Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-separable weighted median-cut quantization for images with sparse color histogram

Non-separable color reduction for color images is proposed in this paper. The proposed method befits high bit rate quantization in which, for example, a 24 bits per pixel (bpp) color image is quantized to an image with 18 bpp or more, while the conventional median-cut quantization gives huge quantization errors in such condition. This feature is useful in bit depth conversion for modern high bit depth images and is also useful in visually lossless compression. Moreover, by taking into account color histogram sparseness in which a few colors among huge possible colors are used, lossless quantization with a reasonable processing time is served by the proposed method, whereas the conventional vector quantization requires numerous processing time for lossless quantization.
Glycemic Thresholds for Diabetes-Specific Retinopathy

OBJECTIVE To re-evaluate the relationship between glycemia and diabetic retinopathy. RESEARCH DESIGN AND METHODS We conducted a data-pooling analysis of nine studies from five countries with 44,623 participants aged 20–79 years with gradable retinal photographs. The relationship between diabetes-specific retinopathy (defined as moderate or more severe retinopathy) and three glycemic measures (fasting plasma glucose [FPG; n = 41,411], 2-h post oral glucose load plasma glucose [2-h PG; n = 21,334], and A1C [n = 28,010]) was examined. RESULTS When diabetes-specific retinopathy was plotted against continuous glycemic measures, a curvilinear relationship was observed for FPG and A1C. Diabetes-specific retinopathy prevalence was low for FPG <6.0 mmol/l and A1C <6.0% but increased above these levels. Based on vigintile (20 groups with equal numbers) distributions, glycemic thresholds for diabetes-specific retinopathy were observed over the range of 6.4–6.8 mmol/l for FPG, 9.8–10.6 mmol/l for 2-h PG, and 6.3–6.7% for A1C. Thresholds for diabetes-specific retinopathy from receiver-operating characteristic curve analyses were 6.6 mmol/l for FPG, 13.0 mmol/l for 2-h PG, and 6.4% for A1C. CONCLUSIONS This study broadens the evidence based on diabetes diagnostic criteria. A narrow threshold range for diabetes-specific retinopathy was identified for FPG and A1C but not for 2-h PG. The combined analyses suggest that the current diabetes diagnostic level for FPG could be lowered to 6.5 mmol/l and that an A1C of 6.5% is a suitable alternative diagnostic criterion.
Conditional narrowing without conditions

We present a new evaluation strategy for functional logic programs described by weakly orthogonal conditional term rewriting systems. Our notion of weakly orthogonal conditional rewrite system extends a notion of Bergstra and Klop and covers a large part of programs defined by conditional equations. Our strategy combines the flexibility of logic programming (computation of solutions for logic variables) with efficient evaluation methods from functional programming. In particular, it is the first known narrowing strategy for this class of programs that evaluates ground terms deterministically. This is achieved by a transformation of conditional term rewriting systems (CTRS) into unconditional ones which is sound and complete w.r. t. the semantics of the original CTRS. We show that the transformation preserves weak orthogonality for the terms of interest. This property allows us to apply a relatively efficient evaluation strategy for weakly orthogonal unconditional term rewriting systems (parallel narrowing) on the transformed programs.
Swift: A Hybrid Digital-Analog Scheme for Low-Delay Transmission of Mobile Stereo Video

Efficient and robust wireless stereo video delivery is an enabling technology for various mobile 3D applications. Existing digital solutions have high source coding efficiency but are not robust to channel variations, while analog solutions have the opposite characteristics. In this paper, we design a novel hybrid digital-analog (HDA) solution to embrace the advantages of both solutions and avoid their drawbacks. Basically, in each pair of stereo frames, one frame is digitally encoded to ensure basic quality and the other is analogly processed to opportunistically utilize good channels for better quality. To improve the system efficiency, we design a zigzag coding structure such that both intra-view and inter-view correlations can be explored through prediction in the frames to be analogly coded. A reference selection mechanism is proposed to further improve the coding efficiency. In addition, we address the problem of optimal power and bandwidth allocation between digital and analog streams. We implement a system, named Swift, and perform extensive trace-driven evaluations based on a software-defined radio platform. We show that Swift outperforms an omniscient digital scheme under the same bandwidth and power constraints, or can have around 2x power saving in order to achieve comparable performance. Subjective quality assessment evidences that Swift provides significantly better visual quality than a straightforward HDA extension of SoftCast.
Carotid artery stents for blunt cerebrovascular injury: risks exceed benefits.

