Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Silica Nanoparticles-Supported Metal Catalyst by Wet Impregnation with Catalytic Performance for Tuning Carbon Nanotubes Growth

The catalytic activity of cobalt and iron nanoparticles for the growth of carbon nanotubes (CNTs) was studied by a specific reproducible and up-scalable fabrication method. Co and Fe catalysts were deposited over SiO2 nanoparticles by a wet-impregnation method and two different annealing steps were applied for the catalyst formation/activation. The samples were calcined at an optimal temperature of 450 °C resulting in the formation of metal oxide nano-islands without the detection of silicates. Further reduction treatment (700 °C) under H2 successfully converted oxide nanoparticles to Co and Fe metallic species. Furthermore, the catalytic efficiency of both supported-metal nanoparticles at 2 and 5% in weight of silica was evaluated through the growth of CNTs. The CNT structure, morphology and size dispersion were tailored according to the metal catalyst concentration.
Power-Estimation-Based Synchronous Rectification Solution for Bidirectional DAB-LLC Converter

Combining the auxiliary DAB converter and the bidirectional LLC converter operating at a fixed frequency in an input-series output-parallel (ISOP) structure can achieve bidirectional power regulation and high efficiency in DC-DC transformer (DCX) applications. However, for bidirectional DCX applications, the synchronous rectification (SR) operation becomes challenging since that the instantaneous-transferred power is difficult to obtain, and LLC-DCX will operate in discontinuous current mode (DCM) under light load conditions. In addition, the rectifier-bridge has to be swapped under different power flows. To achieve on-line SR modulation for LLC-DCX under bidirectional power application, a new solution to achieve accurate SR operation, based on instantaneous-transferred power estimation is proposed under full load range. The proposed method uses the added auxiliary DAB converter as a power detector to estimate the power value without input voltage sampling and any auxiliary current sensor or SR detection circuit. Besides, the mathematical derivation of power estimation, DCM operation conditions and the SR conduction period for the rectifier-bridge, are analyzed in depth. Finally, the effectiveness of the proposed method and the correctness of analysis are verified by the simulation and experimental results.
A Deep Neural Network for the Estimation of Tree Density Based on High-Spatial Resolution Image

Tree density is a significant parameter for forest. However, it has always been challenging to use remote-sensing techniques to acquire it efficiently and effectively on a large spatial scale. As a matter of fact, tree counting can be regarded as end-to-end density regression, which uses a remote-sensing image as an input and generates a tree density map as an output. Therefore, the tree number can be easily obtained by the summation of density values in an area. To this end, a deep neural network has been constructed to aggregate multiple decoding paths to extract hierarchical features at different encoding stages, in order to merge tree features of multiple scales in remote-sensing images. At the same time, a hybrid loss function has been proposed to effectively guide the network training and enhance the model ability. A tree count dataset consisting of 2400 sample pairs has been constructed for training and validation. When compared with other popular counting networks, it has been found that the proposed network achieved the best results with a relative mean absolute error (rMAE) of 16.72%, a root mean squared error (RMSE) of 77.96, and an $R^{2}$ of 0.96, evidencing that this is a promising method for estimating tree numbers on a large spatial scale.
The Inter-Relationship between CSR, Inclusive Leadership and Employee Creativity: A Case of the Banking Sector

The stiff situation of competitiveness in every industry has posed some serious challenges for businesses all over the world. Thus, every segment of the business is realizing the importance of creativity to remain alive in a cut-throat competitive environment. However, the banking sector has not received due attention in this regard. To bridge this gap, the current study was carried out to explore the relationship of employees’ perception of corporate social responsibility (CSR) of their bank and employee creativity with the mediating effect of inclusive leadership (IL). The data for the current study were collected from the banking sector of Pakistan through a self-administered questionnaire (n = 533) and were analyzed by using structural equation modeling (SEM) in AMOS. The statistical findings of the current survey validate the direct relationship between CSR and employee creativity. The results also confirm the mediating effect of IL in this relationship. The findings of the current survey will help policymakers from banking institutions to improve their understanding of CSR. Furthermore, these findings will help policymakers to embrace employee creativity as a “new normal” for this sector.
Adaptive fuzzy finite‐time decentralized control for large‐scale stochastic nonlinear systems

An adaptive finite‐time decentralized control algorithm for a class of large‐scale stochastic nonlinear systems is presented. The fuzzy logic system is used to estimate uncertain nonlinearities. One advantage of the developed scheme is that each subsystem only needs to update one adaptive parameter, which alleviates the burden of online estimation. The dynamic surface control method is employed to reduce the “complexity explosion” caused by the repetitive derivation of the intermediate variable function in the backstepping control scheme. A new decentralized controller is designed so that all signals of the controlled system are bounded and the tracking error converges to a small residual set around the origin within a finite time. The simulation results of a numerical example illustrate the effectiveness of the method.
Industrial Dataspace for smart manufacturing: connotation, key technologies, and framework

