Miracle-dz/UniFAR-FTUs huggingface dataset:
Mindfulness for Sustainable Internet Use in Chinese Junior Secondary School Students: A Dual-Path Mediation Model

Mindfulness training can reduce Internet addiction and promote sustainable development, but the possible mediators of this impact have not been thoroughly explored. This study explored the mediating roles of self-control and maladaptive cognitions in the association between mindfulness and Internet addiction to fill this gap. Altogether, 771 Chinese adolescents (M = 13.87 years, SD = 0.78 years) were surveyed about their mindfulness, self-control, maladaptive cognitions, and Internet addiction. The confirmed model presented a good model fit and revealed that (i) mindfulness, self-control, maladaptive cognitions, and Internet addiction were significantly correlated; (ii) mindfulness had indirect negative effects on Internet addiction, mediated by self-control; (iii) mindfulness had an indirect negative impact on Internet addiction, mediated by the path of self-control to maladaptive cognitions; and (iv) this dual-path mediation model might apply to male and female adolescents. The results of the present study suggest that both self-control and maladaptive cognitions are key factors in the association between mindfulness and Internet addiction.
Insensitive Munitions – Design Principles and Technology Developments

The concept of Insensitive Munitions was developed more than 40 years ago. The challenge for the munition designer was to produce munitions that gave the required performance but did not respond violently when subject to accidents or enemy action. Given that munitions contain metastable energetic materials which are by design able to release large quantities of energy in very short timeframes, coupled with the other constraints of reliability, service life, environmental impact, ease of disposal and cost it is easy to understand that this was and to some extent still is a major challenge. This paper provides a brief summary of the key technologies developed over the last 40 years and provides a set of design principles to facilitate the IM design process.
Knowledge Acquisition and Representation for High-Performance Building Design: A Review for Defining Requirements for Developing a Design Expert System

New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach.
Review of Multi-Target Tracking Technology for Marine Radar

Multi-Target Tracking (MTT) is a difficult task in radar data processing. When compared to tracking in various fields or scenario, Maritime MTT (MMTT) is a challenging one and also a daunting task. On one hand, low signal-to-clutter ratio in the highly complex marine environment limits the detection performance for small targets at sea, and the plots obtained by the detector contain missing detections and a large number of false alarms, which make MTT much more difficult. On the other hand, when marine targets are moving in the form of multiple groups, or when the high resolution radar is used in marine detection applications, the measurements of the target pave the way to show efficiently the distribution characteristics of occupying multiple cells. In this case, using of conventional MTT methods is not ideal as their performance is not effective as desired. Currently, the number of papers on MMTT at home and abroad is very limited, and most of them only focus on a single target. This paper summarizes the use of MMTT algorithms based on four methods: conventional MTT method, amplitude aided MTT method, multi-target track-before-detect method, and multiple extended target-tracking method. In addition, this paper also considers and analyzes the future perspective of MMTT comprehensively.
Impact of controlled microwave radiation in enhancing the productivity of Abelmoschus esculentus seedlings (L.) Moench

ABSTRACT The study describes the impact of microwave radiation on the germination rate and growth of Abelmoschus esculentus (L.) Moench (okra). The two okra varieties, viz. Meenaxi-371 and Soniya-1402, were used for the experiment. Their seeds were exposed to 0–14 h (h) of microwave radiation (9.3 GHz). Non-irradiated seeds (0 h exposure) served as control. We found that microwave radiation on seeds resulted in an increase in their germination indices and also stimulated the concentration of β-1,3-glucanase enzyme. The results also indicate a remarkable increase in bioactive compounds such as flavonoids, polyphenols, carotenoids, chlorophyll, lutein, protein, and β-carotene in okra seedlings exposed to 8–10 h of radiation. A further dose escalation in the microwave radiation caused a decline in the germination and growth of the okra plant. The expression level of ACS4, ETR2, and ACS6 showed up-regulation under the influence of microwave irradiated conditions. Therefore, it is evident that a well-controlled and defined irradiation has the potential to enhance the overall growth and yield of selected okra varieties. Abbreviations: RNA: ribonucleic acid; qRT-PCR: quantitative real-time polymerase chain reaction; EMF: electromagnetic field; ACS: amino cyclo synthase; ETR: ethylene transport receptor
Smart Green Prefabrication: Sustainability Performances of Industrialized Building Technologies

