Miracle-dz/UniFAR-FTUs huggingface dataset:
A new, convexity based, necessary and sufficient vertex solution for robust stability check of linear interval parameter matrix families

This paper revisits the problem of checking the robust stability of matrix families generated by interval parameters in a matrix. A previous solution given by the author for this problem involved complete dependence on the quantitative (eigenvalue information) of a set of special matrices labeled the Kronecker Nonsingularity (KN) matrices, making the `convexity' property non-transparent. In the new solution presented in this paper, we combine the qualitative (sign) as well as quantitative (magnitude) information of these KN matrices and present a vertex solution in which the convexity property of the solution is transparent making it more `elegant' than the previous solution. In other words, the new solution clearly underscores the importance of using the sign structure of a matrix in assessing the stability of a matrix. This new solution is made possible by the new insight provided by the qualitative (sign) stability/instability derived from ecological principles. Examples are given which clearly demonstrate effectiveness of the new, convexity based algorithm.
C-Fos mapping and EEG characteristics of multiple mice brain regions in pentylenetetrazol-induced seizure mice model

ABSTRACT Purpose: To confirm different local brain activities characterized in pentylenetetrazol (PTZ)-induced seizure model. Methods: we induced seizure response by a single dose of PTZ injection (45 mg/kg, i.p.). Local activity was recorded in different brain regions by EEG in time and c-Fos staining at different time points (0.5 h, 1 h, 2 h, 4 h) after PTZ treatment. Results: EEG recordings showed distinctive features of activation in different brain areas. With the aggravation of behavioral manifestations of seizures, the frequency and amplitude of the discharges on EEG were increasing gradually. The epileptic response on EEG immediately ended after reaching the maximum stage of seizures, followed by a short period of suppression. The labeling of c-Fos was enhanced in the medial prefrontal cortex, the piriform cortex, the amygdala, hippocampal CA1, CA3 and dentate gyrus, but inapparent in the striatum. The most potent changes in c-Fos were observed in cortex, amygdala nuclei, and dentate gyrus. EEG and c-Fos immunolabeling in neuronal activation showed discrepancies in the striatum. For each brain region, the maximum c-Fos labeling was observed at 2 h after injection and diminished at 4 h. The level of c-Fos immunoreactivity was even lower than the control group, which was accompanied by increased labeling of parvalbumin neurons (PVNs). Conclusions: These findings validated PTZ-induced seizure as a seizure model with a specific spatial-temporal profile. Neuronal activity was enhanced and then subsequently inhibited during seizure evolution. Abbreviations: AEDs: anti-epileptic drugs; AF: Alexa Fluor; CA1: Cornu Ammonis area 1; CA3: Cornu Ammonis area 3; DAB, 3: 3P-diaminobenzidine; DAPI: 4‘,6-diamidino-2-phenylindole; DG: dentate gyrus; EEG: electroencephalogram; GABA: gamma-aminobutyric acid; IEG: immediate early gene; mPFC: medial prefrontal cortex; NAc: nucleus accumbens; PB: phosphate buffer; PBS: phosphate buffered saline; PBST: phosphate buffered saline with Tween; PFA, paraformaldehyde; PTZ: pentylenetetrazol; PVN: parvalbumin neuron; ROI: regions of interest; SE: status epilepticus.
Gitools: Analysis and Visualisation of Genomic Data Using Interactive Heat-Maps

Intuitive visualization of data and results is very important in genomics, especially when many conditions are to be analyzed and compared. Heat-maps have proven very useful for the representation of biological data. Here we present Gitools (http://www.gitools.org), an open-source tool to perform analyses and visualize data and results as interactive heat-maps. Gitools contains data import systems from several sources (i.e. IntOGen, Biomart, KEGG, Gene Ontology), which facilitate the integration of novel data with previous knowledge.
Complex network analysis of free-energy landscapes

The kinetics of biomolecular isomerization processes, such as protein folding, is governed by a free-energy surface of high dimensionality and complexity. As an alternative to projections into one or two dimensions, the free-energy surface can be mapped into a weighted network where nodes and links are configurations and direct transitions among them, respectively. In this work, the free-energy basins and barriers of the alanine dipeptide are determined quantitatively using an algorithm to partition the network into clusters (i.e., states) according to the equilibrium transitions sampled by molecular dynamics. The network-based approach allows for the analysis of the thermodynamics and kinetics of biomolecule isomerization without reliance on arbitrarily chosen order parameters. Moreover, it is shown on low-dimensional models, which can be treated analytically, as well as for the alanine dipeptide, that the broad-tailed weight distribution observed in their networks originates from free-energy basins with mainly enthalpic character.
Synergy between the ectoenzymes CD39 and CD73 contributes to adenosinergic immunosuppression in human malignant gliomas.

