Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Texturing of Real Objects in an Augmented Reality System

The ability to physically change properties of real objects used in augmented reality (AR) applications is limited. Geometrical properties (shape, size) and appearance (color, texture) of a real object remain unchanged during a single application run. However, an AR system can be used to provide a virtual texture for the real object. The texture can be changed dynamically based on user interactions. The developed AR system includes two components, the "3D Table" and the "Texture Painter. " The 3D Table is a table where real objects are placed. The tabletop is used as a projection surface, making it possible to add a context to the real object. The Texture Painter makes it possible to paint on the real object, using a real brush and virtual ink (texture). ARToolkit markers are placed on the 3D Table tabletop to augment the environment with the virtual objects. Markers are either physical (printouts on the tabletop) or virtual (projections). The scene is recorded with a camera and the composed video is projected in real time. The projection shows a virtual environment, real objects painted with virtual ink, and virtual objects positioned where real or virtual ARToolkit markers are placed. The developed system is used in architectural design applications where, due to the different qualities of real architectural models and rendered architectural models, real models are still used. The system was tested at the Academy of Fine Arts in Vienna where it is used as a support tool for architecture students.
Annals of Clinical Microbiology and Antimicrobials Hospital-associated Methicillin-resistant Staphylococcus Aureus (ha-mrsa) in Italy

The aim of our study was to trace the dynamic changes of hospital-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) lineages in Italy, comparing the genotypic backgrounds of contemporary isolates over a period of 17 years, with those of a sample of early MRSA strains from 1980. In total, 301 non-repetitive MRSA clinical isolates, recovered from 19 Italian hospitals between 1990 and 2007 were selected and analyzed for their antibiotic resistance, typed by PFGE and SCCmec, grouped into clonal-types and further characterized using Multi Locus Sequence Typing (MLST). A sample of fifteen early MRSA strains from 1980 was also used for comparison.
Reduced TGF-ß1 Expression and its Target Genes in Human Insulinomas

Aiming to identify signalling pathways relevant for ss-cell growth we performed an explorative micro-array analysis comparing the gene expression profiles of three human insulinomas and one normal pancreatic islet preparation. This revealed an insulinoma-associated down-regulation of the transforming growth factor beta 1 (TGF-beta1) and its target genes. Comparative quantitative real-time PCR (qRT-PCR) including an expanded sample number of both insulinomas (n=9) and pancreatic islet preparations (n=4) confirmed the decreased TGF-beta1 expression and its target molecules (TGFBI, NNMT, RPN2) in insulinomas. Similarly, TGF-beta1 immunofluorescence analysis revealed reduced expression in insulinomas when compared to pancreatic islets. In contrast, TGFBR2 (transforming growth factor beta receptor II) was found up-regulated. However, the consistent down-regulation of the TGF-beta1 targets TGFBI (transforming growth factor, beta-induced), NNMT (nicotinamide N-methyltransferase), RPN2 (ribophorin II) indicates that the parallel up-regulation of TGFBR2 does not compensate for the only marginal TGF-beta1 expression levels in insulinomas. TGFBR2 expression was confirmed at the protein level in insulinomas. SMAD2/3 protein expression was found at higher levels in human pancreatic islets when compared with insulinomas by dual colour confocal microscopy. TGF-beta1 signalling is known to be involved in cell replication and is abrogated in ductal pancreatic tumours. The down-regulation of TGF-beta1 expression and its target molecules in insulinomas is a new aspect of this cytokine. Our data underline parallels in endocrine and exocrine pancreatic tumour development, which may implicate common progenitor cells.
Facial Expression Recognition Using Deep Boltzmann Machine from Thermal Infrared Images

Facial expression recognition from thermal infrared images has attracted more and more attentions in recent years. However, the features adopted in current work are either temperature statistical parameters extracted from the facial regions of interest or several hand-crafted features that are commonly used in visible spectrum. Till now there is no image features specially defined for thermal infrared images. In this paper, we are the first to propose using the Deep Boltzmann Machine to learn thermal features for expression recognition from thermal long wavelength infrared images. First, the face are located and normalized from the thermal infrared images. Then, a Deep Boltzmann Machine model composed of two layers is proposed. The parameters of the Deep Boltzmann Machine model are further fine-tuned for facial expression recognition after pre-training of feature learning. Comparison experimental results on the NVIE database demonstrate that our approach outperforms other approaches using temperature statistic features or hand-crafted features borrowed from visible domain. The learned features from the forehead, mouth, and cheek are more reliable for discriminating disgust, fear, and happiness compared with other facial areas.
Performance Analysis for Downlink Relaying Aided Non-Orthogonal Multiple Access Networks With Imperfect CSI Over Nakagami- ${m}$ Fading

