Miracle-dz/UniFAR-FTUs huggingface dataset:
ARGAN: Adversarially Robust Generative Adversarial Networks for Deep Neural Networks against Adversarial Examples

An adversarial example, which is an input instance with small, intentional feature perturbations to machine learning models, represents a concrete problem in Artificial intelligence safety. As an emerging defense method to defend against adversarial examples, generative adversarial networks-based defense methods have recently been studied. However, the performance of the state-of-the-art generative adversarial networks-based defense methods is limited because the target deep neural network models with generative adversarial networks-based defense methods are robust against adversarial examples but make a false decision for legitimate input data. To solve the accuracy degradation of the generative adversarial networks-based defense methods for legitimate input data, we propose a new generative adversarial networks-based defense method, which is called Adversarially Robust Generative Adversarial Networks(ARGAN). While converting input data to machine learning models using the two-step transformation architecture, ARGAN learns the generator model to reflect the vulnerability of the target deep neural network model against adversarial examples and optimizes parameter values of the generator model for a joint loss function. From the experimental results under various datasets collected from diverse applications, we show that the accuracy of ARGAN for legitimate input data is good-enough while keeping the target deep neural network model robust against adversarial examples.We also show that the accuracy of ARGAN outperforms the accuracy of the state-of-the-art generative adversarial networks-based defense methods.
A Learning-Based Model Predictive Trajectory Planning Controller for Automated Driving in Unstructured Dynamic Environments

This paper presents a learning-based model predictive trajectory planning controller for automated driving in unstructured, dynamic environments with obstacle avoidance. We first address the problem of lacking prior knowledge in unstructured environments by introducing a risk map that maps the density and motion of obstacles and the road to an occupancy risk. Model predictive control is then used to integrate trajectory planning and tracking control into one framework to bridge the gap between planning and control. Meanwhile, we use Gaussian Process (GP) regression to learn the residual model uncertainty for improving the model accuracy. An objective function considering both risks within the feasible region and vehicle dynamics is carefully formulated to obtain collision-free and kinematically-feasible local trajectories. Field experiments are performed on real unstructured environments with our automated vehicle. Experimental results demonstrate the effectiveness of the proposed algorithm for successful obstacle avoidance in various complex unstructured scenarios.
Challenges and Solutions for Physical Testing in Sport: The Profiling Physical Qualities Tool

ABSTRACT The measurement, analysis, and reporting of physical qualities within sport is vital for practitioners to support athlete development. However, several challenges exist to support this process (e.g., establishing comparative data, managing large data sets) within sport. This article presents 7 challenges associated with physical testing in sport and offers solutions to overcome them. These solutions are supported by a description of the Profiling Physical Qualities (ProPQ) tool. The ProPQ tool uses advanced data analysis, visualization, and interactive elements, to enhance stakeholders' use of data to optimize player development and coaching practices. The ProPQ is currently used across rugby league in England.
Numerical Analysis of Vehicle-Bridge Coupling Vibration for Highway Bridges

The analysis of vehicle- bridge coupling vibration for highway bridges is complicated. A numerical method of analyzing vehicle- bridge coupling vibration is presented based on ANSYS software combining principle of separation iteration method and theory of vehicle dynamics. The vehicle and bridge models are built separately by using ANSYS,and the displacement coordination relation between the wheel and the bridge surface is fulfilled with the help of constrain equation at any time,meanwhile the balance of interaction between vehicle and bridge is automatically satisfied. When single vehicle or several vehicles drived through bridges, coupled dynamic time- history response of bridges is analyzed by APDL programming based on transient dynamics function of ANSYS,and the computed results are quantitatively compared with those in references. The results show that this method is reliable. Compared with the results in the references,the relative error of dynamic response of bridges is less 5% on smooth deck,while the varying trend of dynamic response of bridges is similar on roughness deck. Iterative computation is not needed in this method at any load step,so complicated program design is avoided and analysis efficiency is greatly improved.
Effect of Pore Structure and Capillary Number on Gas-Water Flow Patterns in Carbonate Rocks

