Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Analog and Digital Precoding: From Practical RF System Models to Information Theoretic Bounds

Hybrid analog-digital precoding is a key millimeter wave access technology, where an antenna array with reduced number of radio frequency (RF) chains is used with an RF precoding matrix to increase antenna gain at a reasonable cost. However, digital and RF precoder algorithms must be accompanied by a detailed system model of the RF precoder. In this work, we provide fundamental RF system models for these precoders, and show their impact on achievable rates. We show that hybrid precoding systems suffer from significant degradation, once the limitations of RF precoding network are accounted. We subsequently quantify this performance degradation, and use it as a reference for comparing the performance of different precoding methods. These results indicate that hybrid precoders must be redesigned (and their rates recomputed) to account for practical factors.
Combining a vector space representation of linguistic context with a deep neural network for text-to-speech synthesis

Conventional statistical parametric speech synthesis relies on decision trees to cluster together similar contexts, resulting in tied-parameter context-dependent hidden Markov models (HMMs). However, decision tree clustering has a major weakness: it use hard division and subdivides the model space based on one feature at a time, fragmenting the data and failing to exploit interactions between linguistic context features. These linguistic features themselves are also problematic, being noisy and of varied relevance to the acoustics. We propose to combine our previous work on vector-space representations of linguistic context, which have the added advantage of working directly from textual input, and Deep Neural Networks (DNNs), which can directly accept such continuous representations as input. The outputs of the network are probability distributions over speech features. Maximum Likelihood Parameter Generation is then used to create parameter trajectories, which in turn drive a vocoder to generate the waveform. Various configurations of the system are compared, using both conventional and vector space context representations and with the DNN making speech parameter predictions at two different temporal resolutions: frames, or states. Both objective and subjective results are presented. Index Terms: TTS, speech synthesis, deep neural network, vector space model, unsupervised learning
Relationship of Cerebrospinal Fluid Markers to 11C-PiB and 18F-FDDNP Binding

The purpose of this study was to investigate the potential relationships between cerebrospinal fluid (CSF) measurements of β-amyloid-1–42 (Aβ1-42) and total tau to 11C-Pittsburgh compound B (11C-PiB) and 2-(1-{6-[(2-18F-fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene) malononitrile (18F-FDDNP) binding as measured using PET. Methods: A total of 37 subjects were included, consisting of 15 patients with Alzheimer disease (AD), 12 patients with mild cognitive impairment, and 10 healthy controls. All subjects underwent a lumbar puncture and PET using both 11C-PiB and 18F-FDDNP. For both PET tracers, parametric images of binding potential were generated. Potential associations of CSF levels of Aβ1-42 and tau with 11C-PiB and 18F-FDDNP binding were assessed using Pearson correlation coefficients and linear regression analyses. Results: For both global 11C-PiB and 18F-FDDNP binding, significant correlations with CSF levels of Aβ1-42 (r = −0.72 and −0.37, respectively) and tau (r = 0.58 and 0.56, respectively) were found across groups (all P < 0.001, except P < 0.05 for correlation between 18F-FDDNP and Aβ1-42). Linear regression analyses showed that, adjusted for regional volume, age, sex, and diagnosis, global 11C-PiB uptake had an inverse association with Aβ1-42 CSF levels (standardized β = −0.50, P < 0.001), whereas there was a positive association between global 18F-FDDNP binding and tau CSF levels (standardized β = 0.62, P < 0.01). Conclusion: The good agreement between these 2 different types of biomarkers (i.e., CSF and PET) provides converging evidence for their validity. The inverse association between 11C-PiB and CSF tau Aβ1-42 confirms that 11C-PiB measures amyloid load in the brain. The positive association between 18F-FDDNP and CSF tau suggests that at least part of the specific signal of 18F-FDDNP in AD patients is due to tangle formation.
Diabetic nephropathy; principles of diagnosis and treatment of diabetic kidney disease

