Miracle-dz/UniFAR-FTUs huggingface dataset:
A coordination middleware for wireless sensor networks

Middleware development in the growing and promising field of sensor networks is a major challenge in order to facilitate the programmer task and bridge the gap between the applications and the hardware. This paper presents a new middleware for wireless sensor networks based on the Coordination paradigm. The middleware is thought to support both an operational setting based on a (hierarchical) architecture of sensor regions and a coordination model rested on tuple channels. Tuple channels are FIFO structures that allow one-to-many and many-to-one communication between region sensors and the region leader in a single-hop way. The main components of the middleware architecture are described.
Computational Reflection and CSCW Design

Designing computer systems to support collaborative work is hard. One of the major reasons for this is the requirement that such systems be flexible, able to adapt themselves to different users or groups, able to track changes in group behaviour over time, and able to function efficiently in different computational and infrastructural environments. For the designer of a toolkit for building CSCW applications, these problems are heightened, since a toolkit needs to be applicable to a range of applications, each of which require flexibility along these different dimensions. This paper proposes a toolkit based on the theories and techniques of computational reflection, which enable the implementation of malleable, open-ended systems with dynamic properties which are particularly applicable to collaborative systems design.
Osmotic Fragility Index and Stability of Human Erythrocytes in the Presence of Four Oral Antiretroviral Drugs

The relative stability of human erythrocyte membrane in the presence of four oral antiretroviral drugs was investigated in vitro. Blood collected by venipuncture from 60 confirmed healthy humans were used for the study. The osmotic fragility of the erythrocytes was determined by measuring the release of haemoglobin from blood added to tubes containing serially diluted phosphate buffered saline (PBS, pH 7.4). Results revealed that increase of mean corpuscular fragility was not significant (p>0.05) in the presence of nevirapine, lamivudine and abacavir sulfate, while, efavirenz cause a significant (p<0.05) increase from 0.49±0.01 to 0.53±0.04mg/100ml. The erythrocytes were stable at 0.2mg/ml of nevirapine; 0.6mg/ml efavirenz; and 0.2 and 0.4mg/ml lamivudine. Results show that all drugs have the capacity to increase the permeability of the erythrocyte membrane and can compromise the integrity of the erythrocyte.
Photosymbiotic giant clams are transformers of solar flux

‘Giant’ tridacnid clams have evolved a three-dimensional, spatially efficient, photodamage-preventing system for photosymbiosis. We discovered that the mantle tissue of giant clams, which harbours symbiotic nutrition-providing microalgae, contains a layer of iridescent cells called iridocytes that serve to distribute photosynthetically productive wavelengths by lateral and forward-scattering of light into the tissue while back-reflecting non-productive wavelengths with a Bragg mirror. The wavelength- and angle-dependent scattering from the iridocytes is geometrically coupled to the vertically pillared microalgae, resulting in an even re-distribution of the incoming light along the sides of the pillars, thus enabling photosynthesis deep in the tissue. There is a physical analogy between the evolved function of the clam system and an electric transformer, which changes energy flux per area in a system while conserving total energy. At incident light levels found on shallow coral reefs, this arrangement may allow algae within the clam system to both efficiently use all incident solar energy and avoid the photodamage and efficiency losses due to non-photochemical quenching that occur in the reef-building coral photosymbiosis. Both intra-tissue radiometry and multiscale optical modelling support our interpretation of the system's photophysics. This highly evolved ‘three-dimensional’ biophotonic system suggests a strategy for more efficient, damage-resistant photovoltaic materials and more spatially efficient solar production of algal biofuels, foods and chemicals.
LiXQuery: a formal foundation for XQuery research

XQuery is considered to become the standard query language for XML documents. However, the complete XQuery syntax and semantics seem too complicated for research and educational purposes. By defining a concise backwards compatible subset of XQuery with a complete formal description, we provide a practical foundation for XQuery research. We pay special attention to usability by supporting the most typical XQuery expressions.
Quantifying Sources and Types of Smartwatch Usage Sessions

We seek to quantify smartwatch use, and establish differences and similarities to smartphone use. Our analysis considers use traces from 307 users that include over 2.8 million notifications and 800,000 screen usage events, and we compare our findings to previous work that quantifies smartphone use. The results show that smartwatches are used more briefly and more frequently throughout the day, with half the sessions lasting less than 5 seconds. Interaction with notifications is similar across both types of devices, both in terms of response times and preferred application types. We also analyse the differences between our smartwatch dataset and a dataset aggregated from four previously conducted smartphone studies. The similarities and differences between smartwatch and smartphone use suggest effect on usage that go beyond differences in form factor.
A Methodology for Architecture Exploration of Heterogeneous Signal Processing Systems

