Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychosocial Effects on US Government Personnel of Exposure to the 1998 Terrorist Attack on the US Embassy in Nairobi

Objective: The mental health effects of major terrorist attacks on diplomatic government personnel have not been well studied. This study examined the psychiatric and psychosocial effects of the 1998 terrorist bombing of the US Embassy in Nairobi, Kenya, on US government personnel exposed to the bombing. Method: At 8–10 months after the bombing, 179 US government employees (53 Americans, 126 Kenyans, 53% male, age mean = 40.6 and SD = 8.4 years ranging 21–65) were assessed with the Diagnostic Interview Schedule for DSM-IV for disaster-related psychiatric diagnoses and the Disaster Supplement Interview and Questionnaire about their immediate disaster experiences, subjective responses, mental health interventions/treatment, safety perceptions, and coping. Results: About one-third (32%) of these US government personnel developed postdisaster psychiatric disorders, mostly bombing-related PTSD (20%), but few received psychiatric treatment. Prevalence rates of all postdisaster psychiatric disorders, including bombing-related PTSD, were similar between subgroups of Americans and Kenyans, despite the Kenyans reporting more direct disaster trauma exposures, subjective postdisaster distress, and posttraumatic stress symptoms. These US government personnel had fewer psychiatric consequences of the Nairobi bombing than their previously studied civilian counterparts. Conclusions: Possible explanatory factors in the lower prevalence of postdisaster psychopathology in these government personnel compared to the civilians are selection for greater personal resilience for government employment and stigma-based underreporting of mental health needs in governmental workplaces. Stigma is a potential barrier to psychiatric treatment that needs to be addressed in government workplaces.
DNA methylation-mediated modulation of rapid desiccation tolerance acquisition and dehydration stress memory in the resurrection plant Boea hygrometrica

Pre-exposure of plants to various abiotic conditions confers improved tolerance to subsequent stress. Mild drought acclimation induces acquired rapid desiccation tolerance (RDT) in the resurrection plant Boea hygrometrica, but the mechanisms underlying the priming and memory processes remain unclear. In this study, we demonstrated that drought acclimation-induced RDT can be maintained for at least four weeks but was completely erased after 18 weeks based on a combination of the phenotypic and physiological parameters. Global transcriptome analysis identified several RDT-specific rapid dehydration-responsive genes related to cytokinin and phospholipid biosynthesis, nitrogen and carbon metabolism, and epidermal morphogenesis, most of which were pre-induced by drought acclimation. Comparison of whole-genome DNA methylation revealed dehydration stress-responsive hypomethylation in the CG, CHG, and CHH contexts and acclimation-induced hypermethylation in the CHH context of the B. hygrometrica genome, consistent with the transcriptional changes in methylation pathway genes. As expected, the global promoter and gene body methylation levels were negatively correlated with gene expression levels in both acclimated and dehydrated plants but showed no association with transcriptional divergence during the procedure. Nevertheless, the promoter methylation variations in the CG and CHG contexts were significantly associated with the differential expression of genes required for fundamental genetic processes of DNA conformation, RNA splicing, translation, and post-translational protein modification during acclimation, growth, and rapid dehydration stress response. It was also associated with the dehydration stress-induced upregulation of memory genes, including pre-mRNA-splicing factor 38A, vacuolar amino acid transporter 1-like, and UDP-sugar pyrophosphorylase, which may contribute directly or indirectly to the improvement of dehydration tolerance in B. hygrometrica plants. Altogether, our findings demonstrate the potential implications of DNA methylation in dehydration stress memory and, therefore, provide a molecular basis for enhanced dehydration tolerance in plants induced by drought acclimation.
Causal judgments about atypical actions are influenced by agents' epistemic states

