Miracle-dz/UniFAR-FTUs huggingface dataset:
The small molecule nitazoxanide selectively disrupts BAM-mediated folding of the outer membrane usher protein

Bacterial pathogens assemble adhesive surface structures termed pili or fimbriae to initiate and sustain infection of host tissues. Uropathogenic Escherichia coli, the primary causative agent of urinary tract infections, expresses type 1 and P pili required for colonization of the bladder and kidney, respectively. These pili are assembled by the conserved chaperone–usher (CU) pathway, in which a periplasmic chaperone works together with an outer membrane (OM) usher protein to build and secrete the pilus fiber. Previously, we found that the small molecule and antiparasitic drug nitazoxanide (NTZ) inhibits CU pathway–mediated pilus biogenesis in E. coli by specifically interfering with proper maturation of the usher protein in the OM. The usher is folded and inserted into the OM by the β-barrel assembly machine (BAM) complex, which in E. coli comprises five proteins, BamA–E. Here, we show that sensitivity of the usher to NTZ is modulated by BAM expression levels and requires the BamB and BamE lipoproteins. Furthermore, a genetic screen for NTZ-resistant bacterial mutants isolated a mutation in the essential BamD lipoprotein. These findings suggest that NTZ selectively interferes with an usher-specific arm of the BAM complex, revealing new details of the usher folding pathway and BAM complex function. Evaluation of a set of NTZ derivatives identified compounds with increased potency and disclosed that NTZ's nitrothiazole ring is critical for usher inhibition. In summary, our findings indicate highly specific effects of NTZ on the usher folding pathway and have uncovered NTZ analogs that specifically decrease usher levels in the OM.
Obesity and breast cancer screening: Cross‐sectional survey results from the behavioral risk factor surveillance system

Postmenopausal obese women demonstrate an elevated breast cancer risk and experience increased breast cancer morbidity and mortality compared with women with a normal body mass index (BMI). However, to the authors' knowledge, prior studies have yielded inconclusive results regarding the effects of obesity on mammography screening adherence. Using national cross‐sectional survey data, the objective of the current study was to assess the current association between increasing BMI and use of mammography screening.
Fabrication, Flow Control, and Applications of Microfluidic Paper-Based Analytical Devices

Paper-based microfluidic devices have advanced significantly in recent years as they are affordable, automated with capillary action, portable, and biodegradable diagnostic platforms for a variety of health, environmental, and food quality applications. In terms of commercialization, however, paper-based microfluidics still have to overcome significant challenges to become an authentic point-of-care testing format with the advanced capabilities of analyte purification, multiplex analysis, quantification, and detection with high sensitivity and selectivity. Moreover, fluid flow manipulation for multistep integration, which involves valving and flow velocity control, is also a critical parameter to achieve high-performance devices. Considering these limitations, the aim of this review is to (i) comprehensively analyze the fabrication techniques of microfluidic paper-based analytical devices, (ii) provide a theoretical background and various methods for fluid flow manipulation, and (iii) highlight the recent detection techniques developed for various applications, including their advantages and disadvantages.
Flavonoids from Brazilian Cerrado: Biosynthesis, Chemical and Biological Profile

Flavonoids are highly bioactive compounds with very low toxicity, which makes them attractive starting points in drug discovery. This study aims to provide information on plant species containing flavonoids, which are found in the Brazilian Cerrado. First, we present the characterization and plant diversity with emphasis on the families of flavonoid-producing plants, and then we describe the phenylpropanoid pathway which represents the flavonoids’ main route biosynthesis—generally conserved in all species. Chemical structures and biological activities of flavonoids isolated from the Cerrado’s plant species are also described based on examples from the relevant literature studies. Finally, research on the biodiversity of the Cerrado biome should be encouraged, due to the discovery of new sources of flavonoids which can provide several benefits to human health and the possibility of developing new drugs by the pharmaceutical industry.
Functional bowel complaints and quality of life after surgery for colon cancer: prevalence and predictive factors

Low anterior resection syndrome (LARS) severely affects the quality of life (QoL) of patients after surgery for rectal cancer. There are very few studies that have investigated LARS‐like symptoms and their effect on QoL after colon cancer surgery. The aim of this study was to investigate the prevalence of functional abdominal complaints and related QoL after colon cancer surgery compared with patients with similar complaints after rectal cancer surgery.
Incontinence and headache in preschool children

Headaches in preschool children are associated with behavioral and gastrointestinal symptoms. As the co‐occurrence with incontinence is not known in young children, the aim of the study was to examine associations of headache, psychological symptoms and nocturnal enuresis (NE), daytime urinary incontinence (DUI), and fecal incontinence (FI) in a population‐based sample of preschool children.
Secure and Size Efficient Approach to Enhance the Performance of Text Steganographic Algorithm

