Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of DNA Polymerase Genes in Amazonian Amerindian Populations

Due to their continuing geographic isolation, the Amerindian populations of the Brazilian Amazon present a different genetic profile when compared to other continental populations. Few studies have investigated genetic variants present in these populations, especially in the context of next-generation sequencing. Knowledge of the molecular profile of a population is one of the bases for inferences about human evolutionary history, in addition, it has the ability to assist in the validation of molecular biomarkers of susceptibility to complex and rare diseases, and in the improvement of specific precision medicine protocols applied to these populations and to populations with high Amerindian ancestry, such as Brazilians. DNA polymerases play essential roles in DNA replication, repair, recombination, or damage repair, and their influence on various clinical phenotypes has been demonstrated in the specialized literature. Thus, the aim of this study is to characterize the molecular profile of POLA1, POLE, POLG, POLQ, and REV3L genes in Amerindian populations from the Brazilian Amazon, comparing these findings with genomic data from five continental populations described in the gnomAD database, and with data from the Brazilian population described in ABraOM. We performed the whole exome sequencing (WES) of 63 Indigenous individuals. Our study described for the first time the allele frequency of 45 variants already described in the other continental populations, but never before described in the investigated Amerindian populations. Our results also describe eight unique variants of the investigated Amerindians populations, with predictions of moderate, modifier and high clinical impact. Our findings demonstrate the unique genetic profile of the Indigenous population of the Brazilian Amazon, reinforcing the need for further studies on these populations, and may contribute to the creation of public policies that optimize not only the quality of life of this population, but also of the Brazilian population.
ROSETTA: A Resource and Energy-Efficient Inference Processor for Recurrent Neural Networks Based on Programmable Data Formats and Fine Activation Pruning

Recurrent neural networks (RNNs) are extensively employed to perform inference based on the temporal features of the input data. However, their computational workload and power consumption involved in inference are prohibitively high in practice, which may be problematic to achieve a high-speed inference in devices with tight limitations in the available silicon resources and power supply. This paper presents an efficient inference processor for RNNs, named ROSETTA. ROSETTA supports multiple data formats programmable for each vector operand to achieve a wide range or high precision with a limited data size. ROSETTA consistently performs every vector operation based on homogeneous processing units with a high utilization rate. Moreover, ROSETTA skips operations and reduces memory accesses to achieve high energy efficiency by pruning the activation elements in a fine-grained manner. Implemented in a low-cost 28 nm field-programmable gate array, ROSETTA exhibits a resource and energy efficiency as high as 2.51 – 1.14 MOP/s/LUT and 434.01 – 113.29 GOP/s/W, respectively, while producing near-floating-point inference results. The resource and energy efficiency of ROSETTA are higher than those of the previous processor implemented in the same device by up to 206.1% and 304.0%, respectively. The functionality has been verified for several RNN models of various types under a fully-integrated inference system.
The Role of Local Inflammation and Hypoxia in the Formation of Hypertrophic Scars—A New Model in the Duroc Pig

Hypertrophic scars continue to be a major burden, especially after burns. Persistent inflammation during wound healing appears to be the precipitating aspect in pathologic scarring. The lack of a standardized model hinders research from fully elucidating pathophysiology and therapy, as most therapeutic approaches have sparse evidence. The goal of this project was to investigate the mechanisms of scar formation after prolonged wound inflammation and to introduce a method for generating standardized hypertrophic scars by inducing prolonged inflammation. Four wound types were created in Duroc pigs: full-thickness wounds, burn wounds, and both of them with induced hyperinflammation by resiquimod. Clinical assessment (Vancouver Scar Scale), tissue oxygenation by hyperspectral imaging, histologic assessment, and gene expression analysis were performed at various time points during the following five months. Native burn wounds as well as resiquimod-induced full-thickness and burn wounds resulted in more hypertrophic scars than full-thickness wounds. The scar scale showed significantly higher scores in burn- and resiquimod-induced wounds compared with full-thickness wounds as of day 77. These three wound types also showed relative hypoxia compared with uninduced full-thickness wounds in hyperspectral imaging and increased expression of HIF1a levels. The highest number of inflammatory cells was detected in resiquimod-induced full-thickness wounds with histologic features of hypertrophic scars in burn and resiquimod-induced wounds. Gene expression analysis revealed increased inflammation with only moderately altered fibrosis markers. We successfully created hypertrophic scars in the Duroc pig by using different wound etiologies. Inflammation caused by burns or resiquimod induction led to scars similar to human hypertrophic scars. This model may allow for the further investigation of the exact mechanisms of pathological scars, the role of hypoxia and inflammation, and the testing of therapeutic approaches.
HEAT TRANSFER FROM TUBES IN MIST FLOWS