BACKGROUND The importance of ectoenzymes CD39 and CD73 in mediating adenosinergic immunosuppression has been recognized, but their roles in human malignant glioma-associated immunosuppression remain largely unknown. METHODS In this study, the ectoenzyme characteristics of malignant glioma cells and infiltrating CD4(+) T lymphocytes isolated from newly diagnosed malignant glioma patients were investigated. The ectoenzyme activities of both cell populations were determined by nucleotide hydrolysis assay. The immunosuppressive property of the CD39-CD73 synergic effect was evaluated via responder T-cell proliferation assay. RESULTS We observed that CD39(-)CD73(+) glioma cells and infiltrating CD4(+)CD39(high)CD73(low) T lymphocytes exhibited 2 distinct but complementary ectoenzyme phenotypes, which were further verified by enzyme activity assay. The nucleotide hydrolysis cascade was incomplete unless CD39 derived from T lymphocytes and CD73 collaborated synergistically. We demonstrated that increased suppression of responder CD4(+) T-cell proliferation suppression was induced by CD4(+)CD39(+) T cells in the presence of CD73(+) glioma cells, which could be alleviated by the CD39 inhibitor ARL67156, the CD73 inhibitor APCP, or the adenosine receptor A2aR antagonist SCH58261. In addition, survival analysis suggested that CD73 downregulation was a positive prognostic factor related to the extended disease-free survival of glioblastoma patients. CONCLUSIONS Our data indicate that glioma-derived CD73 contributes to local adenosine-mediated immunosuppression in synergy with CD39 from infiltrating CD4(+)CD39(+) T lymphocytes, which could become a potential therapeutic target for treatment of malignant glioma and other immunosuppressive diseases.
Behavioural Biometrics in VR: Identifying People from Body Motion and Relations in Virtual Reality

Every person is unique, with individual behavioural characteristics: how one moves, coordinates, and uses their body. In this paper we investigate body motion as behavioural biometrics for virtual reality. In particular, we look into which behaviour is suitable to identify a user. This is valuable in situations where multiple people use a virtual reality environment in parallel, for example in the context of authentication or to adapt the VR environment to users' preferences. We present a user study (N=22) where people perform controlled VR tasks (pointing, grabbing, walking, typing), monitoring their head, hand, and eye motion data over two sessions. These body segments can be arbitrarily combined into body relations, and we found that these movements and their combination lead to characteristic behavioural patterns. We present an extensive analysis of which motion/relation is useful to identify users in which tasks using classification methods. Our findings are beneficial for researchers and practitioners alike who aim to build novel adaptive and secure user interfaces in virtual reality.
Generalization and optimization of feature set for accurate identification of P2P Traffic in the internet using neural network

P2P applications supposedly constitute a substantial proportion of today's Internet traffic. The ability to accurately identify different P2P applications in internet traffic is important to a broad range of network operations including application-specific traffic engineering, capacity planning, resource provisioning, service differentiation, etc. In this paper, we present a Neural Network approach that precisely identifies the P2P traffic using Multi-Layer Perceptron (MLP) neural network. It is general practice to reduce the cost of classification by reducing the number of features, utilizing some feature selection algorithm. The reduced feature set produced by such algorithms are highly data-dependent and are different for different data sets. Further the feature set produced from one data set does not yield good results when tried upon other data sets. We propose an optimum and universal set of features which is independent of training and test data sets. The proposed feature set has enabled us to achieve significant improvement in performance of the MLP classifier. The few features in the proposed feature set results in a significant reduction in training time, while maintaining the performance, thereby making this approach suitable for real-time implementation.
Differential Regulation of mRNAs for GDNF and its Receptors Ret and GDNFRα After Sciatic Nerve Lesion in the Mouse

