Miracle-dz/UniFAR-FTUs huggingface dataset:
Over- and Under-Exposure Reconstruction of a Single Plenoptic Capture

Light field images, for example, taken with plenoptic cameras, offer interesting post-processing opportunities, including depth-of-field management, depth estimation, viewpoint selection, and 3D image synthesis. Like most capture devices, however, plenoptic cameras have a limited dynamic range, so that over- and under-exposed areas in plenoptic images are commonplace. We therefore present a straightforward and robust plenoptic reconstruction technique based on the observation that vignetting causes peripheral views to receive less light than central views. Thus, corresponding pixels in different views can be used to reconstruct illumination, especially in areas where information missing in one view is present in another. Our algorithm accurately reconstructs under- and over-exposed regions (known as declipping), additionally affording an increase in peak luminance by up to two f-stops, and a comparable lowering of the noise floor. The key advantages of this approach are that no hardware modifications are necessary to improve the dynamic range, that no multiple exposure techniques are required, and therefore that no ghosting or other artifacts are introduced.
Intramedullary nail with integrated cephalocervical screws in the intertrochanteric fractures treatment: Position of screws in fracture stability.

BACKGROUND Stable fracture fixation is important in the treatment of intertrochanteric femur (ITF) fractures in the elderly population to prevent the loss of reduction, achieve early mobility, and restore independence. The aim of this study was to present the results of surgical treatment of stable and unstable ITF fractures using a trochanteric antegrade intramedullary nail with two cephalocervical screws in an integrated mechanism (Intertan®; Smith & Nephew, Memphis, TN) and evaluate the relationship between the loss of reduction and screw position in the femoral neck in two planes. METHODS The authors investigated all varus misalignments and losses of reduction in 57 patients (22 males, 35 females) treated for ITF fractures with the Intertan® between 2010 and 2011. Two indices (screw alignment index in the frontal projection [SAIcoronal] and screw alignment index in the lateral projection [SAIsagittal]) were defined to evaluate the loss of reduction. Patients were also evaluated according to the Harris hip score and Barthel independence index. RESULTS The mean patient age was 77.1 years. The mean follow-up period was 21.7 months. All patients achieved complete union. We did not detect any varus collapse or loss of reduction. At the end of the follow-up period, the mean Barthel independence index was 90.7, and the mean Harris hip score was 83.7. CONCLUSION The use of a trochanteric antegrade intramedullary nail with two cephalocervical screws allows for linear intraoperative compression and rotational stability of the head/neck fragment, prevents reduction loss, and has a wide application area in the femoral head. Its inherent continuous stability permits early weight-bearing and mobilization. It is a safe and an efficient option for the treatment of ITF fractures.
Party Matters: Enhancing Legislative Embeddings with Author Attributes for Vote Prediction

Predicting how Congressional legislators will vote is important for understanding their past and future behavior. However, previous work on roll-call prediction has been limited to single session settings, thus not allowing for generalization across sessions. In this paper, we show that text alone is insufficient for modeling voting outcomes in new contexts, as session changes lead to changes in the underlying data generation process. We propose a novel neural method for encoding documents alongside additional metadata, achieving an average of a 4% boost in accuracy over the previous state-of-the-art.
A non-autonomous function of the core PCP protein VANGL2 directs peripheral axon turning in the developing cochlea

ABSTRACT The cochlea is innervated by neurons that relay sound information from hair cells to central auditory targets. A subset of these are the type II spiral ganglion neurons, which have nociceptive features and contribute to feedback circuits providing neuroprotection in extreme noise. Type II neurons make a distinctive 90° turn towards the cochlear base to synapse with 10-15 outer hair cells. We demonstrate that this axon turning event requires planar cell polarity (PCP) signaling and is disrupted in Vangl2 and Celsr1 knockout mice, and that VANGL2 acts non-autonomously from the cochlea to direct turning. Moreover, VANGL2 is asymmetrically distributed at intercellular junctions between cochlear supporting cells, and in a pattern that could allow it to act directly as an axon guidance cue. Together, these data reveal a non-autonomous function for PCP signaling during axon guidance occurring in the tissue that is innervated, rather than the navigating growth cone. Summary: Planar cell polarity proteins function in cochlear supporting cells to guide peripheral axon guidance and the innervation of outer hair cells by the spiral ganglion.
Towards Enabling Novel Edge-Enabled Applications

