Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Potato Stress Tolerance and Tuber Yield Under a Climate Change Scenario – A Current Overview

Global climate change in the form of extreme heat and drought poses a major challenge to sustainable crop production by negatively affecting plant performance and crop yield. Such negative impact on crop yield is likely to be aggravated in future because continued greenhouse gas emissions will cause further rise in temperature leading to increased evapo-transpiration and drought severity, soil salinity as well as insect and disease threats. This has raised a major challenge for plant scientists on securing global food demand, which urges an immediate need to enhance the current yield of major food crops by two-fold to feed the increasing population. As a fourth major food crop, enhancing potato productivity is important for food security of an increasing population. However, potato plant is highly prone to high temperature, drought, soil salinity, as well as insect and diseases. In order to maintain a sustainable potato production, we must adapt our cultivation practices and develop stress tolerant potato cultivars that are appropriately engineered for changing environment. Yet the lack of data on the underlying mechanisms of potato plant resistance to abiotic and biotic stress and the ability to predict future outcomes constitutes a major knowledge gap. It is a challenge for plant scientists to pinpoint means of improving tuber yield under increasing CO2, high temperature and drought stress including the changing patterns of pest and pathogen infestations. Understanding stress-related physiological, biochemical and molecular processes is crucial to develop screening procedures for selecting crop cultivars that can better adapt to changing growth conditions. Elucidation of such mechanism may offer new insights into the identification of specific characteristics that may be useful in breeding new cultivars aimed at maintaining or even enhancing potato yield under changing climate. This paper discusses the recent progress on the mechanism by which potato plants initially sense the changes in their surrounding CO2, temperature, water status, soil salinity and consequently respond to these changes at the molecular, biochemical and physiological levels. We suggest that future research needs to be concentrated on the identification and characterization of signaling molecules and target genes regulating stress tolerance and crop yield potential.
Self-Paced Free-Running Wheel Mimics High-Intensity Interval Training Impact on Rats’ Functional, Physiological, Biochemical, and Morphological Features

Free-running wheel (FRW) is an animal exercise model that relies on high-intensity interval moments interspersed with low-intensity or pauses apparently similar to those performed in high-intensity interval training (HIIT). Therefore, this study, conducted over a 12-weeks period, aimed to compare functional, thermographic, biochemical and morphological skeletal and cardiac muscle adaptations induced by FRW and HIIT. Twenty-four male Wistar rats were assigned into three groups: sedentary rats (SED), rats that voluntarily exercise in free wheels (FRW) and rats submitted to a daily HIIT. Functional tests revealed that compared to SED both FRW and HIIT increased the ability to perform maximal workload tests (MWT-cm/s) (45 ± 1 vs. 55 ± 2 and vs. 65 ± 2). Regarding thermographic assays, FRW and HIIT increased the ability to lose heat through the tail during MWT. Histochemical analyzes performed in tibialis anterior (TA) and soleus (SOL) muscles showed a general adaptation toward a more oxidative phenotype in both FRW and HIIT. Exercise increased the percentage of fast oxidative glycolytic (FOG) in medial fields of TA (29.7 ± 2.3 vs. 44.9 ± 4.4 and vs. 45.2 ± 5.3) and slow oxidative (SO) in SOL (73.4 ± 5.7 vs. 99.5 ± 0.5 and vs. 96.4 ± 1.2). HITT decreased fiber cross-sectional area (FCSA-μm2) of SO (4350 ± 286.9 vs. 4893 ± 325 and vs. 3621 ± 237.3) in SOL. Fast glycolytic fibers were bigger across all the TA muscle in FRW and HIIT groups. The FCSA decrease in FOG fibers was accompanied by a circularity decrease of SO from SOL fibers (0.840 ± 0.005 vs. 0.783 ± 0.016 and vs. 0.788 ± 0.010), and a fiber and global field capillarization increase in both FRW and HIIT protocols. Moreover, FRW and HIIT animals exhibited increased cardiac mitochondrial respiratory control ratio with complex I-driven substrates (3.89 ± 0.14 vs. 5.20 ± 0.25 and vs. 5.42 ± 0.37). Data suggest that FRW induces significant functional, physiological, and biochemical adaptations similar to those obtained under an intermittent forced exercise regimen, such as HIIT.
Silence Is Golden. Six Reasons Inhibiting the Spread of Third-Party Gossip

