Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Efficiency Measurement and Modeling of Silicon Sensors Optimized for Soft X-ray Detection

Hybrid pixel detectors have become indispensable at synchrotron and X-ray free-electron laser facilities thanks to their large dynamic range, high frame rate, low noise, and large area. However, at energies below 3 keV, the detector performance is often limited because of the poor quantum efficiency of the sensor and the difficulty in achieving single-photon resolution due to the low signal-to-noise ratio. In this paper, we address the quantum efficiency of silicon sensors by refining the design of the entrance window, mainly by passivating the silicon surface and optimizing the dopant profile of the n+ region. We present the measurement of the quantum efficiency in the soft X-ray energy range for silicon sensors with several process variations in the fabrication of planar sensors with thin entrance windows. The quantum efficiency for 250 eV photons is increased from almost 0.5% for a standard sensor to up to 62% as a consequence of these developments, comparable to the quantum efficiency of backside-illuminated scientific CMOS sensors. Finally, we discuss the influence of the various process parameters on quantum efficiency and present a strategy for further improvement.
FINANCIAL DEVELOPMENT AND POVERTY ALLEVIATION: A SYSTEMATIC REVIEW

This study is conducted to validate the effectiveness of financial development in reducing poverty. The study adopted a Systematic Quantitative Assessment Technique and reviewed 91 financial development and poverty alleviation articles published between 2010–2022 to provide insight into the efficacy of financial development in reducing poverty and producing a blueprint for the government for possible adoption. The study also intends to know whether financial development successfully reduced poverty, highlight the evidence showing the success of financial development in reducing poverty, how financial development strategies were implemented to reduce poverty in other countries, and why financial development has been ineffective in reducing poverty. The reviewed articles revealed that financial development benefits the poor by increasing their access to various funding sources, thus improving well-being and reducing poverty. Similarly, it was revealed that lack of institutional quality and low financial penetration are the major reasons why financial development may not successfully reduce poverty. Thus, this study presented a FACI Blueprint to help the government effectively reduce poverty in countries where financial development is weak and unable to reduce poverty.
Predicting Impact of Natural Calamities in Era of Big Data and Data Science

Every year thousands of lives and millions of dollars are lost during natural catastrophic events. Data scientists have recognized the value of employing data mining techniques for evaluating these events to assist in understanding trends, predicting future disasters, and assessing vulnerability of populations. The goal of such analysis is to prepare governments for emergency response and relief efforts as well as to formulate strategies for future disaster mitigation. In addition, increasing pressures from a growing world population further emphasize the need for governments to seek viable solutions for balancing human needs with environmental constraints. Identifying populations vulnerable to environmental calamities includes analysis of past events to identify patterns which may identify at-risk populations and improve predictions of future events. Past analytical techniques used common statistical methods; however, recent developments in the field of data science and Big Data technologies have enabled data scientists to apply predictive and descriptive techniques accurately and economically. In this work, both supervised and unsupervised learning techniques will be applied to natural disaster data extracted from the Emergency Events Database (EM-DAT) for North America, Central America, and the Caribbean. Unsupervised, descriptive analytics were performed using the density based clustering algorithm DBSCAN to identify notable patterns in the disaster data. A supervised, predictive model was built using an artificial neural network to predict the potential monetary impact of natural calamities based on region, country, and natural disaster type.
Providing Warm Compresses for Back Pain in 3rd Trimester Pregnant Women

This study aims to determine the effect of warm compresses on Low Back Pain in pregnant women in Trimester III at the Bunda Sehat Clinic, Cijantung, Jakarta. The method used in this research is quasi-experimental with pre and post-test design with the control group. The research results show that the average Low Back Pain in Trimester III pregnant women before being given warm compresses was 6.1 (moderate pain), and after being given warm compresses was 2.9 (mild pain). There is an effect of warm compresses on Low Back Pain in pregnant women in the third trimester at the Bunda Sehat Clinic, Cijantung, Jakarta, with a p-value of 0.000. ConclusionkWarm compresses affect reducing Low Back Pain for third-trimester pregnant women at the Bunda Sehat Clinic, Cijantung, Jakarta. Keywords: Pregnancy, Warm Compresses, Low Back Pain
Direct numerical simulation of particle Brownian motion in a fluid with inhomogeneous temperature field

