Miracle-dz/UniFAR-FTUs huggingface dataset:
Social Event Classification via Boosted Multimodal Supervised Latent Dirichlet Allocation

With the rapidly increasing popularity of social media sites (e.g., Flickr, YouTube, and Facebook), it is convenient for users to share their own comments on many social events, which successfully facilitates social event generation, sharing and propagation and results in a large amount of user-contributed media data (e.g., images, videos, and text) for a wide variety of real-world events of different types and scales. As a consequence, it has become more and more difficult to exactly find the interesting events from massive social media data, which is useful to browse, search and monitor social events by users or governments. To deal with these issues, we propose a novel boosted multimodal supervised Latent Dirichlet Allocation (BMM-SLDA) for social event classification by integrating a supervised topic model, denoted as multi-modal supervised Latent Dirichlet Allocation (mm-SLDA), in the boosting framework. Our proposed BMM-SLDA has a number of advantages. (1) Our mm-SLDA can effectively exploit the multimodality and the multiclass property of social events jointly, and make use of the supervised category label information to classify multiclass social event directly. (2) It is suitable for large-scale data analysis by utilizing boosting weighted sampling strategy to iteratively select a small subset of data to efficiently train the corresponding topic models. (3) It effectively exploits social event structure by the document weight distribution with classification error and can iteratively learn new topic model to correct the previously misclassified event documents. We evaluate our BMM-SLDA on a real world dataset and show extensive experimental results, which demonstrate that our model outperforms state-of-the-art methods.
Submicroscopic duplication in Xq28 causes increased expression of the MECP2 gene in a boy with severe mental retardation and features of Rett syndrome

Rett syndrome is an X linked mental retardation syndrome almost exclusively affecting girls, and has long been regarded as an X linked dominant condition lethal in hemizygous males.1 Mutations in the gene encoding the methyl-CpG binding protein 2 (MECP2) were demonstrated as the cause of Rett syndrome,2 and confirmed by a number of studies. The vast majority (95%) of MECP2 mutations occurs de novo. Girls affected by “classic” Rett syndrome show mental retardation and regression, with a typical pattern of symptoms including initially normal development, stagnation, loss of acquired abilities, stereotypic hand movements, regression of speech, profound psychomotor retardation, epilepsy, and autism, although molecular diagnostics has proven that variant clinical forms exist.3,4 It has recently been shown that missense mutations in MECP2 can cause severe neonatal encephalopathy in boys.5 Classic Rett phenotypes in boys have so far only been reported in rare cases of somatic mosaicism or XXY karyotypes.6–11 In girls, larger intragenic deletions are responsible for about 11–16% of typical Rett syndrome without point mutations in the coding exons.12,13 Larger deletions have not yet been found in boys, and duplications of MECP2 have not yet been reported as a cause for typical Rett syndrome at all. We have established quantitative PCR for diagnosis of deletions affecting MECP2 , and in this paper, we report a boy manifesting clinical features of Rett syndrome and a submicroscopic duplication within the cytogenetic band Xq28 encompassing the entire MECP2 gene. The boy is the second child of healthy, unrelated parents, whose older brother had developed normally. There is no family history of mental retardation or developmental disorders. The patient was born in the 41st week after an uneventful pregnancy. Birth was spontaneous but with protracted labour (birth weight 3940 g, length 54 cm, head …
An Alzheimer‐associated TREM2 variant occurs at the ADAM cleavage site and affects shedding and phagocytic function