The present work has been undertaken to pursue the high performance of mist-cooled heat exchangers, Hrrt, mist-cooling experiments are conducted for staggered tubes having a fine surface structure in a vertical crossflow, and mist-cooling heat transfer is discussed including the effects of mutual interferences among the tubes. Next, mist-cooling heat transfer is analyzed for an arbitrary configuration of tubes, and design optimization for mist-cooled heat exchangers is developed upon applying the performance-evaluation criteria method of Bergles.
Calculation of Cohesive Energies of 3-D Bismuth Selenide (Bi2Se3) and Bismuth Antimony BiSb Topological Insulators: DFT Study

The cohesive energies of 3-dimensional (3-D) topological insulators bismuth antimony (BiSb) and bismuth selenide (Bi2Se3) were calculated. The Fritz Haber Institute Ab-initio molecular simulations (FHI-aims) code was employed for this calculation. The output files of the FHI-aims code were used during the computation and the total energies at each number of iterations for single free atoms and bulk were then calculated. The results from this work revealed that bismuth atom becomes stable at 3rd iteration meanwhile both selenium and antimony atoms gain stability at the 5th iteration. The results also showed that bismuth antimony acquire stability at the 3rd iteration and bismuth selenide gain stability at 9th iteration. This implies that among the free atoms studied in this work bismuth atom is more stable and for the bulk bismuth antimony is more stable. The cohesive energies of BiSb and Bi2Se3 were calculated using the optimized parameters. The results obtained from the calculation of the cohesive energies in this work were 1.02eV and 1.76eV for BiSb and Bi2Se3 respectively. This results compared reasonably well with experimental results and have little percentage errors of 1.30% for bismuth antimony and 29.55% for bismuth selenide. The deviation observed in this work may be due to the DFT calculation of the solid rather than the atoms themselves.
An implementation of IDRstab with biorthogonality relations for solving linear systems

The IDRstab method, which combines the Induced Dimension Reduction (IDR) (s) method with higher-order stabilizing polynomials, is an effective method for solving large sparse nonsymmetric linear systems. However, IDRstab with a large parameter s is strongly affected by rounding errors, and requires high computational costs. We therefore propose an implementation of IDRstab, which imposes biorthogonality conditions on the iteration vectors, for numerical stability and efficiency. Numerical experiments demonstrate that our proposed variant is often more effective than the original IDRstab for larger s.
Mean Rainfall Patterns for the Three Phases of GATE

Abstract As a part of the GARP Atlantic Tropical Experiment (GATE), quantitative precipitation measurements were made during the summer of 1974 with four C-band digital radars complemented by shipboard raingages. Isohyetal maps covering a 125 000 km2 array centered at 8°30′N, 23°30′W are presented for each of three, approximately 20-day observational phases of GATE. Large mean rain rates exist for all three phases, with the largest ones corresponding to accumulations exceeding 500 mm for some of the maximum isohyets during Phase I. The mean rainfall rate averaged over the B-scale array for all three phases, 11.3 mm day−1, is apparently not significantly different from pre-GATE rainfall climatology. Another striking characteristic of the phase-mean precipitation patterns is the large spatial gradients; e.g., gradients as large as 200 mm in 16 km are observed. Latitude shifts in the zone of maximum confluence (intertropical convergence zone) and in the tracks of the synoptic disturbances are reflected by in.
FOLFOX‐bevacizumab chemotherapy in patients with metastatic neuroendocrine tumors