Non-orthogonal multiple access (NOMA) has been conceived as a breakthrough technology for the fifth generation (5G) wireless networks. With imperfect channel state information (ICSI) taken into account, we study an NOMA-based downlink amplify-and-forward (AF) relaying network under Nakagami- ${m}$ fading in this paper. First, we investigate the system outage behavior, and close-form expressions for the exact and tight lower bounds of the outage probability are attained, respectively. By further evaluating the outage probability at the high SNR region, it is observed that an error floor exists in the outage probability due to the presence of ICSI. Finally, numerical results are presented to demonstrate the validity of our analysis and show the advantages of NOMA over conventional orthogonal multiple access. Moreover, simulation results verify that the optimal relay location for NOMA should be close to the source node.
Maximum Entropy Tiered Tagging

Data sparseness in tagging highly inflectional languages with large tagsets and scarce training resources is a problem that cannot be addressed using only common tagging techniques. Tiered tagging is a two-stage technique that uses for tagging a smaller ”hidden” tagset and, in the second phase, recovers the original tagset using a lexicon and a set of hand-written rules. The recovering is possible only for the words contained in the lexicon. The paper describes an experiment that shows how the maximum entropy framework can be used for tiered tagging without a hand-written set of recovery rules and which works also for unknown words.
Introduction to the Special Issue: Cognitive-Behavioral Interventions with Students with EBD

Significant progress has been made in developing models of social information processing, and cognitive-behavioral processes and related interventions. While there has been limited attention to cognitive-behavioral modification (CBM) in the special education literature, the majority of the contributions have come from the fields of school, clinical, and cognitive psychology. Despite well-documented needs of students with emotional/behavioral disorders (EBD) in areas of anger/aggression, anxiety, depression, and research demonstrating the efficacy of CBM interventions in these areas, these disciplines have operated somewhat independently of each other with respect to CBM. This special issue brings together leading scholars from special education and psychology in a collaborative examination of current knowledge on cognitive-behavioral interventions for students displaying specific challenging behaviors.
TLR7 and TLR8 agonists trigger different signaling pathways for human dendritic cell maturation

Dendritic cells (DCs) play an important role in bridging innate and adaptive immunity. These APCs have the ability to recognize specific molecular signatures of pathogens through TLRs. In particular, the intracellular TLR7 and TLR8, mediating the recognition of ssRNA by DCs, play a major role in the immune response during viral infection. Although differences have been identified between TLR7 and TLR8, in terms of cellular expression and functions, the signaling pathways that lead to DC maturation following TLR7 or TLR8 engagement are largely unknown. We compared the signaling pathways involved in human CD34‐DC maturation induced by agonists selective for TLR7 (imiquimod) or TLR8 (3M002). TLR7 and TLR8 activation up‐regulated CCR7, CD40, CD86, and CD83 expression and IL‐6 and IL‐12p40 production. However, only TLR8 activation led to IL‐12p70 production and il‐12p35 mRNA expression. We found that upon TLR7 and TLR8 activation, JNK and NF‐κB positively regulated the expression of CCR7, CD86, CD83, and CD40 and the production of IL‐6 and IL‐12p40. However, although p38MAPK participated in the up‐regulation of maturation markers in response to TLR7 activation, this kinase exerted an inhibitory effect on CD40 expression and IL‐12 production in TLR8‐stimulated DCs. We also showed that the Jak/STAT signaling pathway was involved in CD40 expression and cytokine production in TLR7‐stimulated DCs but negatively regulated CD83 expression and cytokine secretion in DCs activated through TLR8. This study showed that TLR7 and TLR8 activate similar signaling pathways that play different roles in DC maturation, depending on which TLR is triggered.
Evaluation of Leptospiral Recombinant Antigens MPL17 and MPL21 for Serological Diagnosis of Leptospirosis by Enzyme-Linked Immunosorbent Assays

ABSTRACT Leptospirosis is a zoonosis of multisystem involvement caused by pathogenic strains of the genus Leptospira. In the last few years, intensive studies aimed at the development of a vaccine have provided important knowledge about the nature of the immunological mechanisms of the host. The purpose of this study was to analyze the immune responses to two recombinant proteins, MPL17 and MPL21 (encoded by the genes LIC10765 and LIC13131, respectively) of Leptospira interrogans serovar Copenhageni in individuals during infection. The recombinant proteins were expressed in Escherichia coli as six-His tag fusion proteins and were purified from the soluble bacterial fraction by affinity chromatography with Ni2+-charged resin. The recombinant proteins were used to evaluate their ability to bind to immunoglobulin G (IgG) (and IgG subclass) or IgM antibodies in serum samples from patients in the early and convalescent phases of leptospirosis (n = 52) by enzyme-linked immunosorbent assays. The prevalences of total IgG antibodies against MPL17 and MPL21 were 38.5% and 21.2%, respectively. The titers achieved with MPL17 were statistically significantly higher than those obtained by the reference microscopic agglutination test. The specificity of the assay was estimated to be 95.5% for MPL17 and 80.6% for MPL21 when serum samples from individuals with unrelated febrile diseases and control healthy donors were tested. The proteins are conserved among Leptospira strains that cause human and animal diseases. MPL17 and MPL21 are most likely new surface proteins of leptospires, as revealed by liquid-phase immunofluorescence assays with living organisms. Our results demonstrate that these recombinant proteins are highly immunogenic and, when they are used together, might be useful as a means of diagnosing leptospirosis.
A 684Mbps 57mW joint QR decomposition and MIMO processor for 4×4 MIMO-OFDM systems

