bluuebunny/crossref_metadata_2025_split huggingface dataset:
Satellite Onboard Transmitter Design With Spread Spectrum MIMO Antenna for 5G Wireless Networks
Authors: Muttiah Ravandran 
Published: September 2024

AbstractThe 5G new era implements standalone satellite communications that support wireless networking systems for future mobile communications by locating multiple satellites in low Earth orbit to provide global coverage of the entire Earth's surface. In this research, a newly found model of a satellite onboard transmitter using a uniform circular array multiple‐input multiple‐output antenna was designed to operate at a carrier frequency of 12 GHz and derived theoretical equations compared to the real‐time scenario. The integration of spread spectrum with multiple‐input multiple‐output antenna provides an advantage for higher capacity. It has a higher percentage of gain amplification on improving the transmission of electromagnetic power to meet the bandwidth requirement of center operating frequency, and this can transmit over a bandwidth of 1.28 GHz. The proposed satellite onboard transmitter model design aims to minimize the components, increase the speed of operations for higher bandwidth, and transmit large amounts of information to a large group of users. The transmitter can operate for the speed of 1.28 Gbps using pseudo‐random code, direct‐sequence spread spectrum, quadrature phase shift keying modulation, bandwidth separated in bands for 64 symbols using 128 Chebyshev‐type bandpass filter for transmission using 128‐element uniform circular array multiple‐input multiple‐output antenna. The satellite transmitter antenna produces a maximum gain of 14.526 dBi, and a maximum directivity of 17.986 dBi, and the efficiency at 12 GHz is 45.1% for the radiated power at 0.93 mW. This satellite transmitter will interconnect 5G wireless networks for the application of mobile communications complement terrestrial‐dependent networks.
Evidence for widespread human exposure to food contact chemicals
Authors: Geueke Birgit , Parkinson Lindsey V. , Groh Ksenia J. , Kassotis Christopher D. , Maffini Maricel V. , Martin Olwenn V. , Zimmermann Lisa , Scheringer Martin , Muncke Jane 
Published: September 2024

Abstract
Background
Over 1800 food contact chemicals (FCCs) are known to migrate from food contact articles used to store, process, package, and serve foodstuffs. Many of these FCCs have hazard properties of concern, and still others have never been tested for toxicity. Humans are known to be exposed to FCCs via foods, but the full extent of human exposure to all FCCs is unknown.

Objective
To close this important knowledge gap, we conducted a systematic overview of FCCs that have been monitored and detected in human biomonitoring studies according to a previously published protocol.

Methods
We first compared the more than 14,000 known FCCs to five biomonitoring programs and three metabolome/exposome databases. In a second step, we prioritized FCCs that have been frequently detected in food contact materials and systematically mapped the available evidence for their presence in humans.

Results
For 25% of the known FCCs (3601), we found evidence for their presence in humans. This includes 194 FCCs from human biomonitoring programs, with 80 of these having hazard properties of high concern. Of the 3528 FCCs included in metabolome/exposome databases, most are from the Blood Exposome Database. We found evidence for the presence in humans for 63 of the 175 prioritized FCCs included in the systematic evidence map, and 59 of the prioritized FCCs lack hazard data.

Significance
Notwithstanding that there are also other sources of exposure for many FCCs, these data will help to prioritize FCCs of concern by linking information on migration and biomonitoring. Our results on FCCs monitored in humans are available as an interactive dashboard (FCChumon) to enable policymakers, public health researchers, and food industry decision-makers to make food contact materials and articles safer, reduce human exposure to hazardous FCCs and improve public health.