Edge computing has emerged as a distributed computing paradigm to overcome practical scalability limits of cloud computing. The main principle of edge computing is to leverage on computational resources outside of the cloud for performing computations closer to data sources, avoiding unnecessary data transfers to the cloud and enabling faster responses for clients. While this paradigm has been successfully employed to improve response times in some contexts, mostly by having clients perform pre-processing and/or filtering of data, or by leveraging on distributed caching infrastructures, we argue that the combination of edge and cloud computing has the potential to enable novel applications. However, to do so, some significant research challenges have to be tackled by the computer science community. In this paper, we discuss different edge resources and their potential use, motivated by envisioned use cases. We then discuss concrete research challenges that once overcome, will allow to realize our vision. We also discuss potential benefits than can be obtained by exploiting the hybrid cloud/edge paradigm.
Scalable Graph Embedding for Asymmetric Proximity

Graph Embedding methods are aimed at mapping each vertex into a low dimensional vector space, which preserves certain structural relationships among the vertices in the original graph. Recently, several works have been proposed to learn embeddings based on sampled paths from the graph, e.g., DeepWalk, Line, Node2Vec. However, their methods only preserve symmetric proximities, which could be insufficient in many applications, even the underlying graph is undirected. Besides, they lack of theoretical analysis of what exactly the relationships they preserve in their embedding space. In this paper, we propose an asymmetric proximity preserving (APP) graph embedding method via random walk with restart, which captures both asymmetric and high-order similarities between node pairs. We give theoretical analysis that our method implicitly preserves the Rooted PageRank score for any two vertices. We conduct extensive experiments on tasks of link prediction and node recommendation on open source datasets, as well as online recommendation services in Alibaba Group, in which the training graph has over 290 million vertices and 18 billion edges, showing our method to be highly scalable and effective.
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift

We provide initial seedings to the Quick Shift clustering algorithm, which approximate the locally high-density regions of the data. Such seedings act as more stable and expressive cluster-cores than the singleton modes found by Quick Shift. We establish statistical consistency guarantees for this modification. We then show strong clustering performance on real datasets as well as promising applications to image segmentation.
On attention models for human activity recognition

Deep Learning methods have become very attractive in the wider, wearables-based human activity recognition (HAR) research community. The majority of models are based on either convolutional or explicitly temporal models, or combinations of both. In this paper we introduce attention models into HAR research as a data driven approach for exploring relevant temporal context. Attention models learn a set of weights over input data, which we leverage to weight the temporal context being considered to model each sensor reading. We construct attention models for HAR by adding attention layers to a state-of-the-art deep learning HAR model (DeepConvLSTM) and evaluate our approach on benchmark datasets achieving significant increase in performance. Finally, we visualize the learned weights to better understand what constitutes relevant temporal context.
Assessment of Mesophotic Coral Ecosystem Connectivity for Proposed Expansion of a Marine Sanctuary in the Northwest Gulf of Mexico: Larval Dynamics

While there are several areas containing shallow coral habitats in the Gulf of Mexico (GOM), the availability of suitable reef habitat at mesophotic depths (~30–150 m) along the continental shelf margin suggests the potential for ecologically connected coral populations across hundreds of kilometers in the northwest (NW) GOM. The NW GOM includes a relatively high proportion of mesophotic habitats, including salt diapirs in Flower Garden Banks National Marine Sanctuary (FGBNMS), Bright Bank, and McGrail Bank, the latter two being Habitat Areas of Particular Concern (HAPCs). In response to a proposed expansion plan for the sanctuary boundaries to include additional mesophotic banks in the NW GOM, we investigated the genetic connectivity of the depth-generalist coral Montastraea cavernosa, a ubiquitous member of scleractinian communities throughout the Tropical Western Atlantic. M. cavernosa populations in the NW GOM demonstrated strong connectivity with relatively high levels of gene flow and no significant genetic differentiation occurring over banks up to 120 km apart. Historical migration models based on genetic data predicted panmixia of M. cavernosa across the NW GOM. The comparisons between genetic and biophysical models (see Garavelli et al., 2018; associate manuscript) highlight not only the importance of incorporating multiple assessments of connectivity into management schemes, but also the potentially stochastic nature of oceanographic patterns in the NW GOM and their effect on migration estimates among coral habitats. These trends indicate that M. cavernosa populations have remained well-connected in the NW GOM and that coral populations on each bank have likely been receiving larval recruitment through time. Thus, M. cavernosa populations should be managed as a combined unit within the NW GOM, which supports the proposal to expand the NMS boundaries to include mesophotic habitats beyond West and East FGB.
Butyrylation of Maize and Potato Starches and Characterization of the Products by Nuclear Magnetic Resonance and In Vitro Fermentation