We present a methodology for the exploration of signal processing architectures at the system level. The methodology, named SPADE, provides a means to quickly build models of architectures at an abstract level, to easily map applications, modeled as Kahn Process Networks, onto these architecture models, and to analyze the performance of the resulting system by simulation. The methodology distinguishes between applications and architectures, and uses a trace-driven simulation technique for co-simulation of application models and architecture models. As a consequence, architecture models need not be functionally complete to be used for performance analysis while data dependent behavior is still handled correctly. We have used the methodology for the exploration of architectures and mappings of an MPEG-2 video decoder application.
Utilisation of plasma centrifuges for life support systems on Mars

In this paper the possibility of utilising a plasma centrifuge for oxygen generation in outer space is discussed. It is proposed that a plasma centrifuge can not only create oxygen for human consumption very efficiently but is also able to produce useful by-products. Special emphasis is given to life support systems working in the atmosphere of Mars, where oxygen and carbon raw materials can be obtained directly from the atmosphere. The system under consideration in this work is a plasma centrifuge with axial circulation that contains a fully ionised plasma. Under these conditions the carbon dioxide from the Mars atmosphere will be entirely dissociated. Thus, the atomic oxygen and carbon can easily be separated.
CircStat: AMATLABToolbox for Circular Statistics

Directional data is ubiquitious in science. Due to its circular nature such data cannot be analyzed with commonly used statistical techniques. Despite the rapid development of specialized methods for directional statistics over the last fifty years, there is only little software available that makes such methods easy to use for practioners. Most importantly, one of the most commonly used programming languages in biosciences, MATLAB, is currently not supporting directional statistics. To remedy this situation, we have implemented the CircStat toolbox for MATLAB which provides methods for the descriptive and inferential statistical analysis of directional data. We cover the statistical background of the available methods and describe how to apply them to data. Finally, we analyze a dataset from neurophysiology to demonstrate the capabilities of the CircStat toolbox.
Subarachnoid-pleural fistula after resection of thoracic tumors.

OBJECT Little has been written about the appropriate diagnosis, investigation, and management of subarachnoid-pleural fistula (SPF). The authors report a series of patients with SPF that developed after resection of spinal tumor and discuss the diagnosis and treatment of this entity. METHODS Between 1993 and 2002, nine patients with SPF observed after spinal surgery at the M. D. Anderson Cancer Center were prospectively followed. In all patients the tumors were located in the thoracic region, and the most common entity was vertebral body metastasis (six cases), with renal cell carcinoma being the most common form of the disease (three cases). All but one patient underwent surgery via a transthoracic approach; in only one patient an intradural approach was performed. The most common presentation was overt cerebrospinal fluid (CSF) leakage, manifesting as chest tube drainage (four cases) or as leakage through the wound (one case). A definitive diagnosis of SPF was established in four patients, with evidence of extraspinal leakage on an 111In-radionuclide CSF study. Although all patients initially underwent a trial of lumbar CSF drainage, all but one required open repair, including creation of intercostal muscle (three cases) and omental (one case) flaps. CONCLUSIONS After spinal surgery in which the thorax is entered, a diagnosis of SPF should be considered in any patient with abnormal chest tube output, persistent pleural effusion, or clinical evidence of intracranial hypotension. The diagnosis should be confirmed by performing a radionuclide-labeled CSF study. Definitive open repair is required in most cases and preferentially consists of a vascularized tissue graft, which is most easily obtained from an intercostal muscle flap.
How reliable is repeated testing for hemispatial neglect? Implications for clinical follow-up and treatment trials

Patients with hemispatial neglect following right hemisphere brain damage fail to spontaneously orient towards or respond to contralesional stimuli.1 The diagnosis and longitudinal assessment of the syndrome is not always straightforward. This is mainly due to two reasons: the heterogeneity of the syndrome and inter-individual differences in the time course of recovery from the disorder. The neglect syndrome affects various cognitive components across patients, and one patient may show neglect on certain tasks but not on others.1 ,2 Because there is no single test able to detect neglect in all patients, a battery of several paper-and-pencil tests is usually required.1 ,3 However, little is known about their use as a tool for longitudinal assessments. This is of high clinical importance as repeat assessments are necessary to monitor changes in neglect severity related to spontaneous remission or a specific treatment. If a test per se is not ‘stable’, the variation in test results over repeated sessions may simply reflect low test–retest reliability and not the actual change of the underlying disorder. We therefore investigated the test–retest reliability of three …
A Concept Paper on Smart River Monitoring System for Sustainability in River

