Miracle-dz/UniFAR-FTUs huggingface dataset:
Fault-Tolerant and Adaptive Visual Servoing for Capturing Moving Objects

This article focuses on an adaptive and fault-tolerant vision-guided robotic system that enables to choose the most appropriate control action if partial or complete failure of the vision system in the short term occurs. Moreover, the autonomous robotic system takes physical and operational constraints into account to perform the demands of a specific visual servoing task in a way to minimize a cost function. A hierarchical control architecture is developed based on interwoven integration of a variant of the iterative closest point image registration, a constrained noise-adaptive Kalman filter, a fault detection logic and recovery system, together with a constrained optimal path planner. The dynamic estimator estimates unknown states and uncertain parameters required for motion prediction while imposing a set of inequality constraints for consistency of the estimation process and adjusting adaptively the Kalman filter parameters in the face of unexpected vision errors. It is followed by the implementation of a fault recovery strategy based on a fault detection logic that monitors the health of the visual feedback using the metric fit error of the image registration. Subsequently, the estimated/predicted pose and parameters are passed to an optimal path planner in order to bring the robot end-effector to the grasping point of a moving target as quickly as possible subject to multiple constraints, such as acceleration limit, smooth capture, and line-of-sight angle of the target. Experimental results demonstrated such a visual servoing system succeeded to capture a free-floating object despite the complete failure of the vision system due to occlusion in the last 10 s prior to approach and capture operation.
Mobile Memory Management System Based on User’s Application Usage Patterns

: Currently, the number of functions to improve user convenience in smartphone applications is increasing. In addition, more mobile applications are being loaded into mobile operating system memory for faster launches, thus increasing the memory requirements for smartphones. The memory used by applications in mobile operating systems is managed using software; allocated memory is freed up by either considering the usage state of the application or terminating the least recently used (LRU) application. As LRU-based memory management schemes do not consider the application launch frequency in a low memory situation, currently used mobile operating systems can lead to the termination of a frequently executed application, thereby increasing its relaunch time. This study proposes a memory management system that can efficiently utilize the main memory space by analyzing the application usage information. The proposed system reduces the application launch time by leaving the most frequently used or likely to be run applications in the main memory for as long as possible. The performance evaluation conducted utilizing actual smartphone usage records showed that the proposed memory management system increases the number of times the applications resume from the main memory compared with the conventional memory management system, and that the average application execution time is reduced by approximately 17%.
Physics Teachers’ Perspectives on The Availability of The Integration of E-Formative Assessment in E-Learning based on Website (EFA in ELboW) during Covid-19 Pandemic

In the field of education, the COVID-19 demands changes in the learning process. It is important to know the changes that have occurred so that we can take some actions to face the changes that occurred, and help teachers prepare for the changes that occur in the learning process, especially in the physics learning process. This study aims to determine changes in the teaching, assessing, and using validated instrument aspect due to the COVID-19 pandemic. Also, gathered teacher perspectives on the availability of EFormative Assessment in Web-based E-Learning (EFA on ElboW) integration. The sampling technique used in this study was quota sampling. Data were collected from 33 physics teachers from various districts in Indonesia and analyzed using quantitative descriptive. As a result, the significant value of paired sample test for teaching, assessing and using validated instrument aspect before and during COVID-19 successively are 0.000, 0.003, and 0.183. Then all respondents agreed that the Integration of E-Formative Assessment in Website-Based E-Learning (EFA in ELboW) was needed by physics teachers during the COVID-19 Pandemic. It can be concluded that there are changes in the teaching and assessing aspect. Also, the Integration of E-Formative Assessment in Website-Based E-Learning (EFA in ELboW) was needed by physics teachers to prepare them to deal with the changes that occur in learning due to the COVID-19 Pandemic. Of course, this article has great implication for teachers and researchers.
Nine Year Basic Education Policy Interventions and Students’ Enrolments Rates at Lower Secondary Level: A Lesson from Rwanda

