Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Surface Trap States on Electron and Energy Transfer in CdSe Quantum Dots Studied by Femtosecond Transient Absorption Spectroscopy

The presence of surface trap states (STSs) is one of the key factors to affect the electronic and optical properties of quantum dots (QDs), however, the exact mechanism of how STSs influence QDs remains unclear. Herein, we demonstrated the impact of STSs on electron transfer in CdSe QDs and triplet-triplet energy transfer (TTET) from CdSe to surface acceptor using femtosecond transient absorption spectroscopy. Three types of colloidal CdSe QDs, each containing various degrees of STSs as evidenced by photoluminescence and X-ray photoelectron spectroscopy, were employed. Time-resolved emission and transient absorption spectra revealed that STSs can suppress band-edge emission effectively, resulting in a remarkable decrease in the lifetime of photoelectrons in QDs from 17.1 ns to 4.9 ns. Moreover, the investigation of TTET process revealed that STSs can suppress the generation of triplet exciton and effectively inhibit band-edge emission, leading to a significant decrease in TTET from CdSe QDs to the surface acceptor. This work presented evidence for STSs influence in shaping the optoelectronic properties of QDs, making it a valuable point of reference for understanding and manipulating STSs in diverse QDs-based optoelectronic applications involving electron and energy transfer.
Mathematical modeling of human memory

The mathematical study of human memory is still an open challenge. Cognitive psychology and neuroscience have given a big contribution to understand how the human memory is structured and works. Cognitive psychologists developed experimental paradigms, conceived quantitative measures of performance in memory tasks for both healthy people and patients with memory disorders, but in terms of mathematical modeling human memory there is still a lot to do. There are many ways to mathematically model human memory, for example, by using mathematical analysis, linear algebra, statistics, and artificial neural networks. The aim of this study is to provide the reader with a description of some prominent models, involving mathematical analysis and linear algebra, designed to describe how memory works by predicting the results of psychological experiments. We have ordered the models from a chronological point of view and, for each model, we have emphasized what are, in our opinion, the strong and weak points. We are aware that this study covers just a part of human memory modeling as well as that we have made a personal selection, which is arguable. Nevertheless, our hope is to help scientists to modeling human memory and its diseases.
Antihypertensive prescribing patterns in non-dialysis dependent chronic kidney disease: Findings from the Salford Kidney Study

BACKGROUND Hypertension is commonly observed in patients living with chronic kidney disease (CKD). Finding an optimal treatment regime remains challenging due to the complex bidirectional cause-and-effect relationship between hypertension and CKD. There remains variability in antihypertensive treatment practices. AIM To analyze data from the Salford Kidney Study database in relation to antihypertensive prescribing patterns amongst CKD patients. METHODS The Salford Kidney Study is an ongoing prospective study that has been recruiting CKD patients since 2002. All patients are followed up annually, and their medical records including the list of medications are updated until they reach study endpoints [starting on renal replacement therapy or reaching estimated glomerular filtration rate (eGFR) expressed as mL/min/1.73 m2 ≤ 10 mL/min/1.73 m2, or the last follow-up date, or data lock on December 31, 2021, or death]. Data on antihypertensive prescription practices in correspondence to baseline eGFR, urine albumin-creatinine ratio, primary CKD aetiology, and cardiovascular disease were evaluated. Associations between patients who were prescribed three or more antihypertensive agents and their clinical outcomes were studied by Cox regression analysis. Kaplan-Meier analysis demonstrated differences in survival probabilities. RESULTS Three thousand two hundred and thirty non-dialysis-dependent CKD patients with data collected between October 2002 and December 2019 were included. The median age was 65 years. A greater proportion of patients were taking three or more antihypertensive agents with advancing CKD stages (53% of eGFR ≤ 15 mL/min/1.73 m2 vs 26% of eGFR ≥ 60 mL/min/1.73 m2, P < 0.001). An increased number of patients receiving more classes of antihypertensive agents was observed as the urine albumin-creatinine ratio category increased (category A3: 62% vs category A1: 40%, P < 0.001), with the upward trends particularly noticeable in the number of individuals prescribed renin angiotensin system blockers. The prescription of three or more antihypertensive agents was associated with all-cause mortality, independent of blood pressure control (hazard ratio: 1.15; 95% confidence interval: 1.04-1.27, P = 0.006). Kaplan-Meier analysis illustrated significant differences in survival outcomes between patients with three or more and those with less than three antihypertensive agents prescribed (log-rank, P < 0.001). CONCLUSION Antihypertensive prescribing patterns in the Salford Kidney Study based on CKD stage were consistent with expectations from the current United Kingdom National Institute of Health and Care Excellence guideline algorithm. Outcomes were poorer in patients with poor blood pressure control despite being on multiple antihypertensive agents. Continued research is required to bridge remaining variations in hypertension treatment practices worldwide.
Exploring the Multifaceted Challenges of Women in Engineering: A Comprehensive Literature Review

