Miracle-dz/UniFAR-FTUs huggingface dataset:
COGNITIVE CONFLICT IN STRATEGIC DECISION OF MANAGEMENT TEAMS IN SMALL ENTERPRISES

ABSTRACT Purpose: The objective of this article is to explain how cognitive conflict happens and what are its contributions to the decision-making processes of management teams in small enterprises (SE). Originality/value: Although SEs are important and numerous, the cognitive conflict in their management team and the strategic decision making of this team are understudied. This article helps to feel this gap with contributions and implications which are helpful for research and practice related to those themes. Design/methodology/approach: The descriptive methodological approach was adopted based on qualitative methods and multicase study (Eisenhardt, 1989). Data were collected with interviews and analyzed within and cross-case procedures, according to Miles and Huberman’s (1994) recommendations. Four cases of SE were studied. Findings: The strategic decision processes were considerably determined by cognitive conflicts. Such conflicts questioned decision possibilities and highlighted aspects related to intuition and improvisation, both normally useful and present in the strategic decision processes of SE. Cognitive conflict inhibits improvisation because its occurrence creates useful questionings in decision making preparation. Those questionings generated deepness in discussion and analysis for decision making in the studied SEs.
The Nebula Benchmark Suite: Implications of Lightweight Neural Networks

This article presents a benchmark suite named Nebula that implements lightweight neural network benchmarks. Recent neural networks tend to form deeper and sizable networks to enhance accuracy and applicability. However, the massive volume of heavy networks makes them highly challenging to use in conventional research environments such as microarchitecture simulators. We notice that neural network computations are mainly comprised of matrix and vector calculations that repeat on multi-dimensional data encompassing batches, channels, layers, etc. This observation motivates us to develop a variable-sized neural network benchmark suite that provides users with options to select appropriate size of benchmarks for different research purposes or experiment conditions. Inspired by the implementations of well-known benchmarks such as PARSEC and SPLASH suites, Nebula offers various size options from large to small datasets for diverse types of neural networks. The Nebula benchmark suite is comprised of seven representative neural networks built on a C++ framework. The variable-sized benchmarks can be executed i) with acceleration libraries (e.g., BLAS, cuDNN) for faster and realistic application runs or ii) without the external libraries if execution environments do not support them, e.g., microarchitecture simulators. This article presents a methodology to develop the variable-sized neural network benchmarks, and their performance and characteristics are evaluated based on hardware measurements. The results demonstrate that the Nebula benchmarks reduce execution time as much as 25x while preserving similar architectural behaviors as the full-fledged neural networks.
Genetic effects of F1 pollen sterility genes S-b, S-d and S-e in rice (Oryza sativa L.)

An experimental population commonly used in genetic analyses of gene or quantitative trait loci (QTLs) in rice is chromosome segment substitution lines (CSSLs). In the present study, with the typical indica variety Guangluai 4 as a donor and japonica variety Taichung 65 as a recipient, seven CSSLs carrying F<sub>1 </sub>pollen sterility genes S-b, S-d, S-e, S-b/S-d, S-b/S-e, S-d/S-e, and S-b/S-d/S-e were obtained by specific selection for the target genes, non-specific selection for the genome of the recurrent parents in four backcross populations (BC<sub>1</sub>F<sub>2</sub>, BC<sub>2</sub>F<sub>2</sub>, BC<sub>3</sub>F<sub>2</sub> and BC<sub>3</sub>F<sub>3</sub>). We evaluated the genetic effect of the F<sub>1</sub> pollen sterility genes using 35 F<sub>1 </sub>hybrid individuals in crosses derived from CSSLs and Taichung 65. Pollen fertility of F<sub>1</sub> hybrid plants was observed and the results indicated that the single genes S-b, S-d and S-e can cause 67.7%, 14.6% and 53.2% of pollen sterility, respectively. Multiple genes S-b/S-d, S-b/S-e, S-d/S-e, and S-b/S-d/S-e can cause 76.6%, 85%, 68.7%, and 93% of pollen sterility, respectively.
Evaluation of Some Traits in Local Iranian Quince (Cydonia Oblonga Miller) Genotypes