Glial cell line‐derived neurotrophic factor (GDNF), first characterized for its effect on dopamine uptake in central dopaminergic neurons, appears to be a powerful neurotrophic factor for motor neurons. GDNF has recently been shown to signal through a multisubunit receptor. This receptor is composed of a ligand‐binding subunit, called GDNF receptor α (GDNFRα), and a signalling tyrosine kinase subunit, Ret. To gain further insight into GDNF function, we investigated the expression of GDNF and its receptors after nerve lesion in adult mice. Analysis of expression in muscle, nerve and spinal cord by RNase protection assay and in situ hydridization revealed that, in adult non‐lesioned mice, GDNF mRNA was expressed in the nerve and GDNFRα mRNA in the nerve and the spinal cord, while the expression of Ret was restricted to spinal cord motor neurons. After a sciatic nerve crush a rapid increase in GDNF mRNA was observed in the distal part of the nerve and a delayed elevation in the muscle, while GDNFRα mRNA was up‐regulated in the distal part of the sciatic nerve but not in proximal nerve or spinal cord. The lesion also induced a rapid increase in Ret mRNA expression, but the increase was observed only in spinal cord motor neurons and in dorsal root ganglion neurons. A pattern of expression of GDNF and its receptors similar to that seen after lesion in the adult was detected during embryonic development. Administration of GDNF enhanced sciatic nerve regeneration measured by the nerve pinch test. Taken together, these results suggest that GDNF has an important role during regeneration after nerve damage in the adult.
Rheumatoid arthritis synovial tissue harbours dominant B-cell and plasma-cell clones associated with autoreactivity

Objective To identify potential autoreactive B-cell and plasma-cell clones by quantitatively analysing the complete human B-cell receptor (BCR) repertoire in synovium and peripheral blood in early and established rheumatoid arthritis (RA). Methods The BCR repertoire was screened in synovium and blood of six patients with early RA (ERA) (<6 months) and six with established RA (ESRA) (>20 months). In two patients, the repertoires in different joints were compared. Repertoires were analysed by next-generation sequencing from mRNA, generating >10 000 BCR heavy-chain sequence reads per sample. For each clone, the degree of expansion was calculated as the percentage of the total number of reads encoding the specific clonal sequence. Clones with a frequency ≥0.5% were considered dominant. Results Multiple dominant clones were found in inflamed synovium but hardly any in blood. Within an individual patient, the same dominant clones were detected in different joints. The majority of the synovial clones were class-switched; however, the fraction of clones that expressed IgM was higher in ESRA than ERA patients. Dominant synovial clones showed autoreactive features: in ERA in particular the clones were enriched for immunoglobulin heavy chain gene segment V4–34 (IGHV4–34) and showed longer CDR3 lengths. Dominant synovial clones that did not encode IGHV4–34 also had longer CDR3s than peripheral blood. Conclusions In RA, the synovium forms a niche where expanded—potentially autoreactive—B cells and plasma cells reside. The inflamed target tissue, especially in the earliest phase of disease, seems to be the most promising compartment for studying autoreactive cells.
Household structure, maternal characteristics and childhood mortality in rural sub-Saharan Africa.