A prominent finding in causal cognition research is people's tendency to attribute increased causality to atypical actions. If two agents jointly cause an outcome (conjunctive causation), but differ in how frequently they have performed the causal action before, people judge the atypically acting agent to have caused the outcome to a greater extent. In this paper, we argue that it is the epistemic state of an abnormally acting agent, rather than the abnormality of their action, that is driving people's causal judgments. Given the predictability of the normally acting agent's behaviour, the abnormal agent is in a better position to foresee the consequences of their action. We put this hypothesis to test in four experiments. In Experiment 1, we show that people judge the atypical agent as more causal than the normally acting agent, but also judge the atypical agent to have an epistemic advantage. In Experiment 2, we find that people do not judge a causal difference if no epistemic advantage for the abnormal agent arises. In Experiment 3, we replicate these findings in a scenario in which the abnormal agent's epistemic advantage generalises to a novel context. In Experiment 4, we extend these findings to mental states more broadly construed and develop a Bayesian network model that predicts the degree of outcome-oriented mental states based on action normality and epistemic states. We find that people infer mental states like desire and intention to a greater extent from abnormal behaviour when this behaviour is accompanied by an epistemic advantage. We discuss these results in light of current theories and research on people's preference for abnormal causes.
Novel insights from the Plasmodium falciparum sporozoite-specific proteome by probabilistic integration of 26 studies

Plasmodium species, the causative agent of malaria, have a complex life cycle involving two hosts. The sporozoite life stage is characterized by an extended phase in the mosquito salivary glands followed by free movement and rapid invasion of hepatocytes in the human host. This transmission stage has been the subject of many transcriptomics and proteomics studies and is also targeted by the most advanced malaria vaccine. We applied Bayesian data integration to determine which proteins are not only present in sporozoites but are also specific to that stage. Transcriptomic and proteomic Plasmodium data sets from 26 studies were weighted for how representative they are for sporozoites, based on a carefully assembled gold standard for Plasmodium falciparum (Pf) proteins known to be present or absent during the sporozoite life stage. Of 5418 Pf genes for which expression data were available at the RNA level or at the protein level, 975 were identified as enriched in sporozoites and 90 specific to them. We show that Pf sporozoites are enriched for proteins involved in type II fatty acid synthesis in the apicoplast and GPI anchor synthesis, but otherwise appear metabolically relatively inactive in the salivary glands of mosquitos. Newly annotated hypothetical sporozoite-specific and sporozoite-enriched proteins highlight sporozoite-specific functions. They include PF3D7_0104100 that we identified to be homologous to the prominin family, which in human has been related to a quiescent state of cancer cells. We document high levels of genetic variability for sporozoite proteins, specifically for sporozoite-specific proteins that elicit antibodies in the human host. Nevertheless, we can identify nine relatively well-conserved sporozoite proteins that elicit antibodies and that together can serve as markers for previous exposure. Our understanding of sporozoite biology benefits from identifying key pathways that are enriched during this life stage. This work can guide studies of molecular mechanisms underlying sporozoite biology and potential well-conserved targets for marker and drug development.
Autocatalytic activation of a malarial egress protease is druggable and requires a protein cofactor

Malaria parasite egress from host erythrocytes (RBCs) is regulated by discharge of a parasite serine protease called SUB1 into the parasitophorous vacuole (PV). There, SUB1 activates a PV‐resident cysteine protease called SERA6, enabling host RBC rupture through SERA6‐mediated degradation of the RBC cytoskeleton protein β‐spectrin. Here, we show that the activation of Plasmodium falciparum SERA6 involves a second, autocatalytic step that is triggered by SUB1 cleavage. Unexpectedly, autoproteolytic maturation of SERA6 requires interaction in multimolecular complexes with a distinct PV‐located protein cofactor, MSA180, that is itself a SUB1 substrate. Genetic ablation of MSA180 mimics SERA6 disruption, producing a fatal block in β‐spectrin cleavage and RBC rupture. Drug‐like inhibitors of SERA6 autoprocessing similarly prevent β‐spectrin cleavage and egress in both P. falciparum and the emerging zoonotic pathogen P. knowlesi. Our results elucidate the egress pathway and identify SERA6 as a target for a new class of antimalarial drugs designed to prevent disease progression.
All‐cause mortality predicted by peak oxygen uptake differs depending on spirometry pattern in patients with heart failure and reduced ejection fraction

