Miracle-dz/UniFAR-FTUs huggingface dataset:
A disaster preparedness and response project in Afghanistan: participants' perceptions.

AIM This paper is a report of a study to describe Emergency Mobile Unit team members' and healthcare professionals' perceptions of a disaster preparedness and response project and to explore the elements of participation that could support its sustainability. BACKGROUND Many developing countries have limited preparedness for disaster response. There is a need to better understand the role of national and local participation, and their interplay. We also need to consider the moderation and eventual planned withdrawal of international humanitarian organizations' support. Afghanistan is one example of a country in postdisaster development where the opportunity arose for an in-depth study of disaster preparedness and response. METHOD Data were collected in Finland and Afghanistan in 2004 using an ethnographic approach, with seven thematic interviews (n = 8) and two focus groups (n = 7). The participants were Afghan healthcare professionals and expatriates who had facilitated Emergency Mobile Unit training. FINDINGS Constraints in the project arose from uncoordinated implementation and poor job satisfaction, in addition to intrinsic characteristics of the situation. A second theme to emerge was that participation was a positive response to health emergencies. Thirdly, a need for further development and overall support for Emergency Mobile Units was clearly evident. CONCLUSION Improved coordination and measures to increase job satisfaction for national aid workers are needed, and a more positive knowledge-based response system and continued overall support for emergency mobile teams. Involving disaster-affected people and the local community, especially women, in health development projects will help to ensure both success and sustainability.
Room-Temperature H2 Gas Sensing Characterization of Graphene-Doped Porous Silicon via a Facile Solution Dropping Method

In this study, a graphene-doped porous silicon (G-doped/p-Si) substrate for low ppm H2 gas detection by an inexpensive synthesis route was proposed as a potential noble graphene-based gas sensor material, and to understand the sensing mechanism. The G-doped/p-Si gas sensor was synthesized by a simple capillary force-assisted solution dropping method on p-Si substrates, whose porosity was generated through an electrochemical etching process. G-doped/p-Si was fabricated with various graphene concentrations and exploited as a H2 sensor that was operated at room temperature. The sensing mechanism of the sensor with/without graphene decoration on p-Si was proposed to elucidate the synergetic gas sensing effect that is generated from the interface between the graphene and p-type silicon.
Joint effect of stalling and presentation quality on the quality-of-experience of streaming videos

Over-the-top (OTT) video streaming services have been growing rapidly in the last decade, and thus increasing Quality-of-Experience (QoE) of end users is of great interest in emerging services. Although, numerous subjective studies have been conducted to investigate the impact of video presentation quality and playback interruptions, understanding the interactions between impairment types is still an open problem. In this work, we develop a streaming video dataset that contains compressed videos with different distortion levels as well as playback stalling events. Then, a subjective user study is performed to measure the QoE of these videos. The results of our experiment reveal strong dependency between video presentation quality and playback interruptions that provides useful insight for designing QoE models in video streaming.
Contributing factors to weight gain during long‐term treatment with second‐generation antipsychotics. A systematic appraisal and clinical implications

The increased rates of both overweight and obesity reported in severely mentally‐ill patients are prevalently due to the use of second‐generation antipsychotics (SGAs). Hence, the main purpose of this article is to analyze systematically potential patient‐ and drug‐related factors which may increase the risk of weight gain during long‐term treatment with such medications. Literature information published in English since 1966 and last updated on 17 January 2009 was identified through different databases and using various combinations of search terms. Searches provided 242 articles, whereas 6 additional references were identified manually. Peer‐reviewed articles focusing on the risk of weight gain during SGA‐chronic treatment (at least 52 weeks, N = 81) were acquired. Data were extracted from the 39 peer‐reviewed articles which investigated factors potentially associated with an increased risk of this event. Evidence‐based information suggests that a number of factors, either patient‐ (age, baseline BMI/bodyweight, recent onset of psychotic episodes, need of concomitant psychotropic medications) or drug‐specific (relative receptorial affinity, timing of weight changes plateau, daily dose, iatrogenic concomitant changes in biochemical metabolic parameters) may contribute to increase either rates and/or magnitude of this effect during long‐term treatments with specific SGAs. All contributors and their relationship with specific drugs should be taken into consideration when designing a long‐term therapy with SGAs. Among the best studied agents (clozapine, olanzapine, and risperidone) of this class, the latter seems to be the most susceptible drug to the amplifying effects of both patient‐ and drug‐related factors on the risk of inducing weight changes during chronic treatments.
Mitochondria as targets for detection and treatment of cancer

