Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Physical Assistance Need Using a Musculoskeletal Model

Technologies that provide physical assistance during tasks are often required to provide assistance specific to the task and person performing it. An example is robotic rehabilitation in which the assistance-as-needed (AAN) paradigm aims to provide operators with the minimum assistance required to perform the task. Current approaches use empirical performance-based methods which require repeated observation of the specific task before an estimate of the needed assistance can be determined. In this paper, we present a new approach utilizing a musculoskeletal model (MM) of the upper limb to estimate the operator's assistance needs with respect to physical tasks. With capabilities of the operator defined at the muscular level of the MM, an optimization model is used to estimate the operator's strength capability. Strength required to perform a task is calculated using a task model. The difference or gap between the operator's strength capability and the strength required to execute a task forms the basis for the new AAN paradigm. We show how this approach estimates the effects of limb pose, load direction, and muscle impairments on a person's ability to perform tasks.
Comparative Analysis of Wollastonite‐Diopside Glass‐Ceramic Structures Fabricated via Stereo‐Lithography

One key feature of digital light processing consists of the high flexibility in the design of highly porous reticulated scaffolds. In the present paper, the authors report recent experiences concerning two glasses, both converted into wollastonite‐diopside (CaSiO3–CaMgSi2O6) glass‐ceramics by viscous flow sintering of fine powders (<45 μm) with concurrent crystallization. Glass particles are homogeneously dispersed in a photosensitive polymer, selectively hardened, layer‐by‐layer, by exposure to visible light, forming diamond cell lattices. The printing accuracy is slightly influenced by the glass chemistry, whereas the shape maintenance, after firing at 1100 °C, is observed for both compositions. The newly developed scaffolds are compared to other glass‐ceramic scaffolds, previously developed on the basis of the starting glass: the adoption of a new design does not determine any substantial degradation of mechanical properties.
CONCURRENCY AND COMPUTATION : PRACTICE AND EXPERIENCE Concurrency Computat

This paper studies how to detect anomalies in a distributed manner by using wireless sensor networks (WSNs). We focus on a medical context, where the existing works generally provide large environments to monitor patients using sensors as simple transducers. Those devices forward sensed health parameters to a main base station. This station collects received data and may perform some computations. In this paper, we perform some distributed tasks on the sensors. We propose a distributed algorithm, which allows to raise alarms under some initial rules to alert efficiently medical staff in case of critical situations without needless warnings. Each mote monitors a parameter. When this parameter reaches an abnormal value, the mote communicates with other motes in order to check if it is a ‘local’ anomaly or if the patient is in an abnormal situation. In such cases an alarm is raised. We implemented our algorithm over a network of micaZ sensors running under TinyOS. The obtained results show promising perspectives. Copyright © 2010 John Wiley & Sons, Ltd.
CD4 Ligation on Human Blood Monocytes Triggers Macrophage Differentiation and Enhances HIV Infection

ABSTRACT A unique aspect of human monocytes, compared to monocytes from many other species, is that they express the CD4 molecule. However, the role of the CD4 molecule in human monocyte development and function is not known. We determined that the activation of CD4 via interaction with major histocompatibility complex class II (MHC-II) triggers cytokine expression and the differentiation of human monocytes into functional mature macrophages. Importantly, we determined that CD4 activation induces intracellular signaling in monocytes and that inhibition of the MAPK and Src family kinase pathways blocked the ability of CD4 ligation to trigger macrophage differentiation. We observed that ligation of CD4 by MHC-II on activated endothelial cells induced CD4-mediated macrophage differentiation of blood monocytes. Finally, CD4 ligation by MHC-II increases the susceptibility of blood-derived monocytes to HIV binding and subsequent infection. Altogether, our studies have identified a novel function for the CD4 molecule on peripheral monocytes and suggest that a unique set of events that lead to innate immune activation differ between humans and mice. Further, these events can have effects on HIV infection and persistence in the macrophage compartment. IMPORTANCE The CD4 molecule, as the primary receptor for HIV, plays an important role in HIV pathogenesis. There are many cell types that express CD4 other than the primary HIV target, the CD4+ T cell. Other than allowing HIV infection, the role of the CD4 molecule on human monocytes or macrophages is not known. We were interested in determining the role of CD4 in human monocyte/macrophage development and function and the potential effects of this on HIV infection. We identified a role for the CD4 molecule in triggering the activation and development of a monocyte into a macrophage following its ligation. Activation of the monocyte through the CD4 molecule in this manner increases the ability of monocytes to bind to and become infected with HIV. Our studies have identified a novel function for the CD4 molecule on peripheral monocytes in triggering macrophage development that has direct consequences for HIV infection.
Locality-constrained group sparse coding regularized NMR for robust face recognition