There is an urgent need to increase the environmental, economic, and social sustainability of buildings. Indeed, construction has one of the lowest rates of sustainability among productive sectors, associated with high energy demand and pollutant emissions, frequent cost increase and time delays, and poor and unsafe working conditions. Building prefabrication is a construction technique that can enhance the sustainability of buildings, in terms of predictability, product and process quality, and increased safety for workers. Recently, new approaches and concepts such as Industry 4.0 (Construction 4.0) and circularity of resources emerged in the field of prefabrication to potentiate the benefits of off-site construction. In this scenario, the scope of the work is to analyze the state of the art in the field of prefabricated building technologies in the light of these innovations and to evaluate their performances from a sustainability perspective. The work has been developed in two phases: (1) analysis of 13 case studies of prefabricated technologies in Europe; (2) comparative assessment of their sustainability performances according to 21 qualitative parameters. Based on the results of the work, a set of guidelines is proposed as the outcome, i.e., suggested strategies and approaches for designers and industry professionals that can be used to enhance the sustainability of prefabrication.
Ambulance routing in disaster response considering variable patient condition: NSGA-II and MOPSO algorithms

The shortage of relief vehicles capacity is a common issue throughout disastrous situations due to the abundance of injured people who need urgent medical aid. Hence, ambulances fleet management is highly important to save as many injured individuals as possible. In this regard, the present paper defines different patient groups based on their needs and characteristics. In order to provide the affected people with proper and timely medical aid, changes in their health status are also considered. A Mixed-integer Linear Programming (MILP) model is proposed to find the best sequence of routes for each ambulance and minimize the latest service completion time (SCT) as well as the number of patients whose condition gets worse because of receiving untimely medical services. Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) are used to find high-quality solutions over a short time. In the end, Lorestan province, Iran, is considered as a case study to assess the model's performance and analyze the sensitivity of solutions with respect to the major parameters, which results in insightful managerial suggestions.
Performance Research of Clustering Methods for Detecting State Transition Trajectories in Hemoglobin

The time-series clustering method is one of unsupervised machine learning techniques that classify time-series data. In this article, we applied three methods to the clustering analysis for 200 molecular dynamics (MD) trajectories of human adult hemoglobin (HbA), and have reported their clustering performances for detecting the T-R state transition trajectories (Traj T-R ). By compared with their silhouette indices, we have discussed the proper clustering conditions
Optimal Distribution of Workloads in Cloud-Fog Architecture in Intelligent Vehicular Networks

With the fast growth in network-connected vehicular devices, the Internet of Vehicles (IoV) has many advances in terms of size and speed for Intelligent Transportation System (ITS) applications. As a result, the amount of produced data and computational loads has increased intensely. A solution to handle the vast volume of workload has been traditionally cloud computing such that a substantial delay is encountered in the processing of workload, and this has made a serious challenge in the ITS management and workload distribution. Processing a part of workloads at the edge-systems of the vehicular network can reduce the processing delay while striking energy restrictions by migrating the mission of handling workloads from powerful servers of the cloud to the edge systems with limited computing resources at the same time. Therefore, a fair distribution method is required that can evenly distribute the workloads between the powerful data centers and the light computing systems at the edge of the vehicular network. In this paper, a kind of Genetic Algorithm (GA) is exploited to optimize the power consumption of edge systems and reduce delays in the processing of workloads simultaneously. By considering the battery depreciation, the supporting power supply, and the delay, the proposed method can distribute the workloads more evenly between cloud and fog servers so that the processing delay decreases significantly. Also, in comparison with the existing methods, the proposed algorithm performs significantly better in both using green energy for recharging the fog server batteries and reducing the delay in processing data.
PROBLEMS AND SECURITY THREATS TO IOT DEVICES

