Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Quality Inspection of Bakery Products Based on Shape and Color Information

An automatic intelligent system for the colour and texture inspection of bakery products is proposed. In this system, advance classification technique featuring Support Vector Machine and biologically inspired HMAX based shape descriptor integrated with biologically plausible RGB Opponent-Colour-Channel Descriptor is used to classify bakery products to their respective classes based on the shape and based on their colour referring to different baking durations. The results of this paper are compared with other methods for the automatic bakery products inspection. It is discovered that biologically inspired computer vision models performs accurately and efficiently as compared to the computer vision models which are not biologically plausible, in the bakery products quality inspection. It is also discovered that the One Versus One SVM and Directed Acyclic Graph SVM acquired the maximum accurate classification rate. The proposed method acquired classification accuracy of 95% and 100% for the biscuit shape and biscuit colour recognition, respectively. The proposed method is also consistently stable and invariant. This shows that the biologically inspired computer vision models have the capability to replace existing inspection methods as more reliable and accurate alternative.
Transnational Banking Supervision and Resilience: the SSM Case

In this letter we assess the impact of adopting a transnational supervisor on the resilience of large and complex banks, exploring the establishment of the Single Supervisory Mechanism (SSM) in 2014. Using a differences-in-differences approach, we compare the performance of SSM banks vis-à-vis other banks with a similar size and complexity. Our results suggest that the adoption of a transnational supervisor can improve the resilience of large and complex banks, particularly for those operating in countries with larger banking sectors, higher market concentration and higher supervisory discretion. JEL classification: G20; G21; G28; G32.
Green synthesis of silver nanoparticles using Aloe vera extract and assessing their antimicrobial activity against skin infections

The synthesis of nanomaterials is currently one of the most active in nanoscience branches especially those help to improve the human quality life. Silver ions have the disadvantage of forming complexes and the effect of the ions remained only for short time. This disadvantage have been overcome by the use of silver nanoparticles (AgNPs) which are in inert form and also exhibit antimicrobial function by inducing the production of reactive oxygen species. In fish spas, clients may submerge their hands, feet or whole body in basins with Garra rufa fish, for dead skin removal. Skin infections may result from using these spas. We also focused on identification of some common pathological bacterial and fungal isolates responsible for causing foot cracks. In the present work we have made an attempt to evaluate antibacterial and antifungal activities against various pathogens isolated from fish spa water samples, fish gut and from human foot cracks. The fungal isolates identified were Aspergillus sp. , Penicillium sp. and Trichophyton sp. , and bacterial isolates as Gram positive and Gram-negative organisms. In this work we report the synthesis of silver nanoparticles by green synthesis reduction method of silver nitrate (AgNO3) solution of different concentrations like 1mM,5mM,10mM using Aloevera plant extract of various dilutions like 4:1,3:2,2:3,1:4 respectively. The results show that higher silver nanoparticles were synthesized by using plant extract and water in the ratio of 3:2 and optimal concentration of silver nitrate was found as 10mM. Green synthesized Silver nanoparticles obtained were characterized by UV−visible spectroscopy and Scanning Electron Microscopy (SEM). The zones of inhibition of synthesized silver nanoparticles against the bacterial and fungal pathogens were variable and comparatively the highest was shown by 3:2 diluted plant extract prepared by using 10mM silver nitrate solution of about 24mm and 20mm against Gram positive and Gram negative organisms respectively isolated from fish spa samples. From the present study, it is concluded that green synthesized silver nanoparticles have wide spectrum antibacterial activity in low concentration than antifungal activity and therefore may be used as an alternative approach in medicine and pharmaceutical field in future. Keywords—Green synthesis, silver nanoparticles, fish spa isolates, antimicrobial activity.
Measuring Social Progress

In this chapter, we provide a critical review of the literature on social progress from a prioritarian perspective. We give special attention to the choice of the measure of individual well-being and the aggregation method across individuals in our discussion of various methods that have been proposed in the literature. We present the “growth incidence curve” as a useful device to chart social progress. We illustrate with empirical results for Russia in the period 1995-2005.
Propagation Path Loss Models at 28 GHz Using K-Nearest Neighbor Algorithm

