Miracle-dz/UniFAR-FTUs huggingface dataset:
Disguised Face Identification (DFI) with Facial KeyPoints Using Spatial Fusion Convolutional Network

Disguised face identification (DFI) is an extremely challenging problem due to the numerous variations that can be introduced using different disguises. This paper introduces a deep learning framework to first detect 14 facial key-points which are then utilized to perform disguised face identification. Since the training of deep learning architectures relies on large annotated datasets, two annotated facial key-points datasets are introduced. The effectiveness of the facial keypoint detection framework is presented for each keypoint. The superiority of the key-point detection framework is also demonstrated by a comparison with other deep networks. The effectiveness of classification performance is also demonstrated by comparison with the state-of-the-art face disguise classification methods.
High-Quality, Low-Delay Music Coding in the Opus Codec

The IETF recently standardized the Opus codec as RFC6716. Opus targets a wide range of real-time Internet applications by combining a linear prediction coder with a transform coder. We describe the transform coder, with particular attention to the psychoacoustic knowledge built into the format. The result out-performs existing audio codecs that do not operate under real-time constraints.
Integration of Word Meaning and World Knowledge in Language Comprehension

Although the sentences that we hear or read have meaning, this does not necessarily mean that they are also true. Relatively little is known about the critical brain structures for, and the relative time course of, establishing the meaning and truth of linguistic expressions. We present electroencephalogram data that show the rapid parallel integration of both semantic and world knowledge during the interpretation of a sentence. Data from functional magnetic resonance imaging revealed that the left inferior prefrontal cortex is involved in the integration of both meaning and world knowledge. Finally, oscillatory brain responses indicate that the brain keeps a record of what makes a sentence hard to interpret.
Spectral Graph-Based Method of Multimodal Word Embedding

In this paper, we propose a novel method for multimodal word embedding, which exploit a generalized framework of multi-view spectral graph embedding to take into account visual appearances or scenes denoted by words in a corpus. We evaluated our method through word similarity tasks and a concept-to-image search task, having found that it provides word representations that reflect visual information, while somewhat trading-off the performance on the word similarity tasks. Moreover, we demonstrate that our method captures multimodal linguistic regularities, which enable recovering relational similarities between words and images by vector arithmetics.
Induced production of rabbit articular cartilage-derived chondrocyte collagen II on polyhydroxyalkanoate blends

Three-dimensional porous scaffolds made from blend polyesters of polyhydroxyalkanoates (PHA) were evaluated with respect to their effects on collagen II production. Semi-quantitative reverse transcriptase polymerase chain reaction (RT-PCR) was used to assay collagen II mRNA for evaluation of the ability for the blend scaffolds to induce collagen II production. It was found that scaffold of poly-3-hydroxybutyrate (PHB) blended with a copolyester consisting of 3-hydoxybutyrate-co3-hydroxyhexanate (PHBHHx) in a radio of 1 : 2 had strong ability to induce collagen II production compared with other ratios of PHB/PHBHHx and poly-L-lactic acid (PLA). Collagen II expression level remained approx. 1.5-times higher on the above-mentioned blend compared with that of PLA throughout four weeks cultivation. At the same time, the PHB/PHBHHx blend (1 : 2) exhibited a similar tendency as PLA to maintain the collagen II expression level over the entire culture period. The results showed that the PHB/PHBHHx blend (1 : 2) reported to improve mechanical properties compared with PHB or PHBHHx improved biocompatibility in comparison with PHB, PHBHHx, PLA and other blending systems consisting of PHB/PHBHHX in ratios of 2 :1 and 1 :1, respectively.
Taiwanascus samuelsii sp. nov., an addition to Niessliaceae from the Western Ghats, Kerala, India

A new species of Taiwanascus, T. samuelsii, was collected from southern parts of Western Ghats on dead branches of Anacardium occidentale and is described. The new cleistothecial ascomycete is different from the type and only species in Taiwanascus, T. tetrasporus, in cleistothecial size, setae, and ascospore characteristics.
Clinical implications of small bowel diverticula.