In this work the fluctuating-lattice Boltzmann method was adopted to numerically investigate the Brownian motion of particles in a fluid with inhomogeneous temperature field. It has been found that the Brownian particles are preferential to randomly move into a cold fluid area. Once the particles go into the cold area, the boundary between the hot fluid and cold fluid acts like a temperature barrier, preventing the particles from going out. Most important of all, the Brownian particles can be captured or collected by the cold fluid area if the temperature of cold fluid is lower than a critical value. In addition, the dependence of this critical value on the fluid viscosity is studied.
Effect of regenerative effectiveness on the performance of simple gas turbine

The deregulation of the power and energy sector introduced a strong element of competition. Power plant operators try to develop techniques to maximize profits in the dynamic power industry. New methods of improving and optimizing simple gas turbine power plants are needed to enhance operational decision making and therefore to maximize power plant profitability by reducing operational and maintenance cost and increasing revenue. In this work, the thermodynamic model equations of both a simple gas turbine and regenerative gas turbine cycle were used to analyses the effect of increase in the regenerative effectiveness to the performance of the simple gas turbine. Microsoft Excel 2010 software was used to carried out the analysis. It was observed that for the simple gas turbine the thermal efficiency, heat rate, specific fuel consumption and heat addition have a constant value of 35.4%, 9630Btu/Kwh, 0.2768kg/Kwh, 44237.8Kw, all through, while for the regenerative gas turbine cycle as the value of the regenerative effectiveness increases from 0.8 to 1.0, the thermal efficiency increases from 41.1% to 65.0%, the heat rate decreases from 8753Btu/Kwh to 5536 Btu/Kwh , specific fuel consumption decreases from 0.248945122Kg/Kw.h to 0.157432413 Kg/Kw.h and heat addition reduces from 39782.5Kw to 25158.4Kw. It was seen clearly that the regenerative gas turbine cycle has higher thermal efficiency compare to the simple gas turbine, and as the regenerative effectiveness of the regenerative gas turbine cycle increases the performance of the regenerative gas turbine increases.
Analyzing the Impact of Objects in an Image on Location Estimation Accuracy in Visual Localization

Visual localization refers to the process of determining an observer’s pose by analyzing the spatial relationships between a query image and a pre-existing set of images. In this procedure, matched visual features between images are identified and utilized for pose estimation; consequently, the accuracy of the estimation heavily relies on the precision of feature matching. Incorrect feature matchings, such as those between different objects and/or different points within an object in an image, should thus be avoided. In this paper, our initial evaluation focused on gauging the reliability of each object class within image datasets concerning pose estimation accuracy. This assessment revealed the building class to be reliable, while humans exhibited unreliability across diverse locations. The subsequent study delved deeper into the degradation of pose estimation accuracy by artificially increasing the proportion of the unreliable object—humans. The findings revealed a noteworthy decline started when the average proportion of the humans in the images exceeded 20%. We discuss the results and implications for dataset construction for visual localization.
Enhancing Bone Cement Efficacy with Hydrogel Beads Synthesized by Droplet Microfluidics

