Miracle-dz/UniFAR-FTUs huggingface dataset:
Edinburgh Research Explorer Matrix Completion under Interval Uncertainty

Matrix completion under interval uncertainty can be cast as a matrix completion problem with element-wise box constraints. We present an eﬃcient alternating-direction parallel coordinate-descent method for the problem. We show that the method outperforms any other known method on a benchmark in image in-painting in terms of signal-to-noise ratio, and that it provides high-quality solutions for an instance of collaborative ﬁltering with 100,198,805 recommendations within 5 minutes on a single personal computer.
Association between HRH4 polymorphisms and ankylosing spondylitis susceptibility.

TARGET The purpose of the study was to investigate the association between the histamine H4 receptor (HRH4) polymorphisms and the susceptibility to ankylosing spondylitis (AS). METHODS Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was used to analyze the HRH4 rs8088140 and rs657132 polymorphisms. Linkage disequilibrium and haplotype analyses were conducted with Haploview software. The genotypes distributions of HRH4 polymorphisms in the control group were tested by Hardy-Weinberg equilibrium (HWE), allele, genotype and haplotype frequencies between the cases and control groups were compared by χ(2) test. The controls were matched with cases by age and gender. The relative risk of AS with HRH4 polymorphisms was represented by odds ratio (OR) with 95% confidence interval (CI) calculated by χ(2) test. RESULTS The genotypes distributions of HRH4 rs8088140, rs657132 polymorphisms in controls conformed to HWE. The frequency of rs657132 AA genotype in the case group was obviously higher than that in the control group (P=0.040), and so was the A allele (OR=2.572, 95% CI=1.475-4.486, P=0.022). The frequency differences of A-A haplotype between two groups had statistical significance (P=0.011, OR=2.071, 95% CI=1.172-3.660) through haplotype analysis, indicating A-A might be the susceptible haplotype to AS. CONCLUSION The AA genotypes of HRH4 rs657132 polymorphism may be the susceptible factors for AS, and rs657132 plays a role in generation of AS. In addition, A-A haplotype in rs8088140-rs657132 is also increased the risk of AS.
Assessment of the Combined Effect of Plasma Exchange and Plasma Perfusion on Patients with Severe Hepatitis Awaiting Orthotopic Liver Transplantation

To determine if plasma exchange combined with plasma perfusion is a reliable and effective temporary liver support treatment for patients on the waiting list for OLT, we tested this method in 5 patients with end-stage and 3 patients with middle-stage severe hepatitis. Four patients were successfully controlled until a donor liver was available 4 to 13 days later. In contrast, the remaining 4 patients were not adequately controlled by this treatment and experienced aggravated disease progression, dying 3 to 8 days after treatment while still awaiting OLT. Of those 4 patients who received OLT, 2 patients died from multi-organ failure caused by hepatic failure, while the other 2 survived. These findings show that plasma exchange combined with plasma perfusion provides temporary support for some patients on the waiting list for OLT. The ability of patients to successfully bridge to OLT is closely associated with the degree of liver failure, complications, multi-organ failure, and the length of the waiting period for a donor liver.
Coping and Emotional Adjustment Following Traumatic Brain Injury

ObjectivesTo examine the association between coping style and emotional adjustment following traumatic brain injury. ParticipantsThirty three individuals who had sustained a traumatic brain injury (mean duration of posttraumatic amnesia = 32 days) between 1½ months and almost 7 years previously. Measures: Coping Scale for Adults, Hospital Anxiety and Depression Scale, Rosenberg Self-Esteem Scale, State-Trait Anger Expression Inventory, and the Sickness Impact Profile. ResultsApproximately 50% of the sample reported clinically significant levels of anxiety and depression. Coping characterized by avoidance, worry, wishful thinking, self-blame, and using drugs and alcohol was associated with higher levels of anxiety, depression, and psychosocial dysfunction and lower levels of self-esteem. Coping characterized by actively working on the problem and using humor and enjoyable activities to manage stress was associated with higher self-esteem. Lower premorbid intelligence (measured via the National Adult Reading Test) and greater self-awareness (measured via the Self-Awareness of Deficits Interview) were associated with an increased rate of maladaptive coping. ConclusionsThe strong association between the style of coping used to manage stress and emotional adjustment suggests the possibility that emotional adjustment might be improved by the facilitation of more adaptive coping styles. It is also possible that improving emotional adjustment may increase adaptive coping. The development and evaluation of interventions aimed at facilitating adaptive coping and decreasing emotional distress represent important and potentially fruitful contributions to enhancing long-term outcome following brain injury.
INTER SPACE LOCAL BINARY PATTERNS FOR IMAGE INDEXING AND RETRIEVAL