Intake of butyrylated starches may increase colonic butyrate supply, which can be of public health and clinical benefit by maintaining colonic health. The objective was to investigate if an organocatalytic method with tartaric acid as a catalyst could be applied to produce butyrylated products from different starch sources and to characterize their chemical structure and fermentation capability by using solid-state 13C MAS NMR (magic angle spinning nuclear magnetic resonance) spectroscopy and an in vitro fermentation model, respectively. Low-amylose and high-amylose potato starch (LAPS and HAPS) and low-amylose and high-amylose maize starch (LAMS and HAMS) were subjected to organocatalytic butyrylation. This resulted in products with an increasing degree of substitution (DS) measured by heterogenous saponification and back titration with the HCl (chemical method) depending on reaction time. NMR analysis, however, showed that the major part of the acylation was induced by tartarate (75–89%) and only a minor part (11–25%) by butyrate. Generally, the chemical method overestimated the DS by 38% to 91% compared with the DS determination by NMR. Increasing the DS appeared to lower the in vitro fermentation capability of starches independent of the starch source and, therefore, do not seem to present a feasible method to deliver more butyrate to the colon than lower DS products.
Milk microRNA-146a as a potential biomarker in bovine tuberculosis

In this research communication we exploited the potential use of milk microRNAs (miRs) as biomarkers for bovine tuberculosis (bTB). bTB is a zoonotic disease caused by Mycobacterium bovis which affects animal health, influencing herd economic sustainability. Diagnosis is based on skin delayed-type hypersensitivity reaction and quantification of interferon gamma but both techniques are influenced by several confounding factors. Thus, new methods for early diagnosis are required. In this context, microRNAs have been used as promising biomarkers for both infectious and non-infectious diseases. To determine the possible involvement of microRNAs in bTB, we analysed the expression of four immune-related miRs in 200 cows grouped in cases and controls with respect to positivity to tuberculosis. The analysis showed a different magnitude of expression in the groups indicating that active tuberculosis could influence miRs expression. We used expression values of miR-146a, the highest differentially expressed miR, for Receiver operating characteristic (ROC) curve analysis. In order to determine a test cut-off value for miR-146a expression that would differentiate cases and controls, a value for the miR-146a expression higher than 8 was selected as this gave a test specificity and sensitivity of 80·0% and 86·0% respectively. These values confirm the possibility of using miR-146a as a milk prognostic biomarker for bovine tuberculosis.
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits

We address the problem of regret minimization in logistic contextual bandits, where a learner decides among sequential actions or arms given their respective contexts to maximize binary rewards. Using a fast inference procedure with Polya-Gamma distributed augmentation variables, we propose an improved version of Thompson Sampling, a Bayesian formulation of contextual bandits with near-optimal performance. Our approach, Polya-Gamma augmented Thompson Sampling (PG-TS), achieves state-of-the-art performance on simulated and real data. PG-TS explores the action space efficiently and exploits high-reward arms, quickly converging to solutions of low regret. Its explicit estimation of the posterior distribution of the context feature covariance leads to substantial empirical gains over approximate approaches. PG-TS is the first approach to demonstrate the benefits of Polya-Gamma augmentation in bandits and to propose an efficient Gibbs sampler for approximating the analytically unsolvable integral of logistic contextual bandits.
1 2 A pr 2 01 8 On linear codes and distinct weights

We provide a construction for linear codes attaining the maximum possible number of distinct weights. We then introduce the related problem of determining the existence of linear codes with an arbitrary number of distinct non-zero weights, and we completely determine a solution in the binary case. Introduction A recent work on extremal properties of linear codes presented the problem of determining the maximum possible number of distinct non-zero weights in a linear code [SZSC18], partially providing solutions and leaving the general case as a conjecture. For the sake of completeness, we introduce the problem and the conjecture. Let C be an [n, k]q linear code and let us denote with A (C) the weight distribution of the code C. We also denote with len (C) the length of a code C and with dim (C) its dimension. We are interested in the maximum number of distinct weights that a linear code of dimension k over Fq can have: Lq (k) := max {|A (C)| : dim (C) = k} We remark that this value is obtained by considering all possible codes of dimension k over Fq, regardless on their length. A related problem would be to determine the maximum number of weights in a code of length n, a value which we will denote as Lq (n, k). The relation between Lq (k) and Lq (n, k) is Lq (k) := max n Lq (n, k) , and an interested reader can go through [SZSC18] for more results on this function. By linearity it has to hold Lq (k) ≤ q − 1 q − 1 + 1, (1) and in [SZSC18] it is proved that L2 (k) ≥ 2 k , and Lq (k) ≥ q + 2, (2)
Preprocessing of Various Data Sets Using Different Classification Algorithms for Evolutionary Programming

