 525 °C in a molten MgCl2/KCl medium, although full LiAlSi2O6-Mg0.5AlSi2O6 solid solution is observed in β-quartz, structural constraints restrict the incorporation of magnesium in β-spodumene to a Li0.2Mg0.4AlSi2O6 stoichiometry, limiting lithium recovery to 80%.
Mechanical, Tribological, and Corrosion Resistance Properties of (TiAlxCrNbY)Ny High-Entropy Coatings Synthesized Through Hybrid Reactive Magnetron Sputtering
Authors: Zoita Nicolae C. , Dinu Mihaela , Parau Anca C. , Pana Iulian , Kiss Adrian E.
Published: November 2024

This study investigates the effects of aluminum and nitrogen content on the microstructure, mechanical properties, and tribological performance of high-entropy coatings based on (TiCrAlxNbY)Ny systems. Using a hybrid magnetron sputtering technique, both metallic and nitride coatings were synthesized and evaluated. Increasing the aluminum concentration led to a transition from a crystalline to a nanocrystalline and nearly amorphous (NC/A) structure, with the TiAl0.5CrNbY sample (11.8% Al) exhibiting the best balance of hardness (6.8 GPa), elastic modulus (87.1 GPa), and coefficient of friction (0.64). The addition of nitrogen further enhanced these properties, transitioning the coatings to a denser fine-grained FCC structure. The HN2 sample (45.8% nitrogen) displayed the highest hardness (21.8 GPa) but increased brittleness, while the HN1 sample (32.9% nitrogen) provided an optimal balance of hardness (14.3 GPa), elastic modulus (127.5 GPa), coefficient of friction (0.60), and wear resistance (21.2 × 10−6 mm3/Nm). Electrochemical impedance spectroscopy revealed improved corrosion resistance for the HN1 sample due to its dense microstructure. Overall, the (TiAl0.5CrNbY)N0.5 coating achieved the best performance for friction applications, such as break and clutch systems, requiring high coefficients of friction, high wear resistance, and durability.
Influence of Mechanical Activation on the Evolution of TiSiCN Powders for Reactive Plasma Spraying
Authors: Baimoldanova Lazat , Rakhadilov Bauyrzhan , Kengesbekov Aidar , Kuanyshbai Rashid
Published: November 2024

In modern materials science and surface engineering, reactive plasma spraying (RPS) holds a key position due to its ability to create high-quality coatings with unique properties. The effectiveness of this process is largely determined by the physicochemical characteristics of the initial powder materials. This study examines the effects of mechanical activation for two compositions in the TiSiCN system and their impact on the quality and performance characteristics of RPS-produced coatings. It is shown that mechanical activation induces significant changes in the crystalline structure of the powders, reducing their particle size and increasing their specific surface area, thereby enhancing the reactivity of the materials during mechanochemical reactions. These changes contribute to the formation of dense and durable coatings with improved hardness and thermal stability. Thermogravimetric analysis (TGA) results confirm that the powders retain stable thermal properties and exhibit resistance to oxidation and decomposition. X-ray structural analysis reveals multiphase structures, including TiC, SiC, and TiCN, with the TiCN phase playing a key role in ensuring coating hardness. Additionally, SEM analysis showed that the TiSiCN-2-2 coating possesses a denser and more homogeneous structure with minimal pores and microcracks, providing superior mechanical strength and wear resistance compared to TiSiCN-1-2. Cross-sectional micrographs further revealed that the TiCN + Si coating has a greater average thickness (39.87 μm) and more uniform distribution compared to Ti + SiC (35.48 μm), indicating better application control and a more homogeneous material structure. Mechanical activation significantly influences the properties of powders, allowing for the determination of optimal parameters for RPS, which is a highly efficient method for creating coatings with unique performance characteristics.
Pressure-Induced Structural Phase Transition and Fluorescence Enhancement of Double Perovskite Material Cs2NaHoCl6
Authors: Yan Tingting , Liu Linan , Xi Dongyang , Sun Lei , Jin Dinghan , Li Han
Published: November 2024