In this paper, inter space local binary pattern (ISLBP) algorithm for content based image retrieval (CBIR) is proposed. First the image is separated into red(R), green(G), and blue(B) color spaces, and these are used for inter space local binary patterns (ISLBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors by changing center pixels of one color space with other color space. Local binary pattern (LBP) extracts the information based on distribution of edges in an image. Finally, inter LBP histograms are constructed between the color spaces for image retrieval. The experimentation has been carried out for proving the worth of our algorithm. It is further mentioned that the databases considered for experiment viz. Corel 1000 and MIT VisTex databases. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP on RGB spaces separately.
A Coupled Hidden Conditional Random Field Model for Simultaneous Face Clustering and Naming in Videos

For face naming in TV series or movies, a typical way is using subtitles/script alignment to get the time stamps of the names, and tagging them to the faces. We study the problem of face naming in videos when subtitles are not available. To this end, we divide the problem into two tasks: face clustering which groups the faces depicting a certain person into a cluster, and name assignment which associates a name to each face. Each task is formulated as a structured prediction problem and modeled by a hidden conditional random field (HCRF) model. We argue that the two tasks are correlated problems whose outputs can provide prior knowledge of the target prediction for each other. The two HCRFs are coupled in a unified graphical model called coupled HCRF where the joint dependence of the cluster labels and face name association is naturally embedded in the correlation between the two HCRFs. We provide an effective algorithm to optimize the two HCRFs iteratively and the performance of the two tasks on real-world data set can be both improved.
X-BOT: A Protocol for Resilient Optimization of Unstructured Overlay Networks

Gossip, or epidemic, protocols have emerged as a highly scalable and resilient approach to implement several application level services such as reliable multicast, data aggregation, publish-subscribe, among others. All these protocols organize nodes in an unstructured random overlay network. In many cases, it is interesting to bias the random overlay in order to optimize some efficiency criteria, for instance, to reduce the stretch of the overlay routing. In this paper, we propose X-BOT, a new protocol that allows to bias the topology of an unstructured gossip overlay network. X-BOT is completely decentralized and, unlike previous approaches, preserves several key properties of the original (nonbiased) overlay (most notably, the node degree and consequently, the overlay connectivity). Experimental results show that X-BOT can generate more efficient overlays than previous approaches independently of the underlying physical network topology.
A reversible data hiding method for encrypted images

Since several years, the protection of multimedia data is becoming very important. The protection of this multimedia data can be done with encryption or data hiding algorithms. To decrease the transmission time, the data compression is necessary. Since few years, a new problem is trying to combine in a single step, compression, encryption and data hiding. So far, few solutions have been proposed to combine image encryption and compression for example. Nowadays, a new challenge consists to embed data in encrypted images. Since the entropy of encrypted image is maximal, the embedding step, considered like noise, is not possible by using standard data hiding algorithms. A new idea is to apply reversible data hiding algorithms on encrypted images by wishing to remove the embedded data before the image decryption. Recent reversible data hiding methods have been proposed with high capacity, but these methods are not applicable on encrypted images. In this paper we propose an analysis of the local standard deviation of the marked encrypted images in order to remove the embedded data during the decryption step. We have applied our method on various images, and we show and analyze the obtained results.
Face recognition: a review and comparison of HMM, PCA, ICA and neural networks

This paper describes the review-based comparison and implementation of face recognition. The implementation results described use principal component analysis (PCA) as a preprocessing step. Different authors have used PCA for reducing the dimensions of data. In this paper we use PCA as a preprocessor of ICA (independent component analysis). The accuracy and efficiency of the system depend upon the situation where the system is to be used.
Garbage Collection Technique using Erasure Interval for NAND Flash Memory-based Storage Systems

Recently, many storage systems use SSD based on NAND flash memory, which has many advantages such as low power, low access latency and high reliability. However, NAND flash memory has disadvantages such as erase-beforeprogram, limited P/E cycle, and unbalanced operation latency, compared to conventional magnetic disks. To solve these problems, many works mainly adopt FTL with garbage collection in NAND flash memory systems. However, previous garbage collection techniques are sensitive to the write pattern. In this paper, we propose a garbage collection technique based on the erasure interval, which is called EIGC (Erasure Interval-based Garbage Collection). EIGC is insensitive to the write pattern, compared to other techniques. The proposed technique prolonged the system lifetime about 13% and it reduced the garbage collection overhead about 42.4%, on average. Moreover, our technique reduced the standard deviation about 22.3% on average, compared to other techniques.
Improving the Parameterization of Approximate Subdivision Surfaces

