Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovery of CD8+ T cell epitopes in Chlamydia trachomatis infection through use of caged class I MHC tetramers

Class I MHC tetramers allow direct phenotypic identification of CD8+ T cell populations, but their production remains laborious. A peptide exchange strategy that employs class I MHC products loaded with conditional ligands (caged MHC molecules) provides a fast and straightforward method to obtain diverse arrays of class I MHC tetramers and facilitates CD8+ T cell epitope discovery. Here, we describe the development of photocleavable analogs of the FAPGNYPAL (SV9) epitope that bind H-2Kb and H-2Db with full retention of their structural and functional integrity. We ranked all possible H-2Kb octameric and H-2Db nonameric epitopes that span the genome of Chlamydia trachomatis and prepared MHC tetramers from ≈2,000 of the highest scoring peptides by replacement of the SV9 analog with the peptide of choice. The resulting 2,000-member class I MHC tetramer array allowed the discovery of two variants of an epitope derived from polymorphic membrane protein I (PmpI) and an assessment of the kinetics of emergence and the effector function of the corresponding CD8+ T cells.
Network Clustering via Maximizing Modularity: Approximation Algorithms and Theoretical Limits

Many social networks and complex systems are found to be naturally divided into clusters of densely connected nodes, known as community structure (CS). Finding CS is one of fundamental yet challenging topics in network science. One of the most popular classes of methods for this problem is to maximize Newman's modularity. However, there is a little understood on how well we can approximate the maximum modularity as well as the implications of finding community structure with provable guarantees. In this paper, we settle definitely the approximability of modularity clustering, proving that approximating the problem within any (multiplicative) positive factor is intractable, unless P = NP. Yet we propose the first additive approximation algorithm for modularity clustering with a constant factor. Moreover, we provide a rigorous proof that a CS with modularity arbitrary close to maximum modularity QOPT might bear no similarity to the optimal CS of maximum modularity. Thus even when CS with near-optimal modularity are found, other verification methods are needed to confirm the significance of the structure.
A passivity-based decentralized approach for the bilateral teleoperation of a group of UAVs with switching topology

In this paper, a novel distributed control strategy for teleoperating a fleet of Unmanned Aerial Vehicles (UAVs) is proposed. Using passivity based techniques, we allow the behavior of the UAVs to be as flexible as possible with arbitrary split and join decisions while guaranteeing stability of the system. Furthermore, the overall teleoperation system is also made passive and, therefore, characterized by a stable behavior both in free motion and when interacting with unknown passive obstacles. The performance of the system is validated through semi-experiments.
A blind watermarking algorithm with semantic meaningful watermarks

Watermarking techniques that need no original information during watermark detection, the so-called blind (public) watermarking, are more desirable than others for practical usage and convenience in watermark extraction. We convert a non-blind (private) image watermarking algorithm into a blind one by carefully removing and changing some function units of the original approach. As compared to the original algorithm, these modifications result in little quality degradation but do extend the practical usage of it. As an example, we applied the revised watermarking algorithm to a panorama picture construction tool, the VideoVR system, in which only blind watermarking algorithms can be used. The experimental results show that almost no perceptible distortions are found in the embedded pictures, and the retrieved watermarks can clearly indicate the ownership of the system constructor.
Current-Feed Single-Switch Forward Resonant DC Transformer (DCX) With Secondary Diode-Clamping

A simple current-feed single-switch forward resonant converter with secondary diode-clamping is proposed for low-power high-density bus converter applications in this paper. The quasi-zero-voltage-switching turn-on and quasi-zero-current-switching (ZCS) turn-off for switch are both achieved. Due to the quasi-ZCS turn-off , the high voltage spike in traditional single forward converter with a reset winding is much reduced. A small diode connected to the output capacitor is utilized to clamp the voltage stress of the switches. The operating principle of the proposed converter is analyzed and a MHz 66 W 24 V-to-12 V prototype with all Si devices is built up. Experimental results show good soft-switching features, and the prototype achieves 95.3% peak efficiency with 270 W/in3 power density.
Ischaemic preconditioning reduces troponin T release in patients undergoing coronary artery bypass surgery.