Cs2NaHoCl6, a double perovskite material, has demonstrated extensive application potential in the fields of anti-counterfeiting and optoelectronics. The synthesis of Cs2NaHoCl6 crystals was achieved using a hydrothermal method, followed by the determination of their crystal structures through single crystal X-ray diffraction techniques. The material exhibits bright red fluorescence when exposed to ultraviolet light, confirming its excellent optical properties. An in situ high-pressure fluorescence experiment was conducted on Cs2NaHoCl6 up to 10 GPa at room temperature. The results indicate that the material possibly undergoes a structural phase transition within the pressure range of 6.9–7.9 GPa, which is accompanied by a significant enhancement in fluorescence. Geometric optimization based on density functional theory (DFT) revealed a significant decrease in the bond lengths and crystal volumes of Ho-Cl and Na-Cl across the predicted phase transition range. Furthermore, it was observed that the bond lengths of Na-Cl and Ho-Cl reach an equivalent state within this phase transition interval. The alteration in bond length may modify the local crystal field strength surrounding Ho3+, consequently affecting its electronic transition energy levels. This could be the primary factor contributing to the structural phase transition.
Congruent and Hierarchical Intra-Lake Subdivisions from Nuclear and Mitochondrial Data of a Lake Baikal Shoreline Amphipod
Authors: Väinölä Risto , Kontula Tytti , Mashiko Kazuo , Kamaltynov Ravil M.
Published: November 2024

A central goal of molecular studies on ancient lake faunas is to resolve the origin and phylogeny of their strikingly diverse endemic species flocks. Another equally intriguing goal is to understand the integrity of individual morphologically diagnosed species, which should help to perceive the nature and speed of the speciation process, and the true biological species diversity. In the uniquely diverse Lake Baikal amphipod crustaceans, molecular data from shallow-water species have often disclosed their cryptic subdivision into geographically segregated genetic lineages, but the evidence so far is mainly based on mitochondrial DNA. We now present a lake-wide parallel survey of both mitochondrial and multilocus nuclear genetic structuring in the common shoreline amphipod Eulimnogammarus verrucosus, known to comprise three deep, parapatric mtDNA lineages. Allele frequencies of seven nuclear allozyme loci divide the data into three main groups whose distributions exactly match the distributions of the main mitochondrial lineages S, W, and E and involve a further division of the W cluster into two subgroups. The inter-group differences involve one to four diagnostic loci and additional group-specific alleles. The transition zones are either abrupt (1 km), occur over a long segment of uninhabitable shoreline, or may be gradual with non-coincident clinal change at different loci. Mitochondrial variation is hierarchically structured, each main lineage further subdivided into 2–4 parapatric sublineages or phylogroups, and patterns of further local segregation are seen in some of them. Despite the recurring observations of cryptic diversity in Baikalian amphipods, the geographical subdivisions and clade depths do not match in different taxa, defying a common explanation for the diversification in environmental history.
Impact of an Ambulatory Clinical Pharmacy Population Health Initiative on HbA1c Reduction and Value-Based Measures: A Retrospective, Single-Center Cohort Study
Authors: Nelson Savannah , Butler Tasha A. , Martinez Amanda , Bianco Jessica , Blanco Delilah , Carris Nicholas W.
Published: November 2024

