Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate Probit Analysis of Binary Time Series Data with Missing Responses

The development of adequate models for binary time series data with covariate adjustment has been an active research area in the last years. In the case, where interest is focused on marginal and association parameters, generalized estimating equations (GEE) (see for example Lipsitz, Laird and Harrington (1991) and Liang, Zeger and Qaqish (1992)) and likelihood (see for example Fitzmaurice and Laird (1993) and Molenberghs and Lesaffre (1994)) based methods have been proposed. The number of parameters required for the full specification of these models grows exponentially with the length of the binary time series. Therefore, the analysis is often focused on marginal and first order parameters. In this case, the multivariate probit model (Ashford and Sowden (1970)) becomes an attractive alternative to the above models. The application of the multivariate probit model has been hampered by the intractability of the maximum likelihood estimator, when the length of the binary time series is large. This paper shows that this difficulty can be overcome by the use of Markov Chain Monte Carlo methods. This analysis also allows for valid point and interval estimates of the parameters in small samples. In addition, the analysis is adopted to handle the case of missing at random responses. The approach is illustrated on data involving binary responses measured at unequally spaced time points. Finally, this data analysis is compared to a GEE analysis given in Fitzmaurice and Lipsitz (1995).
Standard-compliant simulation for self-organization schemes in LTE femtocells

Femtocells play a critical role in LTE and LTE-Advanced networks. Their particular advantage is realized by their autonomy in management and optimization. Our interest in this work is in a special category of self-optimization use cases overseeing femtocell handovers. Specifically, we present a flexible, extendable and standards-compliant environment written in MATLAB for studying handover related self-optimization schemes. The paper describes the overall structure and design of the environment, and offers a detailed explanation of the different modules involved. Sample results that validate the environment are also given. To the best of our knowledge, no such environment has been publicly accessible so far.
Optimal Features for Metamorphic Malware Detection

Malware or malicious code intends to harm computer systems without the knowledge of system users. These malicious softwares are unknowingly installed by naive users while browsing the Internet. Once installed, the malware performs unintentional activities like (a) steal username, password; (b) install spy software to provide remote access to the attackers; (c) flood spam messages; (d) perform denial of service attacks; etc. With the emergence of polymorphic and metamorphic malware, signature-based detectors are failing to detect new variants of these malware. The primary reason is that malicious code developed in new generation have different syntactic structures from their predecessor, thereby defeating any pattern matching techniques. Thus, the detection of morphed malware remains a complex open research problem for malware analysts. In this chapter, the authors discuss different types of malware with their detection methods. In addition, they present a proposed method employing machine learning techniques for the detection of metamorphic malware. The methodology demonstrates that appropriately selecting prominent features could improve the classification accuracy. The study also depicts that proposed methods that do not require signatures are effective in identifying and classifying morphed malware.
Heterosexism and homophobia in Scottish school sex education: exploring the nature of the problem.

This paper focuses on instances of heterosexism and homophobia, as well as examples of good practice in sex education, observed in 25 Scottish schools. Possible reasons for why good practice is not more widespread are explored. Qualitative and quantitative data are presented. Various constraints to good practice are identified by teachers, and are discussed in the context of survey data on pupil attitudes towards same-sex sexual relationships, and on teacher confidence in teaching about homosexuality.
Preparation of Colloidal Gold Immunochromatographic Strip for Detection of Paragonimiasis skrjabini

