Miracle-dz/UniFAR-FTUs huggingface dataset:
The "R" factor: perceptions of retirement as a consideration in small business owner succession planning

This exploratory study examines the phenomenon of retirement as a factor of consideration in small business owner succession planning in the United States (U.S.). A mixed methods approach, incorporating both qualitative and quantitative analyses, was used to answer the question: In what ways do perceptions of retirement influence small business owner succession planning? Small business owners (N = 102) primarily from the upper Midwest completed a 15-item online questionnaire which asked both closed and open-ended questions related to business and business owner demographics, as well as owner perceptions of retirement. Businesses included are both family owned and non-family owned. Small business owners selected to participate in the interview met the following criteria: (a) current CEO of a business, (b) CEO of the same business for a minimum of 10 years, (c) business has 2 – 99 employees, (d) for profit business designation. The semi-structured interview protocol was conducted with 17 small business owners. Triangulation of analyses and findings resulted in significance: Perceptions of retirement do influence small business owner succession planning. Society views of retirement are significant as a factor in views owners have of their own retirement. Further research is suggested to expand the research related to succession planning and valence assignment of factors to determine impact, if any, to succession planning follow through as well as further exploration of other factors, post succession, that may have relevance to the phenomenon of succession planning implementation.
A Cascaded Distributed Control Framework in DC Microgrids

The conventional distributed secondary controller, consisting of a voltage controller and a power controller, is based on the parallel framework by exchanging two state variables and requires a voltage observer to regulate the voltage. In this article, a cascaded control framework is proposed to achieve the voltage regulation and power sharing, in which only the power state variable is exchanged without the voltage observer. The secondary power controller is designed to adjust the reference value of the secondary voltage controller. And the output of the voltage controller is used to modify the input of the droop controller. Then a resilient cascaded controller is further proposed to enhance the controller resilience against time delays and disturbances. An extra information exchange block between the power controller and the voltage controller is introduced in the resilient cascaded controller. Moreover, the steady-state analysis is carried out to prove the effectiveness of proposed controllers. A small-signal model is also established to investigate the impact of controller parameter variation on the system dynamics. Finally, several case studies are conducted by simulations to demonstrate the performance of proposed controllers.
Whole-grain pan bread with the addition of jabuticaba peel flour

ABSTRACT: The objective of this study was to analyze the potential of the jabuticaba peel flour (JPF) as an ingredient in whole-grain bread. Pan bread formulations with different concentrations of jabuticaba peel flour were made: 0% (T0), 5% (T1), 10% (T2), and 15% (T3). Proximate composition, pH, water activity, color, phenolic compounds and antioxidant activity of bread were determined. The addition of JPF to the bread formulations led to a reduction of carbohydrate levels (51.14 to 46.55 g 100 g-1), lipids (4.79 to 3.35 g 100 g-1) and an increase in moisture (31.06 to 37.31 g 100 g-1) and ash (0.22 to 0.35 g 100 g-1). The fiber content increased up to three times, and the phenolic compounds up to seven times, thus increasing the antioxidant activity of the JPF-based bread when compared to the control. Bread made with the addition of JPF presented lower L* values (46.72 to 36.07) and higher a* values (3.10 to 9.07) compared to the control. Therefore, jabuticaba peel flour can be considered a potential ingredient for addition to whole-grain pan bread with desirable nutritional and functional characteristics.
Theory, hypothesis and application advance in chamber-based technology and methods for flux measurement