In this paper, we develop and apply K-Nearest Neighbor algorithm to propagation pathloss regression. The path loss models present the dependency of attenuation value on distance using machine learning algorithms based on the experimental data. The algorithm is performed by choosing k nearest points and training dataset to find the optimal k value. The proposed method is applied to impove and adjust pathloss model at 28 GHz in Keangnam area, Hanoi, Vietnam. The experiments in both line-of-sight and non-line-of-sight scenarios used many combinations of transmit and receive antennas at different transmit antenna heights and random locations of receive antenna have been carried out using Wireless Insite Software. The results have been compared with 3GPP and NYU Wireless Path Loss Models in order to verify the performance of the proposed approach.
Practicality and Effectiveness of Student Worksheet Using Inquiry-Based Learning Assisted by Basic Mathematics Skills to Develop Critical Thinking Skills

The purpose of this research is to find out the practicality and effectiveness of student worksheet using IBL assisted by basic mathematics skills to develop critical thinking skills. The method used was quasi-experimental designs with pretest-posttest type. The practicality was obtained through the results of observations of the learning implementation and student responses questionnaire. The effectiveness was obtained through pretest-posttest data analyzed by Ngain and effect size. The results of the observation of the learning implementation and student responses questionnaire were included in very good and very high categories. N-gain test in control and experiment groups was considered in low and medium categories. While, the effect size obtained was in very strong category. In general, the result shows that the student worksheet has met the criteria of practicality and effectiveness.
Fast Packet Processing with eBPF and XDP

Extended Berkeley Packet Filter (eBPF) is an instruction set and an execution environment inside the Linux kernel. It enables modification, interaction, and kernel programmability at runtime. eBPF can be used to program the eXpress Data Path (XDP), a kernel network layer that processes packets closer to the NIC for fast packet processing. Developers can write programs in C or P4 languages and then compile to eBPF instructions, which can be processed by the kernel or by programmable devices (e.g., SmartNICs). Since its introduction in 2014, eBPF has been rapidly adopted by major companies such as Facebook, Cloudflare, and Netronome. Use cases include network monitoring, network traffic manipulation, load balancing, and system profiling. This work aims to present eBPF to an inexpert audience, covering the main theoretical and fundamental aspects of eBPF and XDP, as well as introducing the reader to simple examples to give insight into the general operation and use of both technologies.
A LLEVIATION OF P SYCHOLOGICAL A NXIETY OF C OLLEGE E NGLISH L EARNERS IN W RITING THROUGH B LENDED T EACHING

The psychological anxiety in English writing directly affects the writing performance of English learners. This paper aims to clarify the level of psychological anxiety of English majors in writing, and evaluates the ability of blended teaching to alleviate the anxiety. Therefore, a questionnaire survey was carried out among 124 English majors that had received traditional teaching of English writing for one semester. Their attitudes to English writing and teaching method were analyzed based on the survey results. Then, two classes of English majors were selected for a comparative experiment, with one class receiving the blended teaching of English writing and the other, the traditional teaching method. The anxiety and performance in English writing of both classes were measured before and after the experiment. The results show that most students receiving traditional teaching of English writing had severe psychological anxiety in finishing writing tasks; blended teaching provides English majors a secure and flexible learning environment, which significantly alleviates their psychological anxiety in all dimensions: somatic anxiety, evaluation anxiety, avoidance behavior and self-confidence anxiety. The research results show a new direction for English teaching reform in colleges.
Synthesis and Characterization of Feooh by Electrochemical Deposition Techniques

