Miracle-dz/UniFAR-FTUs huggingface dataset:
Average individuals tweet more often during extreme events: An ideal mechanism for social contagion

Natural disasters are becoming increasingly expensive as climate change and development are exposing communities to greater risks. Disaster preparation and recovery are critical for climate change resilience, and social media is being used more and more to communicate before, during, and after disasters. While there is a growing body of research aimed at understanding how people use social media surrounding disaster events, most existing work has focused on a single disaster case study. In the present study, we analyze five of the costliest disasters in the last decade in the United States (Hurricanes Irene and Sandy, two sets of tornado outbreaks, and flooding in Louisiana) through the lens of Twitter. In particular, we explore the frequency of both generic and specific food-security related terms, and quantify the relationship between network size and Twitter activity during disasters. We find differences in tweet volume for keywords depending on disaster type, with people using Twitter more frequently in preparation for Hurricanes, and for real-time or recovery information for tornado and flooding events. Further, we find that people share a host of general disaster and specific preparation and recovery terms during these events. Finally, we find that among all account types, individuals with “average” sized networks are most likely to share information during these disasters, and in most cases, do so more frequently than normal. This suggests that around disasters, an ideal form of social contagion is being engaged in which average people rather than outsized influentials are key to communication. These results provide important context for the type of disaster information and target audiences that may be most useful for disaster communication during varying extreme events.
Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation

The aim of the present study was to investigate more colon cancer-related genes in different stages. Gene expression profile E-GEOD-62932 was extracted for differentially expressed gene (DEG) screening. Series test of cluster analysis was used to obtain significant trending models. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, functional and pathway enrichment analysis were processed and a pathway relation network was constructed. Gene co-expression network and gene signal network were constructed for common DEGs. The DEGs with the same trend were clustered and in total, 16 clusters with statistical significance were obtained. The screened DEGs were enriched into small molecule metabolic process and metabolic pathways. The pathway relation network was constructed with 57 nodes. A total of 328 common DEGs were obtained. Gene signal network was constructed with 71 nodes. Gene co-expression network was constructed with 161 nodes and 211 edges. ABCD3, CPT2, AGL and JAM2 are potential biomarkers for the diagnosis of colon cancer.
A Model for Understanding Social Commerce

When it comes to purchasing products and services, customers usually display different decision making behaviors although most agree that decisions can be influenced by other people. Since the social web provides a discussion platform for customers, it can be leveraged by companies to lean the discussion to their advantage and influence customers‟ purchase decisions. Recently, an effort to study social commerce was started, with a focus on extracting value from the social web for both businesses and customers. In this paper we aim to contribute to that effort by evaluating the effects of the social web on various stages of purchase decision making and we propose a model for understanding social commerce.
Evaluation of a high framerate multi-exposure laser speckle contrast imaging setup

We present a first evaluation of a new multi-exposure laser speckle contrast imaging (MELSCI) system for assessing spatial variations in the microcirculatory perfusion. The MELSCI system is based on a 1000 frames per second 1-megapixel camera connected to a field programmable gate arrays (FPGA) capable of producing MELSCI data in realtime. The imaging system is evaluated against a single point laser Doppler flowmetry (LDF) system during occlusionrelease provocations of the arm in five subjects. Perfusion is calculated from MELSCI data using current state-of-the-art inverse models. The analysis displayed a good agreement between measured and modeled data, with an average error below 6%. This strongly indicates that the applied model is capable of accurately describing the MELSCI data and that the acquired data is of high quality. Comparing readings from the occlusion-release provocation showed that the MELSCI perfusion was significantly correlated (R=0.83) to the single point LDF perfusion, clearly outperforming perfusion estimations based on a single exposure time. We conclude that the MELSCI system provides blood flow images of enhanced quality, taking us one step closer to a system that accurately can monitor dynamic changes in skin perfusion over a large area in real-time.
Intrinsic slip on hydrophobic surfaces

Continuum models often fail to correctly describe fluids in m icro and nano devices. For simple fluids departures from the standard behavior could be ascrib ed to inappropriateness of the continuum assumption and to violations of the no-slip condition. I n fact liquids behave as continua, with the exception of extreme confinement on length scales of few m olecular diameters, where a new regime – single file motion – sets in [1]. Instead, slippage at the wall is frequently observed, the flow field considerably differing from classical prediction s. In the present paper the intrinsic slip is addressed via Molecular Dynamics simulations of a Couett e flow of liquid water on a hydrophobic surface formed by a Lennard-Jones solid coated with a Sel f Assembled Monolayer (SAM) of octadecyltrichlorosilane (OTS), a widely used technology for wall functionalization. The model reproduces several features of the OTS-SAM coating, e.g. cont a t angle of water and the tilting of OTS molecules with respect to the surface normal. The system exh ibits slippage and the orientation of the OTS molecules is found to induce a preferential slip directi on. Overall, the inferred slippage cannot explain the larger slip length measured in experiments, pro viding indirect evidence of apparent slip, presumably due to gas trapping at the surface.
Advances in Betavoltaic Power Sources