Recently, nuclear norm based matrix regression (NMR) for classification has been proposed to characterize the whole structure of the error image. However, NMR ignores both the label information and the group structure of training samples. This paper presents a novel yet effective coding scheme called locality-constrained group sparse coding regularized NMR (LGNMR) which not only overcomes these limitations but also utilizes the similarities between test samples and training samples. We adopt the inexact augmented lagrange multiplier (IALM) method to solve the proposed model efficiently. Experiments on both Extended Yale B database and AR database have shown that the proposed method outperforms the state-of-the-art regression based classification methods.
Influence of deep cryogenic treatment on hardness and toughness of En31 steel

ABSTRACT The influence of deep cryogenic treatment on hardness and toughness of En 31 steel is discussed in this paper. En 31 steel is a high carbon steel, which is highly demandable for industrial applications. The property enhancement of steel components will reduce the frequent failure of components. Deep cryogenic treatment enhances the mechanical properties of steel components to avoid frequent failures. Deep cryogenic treatment is a cooling treatment, which was done at −196°C for 24 hours and it converts retained austenite into martensite along with the precipitation of carbides. The results show that the hardness of En31 steel is increased due to deep cryogenic treatment when compared with the conventional heat treated steel. The toughness of En31 steel is also increased in deep cryogenically treated steel due to low temperature conditioning of marteniste along with the carbide precipitation.
Council on Library and Information Resources Preservation Science Survey an Overview of Recent Developments in Research on the Conservation of Selected Analog Library and Archival Materials about the Authors Acknowledgments

ii Additional copies are available for $20 per copy. Orders must be placed online through CLIR's Web site. Henk J. Porck studied biochemistry at the Free University (VU) of Amsterdam. His Ph.D. thesis was a biochemical-genetic study at the VU Medical Faculty Department of Anthropogenetics. In 1983 he was appointed conservation scientist at the Koninklijke Bibliotheek (KB), the National Library of the Netherlands in The Hague. His research on paper preservation has included studies on deacidification, artificial aging, ink corrosion, and discoloration. In 1991 he became curator of the KB Paperhistorical Collection. His work in paper history has concentrated on the investigation of historical sources about the quality of nineteenth-century paper and on the classification and identification of handmade decorated papers. René Teygeler started his academic career with a study in sociology and social psychology at Utrecht University. In 1988 he was appointed teacher in bookbinding and graphic techniques at the Amsterdam School of Printing. He completed his education as a book and paper conservator at the State School for Conservators in 1993, and was appointed conservator at the Koninklijke Bibliotheek in The Hague. He continued his academic training in anthropology at Leiden and Utrecht University, and obtained an honorary degree in 1996. His research projects in preservation concentrated on the tropics in general and non-Western manuscripts in particular. He has studied writing materials from South and Southeast Asia, and was involved in a research project on Indonesian writing materials at Leiden University. In 1997 he started the consultancy firm Paper in Development and has since advised many projects in developing countries on preservation, papermaking, and book production. Preface Maintaining original physical objects—evidence or artifacts—for scholarly use in the future remains a primary responsibility of research libraries, archives , and museums, even as more and more information is created in digital form. Most of our recent history, the record of the nineteenth and twentieth centuries, is kept on film, magnetic tape, and paper. Today, great sums of money are being spent to digitize materials for broader access. In many cases, electronic availability has boosted demand for the original. Nevertheless, concern with preserving the original seems to have fallen out of fashion. In the United States in recent years, digitization projects and acquisition of electronic resources have received greater emphasis than has traditional preservation. We are concerned that new interests—both of local institutions and of funding agencies—may jeopardize preservation budgets. It …
Point-of-care Diagnostic Tools to Detect Circulating MicroRNAS as Biomarkers of Disease

MicroRNAs or miRNAs are a form of small non-coding RNAs (ncRNAs) of 19–22 nucleotides in length in their mature form. miRNAs are transcribed in the nucleus of all cells from large precursors, many of which have several kilobases in length. Originally identified as intracellular modulators of protein synthesis via posttranscriptional gene silencing, more recently it has been found that miRNAs can travel in extracellular human fluids inside specialized vesicles known as exosomes. We will be referring to this miRNAs as circulating microRNAs. More interestingly, the miRNA content inside exosomes changes during pathological events. In the present review we analyze the literature about circulating miRNAs and their possible use as biomarkers. Furthermore, we explore their future in point-of-care (POC) diagnostics and provide an example of a portable POC apparatus useful in the detection of circulating miRNAs.
Indirect model-based speech enhancement

