bluuebunny/crossref_metadata_2025_split huggingface dataset:
Passive imaging through inhomogeneous scattering media
Authors: Bian Yaoming , Wang Fei , Liu Haishan , Yuan Haiming , Li Siteng , Huang Wenxin , Situ Guohai 
Published: July 2024

AbstractAccording to the atmospheric scattering model (ASM), the object signal’s attenuation diminishes exponentially as the imaging distance increases. This imposes limitations on ASM-based methods in situations where the scattering medium one wish to look through is inhomogeneous. Here, we extend ASM by taking into account the spatial variation of the medium density, and propose a two-step method for imaging through inhomogeneous scattering media. In the first step, the proposed method eliminates the direct current component of the scattered pattern by subscribing to the estimated global distribution (background). In the second step, it eliminates the randomized components of the scattered light by using threshold truncation, followed by the histogram equalization to further enhance the contrast. Outdoor experiments were carried out to demonstrate the proposed method.
A de novo ARIH2 gene mutation was detected in a patient with autism spectrum disorders and intellectual disability
Authors: Vinci Mirella , Treccarichi Simone , Galati Rando Rosanna , Musumeci Antonino , Todaro Valeria , Federico Concetta , Saccone Salvatore , Elia Maurizio , Calì Francesco 
Published: July 2024

AbstractE3 ubiquitin protein ligase encoded by ARIH2 gene catalyses the ubiquitination of target proteins and plays a crucial role in posttranslational modifications across various cellular processes. As prior documented, mutations in genes involved in the ubiquitination process are often associated with autism spectrum disorder (ASD) and/or intellectual disability (ID). In the current study, a de novo heterozygous mutation was identified in the splicing intronic region adjacent to the last exon of the ARIH2 gene using whole exome sequencing (WES). We hypothesize that this mutation, found in an ASD/ID patient, disrupts the protein Ariadne domain which is involved in the autoinhibition of ARIH2 enzyme. Predictive analyses elucidated the implications of the novel mutation in the splicing process and confirmed its autosomal dominant inheritance model. Nevertheless, we cannot exclude the possibility that other genetic factors, undetectable by WES, such as mutations in non-coding regions and polygenic risk in inter-allelic complementation, may contribute to the patient's phenotype. This work aims to suggest potential relationship between the detected mutation in ARIH2 gene and both ASD and ID, even though functional studies combined with new sequencing approaches will be necessary to validate this hypothesis.
Effect of iodine species on biofortification of iodine in cabbage plants cultivated in hydroponic cultures
Authors: Dobosy Péter , Nguyen Hoang Thi Phuong , Záray Gyula , Streli Christina , Ingerle Dieter , Ziegler Philipp , Radtke Martin , Buzanich Ana Guilherme , Endrédi Anett , Fodor Ferenc 
Published: July 2024

AbstractIodine is an essential trace element in the human diet because it is involved in the synthesis of thyroid hormones. Iodine deficiency affects over 2.2 billion people worldwide, making it a significant challenge to find plant-based sources of iodine that meet the recommended daily intake of this trace element. In this study, cabbage plants were cultivated in a hydroponic system containing iodine at concentrations ranging from 0.01 to 1.0 mg/L in the form of potassium iodide or potassium iodate. During the experiments, plant physiological parameters, biomass production, and concentration changes of iodine and selected microelements in different plant parts were investigated. In addition, the oxidation state of the accumulated iodine in root samples was determined. Results showed that iodine addition had no effect on photosynthetic efficiency and chlorophyll content. Iodide treatment did not considerably stimulate biomass production but iodate treatment increased it at concentrations less than 0.5 mg/L. Increasing iodine concentrations in the nutrient solutions increased iodine content in all plant parts; however, the iodide treatment was 2–7 times more efficient than the iodate treatment. It was concluded, that iodide addition was more favourable on the target element accumulation, however, it should be highlighted that application of this chemical form in nutrient solution decreased the concetrations of selected micoelement concentration comparing with the control plants. It was established that iodate was reduced to iodide during its uptake in cabbage roots, which means that independently from the oxidation number of iodine (+ 5, − 1) applied in the nutrient solutions, the reduced form of target element was transported to the aerial and edible tissues.
Event-related potentials during encoding coincide with subsequent forced-choice mnemonic discrimination
Authors: Rollins Leslie , Khuu Alexis , Bennett Kaylee 
Published: July 2024