Steganography is a fundamental and foremost approach used to ensure confidentiality of secret data. It is an art which ensures invisible communication by concealing secret information in cover media through scientific techniques. The text steganography faces a great challenge in security, robustness and size of stego text. In current studies, an improved, lightweight, secure, robust and size efficient technique is proposed for text steganography that also enhances the performance of existing approaches. To achieve the objectives, the algorithm applies a conditional bitcomplement function on binary value of confidential information. Moreover, start and end bits are also inserted during embedding secret information in cover text, confirming the integrity and confidentiality of secret data. Experimental results reveal that projected approach is more robust and secure without any stego key overhead. Furthermore, it has successfully achieved a size efficient stego text. Therefore, the secret information is harder to track.
A secure inter-domain communication for IoT devices

Nowadays, a multitude of sensors are used to gather data in several fields from smart buildings, to industries, to cars, etc. These sensor data are instrumental in making smart decisions. In order to send data to end users, these sensors are connected to the Internet of Things (IoT) devices. Usually, the intra-domain data transmission is secure, indeed sensors and consumers of data can belong to the same Virtual Private Network (VPN). Security problems can be raised in the inter-domain data transmission because the transmitting channel is not ciphered nor is the identity of devices certain. Therefore, in case of attack, for consumers of data is not possible to recognize real data gathered from devices from fake data sent by attackers. In order to address this challenge, in this paper we present a novel method to secure data acquired from sensors connected to IoT devices. In particular, utilizing a Public Key Infrastructure (PKI) and the ESP32 microcontroller, we can send data privately to each recipient. In order to validate the system, we performed specific analysis considering different levels of security (512, 1024, 2048 bits key length) and increasing number of connected sensors (0, 1, 5, 10, 20). In particular, we considered the time to set up the IoT device and to cipher packets. Experiments have shown that the time required for the setup increases with the increase of the key length. Considering the 512 and 1024 bits keys, the time required to cipher data coming from sensors increase with the increasing of sensors. Instead, for the 2048 bits key length the ciphering time is almost constant, this because packet size and key length are comparable.
Health Vision: An interactive web based platform for healthcare data analysis and visualisation

The exponentially increasing volumes of health data of different types is a challenge for reaching robust conclusions. The Health Vision platform overcomes this issue by providing advanced and multi-scaling data analysis and visualisation. The platform functions through user defined workflows, each organised into four distinct layers: 1. Raw Data, 2. Data Analytics, 3. Decision Support and 4. Data visualisation. In the Raw Data Layer, data from medical records, healthcare platforms, smart homes, monitoring sensors, and medical devices, clinical features from Electronic Health Records (EHRs), etc. can be considered, while the Data Analytics Layer provides data analysis services for data mining. The Decision Support Layer facilitates the selection of appropriate visualisation methods taking into consideration the specifications of the raw data and the output of the data analysis. Finally, the Data visualisation Layer provides intelligent visualisation methodology in order for the user to interact with the data and gain meaningful results. Visualisation is supported by a reactive workflow mechanism, allowing the composition of analysis and visualisation services in a custom application-specific data flow. We demonstrate and evaluate this novel approach in several use cases, where different types of data are involved, including: Clustering of Sjögren's syndrome patients, visualisation of Parkinson's disease patients, mutation association analysis in Chronic Lymphocytic Leukemia patients, behavioral analysis of asthma patients and clinical analysis based on clinical similarities of older adults.
Information Filtering via Trust Relationship for Better Personalized Recommendation

Recommender system is one of the most promising techniques with widest application in solving the problem of information overload. Aimed at providing better performance personalized recommendation, this paper improves a new hybrid recommender method based on social trust relationship and benchmark information filtering algorithm. Epinions and Friendfeed show that the hybrid trust method has better performance with high accuracy. Moreover, trust relationship has positive effect on the personalized recommendation performance.
Modular Circular Waveguide Antenna System For Arbitrary Pattern Synthesis In Scaled Measurement Environments

This contribution presents a design concept for an antenna construction toolkit for arbitrary symmetric pattern design in the Ku-band consisting of slotted circular waveguide elements. The design allows the adjustment of arbitrary amplitudes for the radiating elements using a rotatable aperture. No electric feeding network is needed as the radiators are excited using the fundamental waveguide mode and the amplitudes are adjusted in a solely mechanical way. The toolkit is designed after an existing antenna toolkit made from rectangular waveguide elements but presents benefits in manufacturing, usage and costs. Furthermore the design is easily scalable to other frequencies.
SMAP Fog/Edge: A Secure Mutual Authentication Protocol for Fog/Edge