Diabetes mellitus is a leading epidemic of the present world. It is considered the leading cause of death among end-stage renal disease (ESRD) patients. The complications associated with diabetes mellitus have boosted the number of deaths in the last years. These complications are the result of long lasting effects of diabetes mellitus on the glomerular microvasculature of the kidney. Diabetic nephropathy (DN) develops in patients with several years’ medical history of diabetes and renal failure. However, research shows that patients with type 1 diabetes progress early to ESRD as compared to those with type 2. DN is more prevalent in ethnic minorities as compared to other groups in society. There are new and different treatment options available since medical science has progressed due to increased research efforts. Unfortunately, there is no permanent cure. The aim of this article is to explore the research of therapeutic strategies currently in use by medical practitioners in order to increase understanding of DN.
Adiponectin Agonist ADP355 Attenuates CCl4-Induced Liver Fibrosis in Mice

Liver fibrosis is a growing global health problem characterized by excess deposition of fibrillar collagen, and activation of hepatic stellate cells (HSCs). Adiponectin is known to possess anti-fibrotic properties; however a high physiological concentration and multiple forms circulating in blood prohibit clinical use. Recently, an adiponectin-like small synthetic peptide agonist (ADP355: H-DAsn-Ile-Pro-Nva-Leu-Tyr-DSer-Phe-Ala-DSer-NH2) was synthesized for the treatment of murine breast cancer. The present study was designed to evaluate the efficacy of ADP355 as an anti-fibrotic agent in the in vivo carbon tetrachloride (CCl4)-induced liver fibrosis model. Liver fibrosis was induced in eight-week old male C57BL/6J mice by CCl4-gavage every other day for four weeks before injection of a nanoparticle-conjugated with ADP355 (nano-ADP355). Control gold nanoparticles and nano-ADP355 were administered by intraperitoneal injection for two weeks along with CCl4-gavage. All mice were sacrificed after 6 weeks, and serum and liver tissue were collected for biochemical, histopathologic and molecular analyses. Biochemical studies suggested ADP355 treatment attenuates liver fibrosis, determined by reduction of serum aspartate aminotransferase (AST), alanine aminotransferase ALT) and hydroxyproline. Histopathology revealed chronic CCl4-treatment results in significant fibrosis, while ADP355 treatment induced significantly reversed fibrosis. Key markers for fibrogenesis–α-smooth muscle actin (α-SMA), transforming growth factor-beta1 (TGF-β1), connective tissue growth factor (CTGF), and the tissue inhibitor of metalloproteinase I (TIMP1) were also markedly attenuated. Conversely, liver lysates from ADP355 treated mice increased phosphorylation of both endothelial nitric oxide synthase (eNOS) and AMPK while AKT phosphorylation was diminished. These findings suggest ADP355 is a potent anti-fibrotic agent that can be an effective intervention against liver fibrosis.
The design and implementation of a fault-tolerant RPC system: Ninf-C

We describe the design and implementation of a fault tolerant GridRPC system, Ninf-C, designed for easy programming of large-scale master-worker programs that take from few days to few months for its execution in a grid environment. Ninf-C employs Condor, developed at University of Wisconsin, as the underlying middleware supporting remote file transmission and checkpointing for system-wide robustness for application users on the grid. Ninf-C layers all the GridRPC communication and task parallel programming features on top of Condor in a non-trivial fashion, assuming that the entire program is structured in a master-worker style-in fact, older Ninf master-worker programs can be run directly or trivially ported to Ninf-C. In contrast to the original Ninf, Ninf-C exploits and extends Condor features extensively for robustness and transparency, such as 1) checkpointing and stateful recovery of the master process, 2) the master and workers mutually communicating using (remote) files, not IP sockets, and 3) automated throttling of parallel GridRPC calls; and in contrast to using Condor directly, programmers can set up complex dynamic workflow as well as master-worker parallel structure with almost no learning curve involved. To prove the robustness of the system, we performed an experiment on a heterogeneous cluster that consists of x86 and SPARC CPUs, and ran a simple but long-running master-worker program with staged rebooting of multiple nodes to simulate some serious fault situations. The program execution finished normally avoiding all the fault scenarios, demonstrating the robustness of Ninf-C.
Activation of nervous system development genes in bone marrow derived mesenchymal stem cells following spaceflight exposure