A very simple method of synthesis of goethite, α-FeOOH, nanowire is reported. To fabricate the nanowires, an anodiezed alumina nanoporous template (AAO) is used. AAO has pores with an average diameter of 60 nm. The synthesis is based, on a self-combustion reaction of the chemical precursor (Fe(NO3)3 satured solution) which occurs inside the nanopores. The geometry of AAO determines the morphology of the nanowires, and the confinement conditions in which occurs the heat treatment determines the composition of the nanostructure. The nanowires are characterized using scanning electron microscopy (SEM), high resolution transmission electron microscopy (HR-TEM) and magnetometry (magnetization vs. applied field (M vs. H)). TEM analysis indicates that nanowires are composed of several α-FeOOH single crystals. The nanowires have a clear magnetic oriented structure. Keywords— Iron oxide, Iron oxyhydroxide, Nanowires, Structural and magnetic properties
Transcriptome Characterization and Polymorphism Detection in Subspecies of Big Sagebrush (<em>Artemisia tridentata</em>)

Transcriptome Sequencing, Characterization, and Polymorphism Detection in Subspecies of Big Sagebrush (Artemisa tridentata) Prabin Bajgain Department of Plant and Wildlife Sciences, BYU Master of Science Big sagebrush (Artemisia tridentata) is one of the ecologically most important shrub species in western North America. The species serves as a major source of food and habitat for the near-threatened sage grouse and various other fauna. Habitat loss due to a combination of disturbances followed by establishment of invasive plant species is considered as a serious threat to sustainability of the big sagebrush ecosystem. Because of its importance, restoration of this species is very crucial to those dependent on big sagebrush community. However, restoration of big sagebrush carried out by using diverse seed source can lead to imbalance and degradation in the native ecosystem. Therefore, restoration works aided by understanding of adaptive traits of big sagebrush using molecular markers will aid successful restoration. The major objective of this research was to create a substantial resource of nuclear sequence data and identify markers that can be used in future studies in big sagebrush. We report the development and annotation of the first expressed sequence tag (EST) collection for big sagebrush based on 454 sequencing of leaf tissue. Expressed genes of subspecies tridentata and vaseyana were sequenced using the 454 GS-FLX titanium platform, which produced 823,392 reads with an average read length of 404 bp and 702,001 reads with an average read length of 333 bp for sspp. tridentata and vaseyana, respectively. Assembly of the reads resulted in 212,102 consensus sequences in ssp. tridentata and 199,439 in ssp. vaseyana. A combined assembly of both subspecies sequences generated 29,541 contigs with an average length of 796 bp and 275,866 singletons with an average length of 370 bp. A BLASTx search against the non-redundant (NR) protein database using the contigs obtained from a combined assembly resulted in 21,436 sequences with significant blast alignments (≤ 1e -15 ). Gene Ontology (GO) IDs were assigned to 18,397 sequences. A total of 20,952 SNPs were detected between the two subspecies and 1,182 SNPs were confirmed in tetraploid ssp. wyomingensis. In addition, 1,003 and 507 SSRs were detected in ssp. tridentata contigs and ssp. vaseyana contigs, respectively.
X-ray Structure of the Ca 2 (cid:1) -binding Interaction Domain of C1s INSIGHTS INTO THE ASSEMBLY OF THE C1 COMPLEX OF COMPLEMENT*

C1, the complex that triggers the classical pathway of complement, is assembled from two modular proteases C1r and C1s and a recognition protein C1q. The N-ter-minal CUB1-EGF segments of C1r and C1s are key elements of the C1 architecture, because they mediate both Ca 2 (cid:1) -dependent C1r-C1s association and interaction with C1q. The crystal structure of the interaction domain of C1s has been solved and refined to 1.5 Å resolution. The structure reveals a head-to-tail homodimer involving interactions between the CUB1 module of one monomer and the epidermal growth factor (EGF) module of its counterpart. A Ca 2 (cid:1) ion is bound to each EGF module and stabilizes both the intra- and inter-mono-mer interfaces. Unexpectedly, a second Ca 2 (cid:1) ion is bound to the distal end of each CUB1 module, through six ligands contributed by Glu 45 , Asp 53 , Asp 98 , and two water molecules. These acidic residues and Tyr 17 are conserved in approximately two-thirds of the CUB repertoire and define a novel, Ca 2 (cid:1) -binding CUB module subset. The C1s structure was used to build a model of the C1r-C1s CUB1-EGF heterodimer,
Chatbots in Stressful Customer Service Situations – The Impact of Stress on the Intention to Use Conversational Chatbots