AbstractComputational models and eye-tracking research suggest that encoding variability accounts for the reduced recognition of targets (A) when paired with non-corresponding lures (B′) relative to corresponding lures (A′). The current study examined whether neural activity during learning coincided with subsequent performance on the forced-choice Mnemonic Similarity Task (MST). Event-related potential responses were collected during encoding while young adults completed A–B′ and A–A′ trials of the forced-choice MST. Consistent with previous research, performance was lower on A–B′ trials than A–A′ trials. The subsequent memory effect was not significant for the A–A′ test format. However, for A–B′ trials, we observed a significant Accuracy × Stimulus interaction 1000–1200 ms poststimulus onset across frontal and fronto-central electrodes. As hypothesized, subsequently correct A–B′ trials were associated with a larger amplitude response at encoding to the target (A) than the original version of the non-corresponding lure (B). However, subsequently incorrect trials were associated with a larger amplitude response to the non-corresponding lure (B) than the target stimulus (A). These findings provide additional support for the effect of encoding variability on mnemonic discrimination.
Employing antagonistic C-X-C motif chemokine receptor 4 antagonistic peptide functionalized NaGdF4 nanodots for magnetic resonance imaging-guided biotherapy of breast cancer
Authors: Li Xiaodong , Bao Yunkai , Li Zhuheng , Teng Peihong , Ma Lina , Zhang Hua , Liu Guifeng , Wang Zhenxin 
Published: July 2024

AbstractC-X-C motif chemokine receptor 4 (CXCR4) is a promising therapeutic target of breast cancer because it is overexpressed on cell surface of all molecular subtypes of breast cancer including triplenegative breast cancer (TNBC). Herein, CXCR4 antagonistic peptide-NaGdF4 nanodot conjugates (termed as anti-CXCR4-NaGdF4 NDs) have been constructed for magnetic resonance imaging (MRI)-guided biotherapy of TNBC through conjugation of the C-X-C Motif Chemokine 12 (CXCL12)-derived cyclic peptide with tryptone coated NaGdF4 nanodots (5 ± 0.5 nm in diameter, termed as Try-NaGdF4 NDs). The as-prepared anti-CXCR4-NaGdF4 NDs exhibits high longitudinal relaxivity (r1) value (21.87 mM−1S−1), reasonable biocompatibility and good tumor accumulation ability. The features of anti-CXCR4-NaGdF4 NDs improve the tumor-MRI sensitivity and facilitate tumor biotherapy after injection in mouse-bearing MDA-MB-231 tumor model in vivo. MRI-guided biotherapy using anti-CXCR4-NaGdF4 NDs enables to suppress 46% tumor growth. In addition, about 47% injection dose of anti-CXCR4-NaGdF4 NDs is found in the mouse urine at 24 h post-injection. These findings demonstrate that anti-CXCR4-NaGdF4 NDs enable to be used as renal clearable nanomedicine for biotherapy and MRI of breast cancer.
The incidence of diabetes mellitus and its determining factors in a Kurdish population: insights from a cohort study in western Iran
Authors: Najafi Farid , Moradinazar Mehdi , Khosravi Shadmani Fatemeh , Pasdar Yahya , Darbandi Mitra , Salimi Yahya , Ghasemi Seyed Ramin 
Published: July 2024

