Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieval of the Leaf Area Index from Visible Infrared Imaging Radiometer Suite (VIIRS) Surface Reflectance Based on Unsupervised Domain Adaptation

Several global leaf area index (LAI) products were generated using neural networks, but the training dataset for the neural networks was sensor specific, and the construction of the training dataset was time consuming. In this paper, an unsupervised domain adaptation-based method was proposed to estimate LAI from the Visible Infrared Imaging Radiometer Suite (VIIRS) surface reflectance dataset based on a training dataset constructed from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance dataset. A transfer component analysis (TCA) algorithm was first utilized to map the MODIS and VIIRS surface reflectance into the same subspace to reduce the distribution discrepancies between the MODIS and VIIRS surface reflectance. Then, the embedded data obtained from MODIS surface reflectance dataset, along with the LAI values produced by fusing the MODIS and the Carbon cYcle and Change in Land Observational Products from an Ensemble of Satellites (CYCLOPES) products, were employed to train general regression neural networks (GRNNs). Finally, for retrieving the LAI values, the embedded data acquired from the VIIRS surface reflectance dataset was input into the trained GRNNs. For multiple field sites with different biome types, we used this developed method to retrieve LAI values based on the VIIRS surface reflectance dataset. The results indicate that, based on the training dataset built from MODIS surface reflectance dataset, the domain adaptation-based retrieval method can effectively estimate LAI values from VIIRS surface reflectance dataset. By comparison with the VIIRS and MODIS LAI products, the retrieved LAI values with TCA are more consistent with the reference LAI values acquired from high-resolution remote sensing images. The coefficient of determination (R2) and root mean square error (RMSE) of the retrieved LAI values with TCA at all selected sites are 0.88 and 0.68, respectively. Furthermore, the accuracy of the retrieved LAI values with TCA is higher than the retrieved LAI values without TCA with the R2 0.81 and the RMSE 0.79.
Towards higher-level description of SLA-aware reconfiguration strategies based on state-machine

High number of European projects and international initiatives show an increased interest in the multi-cloud paradigm. One key need identified in these studies is an SLA-driven service model for multi-cloud environment. While offering a multi-cloud application, cloud consumer define reconfiguration strategies to avoid violating SLAs established with their customers. In this context, this paper presents an approach for enriching multi-cloud SLA representations with reconfiguration strategies. Advantages of this approach are twofold: (i) simplify SLA administration and (ii) limit SLA violations caused by reconfiguration strategies. We represent reconfiguration strategies based on state-machine formalism. Furthermore, we define thresholds to guarantee their compliance with multi-cloud SLAs and anticipate SLA violations. An implementation of the approach is presented in the paper and illustrates how these thresholds are computed.
Design of planar diplexers with improved isolation using the tunable transmission zeros of a dual-mode cavity filter

A substrate integrated waveguide dual-mode single cavity filter with two inclined slots on top metal plane provides two transmission zeros. It is shown that the feed offset as well as the slot offset both can be used to tune the zeros over a wide range of frequencies. Leakage loss from the slot is negligibly small. Two bandpass filters are fabricated to validate the predicted zero variation. Further, tunability of the zeros is utilised to greatly improve the isolation characteristics of two X-band planar diplexers. Measurement results show that the isolation is better than 30 dB even if the channel separation is as close as 5% of the average frequency. The effect of packaging on the filter characteristics is also presented.
Retrospective analysis of the spread of bacterial poultry diseases on the territory of Ukraine for the period 2012–2020