Most of the current literature on gossip describes gossipmongers as incessantly sharing evaluative and valuable information about an absent third party in teams, groups, communities, and organizations. However, potential gossipers can similarly decide not to share what they know, depending on the content, the context, or their relationship with the other actors in the gossip triad. We argue that understanding the reasons why people do not gossip may provide useful insights into individual motives, group dynamics, and collective behaviors. This theoretical contribution first critically surveys the existing gossip literature with the aim of highlighting the conditions under which people might refrain from sharing third party information. We then propose to apply Goal Framing theory as a way to bridge a theory of the micro-foundations of human behavior with an analytical model of the gossip triad that disentangles the various ways through which senders, receivers, and objects of gossip may be interrelated. From a goal framing perspective, most research on gossip illustrates the mechanisms in which the hedonic gratification derived from gossiping is reinforced by gain or normative goals. However, a normative or a gain goal frame can prevent the gossip monger from spreading the information, and we argue that depending on different configurations of frames and relations between actors the perceived costs of sending gossip may be far higher than much of the previous literature suggests.
NGL-1/LRRC4C Deletion Moderately Suppresses Hippocampal Excitatory Synapse Development and Function in an Input-Independent Manner

Netrin-G ligand-1 (NGL-1), also known as LRRC4C, is a postsynaptic densities (PSDs)-95-interacting postsynaptic adhesion molecule that interacts trans-synaptically with presynaptic netrin-G1. NGL-1 and its family member protein NGL-2 are thought to promote excitatory synapse development through largely non-overlapping neuronal pathways. While NGL-2 is critical for excitatory synapse development in specific dendritic segments of neurons in an input-specific manner, whether NGL-1 has similar functions is unclear. Here, we show that Lrrc4c deletion in male mice moderately suppresses excitatory synapse development and function, but surprisingly, does so in an input-independent manner. While NGL-1 is mainly detected in the stratum lacunosum moleculare (SLM) layer of the hippocampus relative to the stratum radiatum (SR) layer, NGL-1 deletion leads to decreases in the number of PSDs in both SLM and SR layers in the ventral hippocampus. In addition, both SLM and SR excitatory synapses display suppressed short-term synaptic plasticity in the ventral hippocampus. These morphological and functional changes are either absent or modest in the dorsal hippocampus. The input-independent synaptic changes induced by Lrrc4c deletion involve abnormal translocation of NGL-2 from the SR to SLM layer. These results suggest that Lrrc4c deletion moderately suppresses hippocampal excitatory synapse development and function in an input-independent manner.
IL-33 and IL-18 in Inflammatory Bowel Disease Etiology and Microbial Interactions

The IL-1 cytokines are a newly expanded family, with each of its 11 members playing an important role in health and disease. Typically acting as pro- or anti-inflammatory mediators of first-line innate immunity, their production is particularly important in the context of mucosal defenses, through handling breach of the delicate epithelial barrier and mediating a local immune response to invading pathogens. Mucosal immunity is often aberrantly orchestrated in intestinal diseases, such as Inflammatory Bowel Disease (IBD). Various studies have pointed to IL-1 cytokines as being important players in IBD with context-dependent roles, either through promoting auto-inflammatory mechanisms, or alleviating disease through protection against breach of pathogens across the epithelial barrier. This mini-review will succinctly examine the role of IL-1 family members in IBD, with a special focus on the recently described IL-33 as well as IL-18, and will explore the disease models within which these cytokines have been studied. Furthermore, we will examine the evidence of interplay of these cytokines with the gut microbiota, with hopes of summarizing our current knowledge of these family members and their potential for unraveling novel molecular mechanisms of IBD pathology.
Contextual Fear Conditioning Alter Microglia Number and Morphology in the Rat Dorsal Hippocampus

