Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of Sheltered Workshops. Does Legal Status Matter?

Social enterprise pursues both social and economic goals and is recognized as a formula for achieving sustainable development. Sheltered workshops (SWs) are a manifestation of this phenomenon, their main objective being the labor market integration of disabled people. In this paper, the efficiency of SWs has been studied taking into account the operational and the core social aspects, as well as their distinct nature, namely for-profit or non-profit status. Additionally, we have analyzed the relationship between the social efficiency and the economic returns of these entities. To do this, a semiparametric methodology, combining different data envelopment analysis (DEA) models with truncated regression estimation has been used. It is the non-profit and top-performing SWs that achieve the best social and economic efficiency. For-profit and low-performing SWs show further reductions in social efficiency as a result of the economic crisis and uncertainty in subsidy-related public policies. Their extensive social proactiveness and high economic strength in the crisis period positively influenced their social and economic efficiency. We have also proven that it is the most profitable SWs that have the greatest social efficiency. We consider that our results constitute a useful complement to other evaluation models for social enterprise.
On the Use of a Domain Decomposition Strategy in Obtaining Response Statistics in Non-Gaussian Seas

During recent years, thorough experimental and numerical investigations have led to an improved understanding of dynamic phenomena affecting the fatigue life and survivability of offshore structures, e.g., ringing and springing and extreme wave impacts. However, most of these efforts have focused on modeling either selected extreme events or sequences of highly nonlinear waves impacting offshore structures, possibly overestimating the actual load to be experienced by the structure. Overall, not much has been done regarding short-term statistics. Although clear non-Gaussian statistics and therefore higher probabilities of extreme waves have been observed in random seas due to wave–wave interaction phenomena, which can impact short-term statistics for the structural load, they have not been studied extensively regarding the assessment of the dynamic behavior of offshore structures. Computational fluid dynamics (CFD) models have shown their viability for studying wave–structure interaction phenomena. Despite the continuously increasing computational resources, these models remain too computationally demanding for applications to the large spatial domains and long periods of time necessary for studying short-term statistics of non-Gaussian seas. Higher-order spectral (HOS) models, on the other hand, have been proven to be efficient and adequate in studying non-Gaussian seas. We therefore propose a one-way domain decomposition strategy, which takes full advantage of the recent advances in CFD and of the computational benefits of HOS. When applying this domain decomposition strategy, it appeared to be possible to deduce response statistics regarding the impact of nonlinear wave–wave interactions.
Side-channel Analysis using Deep Learning on Hardware Trojans

A power side-channel analysis is proposed to nd the correct key in hardware trojan affected AES by evaluating correlation between every sub-key guesses. A deep learning method for side-channel analysis (SCA) is proposed, which consists of two phases-characterization and attack. Multilayer perceptron (MLP) and convolutional neural networks(CNN) are used as the models to determine the SCA and their performances are evaluated. Two kinds of desynchronization were used, where maximum possible value with which the trace can be shifted was 0 in rst and 100 in the second. SCA is performed in these desynchronized traces also.
Active Modulation Strategy for Capacitor Voltage Balancing of Three-Level Neutral-Point-Clamped Converters in High-Speed Drives

In this article, the equivalent relationship between the nearest-three-virtual space vector and carrier-based pulsewidth-modulation scheme is established based on space vector coordinate for a three-level neutral-point-clamped (3L-NPC) converter. Moreover, to solve the neutral-point voltage imbalance problem of the studied 3L-NPC converter-fed high-speed drives, an active modulation strategy with the generalized bias-offset injection technique is proposed. Meanwhile, the excessive computational burden is significantly overcome by the fast calculation approach. The effectiveness of the proposed modulation algorithm is validated through both simulation and experimental results obtained from a 45 kW, 32 kr/min aircraft electric starter/generator prototype system.
Regional Analyses of Rainfall-Induced Landslide Initiation in Upper Gudbrandsdalen (South-Eastern Norway) Using TRIGRS Model

