Miracle-dz/UniFAR-FTUs huggingface dataset:
Tourists’ Motivation, Place Attachment, Satisfaction and Support Behavior for Festivals in the Migrant Region of China

This study aimed to explore the relationships among tourist motivation, place attachment, satisfaction and support behavior for hosting festivals in the migrant region of China. A self-administered questionnaire was used to conduct an on-site survey and a second-order structural equation modeling (SEM) technique was employed. The results of the current study showed that visitors’ general festival motivations had a positive influence on their place attachment and satisfaction. Visitors’ theme-related motivations had a positive influence on their place identity and satisfaction. Place dependence and place identity also positively affected their low-effort support behavior. In addition, visitors’ place identity was a positive antecedent of their high-effort support behavior. Visitors’ place attachment had a positive influence on their satisfaction and visitors’ satisfaction positively affected their support behavior. This study encouraged festival organizers to become aware that place attachment performs an important role in attracting tourists, and nostalgia is one of the most important motivations for hosting festivals in the migrant region of China. As a result, this study provides crucial insights that organizers should pay attention to place attachment and place identity in order to satisfy visitors and support festival activities.
Research Progress and Prospect of Aqueous Zinc Ion Battery

Zinc ion battery, a new type of aqueous secondary batteries proposed in recent years, can deliver high energy and high power density. Meanwhile, safe and efficient discharge processes, cheap and nontoxic electrode materials, and easy fabrication are the advantage of Zinc ion battery, showing great practical value and developmental prospects in the field of scale energy storage. In this paper, the development and exploration of aqueous zinc ion battery are reviewed. Also the advantages and challenges of the zinc anode are summarized. Moreover, this paper analyzed the electrochemical properties and reaction mechanism specifically. In addition, the development of cathode materials is predicted by analyzing the insertion and extraction of multivalent ions.
Detection and segmentation the affected brain using ThingSpeak platform based on IoT cloud analysis

The world has accelerated around a new industrial revolution called the Internet of Things, as this technology is expected to enter all aspects of industrial life, commercial and civil applications. The Internet of Things stands for highly important applications in the world of medical applications, which is the access to linking all medical clinics in the world into a single network capable of analyzing patient data and presenting it to medical professionals anywhere in the world. One of the medical applications in the Internet of Things is the discovery of a healthy human brain. This work proposes a health care system based on medical image analysis processes in the programmable ThingSpeak platform using MATLAB built into the platform within the cloud. The analysis is done using the MATLAB program within the Windows operating system and then the analysis is performed within ThingSpeak platform. The analysis includes classification process by using SVM classifier linear kernel in which we achieved 99.4% classification rate as well as using RBF kernel, which achieved 98.6% classification accuracy in classifying infected brains from healthy ones and the work was supported by cross validation technology to ensure effective classification accuracy. The patient brain is segmented then the tumor segment is isolated, its area is calculated, and the tumor boundaries are found, based on the k-mean technique, to support the specialist doctor when performing the analysis process in the cloud environment. Through this work we achieved a match in the analysis processes within the local environment, and ThingSpeak platform environment by 100%, and in order to support our work, we have automated the analysis, visualization and data transfer processes within the cloud and MATLAB environment.
Generative Design of a Mechanical Pedal

Nowadays, there are various tools that support the initial stages of design available to use for engineers, the traditional Computer-Aided Design (CAD) has been implemented in the engineering components design and replaced manual drafting. However, with the advances and the rapid technology development, new trends emerged to cope with this evolution, namely, Generative Design, Topology Optimization, and Generative Engineering Design. The method is based on numerical algorithms that generate a variety of design and modelling options based on the criteria and constraints set by the designer to allow further design exploration. Proposed in this paper is an implementation of the generative design of a mechanical pedal with further finite element analysis.
Study of Image Classification Accuracy with Fourier Ptychography