Background: Studies of pharmacists’ clinical programs have demonstrated improvements in controlling chronic diseases. However, significantly less data are available regarding pharmacist impact in a value-based Patient-Centered Medical Home (PCMH). The present study assessed a population health initiative to incorporate pharmacists for the management of type 2 diabetes (T2D), hypertension, and hyperlipidemia in a PCMH. Methods: This was a single-center retrospective cohort study of patients with T2D and baseline glycated hemoglobin (HbA1c) greater than 9%. Patients were excluded if they received care from an endocrinology provider or were lost to follow-up during the observation window of 1 January 2023 through 31 July 2023. Patients were analyzed in two cohorts: (1) patients who received any outpatient care from a clinical pharmacist (pharmacist cohort) and (2) patients who did not receive any outpatient care from a clinical pharmacist (usual care cohort). The primary outcome was the proportion of patients achieving an HbA1c of less than 8%. Secondary outcomes included blood pressure control and receipt of guideline-directed statin therapy. Results: Ninety-one patients were identified, twenty-nine in the pharmacist cohort and sixty-two in the usual care cohort. The overall population was older (mean age ~66 years), 59% female, and racially diverse (<50% Caucasian). HbA1c less than 8% was achieved in 34% of patients in the pharmacist cohort and 29% of patients in the usual care cohort (p = 0.001). A blood pressure goal of less than 140/90 mmHg was achieved more frequently in the pharmacist cohort (90% vs. 61%, p = 0.006), but guideline-directed statin therapy was similar between groups (90% vs. 79%, p = 0.215). Conclusions: Pharmacists can play an integral role within a PCMH to improve value-based measures for HbA1c and blood pressure control. Further research is needed to assess the impact of pharmacist care on statin use and economic outcomes.
Assessing the Feasibility of Handheld Cameras to Increase Access to Teleretinal Diabetic Retinopathy Screenings in Safety Net Clinics in Los Angeles
Authors: Green Gabrielle , Flores Roxana , Figueroa Elvia , Kuo Tony , Daskivich Lauren P.
Published: November 2024

Background: Handheld cameras may increase access to teleretinal diabetic retinopathy screenings (TDRS), as they are more economical and nimbler than traditional desktop cameras. However, their use in safety net clinical settings is less understood. Methods: The Los Angeles County Department of Public Health collaborated with the Los Angeles County Department of Health Services (DHS) to pilot the use of handheld cameras in DHS’s TDRS program. This study assessed screening metrics and interviewed TDRS coordinators and photographers about their experiences using these cameras. Results: Handheld cameras were harder to operate and performed less optimally on key screening metrics (e.g., image quality) compared to desktop cameras. However, this challenge appeared to be linked to the selected model rather than to all handheld cameras. The adoption of handheld cameras in DHS was aided by their integration into an existing agency infrastructure that already supported the use of desktop cameras; these operational supports included an established workflow, a data platform, and experienced photographers. Conclusions: The use of handheld cameras for TDRS is a promising practice for assuring equitable access to screenings. Handheld cameras are portable, smaller in size, and lower in cost than desktop cameras. Future projects should invest in and assess the performance of higher-quality models of these cameras, especially their use in safety net clinical settings.
Ultrasound Imaging Comparison of Crural Fascia Thickness and Muscle Stiffness in Stroke Patients with Spasticity
Authors: Choi Jongwon , Do Yerim , Lee Haneul
Published: November 2024

Background/Objective: Spasticity following stroke causes structural changes in the muscles and fascia, affecting the mobility and functional recovery of patients. Understanding these structural changes is critical to optimizing the rehabilitation strategies for patients. Therefore, in this study, we aimed to investigate the differences in crural and epimysial fascia thickness and muscle stiffness in the affected and unaffected lower limbs of chronic stroke patients with spasticity. Methods: A total of 88 patients with chronic stroke (mean age: 62.7 ± 10.2 years) were included in this study. Ankle range of motion, crural fascial thickness, and muscle stiffness in affected and unaffected lower limbs were assessed using ultrasound. Results: For the affected lower limbs, 59 patients (67.1%) exhibited a modified Ashworth scale score of 2, whereas 29 patients (32.9%) exhibited a score of 3. Ankle range of motion, fascia thickness, and muscle stiffness were also measured. The range of motion in ankle dorsiflexion and plantar flexion was significantly reduced on the affected side (p < 0.05). Crural fascia thickness was significantly greater in all regions of the affected side (anterior: 0.96 ± 0.14 vs. 0.72 ± 0.08 mm [p < 0.001]; lateral: 1.01 ± 0.14 vs. 0.75 ± 0.14 mm [p < 0.001]), and the epimysial fascia of the tibialis anterior muscle was similarly greater in the affected side (0.46 ± 0.07 vs. 0.34 ± 0.03 mm [p < 0.001]). However, no significant differences in muscle stiffness were observed between the affected and unaffected sides (p > 0.05). Conclusions: Overall, these findings revealed significant fascial thickening with only minimal changes in muscle stiffness on the affected side, highlighting the importance of controlling fascial changes for post-stroke spasticity management.
Fostering the Interdisciplinary Learning of Contemporary Physics Through Digital Technologies: The “Gravitas” Project
Authors: Tuveri Matteo , Steri Arianna , Fadda Daniela , Stefanizzi Riccardo , Fanti Viviana , Bonivento Walter Marcello
Published: November 2024