This paper presents a review on betavoltaic cells including challenges existing within the technology, and research and development currently being conducted. Potential applications for low-power Betavoltaic sources may be found in distributed power systems, unattended sensors, surveillance, remote power, anti-tamper and bio-medical devices & implants. Though betavoltaic cells have been under development for more than 50 years the literature is sporadic. The energy conversion efficiencies of the betavoltaic cells are still below 10 % and there are number of challenges in this technology. The better radiation resistance material such as SiC and GaN have been considered for p-n junction material and tritium (H 3 ) and nickel isotope (N 63 ) have been considered as best radioactive sources as their energy spectra is suitable for absorption in the semiconductor. The substrate material that serves as the sync or storage medium for a radioisotope source has issues associated with loading techniques, thin-film properties, beta-particle interaction, and defect damage. Recent advances in experimental and theoretical works presented in this paper are geared towards enhancing the energy conversion efficiency and durability of the betavoltaic cell.
Tolerance and sequestration of macroalgal chemical defenses by an Antarctic amphipod: a 'cheater' among mutualists

Shallow-water communities along the western Antarctic Peninsula support forests of large, mostly chemically defended macroalgae and dense assemblages of macroalgal-associated amphipods, which are thought to exist together in a community-wide mutualism. The amphipods benefit the chemically defended macrophytes by consuming epiphytic algae and in turn benefit from an associational refuge from fish predation. In the present study, we document an exception to this pattern. The amphipod Paradexamine fissicauda is able to consume Plocamium carti- lagineum and Picconiella plumosa, 2 species of sympatric, chemically defended red macroalgae. In previous studies, Plocamium cartilagineum was one of the most strongly deterrent algae in the community to multiple consumers, and was found here to be unpalatable to 5 other amphipod spe- cies which utilize it as a host in nature. Paradexamine fissicauda maintained on a diet of Ploca - mium cartilagineum for 2 mo were much less likely to be eaten by fish than Paradexamine fissi- cauda maintained on a red alga which does not elaborate chemical defenses, or than a different but morphologically similar sympatric amphipod species. Halogenated secondary metabolites pro- duced by Plocamium cartilagineum were identified from tissues of the Paradexamine fissicauda that had eaten it but not those which had eaten the undefended red alga. This indicates that P. fissi- cauda is sequestering the potent chemical defenses of Plocamium cartilagineum for its own use.
When is the Rat Retrosplenial Cortex Required for Stimulus Integration?

The rodent retrosplenial cortex is known to be vital for spatial cognition, but evidence has also pointed to a role in processing nonspatial information. It has been suggested that the retrosplenial cortex may serve as a site of integration of incoming sensory information. To examine this proposal, the current set of experiments assessed the impact of excitotoxic lesions in the retrosplenial cortex on two behavioral tasks that tax animals’ ability to process multiple and overlapping environmental stimuli. In Experiment 1, rats with retrosplenial lesions acquired a negative patterning discrimination, a form of configural learning that can be solved only by learning the conjunction of cues. Subsequent transfer tests confirmed that both the lesion and control animals had solved the task by using configural representations. Furthermore, in Experiment 2, a 2nd cohort of retrosplenial lesion animals successfully acquired conditioned inhibition. Nevertheless, the same animals failed a subsequent summation test that assesses the ability to transfer what has been learned about one stimulus to another stimulus in the absence of reinforcement. Taken together, these results suggest that in the nonspatial domain, the retrosplenial cortex is not required for forming associations between multiple or overlapping environmental stimuli and, consequently, retrosplenial engagement in such processes is more selective than was previously envisaged.
Automated Fact Checking: Task Formulations, Methods and Future Directions

The recently increased focus on misinformation has stimulated research in fact checking, the task of assessing the truthfulness of a claim. Research in automating this task has been conducted in a variety of disciplines including natural language processing, machine learning, knowledge representation, databases, and journalism. While there has been substantial progress, relevant papers and articles have been published in research communities that are often unaware of each other and use inconsistent terminology, thus impeding understanding and further progress. In this paper we survey automated fact checking research stemming from natural language processing and related disciplines, unifying the task formulations and methodologies across papers and authors. Furthermore, we highlight the use of evidence as an important distinguishing factor among them cutting across task formulations and methods. We conclude with proposing avenues for future NLP research on automated fact checking.
Comparison between LSP and MFCC Parameterizations in a Spanish Speech Synthesis System