In this research, the accuracy of image classification with Fourier Ptychography Microscopy (FPM) has been systematically investigated. Multiple linear regression shows a strong linear relationship between the results of image classification accuracy and image visual appearance quality based on PSNR and SSIM with multiple training datasets including MINST, Fashion MNIST, Cifar, Caltech 101, and customized training datasets. It is, therefore, feasible to predict the image classification accuracy only based on PSNR and SSIM. It is also found that the image classification accuracy of FPM reconstructed with higher resolution images is significantly different from using the lower resolution images under the lower numerical aperture (NA) condition. The difference is yet less pronounced under the higher NA condition.
IMPROVISATION AS A MEANS OF ENHANCING THE TEACHING AND LEARNING OF MATHEMATICS IN SECONDARY SCHOOLS IN ENUGU STATE

Mathematics is an essential part of the education system in Nigeria. However, it is perceived among learners as a tedious and challenging subject. The primary objective of the current study was to enhance the teaching and learning of mathematics using improvisation. The study also examined the role of students location on mathematics learning when the learning material is improvised. The population of the study included secondary school students in both rural and urban areas of Enugu State. A total of 68 secondary school students constituted the study samples. A quasi-experimental design was used. Two hypotheses were tested, and it was concluded that improvisation of learning material enhances students performance in mathematics. Also, the study found that students location does not affect performance in mathematics when instructional material is improvised. The findings and recommendations are discussed.
Hybridization as a biodiversity driver: The case of Veronica × gundisalvi

Hybridization is an important mechanism in plant evolution, which contributes to the adaptability and biological diversity of species in fundamental ways. Based on morphological data, Veronica × gundisalvi Sennen (Veronicaorsiniana × Veronicatenuifolia subsp. tenuifolia) is an Iberian endemic taxon of presumably polytopic hybrid origin restricted to five localities in Catalonia, where the putative parental species grow in sympatry. In this study, species distribution models were developed for the putative parental species to seek potential new localities where active hybridization could be taking place. As a result, a new location of this nothotaxon in Zaragoza is provided, along with a chromosome count and ploidy level estimations. The data presented herefurther support Veronica × gundisalvi as a homoploid hybrid taxon that occurs in non-altered habitats. In contrast to the traditional view of hybridization as deleterious for the conservation of biodiversity, it does not always represent a problem in this regard. Hybridization is a complex evolutionary force that requires case-specific evaluation. Given that biodiversity loss is one of the main contemporary challenges, it is important to consider the creative nature of hybridization, a widespread evolutionary mechanism able to produce novel diversity.
Screen-printed graphene-based electrochemical sensors for a microfluidic device

This work presents a new method for mass fabrication of a new microfluidic device with integrated graphene-based electrochemical electrodes by the screen printing technique for in-channel amperometric detection. Graphene-based working and counter electrodes were fabricated by screen printing graphene paste on a glass substrate, followed by screen printing of a silver/silver chloride (Ag/AgCl) reference electrode. The screen-printed substrate was then bonded to a prefabricated polydimethylsiloxane (PDMS) sheet containing microchannels via oxygen plasma treatment. The developed microfluidic device was then applied for glutathione analysis in pharmaceutical products. The method offers effective and fast glutathione detection with good analytical features including a wide dynamic range (10–500 μM) and a low detection limit (3 μM). In addition, the screen printed graphene electrode (SPGE) exhibits a good stability in a microfluidic flow system and good repeatability for amperometric detection. The method has numerous advantages including low fabrication cost, high sensitivity, high throughput and satisfactory reproducibility. Thus, it holds great promise for advanced analytical applications.
PLC-VIO: Visual–Inertial Odometry Based on Point-Line Constraints

