Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and Phytotoxicity Assessment of Successive Application of Methyl Bromide and Cold Treatment on Export Strawberry Fruits

Simple Summary Spotted wing Drosophila, Drosophila suzukii, is an important quarantine pest in Korea due to its oviposition behavior. In this study, insecticidal effects of methyl bromide (MB) alone and successive application of methyl bromide and cold treatment were compared to examine their potential to reduce methyl bromide usage and shorten the cold treatment periods. Eggs, larvae, and pupae were subjected to treatment with fumigants to determine the 50 and 99% lethal concentration time values. The results show that, through treatment with methyl bromide plus cold, control can be achieved at lower concentrations than for treatment with methyl bromide alone and with shorter treatment periods than for treatment with cold treatment alone. Phytotoxic effects from successive treatment on strawberry were not observed. Therefore, methyl bromide plus cold treatment can effectively control D. suzukii in strawberry without damage to fresh fruits. Abstract Recently, spotted wing Drosophila, Drosophila suzukii, is globally prevalent and causes agricultural losses to many fruits. To export Korean strawberry, methyl bromide fumigation is required to remove D. suzukii infestations, but Korean strawberry farmers are worried about fruit damage because methyl bromide can cause phytotoxicity on fresh commodities. In this report, we assessed the efficacy and phytotoxicity of single and successive application of methyl bromide and cold treatment on an export variety of strawberry to reduce fruit damage. The currently recommended dosage of methyl bromide, 40 g/m3 for 3 h at 18 °C, was enough to control all stages of D. suzukii without phytotoxicity. A dosage of 20 g/m3 of methyl bromide treatment for 3 h, followed by 1 d of cold (0 °C) treatment, showed 100% mortality in all growth stages of D. suzukii without fruit damage. Successive application of methyl bromide and cold treatment shows potential as a method of decreasing phytotoxicity and reducing the use of methyl bromide for environmental considerations.
A multi-attribute congestion-driven approach for evaluation of power generation plans

Summary Independent System Operator (ISO) needs to draw sufficient attention to transmission congestion management (TCM) for guaranteeing power system security when deciding about a proposed power generation plan (PGP). To this end, this paper proposes a multi-attribute decision-making approach. The proposed decision-making procedure for a considered PGP includes three major stages: (1) Obtaining different attributes of TCM for all considered scenarios, i.e. the normal operating case and contingencies due to outage of power system components before and after implementation of the PGP. (2) Identifying the effective scenarios before and after the implementation of the PGP. For this purpose, two multi-attribute decision-making approaches are applied, one of which ISO could adopt based on its managerial point of view: (a) A conjunctive approach in which scenarios meeting minimal predefined thresholds for their obtained TCM attributes are selected. (b) A pessimistic approach based on data envelopment analysis introduced by Charnes, Cooper, and Rhodes (CCR-DEA) in which the severest scenarios are selected. 3) Calculating each scenario's Degree of Severity (DOS) using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and comparing sum of the DOS of the effective scenarios before and after the implementation of the PGP. For an acceptable PGP, sum of effective scenarios' DOS after implementation of the PGP should be less than that of before. The proposed procedure is applied to the IEEE Reliability Test System (RTS) and the results are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.
Contribution of Knowledge Management Systems to Organizational Learning

Organizational Learning is regarded as a major factor that leverages the competitive advantage of a company. Nowadays, many enterprises are relying on Knowledge Management systems for various purposes, but the utilization of these systems for enhancing Organizational Learning has not reached its optimum level. In the actual context, the purpose of the research is to determine how Knowledge Management systems foster effective learning at individual, group and organizational level. In order to explore these facets, five interviews have been conducted with representatives of companies that recognize the importance of Information Systems in achieving Organizational Learning. According to our findings, there are several initiatives towards this direction, but lack of time and accessibility to right information undermine the learning processes. As a consequence, appropriate measures should be taken in order to address the aforementioned challenges and to ensure that Organizational Learning becomes a valuable resource that enhances the performance of a company.
Verspreiding van persoonlikheidstipes by predikante in die gereformeerde Kerke van Suid-Afrika – om risikogroepe vir diensverlating te identifiseer