Impact statement
We present systematically compiled evidence on human exposure to 3601 food contact chemicals (FCCs) and highlight FCCs that are of concern because of their known hazard properties. Further, we identify relevant data gaps for FCCs found in food contact materials and foods. This article improves the understanding of food contact materials’ contribution to chemical exposure for the human population and highlights opportunities for improving public health.
SGLT2 inhibitors ameliorate NAFLD in mice via downregulating PFKFB3, suppressing glycolysis and modulating macrophage polarization
Authors: Lin Xia-fang , Cui Xiao-na , Yang Jin , Jiang Ya-fei , Wei Tian-jiao , Xia Li , Liao Xin-yue , Li Fei , Wang Dan-dan , Li Jian , Wu Qi , Yin De-shan , Le Yun-yi , Yang Kun , Wei Rui , Hong Tian-pei 
Published: September 2024

AbstractSodium-glucose co-transporter 2 (SGLT2) inhibitor (SGLT2i) is a novel class of anti-diabetic drug, which has displayed a promising benefit for non-alcoholic fatty liver disease (NAFLD). In this study, we investigated the protective effects of SGLT2i against NAFLD and the underlying mechanisms. The db/db mice and western diet-induced NAFLD mice were treated with dapagliflozin (1 mg·kg−1·d−1, i.g.) or canagliflozin (10 mg·kg−1·d−1, i.g.) for 8 weeks. We showed that the SGLT2i significantly improved NAFLD-associated metabolic indexes, and attenuated hepatic steatosis and fibrosis. Notably, SGLT2i reduced the levels of pro-inflammatory cytokines and chemokines, downregulated M1 macrophage marker expression and upregulated M2 macrophage marker expression in liver tissues. In cultured mouse bone marrow-derived macrophages and human peripheral blood mononuclear cell-derived macrophages, the SGLT2i (10, 20 and 40 μmol/L) significantly promoted macrophage polarization from M1 to M2 phenotype. RNA sequencing, Seahorse analysis and liquid chromatography-tandem mass spectrometry analysis revealed that the SGLT2i suppressed glycolysis and triggered metabolic reprogramming in macrophages. By using genetic manipulation and pharmacological inhibition, we identified that the SGLT2i targeted PFKFB3, a key enzyme of glycolysis, to modulate the macrophage polarization of M1 to M2 phenotype. Using a co-culture of macrophages with hepatocytes, we demonstrated that the SGLT2i inhibited lipogenesis in hepatocytes via crosstalk with macrophages. In conclusion, this study highlights a potential therapeutic application for repurposing SGLT2i and identifying a potential target PFKFB3 for NAFLD treatment.
Pressure-tuning of α-RuCl3 towards a quantum spin liquid
Authors: Stahl Q. , Ritschel T. , Garbarino G. , Cova F. , Isaeva A. , Doert T. , Geck J. 
Published: September 2024

AbstractThe layered material α-RuCl3 is a promising candidate to realize the Kitaev quantum spin liquid (QSL) state. However, at ambient pressure, deviations from the perfect Kitaev geometry prevent the existence of the QSL state at low temperatures. Here we present the discovery of a pressure-induced high-symmetry phase in α-RuCl3, which creates close to ideal conditions for the emergence of a QSL. Employing a novel approach based on Bragg and diffuse scattering of synchrotron radiation, we reveal a pressure-induced reorganization of the RuCl3-layers. Most importantly, this reorganization affects the structure of the layers themselves, which acquire a high trigonal symmetry. For this trigonal phase the largest ratio between the Kitaev (K) and the Heisenberg exchange (J) ever encountered is found: K/J = 124. Additionally, we demonstrate that this phase can also be stabilized by a slight biaxial pressure. This not only resolves the conflicting reports of low-temperature structures in the literature, but also facilitates the investigation of the high-symmetry phase and its potential QSL using a range of experimental techniques.
Tunable cell differentiation via reprogrammed mating-type switching
Authors: Heng Yu Chyuan , Kitano Shohei , Susanto Adelia Vicanatalita , Foo Jee Loon , Chang Matthew Wook 
Published: September 2024