River is a major source of water in Malaysia and one of the major threats to its sustainability is pollution. The existing methods for monitoring of water quality in rivers are manual monitoring and continuous monitoring. These methods are costly and less efficient. Hence, we propose a smart river monitoring system (SRMS) that uses unmanned aerial vehicles (UAVs) or drones and low power wide area (LPWA) communication technology. The Internet of Things (IoT) and data analytic are promising techniques which provide real-time monitoring and enhances efficiency. However, due to the span of river that needs to be monitored, conventional communication technology such as Wi-Fi, Zigbee, Bluetooth are not suitable. Hence, there is the need for LPWA communication technology. We discuss the application of LPWA and UAV for sustainability of rivers in Malaysia as a case study. Preliminary results show that the use of UAV will increase the efficiency of measuring the water quality parameters compared to manual monitoring method. Also, real-time monitoring enables us to study the changes in water quality. Finally, we provide future direction in the application of UAV and LPWA for sustainability in river.
A Bayesian Method for Evaluating and Discovering Disease Loci Associations

Background A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations.
Regional-scale rice-yield estimation using stacked auto-encoder with climatic and MODIS data: a case study of South Korea

ABSTRACT In South Korea, rice is the most important grain crop that it is crucial to develop yield estimation model for supporting sustainable agriculture and national food security. The main objectives of this paper are (1) to propose a Deep Learning (DL) algorithm, the Stacked Sparse Auto-encoder (SSAE), for rice-yield estimation using climatic and Moderate Resolution Imaging Spectroradiometer (MODIS) data; (2) to choose scenarios showing the best combined performance in terms of length of crop season (before and after harvest) and aggregation periods (7, 10, 15, and 30 days) of climatic data; and (3) to analyse the results in both the temporal and spatial perspectives. In this procedure, the SSAE model was built around the study objectives and compared with the artificial neural network (ANN) model for evaluation of its performance. According to the results, the combined 15-day-aggregated climatic data (between June and August) and MODIS data were selected as the optimal feature set for rice-yield estimation in the study area, Jeolla-do; the SSAE model outperformed ANN, showing root mean square error (RMSE) and RMSE% of 33.09 kg(10a)−1 (5.21 kg(10a)−1lower than ANN) and 6.89% (1.14% lower than ANN). Throughout the experiments, the rice-yield-estimation potentiality of a DL algorithm, namely the SSAE, was substantiated.
Development of a numerical for dynamic depositioning of non-Newtonian slurries

This study aims to improve the predictive capabilities of flow pattern and depositional behaviour of non-Newtonian, high concentration sand and fines mixtures. The depositional behaviour influences the geometry of the deposit and the distribution of sand and fines particles, which in turn influence the strength and consolidation performance of the deposit. Ultimately this affects the area reclamation targets from the mining industry. In this study an existing numerical model, Delft3D (a three-dimensional, open source flow model from Deltares utilized world-wide in various hydrodynamic and sediment transport studies), is extended with the physics that describe non-Newtonian rheology and sand settling in shear flow. The rheology determines the yield stress and viscosity of a fluid. Shear induced sand settling occurs for fluids with a yield stress. Sand settles under shear whereas smaller particles stay suspended, producing segregation. Segregation leads to non-uniformity in deposit composition (e.g sand and fines dominated areas). Rheology and sand settling mutually interact, directly influencing deposition patterns. This study is a continuation of the work of [Hanssen, 2016], who included specific rheology and sand settling formulation in a one-dimensional version of Delft3D (i.e. 1DV). As part of this work, further verification of this one-dimensional model has been performed and the model has been extended to two-dimensional vertical (i.e. 2DV in a longitudinal cross section). The extended model has been tested in 2DV with deposition over a 400 meters slope. A sensitivity analysis is performed to consider the effect of different solid contents and rheological properties. The model is also tested on specific oil sand applications and data, such as tailings deposition down a beach, mutual interaction of tailings with different rheology or strength and a characterization of fines capture compared with data. This study proved that the extended version of Delft3D can simulate a 2DV non-Newtonian high density flow including sand settling. However there are still some physical processes where the model needs improvements or further research is needed, such as laminar-turbulence regime; transition to 3D and the motion of sand layers. Further model verification and development goes hands in hands with a good data set. Specifically important are flume/field tests with rheology data and its variation with time, especially for polymer added tailings, to verify the model.
GENERATING UAV ACCURATE ORTHO- MOSAICKED IMAGES USING A SIX-BAND MULTISPECTRAL CAMERA ARRANGEMENT