OBJECTIVE: To investigate whether ischaemic preconditioning could reduce myocardial injury, as manifest by troponin T release, in patients undergoing elective coronary artery bypass surgery. DESIGN: Randomised controlled trial. SETTING: Cardiothoracic unit of a tertiary care centre. PATIENTS: Patients with three vessel coronary artery disease and stable angina admitted for first time elective coronary artery bypass surgery were invited to take part in the study; 33 patients were randomised into control or preconditioning groups. INTERVENTION: Patients in the preconditioning group were exposed to two additional three minute periods of myocardial ischaemia at the beginning of the revascularisation operation, before the ischaemic period used for the first coronary artery bypass graft distal anastomosis. MAIN OUTCOME MEASURE: Serum troponin T concentration at 72 hours after cardiopulmonary bypass. RESULTS: The troponin T assays were performed by blinded observers at a different hospital. All patients had undetectable serum troponin T (< 0.1 microgram/l) before cardiopulmonary bypass, and troponin T was raised postoperatively in all patients. At 72 hours, serum troponin T was lower (P = 0.05) in the preconditioned group (median 0.3 microgram/l) than in the control group (median 1.4 micrograms/l). CONCLUSIONS: The direct application of a preconditioning stimulus in clinical practice has been shown, for the first time, to protect patients against irreversible myocyte injury.
JNK1 Is Required for T Cell-Mediated Immunity Against Leishmania major Infection1

c-Jun N-terminal kinase (JNK) is a mitogen-activated protein kinase that plays important regulatory roles in helper T cell differentiation. In the current study, we used Jnk1-deficient mice to examine the function of JNK during an in vivo pathogenic infection, leishmaniasis, which is strongly influenced by Th1/Th2 effector mechanisms. The data show that Jnk1-deficient mice, despite their usually genetically resistant background, were unable to resolve Leishmania infections. Jnk1−/− mice displayed reduced delayed-type hypersensitivity in response to the pathogen, which was associated with a T cell defect. We found that, although these mice can direct an apparent Th1-response, there is also simultaneous generation of Leishmania-specific Th2 responses, which possibly down-modulate protective Th1-mediated immune function. These findings demonstrate that the negative regulation of Th2 cytokine production by the JNK1 signaling pathway is essential for generating Th1-polarized immunity against intracellular pathogens, such as Leishmania major.
Status updates through queues

Anytime, anywhere network connectivity, together with portable sensing and computing devices have led to applications in which sources, for example people or environmental sensors, send updates of their status, for example location, to interested recipients, say a location service. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited network resources. We employ a time-averaged age metric for characterizing performance of such status update systems. We use system abstractions consisting of a source, a service facility and monitors, with the model of the service facility (physical constraints) a given. While prior work examined first-come-first-served (FCFS) queues, this paper looks at the queue discipline of last-come-first-served (LCFS). We explore LCFS systems with and without the ability to preempt the packet currently in service. For each we derive a general expression for system age and solve for the average age a Poisson source can achieve given memoryless service. Specifically, when preemption is allowed, we evaluate how the source would share the service facility with other independent Poisson sources.
Design and Development of Hybrid Portable Mini Wind Turbine

Awareness about the important of renewable energy such as solar, wind and geothermal as a primary alternative to non-renewable energy sources has been increase among the world society. Many country like United Kingdom, Spain, United State of America and Japan has started to develop a renewable technology especially wind energy in order to supply electricity to their citizen. In Malaysia the wind energy is not widely used for power generation as the average wind speed which is about 3-6 m/s (East Coast region) make it not very efficient for large scale of power production. However, a small scale of wind turbine can be used to generate an electricity from a low wind speed. This small capacity of electricity that generated by the wind turbine can be useful to many situation. For example, during an emergency or disaster where there is a shortage in electrical supply, the small scale wind turbine can be used to charge up a telecommunication device such as phone to make an emergency call at the disaster area. Other than that, the small scale wind turbine can also be utilize at rural area where there is no electrical supply to power up a small device.
Combining feature fusion and decision fusion for classification of hyperspectral and LiDAR data

This paper proposes a method to combine feature fusion and decision fusion together for multi-sensor data classification. First, morphological features which contain elevation and spatial information, are generated on both LiDAR data and the first few principal components (PCs) of original hyper-spectral (HS) image. We got the fused features by projecting the spectral (original HS image), spatial and elevation features onto a lower subspace through a graph-based feature fusion method. Then, we got four classification maps by using spectral features, spatial features, elevation features and the graph fused features individually as input of SVM classifier. The final classification map was obtained by fusing the four classification maps through the weighted majority voting. Experimental results on fusion of HS and LiDAR data from the 2013 IEEE GRSS Data Fusion Contest demonstrate effectiveness of the proposed method. Compared to the methods using single data source or only feature fusion, with the proposed method, overall classification accuracies were improved by 10% and 2%, respectively.
Likelihood-ratio calibration using prior-weighted proper scoring rules