Visual–inertial odometry (VIO) is widely studied and used in autonomous robots. This article proposes a novel tightly coupled monocular VIO system based on point-line constraints (PLC-VIO). In the front end, PLC-VIO presents a line segment extraction and merging algorithm based on the EDLines method and achieves real-time feature tracking based on the geometric constraints between feature points and lines. In the back end, PLC-VIO reconstructs new 3-D landmarks of feature lines through points on the line and optimizes the states by minimizing a cost function that combines the preintegrated inertial measurement unit (IMU) error term together with the point and line reprojection error terms in a sliding window optimization framework. A loop closure module is also integrated, which enables relocalization and drift elimination. The corresponding experimental evaluations are conducted using public datasets to validate the effectiveness and robustness of the proposed system, and the results show that PLC-VIO can achieve good performance when compared with other state-of-the-art systems and, at the same time, with no compromise to real-time performance. Note to Practitioners—Visual–inertial odometry (VIO) can estimate the states of the rigid body (including position, attitude, and velocity) that is widely used in robotic navigation, autonomous driving, virtual reality (VR), and augmented reality (AR). Aiming at the problem of estimating the states of autonomous robots in the GPS-denied environment, this article proposes a novel VIO system based on the point-line constraints (PLC-VIO). PLC-VIO can not only achieve accurate pose estimation for robots due to the introduction of the line features but also make no concession to real-time performance. Furthermore, PLC-VIO can also enrich the texture features of the environment during the 3-D mapping construction. The corresponding experiments are implemented in public datasets to evaluate the effectiveness, efficiency, and robustness of the proposed system. We believe that PLC-VIO can be widely used in robotic navigation and AR/VR fields to provide accurate position and environment information in real time.
Design of Flexible Tactile Array Sensor

Flexible electronics is an imminent revolution in industry, where devices can be developed using sustainable materials and processes. Some of the criteria for sustainability are low cost, low energy consumption, recyclability, and biodegradability. Besides, this technology is bringing into existence electronic gadgets that are light weight, flexible, and conform to the human body. In this paper, we describe a prototype tactile array sensor (TAS) that can enhance the existing prosthetic gadgets. As an example, the sensor can be used to detect an approaching object or surface for a prosthetic foot. Finite element method simulations have been done to show the feasibility of the proposed approach. Flexibility is of importance for prosthetics used by children of growing age for better adaptability, reduced frequency of changes, and creativity in product design [Torres-Jara, Dexterous and Compliant Robotic US 8,662,552 B2,2014]. Once developed, this application for sustainable prosthesis is expected to complement the pioneering work done at the MIT Tata Center toward the development of affordable mobile-enabled diabetic foot analyzer that has enabled regular monitoring of detection of loss of sensation in the feet of diabetic patients avoiding foot ulcers and leg amputation.
Review on Some Features of the Chinese Jujube (Ziziphus jujuba Mill.)

The Chinese jujube (Ziziphus jujuba Mill.), originating from China, with a history of over 4000 years, is one of the major fruit crops cultivated in China and on important areas in Central Asia, India, Iran, the Middle East etc. The high resistances to drought, salty soils and similar climate to that of China recommend this fruit tree as a valuable crop, especially in the context of climate changes and extended desertification. Chinese jujube has a high tolerance to pests and disease, being suitable for organic farming. The lack of divulgative papers on jujube true nutritional, medicinal and economic value, makes it still unknown for the great part of Romanian and European consumers, intensive advertising campaign is needed. The aim of this review is to highlight the requirements of the Chinese jujube (Ziziphus jujuba Mill.) in regards to the soil, water, climate as well as its high nutritional and
End-to-end Relation-Enhanced Learnable Graph Self-attention Network for Knowledge Graphs Embedding

