Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear optical diagnostics of laser-excited semiconductor surfaces

The effect of pulsed laser annealing of ion-implanted semiconductors was discovered in the late 1970's. As a result researchers concentrated on the fundamental problems related to the absorption of laser radiation localized in time and space and at the possible application of lasers to microelectronics. Experiments on laser annealing have raised a series of fundamental questions, including the role of dense electron-hole plasmas in fast melting semiconductors, the stages of the melting process and the mechanism of laser-induced amorphization. To answer these questions, which are only a small part of the full range of problems, it is vitally important to develop experimental techniques for the diagnostics of semiconductor surfaces and phase transitions. This book analyzes the current concepts of laser beam interaction with semiconductors and the potential of using optical methods in diagnostics. Also discussed is the new information which may come from optical techniques on the structure of semiconductor crystal surfaces and phase transitions.
Quality of Life and Psychological Distress among Patients with Small Renal Masses

Background: Quality of life (QoL) and psychological distress represent an important aspect of the daily life of cancer patients. The aim of this systematic review was to critically analyze available literature regarding QoL and psychological distress in patients with small renal masses (SRMs). (2) Methods: A systematic search of EMBASE, PUBMED and American Psychological Association (APA-net) was performed on 30 April 2022. Studies were considered eligible if they included patients with SRMs, had a prospective or retrospective design, included at least 10 patients, were published in the last 20 years, and assessed the QoL or psychological distress in patients that underwent active surveillance (AS) in comparison to those that underwent ablation/surgery treatments. (3) Results: The patients that underwent AS were statistically significantly older, with smaller renal masses than those that underwent surgery/ablation. A study showed a significant reduction in total scores of Short Form-12 (SF-12) among AS patients when compared to partial nephrectomy (PN) patients at enrollment (95.0 ± 15.8 vs. 99.1 ± 13.9), 2 years (91.0 ± 16.4 vs. 100.3 ± 14.3), and at 3 years (92.9 ± 15.9 vs. 100.3 ± 14.3), p < 0.05, respectively. That was mainly due to lower physical health scores. On the other hand, another study showed that AS patients with a biopsy-proven malignant tumor had a worse psychological distress sub-score (PDSS) compared to patients treated with surgery/ablation after biopsy. (4) Conclusions: It seems that there is an influence on QoL and psychological distress while on AS of SMRs. However, due to the low amount of available data, the impact of AS or active treatment on QoL or psychological distress of patients with small renal masses warrants further investigation.
Catalytic promiscuity of O-methyltransferases from Corydalis yanhusuo leading to the structural diversity of benzylisoquinoline alkaloids

Abstract O-methyltransferases play essential roles in producing structural diversity and improving the biological properties of benzylisoquinoline alkaloids (BIAs) in plants. In this study, Corydalis yanhusuo, a plant used in traditional Chinese medicine due to the analgesic effects of its BIA-active compounds, was employed to analyze the catalytic characteristics of O-methyltransferases in the formation of BIA diversity. Seven genes encoding O-methyltransferases were cloned, and functionally characterized using seven potential BIA substrates. Specifically, an O-methyltransferase (CyOMT2) with highly efficient catalytic activity of both 4′- and 6-O-methylations of 1-BIAs was found. CyOMT6 was found to perform two sequential methylations at both 9- and 2-positions of the essential intermediate of tetrahydroprotoberberines, (S)-scoulerine. Two O-methyltransferases (CyOMT5 and CyOMT7) with wide substrate promiscuity were found, with the 2-position of tetrahydroprotoberberines as the preferential catalytic site for CyOMT5 (named scoulerine 2-O-methyltransferase) and the 6-position of 1-BIAs as the preferential site for CyOMT7. In addition, results of integrated phylogenetic molecular docking analysis and site-directed mutation suggested that residues at sites 172, 306, 313, and 314 in CyOMT5 are important for enzyme promiscuity related to O-methylations at the 6- and 7-positions of isoquinoline. Cys at site 253 in CyOMT2 was proved to promote the methylation activity of the 6-position and to expand substrate scopes. This work provides insight into O-methyltransferases in producing BIA diversity in C. yanhusuo and genetic elements for producing BIAs by metabolic engineering and synthetic biology.
Storage of the Early Ripe Almonds under Modified Atmosphere to Preserve Kernel Qualitative and Sensory Traits

