Miracle-dz/UniFAR-FTUs huggingface dataset:
Storage Optimization using Adaptive Thresholding Motion Detection

Data storage is always an issue, especially for video data from CCTV cameras that require huge amounts of storage. Moreover, monitoring past events is a laborious task. This paper proposes a motion detection method that requires fewer calculations and reduces the required data storage up to 70%, as it stores only the informative frames, enabling the security personnel to retrieve the required information more quickly. The proposed method utilized a histogram-based adaptive threshold for motion detection, and therefore it can work in variable luminance conditions. The proposed method can be applied to streamed frames of any CCTV camera to efficiently store and retrieve informative frames. Keywords-storage optimization; adaptive threshold; motion detection; video mining
Review article: State-of-the-art trajectory tracking of autonomous vehicles

Abstract. Air pollution, energy consumption, and human safety issues have aroused people's concern around the world. This phenomenon could be significantly alleviated with the development of automatic driving techniques, artificial intelligence, and computer science. Autonomous vehicles can be generally modularized as environment perception, path planning, and trajectory tracking. Trajectory tracking is a fundamental part of autonomous vehicles which controls the autonomous vehicles effectively and stably to track the reference trajectory that is predetermined by the path planning module. In this paper, a review of the state-of-the-art trajectory tracking of autonomous vehicles is presented. Both the trajectory tracking methods and the most commonly used trajectory tracking controllers of autonomous vehicles, besides state-of-art research studies of these controllers, are described.
Distributed Nash equilibrium seeking of aggregative games under networked attacks

This paper investigates the distributed Nash equilibrium seeking problem of aggregative games in the presence of networked attacks. A switched algorithm with the fast estimate dynamics is proposed to explore the effect of attacks on seeking a Nash equilibrium. To guarantee the convergence of this algorithm, such a switched strategy is modeled as a hybrid system by using the hybrid automaton and time‐ratio conditions. Then, by constructing an appropriate Lyapunov function, we can prove that the hybrid dynamical system is exponentially stable and the Nash equilibrium can be achieved exponentially though the communication network is affected by attacks. Finally, a Nash–Cournot game is provided to verify the main results.
A novel circularly polarized slotted substrate integrated waveguide antenna array for satellite applications

Amgad A. Salama, Electrical Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, Egypt. Email: am_adeli@ece.concordia. ca Abstract In this article, three novel slotted substrate integratedwaveguide (SIW) antenna elements are demonstrated with different radiator configurations, namely, two arms Archimedean antenna, single‐arm spiral antenna (monofilar), and four concentric circular loops antenna. Additionally, their near, as well as far‐field characteristics, have been investigated. The two arms Archimedean spiral antenna has a superior radiation characteristic of 18% return loss bandwidth (RLBW), 12% boresight axial ratio bandwidth (ARBW), and five dBi directivity. Furthermore, a 1 � 10 slotted SIW travelling wave antenna array has been designed, fabricated, and measured. The performance of the proposed antenna array versus the last reported antenna was evaluated and the proposed antenna array performance is superior to that of the others. Moreover, the measurements of the proposed array have a good agreement with the simulation results in which, 35%, 13% RLBW, and ARBW, respectively, have been achieved. The directivity of the proposed antenna array is 14 dBi.
What is The Effect of Sleeve Gastrectomy in Patients with a BMI ≥ 50 kg/m2?