INTRODUCTION The household dynamics of childhood mortality in rural areas of sub-Saharan Africa is less researched despite the fact that mortality rates are almost two times that of urban settings. This study aimed to investigate the influence of household structure on childhood mortality while controlling for household and maternal characteristics in rural sub-Saharan Africa. METHODS Eight countries with recent demographic and health survey data not earlier than the year 2010 were selected, two from each sub-region of sub-Saharan Africa. The outcome variables were risk of infant and child death while the main independent variables included sex of household head and household structure. Descriptive statistics were generated for all variables. Mortality rates disaggregated by sex of household head and household structure were estimated using the Kaplan-Meier method. Cox proportional hazard regression models were fitted to investigate the relationship between the outcome and explanatory variables in each country. RESULTS The percentage of children living in female-headed households (FHHs) ranged from 5.2% in Burkina Faso to 49.1% in Namibia while those living in extended family households ranged from 27.4% in Rwanda to 59.9% in Namibia. Multivariate hazard regression showed that, in the majority of the countries, there was no significant relationship between living in FHHs and childhood mortality, but the direction and magnitude of effect varied across countries. A significant negative effect of FHHs on infant mortality was observed in Burkina Faso (HR=1.64, 95% confidence interval (CI): 1.09-2.48) and Zambia (HR=1.49, 95%CI: 1.02-2.17). Likewise, children in extended family households had a higher risk of child mortality in Burkina Faso (HR=1.33, 95%CI: 1.04-1.69) and Zambia (HR=1.59, 95%CI: 1.02-2.49). There was not much difference in the effect of FHHs between infancy (0-11 months) and childhood (12-59 months) in the other countries. The pooled adjusted hazard ratio (HR) showed that the risk of death in childhood was 23% higher in extended family households (HR=1.23, 95%CI: 1.09-1.39) than in nuclear family households. CONCLUSIONS In rural sub-Saharan Africa, children in FHHs do not have significantly higher infant and child mortality. Also, there was no difference in infant mortality between nuclear and extended family households but the latter constitute a higher risk for child mortality.
A survey of adaptive services to cope with dynamics in wireless self-organizing networks

In this article, we consider different types of wireless networks that benefit from and, in certain cases, require self-organization. Taking mobile ad hoc, wireless sensor, wireless mesh, and delay-tolerant networks as examples of wireless self-organizing networks (WSONs), we identify that the common challenges these networks face are mainly due to lack of centralized management, device heterogeneity, unreliable wireless communication, mobility, resource constraints, or the need to support different traffic types. In this context, we survey several adaptive services proposed to handle these challenges. In particular, we group the adaptive services as core services and network-level services. By categorizing different types of services that handle adaptation and the types of adaptations, we intend to provide useful design guidelines for achieving self-organizing behavior in network protocols. Finally, we discuss open research problems to encourage the design of novel protocols for WSONs.
CloudShelter: Protecting Virtual Machines' Memory Resource Availability in Clouds

We present CloudShelter, an architecture to protect virtual machines' memory availability from undesired resource contention on the cloud servers. We introduce a new micro-architectural metric: Memory Round Trip Time, to quantify VMs' memory QoS. Using this metric, (1) CloudShelter defines new QoS options for customers when launching VMs. These options can guarantee VMs' memory QoS at different levels even when they face intensive contention with co-located VMs; (2) CloudShelter periodically monitors VMs' memory QoS at runtime: once QoS violations against customers' demands are detected, CloudShelter places this VM into an isolated environment to eliminate contention. CloudShelter can reduce 30.1% performance interference from LLC/DRAM contention and 81.6% interference from bus contention1.
MicroRNA discovery by similarity search to a database of RNA-seq profiles

In silico generated search for microRNAs (miRNAs) has been driven by methods compiling structural features of the miRNA precursor hairpin, as well as to some degree combining this with the analysis of RNA-seq profiles for which the miRNA typically leave the drosha/dicer fingerprint of 1–2 ~22 nt blocks of reads corresponding to the mature and star miRNA. In complement to the previous methods, we present a study where we systematically exploit these patterns of read profiles. We created two datasets comprised of 2540 and 4795 read profiles obtained after preprocessing short RNA-seq data from miRBase and ENCODE, respectively. Out of 4795 ENCODE read profiles, 1361 are annotated as non-coding RNAs (ncRNAs) and of which 285 are further annotated as miRNAs. Using deepBlockAlign (dba), we align ncRNA read profiles from ENCODE against the miRBase read profiles (cleaned for “self-matches”) and are able to separate ENCODE miRNAs from the other ncRNAs by a Matthews Correlation Coefficient (MCC) of 0.8 and obtain an area under the curve of 0.93. Based on the dba score cut-off of 0.7 at which we observed the maximum MCC of 0.8, we predict 523 novel miRNA candidates. An additional RNA secondary structure analysis reveal that 42 of the candidates overlap with predicted conserved secondary structure. Further analysis reveal that the 523 miRNA candidates are located in genomic regions with MAF block (UCSC) fragmentation and poor sequence conservation, which in part might explain why they have been overlooked in previous efforts. We further analyzed known human and mouse miRNA read profiles and found two distinct classes; the first containing two blocks and the second containing >2 blocks of reads. Also the latter class holds read profiles that have less well defined arrangement of reads in comparison to the former class. On comparison of miRNA read profiles from plants and animals, we observed kingdom specific read profiles that are distinct in terms of both length and distribution of reads within the read profiles to each other. All the data, as well as a server to search miRBase read profiles by uploading a BED file, is available at http://rth.dk/resources/mirdba.
A 90nm CMOS 1.2v 6b 1GS/s two-step subranging ADC