The exchange flux of greenhouse gases, such as carbon (CO 2 , CH 4 ), nitrogen (N 2 O) and water vapour (H 2 O), is the core of material cycle in the ecosystem and the bond of interaction among geosphere, biosphere and atmosphere. The development of stable isotope infrared spectroscopy and mass spectrometry technology and methods makes it possible to measure carbon stable isotopic composition ( δ 13 C) and oxygen stable isotopic composition ( δ 18 O)(CO 2 ), δ 13 C (CH 4 ), nitrogen stable isotope composition ( δ 15 N) and δ 18 O (N 2 O), hydrogen stable isotopic composition ( δ D) and δ 18 O (H 2 O), which realizes the observation of greenhouse gas and its isotope flux at the soil, plant and ecosystem scales in combined with chamber-based technology and methods for flux measurement. Taking the chamber-based technology and methods for CO 2 and its δ 13 C flux measurement as an example, this review which summarizes the basic principle and classification of the flux measurement system, expounds the theory requirements and assumptions of system design, summarizes the application advance and problems of chamber-based technology and methods for flux measurement in soil, plants (leaf, stem, and root) and ecosystem scales from the field to indoor, and prospects the importance of precision and accuracy of gas analysis and measurement data and the representativeness of measurement data in chamber-based flux measurement.
Scene Independency Matters: An Empirical Study of Scene Dependent and Scene Independent Evaluation for CNN-Based Change Detection

Visual change detection in video is one of the essential tasks in computer vision applications. Recently, a number of supervised deep learning methods have achieved top performance over the benchmark datasets for change detection. However, inconsistent training-testing data division schemes adopted by these methods have led to documentation of incomparable results. We address this crucial issue through our own propositions for benchmark comparative analysis. The existing works have evaluated the model in scene dependent evaluation setup which makes it difficult to assess the generalization capability of the model in completely unseen videos. It also leads to inflated results. Therefore, in this paper, we present a completely scene independent evaluation strategy for a comprehensive analysis of the model design for change detection. We propose well-defined scene independent and scene dependent experimental frameworks for training and evaluation over the benchmark CDnet 2014, LASIESTA and SBMI2015 datasets. A cross-data evaluation is performed with PTIS dataset to further measure the robustness of the models. We designed a fast and lightweight online end-to-end convolutional network called ChangeDet (speed-58.8 fps and model size-1.59 MB) in order to achieve robust performance in completely unseen videos. The ChangeDet estimates the background through a sequence of maximum multi-spatial receptive feature (MMSR) blocks using past temporal history. The contrasting features are produced through the assimilation of temporal median and contemporary features from the current frame. Further, these features are processed through an encoder-decoder to detect pixel-wise changes. The proposed ChangeDet outperforms the existing state-of-the-art methods in all four benchmark datasets.
Adaptive Packet Padding Approach for Smart Home Networks: A Tradeoff Between Privacy and Performance

The presence of connected devices in homes introduces numerous threats to privacy via the analysis of the encrypted traffic these devices generate. Prior works have shown that traffic attributes such as packet size combined with machine learning techniques enable the inference of private information from Internet of Things users. One of the commonly used techniques to mitigate those privacy threats is traffic obfuscation, such as packet padding. Most padding mechanisms that were previously proposed statically select the number of bytes inserted in the packets, which incurs high overhead and ineffective privacy improvement. These static mechanisms are particularly unsuitable for networks whose traffic patterns are significantly dynamic, such as smart homes. This article proposes an adaptive packet padding approach based on software-defined networking (SDN) that adjusts the number of bytes inserted into packets in response to variations in the home network utilization. The proposed technique monitors the network to instruct a padding mechanism through a representational state transfer (REST) interface proposed in this article. This mechanism ensures that the length of packets generated by connected devices is modified. The evaluation includes four supervised learning mechanisms, random forest (RF), support vector machine (SVM), decision tree, and $k$ -nearest neighbors (KNNs), to measure privacy improvement through the metrics accuracy, recall, and $F1$ -score. Goodput, jitter, and packet loss induced by the proposal are also evaluated. Our proposal is shown to overcome the state-of-the-art solutions in privacy preservation with a significantly lower overhead. For instance, the accuracy of RF on identifying devices decreases from 96% to 4.96%.
The North Korean Economy: Sustainable or Muddling-Through?