In Norway, shallow landslides are generally triggered by intense rainfall and/or snowmelt events. However, the interaction of hydrometeorological processes (e.g., precipitation and snowmelt) acting at different time scales, and the local variations of the terrain conditions (e.g., thickness of the surficial cover) are complex and often unknown. With the aim of better defining the triggering conditions of shallow landslides at a regional scale we used the physically based model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope stability) in an area located in upper Gudbrandsdalen valley in South-Eastern Norway. We performed numerical simulations to reconstruct two scenarios that triggered many landslides in the study area on 10 June 2011 and 22 May 2013. A large part of the work was dedicated to the parameterization of the numerical model. The initial soil-hydraulic conditions and the spatial variation of the surficial cover thickness have been evaluated applying different methods. To fully evaluate the accuracy of the model, ROC (Receiver Operating Characteristic) curves have been obtained comparing the safety factor maps with the source areas in the two periods of analysis. The results of the numerical simulations show the high susceptibility of the study area to the occurrence of shallow landslides and emphasize the importance of a proper model calibration for improving the reliability.
Teaching Strategic Decision Making: Business Management Simulations as a Tool for Generative Learning

This paper takes a generative learning perspective to study the pedagogical benefits of employing simulated virtual learning environments to replicate real world business decision making. Simulated business games have been growing in importance on many business programmes over the last twenty years, and the increase in online delivery due the Covid 19 pandemic has heightened the focus on this type of virtual delivery. As members of a management students take part in running a simulated business gaining real management experience. Students make weekly strategic decisions for their company, market results are then released for the company each week and the students need to react. The students compete against each other bringing a real element of competition to the experience. This investigation focuses on the student’s perspective of their learning experience through a generative learning analysis of their individual reflections. The findings highlight the development of crucial management skills in the areas of analysis, teamwork, presentations and decision making. The main contribution of the paper is the confirmation of a generative learning cycle between course content, engagement in the simulation and skills development. These findings provide a framework for educators integrating a simulation of this type into their programmes.
The Effect of Austerity Packages on Government Popularity During the Great Recession

Abstract During the Great Recession, governments across the continent implemented austerity policies. A large literature claims that such policies are surprisingly popular and have few electoral costs. This article revisits this question by studying the popularity of governments during the economic crisis. The authors assemble a pooled time-series data set for monthly support for ruling parties from fifteen European countries and treat austerity packages as intervention variables to the underlying popularity series. Using time-series analysis, this permits the careful tracking of the impact of austerity packages over time. The main empirical contributions are twofold. First, the study shows that, on average, austerity packages hurt incumbent parties in opinion polls. Secondly, it demonstrates that the magnitude of this electoral punishment is contingent on the economic and political context: in instances of rising unemployment, the involvement of external creditors and high protest intensity, the cumulative impact of austerity on government popularity becomes considerable.
Spatiotemporal feedforward between PKM2 tetramers and mTORC1 prompts mTORC1 activation

Most mammalian cells couple glucose availability to anabolic processes via the mTORC1 pathway. However, the mechanism by which fluctuations in glucose availability are rapidly translated into mTORC1 signals remains elusive. Here, we show that cells rapidly respond to changes in glucose availability through the spatial coupling of mTORC1 and tetramers of the key glycolytic enzyme pyruvate kinase M2 (PKM2) on lysosomal surfaces in the late G1/S phases. The lysosomal localization of PKM2 tetramers enables rapid increases in local ATP concentrations around lysosomes to activate mTORC1, while bypassing the need to elevate global ATP levels in the entire cell. In essence, this spatial coupling establishes a feedforward loop to enable mTORC1 to rapidly sense and respond to changes in glucose availability. We further demonstrate that this mechanism ensures robust cell proliferation upon fluctuating glucose availability. Thus, we present mechanistic insights into the rapid response of the mTORC1 pathway to changes in glucose availability. The underlying mechanism may be applicable to the control of other cellular processes.
Optimization of Centralized Equalization Systems Based on an Integrated Cascade Bidirectional DC–DC Converter

This article presents a novel integrated cascade bidirectional dc–dc converter for optimizing a centralized charge equalization system. Through the integrated cascade structure, the polarity switches and the bidirectional dc–dc converter in the traditional centralized system are integrated, and the cells with different voltage polarities are equalized by controlling the operating state of the converter. Compared with the conventional methods, the number of active switches is significantly reduced, leading to a more compact size and a higher reliability. Moreover, with a phase-shifted pulsewidth modulation strategy, the peak value of the transformer current is reduced and the soft-switching operation is realized, thus greatly reducing the transformer and switching losses. Finally, the experimental results on 13 series-connected battery cells show that the proposed scheme exhibits the excellent performance in terms of equalizing efficiency and speed. The performance improvement of the proposed equalizer is further validated by a systematic comparison with the conventional centralized equalization methods.
Sensitivity Analysis for Geometrical Parameters of BGA in Flip-Chip Packaging Under Random Shear Stress and Thermal Temperature