BACKGROUND Small bowel diverticula are usually asymptomatic and rare. Their importance is based on the fact that they carry the risk of serious complications. OBJECTIVE To study the implications and the therapeutic approach regarding small bowel diverticulosis. METHODS The medical records of 54 patients with diverticular disease of the small bowel, including Meckel's and duodenum diverticula, were retrospectively reviewed. The mean age of the 32 male and 22 female patients was 53.2 years. RESULTS Diverticula were found in the duodenum in 11 cases, in the jejunum and ileum in 21 cases, and with Meckel's diverticula in 22 cases. In 24% of the patients the diverticula were multiple. The most common clinical symptom was abdominal pain, in 44.4%. Most of the duodenum diverticula were asymptomatic; 47.6% of the patients with diverticular disease located in the jejunum and ileum presented with chronic symptoms. The overall diagnostic rate for symptomatic diverticula before surgery was 52.7%; in 33.3% diverticula were found incidentally during other diagnostic or therapeutic procedures. Forty-one patients were managed surgically. 15 patients were operated on urgently because of infection or rupture, 4 patients for bleeding, 5 patients for intestinal obstruction, and one patient for jaundice. CONCLUSIONS The incidence of asymptomatic small bowel diverticula is difficult to ascertain. Patients with Meckel's and duodenal diverticula are usually asymptomatic, while the majority of jejunal and ileal diverticula patients present with chronic symptoms. The pre-operative diagnostic rate is higher for duodenal diverticula. Small bowel diverticula do not require surgical treatment unless refractory symptoms or complications occur.
Isolation , identification and characterization of phosphate solubilizing bacteria from different crop soils of Srivilliputtur Taluk , Virudhunagar District , Tamil Nadu

The use of phosphate solubilizing bacteria (PSB) as biofertilizers has concurrently increased phosphorous uptake in plants and improved yields in several crop species. A laboratory study was conducted to isolate, identify and characterize the phosphate solubilizing bacteria from different crop soils such as Okra, Chilli, tomato, Cotton and Egg plant. The population dynamic of PSB was higher in the rhizosphere soil of tomato followed by brinjal. Based on the solubilization zone production in the solid medium, two isolates from each crop plant were selected and used for studies. The selected PSB strains were screened in vitro. Among 10 PSB isolates, 6 strains were identified as Bacillus megaterium, 2 strains as Pseudomonas putida and CP2 and CTP2 as P. fluorescence. The selected strains differed in utilization of different carbon, nitrogen, amino acid and vitamin sources.
Learning Discrete Distributions from Untrusted Batches

We consider the problem of learning a discrete distribution in the presence of an $\epsilon$ fraction of malicious data sources. Specifically, we consider the setting where there is some underlying distribution, $p$, and each data source provides a batch of $\ge k$ samples, with the guarantee that at least a $(1-\epsilon)$ fraction of the sources draw their samples from a distribution with total variation distance at most $\eta$ from $p$. We make no assumptions on the data provided by the remaining $\epsilon$ fraction of sources--this data can even be chosen as an adversarial function of the $(1-\epsilon)$ fraction of "good" batches. We provide two algorithms: one with runtime exponential in the support size, $n$, but polynomial in $k$, $1/\epsilon$ and $1/\eta$ that takes $O((n+k)/\epsilon^2)$ batches and recovers $p$ to error $O(\eta+\epsilon/\sqrt{k})$. This recovery accuracy is information theoretically optimal, to constant factors, even given an infinite number of data sources. Our second algorithm applies to the $\eta = 0$ setting and also achieves an $O(\epsilon/\sqrt{k})$ recover guarantee, though it runs in $\mathrm{poly}((nk)^k)$ time. This second algorithm, which approximates a certain tensor via a rank-1 tensor minimizing $\ell_1$ distance, is surprising in light of the hardness of many low-rank tensor approximation problems, and may be of independent interest.
Land surface spinup for episodic modeling