In patients with heart failure and reduced ejection fraction (HFrEF), it remains unclear how exacerbated impairments in peak exercise oxygen uptake (V̇O2peak) caused by coexistent obstructive or restrictive ventilatory defects affect mortality risk. We evaluated in patients with HFrEF, whether demonstrating either an obstructive or restrictive‐patterned ventilatory defect on spirometry affects V̇O2peak to yield all‐cause mortality risk predicted by V̇O2peak that is spirometry pattern specific.
Time distribution for pharmacists conducting a randomized controlled trial—An observational time and motion study

Introduction An expected future increase in older adults will demand changes in health care delivery, making development, implementation and evaluation of new health care models essential. The rationale for political decision-making concerning the implementation and application of interventions in health care should include cost estimations, specifically those involving clinical interventions. To provide such data knowledge of time spent on the intervention is imperative. Time and motion methodology is suitable to quantify health care personnel’s time distribution. Aim To investigate the time distribution for pharmacists conducting a randomized controlled trial (RCT) implementing a clinical intervention. Materials and methods The setting was an RCT with a 5-step pharmacist-intervention in collaboration with the interdisciplinary team in a geriatric ward. Two pharmacists were involved in the trial during the observation period. Pharmacist activities, classified as RCT-tasks (intervention or administrative), non-RCT tasks and social/breaks, were recorded applying the Work Observation Method By Activity Timing methodology, enabling recording of predefined work tasks as well as interruptions and multitasking. One observer collected data over eight weeks. Results In total, 109.1 hours were observed resulting in 110.2 hours total task time, including multitasking. RCT tasks comprised 85.4% of the total observed time, and nearly 60% of the RCT time was spent on intervention tasks. Medication reviews was the most time consuming task, accounting for 32% of the observed time. The clinical pharmacists spent 14% of the intervention time communicating verbally, mainly with patients and healthcare professionals. Conclusion During the RCT, the clinical pharmacists spent about half their time performing the actual intervention. Consequently, costs for providing such a clinical pharmacist service should reflect actual time spent; otherwise, we may risk overestimating theoretical costs.
Salient Object Detection Based on Visual Perceptual Saturation and Two-Stream Hybrid Networks

Inspired by the perceived saturation of human visual system, this paper proposes a two-stream hybrid networks to simulate binocular vision for salient object detection (SOD). Each stream in our system consists of unsupervised and supervised methods to form a two-branch module, so as to model the interaction between human intuition and memory. The two-branch module parallel processes visual information with bottom-up and top-down SODs, and output two initial saliency maps. Then a polyharmonic neural network with random-weight (PNNRW) is utilized to fuse two-branch’s perception and refine the salient objects by learning online via multi-source cues. Depend on visual perceptual saturation, we can select optimal parameter of superpixel for unsupervised branch, locate sampling regions for PNNRW, and construct a positive feedback loop to facilitate perception saturated after the perception fusion. By comparing the binary outputs of the two-stream, the pixel annotation of predicted object with high saturation degree could be taken as new training samples. The presented method constitutes a semi-supervised learning framework actually. Supervised branches only need to be pre-trained initial, the system can collect the training samples with high confidence level and then train new models by itself. Extensive experiments show that the new framework can improve performance of the existing SOD methods, that exceeds the state-of-the-art methods in six popular benchmarks.
An improved parameter identification method of redundant manipulator