ABSTRACT Quince (Cydonia oblonga Miller.) belongs to the Rosaceae family and is generally used for fresh consumption and processed items. In this research, fruit characteristics of eight quince genotypes from Iran were investigated via genotype by trait interactions (GTI) biplot. Results indicated that the first two principal components analysis (PC1 and PC2) were used to create a two-dimensional GTI biplot that accounted percentages of 31% and 22%, respectively, of sums of squares of the GTI. The vertex genotypes in polygon were Svs1, Esf, Nb1, Kud2 and Et1; and Svs1 was the winning genotype for pectin, fruit length, phosphorus percent and fruit hardness while Esf was the best genotype for iron percent, fruit diameter, fruit weight and end hold. There were positive correlation among pectin, fruit length, fruit hardness and phosphorus percent as well as among zinc percent, branch length, fruit apparent specific weight, calcium percent and potassium percent. Genotype Svs1 was more desirable followed by genotypes Nb4, Esf and Et1 based on ideal entry biplot and pectin and fruit length were the best traits according to ideal tester biplot. The best genotype for obtaining of high fruit weight was Esf following to Nb4, Svs1 and Nb1 and ranking traits based on fruit weight showed that fruit diameter is more important followed by end hold and iron percent. This study showed that there was relatively high level of variation in quince genotypes grown and morphological traits used in this research indicating that they can be used for characterization and diversity analysis of quince. We concluded from this study that it is imperative for breeders to pay more attention to improve quince morphological traits coordinated to fruit yield performance.
Meaningful analysis of innovation, business and entrepreneurial ecosystem concepts

Over the last decade academic literature has faced a boom of publications devoted to the notion of ecosystem, which resulted in the emergence of various research streams and corresponding fragmentation of the research domain. The existing variety of meanings and contradictory definitions necessitates conducting a thorough literature review on three tightly coupled concepts of innovation ecosystem, business ecosystem and entrepreneurial ecosystem. This study is based upon a mixed technique, which combines a bibliometric analysis and in-depth investigation of papers devoted to these research streams. Through examining their theoretical background, constructing conceptual structures and performing an in-depth analysis we were able to define the essence of innovation, business and entrepreneurial ecosystems as well as their distinctive features. Then, we proceeded with a comparative analysis of these concepts, which allowed us to outline the existing similarities and to demarcate the concepts from an ontological perspective. This study provides certain clarification for the existing conceptual mix in the field of the ecosystem research and can be used as a foundation for a further investigation of the concept.
Nestling and adult sparrows respond differently to conspecific dialects

&NA; Understanding the causes and consequences of divergence in mate recognition traits has long been a fundamental question in evolutionary biology. In songbirds, songs are culturally transmitted, and cultural divergence can generate discrete geographic variation in song (i.e., dialects). Understanding how responses to within‐ versus across‐species variation in songs changes across life stages may shed light on the functional significance of population divergence in learned traits. Here, we use a novel combination of song playbacks to adult and nestling golden‐crowned sparrows to compare responses to local conspecific, foreign conspecific, and heterospecific songs prior to and after song learning. We found that nestlings respond equally little to both foreign conspecific and heterospecific songs. By contrast, the response of adult males to foreign conspecific songs was stronger than their response to heterospecific song, but weaker than their response to local conspecific song. Our study suggests that early local experience may interact with conspecific biases prior to song learning, in a way that has not been previously documented. Our results illustrate the importance of studying behavior at multiple life stages in order to better understand the effect of early experience on cultural and biological evolution.
Drone Image Stitching Using Local Mesh-Based Bundle Adjustment and Shape-Preserving Transform