This study examined the relationship between Nine Year Basic Education (9YBE) Policy interventions and students’ enrolment rates at Lower Secondary in the Republic of Rwanda. The study analyzed views of 218 teachers in 29 day-lower secondary schools in Gisagara District. Questionnaire and focus group discussions were research instruments. Data were analyzed using frequency tables, percentages, and chi-square test at the 0.05 significance level. The respondents (98.46 %) rated the 9YBE policy interventions to have an association with students’ enrolments rate due to the combination of interventions. Chi-square test results showed that each 9YBE policy intervention scored a p-value less than 0.05. This infers that the 9YBE policy interventions had a statistically significant association with students’ enrolment rates by addressing child, household, and school-based problems simultaneously. Moreover, a supporting system for overage children and those who progress without prerequisite competencies was suggested as a policy option for high enrolment. Abel Dufitumukiza *
Impact of different quantity of Zinc oxide nanoparticles on growth and hematology of Mrigal Cirrhinus mrigala

Zinc is essential for aquatic biota including fishes at a lower concentration, but when it reaches higher concentration it becomes toxic. The objectives of the present work were related to the impact of different quantities of zinc oxide nanoparticles on the growth and hematology of Mrigal Cirrhinus mrigala. The zinc oxide nanoparticles were synthesized by chemical precipitation method and characterized using by UV-VIS, SEM, EDAX, FTIR and XRD. Different quantity of zinc oxide nanoparticles such as 0, 5,10,15,20 and 25mg/100g were prepared by using a fish meal, groundnut oil cake, wheat flour, and tapioca flour. Feed utilization and hematological parameters of Mrigal were estimated after 21 days of feeding. UV-visible adsorption spectra show that the peak absorbance of ZnO nanoparticles was observed 500 nm. SEM shows that nanoparticles formed are clustered because of the adhesive nature of flower-shaped appearance. EDAX shows that the zinc oxide nanoparticles and the peaks are located between 1.0Kev and 8.5Kev. The FTIR spectrum of zinc oxide nanoparticles was analyzed in the range of 400-4000cm-1 and spectral bands were observed. The XRD results were viewed as the crystalline nature and average size of zinc oxide nanoparticles. Survival rate indicated that all Mrigal were healthy during the period of 21 days except in feed II,IV, and V. The feed utilization and growth parameters are higher in feed IV. Hematological parameters such as hemoglobin, RBC, Hematocrit, MCV, MCH, MCHC of Mrigal progressively increased and WBC and platelets decreased with increase in the quantity of Zinc Oxide nanoparticles.
Patterns of Genetic Structure and Evidence of Gene Flow between Arabian Peninsula and European Populations

Patterns of Genetic Structure and Evidence of Gene Flow between Arabian Peninsula and European Populations. Biomed Abstract The genetic interaction was observed between Asian and European populations. However, genetic admixtures among Eurasians, particularly between East Asians and North western Europeans have been reported but population admixture and gene flow between Arabian Peninsula and European populations have been poorly studied at the level of genome. Here, we have compared the whole-exome sequencing of 1208 individuals from the Arabian Peninsula, Africa, Europe, Caucasian, East and South Asia, to identify genetic structure and gene flow between them. We have shown that there is less differentiation between Arabian Peninsula and Italy samples than that between the Arabian Peninsula and other Europeans in this study. As well as Italy samples exhibit higher similarity of copy number variation of deletion and duplication with Qatari individuals. Arabian Peninsula ancestry expanded into the South Asian, Caucasian and parts of European populations. Large identity by descent tracts (≥ 2.0 cM) were identified between Arabian Peninsula and individuals from Kenya and Nigeria. outgroup f3-statistics suggest that within Europeans, Southern Europeans share more genetic drift with Arabian Peninsula than with other European regions. It is possible that these patterns reflect the Arabs migration to the Italian island of Sicily, perhaps dating back to the 831-1072 AD. Our results showed genetic structure of Afro-Eurasian populations, with different levels of southern European admixture, as a result of the genetic interaction with Arabian Peninsula.
Decentralizing indexing and bootstrapping for online applications