Background: To investigate the effect of Sleeve Gastrectomy (SG) in patient with a Body Mass Index (BMI)≥50 kg/m² groups on weight loss and comorbidities as the first and alone option. Methods: The prospectively maintained data obtained from patients with a BMI ≥ 50 who underwent SG between February, 2016 - February, 2020 were evaluated. Results: 138 patient with a BMI≥50 kg/m² underwent surgery. Average BMI: 56.36±7.661, age 37.41±12.33. Forty eight patients underwent cholecystectomy and/or hiatal hernia repair (HHR), as well. The percentage of excess weight loss (%EWL) values of patients in months 3, 6, 12 and 24 were 36.70%, 54.34%, 67.58%, 72.45%, 74.14% and the percentage of total weight loss (TWL%) values were 20.17%, 29.59%, 36.93%, 39.62%, 40.65%, respectively. The mean BMI values in month 0 and in the 3rd, 6th, 12th, 18th, 24th months were 56.36, 45.10, 39.76, 35.48, 33.96 and 33.42 respectively. The values measured in the month 0 and in the 3rd, 6th, 12th, 18th, 24th months were significantly different for EWL%, TWL% and BMI variables (p<0.001), but EWL% (p = 0.527), TWL% (p = 0.396) and BMI (p=0.657) were not found significantly different between the 18th and 24th months. When EWL% was accepted as ≥50, the success rate was found to be 93.55%(n=93) and 92%(n=50) in months 12 and 24, respectively. Conclusion: SG appears to be an effective and safe treatment method as the first option for weight loss and for treatment of concomitant disorders in patient with a BMI ≥ 50 kg/m² groups. Further long-term studies are needed to confirm these results.
How Temporal Order of Inconsistent CSR Information Affects Consumer Perceptions?

What happens first between a corporate social responsibility (CSR) communication and a crisis can result in different levels of perceived cognitive dissonance and corporate hypocrisy depending on whether there is information inconsistency between the CSR communication and the crisis. This paper presents the findings from an experimental study and an online survey conducted and administered to investigate the contingency influence on consumer perceptions in response to inconsistent information. The results indicate that consumers experience greater cognitive dissonance and perceive more corporate hypocrisy when they are exposed, first, to a CSR initiative and then to a crisis, than when the order is reversed, provided that the CSR initiative and the crisis are congruent with the same social issue. However, there are no significant differences when the CSR initiative is incongruent with the crisis. Further, the findings of the study suggest that consumer cognitive dissonance not only directly influences the perceived corporate reputation, but also indirectly affects the perceived corporate reputation through a mediating effect of perceived corporate hypocrisy. The theoretical contribution of this study lies in providing a better understanding of consumer perceptions (including cognitive dissonance, perceived corporate hypocrisy and corporate reputation) in response to inconsistent CSR information. Meanwhile, the managerial contribution of this study stands by providing insights into the use of CSR communication strategies.
Genes of SARS-CoV-2 and emerging variants

The pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is distinctly different from outbreaks caused by other coronaviruses: SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). The differences in the rapid transmission and severity of human coronaviruses are due to the genetic composition of the virus. SARS-CoV-2 contains genes encoding non-structural proteins (NSPs), structural proteins, and accessory proteins. The NSPs are mainly involved in replication of the virus within the host and inhibition of the host defence system. Structural proteins are involved in viral entry and attachment to host cells, preservation of the core virion and elicit the majority of the immune response. The functions of the accessory proteins are largely unknown. Most focus has been given to structural proteins, especially the spike protein as the strongest vaccine candidate. However, the recent emergence of spike variants and their ability to rapidly transmit and escape neutralisation by vaccine-induced antibodies has threatened the global community. Meanwhile, recent studies of accessory proteins reveal their importance in viral pathogenesis. Hence, proper understanding of the functions of all unknown viral proteins is crucial to devise alternate antiviral strategies.
A Wide-Load-Range and Compact MHz Wireless Power Transfer System Based on Novel Reactance Compression Design and Edge Inductor