This article proposes a strategy for drone image stitching using local mesh-based bundle adjustment and shape-preserving transform, which aims to effectively stitch multiple overlapping drone images into a natural panoramic image. Existing traditional methods using a simple homography cannot handle the situation that the input drone images have parallax effect, and the image mosaic result always suffers from artifacts. In order to achieve natural-looking stitching results without the above limitation, we divide the proposed method into the following steps. Starting from initial feature sets obtained by off-the-shelf feature extraction methods, we incorporate the parallax errors into an energy minimum framework and construct a robust alignment energy. This energy can be minimized efficiently based on local bundle adjustment and robust $3\sigma $ principle, which could eliminate parallax effects and achieve accurate alignment. Then the seamless panoramic image is obtained by warping the target image and the source images onto the mesh plane directly. An image patch can be transformed by projective transformation (e.g., homography), which provides good alignment but may cause distortions. Consequently, combined with mesh-based shape-preserving transform, our proposed strategy can improve the naturalness of the results flexibly. Experiments show that our stitching strategy can eliminate parallax effects more effectively and achieve natural-looking results compared to other state-of-the-art methods.
Dissociated cortical phase- and amplitude-coupling patterns in the human brain

Coupling of neuronal oscillations may reflect and facilitate the communication between neuronal populations. Two primary neuronal coupling modes have been described: phase-coupling and amplitude-coupling. Theoretically, both coupling modes are independent, but so far, their neuronal relationship remains unclear. Here, we combined MEG, source-reconstruction and simulations to systematically compare cortical phase-coupling and amplitude-coupling patterns in the human brain. Importantly, we took into account a critical bias of amplitude-coupling measures due to phase-coupling. We found differences between both coupling modes across a broad frequency range and most of the cortex. Furthermore, by combining empirical measurements and simulations we ruled out that these results were caused by methodological biases, but instead reflected genuine neuronal amplitude coupling. Overall, our results suggest that cortical phase- and amplitude-coupling patterns result from distinct neural mechanisms. Furthermore, our findings highlight and clarify the compound nature of amplitude coupling measures.
Detection of High-Risk Human Papillomavirus by Chromogenic in Situ Hybridization Method in Liquid-Based Cervicovaginal Cytology Specimens with Atypical Squamous Cells of Undetermined Significance

Background : Cervical cancer is the second most common cancer after breast cancer in women worldwide. Owing to comprehensive cervical screening programs, a significant decrease has been observed in the incidence of invasive cervical cancers. Human Papillomavirus (HPV) is the underlying etiology in 99.7% of the cases of cervical cancer and is a major risk factor for the development of precancerous and cancerous cervical lesions. Chromogenic in situ hybridization method (CISH) is one of the methods used to detect high risk HPV in liquid -based smears. Aims : In this study, we conducted an archive search in the department of pathology and we used chromogenic in situ hybridization technique to investigate whether HPV DNA was present in liquid -based smears of 68 patients who had been found to have atypical squamous cells of undetermined significance (ASCUS) and whether a cervical intraepithelial lesion was present in the biopsy samples of patients who were positive for HPV DNA. Methods and Material :. We prepared additional samples from liquid -based preparations obtained by the ThinPrep method. The CISH procedure was performed on the Benchmark Automated Slide Stainer (Ventana) according to the manufacturer’s standard protocol. Results and Conclusions : We found HPV DNA in the samples of 10 patients by using INFORM HPV III high risk (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 68, and 70) (Ventana, Tucson, AZ) probe, with CISH method on each additional sample, and biopsy results of the respective patients, indicated low grade squamous intraepithelial lesion (LGSIL) in 8 patients and high grade squamous intraepithelial lesion (HGSIL) in 2 cases. Keywords: Human papillomavirus, chromogenic in situ hybridization, atypical squamous cells of undetermined significance DOI: 10.7176/JHMN/80-10 Publication date: September 30 th 2020
Data-Driven Incipient Fault Detection via Canonical Variate Dissimilarity and Mixed Kernel Principal Component Analysis