BACKGROUND Carotid stenting has been advocated in patients with grade III blunt carotid artery injuries (hereafter referred to as "blunt CAIs") because of the persistence of the pseudoaneurysm and concern for subsequent embolization or rupture. HYPOTHESIS Carotid stenting is safe and effective for blunt CAIs. DESIGN Analysis of a prospective database of all patients with blunt CAIs. SETTING A state-designated, level I, urban trauma center. PATIENTS AND METHODS In January 1, 1996, we initiated comprehensive screening for blunt CAIs with angiography based on injury patterns. Patients without contraindications receive anticoagulation therapy immediately for documented lesions. Patients with persistent pseudoaneurysms on a second angiography at 7 to 10 days after injury are candidates for stent placement. RESULTS During the study period (January 1, 1996, to May 1, 2004), 46 patients sustained blunt carotid pseudoaneurysms; 23 (50%) underwent carotid stent placement. There were 4 complications in patients undergoing carotid stent placement: 3 strokes and 1 subclavian dissection. Follow-up angiography was performed in 38 patients (18 patients with stents who received antithrombotic agents, 20 patients who received antithrombotic agents alone); 8 patients had poststent carotid occlusion despite having received concurrent anticoagulation therapy. Carotid occlusion rates were significantly different (45% in patients with stents vs 5% in those who received antithrombotic agents alone). In the patients not undergoing stent placement, the only complication was a middle cerebral artery stroke in a patient not treated with antithrombotic therapy. CONCLUSIONS Patients who have carotid stents placed for blunt carotid pseudoaneurysms have a 21% complication rate and a documented occlusion rate of 45%. In contrast, patients treated with antithrombotic agents alone had an occlusion rate of 5%; no asymptomatic patient treated with antithrombotic agents for their injury had a stroke. Antithrombotic therapy remains the recommended therapy for blunt CAIs, but the role of intraluminal stents remains to be defined.
Enhancing quality and accuracy of speech recognition system by using multimodal audio-visual speech signal

Most developments in speech-based automatic recognition have relied on acoustic speech as the sole input signal, disregarding its visual counterpart. However, recognition based on acoustic speech alone can be afflicted with deficiencies that prevent its use in many real-world applications, particularly under adverse conditions. This paper aims to build a connected-words audio visual speech recognition system (AV-ASR) for English language that uses both acoustic and visual speech information to improve the recognition performance. Mel frequency cepstral coefficients (MFCCs) have been used to extract the audio features from the speech-files. For the visual counterpart, the Discrete Cosine Transform (DCT) Coefficients have been used to extract the visual feature from the speaker's mouth region and Principle Component Analysis (PCA) have been used for dimensionality reduction purpose, These features are then concatenated with traditional audio ones, and the resulting features are used for training hidden Markov models (HMMs) parameters using word level acoustic models. The system has been developed using hidden Markov model toolkit (HTK) that uses hidden Markov models (HMMs) for recognition. The potential of the suggested approach is demonstrate by a preliminary experiment on the GRID sentence database one of the largest databases available for audio-visual recognition system, which contains continuous English voice commands for a small vocabulary task. The experimental results show that the proposed Audio Video Speech Recognizer (AV-ASR) system exhibits higher recognition rate in comparison to an audio-only recognizer as well as it indicates robust performance. An increase of success rate by 3.9% for the grammar based word recognition system overall speakers is achieved for speaker independent test and for speaker dependent, it changes from speaker to another between 7% and 1%. Also when test the system under noisy environment it improve the result.
Negative Stereotypical Portrayals of Muslims in Right‐Wing Populist Campaigns: Perceived Discrimination, Social Identity Threats, and Hostility Among Young Muslim Adults

Anti-Islamic sentiments have become central to right-wing populist mobilization in Western societies, which often results in negative portrayals of Muslims in political campaigns. Although these portrayals may have detrimental effects on minority members' identity formation and attitudes toward majority members, little is known about their effects on members of the depicted group. A lab experiment with 145 young Muslims reveals that right-wing populist ad exposure increases perceived discrimination, which in turn decreases individuals' self-esteem and national identification, and encourages hostility toward majority members. Religious identification, in contrast, is not affected by ad exposure. Implications of these findings for intergroup relations and democratic processes are discussed.
Detecting Changes in Ontologies via DAG Comparison

Ontologies are shared conceptualizations of a certain domain. As such domains may change, also changes in the ontologies have to be considered, as otherwise there is no way to state which knowledge was valid at an arbitrary point in time. Various ontology version management systems deal with this problem. But often, the differences between two versions of an ontology are not known, thus, it is not possible to incorporate changes into the versioning system. In this paper we present our graph based ontology change detection approach, an evaluation of the prototypic implementation and a comparison to existing change detection systems.
A New Robot Design to Passively Damp Flexible Robotic Arms