This paper presents a configurable MIMO detector with QR decomposition and channel interpolation for 4×4 MIMO-OFDM systems. QR decomposition (QRD) processor and MIMO detector are usually investigated independently in the literature; however, this methodology usually limits operating condition to only slow fading channel. Therefore, this study jointly designs a hardware architecture for QR decomposition and MIMO detection without interface memory buffer, and the channel interpolation is also performed at the same time. This QR-based MIMO detector is implemented in a 90nm CMOS process with 2.02mm2 core area. The chip consumes 56.8mW at 114MHz operating frequency with 1.0V supply and achieves 684Mbps throughput. The proposed chip, which performs one QRD and one MIMO detection for one OFDM symbol, is the first MIMO detector in the literature that supports real-time QR decomposition and MIMO detection for fast fading MIMO-OFDM systems.
Incremental minimum-violation control synthesis for robots interacting with external agents

We consider the problem of control strategy synthesis for robots that interact with external agents, together known as the environment. Both the robot and the environment are modeled as dynamical systems with differential constraints and take part in a nonzero-sum two-player differential game to fulfill their respective task specifications while satisfying a set of safety rules. They minimize a cost function that is representative of the level of unsafety with respect to these safety rules. Throughout, the problem is motivated by an autonomous car in an urban environment that interacts with other cars in situations such as navigating stop signs at road junctions and single-lane roads. Ideas behind sampling-based motion-planning algorithms are used to incrementally construct a finite Kripke structure abstraction of a continuous dynamical system. Model-checking techniques for safety rules expressed using Linear Temporal Logic (LTL) are then leveraged to propose an algorithm which synthesizes a control strategy for the two-player game. We analyze the algorithm to show that, with probability one, it converges to the Stackelberg equilibrium asymptotically. This algorithm is also demonstrated in a number of simulation experiments.
„Yes Wii Can“ : acceptance of the Nintendo Wii among seniors living in a retirement home

The current study tried to investigate the acceptance of the Nintendo Wii among inhabitants of retirement homes. A modification of the theory acceptance model (TAM) was used, where next to the impact of perceived usefulness and perceived ease of use also the impact of self-efficacy and personality on the acceptance of the Nintendo Wii was measured. Because of unforeseen problems by collecting the required data, it was not possible to operate the study in its original form. So instead the study focused on these problems. The main findings in analyzing these problems pointed in the direction of the question of how to administer a questionnaire the best way in a retirement home. A structured Interview seemed to be best suited when handling a questionnaire as a measurement tool. Also it turned out to be very difficult for the participants to rate their answers/statements accordingly to ratings scales. They got confused and most of them began to give the answer just with the „yes“ or „no“ extreme.
Comparison of admission random glucose, fasting glucose, and glycated hemoglobin in predicting the neurological outcome of acute ischemic stroke: a retrospective study

Background Hyperglycemia is a known predictor of negative outcomes in stroke. Several glycemic measures, including admission random glucose, fasting glucose, and glycated hemoglobin (HbA1c), have been associated with bad neurological outcomes in acute ischemic stroke, particularly in nondiabetic patients. However, the predictive power of these glycemic measures is yet to be investigated. Methods This retrospective study enrolled 484 patients with acute ischemic stroke from January 2009 to March 2013, and complete records of initial stroke severity, neurological outcomes at three months, and glycemic measures were evaluated. We examined the predictive power of admission random glucose, fasting glucose, and HbA1c for neurological outcomes in acute ischemic stroke. Furthermore, subgroup analyses of nondiabetic patients and patients with diabetes were performed separately. Results Receiver operating characteristic (ROC) analysis revealed that admission random glucose and fasting glucose were significant predictors of poor neurological outcomes, whereas HbA1c was not (areas under the ROC curve (AUCs): admission random glucose = 0.564, p = 0.026; fasting glucose = 0.598, p = 0.001; HbA1c = 0.510, p = 0.742). Subgroup analyses of nondiabetic patients and those with diabetes revealed that only fasting glucose predicts neurological outcomes in patients with diabetes, and the AUCs of these three glycemic measures did not differ between the two groups. A multivariate logistic regression analysis of the study patients indicated that only age, initial stroke severity, and fasting glucose were independent predictors of poor neurological outcomes, whereas admission random glucose and HbA1c were not (adjusted odds ratio: admission random glucose = 1.002, p = 0.228; fasting glucose = 1.005, p = 0.039; HbA1c = 1.160, p = 0.076). Furthermore, subgroup multivariate logistic regression analyses of nondiabetic patients and those with diabetes indicated that none of the three glycemic measures were associated with poor neurological outcomes. Discussion Fasting glucose is an independent predictor of poor neurological outcomes in patients with acute ischemic stroke and had greater predictive power than that of admission random glucose and HbA1c. The predictive power of glycemic measures for poor neurological outcomes did not differ significantly between the nondiabetic patients and those with diabetes.
Can Intra-Firm IT Skills Benefit Supply Chain Integration and Performance?