Abstract. Soil moisture strongly controls the surface fluxes in mesoscale numerical models, and thereby influences the boundary layer structure. Proper initialization of soil moisture is therefore critical for faithful simulations. In many applications, such as air quality or process studies, the model is run for short, discrete periods (a day to a month). This paper describes one method for soil initialization in these cases – self-spinup. In self-spinup, the model is initialized with a coarse-resolution operational model or reanalysis output, and run for a month, cycling its own soil variables. This allows the soil variables to develop appropriate spatial variability, and may improve the actual values. The month (or other period) can be run more than once if needed. The case shown is for the Boundary Layer Late Afternoon and Sunset Turbulence experiment, conducted in France in 2011. Self-spinup adds spatial variability, which improves the representation of soil moisture patterns around the experiment location, which is quite near the Pyrenees Mountains. The self-spinup also corrects a wet bias in the large-scale analysis. The overall result is a much-improved simulation of boundary layer structure, evaluated by comparison with soundings from the field site. Self-spinup is not recommended as a substitute for multi-year spinup with an offline land data assimilation system in circumstances where the data sets required for such spinup are available at the required resolution. Self-spinup may fail if the modeled precipitation is poorly simulated. It is an expedient for cases when resources are not available to allow a better method to be used.
Dynamic mechanical analysis of the interphase in bacterial polyester/cellulose whiskers natural composites

Nanocomposite materials were prepared from an elastomeric poly(hydroxyoctanoate) (PHO) latex as a fully amorphous or semi-crystalline matrix using a colloidal suspension of hydrolyzed cellulose whiskers as natural and biodegradable filler. After stirring, the preparations were cast and evaporated. High performance materials were obtained from these systems, preserving the natural character of PHO. Interfacial phenomena were assumed to be noticeable owing to the high specific area of this filler. Dynamic mechanical analysis was performed on these systems to test the influence of the interphase on the molecular mobility of the amorphous phase. To quantify the distance away from the surface at which the molecular mobility is restricted, a physical model was used to predict the mechanical loss angle. This allows removal of the filler reinforcement effect keeping only the interfacial effect. It was shown that the local motion at the filler-matrix interface of amorphous PHO chains is strongly affected when an amorphous PHO was used as the matrix. No significant change was observed when a semi-crystalline PHO was used as the matrix. This result was ascribed to a possible trancrystallization phenomenon of semi-crystalline PHO in contact with cellulose whisker surface, which prevents any contact between amorphous PHO chains and filler surface.
DeepVO: A Deep Learning approach for Monocular Visual Odometry

Deep Learning based techniques have been adopted with precision to solve a lot of standard computer vision problems, some of which are image classification, object detection and segmentation. Despite the widespread success of these approaches, they have not yet been exploited largely for solving the standard perception related problems encountered in autonomous navigation such as Visual Odometry (VO), Structure from Motion (SfM) and Simultaneous Localization and Mapping (SLAM). This paper analyzes the problem of Monocular Visual Odometry using a Deep Learning-based framework, instead of the regular 'feature detection and tracking' pipeline approaches. Several experiments were performed to understand the influence of a known/unknown environment, a conventional trackable feature and pre-trained activations tuned for object classification on the network's ability to accurately estimate the motion trajectory of the camera (or the vehicle). Based on these observations, we propose a Convolutional Neural Network architecture, best suited for estimating the object's pose under known environment conditions, and displays promising results when it comes to inferring the actual scale using just a single camera in real-time.
Application of higher order statistics techniques to EMG signals to characterize the motor unit action potential