Distribution of personality types among ministers in the Reformed Churches of South Africa – to identify groups at risk for leaving service. With the use of a personality assessment based on the Hippocratic personality module, the researcher established that there is a significant distribution of personality types among pastors in the Reformed Churches in South Africa (RCSA). The main focus was to establish whether high-risk groups groups, which may be predisposed to leave the ministry prematurely, exist. This study revealed significant results in a group of pastors posing as possibly at risk for leaving the ministry, as well as a group of pastors that will function optimally within the RCSA. To establish this risk factor, the concept of ‘goodness of fit’ was used. In this way, the information gathered was used to develop a norm group, making it possible to effectively compare the individual pastor’s personality within the larger scope of pastors in the RCSA. With the use of this norm group, the researcher was able to make conclusions that are specifically applicable to the pastors in the RCSA. It was established that the Phlegmatic personality type has the largest representation among ministers in the RCSA. This is significant due to the fact that ministers with this personality type are largely drawn to the ministry in the RCSA. On the other side of the spectrum, the Sanguine and Melancholic personality types have the lowest representations. This may represent a possible higher risk group for leaving the ministry.Contribution: The research presented in this artcle, therefore, focused on the degree to which some pastors in the RCSA’s personal tendencies influence their ministerial work and the likelihood of leaving the ministry.
Desempenho comercial e padrão de concorrência internacional: uma análise do setor têxtil-confecções catarinense entre 1996 e 2006

Throughout the history, the textile industry has followed the changes in the productive pattern of the transformation industry. In the recent years, it can be seen a great transformation in the productive process by means of the incorporation of microelectronics and by the reduction of labor force intensity. In addition, changes had occurred in the distribution of international production chains and in the main variables that defines industry´s competitiveness between firms and countries. This article is intended to identify how Santa Catarina´s textile-firms commercial behavior is been established, considering the exporting behavior of the firms within this industry in the national level. It was observed that Santa Catarina state had a better performance than the sector´s national aggregation. However, at both levels it can be seen the evolution of a worrying scenario in the sense of the firms competitiveness conditions in textile industry.
Power Systems in Emergencies: From Contingency Planning to Crisis Management

Review of the Subject Different Forms of Disturbances Emergency Control Typical Mechanism of Development of Disturbances The Power System Operational and Control Infrastructure Measures to Minimize the Impact of Sudden Disturbances Measures to Minimize the Impact of Foreseen Disturbances Restoration of Normal Conditions After a Sudden Disturbance Restoration of Normal Conditions After a Foreseen Disturbance Training of Staff to Handle Disturbed Conditions Review of Some Major Disturbances Costs and Benefits of Emergency Control Emergency Control in the Future.
A Packet Loss Monitoring System for In-Band Network Telemetry: Detection, Localization, Diagnosis and Recovery

Network measurement provides rich data for network monitoring, control, and management. In-band network telemetry (INT) is a new network measurement technology that uses normal data packet to collect network information hop-by-hop. However, the design and implementation of INT protocol cannot do anything about packet loss: (1) The end-to-end telemetry mechanism makes INT unable to detect packet loss; (2) Since data packets may be lost due to various reasons, INT telemetry information will inevitably be lost. In summary, INT system by itself is unreliable. Incomplete telemetry data will seriously affect the performance of upper-layer network telemetry applications. In this paper, we present our successful experience in INT packet loss monitoring. We design, implement, and open source a powerful packet loss monitoring system for INT, called LossSight. The functions of LossSight include the detection of packet loss events, the deduction of the time and location of the losses, the diagnose of the root cause of the losses, and the recovery of the lost INT information. Experiment results show that LossSight provides excellent performance and extremely low overhead, including detection accuracy and diagnostic precision close to 100%, and detection latency of just milliseconds. In particular, LossSight uses a generative adversarial network to recover lost telemetry information, with excellent accuracy and reliability. LossSight has been running stably in the supercomputing interconnection environment of the National Supercomputing Center in Jinan. We suggest that all INT applications that require reliable telemetry information should be implemented based on LossSight.
Molecular Characterization of Class 1, 2 and 3 Integrons in Serratia spp. Clinical Isolates in Poland – Isolation of a New Plasmid and Identification of a Gene for a Novel Fusion Protein

Purpose Gram-negative rods of the genus Serratia play an increasing role as etiological agents of healthcare-associated infections (HAI) in humans. These bacteria are characterized by natural and acquired resistance to several groups of antibacterial agents. The aim of the study was to characterize class 1, 2 and 3 integrons in the clinical isolates of Serratia spp. in Poland. Methods The study comprised 112 clinical strains of Serratia, isolated from patients hospitalized in Poland in 2010–2012. Identification of strains was confirmed using MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry) system. Detection of class 1, 2 and 3 integrase DNA sequence was performed by multiplex-PCR. Amplicons obtained in the PCR reactions were purified and then sequenced bidirectionally. Results Among the analyzed strains, Serratia marcescens was a predominant species (103/112, 92.0%). All three classes of integrase DNA sequence were detected in the analyzed strains of Serratia spp. DNA sequence of class 3 integron, besides integrase gene, revealed three gene cassettes (dfrB3, blaGES-7,blaOXA/aac(6ʹ)-Ib-cr). BLAST analysis of DNA sequence revealed that class 3 integron was carried on 9448 bp plasmid which was named pPCMI3 – whole sequence of its DNA was submitted to GenBank NCBI (National Center for Biotechnology Information) – NCBI MH569711. Conclusion In this study, we identified a new plasmid pPCMI3 harboring class 3 integron. This is the first report of a gene oxa/aac(6ʹ)-Ib-cr coding for a novel fusion protein, which consists of OXA β-lactamase and acetyltransferase aac(6ʹ)-Ib-cr. In the analyzed strains, class 1 and 2 integrons were also detected. Among the strains with class 1 integron, nine contained cassette array 5ʹCS-aadA2-ORF-dfrA12-3ʹCS, and two – cassette array 5ʹCS-aacC1-ORF-ORF-aadA1-3ʹCS, which were not previously reported in Serratia spp.
Quality management and performance: An annotated review