Prior-weighted logistic regression has become a standard tool for calibration in speaker recognition. Logistic regression is the optimization of the expected value of the logarithmic scoring rule. We generalize this via a parametric family of proper scoring rules. Our theoretical analysis shows how different members of this family induce different relative weightings over a spectrum of applications of which the decision thresholds range from low to high. Special attention is given to the interaction between prior weighting and proper scoring rule parameters. Experiments on NIST SRE'12 suggest that for applications with low false-alarm rate requirements, scoring rules tailored to emphasize higher score thresholds may give better accuracy than logistic regression.
Neuroanatomical, Sensorimotor and Cognitive Deficits in Adult Rats with White Matter Injury Following Prenatal Ischemia

Perinatal brain injury including white matter damage (WMD) is highly related to sensory, motor or cognitive impairments in humans born prematurely. Our aim was to examine the neuroanatomical, functional and behavioral changes in adult rats that experienced prenatal ischemia (PI), thereby inducing WMD. PI was induced by unilateral uterine artery ligation at E17 in pregnant rats. We assessed performances in gait, cognitive abilities and topographical organization of maps, and neuronal and glial density in primary motor and somatosensory cortices, the hippocampus and prefrontal cortex, as well as axonal degeneration and astrogliosis in white matter tracts. We found WMD in corpus callosum and brainstem, and associated with the hippocampus and somatosensory cortex, but not the motor cortex after PI. PI rats exhibited mild locomotor impairments associated with minor signs of spasticity. Motor map organization and neuronal density were normal in PI rats, contrasting with major somatosensory map disorganization, reduced neuronal density, and a marked reduction of inhibitory interneurons. PI rats exhibited spontaneous hyperactivity in open‐field test and short‐term memory deficits associated with abnormal neuronal density in related brain areas. Thus, this model reproduces in adult PI rats the main deficits observed in infants with a perinatal history of hypoxia‐ischemia and WMD.
Informatics Enhanced SNP Microarray Analysis of 30 Miscarriage Samples Compared to Routine Cytogenetics

Purpose The metaphase karyotype is often used as a diagnostic tool in the setting of early miscarriage; however this technique has several limitations. We evaluate a new technique for karyotyping that uses single nucleotide polymorphism microarrays (SNP). This technique was compared in a blinded, prospective fashion, to the traditional metaphase karyotype. Methods Patients undergoing dilation and curettage for first trimester miscarriage between February and August 2010 were enrolled. Samples of chorionic villi were equally divided and sent for microarray testing in parallel with routine cytogenetic testing. Results Thirty samples were analyzed, with only four discordant results. Discordant results occurred when the entire genome was duplicated or when a balanced rearrangement was present. Cytogenetic karyotyping took an average of 29 days while microarray-based karytoyping took an average of 12 days. Conclusions Molecular karyotyping of POC after missed abortion using SNP microarray analysis allows for the ability to detect maternal cell contamination and provides rapid results with good concordance to standard cytogenetic analysis.
Granular nuclear inclusion body disease: Fine structure of tibial muscle and sural nerve

Fine granular (hyaline) intranuclear inclusion bodies were found in perivascular cells of a muscle and a sural nerve biopsy from a 32‐year‐old woman with slowly progressive motor disturbances. The hyaline nuclear inclusion bodies could be distinguished from other intranuclear hyaline inclusions by their granularity, the size of the granules (approximately 5–15 nm), and the positive iron staining reaction. They were not seen in muscle fibers or Schwann cells. Because of these apparently pathognomonic structural features the patient appears to present a condition that has not been described before.
Neural processing of imminent collision in humans

Detecting a looming object and its imminent collision is imperative to survival. For most humans, it is a fundamental aspect of daily activities such as driving, road crossing and participating in sport, yet little is known about how the brain both detects and responds to such stimuli. Here we use functional magnetic resonance imaging to assess neural response to looming stimuli in comparison with receding stimuli and motion-controlled static stimuli. We demonstrate for the first time that, in the human, the superior colliculus and the pulvinar nucleus of the thalamus respond to looming in addition to cortical regions associated with motor preparation. We also implicate the anterior insula in making timing computations for collision events.
An Open Development Environment for Evaluation of Video Surveillance Systems

We introduce the publicly available Open Development for Video Surveillance (ODViS) system that is specifically designed to support ongoing research in tracking and video surveillance. The system provides researchers with the ability to prototype tracking and event recognition techniques, to construct and manage ground truth data sets, and to evaluate the performance of these systems within a graphical user interface. Passive tracking and video surveillance systems are receiving an increasing amount of research attention both in academic and industrial laboratories. Meaningful evaluation of these tracking and surveillance systems is an important but often difficult task. Recent introduction of standard datasets for video surveillance systems, and a corresponding dialog related to empirical analysis have made significant progress [1]. The ODViS system is designed to complement these efforts by providing an Application Programming Interface (API) that allows researchers to link specific surveillance modules into the ODViS framework, a graphical interface for visualizing the behavior of tracking algorithms, and a performance evaluation component that supports comparison of different surveillance modules to one another or predefined ground truth.
CHIPS: Custom Hardware Instruction Processor Synthesis