Smart manufacturing is a popular concept for smarter decision-making and more efficient production. Although distributed methods for data management and processing in smart manufacturing have many advantages such as low cost of adaptation and convenience for local database, some methods are hard to manage variable data sources and discover proper range of data for smart decision-making. Therefore, Dataspace is considered in this article to be a feasible and effective method. From the relation-defined perspective of utilisation of industrial Big Data, the contribution is a novel industrial Dataspace design with static structure and working flow paths for smart manufacturing. In design, the industrial Dataspace platform has been proposed to accommodate smart manufacturing characteristics with the intelligence of pay-as-you-go, like harnessing distributed heterogenous data from industrial enterprises, understanding industrial data by ontology or knowledge, corelating the data with smart applications, and enabling related decisions. A further analytical case in Surface Mounting Technology manufacturing of welding procedure is provided to illustrate the execution of customisation, focused and related decision support, and system evolution within industrial Dataspace.
A road map for planning-deploying machine vision artifacts in the context of industry 4.0

ABSTRACT Machine Vision enhanced by Artificial Intelligence can improve product and process monitoring through inspection. However, applying these solutions to the industrial environment requires a transdisciplinary effort and requisites interoperability. This study proposes a road map to reduce implementation uncertainties. A systematic review of the literature was conducted, considering Machine Vision applications with Artificial Intelligence techniques for Industrial Inspection. Natural Language Processing was used to select the potential documents, by narrowing down those that were not aligned with the desired topic. The remaining documents were analyzed and compared with the proposed road map. This allowed the validation of the proposed concepts confirming their applicability. The results show that the road map is valid for current industrial inspections using Artificial Intelligence and Machine vision providing the support for the development of smarter machines into Industry 4.0 functionalities. Graphical abstract
Direct and spillover effects of social insurance reform: evidence from Vietnam

Abstract The introduction of the 2014 Social Insurance Law is a key reform of social protection in Vietnam. This article may be the first work quantifying the effects of the law’s introduction on family welfare. The propensity score matching combined with the difference-in-differences techniques is used to reduce bias. The study indicates that the generosity of the benefits provided by the law negatively affected the work duration and earnings among couples when only the wife is insured. In contrast, their sick leaves were positively influenced. Concerning spillover effects, wives significantly responded to the change of benefits in terms of work duration and earnings. The study also attempts to identify the mechanism underlying the effects by disaggregating them by family income and couples’ ages. The results suggest that low-income couples and young couples are sensitive to the law’s introduction. The article integrates knowledge from the fields of labor economics, social welfare, and public policy.
Online Gaming and Racism: Impact on Psychological Distress Among Black, Asian, and Latinx Emerging Adults

Although online racism occurs frequently and explicitly in online gaming (e.g., anti-Black hate speeches), no research has examined the psychological impact on racial/ethnic minority players. Thus, the current study examined the mediating role of online racism in the link between time spent in online gaming and psychological distress. Using data from 765 racial minority emerging adults in the United States and with gender controlled, time spent in online gaming predicted greater exposure to online racism, which in turn was linked to higher psychological distress. Post hoc multi-group comparison suggested that the findings were consistent with the Black group but neither the direct nor indirect effects of the model were significant for the Asian and Latinx groups. The results highlight the unjust digital burden and psychological costs of racism in online gaming among racial minority emerging adults, particularly among Black individuals. Limitations and implications for research are discussed.
Best Practices for the Deployment of Edge Inference: The Conclusions to Start Designing

The number of Artificial Intelligence (AI) and Machine Learning (ML) designs is rapidly increasing and certain concerns are raised on how to start an AI design for edge systems, what are the steps to follow and what are the critical pieces towards the most optimal performance. The complete development flow undergoes two distinct phases; training and inference. During training, all the weights are calculated through optimization and back propagation of the network. The training phase is executed with the use of 32-bit floating point arithmetic as this is the convenient format for GPU platforms. The inference phase on the other hand, uses a trained network with new data. The sensitive optimization and back propagation phases are removed and forward propagation is only used. A much lower bit-width and fixed point arithmetic is used aiming a good result with reduced footprint and power consumption. This study follows the survey based process and it is aimed to provide answers such as to clarify all AI edge hardware design aspects from the concept to the final implementation and evaluation. The technology as frameworks and procedures are presented to the order of execution for a complete design cycle with guaranteed success.
Detecting Fake News Tweets from Twitter