Mitochondria are dynamic intracellular organelles that play a central role in oxidative metabolism and apoptosis. The recent resurgence of interest in the study of mitochondria has been fuelled in large part by the recognition that genetic and/or metabolic alterations in this organelle are causative or contributing factors in a variety of human diseases including cancer. Several distinct differences between the mitochondria of normal cells and cancer cells have already been observed at the genetic, molecular and biochemical levels. As reviewed in this article, certain of these alterations in mitochondrial structure and function might prove clinically useful either as markers for the early detection of cancer or as unique molecular sites against which novel and selective chemotherapeutic agents might be targeted.
Development and validation of the trait and state versions of the Post-Event Processing Inventory

ABSTRACT Background: Post-event processing (PEP) refers to negative and prolonged rumination following anxiety-provoking social situations. Although there are scales to assess PEP, they are situation-specific, some targeting only public-speaking situations. Furthermore, there are no trait measures to assess the tendency to engage in PEP. Objectives: The purpose of this research was to create a new measure of PEP, the Post-Event Processing Inventory (PEPI), which can be employed following all types of social situations and includes both trait and state forms. Design and method: Over two studies (study 1, N = 220; study 2, N = 199), we explored and confirmed the factor structure of the scale with student samples. Results: For each form of the scale, we found and confirmed that a higher-order, general PEP factor could be inferred from three sub-domains (intensity, frequency, and self-judgment). We also found preliminary evidence for the convergent, concurrent, discriminant/divergent, incremental, and predictive validity for each version of the scale. Both forms of the scale demonstrated excellent internal consistency and the trait form had excellent two-week test–retest reliability. Conclusion: Given the utility and versatility of the scale, the PEPI may provide a useful alternative to existing measures of PEP and rumination.
Structured binary feature extraction for hyperspectral imagery classification

In this paper, we propose a novel structured binary feature extraction method for hyperspectral image classification. To pursuit high discriminative ability and low memory cost, we resort to applying the learning to hash technique to the traditional spectral-spatial hyperspectral features. We show how the structured information among different kinds of features and different feature groups can be used to learn discriminative binary features for classification. Experiments on two standard benchmark hyperspectral data sets demonstrate the effectiveness of the proposed method.
A misleading feeling of happiness: metamemory for positive emotional and neutral pictures

ABSTRACT Emotional information is often remembered better than neutral information, but the emotional benefit for positive information is less consistently observed than the benefit for negative information. The current study examined whether positive emotional pictures are recognised better than neutral pictures, and further examined whether participants can predict how emotion affects picture recognition. In two experiments, participants studied a mixed list of positive and neutral pictures, and made immediate judgements of learning (JOLs). JOLs for positive pictures were consistently higher than for neutral pictures. However, recognition performance displayed an inconsistent pattern. In Experiment 1, neutral pictures were more discriminable than positive pictures, but Experiment 2 found no difference in recognition based on emotional content. Despite participants’ beliefs, positive emotional content does not appear to consistently benefit picture memory.
Thermal Identification, Model, and Experimental Validation of a Toroidally Wound Mover Linear-Switched Reluctance Machine

Thermal analysis is an important issue in machine design which allows to have a knowledge of the machine temperature rise. This paper presents the thermal analysis, modeling, and experiments of a linear-switched reluctance machine (LSRM) with toroidally wound mover and segmental structure. First, a 3-D heat flow model with the homogenized region for the presented LSRM is established using the thermal equivalent circuit. The equivalent thermal resistance of the model is developed together with the nodes forming of the thermal resistance network. The thermal identification to each component such as windings and core steel is performed. Then both the numerical 2-D and 3-D heat flow model for the presented LSRM are established by finite-element analysis which can give the detailed temperature distribution of the entire machine. At last, the actual experiment on a prototype is carried out, validating the accuracy, and feasibility of the thermal equivalent model above.
SNP ascertainment bias in population genetic analyses: Why it is important, and how to correct it

Whole genome sequencing and SNP genotyping arrays can paint strikingly different pictures of demographic history and natural selection. This is because genotyping arrays contain biased sets of pre‐ascertained SNPs. In this short review, we use comparisons between high‐coverage whole genome sequences of African hunter‐gatherers and data from genotyping arrays to highlight how SNP ascertainment bias distorts population genetic inferences. Sample sizes and the populations in which SNPs are discovered affect the characteristics of observed variants. We find that SNPs on genotyping arrays tend to be older and present in multiple populations. In addition, genotyping arrays cause allele frequency distributions to be shifted towards intermediate frequency alleles, and estimates of linkage disequilibrium are modified. Since population genetic analyses depend on allele frequencies, it is imperative that researchers are aware of the effects of SNP ascertainment bias. With this in mind, we describe multiple ways to correct for SNP ascertainment bias.
Radiation-induced heart disease in lung cancer radiotherapy