The interdisciplinary teaching of contemporary physics has become increasingly common in physics education, especially for high school students and teachers. This approach, which integrates content and methodologies from various disciplines, fosters scientific reasoning, enhances creativity, and increases student motivation and interest in physics. The use of digital technologies, such as social media platforms, supports these educational goals by facilitating the inclusive and cost-effective dissemination of scientific knowledge and the development of soft skills. This paper introduces the “Gravitas” project, an initiative that employs an interdisciplinary approach to present contemporary physics topics to high school students through social media. Coordinated by the Cagliari Division of the National Institute of Nuclear Physics (INFN) in Italy, the “Gravitas” project offers a non-traditional learning environment where students explore modern physics and philosophy and the history of science. Through the creation of educational materials, such as social media posts, students actively engage in their learning. In 2022, around 250 students from 16 high schools across Sardinia, Italy, participated in this project. This paper discusses the learning outcomes, highlighting the potential of integrating formal high school curricula with innovative educational and digital tools.
Non-Equilibrium Quantum Brain Dynamics: Water Coupled with Phonons and Photons
Authors: Nishiyama Akihiro , Tanaka Shigenori , Tuszynski Jack Adam
Published: November 2024

We investigate Quantum Electrodynamics (QED) of water coupled with sound and light, namely Quantum Brain Dynamics (QBD) of water, phonons and photons. We provide phonon degrees of freedom as additional quanta in the framework of QBD in this paper. We begin with the Lagrangian density QED with non-relativistic charged bosons, photons and phonons, and derive time-evolution equations of coherent fields and Kadanoff–Baym (KB) equations for incoherent particles. We next show an acoustic super-radiance solution in our model. We also introduce a kinetic entropy current in KB equations in 1st order approximation in the gradient expansion and show the H-theorem for self-energy in Hartree–Fock approximation. We finally derive conserved number density of charged bosons and conserved energy density in spatially homogeneous system.
Bayesian Mechanics of Synaptic Learning Under the Free-Energy Principle
Authors: Kim Chang Sub
Published: November 2024

The brain is a biological system comprising nerve cells and orchestrates its embodied agent’s perception, behavior, and learning in dynamic environments. The free-energy principle (FEP) advocated by Karl Friston explicates the local, recurrent, and self-supervised cognitive dynamics of the brain’s higher-order functions. In this study, we continue to refine the FEP through a physics-guided formulation; specifically, we apply our theory to synaptic learning by considering it an inference problem under the FEP and derive the governing equations, called Bayesian mechanics. Our study uncovers how the brain infers weight changes and postsynaptic activity, conditioned on the presynaptic input, by deploying generative models of the likelihood and prior belief. Consequently, we exemplify the synaptic efficacy in the brain with a simple model; in particular, we illustrate that the brain organizes an optimal trajectory in neural phase space during synaptic learning in continuous time, which variationally minimizes synaptic surprisal.
Gravitational Hamiltonian Systems and the Retarded Gravity Inequality
Authors: Yahalom Asher
Published: November 2024