We provide a method for improving the parameterization of patching schemes that approximate Catmull‐Clark subdivision surfaces, such that the new parameterization conforms better to that of the original subdivision surface. We create this reparameterization in real‐time using a method that only depends on the topology of the surface and is independent of the surface's geometry. Our method can handle patches with more than one extraordinary vertex and avoids the combinatorial increase in both complexity and storage associated with multiple extraordinary vertices. Moreover, the reparameterization function is easy to implement and fast.
Optimizing a discourse structuring component for utterance generation in human-computer dialogue

In this paper we describe a series of optimizations brought to a discourse structuring module for answer generation in dialogue systems. Starting from a baseline rhetorical structure updating algorithm, based on a first-order logic simulation of SDRT (“Segmented Discourse Representation Theory”), several improved versions are obtained, applying a series of pragmatically-driven, psychologically-motivated or purely computational optimizations. These optimizations stem from a reduction in the complexity of the baseline algorithm, as well as from a better conformance of the rhetorical structures obtained to linguistic predictions.
Alleviating Quite Quitting through Employee Value Proposition and the Moderating Role of Internal Communication

The workplace experienced a transformative shift in 2022 with the emergence of "quiet quitting," where employees disengage silently due to burnout and dissatisfaction. This phenomenon, distinct from formal resignations, highlights a decline in enthusiasm and commitment. Over 50% of Indian workers currently face burnout, emphasizing the need for organizations to address underlying causes. This study explores the intricate connections between Employee Value Proposition (EVP), Expectancy Theory, Psychological Ownership, Internal Communication, and Engagement. Effective communication is crucial, with research showing a 96% reduction in quiet resignations when leaders communicate well. The changing post-COVID landscape underscores the need to reassess EVP requirements, placing emphasis on flexibility, mental health support, and digital skill development.
Reasoning with large numbers of individuals moves on: extending the instance store

The Semantic Web [2] aims at enabling Web resources to be accessible to automated processes by adding “semantic annotations”—metadata (data about data) that describes their content. It is envisaged that the semantics in semantic annotations will be given by ontologies [8], which will provide a source of precisely defined terms (vocabularies) that are amenable to automated reasoning. A standard for expressing ontologies in the Semantic Web has already emerged: the ontology language OWL [4], which recently became a W3C proposed recommendation. One of the main features of OWL is that there is a direct correspondence between (two of the three “species” of) OWL and Description Logics (DLs) [12]. This means that reasoning procedures from DLs can be used in order to infer useful facts from ontology based annotations in OWL. In particular, since annotations are usually defined as individual instances of ontology classes, it is reasonable then to use ABox reasoning (the DL term for reasoning about individuals) to reason about annotations [3]. However, developing a practical ABox reasoner for such annotations is difficult. This difficulty arises not only from the computational complexity of ABox reasoning, but also from the fact that the number of annotations might be extremely large. On the one hand, the task of reasoning with large amounts of individuals is difficult even for the state-of-art optimised ABox reasoner RACER [9]. On the other hand, efficient management of very large volumes of data is well known to be a stronghold of relational databases. The approach of combining relational databases with Description Logics to deal with large amounts of data was, therefore, proposed in [11] which we call an Instance Store. The Instance Store provides an infrastructure for reasoning with large numbers of individuals. It combines a DL reasoner with a database in order to provide large scale storage of instance data, and sound and complete answers to instance retrieval queries for arbitrary query concepts. However, in order to simplify the integrated architecture, and to provide acceptable query answering performance, the current Instance Store only supports ABox axioms asserting that a given individual is an instance of a given (possibly complex) concept (e.g., John is an instance of the class of persons having at least one female child); but it forbids axiom assertions involving role relationships between pairs of individuals (e.g., an assertion that Mary is a child of John). Certainly, the idea of the Instance Store is not new, but, to the best of our knowledge, it is the first implementation of a general purposed role-free1 DL reasoner over individuals that is sound and complete, has reasonable response times. This claim is supported by presenting a variety of empirical test results [11] contrasting the Instance Store with the other existing techniques such as RACER.
Fluid mechanical consequences of pendular activity, segmentation and pyloric outflow in the proximal duodenum of the rat and the guinea pig