Site-specific weed management in a very early phenological stage of crop and weed plants requires the ultra-high spatial resolution imagery provided by unmanned aerial vehicles (UAV) flying at low altitudes. These UAV images cannot cover the whole field, resulting in the need to take a sequence or series of multiple overlapped (end-lap and side-lap) images. As consequence, a large number of UAV images are acquired for each plot. These multiple overlapped images must be oriented by calculating the bundle adjustment and ortho-rectified throughout an aerial-triangulation procedure to create an accurately georeferenced ortho-mosaicked image of the entire field. As the spatial accuracy of ortho-mosaicked image is mainly dependent on camera calibration and percentage of overlapping, this paper describes the effect of flight parameters and sensor arrangement using an UAV flying at 30 m altitude and six-band multispectral camera (miniature camera array composed of a master channel and five more channels or bands) on the workflow of the mosaicking process. The objective is to develop a procedure to generate an accurate ortho-image. This procedure would be then used in multispectral UAV imagery taken on crops for weed seedling mapping. The main phases of UAV workflow were: sensor calibration, mission planning, UAV flight and processing images. Regarding the sensor calibration, six different geometric calibrations were calculated, one for each image registered corresponding to every band. Referring to mission planning, two end-lap and side-lap settings (60%-30% and 70%-40%) were considered. Calibration and image overlapping are related to the flight duration and accuracy resolving aerial-triangulation. Different aerialtriangulations were calculated for different scenarios taken into account several combinations of calibrations and the overlapping values. The spatial accuracy of the different generated ortho-mosaicked images using both overlapping values and calibration were evaluated by the ASPRS (American Society for Photogrammetry and Remote Sensing) test. The results showed that the best setting of flight to keep the spatial accuracy in the bundle adjustment was 4070% overlapping and using the master channel for the aero-triangulation and its own calibration parameters. Generally, high values of end-lap and side-lap improved the accuracy of block photogrammetric adjustment, although they increased the flight length and decreased the area overflow. In addition, the framework to process and mosaic the images taken by this type of sensor was
The antigen-presenting activities of Ia+ dendritic cells shift dynamically from lung to lymph node after an airway challenge with soluble antigen

Dendritic cells (DC) are widely distributed in the lung where they are distinguished by their morphology and class II major histocompatibility complex (Ia) antigen expression. Although a role for DC as pulmonary antigen-presenting cell (APC) has been suggested, little is currently known concerning how these cells respond to inhaled antigens in vivo. Hen-egg lysozyme (HEL) was injected intratracheally into Lewis rats; DC were subsequently purified from the lung and regional lymph nodes (LN) at intervals of up to 14 d and examined for their ability to stimulate the proliferation of HEL-immune T cells in vitro in the absence of added HEL. Pulmonary DC displayed APC activities at 3 h and for up to 7 d after the injection of antigen. Dendritic cells in the draining hilar LN showed APC activities that appeared at 24 h, peaked at day 3, and then diminished progressively. After the primary sensitization, HEL- immune T cells were detected in hilar LN but not in the lung. A second airway challenge with HEL at day 14 yielded an antigen-specific pulmonary immune response, characterized histologically by the accumulation of mononuclear cells around lung venules. We conclude that APC activities shift from lung to lymph node during the response to inhaled antigen.
Identification and Phylogeny of the First T Cell Epitope Identified from a Human Gut Bacteroides Species

Host T cell reactivity toward gut bacterial epitopes has been recognized as part of disease pathogenesis. However, the specificity of T cells that recognize this vast number of epitopes has not yet been well described. After colonizing a C57BL/6J germ-free mouse with the human gut symbiotic bacteria Bacteroides thetaiotaomicron, we isolated a T cell that recognized these bacteria in vitro. Using this T cell, we mapped the first known non-carbohydrate T cell epitope within the phylum Bacteroidetes. The T cell also reacted to two other additional Bacteroides species. We identified the peptide that stimulated the T cell by using a genetic approach. Genomic data from the epitope-positive and epitope-negative bacteria explain the cross-reactivity of the T cell to multiple species. This epitope degeneracy should shape our understanding of the T cell repertoire stimulated by the complex microbiome residing in the gastrointestinal tract in both healthy and disease states.