Miracle-dz/UniFAR-FTUs huggingface dataset:
Recursive Ground Truth Estimator for Social Data Streams

The paper develops a recursive state estimator for social network data streams that allows exploitation of social networks, such as Twitter, as sensor networks to reliably observe physical events. Recent literature suggested using social networks as sensor networks leveraging the fact that much of the information upload on the former constitutes acts of sensing. A significant challenge identified in that context was that source reliability is often unknown, leading to uncertainty regarding the veracity of reported observations. Multiple truth finding systems were developed to solve this problem, generally geared towards batch analysis of offline datasets. This work complements the present batch approaches by developing an online recursive state estimator that recovers ground truth from streaming data. In this paper, we model physical world state by a set of binary signals (propositions, called assertions, about world state) and the social network as a noisy medium, where distortion, fabrication, omissions, and duplication are introduced. Our recursive state estimator is designed to recover the original binary signal (the true propositions) from the received noisy signal, essentially decoding the unreliable social network output to obtain the best estimate of ground truth in the physical world. Results show that the estimator is both effective and efficient at recovering the original signal with a high degree of accuracy. The estimator gives rise to a novel situation awareness tool that can be used for reliably following unfolding events in real time, using dynamically arriving social network data.
Discrete Models of Biopolymers

Discretized models of biopolymer structures can be used not only as approximations of the actual spatial structures but also as a computationally feasible approach to the generic features of the sequence-structure relationships. We review the combinatorics of nucleic acid secondary structures as well as lattice models of proteins, and show how properties such as the existence of extended neutral networks or shape space covering can be explained on this basis.
Emerging Roles of RNA-Binding Proteins in Plant Growth, Development, and Stress Responses

Posttranscriptional regulation of RNA metabolism, including RNA processing, intron splicing, editing, RNA export, and decay, is increasingly regarded as an essential step for fine-tuning the regulation of gene expression in eukaryotes. RNA-binding proteins (RBPs) are central regulatory factors controlling posttranscriptional RNA metabolism during plant growth, development, and stress responses. Although functional roles of diverse RBPs in living organisms have been determined during the last decades, our understanding of the functional roles of RBPs in plants is lagging far behind our understanding of those in other organisms, including animals, bacteria, and viruses. However, recent functional analysis of multiple RBP family members involved in plant RNA metabolism and elucidation of the mechanistic roles of RBPs shed light on the cellular roles of diverse RBPs in growth, development, and stress responses of plants. In this review, we will discuss recent studies demonstrating the emerging roles of multiple RBP family members that play essential roles in RNA metabolism during plant growth, development, and stress responses.
Coordinated Expression of DNAM-1 and LFA-1 in Educated NK Cells

The functional capacity of NK cells is dynamically tuned by integrated signals from inhibitory and activating cell surface receptors in a process termed NK cell education. However, the understanding of the cellular and molecular mechanisms behind this functional tuning is limited. In this study, we show that the expression of the adhesion molecule and activation receptor DNAX accessory molecule 1 (DNAM-1) correlates with the quantity and quality of the inhibitory input by HLA class I–specific killer cell Ig-like receptors and CD94/NKG2A as well as with the magnitude of functional responses. Upon target cell recognition, the conformational state of LFA-1 changed in educated NK cells, associated with rapid colocalization of both active LFA-1 and DNAM-1 at the immune synapse. Thus, the coordinated expression of LFA-1 and DNAM-1 is a central component of NK cell education and provides a potential mechanism for controlling cytotoxicity by functionally mature NK cells.
Exports, Imports and Wages: Evidence from Matched Firm-Worker-Product Panels