Model-based speech enhancement methods, such as vector-Taylor series-based methods (VTS) [1, 2], share a common methodology: they estimate speech using the expected value of the clean speech given the noisy speech under a statistical model. We show that it may be better to use the expected value of the noise under the model and subtract it from the noisy observation to form an indirect estimate of the speech. Interestingly, for VTS, this methodology turns out to be related to the application of an SNR-dependent gain to the direct VTS speech estimate. In results obtained on an automotive noise task, this methodology produces an average improvement of 1.6 dB signal-to-noise ratio (SNR), relative to conventional methods.
Fuzzy Decomposition of Spatially Extended Objects

Modern database applications including computer-aided design, multimedia information systems, medical imaging, molecular biology, or geographical information systems impose new requirements on the effective and efficient management of spatial data. Particular problems arise from the need of high resolutions for large spatial objects. In this short paper, we sketch a new decompositioning approach based on clustering. We propose to describe a voxelized spatial object by a set of Gaussian distribution functions. Based on this decompositioning technique, we propose intersection queries which do not simply return a boolean value for each database object, but assign to each object a probability value indicating how likely an intersection is. The benefit of this approach compared to traditional approaches is that we do not any longer need an expensive refinement step for detecting whether objects intersect exactly on the fine-grained voxel sets.
Introducing a new parameter for quality control of proteome profiles: Consideration of commonly expressed proteins

Interpretation of proteome profiling experiments largely relies on comparative analyses. False‐positive identifications may cause fatal misinterpretation of data. On the other hand, proteome analysis may also suffer from false negatives, when proteins that are actually present are not detected. This circumstance may be as fatal as false‐positive identifications and was hardly considered until now. Appropriate positive controls would facilitate quality assessment of proteome profiling experiments. Based on cell biology knowledge, our aim was to generate a list of commonly expressed proteins, which may serve as positive control. Following a pragmatic experimental strategy, we compared the cytoplasmic fractions of four largely differing kinds of cells, which were human DCs, endothelial cells, fibroblasts and keratinocytes. Proteome profiling was performed by 2D‐PAGE in addition to shotgun analysis. By shotgun analysis, 665 proteins were identified, which occurred in each of the four cells types; 360 proteins of those were also detectable in the corresponding 2‐D gels. We consider these proteins as common proteins. All shotgun analysis data, including mass fragmentation spectra of the corresponding peptides, are accessible via the proteomics identification database (http://www.ebi.ac.uk/pride). As expected, most of the common proteins could be clearly assigned to at least one of the following functional categories: chaperones, cytoskeleton, energy metabolism, redox regulation, nucleic acid processing, protein turnover, membrane transport, protein synthesis and signaling. We suggest that the present data may prove helpful for data assessment, quality control and interpretation of a large variety of experiments based on proteome profiling.
Fabrication of deep-narrow microgrooves by micro-EDM using rotary dentate disc foil electrodes in emulsion

To accelerate the renewal of working fluid in machining gaps, this paper proposed using a dentate disc foil electrode (DDFE) for rotary micro electrical discharge machining (micro-EDM) to fabricate deep-narrow microgrooves. The DDFEs were machined from 30 µm thick Fe78Si9B13 amorphous alloy foils through wire electrical discharge machining. Under different process parameters, a series of experiments for fabricating microgrooves were performed by micro-EDM using the DDFE in emulsion. The effects of applied voltage, machining modes, clockwise rotation speed of the DDFE, and machining depth on the microgroove width were investigated in detail. Furthermore, the morphologies and dimensions of the microgrooves were characterized using a laser scanning confocal microscope and scanning electron microscope. The experimental results indicate that when the applied voltage U was 60 V, the DDFE clockwise rotation speed n was 3000 r min−1, the machining depth H was equal to the tooth height of 500 µm, the supply direction of the working fluid was right yet opposite to the the workpiece feed direction, a stable and fast micro-EDM process was achieved and a deep-narrow microgroove of width approximately 78 µm and aspect ratio 6.4 was obtained. With the optimized process parameters, array microgroove structures and column microstructures were fabricated successfully on #304 stainless steel workpieces.
MappSent: a Textual Mapping Approach for Question-to-Question Similarity

Since the advent of word embedding methods, the representation of longer pieces of texts such as sentences and paragraphs is gaining more and more interest, especially for textual similarity tasks. Mikolov et al. (2013) have demonstrated that words and phrases exhibit linear structures that allow to meaningfully combine words by an element-wise addition of their vector representations. Recently, Arora et al. (2017) have shown that removing the projections of the weighted average sum of word embedding vectors on their first principal components, outperforms sophisticated supervised methods including RNN’s and LSTM’s. Inspired by Mikolov et al. (2013) and Arora et al. (2017) findings and by a bilingual word mapping technique presented in Artetxe et al. (2016), we introduce MappSent, a novel approach for textual similarity. Based on a linear sentence embedding representation, its principle is to build a matrix that maps sentences in a joint-subspace where similar sets of sentences are pushed closer. We evaluate our approach on the SemEval 2016/2017 question-to-question similarity task and show that overall MappSent achieves competitive results and outperforms in most cases state-of-art methods.
Visual Model Feature Tracking For UAV Control