The Internet of Things or IoT is billions of physical devices connected to the Internet. Its main premise is simply an extended type of connection, which can then be used as a basis for all kinds of functions. IoT describes a network of physical objects - "things" that are built into sensors, software and other technologies to connect and communicate with other devices and systems over the Internet. Problems of system protection, including the use of IoT devices are studied by many scientists and specialists in this field, but in today's world, not every manufacturer is ready to declare vulnerabilities and general insecurity of their products (devices). Throughout the IoT environment, from manufacturers to users, there are still many IoT security issues, such as manufacturing standards, update management, physical hardening, user knowledge and awareness. This article examines the vulnerabilities of the Internet of Things. The analysis of information transfer technologies of IoT devices (in particular ZigBee, Signfox and Bluetooth) is carried out. The most common threats that a user may encounter have been identified and analyzed. It is also established that usually not only the manufacturer poses a threat to the security of IoT devices. There are also a number of tips for users who want to reduce the risk of data leakage associated with vulnerabilities in the Internet of Things. Unfortunately, it is not uncommon for such devices to be incorrectly set up, used and stored. Extremely common is the user's refusal to update the software, which in turn leaves open those vulnerabilities that the manufacturer is trying to fix. The main purpose of the article is to determine the causes of security threats to the Internet of Things, by analyzing data transmission technologies, analysis of the threats themselves, identifying the most critical of them and ways to reduce the risk of data theft
Easy and eco-friendly synthesis of ordered mesoporous carbons by self-assembly of tannin with a block copolymer

Ordered mesoporous carbons were prepared by the self-assembly of Mimosa tannin, a natural polyphenolic molecule, and a micellar solution of Pluronic® F127, used as soft template. The synthesis was carried out at 20 °C using water as the only solvent and without crosslinker agent (i.e., formaldehyde). When tannin, at any pH lower than 4.2, and Pluronic solutions were mixed, a phase separation mechanism immediately occurred due to the strong interaction between both polymers. The precipitated resin was recovered, dried and pyrolysed at 400, 700 and 900 °C. Ordered mesoporous carbon materials were obtained, having both high pore volume and surface areas, up to 0.64 cm3 g−1 or 720 m2 g−1, respectively.
A Compact High-Torque Twisted String Actuator Using Parallel Bundle-Driven Actuation With an Asymmetric Behavior Compensator

The twisted string actuator (TSA) has been extensively studied as an alternative to metallic gear reducers due to its low-cost, lightweight, compliance, and highly adjustable actuation characteristics. Owing to these advantages, TSAs are utilized to realize lightweight human–robot interactive robots requiring safe interaction, such as wearables and prosthetics, at a relatively low cost. However, because its force transmission ratio is almost proportional to the length of the string, the string of the conventional TSA must be elongated to achieve high force output. Thus, it is difficult to obtain high force capacity while maintaining a small size. To overcome this limitation, in this article, we propose a novel TSA based on parallel bundle-driven actuation to significantly reduce the length of the TSA while achieving high force output. Furthermore, in order to boost the proposed TSA performance, we also present a passive mechanism of an asymmetric behavior compensator. The experimental results show that the force transmission ratio of the proposed TSA is increased by 21%, compared with that of the conventional TSA. Consequently, the proposed TSA has a 44% higher torque capacity with a 37% shorter string than those of theconventional TSA.
Validation of a steroidomic model and its application in doping control

In doping control, steroid profiles have greatly evolved since the introduction of the T/E ratio as more endogenous steroids hit the market and more insights into the steroid metabolism were gained. With the introduction of a Bayesian adaptive model to establish individual thresholds to circumvent large inter-individual variations of steroid metabolites, a big leap in steroid profiling was made. However, as different confounding factors of the steroid profile were investigated in doping analysis (e.g. genetic polymorphisms, alcohol, …), the interpretation of steroid profiles became more complicated in order to detect atypical findings for misuse with endogenous steroids. A statistical discrimination algorithm based upon Support Vector Machines was developed for evaluation of longitudinal steroid profiles which are stored in the biological passport. This steroidomic model allows a quick and accurate evaluation of comprehensive steroid profiles including minor steroid metabolites. The validity of this model was tested upon a database containing longitudinal data from 47 volunteers as well as excretion urines after administration of various endogenous steroids: testosterone undecanoate, testosterone gel, dehydroepiandrosterone, dihydrotestosterone gel, 4-androstenedione, 4-androstenediol, 5-androstenediol, 6-oxo-androstenedione and 7-keto-dehydroepiandrosterone. The model was further optimised for feasible application in a doping control setting using sensitive steroid metabolites. The model is applied to different kinds of phenotypic steroid profiles and results were verified with those of a confirmatory IRMS method.
The Nexus between Female Child Trafficking and Pakhtun Culture in Peshawar