This paper presents a hardware configuration for a long reach robotic arm in which passive dampers eliminate unwanted oscillation. This paper derives and reduces the equations of motion for the proposed configuration; then develops a "realistic" design. Using a single degree of freedom approximation, the paper presents and experimentally verifies equations for the dominant natural frequency and damping ratio. The paper demonstrates that the equations are good predictors of dynamic response for a large set of robots. The design is verified via experiment.
Evolving Fuzzy Image Segmentation with Self-Configuration

Current image segmentation techniques usually require that the user tune several parameters in order to obtain maximum segmentation accuracy, a computationally inefficient approach, especially when a large number of images must be processed sequentially in daily practice. The use of evolving fuzzy systems for designing a method that automatically adjusts parameters to segment medical images according to the quality expectation of expert users has been proposed recently (Evolving fuzzy image segmentation EFIS). However, EFIS suffers from a few limitations when used in practice mainly due to some fixed parameters. For instance, EFIS depends on auto-detection of the object of interest for feature calculation, a task that is highly application-dependent. This shortcoming limits the applicability of EFIS, which was proposed with the ultimate goal of offering a generic but adjustable segmentation scheme. In this paper, a new version of EFIS is proposed to overcome these limitations. The new EFIS, called self-configuring EFIS (SC-EFIS), uses available training data to self-estimate the parameters that are fixed in EFIS. As well, the proposed SC-EFIS relies on a feature selection process that does not require auto-detection of an ROI. The proposed SC-EFIS was evaluated using the same segmentation algorithms and the same dataset as for EFIS. The results show that SC-EFIS can provide the same results as EFIS but with a higher level of automation.
The Problematics of Human Prototyping and Animation

Several ideas and experiments are presented for the creation and realistic animation of three‐dimensional scenes involving human beings conscious of their environment. The various approaches should allow the intelligent creation of human beings using prototypes and generate their animation based on mechanics, artificial intelligence and robotics. This paper discusses the problems involved in three major steps of the simulation of human beings: the creation of the human shapes, the motion of the human skeleton, and the deformation of the surfaces. Several examples are presented illustrating positional constraints, dynamics, behavioural animation and finite element theory.
CD4-Independent Infection of Astrocytes by Human Immunodeficiency Virus Type 1: Requirement for the Human Mannose Receptor

ABSTRACT Human immunodeficiency virus type 1 (HIV-1) infection occurs in the central nervous system and causes a variety of neurobehavioral and neuropathological disorders. Both microglia, the residential macrophages in the brain, and astrocytes are susceptible to HIV-1 infection. Unlike microglia that express and utilize CD4 and chemokine coreceptors CCR5 and CCR3 for HIV-1 infection, astrocytes fail to express CD4. Astrocytes express several chemokine coreceptors; however, the involvement of these receptors in astrocyte HIV-1 infection appears to be insignificant. In the present study using an expression cloning strategy, the cDNA for the human mannose receptor (hMR) was found to be essential for CD4-independent HIV-1 infectivity. Ectopic expression of functional hMR rendered U87.MG astrocytic cells susceptible to HIV-1 infection, whereas anti-hMR serum and hMR-specific siRNA blocked HIV-1 infection in human primary astrocytes. In agreement with these findings, hMR bound to HIV-1 virions via the abundant and highly mannosylated sugar moieties of HIV-1 envelope glycoprotein gp120 in a Ca2+-dependent fashion. Moreover, hMR-mediated HIV-1 infection was dependent upon endocytic trafficking as assessed by transmission electron microscopy, as well as inhibition of viral entry by endosomo- and lysosomotropic drugs. Taken together, these results demonstrate the direct involvement of hMR in HIV-1 infection of astrocytes and suggest that HIV-1 interaction with hMR plays an important role in HIV-1 neuropathogenesis.
Business process patterns and frameworks: Reusing knowledge in process innovation

Purpose – To develop a novel approach for encapsulating high level business knowledge and logic of a given application domain in patterns and frameworks, which can be reused and be applied to improve a process for a given business in the domain and to develop an application to support such process.Design/methodology/approach – Formal and explicit business process patterns (BPP) have been developed that synthesize best practices found in hundreds of real projects of process redesign. From these, software business objects (BO) frameworks that encapsulate business logic have been derived.Findings – Good characterization of the processes and associated decisions by means of formal BPP allows including complex generalized business decisions logic in BO frameworks. Such logic is built upon the best current knowledge of analytical methods, such as business intelligence, optimization and heuristics.Practical implications – This approach provides a very flexible way, based on reusable components, to develop soluti.
Highly Parallel Sparse Matrix-Matrix Multiplication

Generalized sparse matrix-matrix multiplication is a key primitive for many high performance graph algorithms as well as some linear solvers such as multigrid. We present the first parallel algorithms that achieve increasing speed ups for an unbounded number of processors. Our algorithms are based on two-dimensional block distribution of sparse matrices where serial sections use a novel hypersparse kernel for scalability. We give a state-of-the-art MPI implementation of one of our algorithms. Our experiments show scaling up to thousands of processors on a variety of test scenarios.
The Springfield Project service: evaluation of a Solihull Approach course for foster carers