While inter-firm collaboration and integration remain critical for supply chain performance and information technology (IT) has been playing an increasingly important role in inter-firm cooperation, whether intra-firm IT skills can impact the inter-firm integration of IT has not been explored in the IS area. IT human capital involving soft skills and hard skills is a relatively unexplored topic, especially in the supply chain context. This study develops a model to examine whether intra-firm IT skills can have cross-boundary effects on supply chain collaboration and integration, which then can lead to greater supply chain performance. Accordingly, eight hypotheses were proposed and the model was tested with Partial Least Square technique based on the data collected from a survey of 250 manufacturing firms in Taiwan. The results largely support our model with seven hypotheses confirmed. By focusing on the supply chain context, this study thus extends and integrates the literatures on IT skills and supply chain management by showing the boundary-spanning effect of intra-firm capabilities on inter-firm collaboration, integration and performance. Implications of the results are provided and limitations and future research directions are discussed.
Image Retrieval based on combined features of image sub-blocks

In this paper we propose a new and efficient technique to retrieve images based on sum of the values of Local Histogram and GLCM (Gray Level Co-occurrence Matrix) texture of image sub-blocks to enhance the retrieval performance. The image is divided into sub blocks of equal size. Then the color and texture features of each sub-block are computed. Most of the image retrieval techniques used Histograms for indexing. Histograms describe global intensity distribution. They are very easy to compute and are insensitive to small changes in object translations and rotations. Our main focus is on separation of the image bins (histogram value divisions by frequency) followed by calculating the sum of values, and using them as image local features. At first, the histogram is calculated for an image sub-block. After that, it is subdivided into 16 equal bins and the sum of local values is calculated and stored. Similarly the texture features are extracted based on GLCM. The four statistic features of GLCM i.e. entropy, energy, inverse difference and contrast are used as texture features. These four features are computed in four directions (0 0 , 45 0 , 90 0 , and 135 0 ). A total of 16 texture values are computed per an image sub-block. An integrated matching scheme based on Most Similar Highest Priority (MSHP) principle is used to compare the query and target image. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image. This matrix is used for matching the images. Sum of the differences between each bin of the query and target image histogram is used as a distance measure for Local Histogram and Euclidean distance is adopted for texture features. Weighted combined distance is used in retrieving the images. The experimental results show that the proposed method has achieved highest retrieval performance.
Molecular Transformations as a Way of Finding and Exploiting Consistent Local QSAR

The idea of a "transformation", making a small change to a chemical structure, for instance removing or replacing a substituent, is familiar to chemists. We suggest two ways of representing a transformation in silico, as a substructure descriptor difference vector, and as the set of atoms remaining once a maximum common substructure is eliminated. Such transformations can be filtered sensibly, and it is easy to compare one transformation to another. These representations have two applications. First, we can use these methods to automatically organize and display sets of closely related compounds such that any consistent local QSAR in a data set can be easily seen, the T-ANALYZE application. Second, we can suggest to a chemist how to change a molecule "on hand" to a more active one based on local QSAR for that activity, the T-MORPH application.
Reconciling agricultural productivity and environmental integrity: A grand challenge for agriculture

Agriculture meets a major human need and both affects and depends on all other life support systems. Current trends point to continued human population growth and ever higher levels of consumption as the global economy expands. This will stress the capacity of agriculture to meet food needs without further sacrificing the environmental integrity of local landscapes and the global environment. Agriculture's main challenge for the coming decades will be to produce sufficient food and fiber for a growing global population at an acceptable environmental cost. This challenge requires an ecological approach to agriculture that is largely missing from current management and research portfolios. Crop and livestock production systems must be managed as ecosystems, with management decisions fully informed of environmental costs and benefits. Currently, too little is known about important ecological interactions in major agricultural systems and landscapes and about the economic value of the ecosystem services assoc.