AbstractThis study introduces a synthetic biology approach that reprograms the yeast mating-type switching mechanism for tunable cell differentiation, facilitating synthetic microbial consortia formation and cooperativity. The underlying mechanism was engineered into a genetic logic gate capable of inducing asymmetric sexual differentiation within a haploid yeast population, resulting in a consortium characterized by mating-type heterogeneity and tunable population composition. The utility of this approach in microbial consortia cooperativity was demonstrated through the sequential conversion of xylan into xylose, employing haploids of opposite mating types each expressing a different enzyme of the xylanolytic pathway. This strategy provides a versatile framework for producing and fine-tuning functionally heterogeneous yet isogenic yeast consortia, furthering the advancement of microbial consortia cooperativity and offering additional avenues for biotechnological applications.
Computing high-degree polynomial gradients in memory
Authors: Bhattacharya Tinish , Hutchinson George H. , Pedretti Giacomo , Sheng Xia , Ignowski Jim , Van Vaerenbergh Thomas , Beausoleil Ray , Strachan John Paul , Strukov Dmitri B. 
Published: September 2024

AbstractSpecialized function gradient computing hardware could greatly improve the performance of state-of-the-art optimization algorithms. Prior work on such hardware, performed in the context of Ising Machines and related concepts, is limited to quadratic polynomials and not scalable to commonly used higher-order functions. Here, we propose an approach for massively parallel gradient calculations of high-degree polynomials, which is conducive to efficient mixed-signal in-memory computing circuit implementations and whose area scales proportionally with the product of the number of variables and terms in the function and, most importantly, independent of its degree. Two flavors of such an approach are proposed. The first is limited to binary-variable polynomials typical in combinatorial optimization problems, while the second type is broader at the cost of a more complex periphery. To validate the former approach, we experimentally demonstrated solving a small-scale third-order Boolean satisfiability problem based on integrated metal-oxide memristor crossbar circuits, with competitive heuristics algorithm. Simulation results for larger-scale, more practical problems show orders of magnitude improvements in area, speed and energy efficiency compared to the state-of-the-art. We discuss how our work could enable even higher-performance systems after co-designing algorithms to exploit massively parallel gradient computation.
Development of predictive indices for evaluating the UHI adaptation potential of green roof- and wall-based scenarios in the Mediterranean climate
Authors: Susca Tiziana , Iaria Jacopo , Zanghirella Fabio 
Published: September 2024

AbstractUrban heat islands can jeopardize urban inhabitants, but the installation of green roofs (GRs) and walls (GWs) can contribute to mitigating urban overheating. The present study provides novel indices to easily predict the spatial median variation in air temperature at pedestrian heights related to the application of GR- and GW-based scenarios during the hottest hours of a typical summer day by varying the building height (BH), coverage percentage, and leaf area index. The indices are meant to be applied to built areas with 0.3–0.4 urban density in the Mediterranean climate and are derived from regression models fed with the outputs of 281 simulations of three urban areas developed and run in ENVI-met software. The developed models are all highly significant. The GR model shows that mitigation is influenced by all three parameters, and it can estimate mitigation with a root mean square error of 0.05 °C. Compared with the other parameters, the GW models revealed that the BH did not influence the decrease in air temperature. The green façade and living wall (LW) indices predict mitigation with errors of 0.04 °C and 0.05 °C, respectively. However, for the LW model, further parameters should be considered to improve its reliability.
Impairment of health-related quality of life among people with type 2 diabetes and advanced liver fibrosis
Authors: Michel Maurice , Funuyet-Salas Jesús , Doll Michelle , Alqahtani Saleh A. , Armandi Angelo , Labenz Christian , Galle Peter R. , Schattenberg Jörn M. 
Published: September 2024