meets human needs for high-quality protein products (poultry meat, eggs) and characterized by rapid return on investment. infectious of retrospective analysis of spread of these diseases in analyzing systematizing the results of bacteriological investigations. In order to analyze the spread of bacterial diseases of poultry in of regions in analyzed data on 20 diseases of poultry, namely: hemophilosis, infectious enterotoxemia, yersiniosis, campylobacteriosis, colibacteriosis, coligranulomatosis, klebsiella, listeriosis, mycoplasmosis, neisseriosis, pasteurellosis, pathogenic proteus, pneumo- coccosis, pseudomonosis, pullorosis, septicemia, staphylococcosis, streptococcosis and tuberculosis. coligranulomatosis 0.05% and hemophilosis 0.02%. According to the results of bacteriological research of poultry for such diseases as yersiniosis, campylobacteriosis and mycoplasmosis – no positive test was found for the entire analyzed period. According to the results of ecological and geographical analysis, the heterogeneity of the nosological profile of bacterial diseases of poultry in different regions of Ukraine was established.
Interfacial and Electrical Characterization in MOSFETs with CeO 2 Gate Dielectric

Dept. of Electronic Engineering, Ming Chuan University, Taiwan No. 5, De-Ming Rd., Gui-Shan, Taoyuan County 333, Taiwan *Tel: +886-3-3507001 ext 3753, Fax: +886-3-3593877, E-mail: fcchiu@mcu.edu. tw Institute of Mechatronic Engineering, National Taipei University of Technology, Taiwan 1, Sec. 3, Chung-Hsiao E. Rd., Taipei 106, Taiwan Institute of Electronics Engineering, National Tsing-Hua University, Taiwan
A Technology Review of Energy Storage Systems, Battery Charging Methods and Market Analysis of EV Based on Electric Drives

The transportation sector is by far the largest oil consumer making it a prime contributor to air pollution. EVs (Electric vehicles) will be beneficial to the environment and will help to alleviate the energy crisis due to their low dependence on oil and negligible emissions. Technology innovation in EVs is of significant interest to researchers, companies, and policy-makers in many countries. EVs integrate various kinds of distinct technologies where some of the important factors in considerations related to EVs are: a wide range of electrical drive configurations; advanced electronics that enable automotive innovations; meeting the challenges of automotive electronics; electrifying transportation in the future. This paper reviews the recent progress in EV technology, which consists of various motor drives applied in EV propulsion, classification of EVs such as BEV, PHEV, HEV, FCEV, and types of energy storage system with chargers, and software simulating devices. This paper also highlights the EV market with various challenges. The main findings of this research are: (1) Battery technology is the EV's bottleneck. Lithium-ion batteries for vehicles have high capacity and large serial-parallel numbers, which, coupled with problems such as safety, durability, uniformity, and cost, impose limitations on the wide application. (2) Incentives and encouragement for EV owners should be tailored to their specific needs in order to improve their socioeconomic standing. (3) Hyundai, MG Motors, Tesla, and Tata Motors appear to be the key players in India's critical subdomains of the EV market. (4) EV simulation software is necessary for vehicle design and development before the mass production of EVs. (5) PMSM has the potential to provide a high torque-to-current ratio, a high power-to-weight ratio, high efficiency, and robustness. Currently, the BLDC (Trapezoidal SPMSM) motors are the most preferred motors for electric vehicle applications due to their traction characteristics.
IT fit on auditors’ performance in Yemen

The alignment between the importance and utilisation of IT (IT fit), and the impact of IT fit on organisational performance has been an issue of concern for many researchers. Therefore, this study examined the effect of organisational, social, individual, and environmental factors on IT fit and on auditors’ performance as well as the influence of IT fit on auditors’ performance. It also examined the mediating effect of IT fit on the relationship between these independent variables and auditors’ performance. Data from 274 auditors were analyzed using the PLS-SEM. The results indicate that auditors perceived their utilisation of IT utilisation to be less than the importance of IT, hence providing important insights into the importance and the utilisation of technologies in the context of audit work in Yemen. The findings suggest that information systems audit in Yemen is still at the minimum level. Further analyses on the effect of the independent variables, namely IT knowledge, facilitating resources, IT trust, competitive pressure, management support, client’s complexity of the IT system, internalisation and cognitive style, on IT fit show them to be positive and significant. Interestingly, IT fit is found to be a mediator between these eight variables and auditors’ performance. This study also finds that management support, IT knowledge, IT trust, internalisation, IT training, client’s complexity of the IT System, cognitive style and IT fit have positive and significant effects on auditors’ performance. The three most important variables are IT knowledge, facilitating resources, and management support. The findings suggest the important role of IT fit in increasing the effect of these variables on auditors’ performance. Therefore, audit firms and professional bodies need to focus on the issue of IT fit to increase the performance of their auditors.
Effects of diclofenac on the gametes and embryonic development of Arbacia lixula