Chatbots enhance the efficiency of several customer touchpoints in terms of the customer experience and associated costs. However, what happens in stressful situations? Do customers still use chatbots in such cases? Research on the usage of chatbots has focused on technological aspects. By contrast, this paper contributes to a research stream that analyzes the acceptance of chatbots. This research reflects stress as an influencing factor in the technology acceptance model (TAM) and examines the moderating role of stress on usefulness and their relationship on the intention to use chatbots. In an experimental design a first group of subjects talked to a call center agent. A second group was pretended to talk to a chatbot. Actually, this group also talked to an agent, whose voice was manipulated by a voice changer. The empirical results demonstrate that the impact of stress needs to be considered when employing chatbots for daily interactions with customers.
Human Activity Recognition in a Car with Embedded Devices

Detection and prediction of drowsiness is key for the implementation of intelligent vehicles aimed to prevent highway crashes. There are several approaches for such solution. In thispaper the computer vision approach will be analysed, where embedded devices (e.g.videocameras) are used along with machine learning and pattern recognition techniques for implementing suitable solutions for detecting driver fatigue. Most of the research in computer vision systems focused on the analysis of blinks, this is a notable solution when it is combined with additional patterns like yawing or head motion for the recognition of drowsiness. The first step in this approach is the face recognition, where AdaBoost algorithm shows accurate results for the feature extraction, whereas regarding the detection of drowsiness the data-driven classifiers such as Support Vector Machine (SVM) yields remarkable results. One underlying component for implementing a computer vision technology for detection of drowsiness is a database of spontaneous images from the Facial Action Coding System (FACS), where the classifier can be trained accordingly. This paper introduces a straightforward prototype for detection of drowsiness, where the Viola-Jones method is used for face recognition and cascade classifier is used for the detection of a contiguous sequence of eyes closed, which a reconsidered as drowsiness.
A study of White-tailed Eagle Haliaeetus albicilla movements and mortality at a wind farm in Norway

The wind power plant on the island of Smøla, western Norway, is currently the largest in Norway; it has 68 turbines with nominal capacity of 2–2.3 MW each, hub height of 70 m and rotor blade radius of 38–41 m,. It was constructed in two phases between 2001 and 2005. Approximately 60 White-tailed Eagle Haliaeetus albicilla territories are found in the whole Smøla archipelago. Before construction there were 13 Eagle pairs holding territories in the wind farm area and within 500 m of it, whereas in 2009 this was reduced to only five. Since 1996, baseline data on the White-tailed Eagle population size and reproduction have been collected.
Rethinking local and global feature representation for semantic segmentation

Although fully convolution networks (FCN) have dominated semantic segmentation since the birth of [24], they are inherently limited in capturing long-range structured relationship with the layers of local kernels. While recent Transformer-based models have proven extremely successful in computer vision tasks by capturing global representation, they would deteriorate semantic segmentation by over-smoothing the regions contain ﬁne details ( e.g. , boundaries and small objects). To this end, we propose a Dual-Stream Convolution-Transformer segmentation framework, called DSCT, by taking advantage of both the convolution and Transformer to learn a rich feature representation for semantic segmentation. Speciﬁcally, DSCT extracts high resolution local feature information from convolution layers and global feature representation across the Transformer layers. Moreover, a feature fusion module is plugged to exchange information between spatial stream and context stream at each stage. With the local and global context modeled explicitly in every layer, the two streams can be combined with a simple decoder to provide a powerful segmentation model. Extensive experiments show that our model builds a new state of the art on Cityscapes dataset (83.31% mIoU) with only 80K training iterations and appealing performance (49.27% mIoU) on ADE20K, outperforming most of the alternatives with a new perspective.
REVIEW OF ROUTING PROTOCOL BASED ON TRUST IN MANET