Confronting the continuing economic sanctions, the flood disaster, and the COVID 19, North Korea is now in a critical phase whether the North Korean economy will shift to a sustainable economy or, as it has done in the past three decades, barely manage to maintain at a survival level. To explore the question, this study investigates North Korea’s economic policy changes by extracting the keywords from the North Korean economic journal Economic Research, which is a representative state published document. We use a text mining approach to overcome limitations, such as the lack of objectivity and accuracy of the classification of topics in manual text analysis for North Korean studies. Contrary to the conventional assumption that the North Korean economic policies are driven by dogmatic Juche (self-reliance) ideology, we find that the strategy of economic policies differs depending on the leader and political and economic circumstances at the time. In particular, since Kim Jong-un assumed office in 2011, the topics have diversified, and now cover a wide range of subjects on capitalism. Nevertheless, without North Korea’s decisive reform measures and international cooperation, it will be hard to observe that the North Korean economy can go beyond ‘muddling-through’ for sustainable development.
CT features of patients with imported 2019-nCo-pneumonia/ 输入性新型冠状病毒肺炎的CT表现

目的 探讨新型冠状病毒(2019-nCoV)肺炎(novel coronavirus pneumonia,NCP)的胸部CT影像学表现,为早期诊断提供影像学依据。 方法 回顾性分析我院收治的10例新型冠状病毒核酸阳性患者的年龄、性别、临床病史、流行病学病史、实验室检查结果及胸部CT的影像学资料。 结果 10例患者中男6例,女4例,年龄22～70岁。 8例患者有发热、干咳的临床表现。 9例在影像学上表现为单侧肺或者双侧肺中外带肺野或胸膜下磨玻璃样病灶,病灶处于动态变化中,具有多样性、多灶性的特点。 增粗血管穿行病灶内、支气管气像在本病中较为常见。 胸腔积液少见。 结论 NCP的影像学具有一定的特征,再结合流行病学病史及临床特点,可对NCP做出初步诊断,是对核酸金标准的有效补充。
Developing a tool set to investigate antimicrobial mode of action in a phytopathogen

Bacteria are the most ubiquitous organisms on Earth. In a human body, there are more bacterial than human cells. Bacteria are an essential part of the carbon and nitrogen cycles which make life on Earth possible. The metabolic diversity of bacteria has been harnessed for the synthesis of industrial compounds such as pharmaceuticals, food ingredients and additives, and biocatalysts. However, a small proportion of bacteria are pathogenic, causing harm to humans and agriculture. To combat these bacteria, humans have developed antibiotics and antimicrobials, which drastically reduced mortality from bacterial diseases, increased human life expectancy worldwide, and increased the yield of food production. The widespread use of antimicrobials stimulated bacterial resistance, which has rapidly become a threat to public health and agriculture. The continued discovery of new antimicrobials is needed to avoid a widespread pandemic of antibiotic resistant bacteria and to combat plant diseases more effectively. Once discovered, antimicrobial substances can be chemically modified to improve potency, stability, delivery, or pharmacokinetics. In this thesis we investigated the mode of action of the gold liganded antimicrobial compound 7b-BF4 in the model bacterial organism Bacillus subtilis. We also studied the antimicrobial effect of chalcones BC1 and T9A in B. subtilis as well as in the citrus-infecting bacteria Xanthomonas citri. In studying the mode of action of those substances we have developed techniques that revealed new insights into the cell biology of X. citri that can be used for further studies.
The Time Diversification Controversy: An Analysis of the Italian Financial Market

Does the risk of an investment change with its timehorizon? In this article we put to test the competing claims presented by the literature on the so-called time diversification controversy. Using data from the Italian financial market of the last twenty years, we look at the evolution of different measures of risk as we extend the investment period. Our results seem to confirm Samuelson’s view, that, under certain conditions, the riskiness of an investment increases with the time horizon.
Lactic acid bacteria as starter cultures: An update in their metabolism and genetics