To achieve more accurate simulation and control in the use of the manipulator, it is necessary to establish an accurate dynamic model of the redundant manipulator. The research of this article focuses on the dynamic parameter identification method of the redundant manipulator. In the study, the spinor theory is applied to the Newton–Euler dynamic equation, the Coulomb + viscous friction model is adopted, and the minimum parameter set is obtained by linearization derivation. The parameter identification of the manipulator is realized using the method of offline identification of the measured current, and the coefficient of the excitation trajectory is optimized using the nonlinear optimization function. Finally, the parameter set with high accuracy is obtained, and the motion trajectory of each joint can be obtained. The scheme has high accuracy and can meet the needs of practical application. To verify the accuracy and reliability of this method, we have carried out experiments on a service robot “Walker” and obtained the desired results.
Inverse and forward kinematics and workspace analysis of a novel 5-DOF (3T2R) parallel–serial (hybrid) manipulator

The proposed study provides a solution of the inverse and forward kinematic problems and workspace analysis for a five-degree-of-freedom parallel–serial manipulator, in which the parallel kinematic chain is made in the form of a tripod and the serial kinematic chain is made in the form of two carriages displaced in perpendicular directions. The proposed manipulator allows to realize five independent movements—three translations and two rotations motion pattern (3T2R). Analytical relationships between the coordinates of the end-effector and five controlled movements provided by manipulator’s drives (generalized coordinates) were determined. The approach of reachable workspace calculation was defined with respect to available design constraints of the manipulator based on the obtained algorithms of the inverse and forward kinematics. Case studies are considered based on the obtained algorithms of inverse and forward kinematics. For the inverse kinematic problem, the solution is obtained in accordance with the given laws of position and orientation change of the end-effector, corresponding to the motion along a spiral-helical trajectory. For the forward kinematic problem, various assemblies of the manipulator are obtained at the same given values of the generalized coordinates. An example of reachable workspace designing finalizes the proposed study. Dimensions and extreme values of the end-effector orientation angles are calculated.
Leonurine Alleviates Hypoxia-Induced Myocardial Damage by Regulating miRNAs

Objective miRNAs as pharmaco-targets have been investigated in multifarious diseases. Our study aimed to determine whether leonurine was a potential cardioprotective agent by targeting miRNAs in hypoxia-stimulated mice and H9c2 cardiomyocytes. Methods Cell proliferation and apoptosis were examined by CCK-8 and TUNEL assay in hypoxia-stimulated rat H9c2 cardiomyocytes. miRNAs expression levels in cardiomyocytes in response to hypoxia stimulation were detected by RT-qPCR. Mice with myocardial injury were induced by chronic intermittent hypoxia stimulation. Results Leonurine alleviated hypoxia-induced cardiac hypertrophy in mice. Moreover, up-regulation of miR-31 and down-regulation of miR-210 in hypoxia-stimulated mice were reversed by leonurine administration. Leonurine exhibited cardioprotective activity in an vitro cell model of hypoxia-stimulated rat H9c2 cardiomyocytes, reflecting that the compound improved hypoxia-induced growth inhibition and apoptosis of cardiomyocytes. TUNEL assay revealed that transfection of miR-31 inhibitors or miR-210 mimics abrogated hypoxia-induced cardiomyocyte apoptosis. In contrast to that, miR-31 mimics or miR-210 inhibitors counteracted the anti-apoptotic effect of leonurine on hypoxia-treated rat H9c2 cardiomyocytes. Conclusion Our findings suggest that miR-31 and miR-210 as the upstream regulators of leonurine are involved in hypoxia-induced cardiomyocyte apoptosis. Leonurine can target miRNAs to protect against hypoxia-induced myocardial damage. miRNAs as potential drug targets may provide prospective therapeutic strategies for the treatment of myocardial damage.
Robot visual measurement and grasping strategy for roughcastings

To overcome the challenging problem of visual measurement and grasping of roughcasts, a visual grasping strategy for an industrial robot is designed and implemented on the basis of deep learning and a deformable template matching algorithm. The strategy helps realize the positioning recognition and grasping guidance for a metal blank cast in complex backgrounds under the interference of external light. The proposed strategy has two phases: target detection and target localization. In the target detection stage, a deep learning algorithm is used to recognize the combined features of the surface of an object for a stable recognition of the object in nonstructured environments. In the target localization stage, high-precision positioning of metal casts with an unclear contour is realized by combining the deformable template matching and LINE-MOD algorithms. The experimental results show that the system can accurately provide visual grasping guidance for robots.
Nobiletin Inhibits Cell Growth, Migration and Invasion, and Enhances the Anti-Cancer Effect of Gemcitabine on Pancreatic Cancer Cells