Almonds are often used both in confectionery products and for fresh consumption. Thus, to enhance the use of early ripe or unripe fresh almonds, it is important to maintain the organoleptic and qualitative traits of the product for a period of time as long as possible. The objective of the research was to study different types of almonds storage, not artificially dried, under a modified atmosphere to maintain quality in almond kernels mainly destoned to table consumption. The storage of samples was in a modified atmosphere in 100 ± 1 kPa CO2, 100 ± 1 kPa N2 or air and at +4 °C and +10 °C, respectively for 12 days. Some analytical parameters and sensory analysis were explored. Test results showed that the modified atmosphere of N2 at +4 °C was the most suitable for keeping the chemical, physical and sensorial attributes of fresh almond kernels, maintaining their quality intact for up to almost two weeks of storage.
OVERVIEW OF BUSINESS INTELLIGENCE MATURITY MODELS

Today, companies wish to evaluate and justify their investments into Business Intelligence systems, which requires measurement of their business value and comparison with similar systems in other companies. Maturity models offer an adequate baseline for comparison. Maturity models define levels of definition, efficiency, manageability and measurement of the monitored environment. This paper briefly describes and analyzes six different maturity models that can be used for the maturity of BI systems assessment. An overview and analysis will show that most of the models do not cover the whole area of Business Intelligence, but they rather focus on a specific point of view and/or area of the problem domain. Results show that by using maturity models, only a short period of time is needed in order for one to discover the areas within the company or institution that need special, more intensive attention and work. Namely, results of the analysis often expose problematic areas that could be easily overlooked.
Testing for market efficiency in cryptocurrencies: evidence from a non-linear conditional quantile framework

ABSTRACT This study tests for the weak-form market efficiency of 15 cryptocurrency prices. The conventional unit root tests and stationary test results reveal that most cryptocurrency markets are efficient markets. However, the non-linear quantile unit root test proposed by Li and Park (2018) rejects the unit root null hypothesis over the whole quantile level. To derive more informative ideas, we split the whole quantile interval to several sub-intervals and find asymmetric behaviour of the market efficiency across the lower and upper sub-intervals in several cryptocurrency markets. Moreover, non-linear quantile unit root tests for Chainlink, Bitcoin Cash, Binance Coin, EOS, Tron, and Stellar indicate that markets for these cryptocurrencies are efficient at the upper sub-intervals.
Training practices and perceptions of soccer officials: Insights from the Referee Training Activity Questionnaire

This study sought to: (1) document the multifaceted training practices of soccer officials in relation to their role and officiating category; and (2) explore the association between the officials’ training practices and perceptions of the attributes pertinent to optimal performance. Field referees and assistant referees at officiating categories 1–3 (n = 173) with the Scottish Football Association were invited to participate in this national cross-sectional study. Using the Referee Training Activity Questionnaire (RTAQ), officials reported the volume and type of training engaged in during a 2-week in-season period. Respondents’ perceptions of the skills pertinent to performance were also explored using a 7-point Likert scale (1 = not at all important; 7 = extremely important), with the frequency in which they trained these skills assessed using a 5-point Likert Scale (1 = less than once a month; 5 = more than once a week). Ninety-one responses were received, representing a 52.6% response rate. Irrespective of their role or level of professional attainment, the officials’ training was focused mostly on physical conditioning, with significantly less time apportioned to decision-making (P < 0.001; ES = 1.28), psychological (P < 0.001; ES = 1.47), and technical (P < 0.001; ES = 1.23) skills training. Meanwhile, although decision-making and psychological skills were rated as “very important” to “extremely important” amongst both field referees and assistant referees, officials purposefully trained these skills “less than once a month. ” The present study provides important new insights into the training practices engaged in by soccer officials. As accurate decision-making is at the forefront of soccer officiating, enhancing the exposure of match officials to match-related decision-making during training should be considered a priority for future research.
Thermographic Analysis of Photovoltaic Panels

The paper proposes processing and interpretation of the thermo-graphical images acquired on a grid-connected photovoltaic plant (20 kWp). Infrared analysis allows a reliable evaluation of the state of health of the plant and at the same time the detection of the actions needed of the maintenance. In particular the identification of possible differences between the strings and the rapid location of local hot spots, breakdowns or other problems are presented.
Improved feature point extraction method of ORB-SLAM2 dense map