Incipient fault detection plays a crucial role in preventing the occurrence of serious faults or failures in industrial processes. In most industrial processes, linear, and nonlinear relationships coexist. To improve fault detection performance, both linear and nonlinear features should be considered simultaneously. In this article, a novel hybrid linear-nonlinear statistical modeling approach for data-driven incipient fault detection is proposed by closely integrating recently developed canonical variate dissimilarity analysis and mixed kernel principal component analysis (MKPCA) using a serial model structure. Specifically, canonical variate analysis (CVA) is first applied to estimate the canonical variables (CVs) from the collected process data. Linear features are extracted from the estimated CVs. Then, the canonical variate dissimilarity (CVD) which quantifies model residuals in the CVA state-subspace is calculated using the estimated CVs. To explore the nonlinear features, the nonlinear principal components are extracted as nonlinear features through performing MKPCA on CVD. Fault detection indices are formed based on Hotelling's $T^2$ as well as $Q$ statistics from the extracted linear and nonlinear features. Moreover, kernel density estimation is utilized to determine the control limits. The effectiveness of the proposed method is demonstrated by the comparisons with other relevant methods via simulations based on a closed-loop continuous stirred-tank reactor process.
Developing a PCR assay to detect Aspergillus parasiticus

Aspergillus parasiticus is one of the producers of aflatoxins in food. They may produce aflatoxin B and G which can lead to serious diseases in human. Aflatoxin is known as a type of carcinogens. People ingesting infected food even in a very low level for a long time can get cancer because of aflatoxin accumulation. Detection of aflatoxin or aflatoxin producers in foods is necessary to improve the life quality by decreasing the risk of getting diseases. Recently, the contemporary method to detect A. parasiticus is a morphological method but it still retains many limitations. In this study, a PCR based method was developed to provide a basic for develop a new method to detect A. parasiticus in food that overcame the disadvantages of the conventional morphological method. A specific set of primers was designed based on norB-cypA genes and successfully optimized for best amplification results at 62 ̊C. The sensitivity of the test was identified to be 0.005 ng/μL of target fungi DNA. A DNA isolation protocol was also optimized to ensure the success of the PCR assay, using SDS lysis, sand and thermal shock. The protocol from DNA isolation to PCR was successfully developed and provided a useful tool to improve the diagnosis of aflatoxins at an early stage and control all stages of food production. The success of this study is designing a pair of primers and a PCR assay which is specific for detection of A. parasiticus among other aspergilus species. This PCR assay can be used in the future for further development a PCR method for detection of A. parasiticus in food.
Postsynaptic cell firing bidirectionally regulates future long-term potentiation in the rat hippocampus

Synaptic plasticity phenomena such as long-term potentiation (LTP) have been proposed as neurobiological mechanisms of learning and memory. LTP depends on coordinated presynaptic and postsynaptic activity, driven by action potential (AP) firing. While APs serve as the neuronal output signal which integrates different inputs, they can also backpropagate into the dendrites and influence the cell’s own physiology. Such backpropagating APs may act as a retrograde signal to detect the coincidence of presynaptic and postsynaptic activity. Importantly, APs can modulate synaptic plasticity and trigger metaplasticity, a higher-order type of plasticity whereby a neuron’s history of activity changes their ability to undergo subsequent plasticity (a process known as “priming”). APinduced metaplasticity in the hippocampus, a brain region important for some modes of memory, has, however, been diverse; while some studies suggest that previous AP firing facilitates the induction and maintenance of LTP, others show the opposite. Due to inconsistencies in experimental paradigms used to induce AP-dependent metaplasticity and subsequent LTP, the parameters responsible for facilitating or inhibiting LTP are poorly understood. The aim of this thesis was to elucidate the parameters driving AP-mediated metaplasticity by addressing inconsistencies between previous studies. The main focus was on the influence of different patterns of activity used either to prime or induce LTP, specifically theta-burst stimulation (TBS) and high-frequency stimulation (HFS) which are known to trigger distinct intracellular signalling cascades. It was hypothesised that the metaplastic effects of postsynaptic firing are determined by either the pattern of firing during priming, or the method of LTP induction, or both. This hypothesis was investigated by systematically testing the influence of different experimental parameters on AP-induced metaplasticity, utilising field and intracellular recordings in area CA1 of acute hippocampal
Economic Model Predictive Control of a Point Absorber Wave Energy Converter