Abstract Diclofenac (DCF), a non-steroidal anti-inflammatory drug (NSAID), is among the main pollutants of aquatic environments. Nevertheless, even if several authors evaluated its effects on marine organisms, no work has ever analysed its impact on the sea urchin Arbacia lixula. The purpose of this study was to analyse, for the first time, the impact of DCF at different concentrations (50 mg/l, 5 mg/l, 0.5 mg/l, 0.05 mg/l) on A. lixula embryos and gametes to indicate possible safe minimum levels of release of this drug in marine environments. Our results showed significant concentration-dependent effects on embryonic development (decrease in the number of developed embryos and increase in the quantity of degenerated eggs) and significant levels of bioaccumulation at DCF concentrations of 50 mg/l in both gametes and embryos. DCF showed a significant impact on the fertilisation of A. lixula due to its effects on gametes, confirming the possibility of environmental risk and highlighting the need to improve wastewater treatment and drug disposal processes.
Examining the Phenomenon of Sharenting

Sharenting was coined by adding the terms "parenting" and "sharing" to describe parents' tendency to post about their children on social media apps (Sharenting, n.d). Technological advances increased the availability of social media networking apps and made creating profiles easier. As a result, sharenting has become more prevalent among parents. Exploring this phenomenon is really complicated and the most controversial implication is the privacy intrusion children are subjected to. This implication has been thoroughly explored in research, and although it is interesting it is beyond the scope of this paper. Instead, the literature review will analyze the motive of sharenting, and multiple factors that affect it (Holiday et.al., 2020; Briazu et.al., 2021). The notable implications of sharenting include the pressing issue of the privacy paradox, and the distortion of children’s digital representations (Fox et.al., 2022; Ouvrein & Verswijvel, 2019). Sharenting is controversial but current research indicates that boundary negotiation between children and parents is necessary to avoid frustrations (Lipu & Siibak, 2019).
CrowdIM: Crowd-Inspired Intelligent Manufacturing Space Design

Crowd-inspired intelligent manufacturing space (CrowdIM) aims to leverage the aggregated power of heterogeneous human–machine–things (HMT) agents for improving the efficiency of intelligent manufacturing. A significant scientific problem in CrowdIM is how to improve individual skills and crowd intelligence through cooperation, complementation, competition, and confrontation among HMT agents. The emergence mechanism of biological crowd intelligence provides an inspiration to address this challenge. This article explores the mapping mechanisms between natural crowd intelligence and CrowdIM, from the aspects, such as collective dynamics, self-adaptive mechanism, crowd intelligence optimization, graph structure mapping model, evolutionary game dynamics, multiagent learning, and so on. We further propose a general model of CrowdIM and expound it through a typical case study.
Latency-Optimized Design of Data Bus Inversion

This paper proposes two new encoders for data bus inversion (DBI), which conventionally uses a majority voter to pick a data representation that minimizes switching activities and thus reduces the corresponding energy consumption. The new encoders employ simpler approximate voters comprising only two gate levels, which improve latency more than twice while still achieving switching activity savings by 9% and 11%, respectively. Although the proposed voters are not always accurate, the errors in the voters do not affect the correctness of data movement. We report various metrics, including latencies, areas, and operating powers, regarding five different designs, two proposed designs along with three conventional designs, based on 65-nm process implementations.
Application of wavelet energy spectrum in railway track detection