Purpose This paper aims to quickly obtain an accurate and complete dense three-dimensional map of indoor environment with lower cost, which can be directly used in navigation. Design/methodology/approach This paper proposes an improved ORB-SLAM2 dense map optimization algorithm. This algorithm consists of three parts: ORB feature extraction based on improved FAST-12, feature point extraction with progressive sample consensus (PROSAC) and the dense ORB-SLAM2 algorithm for mapping. Here, the dense ORB-SLAM2 algorithm adds LoopClose optimization thread and dense point cloud map and octree map construction thread. The dense map is computationally expensive and occupies a large amount of memory. Therefore, the proposed method takes higher efficiency, voxel filtering can reduce the memory while ensuring the density of the map and then use the octree format to store the map to further reduce memory. Findings The improved ORB-SLAM2 algorithm is compared with the original ORB-SLAM2 algorithm, and the experimental results show that the map through improved ORB-SLAM2 can be directly used in navigation process with higher accuracy, shorter tracking time and smaller memory. Originality/value The improved ORB-SLAM2 algorithm can obtain a dense environment map, which ensures the integrity of data. The comparisons of FAST-12 and improved FAST-12, RANSAC and PROSAC prove that the improved FAST-12 and PROSAC both make the feature point extraction process faster and more accurate. Voxel filter helps to take small storage memory and low computation cost, and octree map construction on the dense map can be directly used in navigation.
Robotic Technologies and Well-being for Older Adults Living at Home

Purpose The purpose of this study is to investigate the benefits for aged care providers of adding affordable robotic technology to their services packages to enhance the well-being of older adults from culturally and linguistically diverse (CALD) backgrounds who choose to live at home. Design/methodology/approach This study, adopting a transformative service research lens, was performed with a group of older Australian adults from CALD backgrounds aged approximately 70 years. This study conducted four rounds of home trials with three different, commercially available robotic technologies from January to November 2020. Each trial lasted seven days. Findings The findings reveal that older adults from CALD backgrounds are open to learning about new technologies and can successfully interact independently with multiple robotic technologies in their own homes. The results indicate that robot technology has the potential to increase the well-being of older people by enhancing a sense of belonging, independence and quality of life while living at home. Research limitations/implications This study shows a promising future involving the use of available technology to assist older people from CALD backgrounds to live better lives at home. Ageing at home can be central to a person’s sense of identity and independence, and this study is a big step towards a new aged care system desperately needed in a society with a rapidly ageing population. Originality/value To the best of the authors’ knowledge, this study is among the first to introduce three different commercially available robots, each designed to satisfy companionship, cleaning and/or communication needs in the homes of older adults from CALD backgrounds to increase their overall well-being.
NeBula: TEAM CoSTAR's Robotic Autonomy Solution that Won Phase II of DARPA Subterranean Challenge

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR’s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.
Synchronization of Stochastic Lévy Noise Systems on a Multi-Weights Network and Its Applications of Chua’s Circuits

In previous work, generally, stochastic delayed coupled systems were considered on a network with a single weight. However, stochastic delayed coupled systems on a network with multi-weights have not been fully investigated and remain to be important and challenging. Hence, in this paper, time delays and Lévy noise are taken into account in stochastic coupled systems on a network with multi-weights. Furthermore, synchronization of stochastic delayed coupled systems with Lévy noise on a network with multi-weights (SDCSLM) is first studied via aperiodically intermittent control. Then, by means of the Lyapunov method, graph theory and some techniques of inequalities, some sufficient conditions for $p$ th moment exponential synchronization of SDCSLM are obtained. Particularly, as a practical application of the theoretical results, the exponential synchronization in mean square of stochastic Chua’s circuits with time delays and Lévy noise on a network with multi-weights is studied in detail. Finally, some numerical simulations are given to show the effectiveness of the theoretical results.
Research on Hyperparameter Optimization of Concrete Slump Prediction Model Based on Response Surface Method

In this paper, eight variables of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate and flow are used as network input and slump is used as network output to construct a back-propagation (BP) neural network. On this basis, the learning rate, momentum factor, number of hidden nodes and number of iterations are used as hyperparameters to construct 2-layer and 3-layer neural networks respectively. Finally, the response surface method (RSM) is used to optimize the parameters of the network model obtained previously. The results show that the network model with parameters obtained by the response surface method (RSM) has a better coefficient of determination for the test set than the model before optimization, and the optimized model has higher prediction accuracy. At the same time, the model is used to evaluate the influencing factors of each variable on slump. The results show that flow, water, coarse aggregate and fine aggregate are the four main influencing factors, and the maximum influencing factor of flow is 0.875. This also provides a new idea for quickly and effectively adjusting the parameters of the neural network model to improve the prediction accuracy of concrete slump.
Investigation of TLR2 -EcoRV, NOD2- BsaHI ve IFNγ- HphI allele frequency distribution among Turkish Native Cattle Breeds