Effective filling materials, typically bone cements, are essential for providing mechanical support during bone fracture treatment. A current challenge with bone cement lies in achieving continuous drug release and forming porous structures that facilitate cell migration and enhance osteoconductivity. We report a droplet microfluidics-based method for synthesizing uniform-sized gelatin hydrogel beads. A high hydrogel concentration and increased crosslinking levels were found to enhance drug loading as well as release performance. Consequently, the droplet microfluidic device was optimized in its design and fabrication to enable the stable generation of uniform-sized droplets from high-viscosity gelatin solutions. The size of the generated beads can be selectively controlled from 50 to 300 μm, featuring a high antibiotic loading capacity of up to 43% dry weight. They achieve continuous drug release lasting more than 300 h, ensuring sustained microbial inhibition with minimal cytotoxicity. Furthermore, the hydrogel beads are well suited for integration with calcium phosphate cement, maintaining structural integrity to form porous matrices and improve continuous drug release performance. The uniform size distribution of the beads, achieved through droplet microfluidic synthesis, ensures predictable drug release dynamics and a measurable impact on the mechanical properties of bone cements, positioning this technology as a promising enhancement to bone cement materials.
Identification and Validation of Hub Genes Related to Neutrophil Extracellular Traps-Mediated Cell Damage During Myocardial Infarction

Purpose Studies have shown that neutrophil-mediated formation of neutrophil extracellular traps (NETs) leads to increased inflammatory response and cellular tissue damage during myocardial infarction (MI). We aimed to identify and validate possible hub genes in the process of NETs-mediated cell damage. Methods We performed an immune cell infiltration analysis of the MI transcriptome dataset based on CIBERSORT and ssGSEA algorithms. Gene expression profiles of NETs formation (GSE178883) were used to analyze the physiological processes of peripheral blood neutrophils after phorbol myristate acetate (PMA) stimulation. Bioinformatics and machine learning algorithms were utilized to find candidate hub genes based on NETs-related genes and transcriptome datasets (GSE66360 and GSE179828). We generated the receiver operating curve (ROC) to evaluate the diagnostic value of hub genes. Next, the correlation between hub genes and immune cells was analyzed using CIBERSORT, ssGSEA and xCell algorithms. Finally, we used quantitative real-time PCR (qRT-PCR) and immunohistochemistry to verify gene expression. Results Immune cell infiltration analysis revealed that inflammatory cells such as neutrophils were highly expressed in the peripheral blood of patients with MI. Functional analysis of differentially expressed genes (DEGs) in GSE178883 indicated that the potential pathogenesis lies in immune terms. Using weighted gene co-expression network analysis (WGCNA) and machine learning algorithms, we finally identified the seven hub genes (FCAR, IL1B, MMP9, NFIL3, CXCL2, ICAM1, and ZFP36). The qRT-PCR results showed that IL-1B, MMP9, and NFIL3 mRNA expression was up-regulated in the MI group compared to the control. Immunohistochemical results showed high MMP9, IL-1B, and NFIL3 expression in the infarcted area compared to the non-infarcted area and sham-operated groups. Conclusion We identified seven hub genes associated with NETs-mediated cellular damage during MI. Our results may provide insights into the mechanisms of neutrophil-mediated cell injury during MI.
Laherradurin Inhibits Tumor Growth in an Azoxymethane/Dextran Sulfate Sodium Colorectal Cancer Model In Vivo

Simple Summary The complexity of the tumor cell, its ability to evade death, and its capacity to proliferate and conquer new tissues and organs make its treatment a challenge. Major challenges posed by therapeutic agents include their toxicity and consequences for patients after chemotherapy. Natural products provide a fundamental basis for the development of chemoagents. Our research aimed to test in vivo the antitumor activity of laherradurin in CRC and to measure its toxic effect. Our findings show that laherradurin inhibits growth and decreases the size of tumors in the colon compared with cisplatin. In addition, blood tests show no hepatic or renal damage or damage at the immunological level. Likewise, the disease activity index shows that those animals treated with laherradurin had diminished signs of disease. In our work, we provide new and conclusive evidence on the antitumor effect of laherradurin and measure its toxic activity under different criteria. Abstract Colorectal cancer (CRC) is the third most common neoplasia in the world. Its mortality rate is high due to the lack of specific and effective treatments, metastasis, and resistance to chemotherapy, among other factors. The natural products in cancer are a primary source of bioactive molecules. In this research, we evaluated the antitumor activity of an acetogenin (ACG), laherradurin (LH), isolated from the Mexican medicinal plant Annona macroprophyllata Donn.Sm. in a CRC murine model. The CRC was induced by azoxymethane–dextran sulfate sodium (AOM/DSS) in Balb/c mice and treated for 21 days with LH or cisplatin. This study shows for the first time the antitumor activity of LH in an AOM/DSS CRC model. The acetogenin diminished the number and size of tumors compared with cisplatin; the histologic studies revealed a recovery of the colon tissue, and the blood toxicity data pointed to less damage in animals treated with LH. The TUNEL assay indicated cell death by apoptosis, and the in vitro studies exhibited that LH inhibited cell migration in HCT116 cells. Our study provides strong evidence of a possible anticancer agent for CRC.
The Purification of Hydrogen