Correspondence Pan Hui, The Hong Kong University of Science and Technology, China. Email: panhui@cse.ust. hk Abstract Peer-to-peer (P2P) networks utilize centralized entities (trackers) to assist peers in finding and exchanging information. Although modern P2P protocols are now trackerless and their function relies on distributed hash tables (DHTs), centralized entities are still needed to build file indices (indexing) and assist users in joining DHT swarms (bootstrapping). Although the functionality of these centralized entities are limited, every peer in the network is expected to trust them to function as expected (e.g. to correctly index new files). In this work, a new approach for designing and building decentralized online applications is proposed by introducing DIBDApp. The approach combines blockchain, smart contracts and BitTorrent for building up a combined technology that permits to create decentralized applications that do not require any assistance from centralized entities. DIBDApp is a software library composed of Ethereum smart contracts and an API to the BitTorrent protocol that fully decentralizes indexing, bootstrapping and file storing. DIBDApp enables any peer to seamlessly connect to the designed smart contracts via the Web3J protocol. Extensive experimentation on the Rinkeby Ethereum testnet shows that applications built using the DIBDApp library can perform the same operations as in traditional backend architectures with a gas cost of a few USD cents.
Immediate lymphatic reconstruction for breast cancer

Upper extremity lymphedema remains a significant source of morbidity in breast cancer patients despite significant improvements in breast cancer care. The risk of lymphedema is particularly elevated in patients requiring an axillary lymph node dissection and/or adjuvant radiation to treat their disease. Current treatment options for lymphedema, including conservative management or surgery, are limited and are often aimed at improving symptoms and quality of life rather than curing the disease. In this review we describe immediate lymphatic reconstruction, a novel surgical procedure that is done concurrent with axillary lymph node dissection in an effort to prevent the development of breast cancer-related lymphedema. Based on our growing knowledge of the pathophysiology of lymphedema, microsurgical techniques are used at the time of axillary lymph node dissection to perform a lymphovenous bypass between transected, leaking lymphatic channels and an adjacent, small calibre vein in the axilla. Using several objective metrics for shortand longterm surveillance, patients are monitored for the development of postoperative lymphedema. Early outcomes from using this technique have been promising, both in the literature and within our own institutions, demonstrating significant improvements in rates of postoperative lymphedema. However, future study is still required to better understand the long-term efficacy of immediate lymphatic reconstruction.
Insider’s advantage: when foreign firms do not capture opportunity in the local labour market

Previous studies have argued that, relative to local firms, multinational firms may have an “outsider’s advantage” in hiring women. Using a large data set of executives in the countries of the Gulf Cooperation Council, in a region with some of the lowest rates of female labour force participation in the world, I present new evidence of a setting in which foreign firms do not capture opportunity in the local labour market. I find that foreign firms, on average, are not more likely than local firms to hire female executives and are less likely to place women into top management roles. I propose that foreign firms may have fewer social networks and resources, or lack “insider’s advantage”, relative to local firms for recruiting women into executive positions.
J-POP: Japanese Puzzles as Optimization Problems

Japanese puzzle games such as Sudoku and Futoshiki are familiar recreational pursuits, but they also present an interesting computational challenge. A number of algorithms exist for the automated solution of such puzzles, but, until now, these have not been compared in a unified way. Here, we present an integrated framework for the study of combinatorial black-box optimization, using Japanese puzzles as the test-bed. Importantly, our platform is extendable, allowing for the easy addition of both puzzles and solvers. We compare the performance of a number of optimization algorithms on five different puzzle games, and identify a subset of puzzle instances that could provide a challenging benchmark set for future algorithms.
Numerical Investigation of Reactivity Controlled Compression Ignition Engine Performance under Fuel Aggregation Collision to Piston Bowl Rim Edge Situation