Rock pore structure and capillary number determine gas-water flow through limestone. Limestone is of key importance for natural gas production and gas storage; however, there is still limited direct evidence on the precise influence of the pore space morphology (vugs, fractures, and homogeneous pore matrix) and capillary number. Here, we thus studied gas-water flow patterns in various limestones via in-situ X-ray microtomography combined with numerical flow simulations. Pore structure heterogeneity significantly affected the fluid migration path. Gas flowed rapidly through large pores and vugs but flowed slowly through microfractures. In contrast, water flowed through microfractures and small pores but did not enter large pores at low capillary number conditions. Water flow simulations [performed for different capillary numbers directly on microcomputed tomography (μ-CT) images] demonstrated that snap-off and dead-end corners controlled the distribution of residual gas, consistent with the experiments. In addition, the simulations showed that less residual gas distributed around dead-end corners at a low capillary number, and a part of the residual gas can be displaced by increasing viscous forces. Moreover, a power-low relationship between gas cluster volume and surface area was observed, and the gas cluster size distribution could also be fitted with a power-law correlation. In all types of tested limestones, the power-law exponents (p ≈ 0.77, τ ≈ 0.86) were lower than that predicted by simple percolation theory (which predicts p ≈ 1, τ ≈ 2.189). There was evidence that a simple percolation model was unlikely to provide reliable predictions in homogeneous porous media, and we further extended the application scope of this conclusion to heterogeneous porous media. This work therefore provides fundamental data and improves fundamental understanding of gas-water flow through limestones and aids in the further advancements of improved hydrocarbon recovery and gas storage in limestone reservoirs.
Weakly nonlinear Ekman pumping in the Sri Lanka Dome and the Southwest Monsoon Current

The Sri Lanka Dome is a cyclonic recirculation feature in the Southwest Monsoon Current system in the southern Bay of Bengal. Cooler sea surface temperature (SST) in the vicinity of this system is often denoted as the Bay of Bengal “Cold Pool”. Although the wind shadow of Sri Lanka creates a region of strong positive wind stress curl, both sea level height dynamics and the distribution of cool SST cannot be explained by wind stress curl alone via traditional Ekman pumping. Moreover, the Cold Pool region is often aligned with the eastern portion of the Sri Lanka Dome, as defined by sea surface height. Previous work has attributed the spatial SST pattern to lateral advection. In this analysis, we explore whether low latitude weakly nonlinear ‘vorticity’ Ekman pumping could be an explanation for both cooling and observed changes in sea level height in the southwest Bay of Bengal. We show that weakly nonlinear upwelling, calculated from ERA5 and AVISO geostrophic currents, co-locates with changes in sea level height (and presumably isopycnals). While the SST signal is sensitive to several factors including the net surface flux, regional upwelling explains changes in AVISO sea level height if the nonlinear terms are included, in both the Sri Lanka Dome and the region of the Southwest Monsoon Current.
Production of Atosiban’s Key Intermediate Pentapeptide: Synthetic Approaches to the Development of a Peptide Synthesis with Less Racemization and Simplifier Purification Process

The key intermediate NH2-Ile-Thr(Bzl)-Asn-Cys(Bzl)-Pro-COOH of Atosiban was prepared from N-Boc-S-Bzl-cysteine by the stepwise lengthening of the chain according to the repetitive N,O-bis(trimethylsilyl)acetamide/N-hydroxysuccinimide ester (BSA/NHS) strategy. This synthetic route required no chromatography purification and can be readily performed, yielding a highly pure pentapeptide compound.
Digital Art Pattern Design Based on Visual Material Colouring Intelligent Programming System