Gravity and electromagnetic interactions are the only fundamental physical interactions (outside the nuclear domain). In this work, we shall concentrate on Hamiltonians containing gravitational interaction, which according to general relativity must be retarded. In recent years, retarded gravity has explained many of the mysteries surrounding the “missing mass” related to galactic rotation curves, the Tully–Fisher relations, and gravitational lensing phenomena. Indeed, a recent paper analyzing 143 galaxies has demonstrated that retarded gravity will suffice to explain galaxies’ rotation curves without the need to postulate dark matter for multiple types of galaxies. Moreover, it also demystified the “missing mass” related to galactic clusters and elliptic galaxies in which excess matter was derived through the virial theorem. Here, we give a mathematical criterion that specifies the cases in which retardation is important for gravity (and when it is not). The criterion takes the form of an inequality.
“In Mathematical Language”: On Mathematical Foundations of Quantum Foundations
Authors: Plotnitsky Arkady
Published: November 2024

The argument of this article is threefold. First, the article argues that from its rise in the sixteenth century to our own time, the advancement of modern physics as mathematical-experimental science has been defined by the invention of new mathematical structures. Second, the article argues that quantum theory, especially following quantum mechanics, gives this thesis a radically new meaning by virtue of the following two features: on the one hand, quantum phenomena are defined as essentially different from those found in all previous physics by purely physical features; and on the other, quantum mechanics and quantum field theory are defined by purely mathematical postulates, which connect them to quantum phenomena strictly in terms of probabilities, without, as in all previous physics, representing or otherwise relating to how these phenomena physically come about. While these two features may appear discordant, if not inconsistent, I argue that they are in accord with each other, at least in certain interpretations (including the one adopted here), designated as “reality without realism”, RWR, interpretations. This argument also allows this article to offer a new perspective on a thorny problem of the relationships between continuity and discontinuity in quantum physics. In particular, rather than being concerned only with the discreteness and continuity of quantum objects or phenomena, quantum mechanics and quantum field theory relate their continuous mathematics to the irreducibly discrete quantum phenomena in terms of probabilistic predictions while, at least in RWR interpretations, precluding a representation or even conception of how these phenomena come about. This subject is rarely, if ever, discussed apart from previous work by the present author. It is, however, given a new dimension in this article which introduces, as one of its main contributions, a new principle: the mathematical complexity principle.
Still No Evidence for an Effect of the Proportion of Non-Native Speakers on Natural Language Complexity
Authors: Koplenig Alexander
Published: November 2024

In a recent study, I demonstrated that large numbers of L2 (second language) speakers do not appear to influence the morphological or information-theoretic complexity of natural languages. This paper has three primary aims: First, I address recent criticisms of my analyses, showing that the points raised by my critics were already explicitly considered and analysed in my original work. Furthermore, I show that the proposed alternative analyses fail to withstand detailed examination. Second, I introduce new data on the information-theoretic complexity of natural languages, with the estimates derived from various language models—ranging from simple statistical models to advanced neural networks—based on a database of 40 multilingual text collections that represent a wide range of text types. Third, I re-analyse the information-theoretic and morphological complexity data using novel methods that better account for model uncertainty in parameter estimation, as well as the genealogical relatedness and geographic proximity of languages. In line with my earlier findings, the results show no evidence that large numbers of L2 speakers have an effect on natural language complexity.
Effect of per Capita Income, GDP Growth, FDI, Sectoral Composition, and Domestic Credit on Employment Patterns in GCC Countries: GMM and OLS Approaches
Authors: Adam Nawal Abdalla , Alzuman Abad
Published: November 2024

This paper examines the impact of per capita income, gross domestic product (GDP) growth, foreign direct investment (FDI), sectoral composition, and domestic credit on employment patterns in the Gulf Cooperation Council (GCC) countries from 2013 to 2023, based on “Okun’s law”. The dynamic data panel was analyzed using the generalized method of moments (GMM) and the ordinary least square (OLS) method. The research findings reveal that the agricultural sector’s contributions have significantly influenced the employment patterns in GCC countries, emphasizing the traditional role of agriculture in creating job opportunities. However, the contribution of the services and industrial sectors has no significant impact on employment patterns. Domestic credit and FDI inflows have significantly influenced employment patterns in GCC countries, underscoring their vital role in sustaining long-term economic stability. Per capita income and GDP growth did not significantly impact the employment pattern in the GCC countries during the study period. This research provides valuable insights to policymakers, highlighting the need to focus on the services and industrial sectors to promote their contribution to employment in GCC countries. The research findings also augment the literature by identifying the key economic indicators contributing to GCC countries’ employment creation.
Self-Control or Crime Control: Teachers’ Insights on Good Practices in 1:1 Classrooms and Implications for Professional Development
Authors: Amdam Synnøve H. , Nagel Ilka , Njå Morten B. , Forsström Sanna
Published: November 2024