Lactic acid bacteria (LAB) are members of an heterogenous group of bacteria which plays a significant role in a variety of fermentation processes. The general description of the bacteria included in the group is gram-positive, non-sporing, non-respiring cocci or rods. An overview of the genetics of lactococci, Streptococcus thermophilus, lactobacilli, pediococci, leuconostocs, enterococci and oenococciis presented with special reference to their metabolic traits. The three main pathways in which LAB are involved in the manufacture of fermented foods and the development of their flavour, are (a) glycolysis (fermentation of sugars), (b) lipolysis (degradation of fat) and (c) proteolysis (degradation of proteins). Although the major metabolic action is the production of lactic acid from the fermentation of carbohydrates, that is, the acidification of the food, LAB are involved in the production of many beneficial compounds such as organic acids, polyols, exopolysaccharides and antimicrobial compounds, and thus have a great number of applications in the food industry (i.e. starter cultures). With the advances in the genetics, molecular biology, physiology, and biochemistry and the reveal and publication of the complete genome sequence of a great number of LAB, new insights and applications for these bacteria have appeared and a variety of commercial starter, functional, bio-protective and probiotic cultures with desirable properties have marketed.
MagC, magnetic collection of ultrathin sections for volumetric correlative light and electron microscopy

The non-destructive collection of ultrathin sections onto silicon wafers for post-embedding staining and volumetric correlative light and electron microscopy traditionally requires exquisite manual skills and is tedious and unreliable. In MagC introduced here, sample blocks are augmented with a magnetic resin enabling remote actuation and collection of hundreds of sections on wafer. MagC allowed the correlative visualization of neuroanatomical tracers within their ultrastructural volumetric electron microscopy context.
Two-Way AF MIMO Multi-Relay System Design Using MMSE-DFE Techniques

Targeting at a better design of the analogue network coding (ANC)-assisted two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) multi-relay communication systems, we bring in the nonlinear minimal mean-squared error (MMSE)-decision feedback equalization (DFE) receiving technique to jointly optimize the source precoding, relay amplifying, feed-forward and feedback matrices. Under the transmission power constraints at both source nodes and each relay node, the two-way sum mean-squared error (MSE) of the signal waveform estimation of all data streams is minimized. To solve the complicated nonconvex optimization problem with four groups of system parameters, this paper develops an iterative block coordinate descent (BCD) algorithm, which converges to at least a Nash point. On the basis of it, for mitigating the error propagation in MMSE-DFE receivers, a group of permutation matrix variables, determining the detection orders of all data streams, are further introduced in our system optimization. Moreover, in case there is no sufficiently precise channel state information (CSI), we also make an extension of the developed algorithms, yielding a robust design scheme, to handle the channel uncertainties. Numerical simulation results show that, compared with the existing linear MMSE receiving-based algorithm, our proposed nonlinear ones provide improved MSE and bit-error-rate (BER) performance as well as good robustness against the imperfect CSI, indicating a promising application prospect of this research.
A 270-mV 6T SRAM Using Row-Based Dual-Phase VDD Control in 28-nm CMOS

This paper presents a 28-nm 32kb 6T static random access memory (SRAM) operating down to the sub-threshold regime. This design employs a dual-phase VDD (DPVDD) control technique in a row-based manner to reduce the minimum functional voltage (Vmin) below the threshold voltage of the transistor (Vth). With the proposed DPVDD technique, during the read operation, the ratio of the read current to the leakage current caused by the unselected bit-cells on the same bit-line is increased by a temporally boosted cell VDD, which increases the signal swing on the bit-line and minimizes the stability degradation caused by the leakage current. In addition, the proposed DPVDD can enhance the stability of the half-selected cells to mitigate the half-select disturbance. A 32-kb 6T SRAM test chip was implemented in 28-nm CMOS technology with a macro area of 0.028 mm2. Measurement results show that the SRAM with the proposed DPVDD achieves Vmin of 0.27 V and the minimum energy of 0.041 fJ/bit.
A Local Region-Based Level Set Method With Markov Random Field for Side-Scan Sonar Image Multi-Level Segmentation

Side-scan sonar is widely utilized in the field of underwater exploration. Accurate segmentation of the side-scan sonar images is an essential part of sonar image processing. To improve the accuracy of image segmentation and reduce the occupancy of computing resources, a new active contour model for image segmentation is proposed in this article. Firstly, we make the energy function of each pixel determined by itself and its neighbors. This article embeds the local texture neighborhood region system and define its structure to against the noise and object boundary pollution of the image. Further, we introduce a Bayesian framework that embeds the Markov Random Field model and local texture information to counteract the problem of intensity inhomogeneity, improve the accuracy of segmentation, and reduce computational cost. Finally, according to this model, we customize a new multi-class energy function which applied to the level set function. By minimizing this energy equation, we can divide the image into three classes: object, shadow, and seabed background. The experimental results show that this method has a good effect on the synthesized high-noise sonar images and real sonar images, and also have significantly increased the accurate recognition of underwater targets.
Heuristic Search Value Iteration for Zero-Sum Stochastic Games