Changing climatic conditions and growing population size lead take precautions against potential risks. Researchers who study in the agricultural field, including animal production, focus on finding out variants and breeds resistant to diseases and environmental stress. Detecting gene regions that affect resistance to diseases and environmental stress might increase the performance of the selection in favor of these traits. Due to these reasons in this study, five Turkish native cattle breeds were investigated for SNPs belonging to TLR2, NOD2, and IFNγ (using EcoRV, BsaHI ve HphI enzymes, respectively) reported to be associated with paratuberculosis previously. In total, 169 animals were analyzed from Native Southern Yellow (NSY= 29), East Anatolian Red (EAR=35), Anatolian Grey (AG=36), South Anatolian Red (SAR=34), and Native Black (NB=35). The genotype and allele frequencies were calculated with the PopGene32 program, and Khi square test was performed to determine whether the populations were in Hardy-Weinberg equilibrium (HWE). While at TLR2- EcoRV and NOD2- BsaHI loci, two alleles (A and C, C and T, respectively), IFNγ- HphI locus was found to be monomorphic for the G allele. For TLR2- EcoRV locus, the C allele was found as predominant except NB breed, and the C allele was predominant for all breeds at NOD2- BsaHI locus. However, in all breeds, NOD2- BsaHI locus was at HWE, for TLR2- EcoRV NSY and SAR breeds showed derivation from HWE.
PCB Winding for Electric Machines with Integrated 3D printed Heat Exchanger

This paper proposes a printed circuit board (PCB) winding for radial flux electric machines. In addition, a 3-D printed heat exchanger is proposed to cool the PCB-based winding. The motivation is to minimize the cost of the stator winding, as winding the traditional magnet wire can be an expensive process. The integrated 3D printed heat exchanger (I3DHX) uses polymer-based fused filament fabrication (FFF). Most high-power density machines are cooled by a water jacket, which means the heat generated by windings must travel through the stator yoke to be rejected. The proposed approach focuses on moving the heat exchanger closer to the windings, which allows for increased current density in the windings, resulting in smaller slot areas and overall machine size.
Developments in Business Simulations and Experiential Learning, Volume 32, 2005 DECISION MAKING IN BUSINESS SIMULATION DESIGN

To develop effective business simulation exercises it is critical that developers and users understand the human decision-making process so that simulations achieve the desired learning objectives. Understanding how to present the situation and define the environment is central to creating a learning exercise where decision makers can improve their decision-making performance. It is an important pedagogical issue to know whether the business simulation is being designed to reinforce and build a decision maker’s ability to respond in a normative reasoned fashion to a decision problem, or to experience the situation in its complexity and respond in a synthetic intuitive fashion. To comprehend the implications of these two viewpoints the debate between promoters of the normative view on decision making and the descriptive view on decision making are presented. A critical analysis of these different perspectives is shown to influence how decision making should be taught, how simulations should be designed, and how learning outcomes should be measured.
Cloud macrophysical characteristics in China mainland and east coast from 2006 to 2017 using satellite active remote sensing observations

Using the CloudSat and CALIPSO active remote sensing dataset from 2006 to 2017, this study investigates the spatial and temporal distribution along with vertical distribution of cloud macrophysical characteristics in six study areas over China mainland and east coast (15°–55°N, 70°–140°E). The results show that the cloud top height and cloud base height have significant regional, seasonal and zonal variations. The regional differences in the seasonal average vertical distribution of cloud cover are especially large, which are particularly reflected by the differences of heights with peak value of cloud cover, the curve characteristics of cloud cover with height, and the standard deviation of cloud cover. The cloud spacing, which is the distance between two cloud layers for cloud system with layers no less than 2, is found greater in the ocean area than in the land area and is greater in the low‐latitude area than in the high‐latitude area. Moreover, with the increase of the number of cloud layers in the cloud system, the cloud spacing decreases gradually. It is worth noting that the frequency distribution of cloud layers is the same as that of cloud spacing. By dividing clouds into eight types according to CloudSat data, the occurrence frequency of different cloud types shows great differences, ranking from high to low as high cloud > altostratus > altocumulus > stratus > stratocumulus > cumulus > nimbostratus > deep convective cloud. Altostratus mainly occurs in northern regions, and high cloud mostly occurs in Tibetan Plateau, southern China mainland and eastern ocean. The vertical distributions of cloud macrophysical characteristics over the six typical study areas have been further demonstrated by constructing Pc‐τ diagram.