Norway ranks high in digitalization in schools, with over 90% of students in grades 1–10 having their own digital device supplied by their school districts and reporting the highest use of digital tools globally in the latest PISA report. However, research shows that implementation processes and competence measures for teachers’ professional use of digital devices vary considerably between schools. This study aims to inform the development of research-practice partnership (RPP) measures focused on professional digital competence development in digitalizing schools internationally by exploring what teachers consider important for good teaching practices in 1:1 computing classrooms. We draw on both closed and open survey responses from 1505 Norwegian teachers in highly digitalized schools where the most experienced teachers have had 1:1 computing since 2014. The findings show that classroom management is seen as gradually more important with higher digital teaching competence and more experience, but that the teachers’ understandings of what digital competence entails and their use of classroom management strategies are rather limited. The study concludes that professional competence development measures that provide broader understandings of digital competence and classroom management are needed, dependent on competence levels and experience, as well as systematic training of students’ digital self-regulation.
A Carbon-Particle-Supported Palladium-Based Cobalt Composite Electrocatalyst for Ethanol Oxidation Reaction (EOR)
Authors: Ding Keqiang , Li Weijia , Li Mengjiao , Bai Ying , Liang Xiaoxuan , Wang Hui
Published: November 2024

For the first time, carbon-particle-supported palladium-based cobalt composite electrocatalysts (abbreviated as PdxCoy/CPs) were prepared using a calcination–hydrothermal process–hydrothermal process (denoted as CHH). The catalysts of PdxCoy/CPs prepared using CoC2O4·2H2O, (CH3COO)2Co·4H2O, and metallic cobalt were named catalyst c1, c2, and c3, respectively. For comparison, the catalyst prepared in the absence of a Co source (denoted as Pd/CP) was identified as catalyst c0. All fabricated catalysts were thoroughly characterized by XRD, EDS, XPS, and FTIR, indicating that PdO, metallic Pd, carbon particles, and a very small amount of cobalt oxide were the main components of all produced catalysts. As demonstrated by the traditional electrochemical techniques of CV and CA, the electrocatalytic performances of PdxCoy/CP towards the ethanol oxidation reaction (EOR) were significantly superior to that of Pd/CP. In particular, c1 showed an unexpected electrocatalytic activity for EOR; for instance, in the CV test, the peak f current density of EOR on catalyst c1 was 129.3 mA cm−2, being about 10.7 times larger than that measured on Pd/CP, and in the CA test, the polarized current density of EOR recorded for c1 after 7200 s was still about 2.1 mA cm−2, which was larger than that recorded for Pd/CP (0.6 mA cm−2). In the catalyst preparation process, except for the elements of C, O, Co, and Pd, no other elements were involved, which was thought to be the main contribution of this preliminary work, being very meaningful to the further exploration of Pd-based composite EOR catalysts.
Bacterial Consortium Biofilm-Based Electrochemical Biosensor for Measurement of Antioxidant Polyphenolic Compounds
Authors: Sukma Rani Melati , Iswantini Dyah , Nurhidayat Novik , Rafi Mohamad
Published: November 2024