Natural products are very promising adjuvants with a variety of biological activities. Nobiletin, a citrus polymethoxyflavone, has been shown to exert an anticancer effect in various cell lines. In this study, we investigated the effects of nobiletin on cell viability, sphere formation, migration and invasion of pancreatic cancer cells, and the underlying mechanisms. Our results demonstrate that nobiletin significantly inhibited PANC-1 cell migration and invasion, and these effects were associated with downregulation of MMP-2. We also found that nobiletin, in a low concentration, exhibited a strong inhibitory effect on sphere formation. The potential molecular mechanisms were related to significant downregulation of p-mTOR and p-STAT3. Furthermore, we found that nobiletin combined with gemcitabine synergistically inhibited PANC-1 cell viability and sphere formation. The underlying mechanisms of the synergistic inhibition on growth were associated with decreases in p-STAT3 expression. Overall, our results suggest that nobiletin may be a promising candidate for pancreatic cancer adjuvant treatment.
Baicalein Exerts Anti-Neuroinflammatory Effects by Inhibiting the TLR4-ROS /NF-κB-NLRP3 Inflammasome

Emerging evidence indicates that NOD-like receptor protein 3 (NLRP3) inflammasome-induced inflammation plays a critical role in the pathogenesis of Parkinson’s disease (PD). Baicalein has been considered as a possible option for PD treatment based on its anti-neuroinflammatory effects. However, no studies have elucidated the precise mechanisms underlying the anti-neuroinflammatory activity of baicalein, particularly inflammasome-mediated effects. In this present study, rotenone-induced PD mice and BV2 microglia were used to investigate the anti-neuroinflammatory effects of baicalein and explore its underlying mechanism in vivo and in vitro. The results demonstrated that baicalein alleviated motor impairments and attenuated several inflammatory responses in rotenone-induced PD mice. Also, baicalein inhibited the expression of NLRP3 and activated caspase-1 in brain tissues. Correspondingly, baicalein prominently suppressed the inflammatory response in BV2 microglia induced by rotenone. Furthermore, in vitro data showed that baicalein suppressed the expression of NLRP3 and activated caspase-1 by abrogating the upregulation of ROS, as well as by inhibiting the TLR4/NF-κB signaling cascade. Overall, the results of the present study indicated that baicalein exerted anti-neuroinflammatory effects partly by inhibiting activation of the NLRP3 inflammasome, and targeting NLRP3 inflammasome signaling offers a novel therapeutic strategy for PD treatment.
Scalable information-theoretic path planning for a rover-helicopter team in uncertain environments

Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different bimodal probability distributions or introduce bias toward one mode of a bimodal probability distribution. The use of a standard deviation (SD) metric reduces bias while retaining the ability to distinguish between higher and lower risk distributions. Areas of high SD can be safely explored through observation with an autonomous Mars Helicopter allowing safer and faster path plans for ground-based rovers. First, this study presents a single-agent information-theoretic utility-based path planning method for a highly correlated uncertain environment. Then, an information-theoretic two-stage multiagent rapidly exploring random tree framework is presented, which guides Mars helicopter through regions of high SD to reduce uncertainty for the rover. In a Monte Carlo simulation, we compare our information-theoretic framework with a rover-only approach and a naive approach, in which the helicopter scouts ahead of the rover along its planned path. Finally, the model is demonstrated in a case study on the Jezero region of Mars. Results show that the information-theoretic helicopter improves the travel time for the rover on average when compared with the rover alone or with the helicopter scouting ahead along the rover’s initially planned route.