Many young people in care have experienced trauma. The emotional and behavioural issues that often ensue, along with foster carers’ varying levels of confidence and skills, are cited as the main reasons for placement disruption. Placement breakdown can represent a further trauma for young people and is also highly costly for local authorities. The need for interventions to develop foster carers’ competence and confidence in understanding and managing foster children’s behaviour is therefore significant. The Solihull Approach (SA) promotes the parent and child relationship by emphasising the need for emotional containment and a reciprocal relationship so as to form a framework for thinking about, understanding and effectively managing behaviour. The ‘Solihull Approach course for foster carers: understanding your foster child’s behaviour’ is a 12-week programme tailored to the demands of this task. It has been run within the Springfield Project in Fife, Scotland for the past four years. In the reported study 83 participants completed evaluation forms. A thematic analysis of their replies revealed that the most important things learned were: taking a step back; understanding the effects of trauma; reciprocity; communication and play; containment (of my child); understanding my child; and the ability to offload when full up. The course helped participants to better understand their foster child by clarifying the nature of the relationship and their role, understanding the impact of the child’s early experiences and appreciating that she or he is not to blame. Participants took from the course: increased understanding; being part of the group; staying calm and thinking before they act; feeling more confident; and looking after themselves and seeking containment. Pre- and post-Child Behaviour Checklist (CBCL) questionnaires were collected from 34 carers with children in the six to 18 age group and 13 looking after children aged one-and-a-half to five years. Paired samples t-tests revealed no statistically significant difference in pre- and post-scores in either the six- to 18-year-olds (t(33) = 1.6, p = 0.114) or the one-and-a-half- to five-year-olds (t(12) = 2, p = 0.069). Possible reasons for this and its implications are explored. However, the identified qualitative themes suggest that the aims of the training are being met. There was a strong overall sense that foster carers found the course helpful and informative, suggesting that it could represent a valuable intervention for promoting placement security.
A Comparison of Teacher Quality in Math for Late Elementary and Middle School Students With and Without Disabilities

Students with disabilities (SWDs) perform below their peers in math on national and state assessments. The quality of teachers who provide these students with math instruction is an unexamined variable that could influence this low achievement. We used data from more than 1 million students to compare the quality of teachers assigned to teach math to fourth- through eighth-grade SWDs and students without disabilities, using multiple indicators of teacher quality. Overall, SWDs had access to teachers of similar quality as their peers, but grouping all disabilities masked heterogeneity. Students with learning disabilities were only 2 to 8 percentage points more likely than their peers to have teachers with special education certification. Based on our findings, the low math achievement of SWDs is unlikely to be the result of limited access to the same teacher quality as their peers without disabilities.
Automation of differential blood count

A technique for automating the differential count of blood is presented. The proposed system takes, as input, color images of stained peripheral blood smears and identifies the class of each of the white blood cells (WBC), in order to determine the count of cells in each class. The process involves segmentation, feature extraction and classification. WBC segmentation is a two-step process carried out on the HSV-equivalent of the image, using k-means clustering followed by the EM-algorithm. Features extracted from the segmented cytoplasm and nucleus, are motivated by the visual cues of shape, color and texture. Various classifiers have been explored on different combinations of feature sets. The results presented are based on trials conducted with normal cells. For training the classifiers, a library set of 50 patterns, with about 10 samples from each class, is used. The test data, disjoint from the training set, consists of 34 patterns, fairly represented by every class. The best classification accuracy of 97% is obtained using neural networks, followed by 94% using SVM.
Research Paper Series Globalisation and Labour Markets Programme International Fragmentation and Relative Wages in the Uk the Centre Acknowledges Financial Support from the Leverhulme Trust under Programme Grant F114/bf Acknowledgements Financial Support from the European Commission Fifth Framework 

While growing wage inequality is of ongoing concern in many developed countries, there still does not exist a consensus on the predominant source of this trend. Some argue that skill-biased technological change is responsible for the shift in the relative demand of skilled workers while others hold increased import competition from low-wage countries reducing employment for the unskilled responsible for the growing income divide within countries. This paper reexamines the trade-based explanation by focussing on international outsourcing. In a recent paper, Feenstra and Hanson (1996) estimate the effect of international outsourcing on wage inequality in the US. This paper extends the FH approach using more detailed definitions of import penetration and outsourcing as well as data for UK manufacturing industries for the period 1982-1996. The econometric results suggest that technical change and import penetration matter for wage inequality (although the effect of the latter depends crucially on whether or not estimations are weighted) while the role of outsourcing cannot be clearly determined.