The electromyographic (EMG) signal provides information about the performance of muscles and nerves. At any instant, the shape of the muscle signal, motor unit action potential (MUAP), is constant unless there is movement of the position of the electrode or biochemical changes in the muscle due to changes in contraction level. The rate of neuron pulses, whose exact times of occurrence are random in nature, is related to the time duration and force of a muscle contraction. The EMG signal can be modeled as the output signal of a filtered impulse process where the neuron firing pulses are assumed to be the input of a system whose transfer function is the motor unit action potential. Representing the neuron pulses as a point process with random times of occurrence, the higher order statistics based system reconstruction algorithm can be applied to the EMG signal to characterize the motor unit action potential. In this paper, we report results from applying a cepstrum of bispectrum based system reconstruction algorithm to real wired-EMG (wEMG) and surface-EMG (sEMG) signals to estimate the appearance of MUAPs in the Rectus Femoris and Vastus Lateralis muscles while the muscles are at rest and in six other contraction positions. It is observed that the appearance of MUAPs estimated from any EMG (wEMG or sEMG) signal clearly shows evidence of motor unit recruitment and crosstalk, if any, due to activity in neighboring muscles. It is also found that the shape of MUAPs remains the same on loading.
KPC and NDM-1 Genes in Related Enterobacteriaceae Strains and Plasmids from Pakistan and the United States

To characterize the genomic context of New Delhi metallo-β-lactamase-1 (NDM-1) and Klebsiella pneumoniae carbapenemase (KPC), we sequenced 78 Enterobacteriaceae isolates from Pakistan and the United States encoding KPC, NDM-1, or no carbapenemase. High similarities of the results indicate rapid spread of carbapenem resistance between strains, including globally disseminated pathogens.
Radon survey and soil gamma doses in primary schools of Batman, Turkey

A survey was conducted to evaluate levels of indoor radon and gamma doses in 42 primary schools located in Batman, southeastern Anatolia, Turkey. Indoor radon measurements were carried out using CR-39 solid-state nuclear track detector-based radon dosimeters. The overall mean annual 222Rn activity in the surveyed area was found to be 49 Bq m−3 (equivalent to an annual effective dose of 0.25 mSv). However, in one of the districts (Besiri) the maximum radon value turned out to be 307 Bq m−3. The estimated annual effective doses are less than the recommended action level (3–10 mSv). It is found that the radon concentration decreases with increasing floor number. The concentrations of natural and artificial radioisotopes were determined using gamma-ray spectroscopy for soil samples collected in close vicinity of the studied schools. The mean gamma activity concentrations in the soil samples were 31, 25, 329 and 12 Bq kg−1 for 226Ra, 232Th, 40K and 137Cs, respectively. The radiological parameters such as the absorbed dose rate in air and the annual effective dose equivalent were calculated. These radiological parameters were evaluated and compared with the internationally recommended values.
One-year and long-term mortality in patients hospitalized for chronic obstructive pulmonary disease.

BACKGROUND Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Identifying potentially-modifiable predictors of mortality could help optimize COPD patient management. The aim of this study is to determine long-term mortality following hospitalization due to acute exacerbations of COPD (AECOPD), as well as AECOPD mortality predictors. METHODS We conducted a retrospective study by reviewing the medical records of all patients admitted with AECOPD in the University Hospital Complex of Santiago de Compostela in 2007 and 2008. In order to identify variables independently associated with mortality, we conducted a multivariate Cox proportional hazard regression analysis including those variables which proved to be significant in the univariate analysis. RESULTS Seven hundred and fifty seven patients were assessed. Patient mean age was 74.8 years and males accounted for 77% of all patients. Mean stay was 12.2 days. Three point six percent of all patients required intensive care. As for mortality rates, 1-year mortality was 26.2%, and 5-year mortality was 64.3%. In both scenarios, the most frequent causes of death were respiratory and cardiovascular disorders. Factors independently associated with mortality were older age, hospitalization by internal medicine (IMU), length of stay, the need for mechanical ventilation (MV) or noninvasive mechanical ventilation (NIV), early readmission, and history of atrial fibrillation (AF) and dementia. CONCLUSIONS In patients with COPD, age, exacerbation severity and comorbidity have long-term prognostic significance.
Deploying Mesh Nodes under Non-Uniform Propagation