Background Paragonimiasis is a food-borne trematodiasis, a serious public health issue and a neglected tropical disease. Paragonimus skrjabini is a unique species found in China. Unlike paragonimiasis westermani, it is nearly impossible to make a definitive diagnosis for paragonimiasis skrjabini by finding eggs in sputum or feces. Immunodiagnosis is the best choice to detect paragonimiasis skrjabini. There is an urgent need to develop a novel, rapid and simple immunoassay for large-scale screening patients in endemic areas. Methodology/Principal Findings To develop a rapid, simple immunodiagnostic assay for paragonimiasis, rabbit anti-human IgG was conjugated to colloidal gold particles and used to detect antibodies in the sera of paragonimiasis patients. The synthesis and identification of colloidal gold particles and antibody-colloidal gold conjugates were performed. The size of colloidal gold particles was examined using a transmission electron microscope (TEM). The average diameter of colloidal gold particles was 17.46 nm with a range of 14.32–21.80 nm according to the TEM images. The formation of antibody-colloidal gold conjugates was monitored by UV/Vis spectroscopy. Excretory-secretory (ES) antigen of Paragonimus skrjabini was coated on nitrocellulose membrane as the capture line. Recombinant Staphylococcus protein A was used to prepare the control line. This rapid gold immunochromatographic strip was assembled in regular sequence through different accessories sticked on PVC board. The relative sensitivity and specificity of the strip was 94.4% (51/54) and 94.1% (32/34) respectively using ELISA as the standard method. Its stability and reproducibility were quite excellent after storage of the strip at 4°C for 6 months. Conclusions/Significance Immunochromatographic strip prepared in this study can be used in a rapid one-step immunochromatographic assay, which is instantaneous and convenient.
What’s New in Old Horses? Postmortem Diagnoses in Mature and Aged Equids

Postmortem findings in 241 equids admitted to a teaching hospital that were at least 15 years old at autopsy were reviewed (1) to determine disease prevalence, (2) to compare the cause of death (or euthanasia) in equids 15 to 19 years of age (n = 116) with that in equids ≥20 years of age (n = 125), and (3) to catalog coexisting lesions in equids with pituitary pars intermedia dysfunction (PPID). Breed and sex were evenly distributed between the age groups. Death or euthanasia was attributed to disease of the digestive system (41.5%), pituitary gland (12.9%), locomotor system (10.0%), nervous system (7.9%), cardiovascular system (4.6%), urinary system (4.6%), reproductive system (4.2%), respiratory system (4.2%), integumentary system (4.2%), lymphoid system (2.5%), liver (2.5%), or systemic neoplasia (1.2%). Nervous system disease was more common in the 15- to 19-year group; urinary tract disease was more common in the ≥20-year group. Neoplastic disease, regardless of systemic location, was the basis for death or euthanasia in 18.7% of all equids. Squamous cell carcinoma, lymphoma, and melanoma were the most common malignant neoplasms. PPID was the most common specific diagnosis, based on the postmortem presence of hyperplasia or adenoma, and was the reason for euthanasia in 47.7% of 65 equids with PPID. The most common nonpituitary causes for death or euthanasia in equids with PPID were colic, lameness, cancer, and spinal cord disease. Coexisting conditions in equids with PPID that were not considered the basis for euthanasia included neoplasms, infections, lameness, and recurrent airway obstruction.
Computer simulations of the restricted primitive model at very low temperature and density

The problem of successfully simulating ionic fluids at low temperature and low density states is well known in the simulation literature: using conventional methods, the system is not able to equilibrate rapidly due to the presence of strongly associated cation–anion pairs. In this paper we present a numerical method for speeding up computer simulations of the restricted primitive model (RPM) at low temperatures (around the critical temperature) and at very low densities (down to 10 − 10σ − 3, where σ is the ion diameter). Experimentally, this regime corresponds to typical concentrations of electrolytes in nonaqueous solvents. As far as we are aware, this is the first time that the RPM has been equilibrated at such extremely low concentrations. More generally, this method could be used to equilibrate other systems that form aggregates at low concentrations.
Predictive and Prognostic Molecular Biomarkers for Response to Neoadjuvant Chemoradiation in Rectal Cancer

The standard of care in locally advanced rectal cancer is neoadjuvant chemoradiation (nCRT) followed by radical surgery. Response to nCRT varies among patients and pathological complete response is associated with better outcome. However, there is a lack of effective methods to select rectal cancer patients who would or would not have a benefit from nCRT. The utility of clinicopathological and radiological features are limited due to lack of adequate sensitivity and specificity. Molecular biomarkers have the potential to predict response to nCRT at an early time point, but none have currently reached the clinic. Integration of diverse types of biomarkers including clinicopathological and imaging features, identification of mechanistic link to tumor biology, and rigorous validation using samples which represent disease heterogeneity, will allow to develop a sensitive and cost-effective molecular biomarker panel for precision medicine in rectal cancer. Here, we aim to review the recent advance in tissue- and blood-based molecular biomarker research and illustrate their potential in predicting nCRT response in rectal cancer.
Hadoop-BAM: directly manipulating next generation sequencing data in the cloud