With the continuous enhancement of computer technology, digital technology brings more convenience to people with its powerful functions. After the digital technology is applied to the design field, it greatly expands the creative space of art design. In the digital age, fabric printing and dyeing design needs to be combined with digital technology under the guidance of art theory. Traditional flat patterns can no longer satisfy people’s pursuit of visual illusion patterns with a sense of space and three-dimensionality. The use of computer representation can realize the innovative artistic design and can directly generate various highly creative visual images in the computer according to the theme and creative needs. We input the digital data related to the fabric, such as graphics, photographic photos, logos, fonts, and textures, into the computer and then use various application software to perform various special effects on them to produce creative, unique, and surprising picture effects. In the aspect of exploring the meaning of the theme, the application of spatial expression means is studied, and practical research is carried out to guide the design of works with spatial beauty and creativity. In view of the neglect of artistic design, on the basis of studying the space art expression of traditional printing and dyeing process patterns, the traditional space art expression is combined with computer image processing technology. And special techniques are used to create differences in various textile fabrics and garments. We use the software of digital art design to carry out the artistic creation practice of spatial expression. Through the application of computer software functions, combined with the guidance of spatial expression techniques, the design comparison of patterns is carried out, which provides design practice ideas for the integration and innovation of traditional printing and dyeing technology and modern design. The implementation of the visual material colouring programming system reduces the coupling between artists and programmers and reduces the coupling between art collections and producers. The colouring program in the process of art pattern development improves the efficiency of art design.
Targeting BPTF Sensitizes Pancreatic Ductal Adenocarcinoma to Chemotherapy by Repressing ABC-Transporters and Impairing Multidrug Resistance (MDR)

Simple Summary Pancreatic ductal adenocarcinoma is a devastating disease and an extremely chemoresistant tumour. In the present manuscript, we described the role of BPTF during tumour pancreatic ductal adenocarcinoma progression and in response to gemcitabine treatment, a gold standard treatment in this tumour type. Through different genetic approaches, we reduced BPTF levels in a panel of pancreatic ductal adenocarcinoma cell lines. We validated its therapeutic effect in cell cultures and in mouse models of pancreatic cancer. A reduction in BPTF levels impaired cell proliferation and sensitized pancreatic tumour cells to gemcitabine. We demonstrated that BPTF-silencing reduced the expression of several ABC-transporters, which are involved in gemcitabine resistance, and enhanced its accumulation in the tumour cell, improving its therapeutic effect. Abstract Pancreatic ductal adenocarcinoma (PDA) is characterized by an extremely poor prognosis due to its late diagnosis and strong chemoresistance to the current treatments. Therefore, finding new therapeutic targets is an urgent need nowadays. In this study, we report the role of the chromatin remodeler BPTF (Bromodomain PHD Finger Transcription Factor) as a therapeutic target in PDA. BPTF-silencing dramatically reduced cell proliferation and migration in vitro and in vivo in human and mouse PDA cell lines. Moreover, BPTF-silencing reduces the IC50 of gemcitabine in vitro and enhanced its therapeutic effect in vivo. Mechanistically, BPTF is required for c-MYC recruitment to the promoter of ABC-transporters and its downregulation facilitates gemcitabine accumulation in tumour cells, increases DNA damage, and a generates a strong synergistic effect in vivo. We show that BPTF is a therapeutic target in pancreatic ductal adenocarcinoma due to its strong effect on proliferation and in response to gemcitabine.
Investigation the inhibitory effects of AgNPs generated by Bifidobacterium spp. on bacteria isolated from ready-to-eat foods