Voice parameterization using Line Spectral Pair was implemented to a Mexican Spanish HMM-based Speech Synthesis System. Five phrases were synthesized and statistically validated by applying a MOS test to 30 listeners who analyzed the original voices versus synthetic voice. Results were compared with a synthesizer where MFCC was used as voice parameterization. Two aspects were evaluated on the voice: Naturalness and Intelligibility. The comparison shows that LSP parameterization is above the mean score and pointed better than MFCC.
Supporting Collaboration in Small Volunteer Groups with Socio-Technical Guidelines

In this paper, we present a study on group work in which student volunteers from different disciplines worked together to create an augmented reality expedition. The goal of the project was to develop an augmented campus tour for students. The project was successful in delivering the app but through post project interviews we found that volunteers were not satisfied with the process and expressed negative insights. In order to understand this phenomenon, we developed and applied a set of categories for detecting underlying problems in socio-technical processes of volunteer group work. Applying those categories to the aforementioned project allowed us to assess their feasibility. This led to refined categories that can potentially support other volunteer groups to create a suitable socio-technical environment.
Virtual Reality in Psychology

The benefits of using virtual environments (VEs) in psychology arise from the fact that movements in virtual space, and accompanying perceptual changes, are treated by the brain in much the same way as those in equivalent real space. The research benefits of using VEs, in areas of psychology such as spatial learning and cognition, include interface flexibility, the reproducibility of virtual experience, and the opportunity for on-line monitoring of performance. Applications of VEs are many and varied, but are especially beneficial where experience can be tailored via augmentation, and where dangerous training situations can be avoided. The use of programmable agents has great future potential in relation to training and interpersonal skill development, also perhaps in clinical diagnosis and therapy. Progress in VE usage in psychological education is limited by cost and availability, though VEs are being used increasingly in classroom and laboratory teaching exercises. Virtual Reality was said to be “an answer waiting for a question”, but questions are being recognized, so that applications of VEs within the behavioural sciences are likely to multiply.
Machine Learning and Radiogenomics: Lessons Learned and Future Directions

Due to the rapid increase in the availability of patient data, there is significant interest in precision medicine that could facilitate the development of a personalized treatment plan for each patient on an individual basis. Radiation oncology is particularly suited for predictive machine learning (ML) models due to the enormous amount of diagnostic data used as input and therapeutic data generated as output. An emerging field in precision radiation oncology that can take advantage of ML approaches is radiogenomics, which is the study of the impact of genomic variations on the sensitivity of normal and tumor tissue to radiation. Currently, patients undergoing radiotherapy are treated using uniform dose constraints specific to the tumor and surrounding normal tissues. This is suboptimal in many ways. First, the dose that can be delivered to the target volume may be insufficient for control but is constrained by the surrounding normal tissue, as dose escalation can lead to significant morbidity and rare. Second, two patients with nearly identical dose distributions can have substantially different acute and late toxicities, resulting in lengthy treatment breaks and suboptimal control, or chronic morbidities leading to poor quality of life. Despite significant advances in radiogenomics, the magnitude of the genetic contribution to radiation response far exceeds our current understanding of individual risk variants. In the field of genomics, ML methods are being used to extract harder-to-detect knowledge, but these methods have yet to fully penetrate radiogenomics. Hence, the goal of this publication is to provide an overview of ML as it applies to radiogenomics. We begin with a brief history of radiogenomics and its relationship to precision medicine. We then introduce ML and compare it to statistical hypothesis testing to reflect on shared lessons and to avoid common pitfalls. Current ML approaches to genome-wide association studies are examined. The application of ML specifically to radiogenomics is next presented. We end with important lessons for the proper integration of ML into radiogenomics.
EFFECTS OF PLYOMETRIC TRAINING ON SPORT-SPECIFIC TESTS IN FEMALE VOLLEYBALL PLAYERS

Vertical jump height has been identified as a critical component in the sport of volleyball. Therefore, improving vertical jump in volleyball should be the main objective for all coaches. The main objective of this study was to determine the effects of plyometric training methods on jumping ability in female junior volleyball players. Sixty female volleyball players (mean ± SD age, 17 ± 6 months) participated in this study. The experimental group conducted six weeks of plyometric training method for developing explosive leg power. Players were tested for Attack and Block jump test with and without approach. There were significant interaction between the groups for right foot block jump and left foot block jump. Plyometric training induced significant improvements in RFBJ (p<0.01), LFBJ, COBJ, SSBJ (p<0.05). However, control group showed no significant improvements (p>0.05) in any Spike and Block jump test. In conclusion, completion of a 6 week plyometric training program improved selected Block jump tests in female junior players. However, there were no significant changes in Attack jumps following the plyometric training program.
Overexpression of CXXC5 is a strong poor prognostic factor in ER+ breast cancer