Within the operations management literature, quality management (QM) has been one of the most popular research areas over the last two decades. QM is an integrative management philosophy aimed at the continuous improvement of performance. Consequently, the impact of QM practices on firm performance has been the subject of constant interest and challenge among researchers. Numerous empirical studies have attempted to investigate QM practice–performance relationships in different contexts. Based on an extensive review of the literature, this paper attempts to reflect the research stream on the impact of QM on firm performance and to provide insights for future research. For this purpose, the reviewed QM literature is organised and classified along three main themes: QM practices, performance and QM–performance relationships.
Apoptosis Enhances the Replication of Human Coronavirus OC43

Human coronavirus OC43 (HCoV-OC43) is one of the coronaviruses causing a mild common cold, but few studies have been made on this strain. Here, we identified the molecular mechanisms involved in HCoV-OC43-induced apoptosis and its implications for viral reproduction in Vero cells and MRC-5 cells. HCoV-OC43 infection induced apoptosis that was accompanied by cleavage of caspase-3 and PARP, degradation of cyclin D1, and cell cycle arrest at S and G2M phases. Dephosphorylation of STAT1 and STAT3, induced by HCoV-OC43 infection, was also associated with HCoV-OC43-mediated apoptosis. The pan-caspase inhibitor effectively prevented HCoV-OC43-induced apoptosis and reduced viral replication, suggesting that apoptosis contributes to viral replication. Collectively our results indicate that HCoV-OC43 induces caspase-dependent apoptosis to promote viral replication in Vero cells and MRC-5 cells.
Analysis and solution to the single-level batch production smoothing problem

Many companies use mixed-model production systems running under the Just-in-Time philosophy in order to efficiently meet customer demands for a variety of products. Such systems require demand be stable and production sequence be leveled. The production smoothing problem aims at finding level schedules in which the appearances of products are dispersed over the horizon as uniformly as possible. In this paper, the production smoothing problem is extended to a more general manufacturing environment where a single machine can be identified as either the final or the bottleneck stage of the system and products may have arbitrary non-zero setup and processing time requirements on this single machine. An optimization model is built for the problem and a two phase solution methodology is developed. The first phase problem is shown to be NP-hard and a parametric heuristic procedure is proposed for its solution. In contrast, the second phase problem is shown to be efficiently solvable and currently available solution methods are adopted from the literature. A computational study is designed to test the proposed two phase solution methodology and also the parametric heuristic procedure. Computational results show that the proposed two phase solution methodology enables effective and efficient control of the studied manufacturing system, and the heuristic procedure developed for the first phase problem is time efficient and promises near optimal solutions for a variety of test instances.
Violation of the mean path length invariance property

The invariance property of the mean path length is an astonishing law of Nature governing the motion of particles inside a disordered material. Whatever the strength of the disorder, the property states that the mean path length is exclusively determined by the ratio between the volume and the surface. Till now, the property has been reported as universal and valid in any kind of disordered medium and also beyond diffusion conditions. Nevertheless, we found out that the property fails in anomalous transport and in other kinds of random walk. By means of Monte Carlo simulations of light transport, we show that, in these cases, the invariance property loses its validity and the mean path length becomes dependent on the diffusive characteristics of the medium. The critical issue of such a violation lies in the breaking of isotropy and homogeneity of the radiance in the whole volume. These results are valid for all natural or artificial phenomena where random walkers, whatever their nature, are able to experiment anomalous transport.
Almost Unsupervised Text to Speech and Automatic Speech Recognition