The existing methods ignore the adverse effect of knowledge graph incompleteness on knowledge graph embedding. In addition, the complexity and large-scale of knowledge information hinder knowledge graph embedding performance of the classic graph convolutional network. In this paper, we analyzed the structural characteristics of knowledge graph and the imbalance of knowledge information. Complex knowledge information requires that the model should have better learnability, rather than linearly weighted qualitative constraints, so the method of end-to-end relation-enhanced learnable graph self-attention network for knowledge graphs embedding is proposed. Firstly, we construct the relation-enhanced adjacency matrix to consider the incompleteness of the knowledge graph. Secondly, the graph self-attention network is employed to obtain the global encoding and relevance ranking of entity node information. Thirdly, we propose the concept of convolutional knowledge subgraph, it is constructed according to the entity relevance ranking. Finally, we improve the training effect of the convKB model by changing the construction of negative samples to obtain a better reliability score in the decoder. The experimental results based on the data sets FB15k-237 and WN18RR show that the proposed method facilitates more comprehensive representation of knowledge information than the existing methods, in terms of Hits@10 and MRR.
Adaptive Control Method for Dynamic Synchronization of Wearable Robotic Assistance to Discrete Movements: Validation for Use Case of Lifting Tasks

Dynamic control of robotic exoskeletons is paramount to ensuring safe, synergistic assistive action of functional benefit to users. To date, exoskeleton controllers have excelled in rhythmic and quasi-rhythmic tasks, whereas control methods for assisting discrete movements remain limited by their task-specificity. Inspired by neurophysiological dynamic movement primitives (DMPs), we formulated a novel controller that facilitated a variety of lifting movements using a single adaptive DMP (aDMP), for wearable robotic assistance of discrete movements. For a variety of load lifting tasks, we first benchmarked our method's trajectory prediction accuracy against the state-of-the-art DMP using passively recorded exoskeleton sensor data (offline), followed by a functional validation of online aDMP trajectory estimates. Finally, we assessed the functional effects of aDMP-based exoskeletal assistance on joint kinematics and muscular activity during repetitive lifting. The new aDMP method accurately predicted and smoothly synchronized robotic assistance with variable movement trajectories, resulting in reduced muscular activation of the erector spinae muscles (up to 47.6%) while preserving lower-limb joint kinematics and reducing the extension time by 15.5% compared to unassisted conditions. This method holds promise for use in a wide range of wearable robotic applications, including both clinical rehabilitation and user assistance in activities of daily living and/or manual labor.
Unleashing Coveraged-Based Fuzzing Through Comprehensive, Efficient, and Faithful Exploitable-Bug Exposing

Fuzzing has become an essential means of finding software bugs. Bug finding through fuzzing requires two parts—exploring code paths to reach bugs and exposing bugs when they are reached. Existing fuzzing research has primarily focused on improving code coverage but not on exposing bugs. Sanitizers such as AddressSanitizer (ASAN) and MemorySanitizer (MSAN) have been the dominating tools for exposing bugs. However, sanitizer-based bug exposing has the following limitations. (1) sanitizers are not compatible with each other. (2) sanitizers incur significant runtime overhead. (3) sanitizers may generate false positives, and (4) exposed bugs may not be exploitable. To address these limitations, we propose Expozzer, a fuzzing system that can expose bugs comprehensively, efficiently, and faithfully. The intuition of Expozzer is to detect bugs through divergences in a properly diversified dual-execution environment, which does not require maintaining or checking execution metadata. We design a practical and deterministic dual-execution engine, a co-design for dual-execution and fuzzers, bug-sensitive diversification, comprehensive, and efficient divergence detection to ensure the effectiveness of Expozzer. The results of evaluations show that Expozzer can detect not only CVE-assigned vulnerabilities reliably, but also new vulnerabilities in well-tested real-world programs. Expozzer is 10 times faster than MemorySanitizer and is similar to AddressSanitizer.
Protective Effect of SCUBE1 on Oxidative Stress-induced Apoptosis in Human Ovarian Granulosa Cells