AbstractDiabetes mellitus (DM) is among the most widespread non-communicable diseases and poses a substantial global health challenge. The aim of this study was to examine the incidence of DM and its nutritional, anthropometric, laboratory, demographic, and behavioral determinants, as well as comorbidities, within a Kurdish population residing in western Iran. This research was conducted in the Ravansar Non-Communicable Disease (RaNCD) cohort study, followed 9170 participants aged 35–65 years, for an average ± SD of 7.11 ± 1.26 years, from 2015 until 2023. A hierarchical Cox regression model was used to estimates the adjusted hazard ratios (HRs). The incidence of DM was 4.45 (95% CI 3.96, 4.99) per 1000 person-years. We found several significant predictors for DM incidence, including prediabetes, comorbidity, urban residence, total antioxidant capacity (TAC), and the interaction between gender and body mass index (BMI). Prediabetes emerged as the strongest predictor of DM incidence, with a hazard ratio of 10.13 (CI 7.84, 13.09). Additionally, having two diseases (HR = 2.18; 95% CI 1.44, 3.29) or three and more diseases (HR = 3.17; 95% CI 2.06, 4.90) increased the risk of developing DM. Also, the hazard ratios for the effects of gender on DM incidence in the normal, overweight, and obese BMI groups were 0.24, 0.81, and 1.01, respectively. The presence of prediabetes and obesity serve as the crucial indicators for the onset of DM, emphasizing the pressing need for interventions to prevent DM in these circumstances. Furthermore, there are notable disparities between urban and rural populations in this study, warranting further investigations to ascertain the underlying causes of such variations.
Induction of LTP mechanisms in dually innervated dendritic spines
Authors: Tullis Jonathan E. , Bayer K. Ulrich 
Published: July 2024

AbstractDendritic spines are the postsynaptic compartments of excitatory synapses, however, a substantial subset of spines additionally receives inhibitory input. In such dually innervated spines (DiSs), excitatory long-term potentiation (LTP) mechanisms are suppressed, but can be enabled by blocking tonic inhibitory GABAB receptor signaling. Here we show that LTP mechanisms at DiSs are also enabled by two other excitatory LTP stimuli. In hippocampal neurons, these chemical LTP (cLTP) stimuli induced robust movement of the Ca2+/calmodulin-dependent protein kinase II (CaMKII) to DiSs. Such synaptic CaMKII accumulation is an essential LTP mechanism at singly innervated spines (SiSs). Indeed, CaMKII accumulation at DiSs was also accompanied by other readouts for successful LTP induction: spine growth and surface insertion of GluA1. Thus, DiSs are capable of the same LTP mechanisms as SiSs, although induction of these mechanism additionally requires either reduced inhibitory signaling or increased excitatory stimulation. This additional regulation may provide further computational control.
Predicting blood–brain barrier permeability of molecules with a large language model and machine learning
Authors: Huang Eddie T. C. , Yang Jai-Sing , Liao Ken Y. K. , Tseng Warren C. W. , Lee C. K. , Gill Michelle , Compas Colin , See Simon , Tsai Fuu-Jen 
Published: July 2024

AbstractPredicting the blood–brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improve the accuracy and shorten the time for new drug development. The primary goal of this research is to develop artificial intelligence (AI) computing models and novel deep learning architectures capable of predicting whether molecules can permeate the human blood–brain barrier (BBB). The in silico (computational) and in vitro (experimental) results were validated by the Natural Products Research Laboratories (NPRL) at China Medical University Hospital (CMUH). The transformer-based MegaMolBART was used as the simplified molecular input line entry system (SMILES) encoder with an XGBoost classifier as an in silico method to check if a molecule could cross through the BBB. We used Morgan or Circular fingerprints to apply the Morgan algorithm to a set of atomic invariants as a baseline encoder also with an XGBoost classifier to compare the results. BBB permeability was assessed in vitro using three-dimensional (3D) human BBB spheroids (human brain microvascular endothelial cells, brain vascular pericytes, and astrocytes). Using multiple BBB databases, the results of the final in silico transformer and XGBoost model achieved an area under the receiver operating characteristic curve of 0.88 on the held-out test dataset. Temozolomide (TMZ) and 21 randomly selected BBB permeable compounds (Pred scores = 1, indicating BBB-permeable) from the NPRL penetrated human BBB spheroid cells. No evidence suggests that ferulic acid or five BBB-impermeable compounds (Pred scores < 1.29423E−05, which designate compounds that pass through the human BBB) can pass through the spheroid cells of the BBB. Our validation of in vitro experiments indicated that the in silico prediction of small-molecule permeation in the BBB model is accurate. Transformer-based models like MegaMolBART, leveraging the SMILES representations of molecules, show great promise for applications in new drug discovery. These models have the potential to accelerate the development of novel targeted treatments for disorders of the central nervous system.
Explosive eruption style modulates volcanic electrification signals
Authors: Vossen Caron E. J. , Cimarelli Corrado , D’Auria Luca , Cigala Valeria , Kueppers Ulrich , Barrancos José , Bennett Alec J. 
Published: July 2024