AbstractPeople with type 2 diabetes mellitus (T2DM) show a high prevalence of steatotic liver disease (SLD), and especially metabolic dysfunction-associated steatotic liver disease (MASLD), with liver fibrosis. Their health-related quality of life (HRQL) is affected by multiple in part overlapping factors and aggravated by metabolic and liver-related comorbidities, including liver fibrosis stage. The aim of this study was to investigate the effect size of advanced fibrosis (AF) on the HRQL in people with T2DM. A total of 149 individuals with T2DM treated at a primary care provider within the German disease management program (DMP) were included in the final analysis. Vibration-controlled transient elastography (VCTE) was used to non-invasively detect steatosis and AF. The EQ-5D-3L questionnaire was used to assess the HRQL. Uni- and multivariable linear regression models were used to identify independent predictors of impaired HRQL. The majority was male (63.1%), and the median age was 67 years (IQR 59; 71). In the entire cohort, the prevalence of MASLD and AF was 70.7% and 19.5%, respectively. People with T2DM and AF had an overall lower HRQL in comparison to those without AF (p < 0.001). Obesity (β: − 0.247; 95% CI − 0.419, − 0.077) and AF (β: − 0.222; 95% CI − 0.383, − 0.051) remained independent predictors of a poor HRQL. In turn, T2DM-related comorbidities were not predictive of an impaired HRQL. Obesity and AF negatively affect the HRQL in patients with SLD and T2DM in primary care. Awareness of liver health and specific interventions may improve patient-reported and liver-related outcomes in people with T2DM.
Efficacy of galcanezumab in migraine central sensitization
Authors: Danno Daisuke , Imai Noboru , Kitamura Shigekazu , Ishizaki Kumiko , Kikui Shoji , Takeshima Takao 
Published: September 2024

AbstractGalcanezumab, a monoclonal antibody targeting the calcitonin gene-related peptide pathway (CGRP mAb), acts peripherally due to its large size. However, recent studies have suggested that CGRP mAbs may also have a central mode of action. This study aimed to evaluate the central effects of galcanezumab on migraine central sensitization.This prospective real-world study was conducted at three headache centers in Japan between May 2021 and May 2022. Patients treated with galcanezumab for migraines were included in the study. The primary outcome was the change in the validated Central Sensitization Inventory (CSI) score from baseline to six months of treatment. We also assessed changes in the Allodynia Symptom Checklist (ASC-12) score. Eighty-six patients with migraine (73 female and 13 male) were analyzed. At 6 months, CSI and ASC-12 scores were significantly reduced compared to baseline (CSI: 36.0 vs. 29.3, p < 0.001; and ASC-12: 5.55 vs. 4.26, p < 0.01). Furthermore, these effects were observed as early as three months of treatment. In this study, we demonstrated the real-world efficacy of galcanezumab in improving central sensitization in migraine, with significant effects seen in the early phase of treatment.Trial registration: This study was registered with UMIN-CTR on May 2, 2021 (UMIN000044096).
A systematic review and meta analysis on digital mental health interventions in inpatient settings
Authors: Diel Alexander , Schröter Isabel Carolin , Frewer Anna-Lena , Jansen Christoph , Robitzsch Anita , Gradl-Dietsch Gertraud , Teufel Martin , Bäuerle Alexander 
Published: September 2024

AbstractE-mental health (EMH) interventions gain increasing importance in the treatment of mental health disorders. Their outpatient efficacy is well-established. However, research on EMH in inpatient settings remains sparse and lacks a meta-analytic synthesis. This paper presents a meta-analysis on the efficacy of EMH in inpatient settings. Searching multiple databases (PubMed, ScienceGov, PsycInfo, CENTRAL, references), 26 randomized controlled trial (RCT) EMH inpatient studies (n = 6112) with low or medium assessed risk of bias were included. A small significant total effect of EMH treatment was found (g = 0.3). The effect was significant both for blended interventions (g = 0.42) and post-treatment EMH-based aftercare (g = 0.29). EMH treatment yielded significant effects across different patient groups and types of therapy, and the effects remained stable post-treatment. The results show the efficacy of EMH treatment in inpatient settings. The meta-analysis is limited by the small number of included studies.
Optical detection strategies for Ni(ii) ion using metal–organic chemosensors: from molecular design to environmental applications
Authors: Naithani Sudhanshu , Dubey Ritesh , Goswami Tapas , Thetiot Franck , Kumar Sushil 
Published: September 2024

This study focuses on various luminescent and colorimetric metal–organic sensors employed for Ni(ii) detection, with an emphasis on state-of-the-art overview, latest development and challenges.
Decomposing Variation in Vocabulary and Listening Comprehension Task Performance in Spanish and English Into Person, Ecological, and Assessment Differences for Spanish–English Bilingual Children in the United States
Authors: Kim Young-Suk Grace , Gutierrez Nuria , Petscher Yaacov 
Published: September 2024