The present research delves into the complex dynamics of gender equality, highlighting women's experiences within the engineering sector. Drawing from a literature spanning from 2005 to 2023, we gathered insights from 108 pertinent articles on the topic. Our results show that a substantial portion of research underscore the persistent biases and barriers women encounter in engineering. Through our analysis, we unveiled four dominant themes: “The Impact of Sex Differences on Productivity,” “Gender Digital Divide,” “Discriminatory Behaviour,” and “Women and Performance. ” Applying the glass ceiling theory as analytical framework, we discern a prevailing neglect toward women's challenges in the engineering field. Our findings accentuate the necessity for innovative policy interventions. To this end, we introduce a comprehensive policy model tailored to champion robust gender equity initiatives within the engineering field.
A Reconfigurable DLL-Based Digital-to-Time Converter Using Charge Pump Current Interpolation and Digital Predistortion Linearization

This brief presents a digital-to-time converter (DTC) based on a reconfigurable delay-locked loop that employs dual feedback taps and interpolation at the output of two charge pumps biased with programmable complementary currents from a current digital-to-analog converter (I-DAC) to achieve fine delay tuning. Through selection of the feedback and output delay line taps, the 65-nm CMOS prototype can be configured to achieve different specs, such as a 24.5 ps delay span with a 0.46 ps maximum delay step and 1.33 ps maximum RMS jitter or a span of 244 ps with a 3.30 ps maximum step and 2.63 ps maximum RMS jitter when a 7-bit I-DAC and a 2 GHz input are used. A simple digital predistortion method to compensate for the inherent nonlinearity of the architecture is presented and experimentally shown to improve the worst-case integral nonlinearity from −14.3 LSB (−27.6 ps) to +1.79 LSB (+3.43 ps) for the 244 ps delay span case, and by 67%–88% at all taps for the same loop configuration. Excluding the I-DAC, which would require an estimated 0.2 mW, the DTC consumes 0.665 mW from a 1.25-V supply at 2 GHz and occupies an area of 46 <inline-formula> <tex-math notation="LaTeX">$ {\mu }\text{m}\,\,{\times }$ </tex-math></inline-formula> 28 <inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula>.
Platelet microRNAs as Potential Novel Biomarkers for Antiplatelet Therapy with P2Y12 Inhibitors and Their Association with Platelet Function

Introduction: Patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) require dual antiplatelet therapy (DAPT). However, the response to treatment can vary considerably. Certain platelet microRNAs (miRs) are suspected to predict DAPT response and influence platelet function. This study aimed to analyze selected miRs’ expressions and compare them among patients treated with different P2Y12 inhibitors while assessing their association with platelet activity and turnover parameters. Materials and methods: We recruited 79 ACS patients post-PCI treated with clopidogrel, ticagrelor, or prasugrel, along with 18 healthy volunteers. Expression levels of miR-126-3p, miR223-3p, miR-21-5p, miR-197-3p, and miR-24-3p, as well as immature platelet fraction (IPF) and ADP-induced platelet reactivity, were measured and compared between groups. Results: Analyses revealed significantly lower expressions of miR-126-3p, miR-223-3p, miR-21-5p, and miR-197-3p in patients treated with ticagrelor, compared to clopidogrel (fold changes from −1.43 to −1.27, p-values from 0.028 to 0.048). Positive correlations were observed between platelet function and the expressions of miR-223-3p (r = 0.400, p = 0.019) and miR-21-5p (r = 0.423, p = 0.013) in patients treated with potent drugs. Additionally, miR-24-3p (r = 0.411, p = 0.012) and miR-197-3p (r = 0.333, p = 0.044) showed correlations with IPF. Conclusions: The identified platelet miRs hold potential as biomarkers for antiplatelet therapy. (ClinicalTrials.gov number, NCT06177587).
Comparison of outcomes in patients with severe aortic stenosis treated with small and large Medtronic Evolut R and Evolut PRO self-expandable prosthetic valves