Stalled cell division in precursor bone cells and reduced osteoblast function are considered responsible for the microgravity‐induced bone loss observed during spaceflight. However, underlying molecular mechanisms remain unraveled. Having overcome technological difficulties associated with flying cells in a space mission, we present the first report on the behavior of the potentially osteogenic murine bone marrow stromal cells (BMSC) in a 3D culture system, flown inside the KUBIK aboard space mission ISS 12S (Soyuz TMA‐8 + Increment 13) from March 30 to April 8, 2006 (experiment “Stroma‐2”). Flight 1g control cultures were performed in a centrifuge located within the payload. Ground controls were maintained on Earth in another KUBIK payload and in Petri dishes. Half of the cultures were stimulated with osteo‐inductive medium. Differences in total RNA extracted suggested that cell proliferation was inhibited in flight samples. Affymetrix technology revealed that 1,599 genes changed expression after spaceflight exposure. A decreased expression of cell‐cycle genes confirmed the inhibition of cell proliferation in space. Unexpectedly, most of the modulated expression was found in genes related to various processes of neural development, neuron morphogenesis, transmission of nerve impulse and synapse, raising the question on the lineage restriction in BMSC. J. Cell. Biochem. 111: 442–452, 2010. © 2010 Wiley‐Liss, Inc.
The sizing rules method for analog integrated circuit design

Presents the sizing rules method for analog CMOS circuit design that consists of: first, the development of a hierarchical library of transistor pair groups as basic building blocks for analog CMOS circuits; second, the derivation of a hierarchical generic list of constraints that must be satisfied to guarantee the function of each block and its reliability with respect to physical effects; and third, the development of an automatic recognition of building blocks in a circuit schematic. The sizing rules method efficiently captures design knowledge on the technology-specific level of transistor pair groups. This reduces the preparatory modeling effort for analog circuit synthesis. Results of industrial applications to circuit sizing, design centering, response surface modeling and analog placement show the significance of the sizing rules method. Sizing rules especially make sure that automatic circuit sizing and design centering lead to technically meaningful and robust results.
FBK-UEdin Participation to the WMT13 Quality Estimation Shared Task

In this paper we present the approach and system setup of the joint participation of Fondazione Bruno Kessler and University of Edinburgh in the WMT 2013 Quality Estimation shared-task. Our submissions were focused on tasks whose aim was predicting sentence-level Human-mediated Translation Edit Rate and sentence-level post-editing time (Task 1.1 and 1.3, respectively). We designed features that are built on resources such as automatic word alignment, n-best candidate translation lists, back-translations and word posterior probabilities. Our models consistently overcome the baselines for both tasks and performed particularly well for Task 1.3, ranking first among seven participants.
Approximation method to rank-one binary matrix factorization

In this paper, we study the rank-one binary matrix factorization problem, which plays a key role in analyzing the high dimensional discrete-attributed datasets. We first transform this problem into an equivalent binary quadratic programming, and then a mixed-integer linear formulation is obtained using linearization technique. A characterization on the extreme points is given for the polyhedron of the linearized formulation. To the best of our knowledge, this is the first time to study the extreme points property of the rank-one binary matrix factorization. Based on this property, a LP rounding based 2-approximation algorithm is designed for this problem. Numerical results illustrate the efficiency of the proposed approximation algorithm.
Acoustical Vision of Neglected Stimuli: Interaction among Spatially Converging Audiovisual Inputs in Neglect Patients