Sequence variations occurring in the gene encoding the triggering receptor expressed on myeloid cells 2 (TREM2) support an essential function of microglia and innate immunity in the pathogenesis of Alzheimer's disease (AD) and other neurodegenerative disorders. TREM2 matures within the secretory pathway, and its ectodomain is shed on the plasma membrane. Missense mutations in the immunoglobulin (Ig)‐like domain such as p.T66M and p.Y38C retain TREM2 within the endoplasmic reticulum and reduce shedding as well as TREM2‐dependent phagocytosis. Using mass spectrometry, we have now determined the cleavage site of TREM2. TREM2 is shed by proteases of the ADAM (a disintegrin and metalloproteinase domain containing protein) family C‐terminal to histidine 157, a position where an AD‐associated coding variant has been discovered (p.H157Y) in the Han Chinese population. Opposite to the characterized mutations within the Ig‐like domain, such as p.T66M and p.Y38C, the p.H157Y variant within the stalk region leads to enhanced shedding of TREM2. Elevated ectodomain shedding reduces cell surface full‐length TREM2 and lowers TREM2‐dependent phagocytosis. Therefore, two seemingly opposite cellular effects of TREM2 variants, namely reduced versus enhanced shedding, result in similar phenotypic outcomes by reducing cell surface TREM2.
A Systematic Approach for Exploring Tradeoffs in Predictive HVAC Control Systems for Buildings

Heating, Ventilation, and Cooling (HVAC) systems are often the most significant contributor to the energy usage, and the operational cost, of large office buildings. Therefore, to understand the various factors affecting the energy usage, and to optimize the operational efficiency of building HVAC systems, energy analysts and architects often create simulations (e.g., EnergyPlus or DOE-2), of buildings prior to construction or renovation to determine energy savings and quantify the Return-on-Investment (ROI). While useful, these simulations usually use static HVAC control strategies such as lowering room temperature at night, or reactive control based on simulated room occupancy. Recently, advances have been made in HVAC control algorithms that predict room occupancy. However, these algorithms depend on costly sensor installations and the tradeoffs between predictive accuracy, energy savings, comfort and expenses are not well understood. Current simulation frameworks do not support easy analysis of these tradeoffs. Our contribution is a simulation framework that can be used to explore this design space by generating objective estimates of the energy savings and occupant comfort for different levels of HVAC prediction and control performance. We validate our framework on a real-world occupancy dataset spanning 6 months for 235 rooms in a large university office building. Using the gold standard of energy use modeling and simulation (Revit and Energy Plus), we compare the energy consumption and occupant comfort in 29 independent simulations that explore our parameter space. Our results highlight a number of potentially useful tradeoffs with respect to energy savings, comfort, and algorithmic performance among predictive, reactive, and static schedules, for a stakeholder of our building.
Hyponatremia, Hypernatremia, and Mortality in Patients With Chronic Kidney Disease With and Without Congestive Heart Failure

Background— Hyponatremia is common in patients with conditions such as congestive heart failure and is associated with increased mortality in hospitalized patients. Congestive heart failure is common in patients with chronic kidney disease, but the association of serum sodium concentration with mortality in such patients is not well characterized. Methods and Results— We examined the association of serum sodium concentration with all-cause mortality in a nationally representative cohort of 655 493 US veterans with non–dialysis-dependent chronic kidney disease (95 961 [15%] of them with congestive heart failure). Associations were examined in time-dependent Cox models with adjustment for potential confounders. During a median follow-up of 5.5 years, a total of 193 956 patients died (mortality rate, 62.5/1000 patient-years; 95% confidence interval, 62.2–62.8). The association of serum sodium level with mortality was U-shaped, with the lowest mortality seen in patients with sodium level of 140 mEq/L and with both lower and higher levels showing significant associations with increased mortality. Patients with serum sodium levels of <130, 130 to 135.9, 145.1 to 150, and ≥150 mEq/L compared with 136 to 145 mEq/L had multivariable-adjusted mortality hazard ratios (95% confidence interval) of 1.93 (1.83–2.03), 1.28 (1.26–1.30), 1.33 (1.28–1.38), and 1.56 (1.33–1.83) (P<0.001 for all). The associations remained consistent in subgroups of patients with and without congestive heart failure. Conclusions— Both lower and higher serum sodium levels are independently associated with higher mortality in patients with non–dialysis-dependent chronic kidney disease, irrespective of the presence or absence of congestive heart failure.
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation

We present a novel regularization-based Multitask Learning (MTL) formulation for Structured Output (SO) prediction for the case of hierarchical task relations. Structured output prediction often leads to difficult inference problems and hence requires large amounts of training data to obtain accurate models. We propose to use MTL to exploit additional information from related learning tasks by means of hierarchical regularization. Training SO models on the combined set of examples from multiple tasks can easily become infeasible for real world applications. To be able to solve the optimization problems underlying multitask structured output learning, we propose an efficient algorithm based on bundle-methods. We demonstrate the performance of our approach in applications from the domain of computational biology addressing the key problem of gene finding. We show that 1) our proposed solver achieves much faster convergence than previous methods and 2) that the Hierarchical SO-MTL approach outperforms considered non-MTL methods.
Keratinocyte growth factor expression is suppressed in early acute lung injury/acute respiratory distress syndrome by smad and c-Abl pathways*

Objective:Keratinocyte growth factor (KGF) is expressed primarily by fibroblasts, is important for alveolar epithelial proliferation/function, and protects against lung injury in multiple animal models. We wished to determine whether acute lung injury/acute respiratory distress syndrome (ALI/ARDS) alveolar fluid induces KGF and fibroblast genes important for alveolar repair. Design:A single-center cohort study enrolling patients between 2004 and 2006. Setting:A medical intensive care unit of a tertiary care medical center. Patients:Adult patients meeting the American-European Consensus Conference definition of ALI/ARDS. Interventions:Patients with ALI/ARDS were enrolled, and lavage fluid was collected within 48 hours of intubation. Lavage fluid was also collected from two control cohorts. The patients with ALI/ARDS were followed for 28 days or until death. Measurement and Main Results:Fifteen patients with ALI/ARDS, five patients with cardiogenic edema, and five normal lung parenchyma controls were enrolled from 2004 to 2006. Primary normal human lung fibroblasts were incubated with bronchoalveolar lavage fluid and assessed for KGF, connective tissue growth factor, &agr;-smooth muscle actin, and collagen 1 expression by real-time reverse transcriptase-polymerase chain reaction. Fibroblasts incubated with ALI/ARDS lavage fluid expressed 50% less KGF messenger RNA than those incubated with lavage fluid from CE patients (p < 0.01) and 33% than normal parenchymal controls (p < 0.03). Lavage fluid from patients with ALI/ARDS induced more connective tissue growth factor (p < 0.05), collagen 1 (p < 0.03), and &agr;-smooth muscle actin (p < 0.04) than from CE patients. Preincubation of normal human lung fibroblasts with the transforming growth factor (TGF)-&bgr;1 receptor/smad phosphorylation inhibitor SB431542 increased ALI/ARDS-induced KGF expression by 40% (p < 0.04). In cultured human lung fibroblasts, TGF-&bgr;1 suppressed KGF messenger RNA and protein expression, which were reversed by SB431542 and by the c-Abl inhibitor, imatinib mesylate, but not by the p38 map kinase inhibitor, SB203580. Conclusions:ALI/ARDS alveolar fluid suppresses KGF expression, in part, due to TGF-&bgr;1. TGF-&bgr;1 suppression of KGF requires both smad phosphorylation and c-Abl activation.
Efficient construction of an assembly string graph using the FM-index