This work describes the development of an electrochemical biosensor method based on bacterial consortia to determine antioxidant capacity. The bacterial consortium used is a combination of bacteria from the genera Bacillus and Pseudomonas which can produce the enzymes tyrosinase and laccase. The consortium bacteria were immobilized on the surface of the screen-printed carbon electrode (SPCE) to form a biofilm. Biofilms were selected based on the highest current response evaluated electrochemically using cyclic voltammetry analysis techniques. Optimum consortium biofilm conditions were obtained in a phosphate buffer solution of pH 7, and biofilm formation occurred on day 7. This work produces analytical performance with a coefficient of determination (R2) of 0.9924. The limit of detection (LOD) and limit of quantification (LOQ) values are 0.5 µM and 10 µM, respectively. The biosensor showed a stable response until the 10th week. This biosensor was used to measure the antioxidant capacity of five extracts, and the results were confirmed using a standard method, the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method. The highest antioxidant capacity is guava extract and the lowest is tempuyung extract. Thus, the development of this biosensor method can be used as an alternative for measuring antioxidant capacity.
Vector Reconfiguration on a Bidirectional Multilevel LCL-T Resonant Converter
Authors: Shi Jie , Zhang Zhongyi , Xu Yi , Zou Dandan , Cao Hui
Published: November 2024

With the development of distributed energy technology, the establishment of the energy internet has become a general trend, and relevant research about the core component, energy router, has also become a hotspot. Therefore, the bidirectional isolated DC–DC converter (BIDC) is widely used in AC–DC–AC energy router systems, because it can flexibly support the DC bus voltage ratio and achieve bidirectional power flow. This paper proposes a novel vector reconfiguration on a bidirectional multilevel LCL-T resonant converter in which an NPC (neutral-point clamped) multilevel structure with a flying capacitor is introduced to form a novel active bridge, and a coupling transformer is specially added into the active bridge to achieve multilevel voltage output under hybrid modulation. In addition, an LCL-T two-port vector analysis is adopted to elaborate bidirectional power flow which can generate some reactive power to realize zero-voltage switching (ZVS) on active bridges to improve the efficiency of the converter. Meanwhile, due to the symmetry of the LCL-T structure, the difficulty of the bidirectional operation analysis of the power flow is reduced. Finally, a simulation study is designed with a rated voltage of 200 V on front and rear input sources which has a rated power of 450 W with an operational efficiency of 93.8%. Then, the feasibility of the proposed converter is verified.
Enhancing Keystroke Dynamics Authentication with Ensemble Learning and Data Resampling Techniques
Authors: Wang Xiaofei , Hou Daqing
Published: November 2024

Background: Keystroke dynamics authentication is a behavioral biometric method that verifies user identity by analyzing typing patterns. While traditional machine learning methods (e.g., decision trees, SVM) have shown potential in this field, their performance suffers in real-world scenarios due to data imbalance and limited recognition of certain classes, undermining system security and reliability. Methods: To address these issues, this study combines the Synthetic Minority Over-sampling Technique (SMOTE) with ensemble learning methods to improve classification accuracy. A Django-based platform was developed for standardized keystroke data collection, generating a balanced dataset to evaluate various classifiers. Experiments: Experiments were conducted using both the Django-collected dataset and the CMU benchmark dataset to compare traditional classifiers with SMOTE-enhanced ensemble learning models, such as Random Forest, XGBoost, and Bagging, on metrics like accuracy, recall, G-mean, and F1-score. Conclusions: The results show that SMOTE-enhanced ensemble learning models significantly outperform traditional classifiers, particularly in detecting minority classes. This approach effectively addresses data imbalance, improving model robustness and security, and provides a practical reference for building more reliable keystroke dynamics authentication systems.
Optimizing Microgrid Performance: Integrating Unscented Transformation and Enhanced Cheetah Optimization for Renewable Energy Management
Authors: Alghamdi Ali S.
Published: November 2024