Summary: Hadoop-BAM is a novel library for the scalable manipulation of aligned next-generation sequencing data in the Hadoop distributed computing framework. It acts as an integration layer between analysis applications and BAM files that are processed using Hadoop. Hadoop-BAM solves the issues related to BAM data access by presenting a convenient API for implementing map and reduce functions that can directly operate on BAM records. It builds on top of the Picard SAM JDK, so tools that rely on the Picard API are expected to be easily convertible to support large-scale distributed processing. In this article we demonstrate the use of Hadoop-BAM by building a coverage summarizing tool for the Chipster genome browser. Our results show that Hadoop offers good scalability, and one should avoid moving data in and out of Hadoop between analysis steps. Availability: Available under the open-source MIT license at http://sourceforge.net/projects/hadoop-bam/ Contact: matti.niemenmaa@aalto.fi Supplementary information: Supplementary material is available at Bioinformatics online.
Getting More Out of Less – A Quantitative Serological Screening Tool for Simultaneous Detection of Multiple Influenza A Hemagglutinin-Types in Chickens

Current avian influenza surveillance in poultry primarily targets subtypes of interest for the veterinary sector (H5, H7). However, as virological and serological evidence suggest, surveillance of additional subtypes is important for public health as well as for the poultry industry. Therefore, we developed a protein microarray enabling simultaneous identification of antibodies directed against different HA-types of influenza A viruses in chickens. The assay successfully discriminated negative from experimentally and naturally infected, seropositive chickens. Sensitivity and specificity depended on the cut-off level used but ranged from 84.4% to 100% and 100%, respectively, for a cut off level of ≥1∶40, showing minimal cross reactivity. As this testing platform is also validated for the use in humans, it constitutes a surveillance tool that can be applied in human-animal interface studies.
Properties of a thermotropic liquid crystalline polymer blended with different thermoplastics

Thermal, rheological, morphological, and mechanical properties of a thermotropic liquid crystalline polymer, TLCP (copolyester Vectra A-950 from Hoechst), blended with a polycarbonate (PC), a polyethylene glycol terephthalate (PETG), and a blend of PC and PETG (20/80) are presented and discussed. Important supercooling effects are observed for the TLCP. For the blends the Gass transition temperature of the matrix is shown to decrease slightly, suggesting partial miscibility of the components
The replicometer is broken: telomeres activate cellular senescence in response to genotoxic stresses

Telomeres, the ends of our linear chromosomes, can function as ‘replicometers’, capable of counting cell division cycles as they progressively erode with every round of DNA replication. Once they are critically short, telomeres become dysfunctional and consequently activate a proliferative arrest called replicative senescence. For many years, telomeres were thought to be autonomous structures, largely isolated from cell intrinsic and extrinsic signals, whose function is to prevent limitless cellular proliferation, a characteristic of most cancer cells. It is becoming increasingly evident, however, that telomeres not only count cell divisions, but also function as sensors of genotoxic stresses to stop cell cycle progression prematurely and long before cells would have entered replicative senescence. This stable growth arrest, triggered by dysfunctional telomeres that are not necessarily critically short, likely evolved as a tumor‐suppressing mechanism as it prevents proliferation of cells that are at risk for acquiring potentially hazardous and transforming mutations both in vitro and in vivo. Here, we review studies supporting the concept that telomeres are important cellular structures whose function not only is to count cell divisions, but also to act as molecular switches that can rapidly stop cell cycle progression permanently in response to a variety of stresses, including oncogenic signals.
Stem cell myths