Cross-modal spatial integration between auditory and visual stimuli is a common phenomenon in space perception. The principles underlying such integration have been outlined by neurophysiological and behavioral studies in animals (Stein & Meredith, 1993), but little evidence exists proving that similar principles occur also in humans. In the present study, we explored such possibility in patients with visual neglect, namely, patients with visuospatial impairment. To test this hypothesis, neglect patients were required to detect brief flash of light presented in one of six spatial positions, either in a unimodal condition (i.e., only visual stimuli were presented) or in a cross-modal condition (i.e., a sound was presented simultaneously to the visual target, either at the same spatial position or a tone of the remaining five possible positions). The results showed an improvement of visual detection when visual and auditory stimuli were originating from the same position in space or at close spatial disparity (168). In contrast, no improvement was found when the spatial separation of visual and auditory stimuli was larger than 168. Moreover, the improvement was larger for visual positions that were more affected by the spatial impairment, i.e., the most peripheral positions in the left visual field (LVF). In conclusion, the results of the present study considerably extend our knowledge about the multisensory integration, by showing in humans the existence of an integrated visuoauditory system with functional properties similar to those found in animals.
The refit model for end-stage liver disease-Na is not a better predictor of mortality than the refit model for end-stage liver disease in patients with cirrhosis and ascites

Background/Aims The modification of the Model for End-Stage Liver Disease (MELD) scoring system (Refit MELD) and the modification of MELD-Na (Refit MELDNa), which optimized the MELD coefficients, were published in 2011. We aimed to validate the superiority of the Refit MELDNa over the Refit MELD for the prediction of 3-month mortality in Korean patients with cirrhosis and ascites. Methods We reviewed the medical records of patients admitted with hepatic cirrhosis and ascites to the Konkuk University Hospital between January 2006 and December 2011. The Refit MELD and Refit MELDNa were compared using the predictive value of the 3-month mortality, as assessed by the Child-Pugh score. Results In total, 530 patients were enrolled, 87 of whom died within 3 months. Alcohol was the most common etiology of their cirrhosis (n=271, 51.1%), and the most common cause of death was variceal bleeding (n=20, 23%). The areas under the receiver operating curve (AUROCs) for the Child-Pugh, Refit MELD, and Refit MELDNa scores were 0.754, 0.791, and 0.764 respectively; the corresponding values when the analysis was performed only in patients with persistent ascites (n=115) were 0.725, 0.804, and 0.796, respectively. The significant difference found among the Child-Pugh, Refit MELD, and Refit MELDNa scores was between the Child-Pugh score and Refit MELD in patients with persistent ascites (P=0.039). Conclusions Refit MELD and Refit MELDNa exhibited good predictability for 3-month mortality in patients with cirrhosis and ascites. However, Refit MELDNa was not found to be a better predictor than Refit MELD, despite the known relationship between hyponatremia and mortality in cirrhotic patients with ascites.
Retaining expressions on de-identified faces

The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in recorded documents. Prior research into face de-identification algorithms has successfully proposed k-anonymity methods that guarantee to thwart face recognition software. However, there has been little investigation into the preservation of the data utility such as gender and expression in the original images. To address this challenge, a new algorithm based on the Active Appearance Model is proposed here. The main attraction of the approach is that of the preservation of the data utility in terms of facial expression, whilst maintaining privacy protection. The former includes not only the preservation of the expression category (e.g. happy or sad), but also the details of the original expression (e.g. the intensity of a smile and movements of the lips). This is considered to be of significant value in real applications of face de-identification, where the given video contains facial images of the same expression with various degrees of intensity.
Failure of Ca2+‐activated, CREB‐dependent transcription in astrocytes

Astrocytes participate in signaling via Ca2+ transients that spread from cell to cell across a multicellular syncytium. The effect, if any, of these Ca2+ waves on the transcription of Ca2+/cAMP‐regulatory element binding protein (CREB)‐dependent genes is not known. We report here that, unlike neurons, increasing intracellular Ca2+ in cultured mouse cortical astrocytes failed to activate CREB‐dependent transcription, even though CREB was phosphorylated at serine 133. In contrast, both CREB phosphorylation and CREB‐dependent transcription were robustly stimulated by increasing cAMP. The failure of Ca2+‐activated transcription in astrocytes was correlated with the absence of CaMKIV, a Ca2+‐dependent protein kinase required for Ca2+‐stimulated gene transcription in neurons. The inability of Ca2+ to signal via CaMKIV may insulate CREB‐dependent gene transcription in astrocytes from activation by Ca2+ waves. © 2008 Wiley‐Liss, Inc.
3D Human Body Pose Estimation by Superquadrics