The ball grid array (BGA) is a type of popular and competitive package in electronic flip-chip packaging due to its feasibility in high density integrated circuits and convenience in the product design process. However, the effects of geometrical parameters on the product reliability and safety under complicated operating situations are not clear. In this article, an independent solder ball and four typical BGA cases are compared and analyzed based on the finite element (FE) method. The coupled random shear stress and thermal temperature are simulated in the FE models by the Latin hypercube sampling (LHS) method. According to the sensitivity analysis, the edges of the solder ball are the most dangerous places, which has the qualitative agreement with the experimental results. The complete grid array in the first BGA case with homogeneous stress and strain distribution is the most reliable and competitive design. Furthermore, the normal and Weibull distributions are not suitable to present the stochastic response of solder balls in flip-chip packaging under random coupled mechanical and thermal stress. In order to effectively improve packaging performance and reliability, the radius of the solder ball acts as the key factor, while the upper and lower height of the solder ball, as well as the pitch along the $X$ - and $Y$ -directions, are all feasible and potential for the geometrical optimization. However, the small scale of the solder ball causing microstress concentration points and discontinuous volumes is the essential challenge for industrial manufacturing. The work in this article provides helpful references to the industrial electronic package geometrical optimal design.
Attending to data: Exploring the use of attendance data within the datafied school

Contemporary schooling is seen to be altering significantly in light of a combined ‘digitisation’ and ‘datafication’ of key processes. This paper examines the nature and conditions of the datafied school by exploring how a relatively prosaic and longstanding school metric (student attendance data) is being produced and used in digital form. Drawing on empirical data taken from in-depth qualitative studies in three contrasting Australian secondary schools, the paper considers ‘anticipatory’, ‘analytical’ and ‘administrative’ aspects of how digitally-mediated attendance data is produced, used and imagined by school staff. Our findings foreground a number of constraints, compromises and inconsistencies that are usually glossed-over in enthusiasms for ‘data-driven’ education. It is argued that these findings highlight the messy realities of schools’ current relationships with digital data, and the broader logics of school datafications.
Prevalence, Cognitive Characteristics and In uence Factors of Amnestic Mild Cognitive Impairment among Community-dwelling Older Adults in Chengdu, China

Peiyuan Qiu Department of Epidemiology and Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu Yan Cai Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu Yangyang Wang Department of Epidemiology and Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu Shiyi Liao Department of Epidemiology and Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu Yunbo Nie School of Medicine and Dentistry, University of Rochester, New York Ye Wang Department of Psychiatry and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu Shan Rao Chengdu Jinxin Mental Diseases Hospital, Chengdu Weihong Kuang (  kwhhlj@scu.edu.cn ) Department of Psychiatry and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu
THz 2-D Frequency Scanning Planar Integrated Array Antenna With Improved Efficiency

A THz 2-D frequency scanning planar integrated array antenna is developed in this letter. Eight THz leaky-wave antennas are combined with a true-time-delay (TTD) phase-shifting feeding network to steer the beam in two directions by sweeping the frequency. Several H-plane 90° bends with linearly increased length are adopted to achieve the scalable TTD phase shift. The feeding lines are closely spaced to reduce the phase-shifting network occupied area in this progressive phase-shifting scheme. Besides, the E-plane 180° bend is used to construct the double-layer phase-shifting network, maintain the number of multiple scanning sweeps and improve the aperture efficiency. Moreover, in the used microelectromechanical systems (MEMS) fabrication technique, the minimum height of the radiation slot is 0.2 mm, which is too thick and deteriorates the radiating performance. When the double-layer step-profiled radiating slot is used instead of the thick slot, a THz leaky-wave antenna with higher radiation efficiency and better gain flatness can be achieved. Finally, a prototype antenna is fabricated and experimentally validated. The operating frequency range is 325–400 GHz and the beam scanning range is 22.7° × 60° with a maximum radiation gain of 25.28 dBi.
Evaluation of Sugarcane Agroindustrial Wastes as Substrate in Soilless Cultivation of Tomato (S. lycopersicum Linnaeus): Effect of Substrate Composition on Yield Production