Contextual fear conditioning is a Pavlovian conditioning paradigm capable of rapidly creating fear memories to contexts, such as rooms or chambers. Contextual fear conditioning protocols have long been utilized to evaluate how fear memories are consolidated, maintained, expressed, recalled, and extinguished within the brain. These studies have identified the lateral portion of the amygdala and the dorsal portion of the hippocampus as essential for contextual fear memory consolidation. The current study was designed to evaluate how two different contextual fear memories alter amygdala and hippocampus microglia, brain derived neurotrophic factor (BDNF), and phosphorylated cyclic-AMP response element binding (pCREB). We find rats provided with standard contextual fear conditioning to have more microglia and more cells expressing BDNF in the dentate gyrus as compared to a context only control group. Additionally, standard contextual fear conditioning altered microglia morphology to become amoeboid in shape – a common response to central nervous system insult, such as traumatic brain injury, infection, ischemia, and more. The unpaired fear conditioning procedure (whereby non-reinforced and non-overlapping auditory tones were provided at random intervals during conditioning), despite producing equivalent levels of fear as the standard procedure, did not alter microglia, BDNF or pCREB number in any dorsal hippocampus or lateral amygdala brain regions. Despite this, the unpaired fear conditioning protocol produced some alterations in microglia morphology, but less compared to rats provided with standard contextual fear conditioning. Results from this study demonstrate that contextual fear conditioning is capable of producing large alterations to dentate gyrus plasticity and microglia, whereas unpaired fear conditioning only produces minor changes to microglia morphology. These data show, for the first time, that Pavlovian fear conditioning protocols can induce similar responses as trauma, infection or other insults within the central nervous system.
Does Transactional Memory Keep Its Promises? Results from an Empirical Study.

Transactional Memory (TM) promises to simplify parallel programming by replacing locks with atomic transactions. This is the first paper to assess the value proposition of TM based on a comparative case study with real programmers. Twelve students, working in teams of two, wrote a parallel desktop search engine in C/C++ during a fifteen week lab. Three randomly chosen study groups (TM teams) competed for the best performance using Intel’s Software Transactional Memory compiler and Pthreads, while three control groups (locks teams) competed using just Pthreads. The study provides empirical evidence that both supports the TM value proposition and at the same time points to problems with TM. The winning TM team’s program performed better than that of the winning locks team, and the TM winners were the first to have a prototype parallel search engine, four weeks earlier than the locks winners. Compared to the locks teams, the TM teams spent less than half the time debugging segmentation faults. On the other hand, TM teams had more problems tuning performance because TM performance was hard to predict. The study also provides insights into general difficulties programmers have with parallel programming. Some insights are technical; for example, some students wrongly assumed that it is safe to read shared variables outside critical sections, resulting in data races in the winning teams’ programs. Other insights are non-technical, including psychological ones; for example, the TM teams were less afraid of using parallel constructs, yet two of the teams procrastinated parallelization. Based on our insights, we elaborate on future research directions. We suggest refinements to TM constructs and tools. We also sketch how to automate similar case studies and propose a methodology for automating the evaluation of new language features for parallelism.
The Clinical and Genetic Features of Co-occurring Epilepsy and Autism Spectrum Disorder in Chinese Children