Motivation: Sequence assembly is a difficult problem whose importance has grown again recently as the cost of sequencing has dramatically dropped. Most new sequence assembly software has started by building a de Bruijn graph, avoiding the overlap-based methods used previously because of the computational cost and complexity of these with very large numbers of short reads. Here, we show how to use suffix array-based methods that have formed the basis of recent very fast sequence mapping algorithms to find overlaps and generate assembly string graphs asymptotically faster than previously described algorithms. Results: Standard overlap assembly methods have time complexity O(N2), where N is the sum of the lengths of the reads. We use the Ferragina–Manzini index (FM-index) derived from the Burrows–Wheeler transform to find overlaps of length at least τ among a set of reads. As well as an approach that finds all overlaps then implements transitive reduction to produce a string graph, we show how to output directly only the irreducible overlaps, significantly shrinking memory requirements and reducing compute time to O(N), independent of depth. Overlap-based assembly methods naturally handle mixed length read sets, including capillary reads or long reads promised by the third generation sequencing technologies. The algorithms we present here pave the way for overlap-based assembly approaches to be developed that scale to whole vertebrate genome de novo assembly. Contact: js18@sanger.ac. uk
Efficient Protocol Decomposition and Performance Analysis of the SSCOP Layer

This paper presents a decomposition of the SSCOP [1] protocol, which is based on the detailed analysis of the performance of the layer. The protocol decomposition aims at mapping the various functions of the SSCOP layer onto modules with optimized running speed when these are applied on modern network processors ([2], [3], [4]). The SSCOP layer is a mandatory part of the ATM Signalling Adaptation Layer (SAAL [5]). The running time performance of the SSCOP has a significant impact on the execution speed of the entire layer. A mapping of the SSCOP most complex functions onto dedicated hardware units leads to accommodating the requirement of speeding up the SSCOP execution. This work analyzes the protocol into primitive functions and presents the performance of the functions that are executed frequently during ATM call setup and tear-down. The measurements from the protocol’s profiling lead to a partitioning of the functions, in order to implement a subset of these in hardware and accomplish their execution in wire speed. The results of this performance analysis have been utilized to improve on the performance of the PRO31. ATM signalling applications can benefit from the proposed hardware software partitioning because of the significant acceleration of the ATM signalling stack that can be achieved in core network subsystems. Key-Words: SSCOP, Performance analysis, Network Processor, Protocol Profiling, Hardware and Software Decomposition.
The Inability to Screen Exhibition Swine for Influenza A Virus Using Body Temperature

Agricultural fairs create an unconventional animal–human interface that has been associated with swine‐to‐human transmission of influenza A virus (IAV) in recent years. Early detection of IAV‐infected pigs at agricultural fairs would allow veterinarians to better protect swine and human health during these swine exhibitions. This study assessed the use of swine body temperature measurement, recorded by infrared and rectal thermometers, as a practical method to detect IAV‐infected swine at agricultural fairs. In our first objective, infrared thermometers were used to record the body surface temperature of 1,092 pigs at the time of IAV nasal swab collection at the end of the exhibition period of 55 agricultural fairs. IAV was recovered from 212 (19.4%) pigs, and the difference in mean infrared body temperature measurement of IAV‐positive and IAV‐negative pigs was 0.83°C. In a second objective, snout wipes were collected from 1,948 pigs immediately prior to the unloading of the animals at a single large swine exhibition. Concurrent to the snout wipe collection, owners took the rectal temperatures of his/her pigs. In this case, 47 (2.4%) pigs tested positive for IAV before they entered the swine barn. The mean rectal temperatures differed by only 0.19°C between IAV‐positive and IAV‐negative pigs. The low prevalence of IAV among the pigs upon entry to the fair in the second objective provides evidence that limiting intraspecies spread of IAV during the fairs will likely have significant impacts on the zoonotic transmission. However, in both objectives, the high degree of similarity in the body temperature measurements between the IAV‐positive and IAV‐negative pigs made it impossible to set a diagnostically meaningful cut point to differentiate IAV status of the individual animals. Unfortunately, body temperature measurement cannot be used to accurately screen exhibition swine for IAV.
The complexities of undertaking counselling evaluation in the workplace