The analysis of the effects of firm-level international trade on wages has so far focused on the role of exports, which are also typically treated as a composite good. However, we show in this paper that firm-level imports can actually be a wage determinant as important as exports. Furthermore, we also find significant differences in the relationship between trade and wages across types of products. In particular, firms that increase their exports (imports) of high- (intermediate-) technology products tend to increase their salaries. Our analysis is based on unique data from Portugal, obtained by merging a matched firm-worker panel and a matched firm-transaction panel. Our data set follows the population of manufacturing firms and all their workers from 1995 to 2005 and allows for several control variables, including job-spell fixed effects.
Extracting Topics with Focused Communities in Multi-dimensional Social Data

Understanding what social media users discuss and what is happening in the real world can be enabled through the automatic analysis and summarization of Online Social Media. Trend Discovery, through the extraction of trending topics, is utilized in marketing campaigns and by companies to identify customer interests and potential new markets. While there is a plethora of techniques to identify trending topics, there is a lack of focus on the characteristics of the underlying population that participate in a trend. Users that mention a topic define a multivariate vector of demographics and user characteristics with the potential to offer insights into the communities that are focused on a topic, both latent and obvious. We propose a novel algorithmic framework for the efficient and scalable extraction of the combination of user characteristics that define a community interested in a topic. Potential results include cases like “female residents of Boston, MA, that support the Democratic party, are focused on the activistic topic #FreeJustina” or “young adults, living in the US, are focused on topic #NavyYardShooting with a Negative sentiment”. Such topics might be significantly popular or not, but community extraction emphasizes the importance and focused interest in a topic even if it is not as popular as other topics with a more defused audience. The proposed framework can support any number of attributes and scales linearly. We assessed our algorithm’s accuracy and efficiency on synthetic and real Twitter data and results show high accuracy and efficiency.
How HTTP/2 is changing web traffic and how to detect it

HTTP constitutes a dominant part of the Internet traffic. Today's web traffic mostly consists of HTTP/1 and the much younger HTTP/2. As the traffic of both protocols is increasingly exchanged over encryption, discerning which flows in the network belong to each protocol is getting harder. Identifying flows per protocol is however very important, e.g., for building traffic models for simulations and benchmarking, and enabling operators and researchers to track the adoption of HTTP/2. This paper makes two contributions. First, using datasets of passive measurements collected in operational networks and Deep Packet Inspection (DPI), we characterize differences in HTTP/1 and HTTP/2 traffic. We show that the adoption of HTTP/2 among major providers is high and growing. Moreover, when comparing the same services over HTTP/1 or HTTP/2, we notice that HTTP/2 flows are longer, but formed by smaller packets. This is likely a consequence of new HTTP/2 features and the reorganization of servers and clients to profit from such features. Second, we present a lightweight method for the classification of encrypted web traffic into appropriate HTTP versions. In order to make the method practically feasible, we use machine learning with basic information commonly available in aggregated flow traces (e.g., NetFlow records). We show that a small labeled dataset is sufficient for training the system, and it accurately classifies traffic for several months, potentially from different measurement locations, without the need for retraining. Therefore, the method is simple, scalable, and applicable to scenarios where DPI is not possible.
Distributed shuffle index: Analysis and implementation in an industrial testbed

The protection of content confidentiality as well as of access and pattern confidentiality of data moved to the cloud have been recently the subject of several investigations. The distributed shuffle index addresses these issues by randomly partitioning data among three independent cloud providers. In this paper, we describe the implementation of the distributed shuffle index in the high-performance Dell EMC platform. We first illustrate the main characteristics of the industry testbed and then show the results of our experiments, confirming the limited performance overhead and the practical applicability of the distributed shuffle index in industrial environments.
Time-varying narrow-band interference rejection in asynchronous multiuser DS/CDMA systems over frequency-selective fading channels