Security is a crucial factor for the appropriate functioning of fog/edge computing. Secured mutual authentication in networks has become key demand as per the current security standard. Several applications are in its requirements like wireless sensor network (WSN), Distributed Systems, Micro-Cloud, Smart City, Smart Industry 4.0. Problem statement is “Design and implementation of Fog servers and edge devices to dynamically interconnect with each other using secured mutual authentication”, which is an NP complete problem. Implementation of secured mutual authentication protocol (SMAP) using techniques of pseudo-random number generator, time-stamps and hash functions can only be considered to evaluate the best performance for connecting large number of smart devices. Our protocol avoids storing master secret keys and repetition of session keys, which makes it more secure and carries no overhead. The experimental results show that the secured mutual authentication system is efficient in comparison to recent benchmarks.
Recognition of Handwritten Chinese Characters Based on Concept Learning

Many deep-learning character recognition methods have been developed over the past few years. Chinese characters are widely used in many countries; however, the deep-learning-based Chinese character recognition methods are faced with various problems, such as a large amount of data required for training, numerous parameters, and a large consumption of computing resources. Concept learning is a hominine learning approach. Unlike existing deep-learning models, conceptual model learning can be realized by using as little as one sample. This paper is the first to propose a handwritten Chinese character recognition method based on concept learning. Different from the existing image representation-based character recognition methods, the proposed method builds a meta stroke library with prior knowledge, and then, presents a Chinese character conceptual model based on stroke relationship learning using a character stroke extraction method and Bayesian program learning. During character recognition, Monte Carlo Markov chain sampling is utilized to obtain the character generation model for each character conceptual. This generation model can calculate the probability of the target and training characters being the same classification, and thereby determines the classification of the target character. The experimental results indicate that, with the proposed method, the conceptual model of each character can be built for character classification prediction using as few as one character sample. Our approach obtains better performance than the state-of-the-art methods on ICDAR-2013 competition dataset.
DriveLaB: An Experimental Platform for Telematics

Speed is a major killer in traffic. This paper presents the DriveLaB telematics platform that monitors drivers in real-time and provides feedback if they are speeding. The platform has been developed in collaboration with a major Danish insurance company and used in three larger field trials. The platform uses an Android/iOS smartphone app at the client side and does all data processing at the server-side, e.g., map-matching. The paper first provides an overview of the entire platform and then focuses on three major technical challenges: 1) A trip scoring algorithm that allows for comparison of scores across trip length. 2) A notification system that provides both positive and negative real-time feedback to the drivers, without leading the drivers' attention away from traffic. 3) Auto start of the cross-platform app to make it convenient for drivers to participate in the field trials. Three field trials, with 32 participants driving 57,933 km has been conducted. The results of these trials validates that trip scores can be compared across trip length. Further, we demonstrate that doing all data-processing on the server side is a viable approach also for real-time notifications and that drivers are notified with reasonable delays. Finally, we show that the client auto start is fast, robust, and convenient.
650 V Highly Reliable GaN HEMTs on Si Substrates over multiple generations: Expanding usage of a mature 150 mm Si Foundry

This manuscript proves maturity of GaN-on-Si technology for the world’s first highly reliable 650V GaN HEMT [2],[3],[4],[5],[6],[7],[8] by demonstrating three years of manufacturing data of since ramp. This technology was initially developed in a pilot line in Transphorm Goleta, CA and then later ported into a Si-CMOS compatible 6-inch foundry at AFSW(Aizu Fujitsu Semiconductor Wafers Solution Ltd). Data set generated from over three thousand wafers worth of data spread over three generations of technology nodes covering multiple products and packages post qualification is presented Silicon manufacturing processes are employed including gold- free, and avoiding the use of evaporation/liftoff typical to compound semiconductors. Best practice of defect detection, failure analysis and process control methods from Si manufacturing industry have been employed to maintain and improve yield for this new technology. Probe yield and line yield for the GaN process now matches that of mature Si-CMOS process running in the same fabrication facility[1]. Wide bandgap high-speed and high- voltage GaN devices significantly reduce the system size and improve energy efficiency of power conversion in all areas of electricity conversion, ranging from PV inverters to electric vehicles. The results below demonstrates that GaN high volume production is now a reality.
Hand Gesture Based Character Recognition using Neural Network

: Communication is the trading of thoughts, messages, or data, as by discourse, visuals, signs, composing, or conduct. Hard of hearing and unable to speak individuals impart among themselves utilizing gesture-based communications, however they think that its hard to open themselves to the outside world. This paper proposes a visual based strategy for Communication amongst hard of hearing and unable to speak individuals with the outside world utilizing computers. This strategy utilizes Indian communication via gestures hand motions given by the client as contribution through webcam and is changed over into an instant message. Not at all like the ordinary strategy for hand signal acknowledgment which makes utilization of gloves or markers or some other gadgets, this technique does not require any extra equipment and makes the client agreeable. Productivity is accomplished by utilizing a blend of various Algorithm together to extract features as opposed to depending on a solitary calculation.
The Analysis of the Influencing Factors on the Problems of Bike-Sharing System in China