AbstractVolcanic lightning detection has proven useful to volcano monitoring by providing information on eruption onset, source parameters, and ash cloud directions. However, little is known about the influence of changing eruptive styles on the generation of charge and electrical discharges inside the eruption column. The 2021 Tajogaite eruption (La Palma, Canary Islands) provided the rare opportunity to monitor variations in electrical activity continuously over several weeks using an electrostatic lightning detector. Here we show that throughout the eruption, silicate particle charging is the main electrification mechanism. Moreover, we find that the type of electrical activity is closely linked to the explosive eruption style. Fluctuations in the electrical discharge rates are likely controlled by variations in the mass eruption rate and/or changes in the eruption style. These findings hold promise for obtaining near real-time information on the dynamic evolution of explosive volcanic activity through electrostatic monitoring in the future.
Influence of Sensory Monitoring on Speech Breathing Planning Processes: An Exploratory Study in Aging Speakers Reporting Dyspnea
Authors: Desjardins Maude , Jomphe Valérie , Lagadec-Gaulin Laurence , Cohen Matthew , Verdolini Abbott Katherine 
Published: July 2024

Purpose:
Previous studies have suggested that inspirations during speech pauses are influenced by the length of adjacent utterances, owing to respiratory motor planning and physiological recovery processes. The goal of this study was to examine how attention to respiratory sensations may influence these processes in aging speakers with dyspnea, by measuring the effect of sensory monitoring on the relationship between utterance length and the occurrence of inspirations, as well as on functional voice and respiratory measures.

Method:
Seventeen adults aged 50 years and older with complaints of voicing-related dyspnea completed a repeated-measures protocol consisting of a 2-week baseline phase and a 4-week sensory monitoring phase. Audiovisual recordings of semistructured speech and self-report questionnaires were collected at study onset, after the baseline phase, and after the sensory monitoring phase. Repeated-measures logistic regressions were conducted to examine changes in the relationship between utterance length and the occurrence of inspirations in adjacent pauses, and repeated-measures analyses of variance were used to investigate any changes in functional voice and respiratory measures.

Results:
Planning and recovery processes appeared to remain constant across the baseline phase. From postbaseline to postsensory monitoring timepoints, a strengthening of the relationship between the presence of an inspiration during a speech pause and the length of the subsequent—but not preceding—utterance was noted. Significant improvements were noted in voice-related handicap from study onset to postsensory monitoring, but no changes were reported in respiratory comfort during speech.

Conclusions:
Results suggest that respiratory planning processes, that is, the ability to plan breath intakes based on the length of upcoming utterances, may be modifiable behaviorally through targeted sensory monitoring. Further studies are warranted to validate the proposed role of respiratory sensation awareness in achieving skilled temporal coordination between voicing and breathing.
Improved model predictive control based on Luenberger state observer for LC‐coupling hybrid active power filter
Authors: Lv Yuan , Zhang Shuhao , Zhang Kai , Yang Chunyuan , Zou Jie , Lei Wang 
Published: July 2024

AbstractAn improved model predictive control (MPC) with Luenberger state observer is proposed in this article for LC‐coupling hybrid active power filter (LC‐HAPF). Traditionally, the implementation of MPC for LC‐HAPF requires additional sensors to measure coupling capacitor voltage, thereby increases the system cost and reduces reliability. The existence of one‐step sampling delay in practice will also affect the final compensation performance. To relax these problems, both continuous and discrete models are deduced first. Then, the Luenberger observer is utilized based on the discrete model to mitigate the steady‐state error without additional sensors. In addition, the sampling delay compensation is provided by improving the prediction horizon. Finally, the effectiveness of the improved MPC for LC‐HAPF is verified by experiment results, indicating that the proposed method has fast dynamic response and low steady‐state error.
N‐polar deep‐recess GaN MISHEMT with enhanced ft·LG by gate dielectric thinning
Authors: Collins Henry , Akso Emre , Clymore Christopher J. , Khan Kamruzzaman , Hamwey Robert , Hatui Nirupam , Guidry Matthew , Keller Stacia , Mishra Umesh K. 
Published: July 2024