To better homogenize the mixture of fuel and air in the combustion chamber and to enhance the controllability of ignition timing in Reactivity Controlled Compression Ignition (RCCI) engines, controlling the start of injection (SOI) timing can be essential. By changing the SOI timing, at some specific crank angles (CAs), the fuel can impact the edge of the piston bowl and create some difficulties. In this research, initially, efforts are made to recognize the range of SOI timing in which this collision process takes place (in the range of 44-54° bTDC), then, performance and the emission levels of the engine were evaluated in the beginning and end of this interval. The findings suggest that the nitrogen oxides emissions and the maximum in-cylinder mean pressure are higher in SOI of 44° bTDC, as compared to those in the SOI timing of 54°bTDC, although the latter has higher ignition delay and unburnt hydrocarbon (UHC) emission. Moreover, some evaluations were carried out to examine how the temperature of the fuel-air mixture can affect the performance of the engine in this specific range. It was found that as the IVC temperature increases, it rises the indicated mean effective pressure (IMEP), in-cylinder pressure, and NOx emission.
Estimating accrual-based models in Poland: the time series data approach and the cross-sectional data approach

The analysis of accruals can be considered as an important tool for examining the level and the patterns of earnings management phenomenon in an enterprise. This paper compares the empirical features of different accrual-based models within industrial public companies listed on the Warsaw Stock Exchange in the period 2002-2017. The conducted research is focused not only on examining the empirical validity of the original Jones model, the modified Jones model and the ROA-matched Jones model. It also submits the alternative regression model used for the detection of earnings management practices, taking into account the following independent variables: operational expenses as a proxy for the current components of nondiscretionary accruals, as well as intangible assets as a proxy for the noncurrent components of non-discretionary accruals. Then, the authorexamined the probability of occurrence of small increases in net income or big bath charges in companies reporting specific values of discretionary accruals. The conclusions drawn in this paper are part of practical research concerning the use of informational and decision-making features of accruals analysis in the Polish post-transitional capital market, acting simultaneously as a prerequisite for further research in this field. This paper compares the empirical features of different accrual-based models within industrial public companies listed on the Warsaw Stock Exchange (WSE) in the period 2002-2017.The study presents an analysis of the essential methodical measurement of the processes of the intentional stimulation of financial results based on the estimation of operational and discretionary accruals. However, it focused not only on examining the empirical validity of the Jones model, the modified Jones model and the ROA-matched Jones model, but also submits an alternative regression tool used to detect EM practices. Consequently, the research proposes a new approach in extracting discretionary accruals, by taking into account the operating expenses as a variable for current components of non-discretionary accruals, as well as the intangible assets as a proxy for the non-current components of normal accruals. The research considered both the time-series and cross-sectoral dimension, thereby making it possible to examine whether the average values of discretionary accruals in companies implementing EM practices
Analysis of Genetic Variability in the Caprine Class II MHC CLA DRB3.2(Cahi DRB3.2) gene locus of the Sangamneri goat breed of India

The objective of this study was to assess the genetic variability present across the Class II MHC DRB 3.2 gene locus in the Sangamneri goat breed of India. Sixty three single nucleotide variations were observed in CLA-DRB3.2 gene of eleven Sangamneri animals. Sixteen haplotypes with Haplotype diversity of 0.974 were found. Besides the snp(s) having two alleles, both triple and tetra allelic single nucleotide variations were present. Thus, the Class II DRB 3.2 gene of the Sangamneri goat breed animals (CLA-DRB3.2/ Cahi DRB3.2) was exhibiting a very high degree of genetic polymorphism. Of the sixty three single nucleotide variations, fifty variations were non-synonymous i.e. they resulted in a change in the corresponding amino acid encoded by the triplet codon in which they were existing. Both conservative and non-conservative amino acid changes were observed to occur. Rich diversity of the DRB3.2 gene reflected well on the ability of the Sangamneri animals to survive in the harsh climatic condition(s), exposed to all kinds of pathogen(s) existing in the environment.
Janus Dendrimer from Poly(Aryl Ether) Linked PAMAM for Supergelation and Guest Release