Traditionally, biochar is generally proposed to substitute Canadian Sphagnum peat moss. Sugarcane bagasse, filter press mud and sugarcane bagasse ash were mixed in different ratios and proposed as an alternative to substitute commercial Sphagnum peat moss (SPM) for the soilless cultivation of tomato (S. lycopersicum Linnaeus). The choice of the agroindustrial waste ratio was performed from physical-chemical sample characterization. During vegetable production, an adequate ratio was evaluated based on plant height, substrate pH, number of leaves, yield, and fruit size. The addition of essential macro- and micro-nutrients was performed manually. The results show that as-received materials contain different minerals with a structure that corresponds to the quartz, cristobalite, and feldspar phases. A morphology composed of lamellate structures was observed for sugarcane bagasse, whereas the filter press mud and the sugarcane bagasse ash presented compact agglomerates with a surface area of 1.60, 3.78, and 1.07 m2 g−1, respectively. The properties of each component promote the water adsorption, retention and releasing capacity. Important differences were observed as the quantity of filter press mud increased, but also it is required an amount of sugarcane bagasse above of 18 wt% to reach a superior performance. This work demonstrated that, in adequate quantities, agroindustrial wastes can be used as a soilless substrate for growing tomatoes in greenhouse, reducing their disposal problems.
Effectiveness of some resistance inducers for controlling carnation vascular wilting caused by Fusarium oxysporum f. sp. dianthi

Abstract The effect of different resistance inducers against carnation vascular wilting caused by Fusarium oxysporum f. sp. dianthi (Fod) was evaluated, as well as its relation with the content of phenols and flavonoids in roots of the carnation plants. Indexed cuttings of carnation (Dianthus caryophyllus L.) were used with three-weeks of rooting (variety Solex susceptible to the disease). The resistance inducers: Ascorbic Acid, Salicylic Acid, Thiamine and Potassium Phosphite, were applied by spray or drench before Fod inoculation. Compared to controls, it was found that disease incidence and severity measured as the area under the disease progress curve, decreased with the application of all inductors except for K3PO3 spray-applied treatment. Plants treated with thiamine showed, in addition, an increase in the content of phenols and flavonoids. These results suggested the potential of thiamine as a resistance inducer in the management of carnation vascular wilting caused by Fusarium oxysporum f. sp. dianthi.
Financial Behavior of Family Businesses: A Bibliometric and Systematic Literature Review

The aim of this paper is to identify some holistic insights and to assess the evolution of the “financial behavior of family businesses” as a field of research. Authors performed an objective, and comprehensive analysis using a bibliometric and systematic review. Thus, three major databases (Scopus, Web of Science, and EBSCO host) were queried and 256 retrieved publications were analyzed. Findings showed an increasing dynamic of the number of publications from 1990 to 2020. The text mining of retrieved publications enables a thematic analysis of the intellectual streams and key concepts underpinning financial policies within family businesses. From a managerial perspective, a review of literature on financial behavior can help raise awareness among family members, managers, and policymakers about family business’ peculiarities that make the financial decisions complex. Finally, this paper reveals trends but also some knowledge gaps to consider in future research about the study of financial decisions within the context of family businesses.
Analyzing the photonic band gaps in two-dimensional plasma photonic crystals with fractal Sierpinski gasket structure based on the Monte Carlo method

In this paper, the properties of photonic band gaps (PBGs) in two types of two-dimensional plasma-dielectric photonic crystals (2D PPCs) under a transverse-magnetic (TM) wave are theoretically investigated by a modified plane wave expansion (PWE) method where Monte Carlo method is introduced. The proposed PWE method can be used to calculate the band structures of 2D PPCs which possess arbitrary-shaped filler and any lattice. The efficiency and convergence of the present method are discussed by a numerical example. The configuration of 2D PPCs is the square lattices with fractal Sierpinski gasket structure whose constituents are homogeneous and isotropic. The type-1 PPCs is filled with the dielectric cylinders in the plasma background, while its complementary structure is called type-2 PPCs, in which plasma cylinders behave as the fillers in the dielectric background. The calculated results reveal that the enough accuracy and good convergence can be obtained, if the number of random sampling points of Mont.
A literature survey on recurrent attention learning for text classification

Witha rapid rise of complex data every year needs more enrichment in machine learning methods to provide vigorous and accurate data classification. Deep learning models such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory(LSTM) have accomplished to obtain better results in the domain of computer vision, object recognition, speech recognition and natural language processing compared to traditional machine learning algorithms. This paper mainly discusses about the blending of attention mechanism with various deep learning models for text classification which improves the performance of text classification task.