Background: Radiation-induced heart disease (RIHD), which affects the patients’ prognosis with both acute and late side effects, has been published extensively in the radiotherapy of breast cancer, lymphoma and other benign diseases. Studies on RIHD in lung cancer radiotherapy, however, are less extensive and clear even though the patients with lung cancer are delivered with higher doses to the heart during radiation treatment. Methods: In this article, after extensive literature search and analysis, we reviewed the current evidence on RIHD in lung cancer patients after their radiation treatments and investigated the potential risk factors for RIHD as compared to other types of cancers. Result: Cardiac toxicity has been found highly relevant in lung cancer radiotherapy. So far, the crude incidence of cardiac complications in the lung cancer patients after radiotherapy has been up to 33%. Conclusion: The dose to the heart, the lobar location of tumor, the treatment modality, the history of heart and pulmonary disease and smoking were considered as potential risk factors for RIHD in lung cancer radiotherapy. As treatment techniques improve over the time with better prognosis for lung cancer survivors, an improved prediction model can be established to further reduce the cardiac toxicity in lung cancer radiotherapy.
Complete tear of the lateral meniscus posterior root is associated with meniscal extrusion in anterior cruciate ligament deficient knees

This study aimed to evaluate the relationship between preoperative lateral meniscal extrusion (LME) and arthroscopic findings of lateral meniscus posterior root tear (LMPRT) in knees with anterior cruciate ligament (ACL) tear. Thirty‐five knees that had LMPRTs with concomitant ACL tears on arthroscopy were evaluated. Patients were divided into two groups, partial and complete root tears, via arthroscopic findings at the time of ACL reconstruction. For comparison, we added two groups, using the same database; 20 normal knees (normal group) and 20 ACL‐injured knees without LM injury (intact LM group). We retrospectively measured preoperative LMEs using magnetic resonance imaging (MRI). Twenty‐three knees had partial LMPRTs. Complete LMPRTs were observed in 12 knees. The average LME was −0.1 ± 0.4 mm in the normal group, 0.2 ± 0.5 mm in the intact LM group, 0.4 ± 0.8 mm in the partial LMPRT group, and 2.0 ± 0.6 mm in the complete LMPRT group. A significant difference in preoperative LMEs was observed between the complete LMPRT group and the other groups (p < 0.001). The receiver operating curve analysis, which distinguishes a partial tear from a complete tear, identified an optimal cut‐off point of 1.1 mm for preoperative LME. This LME cut‐off had a sensitivity of 100% and specificity of 83% for complete LMPRT. We found that preoperative LMEs were larger in complete LMPRTs associated with ACL injuries than in partial LMPRTs. Our results suggest that preoperative MRI‐detected LME may be a useful indicator for estimating LMPRT severity in ACL‐injured knees. Level of evidence: Retrospective comparative study level IV. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1894–1900, 2018.
Spectral-spatial linear discriminant analysis for hyperspectral image classification

We propose a spectral-spatial linear discriminant analysis method (LDA) for dimensionality reduction in hyperspectral image. The proposed method uses a local scatter of the small neighborhood as a regularizer to incorporate into the objective function of the LDA. The intrinsic idea is to design an optimal linear transformation that makes these samples among the neighborhood approximate the local mean in the low-dimensional feature space while simultaneously preserving the original property of LDA. Experimental results based on both adequate training samples and inadequate training samples demonstrate that the proposed method outperforms several traditional dimensionality reduction methods.
A Novel Method of Identifying Paddy Seed Varieties

This paper presents a novel method for identifying three varieties (Taikong 9, Tainan 11, and Taikong 14) of foundation paddy seeds. Taikong 9, Tainan 11, and Taikong 14 paddy seeds are indistinguishable by inspectors during seed purity inspections. The proposed method uses image segmentation and a key point identification algorithm that can segment paddy seed images and extract seed features. A back propagation neural network was used to establish a classifier based on seven features that could classify the three paddy seed varieties. The classification accuracies of the resultant classifier for varieties Taikong 9, Tainan 11, and Taikong 14 were 92.68%, 97.35% and 96.57%, respectively. The experimental results indicated that the three paddy seeds can be differentiated efficiently using the developed system.
Effect of Disbonding Between a Composite Patch and a Cracked Aluminum Plate on the Stress Intensity Factor

Bonded composite patch repairs to metallic structures is receiving increased attention in the recent years. It offers various advantages over rivetted doubler, particularly for airframe repairs. This article presents the crack growth behavior of an edge cracked aluminum plate repaired using boron/epoxy composite patch. The effect of the size and location of this disbond on the tensile behavior of the repaired plate is investigated. An analysis procedure, involving finite element modeling of the cracked plate, adhesive, and composite patch, is conducted to compute the stress intensity factor. The results indicate that the crack growth rate is dominated by the stress intensity factor and the size of the pre-existing disbonds. Cracking of the plate and propagation of the disbond results in an increase in the patch deformation.
Direct Design of Partially Prestressed Concrete Hollow Beams