AbstractThe authors report a novel structure to improve the high‐frequency performance of nitrogen‐polar GaN deep‐recess high electron mobility transistors (HEMTs) wherein a timed plasma etch was used to tailor the profile of the gate dielectric. A favourable trade‐off between gate fringing capacitance and transconductance was established, resulting in an improved current gain cutoff frequency times gate length (ft·LG) figure of merit compared to standard Schottky‐gate and metal‐insulator‐semiconductor (MIS) HEMTs. The etched gate dielectric MISHEMT demonstrated a maximum ft·LG of 15.0 GHz·µm for an LG of 100 nm.
Converter non‐blocking DC fault ride‐through and system fast restoration arrangements in R‐L SFCL‐equipped MMC‐M2TDC system
Authors: Yirun Ji , Guo Peiqian , Qin Liu 
Published: July 2024

AbstractEquipping a DC‐type superconducting fault current limiter (SFCL) in a modular multilevel converter‐based multi‐terminal DC (MMC‐M2TDC) system has the potential to reorganize the protection control arrangements during the DC‐side short‐circuit fault. This paper introduces the converter non‐blocking operation and system fast restoration control of the SFCL MMC‐M2TDC with the DC‐side bipolar fault condition, as well as their feasibility verifications. Considering the characteristics of overdamping oscillation of DC voltage and the additional impedance effect of the new resistor‐inductor SFCL (R‐L SFCL), the unfaulty converter non‐blocking protection enables faulty segment isolation and DC fault ride through without unwanted active power interruption. The restoration control for smooth reconnection and fast recovery of the off‐grid converter station ensures the DC voltage rebuilding process and reduces the required period. To validate the above arrangements, the simulation is conducted upon the PSCAD/EMTDC corresponding to the three‐terminal R‐L SFCL MMC‐M2TDC system. Finally, the research routes for novel superconducting coil design, SFCL scheme design, and multi‐device cooperative strategy are discussed, all of which contribute to promoting the high‐quality development of SFCL in MMC‐M2TDC scenarios.
An asymmetrical quadruple active bridge series resonant DC–DC converter for modular solid‐state transformers
Authors: Khani Saeid , Hosseini Seyed Hossein , Sabahi Mehran 
Published: July 2024

AbstractThe DC–DC conversion stage of a three‐stage solid‐state transformer is the most challenging due to the combination of high power, medium voltage, and medium frequency. This combination also causes most of the losses in the DC–DC stage. To address this issue, a new asymmetrical quadruple active bridge series resonant DC–DC converter (AQAB‐SRC) has been proposed as a building block for solid‐state transformers. The converter achieves soft switching of all switches throughout the operating range by extending and using the half‐cycle continuous conduction mode control strategy. It also has fewer high‐frequency transformers compared to other converters, as more bridges are connected to the same multi‐winding transformer. The optimal design of AQAB‐SRC has been analyzed theoretically, and simulation and lab‐scale experimental results have been obtained to validate the feasibility and validity of the proposed topology.
Optimized allocation of microgrids’ distributed generations and electric vehicle charging stations considering system uncertainties by clustering algorithms
Authors: Yaghoubi‐Nia Mohammad‐Reza , Hashemi‐Dezaki Hamed , Niasar Abolfazl Halvaei 
Published: July 2024

AbstractThe reliability‐oriented optimized sizing and placement of electric vehicle (EV) charging stations (EVCSs) has received less attention. In addition, the literature review shows that a research gap exists regarding a clustering‐based method to optimize the allocation of DGs and EVCSs, considering the system uncertainties. This article tries to fill such a knowledge gap by proposing a new clustering‐based method to optimize the allocation of DGs and EVs simultaneously, considering the uncertainties of EV behaviours and stochastic behaviours of renewable DGs. Developing a new stochastic model for EVs using the clustering algorithm is one of the essential contributions. The uncertain parameters, e.g. EV charging loads based on EV owners’ behaviours (arrival time, departure time, and driving distance) and renewable DGs, would be clustered. The proposed method could solve the execution time challenges of Monte Carlo simulation‐based approaches to concern the stochastic behaviours of smart grids. The simultaneously reliability‐oriented optimal allocation of EVCSs, DGs, and protection equipment, using the proposed clustering‐based algorithm is another main contribution. The IEEE 33‐bus test system is studied to examine the introduced method. Simulation results imply that a 1.45% accuracy improvement could be obtained compared to available analytical ones, while its execution time is appropriate.