In sequential decision making, heuristic search algorithms allow exploiting both the initial situation and an admissible heuristic to efficiently search for an optimal solution, often for planning purposes. Such algorithms exist for problems with uncertain dynamics, partial observability, multiple criteria, or multiple collaborating agents. In this article, we look at two-player zero-sum stochastic games (zsSGs) with a discounted criterion, in a view to propose a solution tailored to the fully observable case, while solutions have been proposed for particular, though still more general, partially observable cases. This setting induces reasoning on both a lower and an upper bound of the value function, which leads us to proposing zsSG-HSVI, an algorithm based on heuristic search value iteration (HSVI), and which thus relies on generating trajectories. We demonstrate that, each player acting optimistically, and employing simple heuristic initializations, HSVI's convergence in finite time to an $\epsilon$-optimal solution is preserved. An empirical study of the resulting approach is conducted on benchmark problems of various sizes.
Visualization of riverine water and vortex dynamics around the Naruto Strait based on high-resolution ocean simulation and satellite images

This paper addresses a fusion visualization of vorticity fields and riverine water maps by combining satellite-derived ocean-color images and simulated velocity fields using a high-resolution ocean model. Our visualization successfully described the transportation of low-sa-linity riverine water from the Yoshino River through the Naruto Strait. The cloudy white riverine water separated from the river plume in Kii Channel and easily passed through the strait owing to the flood current that formed a mushroom vortex. Meanwhile, the high-salinity clear water from the Harima-Nada Sea could horizontally mix in the strong vorticity fields generated by the ebb current after passing the strait. Our fusion visualization is capable of evaluating the transportation and mixing of riverine water through narrow straits.
Analyzing the Impact of Different Filtering Methods on Satellite Altimetry Full Waveform Decomposition

Filtering is an essential step in the denoising of satellite altimetry full waveform data, since any deformation and distortion in the shape of the waveform can cause errors in range estimation and further waveform decomposition will also be adversely affected. This paper evaluated comprehensive performance of the popular filtering approaches like Gaussian filter, Taubin filter, Wavelet filter, and EMD based filter by simulated waveform data and ICESat/GLAS waveform. Firstly, according to the principle of each filter, the optimal parameters of filtering algorithm by ergodic tests were selected, then the Gaussian function using Levenberg-Marquardt method was used to fit full waveform to exact waveform parameters (i.e. peak amplitude, position, and half-width). Thirdly, through comparing SNR, RMSE of the pre and post filtering simulation waveform, and the consistency ratio, the average error of peak amplitude, position, and half-width in each Gaussian components of the fitted simulation waveform, verified the effectiveness of these filters and analyzed their influence on decomposition accuracy. Both the simulation experiments and ICESat/GLAS experimental results suggested that the Taubin filter had superior performance with the lowest peak position error, which turns out it has advantage in full waveform denoising and contributes to better full waveform decomposition. However, it introduces more parameters needed to be selected. The self-adaptive EMD based approach has the highest consistency, which shows EMD-based method is more suitable for the denoising of satellite altimetry full waveform decomposition.
NOMA for Correlated Information Sources in 5G Systems

In this letter, the authors consider the non-orthogonal multiple access (NOMA) scheme for correlated information sources (CIS). We show that in the conventional NOMA scheme, the correlated information is not received by all the users, due to successive interference cancellation (SIC). Then the non-SIC NOMA scheme is proposed for all the users to receive the common information. The data rate achieved by this non-SIC NOMA scheme is derived. The achievable rate region is also analyzed. Numerical results validate the effectiveness of the proposed non-SIC NOMA scheme, compared to the conventional SIC NOMA scheme.