In this paper, we handle the problem of joint suppression of multiple-access interference (MAI) and narrowband interference (NBI) in fading, dispersive channels. The detectors we consider are linear, one-shot structures, which allow for possible window enlargement and signal-space oversampling to improve performance. We focus on both zero-forcing and minimum-mean square-error design strategies, showing that the presence of NBI generally requires a time-varying processing of the observables, no matter what the optimization criterion. A thorough performance assessment of the proposed detectors is also presented, either through analytical formulas or through computer simulations. We finally deal with the problem of blind suppression of both MAI and NBI, introducing batch-estimation procedures to be implemented offline, which require very little and sometimes no prior knowledge as to the interference structure.
Local mixed layer response to wind and buoyancy forcing in the western equatorial Pacific

The behavior of three types of widely used one-dimensional mixed layer models (bulk, turbulence closure, and shear instability) is evaluated under idealized conditions representative of atmospheric forcing over the western equatorial Pacific Ocean. Results show that under heavy precipitation (frequently observed in this region), models with a shear instability mixing component capture the fundamental behavior of the mixed layer better than do those without. On the basis of this comparison, a version of the Price-Weller-Pinkel (PWP) [Price et al., 1986; Schudlich and Price, 1992] mixed layer model is selected for the purpose of simulating near-surface temperature and salinity measurements in this region. Heat and salt budgets calculated from observations taken during the Tropical Ocean Global Atmosphere-Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) pilot study suggest that above the top of the thermocline, local atmospheric forcing is indeed of first-order importance in the evolution of the temperature field. Horizontal advection of salt, however, is observed to be as important as local forcing (evaporation minus precipitation) in the evolution of the salinity field. Driven by observed fluxes, numerical simulation using the PWP model confirm the primary importance of local forcing for the temperature field and the importance of salinity advection for the salinity field. During the TOGA-COARE intensive observing period, simulated and observed temperatures agree well at 9 m depth under weak winds, but the model/data discrepancy gradually increases during periods of stronger westerly winds. The addition of a simplified meridional temperature advection term, based on the mean observed temperature gradient, reduces but does not eliminate the model data discrepancy. The magnitude of model/data salinity discrepancies is consistent with concurrent measurements of instantaneous horizontal salinity gradients and velocities, but not with their time-mean values.
Generation and Characterization of Closely Related Epizootic and Enzootic Infectious cDNA Clones for Studying Interferon Sensitivity and Emergence Mechanisms of Venezuelan Equine Encephalitis Virus

ABSTRACT Venezuelan equine encephalitis virus (VEEV) is a reemerging pathogen and a continuing threat to humans and equines in the Americas. Identification of the genetic determinants that enable epizootic VEEV strains to arise and exploit equines as amplification hosts to cause widespread human disease is pivotal to understanding VEE emergence. The sensitivity to murine alpha/beta interferon-mediated antiviral activity was previously correlated to the epizootic phenotype of several VEEV strains. Infectious cDNA clones were generated from an epizootic subtype IC VEEV strain (SH3) isolated during the 1992 Venezuelan outbreak and a closely related enzootic, sympatric subtype ID strain (ZPC738). These VEEV strains had low-cell-culture-passage histories and differed by only 12 amino acids in the nonstructural and structural proteins. Rescued viruses showed similar growth kinetics to their parent viruses in several cell lines, and murine infections resulted in comparable viremia and disease. Unlike what was found in other studies of epizootic and enzootic VEEV strains, the sensitivities to murine alpha/beta interferon did not differ appreciably between these epizootic versus enzootic strains, calling into question the reliability of interferon sensitivity as a marker of epizootic potential.
Determinants of depressive symptom trajectories among older adults in community and treatment settings