Ready-to-eat (RTE) foods including vegetable salads are one of the most preferable foods sold and served in resturants in Kirkuk city-Iraq. Foodborne diseases endure a major problem in developing countries because lacking of personal hygiene and food safety measurements. Silver nanoparticles (AgNPs) are nanomaterials are one of the crucial and fascinating nanomaterials involved in various fields including control of pathogenic bacteria like foodborne pathogens. Therefore, this study aims to synthesize AgNPs by using eco-friendly Bifidobacterium (a silver reducing agent), and studying their effects against a range of foodborne pathogenic microorganisms. The synthesis of the AgNPs was monitored using ultraviolet visible UV-Vis spectroscopy and Fourier transform spectroscopy (FTIR). The results showed that the absorption spectra of biologically-prepared AgNPs was at wave length ranging from 200-600 nm. The AgNPs have also different functional groups such as O-H, -C ≡ CH, C=C stretching vibration respectively. Antagonism effect of AgNPs on Staphyloccocus aureus, Pseudomonas aeruginosa, E.coli and Proteus mirabilis has been tested that isolates from (RTE) vegetable salads. Diameter of growth inhibition zone of these bacteria was determined using agar well diffusion method.
Narrow But Robust Advantages in Two-Leaf Light Use Efficiency Models Over Big-Leaf Light Use Efficiency Models at Ecosystem Level

This study aims to (1) investigate whether two-big-leaf light use efficiency (LUE) models (TL) outperform big-leaf LUE models (BL) by incorporating different gross primary productivity (GPP) responses in sunlit and shaded leaves; (2) explore the robustness of using the leaf area index (LAI), clumping index ( Ω ) and spherical leaf angle distribution to partition canopies into sunlit and shaded leaves across canopy architectures; (3) identify optimal light response forms in LUE models. To exclude influences of drivers of GPP other than radiation, we collected various formulations of GPP response functions to temperature, vapor pressure deficit, CO 2 , soil water supply, light intensity and cloudiness index to construct 5600 BLs and 1120 TLs. These models were evaluated at 196 globally-distributed eddy covariance sites from the FLUXNET observational network using the Nash-Sutcliffe model efficiency (NSE), root mean squared error and Bayesian information criterion. Across all sites, the best big-leaf model (BL*; NSE = 0.82) was statistically equal to the best TL (TL*; NSE = 0.84). However, daily dynamics in GPP under hot and dry conditions were best described using TL* in 17% of sites, highlighting the local importance in separating sunlit and shaded leaves. Across approaches to represent effective LAI, the best approach relies on using normalized difference vegetation index with a spherical or flexible leaf angle distri- bution across sites rather than satellite LAI and Ω . We also observed similar performance between non-rectangular hyperbola and reciprocal light response functions across TLs. Models degrade when the maximum LUE is not differentiated between sunlit and shaded leaves, but not when light saturation levels are the same. Despite functional differences, the best five TLs agree in a larger contribution of shaded leaf area to total GPP, resulting from higher LAI and LUE. Overall, these results suggest marginal but robust selection of TL compared to BL.
Robust control system design for a aducted fan unmanned aerial vehicle

The flight attitude control system for the small size ducted fan unmanned aerial vehicle (UAV) is presented.Firstly,the mathematic model for the UAV is constructed from the forces and moments analysis of the vehicle,and the derived nonlinear model is linearized in the hovering flight condition.Then the robust flight attitude controller based on this linear model is designed to deal with the parameter uncertainty and external disturbance which is due to the compact configuration.The validity of the controller is verified by the simulation results,and also the controller is applied in the flight testing.The results show that the vehicle with the controller has a good performance of operation stability.
Nanotechnology in Immunotherapy for Type 1 Diabetes: Promising Innovations and Future Advances

Diabetes is a chronic condition which affects the glucose metabolism in the body. In lieu of any clinical “cure,” the condition is managed through the administration of pharmacological aids, insulin supplements, diet restrictions, exercise, and the like. The conventional clinical prescriptions are limited by their life-long dependency and diminished potency, which in turn hinder the patient’s recovery. This necessitated an alteration in approach and has instigated several investigations into other strategies. As Type 1 diabetes (T1D) is known to be an autoimmune disorder, targeting the immune system in activation and/or suppression has shown promise in reducing beta cell loss and improving insulin levels in response to hyperglycemia. Another strategy currently being explored is the use of nanoparticles in the delivery of immunomodulators, insulin, or engineered vaccines to endogenous immune cells. Nanoparticle-assisted targeting of immune cells holds substantial potential for enhanced patient care within T1D clinical settings. Herein, we summarize the knowledge of etiology, clinical scenarios, and the current state of nanoparticle-based immunotherapeutic approaches for Type 1 diabetes. We also discuss the feasibility of translating this approach to clinical practice.
Fuzzy Modeling of Surface Roughness Parameters in Machining Ti-6Al-4V Alloy