- The ad-hoc network is required when two or more wireless mobile nodes wish to transfer packet/data to other nodes. Dynamic source routing protocol (DSR) is widely used in an ad-hoc network routing through DSR is also suffered from attacks through malicious nodes. This is very difficult to identify these venomous nodes, adding trust is good in the routing process helps. Some papers on the same topic have been discussed here.
Corporate Financial Policies: A International Survey

Earlier questionnaire-based studies of corporate fi nance have concentrated mainly on either the American or the European market, and ref err d to only a few aspects of corporate financial decisions. This study, in contr ast, is based on five countries-the U.S., the U.K., Germany, Canada and Japan, and deal s with a broad range of corporate financial issues. We also compare some of the survey results to those based on a sample of S&P500 companies. We found that, as the prevailing theory states, the investment policy is regarded as the most important policy, while the dividend policy is the least important. We also found that the impo rtance of the financing and dividend policies increased with the financial leve rage. The most frequently used technique for investment appraisal is the IRR, foll owed by the NPV. We also found that the use of risk measurement techniques was hig hest in Japan and lowest in the U.S. This finding may suggest a greater aversion to risk among Japanese managers than among their U.S. counterparts. Japanese compan ies have the highest financial leverage while U.S. companies have the lowest. 68% of the questionnaire sampled companies pay dividends with a mean payout ratio of 37.32%, while 81.3% of the S&P500 sample pays dividends with a mean payout rat io of 34%. Japan was also found to be unique in its dividend polices preferen ces. Almost all of the Japanese sampled companies (95.2%) pay a fixed sum per share , compared to only 26.15% for the other countries in the sample. JEL Classifications: G3, G32, G35
CE_A_179053 7..20

Noritaka Takatsu 1 Takashi Hisabe 1 Daijiro Higashi 2 Toshiharu Ueki 1 Toshiyuki Matsui 1 1Department Of Gastroenterology, Fukuoka University Chikushi Hospital, Fukuoka, Japan; 2Department Of Surgery, Fukuoka University Chikushi Hospital, Fukuoka, Japan Introduction: Selective blockade of the integrins and mucosal adhesion molecules is a promising therapeutic strategy for ulcerative colitis (UC). Vedolizumab (VDZ), a humanized IgG1 monoclonal antibody against α4β7 integrin, selectively blocks the trafficking of the leukocytes into the gastrointestinal tract through its binding with the α4β7 integrin. Aim: In this review, we provide an overview of the unique mechanism of VDZ, along with its efficacy, safety, and pharmacokinetic and pharmacodynamic data obtained from clinical trials, observational studies, and meta-analyses. Evidence Review: A positive exposure–efficacy relationship with regard to clinical remission and clinical response was apparent in VDZ induction therapy. No drug-specific safety signals are currently available. Place in Therapy: VDZ has been shown to be effective as firstor second-line induction and maintenance therapy in UC. Conclusion: VDZ is a safe and effective treatment option for patients with UC. Prolonged VDZ induction therapy may contribute to improved outcomes in patients with UC, particularly those previously treated with tumor necrosis factor-α. Prospective head-to-head study of VDZ and other biologics would alter the positioning of VDZ much more clearly.
Enhancers Bind B-Cell-Specific Factors

Two highly homologous enhancers associated with the two murine immunoglobulin A constant-region clusters were recently identified. In order to better understand the molecular basis for the developmental stageand cell-type-restricted expression of X genes, we have undertaken an analysis of the putative regulatory domains of these enhancers. By using a combination of DNase I footprinting, electrophoretic mobility shift assay, and site-specific mutations, four candidate protein binding sites have been identified at analogous positions in both enhancers. A mutation of any of these sites decreases enhancer activity. Two of the sites, XA and XB, are essential for enhancer function, and both of these sites appear to bind both B-cell-specific and general factors. Nevertheless, isolated XA and XB sites show no evidence of inherent transactivating potential, alone or together, even when present in up to three copies. We suggest that the generation of transactivating signals from these enhancers may require the complex interaction of multiple B-cell-specific and nonspecific DNAbinding factors.