Background: Apoptosis of ovarian granulosa cells (GCs) is a sign of follicular atresia. This study aimed to explore the role and mechanism of signal peptide, CUB domain, epidermal growth factor-like protein1 (SCUBE1) in protecting GCs from apoptosis induced by hydrogen peroxide (H2O2). Results: SCUBE1 was expressed in women of all ages and had the highest expression level in the ovaries in multiple organs and tissues of KM mouse. In vitro cell experiments show that SCUBE1 pretreatment reduced H2O2-induced apoptosis and improved cell viability. SCUBE1 also blocked the production of ROS in cells and improved mitochondrial membrane potential. After SCUBE1 pretreatment, anti-apoptotic protein Bcl-2 expression was upregulated, whereas the expression of the pro-apoptotic proteins Bax, Bax/Bcl-2, Caspase-3, and p53 were downregulated. Analysis of the impact of SCUBE1 (c.1169C >G, p.P390R) mutation from the aspect of mutation pathogenicity; protein stability; and gene haplotype insufficiency, indicated that the p.P390R mutation is significantly pathogenic.Conclusions: This is the first time that the potential role of SCUBE1 in protecting GCs from H2O2-induced damage by blocking the production of ROS, increasing the mitochondrial membrane potential and regulating apoptosis-related proteins, attributing to POI, is studied. SCUBE1 (c.1169C >G, p.P390R) mutation has significant pathogenicity but the specific harm needs to be confirmed by further studies.
Phytochemical Profile, Antioxidant and Anti Proliferative Studies in Different Extracts of Artocarpus kemando Miq. Bark

In this study, the stem bark of Artocarpus kemando was used to find alternative antioxidants from natural sources with fewer side effects. A. kemando wasextracted successively using hexane, chloroform and methanol solvents, and evaluated for antioxidant, cytotoxic, and antiproliferative activities. The extracts were investigated for determination of their total phenolic content (TPC) and total flavonoid content (TFC). Then, the antioxidant activities were evaluated using chemical based assays such as ferric reducing antioxidant power (FRAP), total antioxidant capacity, radical scavenging of 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) and 2,2’-azino-bis (3-ethylbenzothia zoline-6-sulphonic) (ABTS), β-carotene-linoleic acid (BC) assay, oxygen radical absorbance capacity (ORAC), and cell based assay. The cytotoxic study was done using four different cell lines namely human estrogen receptor positive (ER+) breast cancer cell line (MCF7), human ovarian cancer cell line (CAOV-3), human promyelocytic leukemia cell line (HL60), and normal immortalised human ovarian surface epithelial cell line (TI074), and were evaluated using microculture tetrazolium salt (MTT) before morphological change study was done on CAOV-3 cell. In this study, methanol extract displayed the most promising antioxidant activity compared to other extracts when tested with DPPH, FRAP, ABTS, TAOC, BC,ORAC, and cytoprotective assays. The remarkable activity showed by the methanol extract might be due to its high content of phenolic and flavonoid compounds at 855.5 ± 0.01 GAE μg/mL and 145.45 ± 0.06 QAE μg/mL, respectively. Nevertheless, the chloroform extract displayed better scavenging activity compared to other extracts with IC50 value of 618 ± 0.04 μg/mL in DPPH assay. Each extract was analysed using Gas Chromatography Mass Spectrophotometry and the chemical constituents obtained were then analysed. In the cytoprotective activity, the methanol extract showed a comparable cytoprotection with ascorbic acid against the free radicals at the lowest effective concentration (EC50) value of 21.48 μg/mL. However, in the cytotoxicity study, only chloroform extract displayed significant toxicity against the cancer cells with IC50 value of 27.9 ± 0.03, 24.1 ± 0.02 and 9.0 ± 0.04 μg/mL after treatment at 24, 48, and 72 h, respectively. The chloroform extract of A. kemando was found capable of inducing apoptosis as shown with cell membrane blebbing, chromatin condensation and formation of apoptotic bodies. The results obtained from the study showed that A. kemando bark could be a potential antioxidant and antitumor agents particularly on human ovarian cancer cells.