The increased integration of renewable energy sources (RESs), such as photovoltaic and wind turbine systems, in microgrids poses significant challenges due to fluctuating weather conditions and load demands. To address these challenges, this study introduces an innovative approach that combines Unscented Transformation (UT) with the Enhanced Cheetah Optimization Algorithm (ECOA) for optimal microgrid management. UT, a robust statistical technique, models nonlinear uncertainties effectively by leveraging sigma points, facilitating accurate decision-making despite variable renewable generation and load conditions. The ECOA, inspired by the adaptive hunting behaviors of cheetahs, is enhanced with stochastic leaps, adaptive chase mechanisms, and cooperative strategies to prevent premature convergence, enabling improved exploration and optimization for unbalanced three-phase distribution networks. This integrated UT-ECOA approach enables simultaneous optimization of continuous and discrete decision variables in the microgrid, efficiently handling uncertainty within RESs and load demands. Results demonstrate that the proposed model significantly improves microgrid performance, achieving a 10% reduction in voltage deviation, a 10.63% decrease in power losses, and an 83.32% reduction in operational costs, especially when demand response (DR) is implemented. These findings validate the model’s efficacy in enhancing microgrid reliability and efficiency, positioning it as a viable solution for optimized performance under uncertain renewable inputs.
DeFFace: Deep Face Recognition Unlocked by Illumination Attributes
Authors: Zhou Xiangling , Gao Zhongmin , Gong Huanji , Li Shenglin
Published: November 2024

General face recognition is currently one of the key technologies in the field of computer vision, and it has achieved tremendous success with the support of deep-learning technology. General face recognition models currently exhibit extremely high accuracy on some high-quality face datasets. However, their performance decreases in challenging environments, such as low-light scenes. To enhance the performance of face recognition models in low-light scenarios, we propose a face recognition approach based on feature decoupling and fusion (DeFFace). Our main idea is to extract facial-related features from images that are not influenced by illumination. First, we introduce a feature decoupling network (D-Net) to decouple the image into facial-related features and illumination-related features. By incorporating the illumination triplet loss optimized with unpaired identity IDs, we regulate illumination-related features to minimize the impact of lighting conditions on the face recognition system. However, the decoupled features are relatively coarse. Therefore, we introduce a feature fusion network (F-Net) to further extract the residual facial-related features from the illumination-related features and fuse them with the initial facial-related features. Finally, we introduce a lighting-facial correlation loss to reduce the correlation between the two decoupled features in the specific space. We demonstrate the effectiveness of our method on four real-world low-light datasets and three simulated low-light datasets. We retrain multiple general face recognition methods using our proposed low-light training sets to further validate the advanced performance of our method. Compared to general face recognition methods, our approach achieves an average improvement of more than 2.11 percentage points on low-light face datasets. In comparison with image enhancement-based solutions, our method shows an average improvement of around 16 percentage points on low-light datasets, and it also delivers an average improvement of approximately 5.67 percentage points when compared to illumination normalization-based methods.
Method for Reconstructing Velocity Field Images of the Internal Structures of Bridges Based on Group Sparsity
Authors: Li Jian , Li Jin , Guo Chenli , Wu Hongtao , Li Chuankun , Liu Rui , Wei Lujun
Published: November 2024

Non-destructive testing (NDT) enables the determination of internal defects and flaws in concrete structures without damaging them, making it a common application in current bridge concrete inspections. However, due to the complexity of the internal structure of this type of concrete, limitations regarding measurement point placement, and the extensive detection area, accurate defect detection cannot be guaranteed. This paper proposes a method that combines the Simultaneous Algebraic Reconstruction Technique with Group Sparsity Regularization (SART-GSR) to achieve tomographic imaging of bridge concrete under sparse measurement conditions. Firstly, a mathematical model is established based on the principles of the tomographic imaging of bridge concrete; secondly, the SART algorithm is used to solve for its velocity values; thirdly, on the basis of the SART results, GSR is applied for optimized solution processing; finally, simulation experiments are conducted to verify the reconstruction effects of the SART-GSR algorithm compared with those of the SART and ART algorithms. The results show that the SART-GSR algorithm reduced the relative error to 1.5% and the root mean square error to 89.76 m/s compared to the SART and ART algorithms. This improvement in accuracy makes it valuable for the tomographic imaging of bridge concrete and provides a reference for defect detection in bridge concrete.