In megahertz (MHz) wireless power transfer (WPT) systems, a varying reflected reactance due to a changing final load deteriorates the overall system performance, such as efficiency and output voltage stability. This article aims to achieve a compact and robust MHz WPT system working over a wide range of load. A novel concept of reactance compression design is proposed to compress the variation of the reflected reactance through positioning of a “reactance window. ” Efficient receiving-side parameter design procedures are then developed to best compress the reactance variation and satisfy maximum output power requirement in a wide load range but without adding any other hardware. This makes it possible to directly apply the existing voltage-source design using a modified Class E power amplifier (PA) and current-source design using an LCC transformation network. An edge inductor also becomes worthy to replace the bulky air-core infinite inductor required by the modified Class E PA, thereby further improving circuit compactness. Finally, the receiving-side design concept and the edge inductor are experimentally implemented to verify their performance over a 5–50-$\Omega$ load and with the maximum final output power of 20 W. The results well validate the improved reactance compression, output voltage stability, efficiency, and harmonic distortions over the wide load range.
Automatic segmentation of retinal edema in optical coherence tomography based on deep neural networks

A multi-task network framework based on convolutional neural networks improvements is proposed for automatic segmentation and classification in three different lesion areas of retinal OCT images. We propose a dilated convolutions module to capture fine-grained semantic information and introduce dense skip connections to integrate features of multiple scales and different semantic levels. Furthermore, we use a joint loss function that balances the relative size of the data labels and the improved generalization of the network. The validity and reliability of our proposed method are trained and verified on OCT datasets. Extensive experimental results demonstrate that the average Dice coefficient of the three lesion areas is 2.61% higher than the most commonly used U-net model in the field of medical image segmentation and reaches 0.81501.
A Regional Network Topology Construction Algorithm Based On Sampling Measurement

Network topology construction is one of the basic means to study the target network. Whether it is the discovery of vital nodes, IP location or network characteristics mining, a complete and accurate network topology is needed. In this paper, a regional network topology construction algorithm based on sampling measurement is proposed to solve the problem of high time cost and resource waste of existing algorithms. Firstly, multiple vantage points located inside and outside the target area are selected to form a probing set. Then the IPes of the target area is extracted based on sampling to form the target IP set. Finally, the probing set is used to probe the target IP set periodically. The network topology of the target region was constructed based on the results of a 40-day internet measurement and compared with the existing database. The experimental results show that the coverage rate of routing nodes in the target area is improved by more than 90% compared with the measured data provided by CAIDA (Center for Applied Internet Data Analysis) and by more than 10% compared with the measured data provided by IPIP.
Studies towards Bioinspired Synthesis of Hetidine‐Type C20‐Diterpenoid Alkaloids

Details of a biogenetically inspired strategy that led to the synthesis of the hetidine-type C20-diterpenoid alkaloid skeleton are reported in this paper. Key steps of our synthesis include a C—H oxidation to convert the atisine-type core to the ajaconine skeleton, as well as an aza-Prins cyclization that establishes the hetidine alkaloid skeleton. An unexpected heptacyclic framework bearing a unique tricyclo[3.3. 1.02,7]nonane moiety has been obtained during our studies, which may represent a new type of C20-diterpenoid alkaloids yet to be discovered.
A novel aggregation method for generating Pythagorean fuzzy numbers in multiple criteria group decision making: An application to materials selection

Abstract Pythagorean Fuzzy Numbers are more capable of modeling uncertainties in real-life decision-making situations than Intuitionistic Fuzzy Numbers. Majority of research in Pythagorean Fuzzy Numbers, used in Multiple Criteria Decision-Making problems, has focused on developing operators and decision-making frameworks rather than the methodologies of generating the Pythagorean Fuzzy Numbers. Hence, this study aims at developing a novel aggregation method to generate Pythagorean Fuzzy Numbers from decision makers’ crisp data for Multiple Criteria Decision-Making problems. The aggregation method differs from other methods, used in generating Intuitionistic Fuzzy Numbers, by its ability to measure the uncertainty degrees in decision makers’ information and using them to generate Pythagorean Fuzzy Numbers. Initially, decision makers evaluate alternatives based on preset criteria using crisp decisions (i.e., crisp numbers) which are assigned by decision makers. A normalization method is used to normalize the given numbers from zero to one. Linear transformation is then used to identify the satisfactory and dissatisfactory elements of all normalized values. In the aggregation stage, the Sugeno fuzzy measure and Shapley value are used to fairly distribute the decision makers’ weights into the Pythagorean fuzzy numbers. Additionally, new functions to calculate uncertainty from decision-makers evaluations are developed using Takagai-Sugeno approach. An illustrative example in engineering materials selection application is presented to demonstrate the efficiency and applicability of the proposed methodology in real-life scenarios. Comparative analysis is performed to compare the results and performance of the introduced approach to other aggregation techniques.
Research on Measurement and Use of Customer Value and Loyalty