CXXC5 is a newly identified CXXC-type zinc finger family protein, which is encoded by the CXXC5 gene localised to the 5q31.3 chromosomal region. Previous studies revealed that CXXC5 is associated with various malignant tumours. The aim of the present study was to investigate the prognosis prediction of CXXC5 in different breast cancer subtypes via the Gene Expression Omnibus database and bc-GenExMiner. CXXC5 overexpression was observed as associated with a poor prognosis for oestrogen receptor positive (ER+) breast cancer. Basal-like breast cancer and triple-negative breast cancer also suggest a poor prognosis, however their CXXC5 expression was low and could not be used as a prognostic factor. The CXXC5 correlated genes and their enriched Gene Ontology (GO) terms were obtained. Among those enriched GO terms, GO:0070062 (extracellular exosome) had the greatest number of associated genes and the associated genes of GO:0000122 (negative regulation of transcription from RNA polymerase II promoter) and GO:0008134 (transcription factor binding) contained CXXC5. These results suggest that overexpression of CXXC5 is a strongly poor prognostic factor in ER+ breast cancer. However, the role of CXXC5 in breast cancer requires further investigation.
Efficient Inference in Stochastic Block Models With Vertex Labels

We study the stochastic block model with two communities where vertices contain side information in the form of a vertex label. These vertex labels may have arbitrary label distributions, depending on the community memberships. We analyze a version of the popular belief propagation (BP) algorithm. We show that this algorithm achieves the highest accuracy possible whenever a certain function of the network parameters has a unique fixed point. When this function has multiple fixed points, the BP algorithm may not perform optimally, where we conjecture that a non-polynomial time algorithm may perform better than BP. We show that increasing the information in the vertex labels may reduce the number of fixed points and, hence, lead to optimality of BP.
Localized Proton Spectroscopy Using Stimulated Echoes

This paper describes a new method for spatially resolved NMR spectroscopy that takes advantage of stimulated echo signals. STEAM (shmulated echo acquisition mode) sequences, already used for a variety of imaging purposes, almost perfectly match the requirements of image-controlled localized ‘H NMR in viva Superior spatial discrimination as well as high flexibility with respect to location, size, and shape of the volume of interest is achieved by employing only three slice-selective 90” rf pulses in the presence of orthogonal gradients. The method is a single-step procedure minimizing rf power requirements and gradient switches. It huther allows accurate determinations of local&d T, and 2-r relaxation times simply by varying the length of corresponding intervals of the STEAM sequence. In fact, the inherent Tr weighting may be used for water suppression and/or reduction of residual eddy current effects. Here we present first results on phantoms and human extremities demonstrating the ease of image selection, localized spectroscopy, and localized determinations of relaxation times. Future steps will deal with water/lipid-suppressed metabolic specU~s~opy.
Aerodynamic Optimization Algorithm with Integrated Geometry Parameterization and Mesh Movement

An efficient gradient-based algorithm for aerodynamic shape optimization is presented. The algorithm consists of several components, including a novel integrated geometry parameterization and mesh movement, a parallel Newton―Krylov flow solver, and an adjoint-based gradient evaluation. To integrate geometry parameterization and mesh movement, generalized B-spline volumes are used to parameterize both the surface and volume mesh. The volume mesh of B-spline control points mimics a coarse mesh; a linear elasticity mesh-movement algorithm is applied directly to this coarse mesh and the fine mesh is regenerated algebraically. Using this approach, mesh-movement time is reduced by two to three orders of magnitude relative to a node-based movement. The mesh-adjoint system also becomes smaller and is thus amenable to complex-step derivative approximations. When solving the flow-adjoint equations using restarted Krylov-subspace methods, a nested-subspace strategy is shown to be more robust than truncating the entire subspace. Optimization is accomplished using a sequential-quadratic-programming algorithm. The effectiveness of the complete algorithm is demonstrated using a lift-constrained induced-drag minimization that involves large changes in geometry.
Communication-Closed Layers as Paradigm for Distributed Systems: A Manifesto

Distributed computations are characterized by a partial order over events: two concurrent events at different processes may be re-ordered without changing the outcome of the computation. For systems that are composed of so-called communication-closed layers, this partial-order argument has been used by Elrad and Francez [13] to reduce the reasoning about distributed systems to a specific sequential form. We discuss existing techniques for communicationclosed layers, and discuss applications to automated verification of state-of-the-art distributed systems.