The abrupt change of train vibration energy is an important basis for judging track defects or deteriorations.Based on the continue wavelet transform′s detailed performance in time-scale mesh generation,and combined with the probability method,the time,scale and time-scale wavelet energy spectrum of train vibration response and track irregularity signal was established after the calculating and analyzing of track irregularity and train vibration energy,then the combined diagnosis and analysis was conducted.Through the track inspection data analysis for Shanghai-Nanjing Passenger Dedicated Railway and ShenchiHuanghua Heavy Haul Railway,the results show that the method this paper proposed can effectively extract the type,damage degree and space position of small disease,and realize the evaluation of track irregularity′s overall state.This offered a new technical approach for railway track disease diagnosis and state evaluation.
A Unified View of DI- and ETD-FDTD Methods for Drude Media

A unified view of direct-integration (DI) and exponential-time-differencing (ETD) methods to incorporate Drude media, such as isotropic plasma and microwave graphene, into finite-difference time-domain (FDTD) simulators is provided. To this end, the Drude constitutive relation is expressed in integral form and the DI integrators are obtained by applying quadrature rules. Analogously, the ETD integrators are obtained by starting from the variation of constants formula and applying the same quadrature rules as in the DI case. This approach allows one to directly compare the two families of methods. In addition, the accuracy of each integrator is discussed and the stability condition of the resulting FDTD schemes is derived in exact closed form by applying the von Neumann method.
Rendimiento de corderos alimentados con ensilaje como alimento total a base de nopal

This study aimed was to evaluate the intake, apparent digestibility, water balance, nitrogen balance, and productive performance in lamb fed cactus pear silage associated with tropical forages. Forty male intact crossbred lambs, with an initial body weight of 18.85 ± 1.2 kg, were used in the experiment. The experimental design was completely randomized, with 5 treatments and 8 replications. The treatments consisted of diets with different proportions of buffelgrass and wheat bran as sources of neutral detergent fiber (NDF), in total feed silage (TFS) based on cactus pear: TFS1 - 279 g/kg of buffelgrass; TFS2 - 240 g/kg of buffelgrass and 17 g/kg of wheat bran; TFS3 - 198 g/kg of buffelgrass and 34 g/kg of wheat bran; TFS4 - 108 g/kg of buffelgrass and 74 g/kg of wheat bran; TFS5 – 118 g/kg of wheat bran. The lowest NDF intake was found in lambs that consumed TFS5 (402 g/d). The non-fibrous carbohydrates apparent digestibility was higher for TFS5, while the NDF apparent digestibility of TFS5 and TFS4 was higher than TFS1. Diets promoted an average daily weight gain of 180.8 g/d. Under experimental conditions, the use of forage cactus pear and concentrate in the form of total mixed rations silage leads to greater intake of crude protein, non-fibrous carbohydrates, ether extract and greater digestibility of non-fibrous carbohydrates and neutral detergent fiber, however, all diets were viable in the feed of confined sheep, providing gains of up to 198 g/d according with the formulation of the diet.
Technology and Local State Capacity: Evidence from Ghana