Sub-diagnostic depression, sleep, and circadian rest-activity rhythm (CAR) syndromes are common in late-life, but their characteristics, prevalence, and relations to future depression are unclear. We characterized commonly occurring sleep, CAR, and depressive sign/symptom patterns using a data-driven approach applied to a large population-based study of older men. We next examined relationships of these baseline syndromes with longitudinal change in depressive symptoms. Common (32.44%) probable depressive syndromes were characterized by somatic/apathy symptoms; a subset (5.74%) with only limited somatic/apathy symptoms also had emotional-related impairment. Subjective complaints without objectively (actigraph) assessed disturbances characterized two distinct classes of men (totaling 37.46%); a pattern of objective disturbance (including greater sleep fragmentation with probable prolonged sleep latency or short (<5 hour) sleep duration) occurred in both the presence (8.87%) and absence (8.51%) of subjective complaints. Only 32.18% appeared to be free of a non-normative CAR parameter; 8 classes were distinguished by activity timing, levels, and the active period length. Baseline sleep and depression latent classes were not meaningfully associated with rates of change in depression severity. The rate of increase in depressive symptoms was higher for classes with later activity and for a class with dampened, earlier, and compressed activity combined. Future work should assess the modifiability of the identified markers of depressive symptom increases through preventative interventions. Nevertheless, there remains a need to understand of mechanisms of variability in pharmacological treatment response among older adults with major depressive disorder (MDD). We therefore assessed prognostic factors associated with distinct trajectories of depressive symptom change over 12-weeks of open-label Venlafaxine XR treatment for MDD. Only about 42% of participants exhibited a clear response, and the clinical prognostic factors linked to unique patterns of non-response included: worse depressive severity, longer illness duration, prior adequate pharmacological treatment, and worse list recognition performance. Overall, this work has public health relevance by providing a novel description of common sleep-wake/depressive syndromes in the community and distinct symptom trajectories found when pharmacologically treating MDD in the clinic. There is a need to integrate the identified prognostic markers with neurobiological research towards a valid predictive science of depression pathogenesis, prevention, and treatment.
Chromatin , Gene , and RNA Regulation Dual Promoter Usage as Regulatory Mechanism of let-7 c Expression in Leukemic and Solid Tumors

Let-7c, an intronicmicroRNA (miRNA) embedded in the long non-coding gene LINC00478, can act as a tumor suppressor by targeting oncogenes. Previous studies indicated that in acute promyelocytic leukemia (APL), a subtype of acutemyelogenous leukemia (AML) bearing the leukemia promoting PML/RARa fusion protein, let-7c expression seems to be controlled by the host gene promoter, in which canonical Retinoic Acid Responsive Elements (RAREs) are bound by PML/RARa in an all transretinoic acid (ATRA)–sensitive manner. Here, let-7c transcriptional regulation was further investigated and a novel intronic promoter upstream of the pre-miRNA was identified. This new promoter has transcriptional activity strongly indicating that at least two promoters need to be considered for let-7c transcription: the distal host gene and the proximal intronic promoter. Therefore, epigenetic modifying enzymes and histone acetylation and methylation status were analyzed on both let-7c promoters. It was demonstrated that ATRA treatment leads to let-7c upregulation inducing a more open chromatin conformation of the host gene promoter, with an enrichment of epigenetic marks that correlate with a more active transcriptional state. Conversely, the epigenetic marks on the intronic promoter are not significantly affected by ATRA treatment. Interestingly, in solid tumors such as prostate and lung adenocarcinoma it was found that both host and intronic promoters are functional. These data suggest that while the host gene promoter may control let-7c expression in AML, in a nonleukemic tumor context instead the intronic promoter contributes or preferentially regulates let-7c
Determination and Validation of New Nonlinear FinFET Model Based on Lookup Tables

The Fin field effect transistor (FinFET) is a multiple gate structure, which is recently emerging as a leading structure to continue the scaling of CMOS technology into the nanometer regime. This promising multiple gate structure has not only the advantage of reducing short channel effects but also of being compatible with the conventional planar CMOS technology. To our knowledge, this is the first letter addressing the nonlinear FinFET model validated by large signal network analyzer measurements. Here, we present a nonlinear FinFET model which is based on lookup tables. The accuracy of the developed model is completely and successfully verified through the comparison with nonlinear FinFET measurements
The ethics of interprofessional collaboration