Introduction Indications for transcatheter aortic valve implantation (TAVI) continue to expand. Very often TAVI must be done in large annuli. Implantation of the bigger prostheses is often associated with more procedural problems, which may affect the outcomes. Aim To compare the outcomes of TAVI procedures using the self-expandable Medtronic Evolut R 34 with the smaller Evolut R or Evolut Pro 23, 26 or 29. Material and methods We analysed 87 patients who received self-expandable Medtronic Evolut R and Pro valves. Group I consisted of 59 (67.81%) patients with Evolut 23, 26 or 29, and group II consisted of 28 (32.18%) patients who received an Evolut 34 valve. Results EuroSCORE II was 5.59 in group I vs 7.87 in group II (p = 0.02). The oversizing rate was higher in group II: 24.1% vs. 18.5% (p < 0.001). The procedure and fluoroscopy times were longer in group II: 209 vs. 187 min (p = 0.03), 44 vs. 27 min (p = 0.01). Moderate paravalvular leak was found more frequently in group II: 5 v 1 (p = 0.04). There was less device success in group II: 22 (78.57%) vs. 57 (96.6%) (p = 0.05). Early safety criteria were similar in both groups: 52 (88.1%) and 24 (92.3%) (p = 0.56). 30-day mortality was similar: 4 (6.7%) vs. 0 in group I and II respectively (p = 0.16). Conclusions TAVI procedures in patients requiring an Evolut R 34 prosthesis are more challenging than in those who need smaller valves. Paravalvular leaks are more frequently observed after TAVI with Evolut R 34, which results in lower device success.
Body Mass Index Trends before and during the COVID-19 Pandemic in Primary School Students in Split-Dalmatia County, Croatia: A Retrospective Study

Within the last decade, childhood obesity has become a serious problem, especially during the COVID-19 pandemic. This research paper aimed to examine whether body mass index (BMI) was higher during the pandemic (2020–2022) than in the pre-pandemic period (2012/2013–2019) using trends related to sex, urban–rural area, and physical activity (PA). This study included data from physical examinations of an entire population of primary school children from Split-Dalmatia County (Croatia) over a period of 10 years. There were 103,804 students from the first, fifth, and eighth grades who participated in the analysis. During the pandemic, the BMI of all the students increased, except for eighth-grade girls. Generations of eighth graders have had significantly different BMIs throughout the past decade. We found that first graders were overweight and obese in urban areas, while in rural areas, this problem was experienced by upper grades. Girls were more overweight and obese in the first and eighth grades, but boys experienced this more in the fifth grade. Reduced PA influenced an increase in BMI in both sexes, especially in girls. During the pandemic, this situation became worse. This study could be useful to experts for the creation of new policies for Split-Dalmatia County and surrounding regions that are similar economically and culturally.
The mediation effect of vitamin A and vitamin D supplement in the association between serum vitamin K levels and musculoskeletal disorders in preschool children