A 1.2V 6b 1GS/s ADC is fabricated in a 90nm CMOS process, occupies 0.13mm2, and consumes 55mW. This ADC uses background offset-calibration to enable the use of minimum-size devices in pre-amplifiers and comparators. A solution that guarantees fast selection of the important reference voltages, and halves the number of switches in the resistor ladder, further improves high-frequency performance
Superpixel segmentation based gradient maps on RGB-D dataset

Superpixels aim to group homogenous pixels by a series of characteristics in an image. They decimate redundancy that may be utilized later by more computationally expensive algorithms. The most popular algorithms obtain superpixels based on an energy function on a graph. However, these graph-based methods have a high computational time consumption. This study presents a fast and high quality over-segmentation method by a watershed transform based on computing the dissimilarity of pixels among RGB(D) cues and gradient maps. Specifically, we first capture a gradient map based on an image to enhance and explain directional variations in the image scene. A distance function then measures the similarity among adjacent pixels, which is calculated according to RGB(D) values. A fast marker-controlled watershed (MCW) algorithm traverses the entire image based on the distance function. Finally, we acquire all watersheds consisting of superpixel contours. Experimental results compare state-of-the-art algorithms and highlight the effectiveness of the proposed method. As an application, the proposed superpixel algorithm can be used in applications aiming for real-time, like mobile robot saliency detection and segmentation.
Neurocognitive Functioning in Children and Adolescents at the Time of Type 1 Diabetes Diagnosis: Associations With Glycemic Control 1 Year After Diagnosis

OBJECTIVE To determine whether impairments in neurocognitive functioning are detectable at type 1 diabetes diagnosis and associated with subsequent glycemic control. RESEARCH DESIGN AND METHODS Children/adolescents (N = 147) aged 5–18 years completed neuropsychological testing during their inpatient hospitalization for new-onset type 1 diabetes. Test scores were compared with normative data using one-sample Student t tests. Children with onset before 8 years of age were compared with children aged 9–18 years using ANOVA, and associations between neurocognitive performance at diagnosis and glycemic control 1 year postdiagnosis were examined using regression analyses. RESULTS Children with type 1 diabetes performed significantly below expectations on most neurocognitive measures (P values <0.0001), with large decrements from the normative mean evident in psychomotor speed (>1 SD), visuomotor integration (0.7 SD), and phonemic fluency (0.8 SD). High incidence of impairment (scores less than second percentile) was evident on all tasks except digit span. Dominant-hand psychomotor speed was significantly associated with poor glycemic control (A1C ≥9.5% [80 mmol/mol]; P = 0.032) 1 year postdiagnosis, controlling for race/ethnicity, sex, and reading ability. Impaired psychomotor speed was associated with a 0.77% increase in mean A1C (8.4 mmol/mol). CONCLUSIONS Deficits were evident in neurocognitive functioning within days of diabetes diagnosis that were associated with diabetes outcomes over 1 year postdiagnosis. Impairment was most apparent in psychomotor speed, consistent with research implicating damage to posterior white matter tracts and associated gray matter regions in type 1 diabetes. Psychomotor impairment may be an early marker for a broader neurobehavioral vulnerability that has implications for long-term diabetes management.
Image hashing resilient to geometric and filtering operations

Image hash functions provide compact representations of images, which is useful for search and authentication applications. In this work, we have identified a general three step framework and proposed a new image hashing scheme that achieves a better overall performance than the existing approaches under various kinds of image processing distortions. By exploiting the properties of discrete polar Fourier transform and incorporating cryptographic keys, the proposed image hash is resilient to geometric and filtering operations, and is secure against guessing and forgery attacks.