This paper aims at determining how customer value and loyalty are measured. The paper relied on previous literature to attain the perceived results. From past literature, the measurement of customer loyalty and value is subjective because of human attributes such as attitude and behavior. It is therefore complicated in doing a survey that will be conclusive. However, from the study, it was deduced that customer loyalty can be determined if a company understands past loyalty experience that will be used to predict future customer loyalty. Customer value on the other hand can be measured based on the cost associated with acquiring a customer and the customer turnover in a given
Optimal radiation pattern synthesis of mutually coupled antenna array using an efficient compensation method

An efficient compensation method is proposed for the reduction of mutual coupling among the elements of an antenna array using the optimum current amplitude excitation weights. The performance of an antenna array degrades heavily due to mutual coupling. The mutual coupling effect can neither be eliminated nor be ignored in the context of the antenna array design. Several analytical and numerical techniques have been proposed in the past few decades for the calculation and compensation of mutual coupling effect. Here, the mutual coupling is compensated by reducing the driving impedance of each identical array element in the array by adopting grey wolf optimization and moth flame optimization algorithms, respectively. The sum of the driving impedances of each element of the antenna array is reduced efficiently by adjusting the feed current amplitudes of all the individual array elements. Compared to the existing known methods, the proposed method is less complex, cost ‐ effective and easy to implement for commercial and in-dustrial applications to achieve better performance.
ASSESSMENT OF THE NEAR SURFACE SENSITIVITY OF THE FULL SPECTRUM INITATION (FSI)-WFM-DOAS RETRIEVAL OF CARBON DIOXIDE COLUMN

Atmospheric CO2 concentrations, have been successfully retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using a new retrieval algorithm called Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS). Initial results from the algorithm are promising with visible structure evident within the retrieved spatial distributions. There is a good correlation between the ∆CO2 anomaly of the in-situ ground-based measurements and the equivalent anomaly of the SCIAMACHY retrieved columns. All measurements are for the year 2003.
Efficient Solar Cells via Green, and Sustainable Coating Technique

Metal Oxide Semiconductor, MOS, solar cells of low cost and stable unit proficiency was established. Solar cells with sol gel SiO2 deposited by spin coating technique were discussed. The sol gel layer is prepared via greener methodology at optimum economic impact as promising and sustainable source of energy. The I–V characteristic of the sample solar cell at different time was investigated. The Photovoltaic performance and optical properties of the resulted cells were recorded and found confident. The green and sustainable context of the method was pronounced and pointed out. These techniques were found useful and inspiring for large scale manufacturing. The procedure, that obeying the commands of sustainability and cope with the principles of green chemistry, was found as ecofriendly-, productive-, applicable-, and sustainable-technique. "
Comparative Study on “Sentence Rewriting for Semantic Parsing” and “Graph-Based Translation Via Graph Segmentation”

Machine translation is universally discussed by people worldwide nowadays along with the developments of computer science and artificial intelligence, however, sentence parsing and the translation errors between original language to target language are still difficult problems during the translation. This essay illustrates the main points of the two articles both of which concentrate on the methods to enhance the precision rate and accuracy of semantic parsing and translation, and makes a comparison between them. Even though these articles can increase the accuracy of translation, some of the backwards still exist and they are proposed to make the articles improved with their objectivity and precision.
Infrastructure investments, regional trade agreements and agricultural market integration in Mozambique