The purification or separation of hydrogen has traditionally been based on solid-state diffusion technology utilising noble metal membranes. The development of this technology, which has been centred around improved diffusion membrane materials based on the silver-palladium alloy system, is reviewed in this paper. It is shown that, despite the emergence of alternative techniques, diffusion technology based on silver-palladium membranes remains the most suitable technique for the production of high purity hydrogen, a product which is required increasingly in many high technology applications.
CONDITIONAL PREDICTIVE ABILITY OF EXCHANGE RATES IN LONG RUN REGRESSIONS* PREDICTIBILIDAD DEL TIPO DE CAMBIO: UNA EVALUACION CONDICIONAL CON REGRESIONES DE LARGO PLAZO

In this paper we evaluate exchange rate predictability using a framework developed by Giacomini and White (2006). This new framework tests for conditional predictive ability rather than unconditional predictive ability, which has been the standard approach. Using several shrinkage based forecasting methods, including new methods proposed here, we evaluate conditional predictability of five bilateral exchange rates at differing horizons. Our results indicate that for most currencies a random walk would not be the optimal forecasting method in a real time forecasting exercise, at least for some predictive horizons. We also show that our proposed shrinkage methods in general perform on par with Bayesian shrinkage and ridge regressions, and sometimes they even perform better.
The Potential of PIP3 in Enhancing Wound Healing

Given the role of phosphatidylinositol 3,4,5-trisphosphate (PIP3) in modulating cellular processes such as proliferation, survival, and migration, we hypothesized its potential as a novel therapeutic agent for wound closure enhancement. In this study, PIP3 was examined in its free form or as a complex with cationic starch (Q-starch) as a carrier. The intracellular bioactivity and localization of free PIP3 and the Q-starch/PIP3 complexes were examined. Our results present the capability of Q-starch to form complexes with PIP3, facilitate its cellular membrane internalization, and activate intracellular paths leading to enhanced wound healing. Both free PIP3 and Q-starch/PIP3 complexes enhanced monolayer gap closure in scratch assays and induced amplified collagen production within HaCAT and BJ fibroblast cells. Western blot presented enhanced AKT activation by free or complexed PIP3 in BJ fibroblasts in which endogenous PIP3 production was pharmacologically inhibited. Furthermore, both free PIP3 and Q-starch/PIP3 complexes expedited wound closure in mice, after single or daily dermal injections into the wound margins. Free PIP3 and the Q-starch/PIP3 complexes inherently activated the AKT signaling pathway, which is responsible for crucial wound healing processes such as migration; this was also observed in wound assays in mice. PIP3 was identified as a promising molecule for enhancing wound healing, and its ability to circumvent PI3K inhibition suggests possible implications for chronic wound healing.
Rice Bran Arabinoxylan Compound and Quality of Life (RBAC-QoL) of Cancer Patients: An Interim Analysis of the RBAC-QoL Study