The present study aims to investigate the factors and forms of female child trafficking in Pakhtun society from the perspective of opinion of leaders and experts. It enlists some of the cultural factors and forms of marriages, which provide critical space for the practice of trafficking even though it goes unnoticed in Pakhtun society. For this purpose, data were collected from 392 respondents, consisting of 116 university teachers, 103 journalists and 173 legal practitioners from Peshawar. Data were collected through a questionnaire. Cronbach’s Alpha test was used to know about the reliability of the tool which was 0.7. Analyses were carried out with the help of suitable statistical tests of Chi square, and gamma. Simple frequency distribution, bi and multivariate level of analyses were carried out. The study found that all the study indicators of Pakhtun culture are responsible for providing breeding ground for female child trafficking. Bride price, excessive dowry compensation marriage (locally known as Swara marriage), and forced marriage are the main factors and forms responsible for female child trafficking in the study area. Results at bivariate and multivariate confirm each other where gender has no critical role in the resulted association between the two variables.
Campers’ Views on the Effects of English Immersion Camp Initiatives for Aural/Oral Skills Development of Pre- and In-Service EFL Teachers

This study examines the effects of three English language immersion camps on the participants. Capitalizing on Participatory Action Research, and informed by Experiential Learning and Social Constructivism, these camps constitute an attempt by a Brazilian Amazonian university to mitigate the lack of fluency and proficiency in English among EFL initial teacher education students and state school teachers of English in the region. Data gathered through interviews and participant observation notes were analyzed following a thematic analysis approach. Results suggest expansion of the participants‟ English vocabulary and knowledge of the American culture, and development of listening and speaking skills. Additionally, a comparison of discourse themes emerging from this study with those from other similar investigations indicates high resonance between them, suggesting that these programs may be a reliable alternative mode of instruction for additional language education, and reinforcing the theory that massive target language comprehensible input and output generate language learning.
PREPARADOS DE PLANTAS BIOATIVAS NA INDUÇÃO DE FITOALEXINAS E NO CONTROLE IN VITRO DE FITOPATÓGENOS DO TOMATEIRO / PREPARATIONS OF BIOATIVE PLANTS IN PHYTOALEXINS INDUCTION AND IN VITRO CONTROL OF TOMATO PHYTOPATHOGENS

Fungal diseases are among the main factors that affect tomato productivity. Vegetable preparations have shown potential in the control of plant diseases, both by antimicrobial action on phytopathogens and by inducing defense mechanisms, such as phytoalexins. The aim of this work was evaluate the potential of vegetable preparations from ten bioactive plants in phytoalexins induction and mycelial growth and spores germination of tomato phytopathogens. To prepare the macerate and the fermented, 150 g of the dry and crushed vegetable material were used, remaining for a period of 24 h and 10 days, respectively, in contact with 1.5 L of distilled water, used in a concentration of 10%. Tests were carried out to evaluate the antifungal potential of plant preparations on mycelial growth and on the spore germination of Alternaria linariae and Septoria lycopersici. Phytoalexin induction was evaluated in soybeans, beans and sorghum. The tests were conducted in a completely randomized design with four replications. In the mycelial growth and spore germination there was an antifungal effect for the vegetable preparations, with emphasis on the treatments based on Ilex paraguariensis and Solanum mauritianum. Similar results were also obtained in the induction of phytoalexins in different cultures. The results demonstrate the potential of I. paraguariensis and S. mauritianum preparations in plant protection.
Demand Elasticity in the IPEX: a Bayesian Experiment under dual pricing scheme

Perugia Abstract: This study run experiment aiming to provide a flexible and analytically elegant framework to reliably estimate the price elasticity of electricity demand. Inference pertains to the demand at hourly level in the Italian wholesale electricity market and uses individual demand bid data. Individuals' bids represent the ex-ante willingness to pay and thus allows for constructing a market demand grounded in the consumer behaviour theory, by exploiting the duality approach. Bayesian econometric estimation is applied, relaxing homoskedasticity assumptions of the traditional linear regression model. It allows to identify robust results, showing that elasticity varies significantly among hours of the day, zone segmentation as well as the level of equilibrium price. Bayesian inference provides also the opportunity to include prior information sourced from previous studies and the institutional structure governing the agents' behaviour. This prior information involves some degree of uncertainty, for this reason Bayesian approach assigns it a probability distribution. Using Bayes rule, prior information is then updated according to the observed data. Results validate the market reform designed to foster competition and increase welfare even through the time-varying pricing schemes that trigger the consumers' price