There is still no comprehensive description of the general population regarding clinical features and genetic etiology for co-occurring epilepsy and autism spectrum disorder (ASD) in Chinese children. This study was a retrospective study of children diagnosed with epilepsy and ASD from January 1st, 2015, to May 1st, 2018, at the Children's Hospital of Fudan University. A total of 117 patients met the inclusion criteria, and 103 subjects were eligible. Among them, 88 underwent genetic testing, and 47 children (53.4%) were identified as having pathogenic or likely pathogenic variants: 39 had single gene mutations (83.0%, 39/47), and eight had copy number variants (17.0%, 8/47), with SCN1A (14.9%, 7/47) and MECP2 (10.6%, 5/47) gene mutations being the most common. Mutations in other genes encoding voltage-gated ion channels including SCN2A, CACNA1A, CACNA1H, CACNA1D, and KCNQ2 were also common, but the number of individual cases for each gene was small. Epilepsy syndrome and epilepsy-associated syndrome were more common (P = 0.014), and higher rates of poly-therapy (P = 0.01) were used in the positive genetic test group than in the negative group. There were no statistically significant differences in drug-refractory epilepsy, ASD severity, or intellectual disability between the positive genetic test group and the negative genetic group. These data strongly indicate the need for ASD screening in children with epilepsy with voltage-gated ion channel gene variants for better diagnosis and early intervention.
Detection of Political Manipulation through Unsupervised Learning

Political campaigns circulate manipulative opinions in online communities to implant false beliefs and eventually win elections. Not only is this type of manipulation unfair, it also has long-lasting negative impacts on people’s lives. Existing tools detect political manipulation based on a supervised classifier, which is accurate when trained with large labeled data. However, preparing this data becomes an excessive burden and must be repeated often to reflect changing manipulation tactics. We propose a practical detection system that requires moderate groundwork to achieve a sufficient level of accuracy. The proposed system groups opinions with similar properties into clusters, and then labels a few opinions from each cluster to build a classifier. It also models each opinion with features deduced from raw data with no additional processing. To validate the system, we collected over a million opinions during three nation-wide campaigns in South Korea. The system reduced groundwork from 200K to nearly 200 labeling tasks, and correctly identified over 90% of manipulative opinions. The system also effectively identified transitions in manipulative tactics over time. We suggest that online communities perform periodic audits using the proposed system to highlight manipulative opinions and emerging tactics.
A Meta-Analytic Review of Predictors of Job Performance for Salespeople

This meta-analysis evaluated predictors of both objective and subjective sales performance. Biodata measures and sales ability inventories were good predictors of the ratings criterion, with corrected rs of . 52 and . 45, respectively. Potency (a subdimension of the Big 5 personality dimension Extraversion) predicted supervisor ratings of performance (r = .28) and objective measures of sales (r = .26). Achievement (a component of the Conscientiousness dimension) predicted ratings (r = .25) and objective sales (r = .41). General cognitive ability showed a correlation of.40 with ratings but only . 04 with objective sales. Similarly, age predicted ratings (r = .26) but not objective sales (r = -.06). On the basis of a small number of studies, interest appears to be a promising predictor of sales success.
Distributed Fault Detection and Isolation Filter Design for a Network of Heterogeneous Multiagent Systems

In this brief a distributed fault detection and isolation (FDI) methodology for a network of heterogeneous multiagent systems with different dynamics and order from one another is proposed. An FDI filter is designed such that the effects of disturbances and control inputs on the residual signals are minimized (for accomplishing the fault detection task) subject to the constraint that the transfer matrix function from the faults to the residuals is equal to a preassigned diagonal transfer matrix (for accomplishing the fault isolation task). Moreover, by utilizing the proposed methodology, isolation of simultaneous occurring faults can also be handled. Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. The extended LMI characterization is then used to reduce the conservativeness of the solution by eliminating the couplings between the Lyapunov matrices and the agents' matrices. Simulation results presented demonstrate the effectiveness and capabilities of our proposed design methodology.
An Anti-occlusion and Scale Adaptive Kernel Correlation Filter for Visual Object Tracking