Titanium alloys are attractive materials used in different engineering applications, due to its excellent combination of properties such as high strength to weight ratio, good corrosion resistance and high temperature applicability. They are also being used increasingly in chemical process, automotive, biomedical and nuclear plant. When machining of Titanium alloys with traditional tools the tool wear rate high. Because of high chemical reactivity and low modulus of elasticity resulting high cutting temperature and strong adhesion between the tool and work piece materials. The poly crystalline diamond (PCD) cutting tool is used for the turning experiment. The turning parameters for the experimental work are cutting speed, feed, nose radius, and depth of cut. From the results, analysis of the influences of the individual parameters on the surface roughness have been carried out. Fuzzy modeling technique is effectively used to predict the surface roughness in the machining of titanium alloy.
Molecular and Pharmacological Evidence for the Expression of Multiple Functional P2 Purinergic Receptors in Human Adipocytes

Extracellular ATP exerts important functions as an extracellular signaling molecule via the activation of specific P2 purinergic receptors (P2X and P2Y). We investigated the expression of the different P2 receptors and their possible functional activation in human adipocytes in primary culture. We performed molecular expression analysis of the P2 receptors in human mature adipocytes; examined their functional activation by different nucleotides evaluating [Ca2+]i modifications and IL-6 secretion, and determined the ability of adipocytes to release ATP in the extracellular medium. Human adipocytes express different P2X and P2Y receptors. Extracellular ATP elicited a rise in [Ca2+]i via the activation of P2X and P2Y receptor subtypes. Human adipocytes spontaneously released ATP in the extracellular medium and secreted IL-6 both at rest and after stimulation with ATP. This stimulatory effect of ATP on IL-6 secretion was inhibited by pre-incubation with apyrase, an ATP metabolizing enzyme. These results demonstrate that human adipocytes express different P2X and P2Y receptors that are functionally activated by extracellular nucleotides. Furthermore, human adipocytes spontaneously release ATP, which can act in an autocrine/paracrine fashion on adipocytes, possibly participating in the regulation of inflammatory cytokine release. Thus, P2 purinergic receptors could be a potential therapeutic target to contrast the inflammatory and metabolic complications characterizing obesity.
Design and Analysis of NB QC-LDPC Codes Over Small Alphabets

We propose a novel approach to optimization of irregular nonbinary (NB) quasi-cyclic (QC)-LDPC codes over small alphabets. In this approach, first, the base parity-check matrices are constructed by a simulated annealing method, and then these matrices are labeled by the field elements while maximizing the so- called generalized girth of the Tanner graph. In order to analyze the performance of the constructed irregular NB LDPC codes, a new ensemble of irregular NB LDPC codes over the extensions of the binary Galois field is introduced. A finite-length random coding bound on the error probability of the maximum-likelihood (ML) decoding over the binary phase shift keying (BPSK) input AWGN channel for the new code ensemble is derived. The frame error rate (FER) performance of the sum-product belief-propagation (BP) decoding of the constructed NB QC-LDPC block codes is compared to that of both the optimized binary QC-LDPC block codes in the 5G standard and the best known NB QC-LDPC codes as well as to the derived random coding bound on the ML decoding error probability. It is shown that the obtained bound predicts the behavior of BP decoding performance of practical NB QC-LDPC codes more accurately than the BP decoding thresholds do.