Introduction Vitamin K deficiency may elevate the incidence of musculoskeletal disorders (MSD), whereas it lacks validation for pediatric populations and has uncertain dose recommendations. In this context, we hypothesized that serum vitamin K levels are associated with MSD in preschool children, and the widely used vitamin A and vitamin D supplements may mediate these associations based on potential mechanisms, which expects to provide guidance for future practice. Methods A cross-sectional study was conducted in Sichuan province in southwestern China, from January 2021 to May 2022. Serum levels of vitamin K1/K2 and 25(OH)D were determined using the high-performance liquid chromatography method, and the diagnosis of MSD was executed by clinicians. Overall and stratified logistic regression analysis based on categorized 25(OH)D levels were conducted to assess association between serum vitamin K levels and MSD prevalence after adjusting for confounders. Mediation analysis was further performed and vitamin A and D supplementation was regressed as the mediator. Results A total of 6,368 children aged 0–6 years old were enrolled. MSD was identified in 1179 (18.51%) of the children, while 5,189 (81.49%) of them did not present such disorder. After adjusting confounders, a significant difference was found in serum vitamin K1 level between children in MSD and Non-MSD group (OR = 0.802, 95%CI 0.745–0.864). No significant difference was found in serum vitamin K2 level between the two groups (OR = 0.975, 95%CI 0.753–1.261). The association between vitamin K1 level and MSD prevalence was partly (36.8%) mediated by vitamin A and D supplementation. Conclusions A low serum vitamin K1 level is connected with an increased risk of MSD among children, highlighting that vitamin A and D supplementation is a helpful intervention to prevent MSD in children with vitamin K deficiency.
Protective Efficacy Induced by the Common Eimeria Antigen Elongation Factor 2 against Challenge with Three Eimeria Species in Chickens

Avian coccidiosis arises from co-infection involving multiple Eimeria species, which could give rise to substantial economic losses in the global poultry industry. As a result, multivalent anticoccidial vaccines containing common Eimeria antigens offer considerable promise for controlling co-infection in clinical practice. In our previous study, Elongation factor 2 (EF2) was deemed as an immunogenic common antigen across various Eimeria species. This current investigation aimed to further assess the immunogenicity and protective efficacy of EF2 in recombinant subunit vaccine format against three Eimeria species. The EF2 gene cloned from Eimeria maxima (E. maxima) cDNA was designated as EF2 of E. maxima (EmEF2). The immunogenicity of the recombinant protein EmEF2 (rEmEF2) was assessed through Western blot analysis. The evaluation of the vaccine-induced immune response encompassed the determination of T lymphocyte subset proportions, cytokine mRNA transcription levels, and specific IgY concentrations in rEmEF2-vaccinated chickens using flow cytometry, quantitative real-time PCR (qPCR), and indirect enzyme-linked immunosorbent assay (ELISA). Subsequently, the protective efficacy of rEmEF2 was evaluated through vaccination and challenge experiments. The findings demonstrated that rEmEF2 was effectively recognized by the His-tag monoclonal antibody and E. maxima chicken antiserum. Vaccination with rEmEF2 increased the proportions of CD4+ and CD8+ T lymphocytes, elevated IL-4 and IFN-γ mRNA transcription levels, and enhanced IgY antibody levels compared to the control groups. Moreover, compared to the control groups, vaccination with rEmEF2 led to decreased weight loss, reduced oocyst outputs, and alleviated enteric lesions. Furthermore, in the rEmEF2-immunized groups, challenges with E. maxima and E. acervulina resulted in anticoccidial index (ACI) scores of 166.35 and 185.08, showing moderate-to-excellent protective efficacy. Nevertheless, challenges with E. tenella and mixed Eimeria resulted in ACI scores of 144.01 and 127.94, showing low protective efficacy. In conclusion, EmEF2, a common antigen across Eimeria species, demonstrated the capacity to induce a significant cellular and humoral immune response, as well as partial protection against E. maxima, E. acervulina, and E. tenella. These results highlight EmEF2 as a promising candidate antigen for the development of multivalent vaccines targeting mixed infections by Eimeria species.
Analysis and Design of LCL Resonant Tank With Reduced Reactive Power for Bidirectional On-Board Charger Applications Utilizing Time-Domain Model

To address the wide voltage conversion requirements in the field of battery charging, the LCL resonant tank adopting pulse frequency modulation is investigated utilizing the time-domain model (TDM) in this article. LCL exhibits similar soft switching characteristics and enhanced voltage gain regulation capability with a simpler resonant tank than the existing classic CLLC. The operating principles, mode distribution, and power transfer properties of LCL during bidirectional operations are presented and analyzed in detail utilizing TDM. By incorporating TDM, the low accuracy deficiency of the first harmonic approximation for wide voltage applications is completely eliminated, and the implementation of full-range zero-voltage switching (ZVS) with time-domain accuracy becomes feasible. An LCL resonant parameters optimization method that is capable of providing the required voltage gain and guaranteeing the achievement of ZVS with reduced reactive power under desired load conditions during bidirectional operations is proposed. Finally, the revealed experimental results from a 1-kW prototype validated the correctness of the TDM theoretical analysis and the effectiveness of the proposed optimization method. The optimized prototype achieves the designed 1.8× voltage gain within a narrow switching frequency range of 88.7–120 kHz and a peak efficiency of 97.306%.
Temperature Sensing Properties of Biocompatible Yb/Er-Doped GdF3 and YF3 Mesocrystals