Tests were conducted on three hollow partially prestressed concrete beams subjected to combined loading in bending, shear and torsion. The beams were designed using the Direct Design Method which is based on the Lower Bound Theorem of the Theory of Plasticity. All beams were of 300 × 300 mm cross-section, 3.8 m in length, and possessed a 200 × 200 mm hollow core and 50 mm wall thickness. The two main variables studied were the ratio in the web of the maximum shear stress due to the twisting moment, to the shear stress arising from the shear force, which varied between 1.09 and 6.85, and the ratio of the maximum twisting moment to the maximum bending moment which varied between 0.35 and 2.62. Good agreement was found between design and experimental failure loads. All beams failed near the design loads and underwent ductile behaviour up to failure. The results indicate that the Direct Design Method can be successfully used to design partially prestressed concrete hollow beams which will cater for the combined effect of bending, shear and torsion loads.
Scaling Similarity Joins over Tree-Structured Data

Given a large collection of tree-structured objects (e.g., XML documents), the similarity join finds the pairs of objects that are similar to each other, based on a similarity threshold and a tree edit distance measure. The state-of-the-art similarity join methods compare simpler approximations of the objects (e.g., strings), in order to prune pairs that cannot be part of the similarity join result based on distance bounds derived by the approximations. In this paper, we propose a novel similarity join approach, which is based on the dynamic decomposition of the tree objects into subgraphs, according to the similarity threshold. Our technique avoids computing the exact distance between two tree objects, if the objects do not share at least one common subgraph. In order to scale up the join, the computed subgraphs are managed in a two-layer index. Our experimental results on real and synthetic data collections show that our approach outperforms the state-of-the-art methods by up to an order of magnitude.
Fire Performance of Corrosion-Damaged Reinforced Concrete Beams

This experimental study examines the effects of fire on corrosion-damaged reinforced concrete beams. Nine beams were cast with the same external dimensions and amount of reinforcement. Corrosion was induced in the beams by a constant current source. The beams were tested at constant service load while being exposed to the CAN/ULC-S101 time-temperature curve. The results indicated that the deflection of reinforced concrete beams increased during a fire exposure as the level of corrosion damage increased. The corrosion products within the pores of the concrete provided a limited insulating effect on the heat front penetration through the concrete cover. Temperature differential developed at the steel level was shown to help delay failure of the beams by the development of the axial thrust force. A major factor affecting the performance of corrosion damaged beams during a fire exposure was the ability of the concrete cover to remain in place.
Visual Analysis of Collective Anomalies Through High-Order Correlation Graph

Detecting, analyzing and reasoning collective anomalies is important for many real-life application domains such as facility monitoring, software analysis and security. The main challenges include the overwhelming number of low-risk events and their multifaceted relationships which form the collective anomaly, the diversity in various data and anomaly types, and the difficulty to incorporate domain knowledge in the anomaly analysis process. In this paper, we propose a novel concept of high-order correlation graph (HOCG). Compared with the previous correlation graph definition, HOCG achieves better user interactivity, computational scalability, and domain generality through synthesizing heterogeneous types of nodes, attributes, and multifaceted relationships in a single graph. We design elaborate visual metaphors, interaction models, and the coordinated multiple view based interface to allow users to fully unleash the visual analytics power over HOCG. We conduct case studies in two real-life application domains, i.e., facility monitoring and software analysis. The results demonstrate the effectiveness of HOCG in the overview of point anomalies, detection of collective anomalies, and reasoning process of root cause analysis.
Basic Simulation Environment for Highly Customized Connected and Autonomous Vehicle Kinematic Scenarios

To enhance the reality of Connected and Autonomous Vehicles (CAVs) kinematic simulation scenarios and to guarantee the accuracy and reliability of the verification, a four-layer CAVs kinematic simulation framework, which is composed with road network layer, vehicle operating layer, uncertainties modelling layer and demonstrating layer, is proposed in this paper. Properties of the intersections are defined to describe the road network. A target position based vehicle position updating method is designed to simulate such vehicle behaviors as lane changing and turning. Vehicle kinematic models are implemented to maintain the status of the vehicles when they are moving towards the target position. Priorities for individual vehicle control are authorized for different layers. Operation mechanisms of CAVs uncertainties, which are defined as position error and communication delay in this paper, are implemented in the simulation to enhance the reality of the simulation. A simulation platform is developed based on the proposed methodology. A comparison of simulated and theoretical vehicle delay has been analyzed to prove the validity and the creditability of the platform. The scenario of rear-end collision avoidance is conducted to verify the uncertainties operating mechanisms, and a slot-based intersections (SIs) control strategy is realized and verified in the simulation platform to show the supports of the platform to CAVs kinematic simulation and verification.