Neuroendocrine tumors (NETs) are highly vascularized neoplasms. While FOLFOX chemotherapy has shown efficacy in patients with advanced NETs, its combination with antiangiogenics has been scarcely described. Here, we report the efficacy and tolerance of FOLFOX‐bevacizumab in this setting. We retrospectively studied all consecutive patients with metastatic NET treated by FOLFOX‐bevacizumab in two expert centers from 2013 to 2020. We assessed time to treatment failure (TTF), objective response rate (ORR) and toxicity. We explored factors associated with TTF and ORR using multivariate analyses. We included 57 patients (35.1% female, median age 61.7 years), with pancreatic (66.7%), small‐intestine (14%) or lung (7%) NETs. Most patients (57.9%) had extra‐hepatic metastases and G3 NETs accounted for 40.3% of cases. Patients received a median of 17 cycles of treatment, including a median of seven cycles of bevacizumab and/or 5‐fluorouracile maintenance. Median TTF was 15.5 months (95% CI: 9.8–21.2) and was shorter in patients age > 60 years (HR 2.56, 95% CI: 1.16–5.64), p = . 020) and >1 previous systemic treatment line (HR 4.15, 95% CI: 1.96–8.78), p < . 001). The ORR was 42.9% and was higher in cases of performance status at 0 (OR 5.25, 95% CI: 1.13–24.35), p = . 034) and G3 NET (OR 5.39, 95% CI: 1.23–23.52), p = . 025). The FOLFOX‐bevacizumab combination has promising efficacy in patients with progressive metastatic NETs and notably for G3 NETs, for which optimal treatment as yet remains ill‐defined. Hence, it could be a relevant alternative to alkylating‐based chemotherapy in this setting and should be further explored prospectively.
A Dynamical Extension of the Desity Functional Theory

A dynamical version of the density functional theory (DFT) for classical (equilibrium) statistical mechanics is presented. A nonlinear Langevin equation with multiplicative noise is derived for a density field. The corresponding Fokker-Planck equation is shown to have the appropriate stationary distribution expressed in terms of the free energy functional.
Fast and robust face detection with skin color mixture models and asymmetric AdaBoost

We present a new approach to face detection with skin color mixture models and asymmetric AdaBoost. First, non-skin color pixels of the input image are rapidly removed based on skin color mixture models in RGB and YCbCr chrominance spaces, from which we extract candidate face regions. Then, face detection with fast asymmetric AdaBoost is carried out in candidate face regions where ratios of pixels of skin color to non-skin color are beyond certain thresholds. To further reduce the computational cost, the integral image technique is employed to calculate ratios of pixels of skin color to non-skin color in candidate face regions. Finally, false alarms are gradually merged and removed by relative geometric relation and the rate of skin color pixels on the intersection line of candidate face regions. Experimental results show that our proposed method reduces significantly false alarms and the processing time while achieves detection rates of more than 99%.
An Analytical Approach to Calculate Soft Error Rate Induced by Atmospheric Neutrons

In the atmosphere, it is generally understood that neutrons are the main contributor to the soft error rate (SER) in electronic devices. These particles are indeed able to trigger nuclear reactions in the sensitive regions of the devices, leading to secondary ions that may ionize the matter sufficiently to upset a memory cell or induce a transient signal, known as soft errors. For reliability purposes, it is crucial to be able to estimate the SER associated with a given technology, which is typically characterized by its sensitive volume and its threshold linear energy transfer (LET). As an alternative to the usual Monte Carlo methods, in this work we present an analytical model for SER prediction, where we separate the radiation–matter interaction from the geometry considerations (sensitive volume). By doing so, we show that the SER can be expressed as the sum of two contributions that can be calculated for any threshold LET and any sensitive volume size. We compare our proposed approach to existing Monte Carlo simulations in the literature, obtaining a very good agreement despite our approximations, thus validating our approach. As an additional result, we can show that, for future down-sized technologies that may be more sensitive to radiation effects, the contribution of neutrons in the 1–10 MeV energy range to the SER is expected to decrease.
Analysis of Carbon Formation on Machined Leather Specimen Using FTIR Technique in Laser Diode Assisted Cutting Process