: The performance analysis and preprocessing of data is very important in data mining. Here, the performance is analyzed on various classification algorithms using different data sets so as to identify which results the best accuracy of different data. The preprocessing helps us to improve data efficiency and remove the noisy data which helps to identify the survival of the fittest. This paper presents the efficient data based on the various classification algorithms and preprocessing is performed. Here, various data sets are chosen, which results in comparison of data set based on the classification algorithm.
Application of Eexergy Analysis to Black Tea Production Process in Camli Tea Factory

This study treats the production process at the Çamlı Tea Factory as a continuous flow open system and analyses it according to the second law of thermodynamics, using the values for the years 2014-2015. Thermodynamic models of the component processes are constructed and each step is examined in terms of exergetic parameters. Tables are presented of the values of exergy input and exergy destruction for each component in the thermodynamic model. The study reports numerical values for important exergy losses in the system and identifies the zones where energy saving should be made.
Naturalistic Driving Study Investigating Self-Regulation Behavior in Early Alzheimer's Disease: A Pilot Study.

BACKGROUND Because cognitive processes decline in the earliest stages of Alzheimer's disease (AD), the driving abilities are often affected. The naturalistic driving approach is relevant to study the driving habits and behaviors in normal or critical situations in a familiar environment of participants. OBJECTIVE This pilot study analyzed in-car video recordings of naturalistic driving in patients with early-stage AD and in healthy controls, with a special focus on tactical self-regulation behavior. METHODS Twenty patients with early-stage AD (Diagnosis and Statistical Manual of Mental Disorders, Fourth Edition [DSM-IV] criteria), and 21 healthy older adults were included in the study. Data collection equipment was installed in their personal vehicles. Two expert psychologists assessed driving performance using a specially designed Naturalistic Driving Assessment Scale (NaDAS), paying particular attention to tactical self-regulation behavior, and they recorded all critical safety events. RESULTS Poorer driving performance was observed among AD drivers: their tactical self-regulation behavior was of lower quality. AD patients had also twice as many critical events as healthy drivers and three times more "unaware" critical events. CONCLUSION This pilot study used a naturalistic approach to accurately show that AD drivers have poorer tactical self-regulation behavior than healthy older drivers. Future deployment of assistance systems in vehicles should specifically target tactical self-regulation components.
Extant fold-switching proteins are widespread

Significance It is commonly thought that each globular protein has a single 3D structure, or fold, that fosters its function. In contrast, recent studies have identified several fold-switching proteins whose secondary structures can be remodeled in response to cellular stimuli. Although thought to be rare, we found 96 literature-validated fold-switching proteins by exhaustively searching the database of protein structures [Protein Data Bank (PDB)]. Characterizing these proteins led us to hypothesize that their abundance may be underrepresented in the PDB. Thus, we developed a computational method that identifies fold-switching proteins and used it to estimate that 0.5–4% of PDB proteins switch folds. These results suggest that proteins switch folds with significant frequency, which has implications for cell biology, genomics, and human health. A central tenet of biology is that globular proteins have a unique 3D structure under physiological conditions. Recent work has challenged this notion by demonstrating that some proteins switch folds, a process that involves remodeling of secondary structure in response to a few mutations (evolved fold switchers) or cellular stimuli (extant fold switchers). To date, extant fold switchers have been viewed as rare byproducts of evolution, but their frequency has been neither quantified nor estimated. By systematically and exhaustively searching the Protein Data Bank (PDB), we found ∼100 extant fold-switching proteins. Furthermore, we gathered multiple lines of evidence suggesting that these proteins are widespread in nature. Based on these lines of evidence, we hypothesized that the frequency of extant fold-switching proteins may be underrepresented by the structures in the PDB. Thus, we sought to identify other putative extant fold switchers with only one solved conformation. To do this, we identified two characteristic features of our ∼100 extant fold-switching proteins, incorrect secondary structure predictions and likely independent folding cooperativity, and searched the PDB for other proteins with similar features. Reassuringly, this method identified dozens of other proteins in the literature with indication of a structural change but only one solved conformation in the PDB. Thus, we used it to estimate that 0.5–4% of PDB proteins switch folds. These results demonstrate that extant fold-switching proteins are likely more common than the PDB reflects, which has implications for cell biology, genomics, and human health.
Parallelizing Bisection Root-Finding: A Case for Accelerating Serial Algorithms in Multicore Substrates

Multicore architectures dominate today's processor market. Even though the number of cores and threads are pretty high and continues to grow, inherently serial algorithms do not benefit from the abundance of cores and threads. In this paper, we propose Runahead Computing, a technique which uses idle threads in a multi-threaded architecture for accelerating the execution time of serial algorithms. Through detailed evaluations targeting both CPU and GPU platforms and a specific serial algorithm, our approach reduces the execution latency up to 9x in our experiments.