Abstract: This paper presents a method for 3D Human Body pose estimation by using a multi-camera system. The pose is estimated by RANSAC-object search with a robust least square fitting of 3D points to SuperQuadric (SQ) models of the searched object. The solution is verified by evaluating the matching score between the SQ object model and 3D real data captured by a multi-camera system and segmented by a special preprocessing algorithm. This method can be used for 3D object recognition, localization and pose estimation of Human Body.
[The Spanish version of the SF-36 Health Survey (the SF-36 health questionnaire): an instrument for measuring clinical results].

BACKGROUND The present study, performed within the International Quality of Life Assessment project (including researchers from 15 countries) presents preliminary results of the process of adaptation of the SF-36 to be used in Spain. METHODS The adaptation was based on the translation/back-translation methodology. Meetings of translators, researchers and patients were organized in order to produce successive versions. A study involving 47 individuals was carried out to assess the relative value (through a visual analogue scale) of each response choice of the questionnaire items. Finally, internal consistency and reproducibility of the Spanish version of the SF-36 was assessed by administering the questionnaire to 46 patients with stable coronary heart disease in two different occasions 2 weeks apart. RESULTS The average ratings of equivalence of the translated version with the original were high regardless of the difficulty of translation. The rank ordering of mean scores for each responses choice agreed with the ranking assigned in the questionnaire in all cases. Cronbach's Alpha was higher than 0.7 for all dimensions (range: 0.71-0.94) except for Social Functioning scale (alpha = 0.45). Intraclass correlation coefficients between both administrations of the questionnaire ranged from 0.58 to 0.99. CONCLUSIONS The adaptation process of the SF-36 has concluded with an instrument apparently equivalent to the original and with an acceptable level of reliability. Nevertheless, other basic characteristics of the adapted questionnaire (i.e. validity and sensitivity to changes) should be also assessed.
Budget-Driven Scheduling Algorithms for Batches of MapReduce Jobs in Heterogeneous Clouds

In this paper, we consider task-level scheduling algorithms with respect to budget and deadline constraints for a batch of MapReduce jobs on a set of provisioned heterogeneous (virtual) machines in cloud platforms. The heterogeneity is manifested in the popular “pay-as-you-go” charging model where the service machines with different performance would have different service rates. We organize the batch of jobs as a k-stage workflow and study two related optimization problems, depending on whether the constraints are on monetary budget or on scheduling length of the workflow. First, given a total monetary budget B, by combining an in-stage local greedy algorithm (whose optimality is also proven) and dynamic programming (DP) techniques, we propose a global optimal scheduling algorithm to achieve minimum scheduling length of the workflow within O(kB2). Although the optimal algorithm is efficient when B is polynomially bounded by the number of tasks in the MapReduce jobs, the quadratic time complexity is still high. To improve the efficiency, we further develop two greedy algorithms, called Global Greedy Budget (GGB) and Gradual Refinement (GR), each adopting different greedy strategies. In GGB we extend the idea of the local greedy algorithm to the efficient global distribution of the budget with minimum scheduling length as a goal whilst in GR we iteratively apply the DP algorithm to the distribution of exponentially reduced budget so that the solutions are gradually refined. Second, we consider the optimization problem of minimizing cost when the (time) deadline of the computation D is fixed. We convert this problem into the standard Multiple-Choice Knapsack Problem via a parallel transformation. Our empirical studies verify the proposed optimal algorithms and show the efficiencies of the greedy algorithms in cost-effectiveness to distribute the budget for performance optimizations of the MapReduce workflows.