Focusing on the issue that the conventional Kernel Correlation Filter (KCF) algorithm has poor performance in handling scale change and obscured objects, this paper proposes an anti-occlusion and scale adaptive tracking algorithm in the basis of KCF. The average Peak-to Correlation Energy and the peak value of correlation filtering response are used as the confidence indexes to determine whether the target is obscured. In the case of non-occlusion, we modify the searching scheme of the KCF. Instead of searching for a target with a fixed sample size, we search for the target area with multiple scales and then resize it into the sample size to compare with the learnt model. The scale factor with the maximum filter response is the best target scaling and is updated as the optimal scale for the following tracking. Once occlusion is detected, the model updating and scale updating are stopped. Experiments have been conducted on the OTB benchmark video sequences for compassion with other state-of-the-art tracking methods. The results demonstrate the proposed method can effectively improve the tracking success rate and the accuracy in the cases of scale change and occlusion, and meanwhile ensure a real-time performance.
Deriving Cyber Security Risks from Human and Organizational Factors - A Socio-technical Approach

Cyber security risks are socio-technical in nature. They result not just from technical vulnerabilities but also, more fundamentally, from the degradation of working practices over time – which move an organization across the boundary of secure practice to a place where attacks will not only succeed, but also have a significantly greater impact on the organization. Yet current risk analysis and management methodologies are not designed to detect these kinds of systemic risks. We present an approach, devised in the field, to deriving these risks – using a qualitative research methodology, akin to grounded theory, but based on preset coding descriptors. This allows organizational and individual behavior identified during interviews, observations or document research to be thematically analyzed, collated and mapped to potential risks, linked to poor working practices. The resulting risk factors can be linked together forming “risk narratives”, showing how the degradation of working practices in one part of the organization can contribute to undermining its ability to respond to cyber security threats in another part of the organization.
Preventing Negative Behaviors among Elementary-School Students through Enhancing Students' Social-Emotional and Character Development

Purpose. Examine the effects of a comprehensive, school-wide social-emotional and character development program using a positive youth development perspective. Specifically, we examined a mediation mechanism whereby positive academic-related behaviors mediated the intervention effects on substance use, violence, and sexual activity. Design. Matched-pair, cluster-randomized, controlled design. Setting. Twenty (10 intervention and 10 control) racially/ethnically diverse schools in Hawaii. Subjects. Elementary-aged students (N= 1784) from grade 5. Intervention. The Positive Action program. Measures. Students self-reported their academic behaviors, together with their substance use, violence, and voluntary sexual activity; teachers rated students' academic behaviors, substance use, and violence. Analysis. Structural equation modeling. Results. Students attending intervention schools reported significantly better academic behavior (B = .273, SE = .039, p < .001) and significantly less substance use (B = –.970, SE = .292, p < .01, incidence-rate ratio [IRR] = .379), violence (B = −1.410, SE = .296, p < .001, IRR = .244), and sexual activity (B = −2.415, SE = .608, p < .001, odds ratio = .089); boys reported more negative behaviors than girls. Intervention effects on student-reported substance use, violence, and sexual activity were mediated by positive academic behavior. Teacher reports corroborated these results, with rated academic behavior partially mediating the effects of the intervention on rated negative behaviors. Conclusion. This study (1) provides evidence that adds insight into one mechanism through which a social-emotional and character development program affects negative outcomes and (2) supports social-emotional and character development and positive youth development perspectives that posit that focusing on youths' assets may reduce negative behaviors.
Towards a Practical Clustering Analysis over Encrypted Data

Clustering analysis is one of the most significant unsupervised machine learning tasks, and it is utilized in various fields associated with privacy issues including bioinformatics, finance and image processing. In this paper, we propose a practical solution for privacy-preserving clustering analysis based on homomorphic encryption (HE). Our work is the first HE solution for the mean-shift clustering algorithm. To reduce the super-linear complexity of the original mean-shift algorithm, we adopt a novel random sampling method called dust sampling which perfectly fits in HE and achieves the linear complexity. We also substitute non-polynomial kernels by a new polynomial kernel so that it can be efficiently computed in HE. The HE implementation of our modified mean-shift clustering algorithm based on the approximate HE scheme HEAAN shows prominent performance in terms of speed and accuracy. It takes about 30 minutes with 99% accuracy over several public datasets with hundreds of data, and even for the dataset with 262, 144 data it takes only 82 minutes applying SIMD operations in HEAAN. Our results outperform the previously best known result (SAC 2018) over 400 times.