The present work reports an easy-to-make procedure of Janus dendrimers containing two most widely used dendrons [poly(aryl ether) and poly(amido amine) {PAMAM}], and utilize them, for the first time, to form a hydrogel with supergelation ability. The first generation (G1G1) Janus dendrimer forms hydrogel with a critical gelation concentration (CGC) of 6.5 mg/mL, whereas the CGC for G1G1.5 dendrimer went as low as 0.90 mg/mL in DMSO-H2O mixture. Judicious choice of solvent medium (ethanol-water) led to the formation of flexible morphology (long fibres to vesicles) by the Janus dendrimers, suggesting the possibility of tuning the mechanism of self-assembly in the system. The dye (rhodamine B) loading efficiency in the gel was successfully carried out using different generations {G1G1 and G1G1.5} of the Janus dendrimer. Generation G1G1 hydrogel (1 wt%) showed maximum dye loading efficiency of 4 mg/mL. Rhodamine B release profiles from the Janus dendrimers were determined and the results indicate that slow release kinetics was observed in the case of G1G1, where the self-assembly is robust.
Structural Variety of Defect Perovskite Variants M3E2X9 (M = Rb, Tl, E = Bi, Sb, X = Br, I)

The compounds Rb3Sb2Br9, Rb3Sb2I9, Rb3Bi2Br9, Rb3Bi2I9, and Tl3Bi2Br9 were synthesized and their crystal structures determined from single crystal X-ray diffraction data. The compounds Rb3Sb2Br9, Rb3Sb2I9, and Rb3Bi2I9 crystallize in the Tl3Bi2I9 type of structure (space group P21/n, no. 14). Rb3Bi2Br9 and Tl3Bi2Br9 crystallize in a new but closely related type of structure (space group P21/a, no. 14). Both structure types feature characteristic double layers comprising corner-sharing EX6 octahedra. The space groups are set in a way that the stacking direction of the layers is the [001] direction. The group-subgroup relations to cubic perovskite ABO3 are discussed. Differences between M3E2X9 types are attributed to distortions of the underlying MX3 close packing. Depending on the atomic size ratio, the distortions are quantified by an order parameter.
Towards multi-drone autonomous construction via deep reinforcement learning

Autonomous construction has been an active research topic for engineers and designers for many years. Meanwhile, technological advancement made in the drone industry is continuously pushing the drone’s capability boundary. The probability of drones actively participating in additive construction is large enough to be realized in the near future. However, there is no system that can control a scalable number of drones for autonomous construction in a dynamic continuous environment. This thesis aims to develop a system for autonomous multi-drone additive construction using deep reinforcement learning-based algorithm. First, the process of multi-drone additive construction is modeled in a computer simulation. Then state-of-art deep reinforcement learning algorithm is applied to achieve collision avoidance in navigation. A software package is then developed and able to be integrated into a 3d modeling software, Rhinoceros, for future use and development for researchers and designers. Finally, this system is applied in two experiments: bricklaying and facade coating to demonstrate usage.
Discovering Latent Topics of Digital Technologies From Venture Activities Using Structural Topic Modeling

This study attempts to explain the interplay between digital technologies and venture creation using structural topic modeling (STM), an automatic text analysis method, to detect latent topics related to digital technologies from large texts. The profile data of 133 344 U.S. companies from CrunchBase are analyzed. The data provide detailed descriptions in text about each company: what each company does. STM enables identification of topics related to digital technologies from the large company profile data. The findings identify those digital technologies that appear to have played the biggest role in the landscape of venture activities in the United States. The study also presents findings showing the temporal changes in such “digital” topics and the association of those topics with different industry sectors. The proposed analytical framework and the findings make contributions to the growing discussion about the intersection between digital technologies and new business creation.