Integration of agricultural markets has been a topic of great interest in Mozambique. Numerous studies have been conducted to assess both domestic and regional integration of maize markets in the country, though with some contradictory results. In this study domestic and regional market integration in Mozambique is assessed, focusing on maize markets as the main crop in the country. In contrast to previous work, this study takes into account new investments in infrastructure as well as changes in regional trade policies, using vector autoregressive (VAR) and vector error correction (VEC) models. The main findings suggest that maize markets in Mozambique are not efficiently integrated. This is particularly true between the deficit markets in the South and the surplus markets in the Centre and North of the country. At the regional level, market integration is also inefficient in many cases. Nonetheless, investments in infrastructure, such as the Zambezi River Bridge, linking the north to the rest of the country, as well as changes in trade policies over the years are shown to be significantly impacting to maize price changes, particularly in the north. The overall results suggest there is room for improvements in the maize value chain performance, particularly there is scope for farmers to engage more in trade and for reducing food loss. Action may include investments on training programs and incentives to shift farmers from the current subsistence farming to a more commercial farming system approach.
Making BBS-Net More Efficiency for RGB-D Salient Object Detection

BBS-Net is a novel bifurcated backbone strategy network based on cascaded refinement, which achieves the most advanced performance in RGB-D salient object detection models. However, the performance of the model in multi-scale feature extraction and depth feature enhancement is not strong enough, and the generated saliency maps contain a lot of background distraction and blurred edges. In this paper, based on BBS-Net framework, we adopt more effective feature extraction network and depth feature enhancement module. Specifically, 1) Use the Res2Net-50 structure that constructs hierarchical residual-like connections within a single residual block as a feature extraction network; 2) Use ECA module as channel attention to extract depth information and enhance cross-modal compatibility. The comprehensive experiments of our method on 6 datasets show that it outperforms the original BBS-Net and 7 current state-of-the-art methods in 4 evaluation metrics.
Microbiota in Uterine Cavity of Unexplained Recurrent Spontaneous Abortion (URSA) Patients in Early Pregnancy

Purpose The purpose of this study is to determine the uterine cavity microbial composition in unexplained recurrent spontaneous abortion (URSA) patients and to understand the correlation between URSA and uterine cavity microbiota. Methods Using the double-lumen embryo transfer tubes to collect uterine cavity fluid samples from pregnant women in their first trimester. 16S rRNA sequencing was conducted to analysis the composition and abundance of the microbiota in samples. Results We enrolled 10 URSA cases and 28 induced miscarriage cases in their early pregnancy. Microbial communities were detected in all samples of URSA group (100%, n = 10) vs. none of control group (0%, n=28). Two most dominant microbes are Lactobacillus and Curvibacter. Conclusion This study showed Lactobacillus and Curvibacter dominated colonizing in uterine cavity of URSA patients during early pregnancy and associated with URSA. Changes of dominant microbiota will lead to bad pregnancy outcome.
Occupational risk factors and preventative practice reflections during COVID pandemic

ABSTRACT Occupational therapy within community mental health teams (CMHT) has a unique potential for upstream preventative practice [Letts, L. (2004). In B. C. Crepeau E. & B. B. Schell (Eds.) Health promotion in Willard & Spackman’s occupational therapy (18th edn., pp. 160–177). Lippincott Williams & Wilkins]. Practicing preventatively, was an opportunity posed by the COVID pandemic, we saw an opportunity to realise our professional potential here and preventative practice as a professional strength. However, working in a fast paced, medically driven environment, has historically been a barrier to authentically accessing the service user [Letts, L. (2004). In B. C. Crepeau E. & B. B. Schell (Eds.) Health promotion in Willard & Spackman’s occupational therapy (18th edn., pp. 160–177). Lippincott Williams & Wilkins]. Further, in the light of the pandemic, we had lost our usual ways of working. In place of face-to-face contact, we were left with the medium of the telephone. We decided to become our own occupational therapists, to reconsider our professional roles by reflecting on the body of knowledge which informs our clinical reasoning, in an ethically driven light, to include the values of occupation, sustainability and client centred practice.