Online media has progressively obtained integral to the route billions of individuals experience news and occasions, frequently bypassing writers—the conventional guardians of breaking news. Occasions,in reality, make a relating spike of posts (tweets) on Twitter. This projects a great deal of significance on the validity of data found via online media stages like Twitter. We have utilized different managed learning techniques like Naïve Bayes, Decision Trees, and Support Vector Machines on the information to separate tweets among genuine and counterfeit news. For our AI models, we have utilized tweet and client highlights as our indicators. We accomplished a precision of 88% utilizing the Random Forest classifier and 88% utilizing the Decision tree. Notwithstanding, we accept that breaking down client records would build the accuracy of our models.
Study on Damage Evolution Mechanism of Rock-Soil Mass of Accumulation Slope Based on Shaking Table Test

To investigate the seismic dynamic characteristics of the accumulation slope, a slope of the Zheduo Mountain tunnel along the Sichuan-Tibet Railway in China was selected as the prototype, based on dimensional analysis and similarity principle, two groups of model tests were carried out at 50° accumulation slope and 60° accumulation slope to obtain the dynamic response influenced by different amplitude of seismic wave. A transfer function analysis method suitable for shaking table test is proposed. Based on the data pretreatment method of eliminating trend terms and digital filter, the frequency response function was calculated by method of average periodic chart. And the variation of frequency response function was analyzed by Pearson correlation coefficient. At last, the least square iteration method was used for modal analysis. It is found that the transfer function changes obviously when both the slopes are destroyed, the weak interlayer has a significant influence on seismic wave transmission. The modal analysis results show that with the increase of the excitation intensity, the natural frequency decreases and the damping ratio increases.
Inclusive leadership and team creativity: a moderated mediation model of Chinese talent management

Abstract In this study, we examine the impact of inclusive leadership—being open, available, and accessible—on team creativity. Based on componential theory of creativity, we propose a moderated mediation model in which (a) inclusive leadership promotes team creativity, (b) team empowerment mediates the positive relationship between inclusive leadership and team creativity, and (c) HRM system strength enhances the effect of team empowerment. Our hypotheses are supported by analysis of multiple-source data from 91 team leaders and 308 individual members in China. We discuss implications for leadership and talent management.
Effect of air drying temperature on phytochemical properties of brown seaweed Bifurcaria bifurcata

The purpose of this study was to determine the effects of convective air-drying at different temperatures (35, 50, 60 and 75°C) on the color of Bifurcaria bifurcata (BB) seaweed powders obtained after milling, the antioxidant activity and polyphenolic and carbohydrate content of the aqueous extracts obtained by ultrasound-assisted extraction. BB seaweed powders exhibited significant color differences between powders obtained from BB dried at 35ºC (yellowish-green) and 50–75 °C (brown). High air drying temperature (above 60ºC) significantly reduced the total polyphenolic, carbohydrate content and scavenging activity of aqueous extracts of BB. Keywords: Phaeophyceae Antioxidant activity Carbohydrates Color Polyphenols
Risk Management Model using Cause and Effect Analysis in Industrial Building Project

The purpose of this study is to determine the main potential risks that occur in the design planning stage of a construction project, especially in an Industrial Building project. Based on the available literature and the experiences of other authors and practitioners, a list of potential risks was developed. Risks events were initially categorized into technical, project management, commercial and external categories. Risks are evaluated by professional practitioners who have experience in construction projects. The evaluation includes the expected likelihood of the event and its impact on changes in scope of work. This study considers each risk among owners, consultants, contractors and others. The data collected were analyzed qualitatively and quantitatively to assess the severity and impact of the event. The recommended responses to major risks are introduced in this study. Keywords: risk management model, planning stage, industrial building.
Designing cross‐linked pyrrole‐thieno [3,4‐b] thiophene copolymer to push forward electrochemical performance and access flexible micro‐supercapacitor with ultra‐long cycling stability

While higher high specific surface area allows micro‐supercapacitor (MSC) electrode materials to have improved performance, it also tends to make them less stable thermodynamically and microstructurally, which can easily deteriorate and seriously affects their service life. So here, we have chosen a cross‐linked copolymer film structure as MSC electrodes. The pyrrole‐thieno [3,4‐b] thiophene (TbT) copolymer film (namely PPy‐co‐TbT) exhibits high specific capacity, which can reach 47.8 mF cm−2 (a specific volumetric capacitance of 23.9 F cm−3 and a specific gravimetric capacitance of 28.1 F g−1) at a current density of 0.1 mA cm−2 using LiCl/PVA gel electrolyte with ultra‐long cycling stability (capacitance retention after 50 000 charge/discharge cycles is still higher than 93%, which is the leading level in MSCs). The electrochemical performance of this cross‐linked copolymer is superior to that of the single‐component polymer, achieving a 1 + 1 > 2 effect. Both features of cross‐linking and copolymerization have positive effects on microelectrodes requiring stable microstructures and high performance. The structurally stable cross‐linked copolymer obtained by copolymerization design may become a durable material for next generation ultra‐long‐life, high‐performance micro‐supercapacitor electrodes and will be widely developed.
Seasonal Variations in Carnosic Acid Content of Rosemary Correlates with Anthocyanins and Soluble Sugars