The leather materials are used in a multitude of sectors, including footwear, apparel, handicrafts, and the automotive industry. Due to the radiant heat generated by a laser beam, the laser cutting of leather results in a carbonized cut edge. There is currently no technology available for measuring the carbonization along the contour edges of leather. The purpose of this experimental investigation was to determine the impact of power diode-based laser cutting on the carbonization of machined buffalo leather with the help of a digital microscope to improve the machining process. The ATR-FTIR spectrum was used to analyze the carbon-related functional group in the mid-IR spectrum of carbonized leather samples. It was found that the proposed method can measure the amount of carbon deposition in the cutting zone. The lower amplitude duty cycle with higher feed rate can reduce carbon formation owing to the lower thermal energy distribution. The amplitude (4.5 V), duty cycle (70%) and feed rate (90 mm/s) can produce optimal performance measures.
Approximate entropy---a new statistic to quantify arc and welding process stability in short-circuiting gas metal arc welding

Based on the phase state reconstruction of welding current in short-circuiting gas metal arc welding using carbon dioxide as shielding gas, the approximate entropy of welding current as well as its standard deviation has been calculated and analysed to investigate their relation with the stability of electric arc and welding process. The extensive experimental and calculated results show that the approximate entropy of welding current is significantly and positively correlated with arc and welding process stability, whereas its standard deviation is correlated with them negatively. A larger approximate entropy and a smaller standard deviation imply a more stable arc and welding process, and vice versa. As a result, the approximate entropy of welding current promises well in assessing and quantifying the stability of electric arc and welding process in short-circuiting gas metal arc welding.
On the Design of Compliant Mechanisms Using Topology Optimization

ABSTRACT This paper presents a method for optimal design of compliant mechanism topologies. The method is based on continuum-type topology optimization techniques and finds the optimal compliant mechanism topology within a given design domain and a given position and direction of input and output forces. By constraining the allowed displacement at the input port, it is possible to control the maximum stress level in the compliant mechanism. The ability of the design method to find a mechanism with complex output behavior is demonstrated by several examples. Some of the optimal mechanism topologies have been manufactured, both in macroscale (hand-size) made in Nylon, and in microscale (<.5mm)) made of micromachined glass.
A 7.5-mV Input and 88%-Efficiency Single-Inductor Boost Converter with Self-Startup and MPPT for Thermoelectric Energy Harvesting

This paper presents a single-inductor boost converter for thermoelectric energy harvesting. A two-stages startup circuit with a three-phase operation is adopted to obtain self-startup with a single inductor. To extract the maximum energy, a coarse- and fine-tuning MPPT is proposed to adaptively and effectively track the internal source resistance. By designing a zero-current detector, the synchronization loss is reduced, which significantly improves the peak efficiency. The boost converter is implemented in a 0.18-μm standard CMOS process. Simulation results show that the converter self-starts the operation from a TEG voltage of 128 mV and achieves 88% peak efficiency, providing a maximum output power of 3.78 mW. The improved MPPT enables the converter to sustain the operation at an input voltage as low as 7.5 mV after self-startup.
Study on the Skin Hydration and Trans Epidermal Water Loss of Aloe Viscose Seamless Knitted Fabric for Autumn and Winter

To explore the skin moisturizing performance of aloe viscose fiber seamless knitted fabric, this experiment takes the different yarn-blending ratios of aloe viscose fiber and viscose fiber, as well as three different tissue structures as factors, establishes a sample scheme according to full factor experimental tests on skin hydration and trans epidermal water loss (TEWL) after the sample fabric had been wrapped around the skin, and uses two-way and one-way ANOVA in SPSS and the Duncan multiple comparison method. The test data were analyzed to study the influence of different materials and the structure of the veil on the moisture retention of the fabric. The results show that the sample scheme with the largest change rate of skin hydration is when the raw material of the veil is aloe viscose/viscose 100/0 yarn, and the structure is 1 + 3 simulated rib. The sample scheme with the minimum change rate of TEWL is when aloe viscose/viscose 75/25 yarn is used as the raw material of the veil, and the structure is 1 + 1 simulated rib, which provides a theoretical basis for the research and development of moisturizing knitted fabric.
Pan-Cancer Landscape of NEIL3 in Tumor Microenvironment: A Promising Predictor for Chemotherapy and Immunotherapy