Background The effect of rice bran arabinoxylan compound (RBAC), a plant-based immunomodulator, on the quality of life (QoL) in cancer patients and underlying physiological pathways remains unclear. Trial design The RBAC-QoL study, a double-blind, randomised, controlled pilot feasibility study, aimed to determine RBAC’s effects on QoL and the associated action mechanisms. Primary outcomes were the EORTC QLQ-C30 functional, symptom, and global QoL scores with inflammatory, nutritional, and cytokine parameters as secondary and exploratory outcomes. Methods Participants were adults diagnosed with solid organ tumours (≥ stage II) undergoing active treatment in several outpatient centres in New South Wales, Australia. Interventions were RBAC or matched placebo at 3g/day for 24 weeks allocated through stratified randomisation with participants, oncologists, and data collectors blinded. Data was collected from five study visits six weeks apart. The trial remained ongoing as of December 2023. An interim intention-to-treat analysis was performed using repeated measure ANOVA with pairwise comparisons where statistical significance was observed and adjusted with covariates. Results Global QoL scores from currently available data (n = 16; RBAC = 7, placebo = 9) were statistically different between groups (F1,8 = 8.6, p = 0.019, eta2[g] = 0.267). Pairwise comparisons found significant differences at Week 6 (p = 0.032, Cohen’s d = 1.454) and marginally at Week 12 (p = 0.069, d = 1.427). Age-adjusted analysis showed a continuous upward trend in QoL improvement over time with RBAC, while the placebo group did not deviate from baseline QoL. Significant elevations of serum white blood cell count (Week 18) and total protein (Weeks 12 and 18) were detected in the RBAC group compared to placebo. The total protein levels correlated highly with white blood cell count (Pearson’s r = 0.539, p < 0.001) and moderately with the global QoL scores (r = 0.338, p = 0.01). No intervention-related adverse events were reported in both groups. Conclusions RBAC improves QoL beyond placebo during active cancer treatment, possibly through the immuno-nutritional pathway - these findings, though preliminary, are valuable for future research. Funding and registration: Daiwa Pharmaceutical Co., Ltd, Japan; BioMedica Nutraceuticals Pty Ltd., Australia. ANZCTR Reg No: ACTRN12619000562178p.
Regulation of Follicular Development in Chickens: WIF1 Modulates Granulosa Cell Proliferation and Progesterone Synthesis via Wnt/β-Catenin Signaling Pathway

Proliferation, apoptosis, and steroid hormone secretion by granulosa cells (GCs) and theca cells (TCs) are essential for maintaining the fate of chicken follicles. Our previous study showed that the Wnt inhibitor factor 1 (WIF1) plays a role in follicle selection. However, the significance of WIF1 in GC- and TC-associated follicular development was not explicitly investigated. This study found that WIF1 expression was strongly downregulated during follicle selection (p < 0.05) and was significantly higher in GCs than in TCs (p < 0.05). WIF1 inhibits proliferation and promotes apoptosis in GCs. Additionally, it promotes progesterone secretion in prehierarchal GCs (pre-GCs, 1.16 ± 0.05 ng/mg vs. 1.58 ng/mg ± 0.12, p < 0.05) and hierarchal GCs (hie-GCs, 395.00 ng/mg ± 34.73 vs. 527.77 ng/mg ± 27.19, p < 0.05) with the participation of the follicle-stimulating hormone (FSH). WIF1 affected canonical Wnt pathways and phosphorylated β-catenin expression in GCs. Furthermore, 604 upregulated differentially expressed genes (DEGs) and 360 downregulated DEGs in WIF1-overexpressed GCs were found through RNA-seq analysis (criteria: |log2⁡(FoldChange)| > 1 and p_adj < 0.05). Cytokine–cytokine receptor interaction and the steroid hormone biosynthesis pathway were identified. In addition, the transcript of estrogen receptor 2 (ESR2) increased significantly (log2⁡(FoldChange) = 1.27, p_adj < 0.05). Furthermore, we found that WIF1 regulated progesterone synthesis by upregulating ESR2 expression in GCs. Additionally, WIF1 suppressed proliferation and promoted apoptosis in TCs. Taken together, these results reveal that WIF1 stimulates follicle development by promoting GC differentiation and progesterone synthesis, which provides an insight into the molecular mechanism of follicle selection and egg-laying performance in poultry.