This paper studies the role of technology in local-government tax collection capacity in the developing world. We first conduct a new census of all local governments in Ghana to document a strong association between technology use and property tax billing, collection and enforcement. We then randomize the use of a new revenue collection technology within one large municipal government. Revenue collectors using the new technology delivered 27 percent more bills and collected 103 percent more tax revenues than control collectors. Collectors using the new technology learned faster about which households in their assigned areas were willing and able to make payments. We reconcile these experimental findings in a simple Beckerian time-use model in which technology allows revenue collectors to better allocate their time towards households that are the most likely to comply with taxpaying duties. The model’s predictions are consistent with experimental evidence showing that treatment collectors are more likely to target households with greater liquidity, income, awareness of taxpaying duties, and satisfaction with local public goods provision. *james.dzansi@theigc.org, anders jensen@hks.harvard. edu, lagakos@bu.edu, henry.telli@theigc.org. For helpful comments and guidance on this project we thank Ray Fisman, Andrew Foster, Gordon Hanson, Asim Khwaja, Craig McIntosh, Karthik Muralidharan, Nii Sowa, Chris Udry, Silvia Vannutelli and seminar participants at Brown, BU, Harvard, Peking HSBC Business School and Williams. For outstanding research assistance we thank Manon Delvaux, Radhika Goyal, Mary Nyarkpoh, Isaac Otoo and Cynthia Zindam. For help implementing a pilot version of the experiment we thank IPA Ghana. For financial support we thank the International Growth Centre and J-PAL. All potential errors are our own.
Air traffic development in ASEAN: an airport capacity analysis

The ASEAN Member States have decided to sign agreements which define the milestones for liberalization of air transport in the region (January 2015). The air transport liberalization up to the 5th freedom right therefore removes the frequency and capacity constraints existing in bilateral air service agreements between ASEAN member states. The interesting question is then whether to know if the liberalization will lead to benefits for the economies of the countries. These benefits could only occur if some conditions are fulfilled: the air transport sector has to be able to receive more traffic. We propose in this paper a relevant methodology to analyse the conditions under which liberalization would benefit to the development of air traffic. This analysis is focused on the airports as they represent the bottleneck of the air transport activity. We then, using data from the OAG database and from the ministry of transport, apply our analysis to the Indonesian market.
The Impact of Intestinal Microorganisms and Their Metabolites on Type 1 Diabetes Mellitus

Background Type 1 diabetes mellitus (T1DM) is an autoimmune disease with a complex etiology comprising numerous genetic and environmental factors; however, many of the mechanisms underlying disease development remain unclear. Nevertheless, a critical role has recently been assigned to intestinal microorganisms in T1DM disease pathogenesis. In particular, a decrease in intestinal microbial diversity, increase in intestinal permeability, and the translocation of intestinal bacteria to the pancreas have been reported in patients and animal models with T1DM. Moreover, intestinal microbial metabolites differ between healthy individuals and patients with T1DM. Specifically, short-chain fatty acid (SCFA) production, which contributes to intestinal barrier integrity and immune response regulation, is significantly reduced in patients with T1DM. Considering this correlation between intestinal microorganisms and T1DM, many studies have investigated the potential of intestinal microbiota in preventive and therapeutic strategies for T1DM. Objective The aim of this review is to provide further support for the notion that intestinal microbiota contributes to the regulation of T1DM occurrence and development. In particular, this article reviews the involvement of the intestinal microbiota and the associated metabolites in T1DM pathogenesis, as well as recent studies on the involvement of the intestinal microbiota in T1DM prevention and treatment. Conclusion Intestinal microbes and their metabolites contribute to T1DM occurrence and development and may become a potential target for novel therapeutics.
F-test and z-test for high-dimensional regression models with a factor structure

The classic F-test and z-test can fail for high-dimensional regression models. This paper addresses this problem, especially for the case where the covariates contain a latent factor structure. We first use a new technique, the cross-section averages (CSA) of covariates, to estimate the latent factors. We then develop two F-type tests, namely, the Wald test and the F-test, to assess the overall significance of covariates. If the covariates are tested jointly significant, we next carry out a CSA-based z-test to sequentially test the significance of covariates one at a time. Compared with the existing approaches in the literature, which often use principal component analysis (PCA) to estimate the latent factors, the new tests do not depend on the accurate estimation of the unknown degrees of freedom, or on the acquisition of unknown eigenvalues. Therefore, they can reduce the uncertainty arising from the estimation of unknown quantities. We show the power and model selection consistency of these tests and propose a follow-up ratio-type test to further control the model size. Numerical simulations and a real data analysis show the competitive performance of these CSA-based tests.