In this paper, we propose an economic model predictive control (EMPC) strategy for the constrained optimization problem of the wave energy converter system. Unlike standard model predictive control (MPC) that uses the tracking cost function, in EMPC, a general economic cost function that directly reflects the economic objective of the system is established. In the wave energy converter (WEC), the general economic cost function aims to maximize the energy extracted from ocean waves and minimize the operation cost. The terminal equality constraint in the optimization problem is used to steer the system state to the steady-state at the end of the optimization horizon. Then the controller solves the non-convex optimization problem in real-time. The auxiliary optimization problem is used for the stability analysis, and the convergence of the system can be proved via the Lyapunov technique. Several simulation results are presented to demonstrate the effectiveness of the proposed strategy.
Public Strategy and Eco-Social Engagement in Latin American States: An Analysis of Complex Networks Arising from Their Constitutions

Over the past four decades, Latin American states have drafted relatively new constitutions in comparison with other regions of the world. These transformations, in some cases, have helped governments leave behind the former authoritarian regimes, or in others, have simply established a more democratic system incorporating a forward-looking approach to rights. For example, stronger individual and collective rights have been forged, together with new avenues for citizen participation. Certainly, many of the new constitutions grant a much broader base of rights, including collective political and territorial rights for indigenous communities, protections against ethnic, racial, and gender discrimination, and greater guarantees of privacy and control over information. Consequently, some Latin American constitutions are held up as among the best in the world. For this study, the constitutional texts of 22 Latin American countries were analyzed with the aim of understanding their regulatory changes and impacts, pointing out the existing inequalities they address, as well as the clear positive trend established in terms of the generation of greater social engagement.
Protocol-Based Particle Filtering and Divergence Estimation

Network protocols are applied to reduce the amount of data which are transmitted simultaneously over the network. In this article, round-robin protocol (RRP) and try-once-discard protocol (TODP) are studied for state estimation over network where information of different sensor nodes are fused. Using these protocols, at each time sample, only one sensor node can send its information over the network and consequently the required bandwidth is significantly reduced. Particle filters (PF) are able to estimate states of generally any nonlinear and non-Gaussian systems. Therefore, in this article, the development of particle filtering in networked systems under RRP and TODP protocols is studied. Toward this goal, two sequential importance sampling resampling algorithms under RRP and TODP are proposed where their corresponding marginal posterior pdfs are approximated by sequentially computations of weights. For the case of RRP, likelihoods of previous measurements are included in the weight computations while for TODP case, only the latest likelihood appears. Moreover, the approximated marginal posterior pdfs under RRP and TODP are compared with the normal posterior pdf using Kullback–Leibler divergence measure. This measure computes the difference between two probability distributions. Finally, the efficiency of the proposed method is demonstrated for a networked interconnected four-tank system.
gamma-Aminobutyric acid inhibits cytokine-mediated synergistic induction of astrocytic interleukin-6 release: A mechanistic study

y-Aminobutyric Acid Inhibits Cytokine-Mediated Synergistic Induction of Astrocytic Interleukin-6 Release: A Mechanistic Study by Grant Toshio Aguinaldo Dr. Bryan L. Spangelo, Examination Committee Chair Professor of Chemistry University of Nevada, Las Vegas A paucity of y-aminobutyric acid (GABA) levels is thought to encourage cytokine release in Alzheimer’s disease (AD). A mechanistic investigation into the GABA-mediated suppression of the synergistic release of interleukin (IL)-6 by IL-ip and tumor necrosis factor (TNF)-a is presented. Preliminary results indicate that p38 and nuclear factor (NF)-kB are essential for the synergistic release of IL-6 by IL-ip and TNF-a. Both IL-ip and TN F-a are able to stimulate the phosphorylation of p38, however, no synergistic stimulation was observed. IL-ip or TNF-a is able to stimulate the degradation of the NF-kB inhibitor, kB-a, with no change in kB-p. Interestingly, TNF-a is able to accelerate kB -a degradation in the presence of IL-ip. While GABA is unable to suppress kB -a degradation and the phosphorylation of p38 by IL-ip and TNF-a, it is postulated that GABA may be able to inhibit IL-6 concentrations by lessening the rate of kB -