Simple Summary A reliable efficacy predictor for immunotherapy is warranted due to its unsatisfying responsive rate among cancer patients. Endonuclease VIII-like protein 3 (NEIL3) is a DNA glycosylase reported to be heightened in specific cancers. However, little is known regarding the immunological features of NEIL3 among cancers. Here, a pan-cancer landscape was presented to elucidate the characteristics of NEIL3 in the tumor microenvironment (TME). In this study, we demonstrated that NEIL3 may be a promising indicator for tumor prognosis, immunotherapy, and chemotherapy. Abstract With the aim of enhancing the understanding of NEIL3 in prognosis prediction and therapy administration, we conducted a pan-cancer landscape analysis on NEIL3. The mutation characteristics, survival patterns, and immune features of NEIL3 across cancers were analyzed. Western blotting, qPCR, and immunohistochemistry were conducted to validate the bioinformatics results. The correlation between NEIL3 and chemotherapeutic drugs, as well as immunotherapies, was estimated. NEIL3 was identified as an oncogene with prognostic value in predicting clinical outcomes in multiple cancers. Combined with the neoantigen, tumor mutational burden (TMB), and microsatellite instability (MSI) results, a strong relationship between NEIL3 and the TME was observed. NEIL3 was demonstrated to be closely associated with multiple immune parameters, including infiltrating immunocytes and pro-inflammatory chemokines, which was verified by experiments. More importantly, patients with a higher expression of NEIL3 were revealed to be more sensitive to chemotherapeutic regimens and immune checkpoint inhibitors in selected cancers, implying that NEIL3 may be an indicator for therapeutic administration. Our study indicated NEIL3 has a strong association with the immune microenvironment and phenotypic changes in certain types of cancers, which facilitated the improved understanding of NEIL3 across cancers and highlighted the potential for clinical application of NEIL3 in precision medical stratification.
Biofabrication of Poly(glycerol sebacate) Scaffolds Functionalized with a Decellularized Bone Extracellular Matrix for Bone Tissue Engineering

The microarchitecture of bone tissue engineering (BTE) scaffolds has been shown to have a direct effect on the osteogenesis of mesenchymal stem cells (MSCs) and bone tissue regeneration. Poly(glycerol sebacate) (PGS) is a promising polymer that can be tailored to have specific mechanical properties, as well as be used to create microenvironments that are relevant in the context of BTE applications. In this study, we utilized PGS elastomer for the fabrication of a biocompatible and bioactive scaffold for BTE, with tissue-specific cues and a suitable microstructure for the osteogenic lineage commitment of MSCs. In order to achieve this, the PGS was functionalized with a decellularized bone (deB) extracellular matrix (ECM) (14% and 28% by weight) to enhance its osteoinductive potential. Two different pore sizes were fabricated (small: 100–150 μm and large: 250–355 μm) to determine a preferred pore size for in vitro osteogenesis. The decellularized bone ECM functionalization of the PGS not only improved initial cell attachment and osteogenesis but also enhanced the mechanical strength of the scaffold by up to 165 kPa. Furthermore, the constructs were also successfully tailored with an enhanced degradation rate/pH change and wettability. The highest bone-inserted small-pore scaffold had a 12% endpoint weight loss, and the pH was measured at around 7.14. The in vitro osteogenic differentiation of the MSCs in the PGS-deB blends revealed a better lineage commitment of the small-pore-sized and 28% (w/w) bone-inserted scaffolds, as evidenced by calcium quantification, ALP expression, and alizarin red staining. This study demonstrates a suitable pore size and amount of decellularized bone ECM for osteoinduction via precisely tailored PGS elastomer BTE scaffolds.
A simple test for new better than used in expectation

We present a statistical procedure to test that a life distribution is exponential against the al ternative that it is continuous new better than used in expectation. The test is shown to be consistent and asymptotic relative efficiency resul ts are obtained against the competitor developed earlier by Hollander and Proschan [2], for certain families of alternatives.