We conducted numerical experiments to study the influence of non-propagating longitudinal and circular contractions, i.e. pendular activity and segmentation, respectively, on flow and mixing in the proximal duodenum. A lattice-Boltzmann numerical method was developed to simulate the fluid mechanical consequences for each of 22 randomly selected sequences of high-definition video of real longitudinal and radial contractile activity in the isolated proximal duodenum of the rat and guinea pig. During pendular activity in the rat duodenum, the flow was characterized by regions of high shear rate. Mixing was so governed by shearing deformation of the fluid that increased the interface between adjacent domains and accelerated their inter-diffusion (for diffusion coefficients approx. less than 10−8 m² s−1). When pendular activity was associated with a slow gastric outflow characteristic of post-prandial period, the dispersion was also improved, especially near the walls. Mixing was not promoted by isolated segmentative contractions in the guinea pig duodenum and not notably influenced by pylorus outflow. We concluded that pendular activity generates mixing of viscous fluids ‘in situ’ and accelerates the diffusive mass transfer, whereas segmentation may be more important in mixing particulate suspensions with high solid volume ratios.
Keystroke Dynamics for User Authentication and Identification by using Typing Rhythm

In this era computer security is an important issue now a days because these are used everywhere to store & process the sensitive data. Specially those used in e-banking, e-commerce, virtual offices, e-learning, distributed, computing & various services over the internet. Using Keystroke dynamics authentication technology can be secured by password from various attacks. This technique is based on human behavior to type their password. Here analysis is done using human behavior with their typing pattern. As keystroke dynamics does not require any hardware, no extra hardware is used. Only software based technology is required for password protection. The result provides emphasis with pleasure security that growing in demand in web-based application.
A thermodynamic climatology of the disturbed stratospheric polar vortex

A climatology of polar vortex disturbances in the Northern Hemisphere winter stratosphere is constructed from MERRA2 Reanalysis data for the winter seasons of 1981–2017. Sixty disturbances (splits or displacements) of the polar vortex are identified during the 37 winter seasons using geometric moments of stratospheric potential vorticity. The likelihood of a disturbed day is negatively correlated with the stratospheric quasi‐biennial oscillation (positively correlated with its easterly phase). It is also, surprisingly, negatively correlated with the presence of a stratospheric Aleutian anticyclone (the Aleutian high). The position of the polar vortex during each disturbance event is averaged to generate an area‐averaging filter that is applied to thermodynamic diagnostic quantities in the air column enclosed by the polar vortex. This diagnosis reveals that the location of the disturbed polar vortex experiences, on average, cooling driven by horizontal temperature advection in the lower and middle stratosphere prior to the onset of the disturbance, along with significant residual (likely adiabatic) cooling in the troposphere in the weeks surrounding the onset. How these thermodynamic signatures associated with a disturbed polar vortex relate to the Aleutian high and the quasi‐biennial oscillation is also explored.
Comparison of the Mantel test and alternative approaches for detecting complex multivariate relationships in the spatial analysis of genetic data

The Mantel test is widely used to test the linear or monotonic independence of the elements in two distance matrices. It is one of the few appropriate tests when the hypothesis under study can only be formulated in terms of distances; this is often the case with genetic data. In particular, the Mantel test has been widely used to test for spatial relationship between genetic data and spatial layout of the sampling locations. We describe the domain of application of the Mantel test and derived forms. Formula development demonstrates that the sum‐of‐squares (SS) partitioned in Mantel tests and regression on distance matrices differs from the SS partitioned in linear correlation, regression and canonical analysis. Numerical simulations show that in tests of significance of the relationship between simple variables and multivariate data tables, the power of linear correlation, regression and canonical analysis is far greater than that of the Mantel test and derived forms, meaning that the former methods are much more likely than the latter to detect a relationship when one is present in the data. Examples of difference in power are given for the detection of spatial gradients. Furthermore, the Mantel test does not correctly estimate the proportion of the original data variation explained by spatial structures. The Mantel test should not be used as a general method for the investigation of linear relationships or spatial structures in univariate or multivariate data. Its use should be restricted to tests of hypotheses that can only be formulated in terms of distances.
Performance of the shifted Rayleigh filter in single-sensor bearings-only tracking

The problem of single-sensor bearings-only tracking continues to present challenges to tracking algorithms, particularly in certain difficult scenarios such as ones with high bearing rates. In such scenarios, the performance of the recently introduced shifted Rayleigh filter (SRF) is compared with that of other techniques such as extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle filter (PF). The results are also compared with the theoretical Cramer-Rao Lower Bound (CRLB). The SRF is a moment matching algorithm, and its key feature is that it generates the exact conditional distribution of target motion, given normal approximation to the prior. Simulations show that the SRF is superior to other moment matching algorithms such as EKF and UKF and is able to achieve comparable performance to PF while being orders of magnitude faster.