Y0.8−xGdxF3:Yb/Er mesocrystals with a biocompatible surface and diverse morphological characteristics were successfully synthesized using chitosan-assisted solvothermal processing. Their structural properties, studied using X-ray powder diffraction, Fourier transform infrared spectroscopy, scanning and transmission electron microscopy and energy dispersive X-ray analysis, were further correlated with the up-conversion emission (λexc = 976 nm) recorded in function of temperature. Based on the change in the visible green emissions originating from the thermally coupled 2H11/2 and 4S3/2 levels of Er3+, the corresponding LIR was acquired in the physiologically relevant range of temperatures (25–50 °C). The detected absolute sensitivity of about 0.0042 °C−1, along with the low cytotoxicity toward both normal human lung fibroblasts (MRC-5) and cancerous lung epithelial (A549) cells, indicate a potential for use in temperature sensing in biomedicine. Additionally, their enhanced internalization in cells, without suppression of cell viability, enabled in vitro labeling of cancer and healthy cells upon 976 nm laser irradiation.
SCGNet: efficient sparsely connected group convolution network for wheat grains classification

Introduction Efficient and accurate varietal classification of wheat grains is crucial for maintaining varietal purity and reducing susceptibility to pests and diseases, thereby enhancing crop yield. Traditional manual and machine learning methods for wheat grain identification often suffer from inefficiencies and the use of large models. In this study, we propose a novel classification and recognition model called SCGNet, designed for rapid and efficient wheat grain classification. Methods Specifically, our proposed model incorporates several modules that enhance information exchange and feature multiplexing between group convolutions. This mechanism enables the network to gather feature information from each subgroup of the previous layer, facilitating effective utilization of upper-layer features. Additionally, we introduce sparsity in channel connections between groups to further reduce computational complexity without compromising accuracy. Furthermore, we design a novel classification output layer based on 3-D convolution, replacing the traditional maximum pooling layer and fully connected layer in conventional convolutional neural networks (CNNs). This modification results in more efficient classification output generation. Results We conduct extensive experiments using a curated wheat grain dataset, demonstrating the superior performance of our proposed method. Our approach achieves an impressive accuracy of 99.56%, precision of 99.59%, recall of 99.55%, and an F 1-score of 99.57%. Discussion Notably, our method also exhibits the lowest number of Floating-Point Operations (FLOPs) and the number of parameters, making it a highly efficient solution for wheat grains classification.
AngoraPy: A Python toolkit for modeling anthropomorphic goal-driven sensorimotor systems

Goal-driven deep learning increasingly supplements classical modeling approaches in computational neuroscience. The strength of deep neural networks as models of the brain lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for hand-engineered or hypothesis-driven connectivity patterns. Consequently, goal-driven models can generate hypotheses about the neurocomputations underlying cortical processing that are grounded in macro- and mesoscopic anatomical properties of the network's biological counterpart. Whereas, goal-driven modeling is already becoming prevalent in the neuroscience of perception, its application to the sensorimotor domain is currently hampered by the complexity of the methods required to train models comprising the closed sensation-action loop. This paper describes AngoraPy, a Python library that mitigates this obstacle by providing researchers with the tools necessary to train complex recurrent convolutional neural networks that model the human sensorimotor system. To make the technical details of this toolkit more approachable, an illustrative example that trains a recurrent toy model on in-hand object manipulation accompanies the theoretical remarks. An extensive benchmark on various classical, 3D robotic, and anthropomorphic control tasks demonstrates AngoraPy's general applicability to a wide range of tasks. Together with its ability to adaptively handle custom architectures, the flexibility of this toolkit demonstrates its power for goal-driven sensorimotor modeling.