Purpose:
We investigated the contributions of person, ecological, and assessment characteristics to one's performance on vocabulary and listening comprehension tasks in English and Spanish. Person characteristics included English learner status, ecological characteristics included instructional program enrollment (bilingual vs. English immersion) and poverty status, and assessment characteristics included the language of assessment (Spanish vs. English) and linguistic grain size (vocabulary vs. listening comprehension).

Method:
Data were from 208 Spanish–English emergent bilingual children in Grade 1 in the United States and were analyzed using explanatory item response models.

Results:
Substantial variance in the tasks across both languages was attributable to the random effects of assessment/item (74%) and person (26%). English learner status was a significant student predictor of language performance, and the instructional program was a significant ecological predictor of language performance. Regarding assessment characteristics, both the language of assessment and linguistic grain size explained the variance in performance. There were no differences in performance on English assessments between children in the Spanish–English bilingual program and children in the English immersion program. However, on the Spanish tasks, children in the bilingual program outperformed their peers in the English immersion program.

Conclusion:
These findings highlight the importance of considering not only person/child characteristics but also ecological and assessment characteristics for Spanish–English bilingual children's performance on oral language tasks.

Supplemental Material:

https://doi.org/10.23641/asha.26972749
A cloud‐based hybrid intrusion detection framework using XGBoost and ADASYN‐Augmented random forest for IoMT
Authors: Salehpour Arash , Norouzi Monire , Balafar Mohammad Ali , SamadZamini Karim 
Published: September 2024

AbstractInternet of Medical Things have vastly increased the potential for remote patient monitoring, data‐driven care, and networked healthcare delivery. However, the connectedness lays sensitive patient data and fragile medical devices open to security threats that need robust intrusion detection solutions within cloud‐edge services. Current approaches need modification to be able to handle the practical challenges that result from problems with data quality. This paper presents a hybrid intrusion detection framework that enhances the security of IoMT networks. There are three modules in the design. First, an XGBoost‐based noise detection model is used to identify data anomalies. Second, adaptive resampling with ADASYN is done to fine‐tune the class distribution to address class imbalance. Third, ensemble learning performs intrusion detection through a Random Forest classifier. This stacked model coordinates techniques that filter noise and preprocess imbalanced data, identifying threats with high accuracy and reliability. These results are then experimentally validated on the UNSW‐NB15 benchmark to demonstrate effective detection under realistically noisy conditions. The novel contributions of the work are a new hybrid structural paradigm coupled with integrated noise filtering, and ensemble learning. The proposed advanced oversampling with ADASYN gives a performance that surpasses all others with a reported 92.23% accuracy.
Dynamic in‐motion wireless charging systems: Modelling and coordinated hierarchical operation in distribution systems
Authors: Majidi Majid , Parvania Masood 
Published: September 2024

AbstractThe high adoption of electric vehicles (EVs) and the rising need for charging power in recent years calls for advancing charging service infrastructures and assessing the readiness of the power system to cope with such infrastructures. This paper proposes a novel model for the integrated operation of dynamic wireless charging (DWC) and power distribution systems offering charging service to in‐motion EVs. The proposed model benefits from a hierarchical design, where DWC controllers capture the traffic flows of in‐motion EVs on different routes and translate them into estimations of charging power requests on power distribution system nodes. The charging power requests are then communicated with a central controller that monitors the distribution system operation by enforcing an optimal power flow model. This controller coordinates the operation of distributed energy resources to leverage charging power delivery to in‐motion EVs and mitigate stress on the distribution system operation. The proposed model is tested on a test distribution system connected to multiple DWC systems in Salt Lake City, and the findings demonstrate its efficiency in quantifying the traffic flow of in‐motion EVs and its translation to charging power requests while highlighting the role of distributed energy resources in alleviating stress on the distribution system operation.