This paper describes an integer-linear-programming (ILP)-based system called custom hardware instruction processor synthesis (CHIPS) that identifies custom instructions for critical code segments, given the available data bandwidth and transfer latencies between custom logic and a baseline processor with architecturally visible state registers. Our approach enables designers to optionally constrain the number of input and output operands for custom instructions. We describe a design flow to identify promising area, performance, and code-size tradeoffs. We study the effect of input/output constraints, register-file ports, and compiler transformations such as if-conversion. Our experiments show that, in most cases, the solutions with the highest performance are identified when the input/output constraints are removed. However, input/output constraints help our algorithms identify frequently used code segments, reducing the overall area overhead. Results for 11 benchmarks covering cryptography and multimedia are shown, with speed-ups between 1.7 and 6.6 times, code-size reductions between 6% and 72%, and area costs ranging between 12 and 256 adders for maximum speed-up. Our ILP-based approach scales well: benchmarks with basic blocks consisting of more than 1000 instructions can be optimally solved, most of the time within a few seconds.
Modelling the unidentified mortality burden from thirteen infectious pathogenic microorganisms in infants

Official statistics routinely underestimate mortality from specific microorganisms and deaths are assigned to non-specific syndromes. Here we estimate mortality attributed to specific pathogens by modelling non-specific infant deaths from laboratory reports and codes on death certificates for these pathogens, 1993–2000 in England and Wales using a generalized linear model. In total, 22·4–59·8% of non-specific deaths in infants (25–66 deaths a year) are attributable to specific pathogens. Yearly deaths from Bordetella pertussis in neonates are 6·8 [95% confidence interval (CI) 1·5–11·9]. In post-neonates 9·4 (95% CI 2·3–16·6) deaths a year are attributable to Neisseria meningitidis, 7·3 (95% CI 2·4–12·3) to Streptococcus pneumoniae, from 2·8 (95% CI 0·8–4·9) to 15·1 (95% CI 9·4–20·9) to respiratory syncytial virus (RSV) and 3 (95% CI 0·3–5·9) to parainfluenza type 2. Our results suggest there is substantial hidden mortality for a number of pathogens in infants. A considerable proportion of deaths classified to infectious syndromes are non-infectious, suggesting low specificity of death certification. Laboratory reports were the more reliable source, reinforcing the asset of strong surveillance systems.
Unbiased reconstruction of the large-scale structure

ABSTRA C T We present a new unbiased minimal variance (UMV) estimator for the purpose of reconstructing the large-scale structure of the Universe from noisy, sparse and incomplete data. Similar to the Wiener filter (WF), the UMV estimator is derived by requiring the linear minimal variance solution given the data and an assumed a priori model specifying the underlying field covariance matrix. However, unlike the WF, the minimization is carried out with the added constraint of an unbiased reconstructed mean field. The new estimator does not necessitate a noise model to estimate the underlying field; however, such a model is required for evaluating the errors at each point in space. The general application of the UMV estimator is to predict the values of the reconstructed field in unsampled regions of space (e.g. interpolation in the unobserved Zone of Avoidance), and to dynamically transform from one measured field to another (e.g. inversion of radial peculiar velocities to over-densities). Here, we provide two very simple applications of the method. The first is to recover a 1D signal from noisy, convolved data with gaps, for example CMB time-ordered data. The second application is a reconstruction of the density and 3D peculiar velocity fields from mock SEcat galaxy peculiar velocity catalogues.
Compressed permuterm index

Recently [Manning et al., 2007] resorted the Permuterm indexof Garfield (1976) as a time-efficient and elegant solution to the string dictionary problem in which pattern queries may possibly include one wild-card symbol (called, Tolerant Retrieval problem). Unfortunately the Permuterm index is space inefficient because its quadruples the dictionary size. In this paper we propose the Compressed Permuterm Index which solves the Tolerant Retrieval problem in optimal query time, i.e. time proportional to the length of the searched pattern, and space close to the k-th order empirical entropy of the indexed dictionary. Our index can be used to solve also more sophisticated queries which involve several wild-card symbols, or require to prefix-match multiple fields in a database of records.The result is based on an elegant variant of the Burrows-Wheeler Transform defined on a dictionary of strings of variable length, which allows to easily adapt known compressed indexes [Makinen-Navarro, 2007] to solve the Tolerant Retrieval problem. Experiments show that our index supports fast queries within a space occupancy that is close to the one achievable by compressing the string dictionary via gzip, bzip or ppmdi. This improves known approaches based on front-coding by more than 50% in absolute space occupancy, still guaranteeing comparable query time.