Bike-sharing has experienced rapid growth in China since 2016. Notwithstanding the fast expansion, or possibly because it grew too fast, some bike-sharing companies have experienced setbacks and failure in 2018. This paper aims to close the gap due to the insufficient analysis on the influencing factors of the bike-sharing system problems in China. The study first used text mining of bikes-sharing related Chinese news reports and social web discussion boards. Subsequently, the study used association rule mining to explore the relationship between keywords generated by text mining of the original data sources. The results of news reports mined keywords show that problems with shared bikes deposits were closely related to the complaints of customers. In the context of social web discussion boards, the keywords relations implies that the users concern about the possible collapse of the bike-sharing companies and related management and economy issues. The information existed before the bike-sharing companies financial failure news took place. Our results also show that the association rule mining relationship of major keywords in news reports and social media can be an early warning sign of the financial failure of sharing bikes companies.
Oil Painting Style Rendering Based on Kuwahara Filter

The Kuwahara filter can generate local smoothed color regions similar to hand-painted strokes, and therefore it can be used to image artistic rendering. However, the existing Kuwahara filtering methods often adopt a fixed-sized filter kernel, which leads to a homogeneous size of strokes. In view of this problem, a multi-scale anisotropic Kuwahara filtering method is proposed in this paper. By using image saliency as control information to adjust the size of filter kernel, strokes with abundant varied geometric scales are generated. This paper also presents an automatic rendering framework based on the proposed algorithm that automatically transforms images into an oil painting style. Using the image’s orientation field of edge, edge gradient magnitude and image saliency to control the bump mapping, the senses of thickness and layers of oil painting’s strokes are generated. By adopting this framework, an artistic oil painting style similar to the “impasto technique” can be simulated well.
Long-Distance and High-Power Capacitive Power Transfer based on the Double-Sided LC Compensation: Analysis and Design

This paper proposes to use the double-sided LC compensation circuit to realize the long-distance and high-power capacitive power transfer. The targeted transfer distance is 150mm for the vehicle charging application, resulting in a loosely-coupled system. The circuit working principle and the transfer efficiency are provided, which indicates the duality with the conventional series-series compensated inductive power transfer system. Using the same capacitive coupler, two load conditions (the constant resistive load and the constant voltage load)are analyzed for the practical applications. The analysis of the CPT system provides the guideline to design and optimize the LC-compensated system. The experimental results show that kW level power transfer can be achieved through 150mm distance with dc-dc efficiency from the dc source to the dc load to be around 88%.
Track to Track Association Based on Iterative Reference Pattern

Track to track association (TTTA) is a key problem in the multi-sensor data fusion system. Traditional TTTA algorithms are based on the absolute position information of targets degrade in the presence of sensor biases, which make the position estimates of targets deviate from their true values. Reference pattern (REP), which uses global structural feature of the spatial distribution of targets, is insensitive to sensor biases. However, false tracks can bring extraneous interferences to REP, while missed detections can result in partial loss of the structural feature. This paper, thus, presents a new TTTA approach based on iterative reference pattern (IREP). On one hand, the proposed method inherits the insensitivity of REP to sensor biases. On the other hand, it alleviates the adverse impact of false tracks and missed detections on REP by introducing the iterative process, which refines the reference track set (RDS) dynamically. Simulation results verify the performance superiority of the proposed method.
A Multiobjective Test Suite with Hexagon Pareto Fronts and Various Feasible Regions

The performance of a Multiobjective Evolutionary Algorithm (MOEA) for many-objective optimization is often evaluated by multiobjective scalable test problems like DTLZ and WFG problems. This is because the scalable test problems are quite useful for an MOEA analysis. However, the scalable test problems do not have enough diversity of the shapes of the Pareto front and the feasible region to evaluate the capability of MOEAs. Previous studies showed that these shapes have a great impact on the performance of MOEAs. Thus, MOEAs should be evaluated on more test problems with different shapes of the Pareto front and the feasible region. In this study, the shapes of the Pareto front in the existing scalable test problems are examined from some viewpoints such as the distribution of optimal or worst solutions for each objective and the degree of the correspondence with the distribution of the weight vectors. The shape of the feasible region is also examined from the viewpoint of the spread of an initial population and the existence of dominance resistant solutions. According to the observations, we propose new shapes of the Pareto front and the feasible region to design a new scalable test suite. Experimental results show that the proposed test suite has totally different properties from the existing test problems.