This paper explores the possibilities to use robust object tracking algorithms based on visual model features as generator of visual references for UAV control. A scale invariant feature transform (SIFT) algorithm is used for detecting the salient points at every processed image, then a projective transformation for evaluating the visual references is obtained using a version of the RANSAC algorithm, in which a series of matched key-points pairs that fulfill the transformation equations are selected, rejecting otherwise the corrupted data. The system has been tested using diverse image sequences showing its capability to track objects significantly changed in scale, position, rotation, generating at the same time velocity references to the UAV flight controller. The robustness our approach has also been validated using images taken from real flights showing noise and lighting distortions. The results presented are promising in order to be used as reference generator for the control system.
Towards a Framework that Allows Using a Cognitive Architecture to Personalize Recommendations in e-Commerce

In this paper we propose the use of a cognitive architecture as a mechanism to improve the level of personalization in a recommendation process. The main idea is to use the cognitive architecture as an advisor that lies between the user and a set of specialized recommenders. The cognitive architecture should know about the strengths and weaknesses of the recommenders, when they can be used and their degree of reliability given the amount of information available, among other things. With this information and the detailed knowledge about the user needs, it should be able to provide much more reliable and trustful recommendations by combining the strengths of each recommender given the specific context. The flexibility of a cognitive architecture in this place of the recommendation process will allow also to consider a much more sophisticated interaction with the user by allowing for example argumentation processes between the user and the system.
Ellipse fitting for interferometry. Part 2: experimental realization.

Extracting phase and amplitude information from the quadrature signals of an optical interferometer is an essential first step in any measurement. Where these signals are displayed as a Lissajous figure, the primary limitation to accuracy is determined by the goodness-of-fit to the ellipse, which is especially problematic for ellipses with high ellipticity. In a companion paper by Collett and Tee [J. Opt. Soc. Am. A31, 2573 (2014)10.1364/JOSAA.31. 002573], we described a novel, linear ellipse fitting method that outperforms all previously published algorithms. Here, we demonstrate the experimental application of this algorithm to several measurement problems of practical interest.
Service delivery models of cloud computing: security issues and open challenges

Cloud computing represents the most recent enterprise trend in information technology and refers to the virtualization of computing resources that are available on demand. Cloud computing saves cost and time for businesses. Moreover, this computing process reflects a radical technological revolution in how companies develop, deploy, and manage enterprise applications over the Internet. Virtualized cloud computing mainly offers cloud-computing delivery models such as software as a service, platform as a service, and infrastructure as a service. Security and privacy are presently considered critical factors in the adaptation of any cloud-service delivery model. Cloud computing leverages several technologies; in the process, this model can inherit potential security threats. Thus far, security issues in cloud computing have rarely been addressed at the service delivery level. Key security concerns include Web application security, network security, data security, integration, vulnerabilities in the virtualized environment, and physical security.
An optimization technique for protocol conformance test generation based on UIO sequences and rural Chinese postman tours

A method for generating test sequences for checking the conformance of a protocol implementation to its specification is described. A rural Chinese postman tour problem algorithm is used to determine a minimum-cost tour of the transition graph of a finite-state machine. It is shown that, when the unique input/output sequence (UIO) is used in place of the more cumbersome distinguishing sequence, both the controllability and observability problems of the protocol testing problem are addressed, providing an efficient method for computing a test sequence for protocol conformance testing. >
Accuracy assessment of time–concentration–effect models in predicting chronic lethality from acute toxicity data

Acute‐to‐chronic (ACE) models (accelerated life testing, ALT; linear regression analysis, LRA) are used to estimate chemical concentrations resulting in low levels of chronic mortality from acute toxicity data, thereby greatly increasing the inferential value of acute data. We applied the ACE models to test data from 72 chemicals and 14 aquatic species (131 acute and 97 chronic tests) and then compared the results with reported chronic no observed effect concentrations (NOEC) and lowest observed effect concentrations (LOEC), as determined by traditional analysis of variance techniques. Acute‐to‐chronic models produced highly accurate chronic lethality estimates compared with reported chronic NOEC and LOEC values. Lethality estimates fell within two times reported NOEC‐LOEC values 71% of the time and within five times 98% of the time. Therefore, ACE models are very appropriate for estimating chronic lethality from acute toxicity data when chronic data are absent and have high applicability in probability‐based hazard and risk assessments. Environ. Toxicol. Chem. 2011; 30:757–762. © 2011 SETAC