Wireless mesh networks are popular as a cost- effective means to provide broadband connectivity to large user populations. A mesh network placement provides coverage, such that each target client location has a link to a deployed mesh node, and connectivity, such that each mesh node wirelessly connects directly to a gateway or via intermediate mesh nodes. Prior work on placement assumes wireless propagation to be uniform in all directions, i.e., an unrealistic assumption of circular communication regions. In this paper, we present approximation algorithms to solve the NP- hard mesh node placement problem for non-uniform propagation settings. The first key challenge is incorporating non-uniform propagation, which we address by formulating the problem input as a connectivity graph consisting of discrete target coverage locations and potential mesh node locations. This graph incorporates non-uniform propagation by specifying the estimated signal quality per link. Secondly, our algorithms are the first to minimize the number of deployed mesh nodes with constant-factor approximation ratio in the non-uniform propagation setting. To achieve this, we formulate the Degree-Constrained Terminal Steiner tree problem and present approximation algorithms which leverage prior results on the Steiner tree problem. Third, it is impractical to measure all possible potential mesh links, and therefore deployment planning must rely on estimations. To address this challenge, we extend our algorithm to iteratively measure the links in the solution Steiner tree, refining the graph input on a per-link basis in order to ensure the deployed network is not disconnected. Finally, we use propagation measurements at 35,000 locations in the deployed GoogleWiFi network to investigate placement in a realistic, non-uniform propagation environment. Under this measured propagation setting, our algorithms result in up to 80% fewer mesh nodes than current algorithms and only require an average of 3 measurements per deployed mesh node to ensure backhaul connectivity.
Long-Term Results of Early Plasmapheresis to Prevent Recurrence of FSGS in High-Risk Renal Transplant Recipients

Background: Recurrent focal segmental glomerulosclerosis (FSGS) following transplantation occurs in 30-40% of affected patients and has been ascribed to the presence of a circulating permeability factor (FSPF). Plasmapheresis (PP) can induce remission of proteinuria in recurrent FSGS and may have a role in preventing recurrence if performed preemptively. However, predicting which patients will recur remains problematic. Methods: Clinical parameters (biopsy-proven FSGS, end-stage renal disease within 3 years of diagnosis or advanced azotemia at presentation or prior allograft loss due to recurrent FSGS) were used to identify patients deemed to be at high-risk for recurrence, who subsequently underwent a protocol of 8 PP treatments in the perioperative period. Recurrence rates, outcomes and treatment responses were compared to those individuals diagnosed with FSGS who did not meet criteria for study participation (“low-risk” patients). Results: A total of 707 adult and pediatric kidney transplants were performed during the study period (1999 – 2009) with 46 (6.5%) having some prior diagnosis of FSGS. Of these, 14 (2% of the total) met the clinical criteria for a high risk of disease recurrence and underwent the study protocol. There was a significantly greater risk of developing recurrent FSGS in the high-risk arm with 5/14 (36%) patients experiencing biopsy-proven recurrent disease compared to none detected in the low-risk group. All patients with recurrence were treated with additional courses of PP. Two patients experienced partial remissions (proteinuria < 2 g/day) and one a complete remission. Death-censored graft survival was similar between the two groups although survival in the low-risk arm was lower than expected due to an excess of patient deaths. Graft function as estimated by serum creatinine was excellent and comparable in both study arms (1.4 mg/dl, low-risk vs 1.5 mg/dl, high-risk). Conclusion: The results indicate that patients at high risk for FSGS recurrence can be identified based on clinical parameters. Furthermore, PP may play a role in decreasing the incidence of recurrent FSGS in high-risk patients, although definitive conclusions regarding optimal management in this patient population can only be drawn from a large, randomized and controlled study.
Ultrahomogeneous Semilinear Spaces

A semilinear space S is ultrahomogeneous if each isomorphism between the semilinear structures induced on two finite subsets can be extended to an automorphism of S. We give a complete classification of all finite ultrahomogeneous semilinear spaces. Our theorem extends a result of A. Gardiner on graphs and a result of A. Devillers and J. Doyen on linear spaces. 2000 Mathematical Subject Classification: 05B25, 51E14, 20B25.