Seasonal variations may influence the quality and quantity of biologically active ingredients in medicinal plants. Rosemary (Rosmarinus officinalis L.) a member of the Lamiaceae family, contains valuable antioxidant, anticancer and antibacterial substances, including Carnosic acid (CA). Here, the fluctuations of important active compounds present in rosemary leaf extracts collected in Golestan, Iran were studied during the year of 2012-2013. Plant phenolics, flavonoids, ascorbates, anthocyanins and soluble sugars were analyzed spectrophotometrically, while CA content was measured by High Performance Liquid Chromatography (HPLC). The highest amounts of total flavonoids occurred in autumn; while CA, phenolics, ascorbic acids and soluble sugars were greatest in winter, probably due to regional high precipitation and subtle winters. Most of the above indicated active compounds were low in early summer. Furthermore, total anthocyanins and soluble sugars showed significant positive correlations with CA over the year. These data suggest that rosemary extracts from the collected leaves in winter contain greater amounts of biologically active compounds; and can be used for standardization of plant materials harvested throughout a year.
Preliminary Investigation of the Carotenoid Compositionof Erythrobacter sp. Strain KJ5 by High-PerformanceLiquid Chromatography and Mass Spectrometry

Separation and identification of carotenoids (Cars) from aerobic marine bacterium Erythrobacter sp. strain KJ5 are reported. The cells of Erythrobacter sp. were grown in a Shioi medium at 28.5°C for three days. Among the four solvents tested, the mixture of methanol and acetone (3:7, v/v) was determined as the optimum solvent for Car extraction from the cells by measuring its absorption spectrum. The Cars were separated via reversed-phase high-performance liquid chromatography using a C8 column and identified by a UV-Vis photodiode array detector and an electrospray ionization mass spectrometry. Bacteriochlorophyll a was not detected from the extracts of cells grown under both light and dark conditions. At least 16 peaks of Cars were separated, wherein eleven peaks showed the same absorption spectrum with λmax at 452-453 nm and at 478-480 nm. The other five peaks had an additional absorption peak at 340 nm, which belongs to cis-isomeric form. Two peaks of Cars were identified to be zeaxanthin and β-carotene.
Analysis the Role of Oxygen, Light Intensity, Threshold Dose and Efficacy Improvement of Anti-Cancer via Type-II Photodynamic Therapy

The role of oxygen, cell killing threshold dose and efficacy improvement of anti-cancer via type-II phototherapy are analyzed by both analytic formulas and numerical data. Higher initial photoinitiator (PS) concentration (C0) and/or light intensity (I0) has a faster efficacy, due to faster depletion of PS and oxygen concentration. Without the external oxygen supply, higher C0 or I0 produces more efficient singlet oxygen, resulting a higher transient efficacy, but they reach the same steady-state value when oxygen is completely depleted. With the external oxygen supply, higher efficacy (with no steady-state limitation), or lower cell viability are achieved. The overall efficacy may be enhanced by resupply of PS or oxygen during the light exposure.
Filtering antennas: A technical review

Filtering antennas or filtennas realize both antennas and filter functions in a single structure with the sole purpose of reducing losses and size in the design of a radio system. This article presents a comprehensive view of various filtennas design techniques and their types, satisfying the requirements of different wireless communication standards. The codesign and synthesis approaches and multilayer structure, slot/slit, and parasitic elements are the frequently used techniques reported in the literature to date for the filtennas design. The codesign and synthesis approaches need an extra filter in the filtenna's design, thus making it more complex. Whereas multilayer, slot, and parasitic elements do not require additional filters, and help the radio design become compact in size. The individual elements, that is, filter and antenna used in the filtenna are designed by cutting slots, stacking, resonators, or metamaterial structures. There are two broad categories of filtennas, namely, planar and nonplanar. Most of the papers covered in this article are planar, whereas, under the nonplanar category, horn filtennas are analyzed. Performance in each case is compared in terms of size, complexity, and cost. Considering filtennas frequency of operation, they are classified as a single band, multiband, ultra‐wideband, and their MIMO configurations are analyzed to improve the reliability of the wireless radio system. Finally, various types of filtennas are compared, and the design guidelines are elaborated, mainly focusing on their application aspect to achieve more compact radio design solutions. The different techniques related to designing filtennas have been compared, and their glance details are provided for a more realistic assessment of individual techniques used till date. Thus, the authors believe that this review article presents a helpful guiding platform for researchers working on filtenna design.