Interprofessional collaboration has become accepted as an important component in today’s health care and has been guided by concerns with patient safety, quality health-care outcomes, and economics. It is widely accepted that interprofessional collaboration improves patient outcomes through enhanced communication among health-care providers and increased accessibility to services. Although there is a paucity of research that provides confirmatory evidence, interprofessional competencies continue to be incorporated into the curricula of health-care students. This article examines the ethics of interprofessional collaboration and ethical issues that arise from the mainstream adoption of interprofessional competencies and the potential for moral distress in nursing.
Subcentimeter Tumor Lesion Delineation for High-Resolution 18F-FDG PET Images: Optimizing Correction for Partial-Volume Effects

In PET, partial-volume effects cause errors in estimation of size and activity for small objects with radiopharmaceutical uptake. Recent methods for image reconstruction, compared with traditional reconstruction techniques, include algorithms for resolution recovery that result in images with higher resolution and enable quantification of size and activity of smaller objects. The purpose of this study was to evaluate a combination of 2 algorithms for volume delineation and partial-volume correction on uptake volumes smaller than 0.7 mL using image reconstruction algorithms with and without resolution recovery. Methods: Volumes of interests (VOIs) were delineated using a threshold intensity calculated as a weighted sum of tumor and background intensities. These VOIs were used for calculating correction factors by convolving a tumor mask with the system point-spread function. The methods algorithms were evaluated using a phantom constructed from 5 small different-sized balloons filled with 18F-FDG in background activity. Six different backgrounds were used. Data were acquired using a PET/CT scanner, and the images were reconstructed using 2 iterative algorithms, one of which used a resolution recovery algorithm. Results: For the images reconstructed using the resolution recovery algorithm, the method for volume delineation resulted in VOI sizes that were correct within 1 SD for all balloons of a volume of 0.35 mL (equivalent diameter, 8.8 mm) and larger, in all backgrounds. For the images reconstructed without resolution recovery, the VOI sizes were background-dependent and generally less accurate. Correct volume delineations generally led to accurate activity estimates. Conclusion: The algorithms tested on the phantom developed for this study could, for this PET camera and these reconstruction algorithms, be used for accurate volume delineation and activity quantification of lesions 0.35 mL and larger.
Effects of resistance exercise on lipolysis during subsequent submaximal exercise.

PURPOSE This study examined effects of prior resistance exercise on fat metabolism during subsequent submaximal exercise with different recovery periods between exercise bouts. METHODS Ten male subjects performed three types of exercise regimens: 1) submaximal endurance exercise only (E), 2) submaximal endurance exercise with prior resistance exercise and 20 min of rest (RE20), and 3) submaximal endurance exercise with prior resistance exercise and 120 min of rest (RE120). Resistance exercise consisted of six exercises, each with three to four sets at 10-repetition maximum. Subjects performed cycle ergometer exercise at 50% of the maximal oxygen uptake for 60 min. RESULTS Prior resistance exercise caused increases in blood lactate, plasma norepinephrine, serum growth hormone (GH), insulin, and glycerol concentrations (P < 0.01). Before the submaximal exercise, serum free fatty acid (FFA) concentration was higher in the RE120 than in the RE20 and E trials (P < 0.01), although concentrations of plasma norepinephrine, serum GH, insulin, and glycerol were higher in the RE20 than in the RE120 and E trials (P < 0.05). Concentrations of FFA and glycerol during the 60-min submaximal exercise were higher in the RE120 and RE20 trials than in the E trial (P < 0.05). No significant difference was observed in the acetoacetate and 3-hydroxybutyrate responses. In the RE20 trial, fat oxidation throughout the 60-min submaximal exercise (mean value) was greater than in the E trial (P < 0.05), but no significant difference was found between the RE120 and E trials. CONCLUSION Fat availability during the submaximal exercise was enhanced by prior resistance exercise. However, augmentation of fat oxidation was observed only in the trial with shorter rest between resistance exercise and submaximal exercise bouts (RE20 trial).