There is a long-standing debate over whether evaluation is an art or a science (Barker et al.: Research Methods in Clinical and Counselling Psychology, Chichester, John Wiley & Sons, 1994). The “science” camp argues for scientific rigour in methodology, whilst the “art” camp maintains that evaluation should be tailored to the specific circumstances under evaluation. The compromise proposed by Barker, Pistrang, & Elliot (1994) suggests that evaluation should be as systematic as possible within the practical and organizational constraints inherent in service settings. The aim of this paper is to present a review of the literature on evaluation and workplace counselling. The paper initially reviews the literature in the counselling/psychotherapy field, and then explores studies on employee assistance programmes. The themes that are explored are the relationship between research and practices; the interactions with stakeholders in the field; the use of control groups and the economic side of counselling.
Methodology for Using Long-Term Accelerometry Monitoring to Describe Daily Activity Patterns in COPD

We sought to develop procedures for computerized analysis of long-term, high-resolution activity monitoring data that allow accurate assessment of the time course of activity levels suitable for use in chronic obstructive pulmonary disease (COPD) patients. Twenty-two COPD patients utilizing long-term oxygen recruited from 5 sites of the COPD Clinical Research Network wore a triaxial accelerometer (RT3, Stayhealthy, Monrovia, CA) during waking hours over a 14-day period. Computerized algorithms were composed allowing minute-by-minute activity data to be analyzed to determine, for each minute, whether the monitor was being worn. Temporal alignment allowed determination of average time course of activity level, expressed as average vector magnitude units (VMU, the vectorial sum of activity counts in three orthogonal directions) per minute, for each hour of the day. Mid-day activity was quantified as average VMU/minute between 10AM and 4PM for minutes the monitor was worn. Over the 14 day monitoring period, subjects wore the monitor an average of 11.4 ± 3.0 hours·day− 1. During mid-day hours, subjects wore the monitor 76.3% of the time and generated an average activity level of 112 ± 55 VMU·min−1. Increase in precision of activity estimates with longer monitoring periods was demonstrated. This analysis scheme allows a detailed temporal pattern of activity to be defined from triaxial accelerometer recordings and has the potential to facilitate comparisons among subjects and between subject groups. This trial is registered at ClinicalTrials.gov (NCT00325754).
A novel integrated analysis-and-simulation approach for detail enhancement in FLIP fluid interaction

This paper advocates a novel integrated method to tightly couple simulation with analysis for the effective modeling and enhancement of scale-aware fluid details. It brings forth a suite of innovations in a unified framework, including depth-image-based space analysis for multi-scale detail detection, time-space analysis based on the logistic regression model that integrates both geometry and physics criteria, and depth-image-based sampling for quality-efficiency tradeoff. Our method contains an intertwined two-level processing architecture at its core. At the analysis level, we propose a rigorous time-space analysis model to pinpoint complex interacting regions, which can take into account multiple detail-relevant factors based on the depth-image sequence captured from FLIP-driven simulation sequence. At the simulation level, details are enhanced by animating extra diffuse materials, and augmenting the air-fluid mixing phenomenon. Directly benefitting from the flexibility of image-space-dominant processing, our unified framework can be entirely implemented on GPU, hence interactive performance could be guaranteed. Comprehensive experiments and evaluations on various diffuse phenomena (e.g., spray, foam, and bubble) have demonstrated its superiority in high-fidelity detail enhancement during fluid simulation and its interaction with surrounding environment for VR applications.
Multiscale Histogram of Oriented Gradient Descriptors for Robust Character Recognition

Characters extracted from images or graphics pose a challenge for traditional character recognition techniques. The high degree of intraclass variation along with the presence of clutter makes accurate recognition difficult, yet the semantic information conveyed by sections of text within images or graphics makes their recognition an important problem. Previous work has shown that, on the two most commonly used datasets of such characters, Histogram of Oriented Gradient (HOG) descriptors have outperformed other methods. In this work we consider two extensions of the HOG descriptor to include features at multiple scales, and evaluate their performance using characters taken from images and graphics. We demonstrate that, by combining pairs of oriented gradients at different scales, it's possible to achieve an increase in performance of 12.4% and 5.6% on the two datasets.