Text to speech (TTS) and automatic speech recognition (ASR) are two dual tasks in speech processing and both achieve impressive performance thanks to the recent advance in deep learning and large amount of aligned speech and text data. However, the lack of aligned data poses a major practical problem for TTS and ASR on low-resource languages. In this paper, by leveraging the dual nature of the two tasks, we propose an almost unsupervised learning method that only leverages few hundreds of paired data and extra unpaired data for TTS and ASR. Our method consists of the following components: (1) a denoising auto-encoder, which reconstructs speech and text sequences respectively to develop the capability of language modeling both in speech and text domain; (2) dual transformation, where the TTS model transforms the text $y$ into speech $\hat{x}$, and the ASR model leverages the transformed pair $(\hat{x},y)$ for training, and vice versa, to boost the accuracy of the two tasks; (3) bidirectional sequence modeling, which addresses error propagation especially in the long speech and text sequence when training with few paired data; (4) a unified model structure, which combines all the above components for TTS and ASR based on Transformer model. Our method achieves 99.84% in terms of word level intelligible rate and 2.68 MOS for TTS, and 11.7% PER for ASR on LJSpeech dataset, by leveraging only 200 paired speech and text data (about 20 minutes audio), together with extra unpaired speech and text data.
Adaptive Extraction of Oil Painting Texture Features Based on Reaction Diffusion Equation

The oil painting retrieval technology based on the reaction diffusion equation has attracted widespread attention in the fields of oil painting processing and pattern recognition. The description and extraction of oil painting information and the classification method of oil paintings are two important processes in content-based oil painting retrieval. Inspired by the restoration and decomposition functional model of equal oil painting, we propose a reaction diffusion equation model. The new model contains two reaction diffusion equations with different principal parts. One principal part is total variation diffusion, which is used to remove noise. The other main part is thermal diffusion, which is used to modify the source term of the denoising reaction-diffusion equation to achieve the effect of protecting the texture of the oil painting. The interaction of the two reaction-diffusion equations finally achieves denoising while maintaining the boundaries and textures. Under the framework of the above reaction diffusion equation model, we introduce Laplace flow to replace the original total variation flow, so that the new denoising reaction diffusion equation combines the isotropic diffusion and total variation flow of the thermal reaction diffusion equation to achieve the effect of adaptive theoretical research. Using regularization methods and methods, we, respectively, get the well-posedness of the two model solutions, which provides the necessary preparation for numerical calculations. Based on the statistical theory and classification principles of support vector machines, combined with the characteristics of oil painting classification, the research and analysis are carried out from the three important aspects of kernel function, training algorithm, and multiclass classifier algorithm that affect the classification effect and speed. Numerical experiments show that the given filter model has a better processing effect on images with different types and different degrees of noise pollution. On this basis, an oil painting classification system based on texture features is designed, combined with an improved gray-level cooccurrence matrix algorithm and a multiclass support vector machine classification model, to extract, train, and classify oil paintings. Experiments with three types of oil paintings prove that the system can achieve a good oil painting classification effect. Different from the original model, the new model is based on the framework of reaction-diffusion equations. In addition, the new model has good effects in removing step effects, maintaining boundaries and denoising, especially in maintaining texture.
Low-noise voltage-controlled oscillators using enhanced LC-tanks

Frequency synthesizers used in modern telecommunication systems, such as cellular telephones, need to have very low phase noise. Therefore, in the design of high performance frequency synthesizers using Phase Locked Loops (PLL), the Voltage-Controlled Oscillator (VCO) has become a key issue. The trend towards monolithic Integration poses some major challenges. This paper discusses the phase noise aspects of LC-tuned oscillators. A general formula is developed, based on the concepts of effective resistance and capacitance. The formula also applies for oscillators using active inductors. From these results the importance of an inductor with very low series resistance is apparent. To circumvent the technological limits given by an Inductor's series resistance, a presented enhanced LC-tank can be used to make a trade-off between noise and power.
Effectiveness of Peer-Led Wellbeing Interventions in Retirement Living: A Systematic Review

Retirement living (RL) communities may be an ideal setting in which to utilize peer-leaders to implement or support health and wellbeing interventions. To date, this literature has not been systematically summarized. The purpose of this study was to fill this gap with a particular focus on describing the extent to which interventions addressed each level of the social ecological model of behavior change. This review utilized established frameworks for assessing methodological quality of studies, including the CONSORT guidelines and RoB2 bias assessment for cluster randomized controlled trials. A total of 153 records were identified from database searches, and seven studies met inclusion criteria. Overall, there is emerging evidence that peer-led health and wellbeing programs in RL communities can positively impact both health behavior, such as increased physical activity or nutrition, and health status, such as lower blood pressure. The study quality was modest to very good, but only one study was deemed not to have a high risk of bias. Peers are generally cost-effective, more accessible, and relatable leaders for health interventions that can still produce impactful changes. Future studies are needed to better understand how to sustain promising interventions.