Stem cells, although difficult to define, hold great promise as tools for understanding development and as therapeutic agents. However, as with any new field, uncritical enthusiasm can outstrip reality. In this review, we have listed nine common myths that we believe affect our approach to evaluating stem cells for therapy. We suggest that careful consideration needs to be given to each of these issues when evaluating a particular cell for its use in therapy. Data need to be collected and reported for failed as well as successful experiments and a rigorous scientific approach taken to evaluate the undeniable promise of stem cell biology.
High order derivatives and decomposition of multivariate polynomials

In this paper, we present an improved method for decomposing multivariate polynomials. This problem, also known as the Functional Decomposition Problem (FDP) [17, 9, 27], is classical in computer algebra (e.g. [17, 18, 19, 23, 24, 7, 25]). Here, we propose to use high order partial derivatives to improve the algorithm described in [14]. Our new approach is more simple, and in some sense more natural. From a practical point of view, this new approach will lead to more efficient algorithms. The complexity of our algorithms will depend of the degree of the input polynomials, and the ratio n/u between the number of variables/polynomials.
Fundamental Technologies in Modern Speech Recognition Distant Speech Recognition Holds the Promise of the Most Natural Human Computer Interface Because It Enables Man-machine Interactions through Speech

D istant speech recognition (DSR) holds the promise of the most natural human computer interface because it enables man-machine interactions through speech, without the necessity of donning intrusive body-or head-mounted microphones. Recognizing distant speech robustly, however, remains a challenge. This contribution provides a tutorial overview of DSR systems based on microphone arrays. In particular, we present recent work on acoustic beamforming for DSR, along with experimental results verifying the effectiveness of the various algorithms described here; beginning from a word error rate (WER) of 14.3% with a single microphone of a linear array, our state-of-the-art DSR system achieved a WER of 5.3%, which was comparable to that of 4.2% obtained with a lapel microphone. Moreover, we present an emerging technology in the area of far-field audio and speech processing based on spherical microphone arrays. Performance comparisons of spherical and linear arrays reveal that a spherical array with a diameter of 8.4 cm can provide recognition accuracy comparable or better than that obtained with a large linear array with an aperture length of 126 cm. INTRODUCTION When the signals from the individual sensors of a microphone array with a known geometry are suitably combined, the array [ From close-talking microphones to far-field sensors ] functions as a spatial filter capable of suppressing noise, reverberation, and competing speech. Such beamforming techniques have received a great deal of attention within the acoustic array processing community in the recent past [1]– [7]. Despite this effort, however, such techniques have often been ignored within the mainstream community working on DSR. As pointed out in [6] and [7], this could be due to the fact that the disparate research communities for acoustic array processing and automatic speech recognition (ASR) have failed to adopt each other's best practices. For instance, the array processing community tends to ignore speaker adaptation techniques, which can compensate for mismatches between acoustic conditions during training and testing. Moreover, this community has largely preferred to work on controlled, synthetic recordings, obtained by convolving noise-and reverberation-free speech with measured, static room impulse responses, with subsequent artificial addition of which featured actual array recordings of real speakers; this task, however , has fallen out of favor, to the extent that it is currently not even mentioned on the PASCAL CHiME Challenge Web site, nor in any of the concomitant publications. This is unfortunate because improvements obtained with novel speech enhancement techniques tend to diminish, or …
Differential effects of tetracaine on charge movements and Ca2+ signals in frog skeletal muscle

The effects of tetracaine on charge movements and on antipyrylazo III signals monitoring intracellular delta [Ca2+] were compared in cut frog semitendinosus muscle fibers in a single vaseline gap-voltage clamp. Low tetracaine concentrations (25-40 microM) markedly reduced delta [Ca2+] signals and shifted the rheobase. However, they neither influenced charge movement nor that peak delta [Ca2+] value associated with the contractile threshold. Higher tetracaine concentrations (100- 200 microM) partly inhibited charge movements in cut fibers. They separated a steeply voltage-sensitive charge, some of whose features resembled 'q gamma' reported in intact fibers, and whose movement preceded delta [Ca2+] signals at threshold. These findings: (a) directly confirm an earlier suggestion that tetracaine acts on steps in excitation-contraction coupling rather than myofilament activation; (b) show that tetracaine at low concentrations can directly interfere with sarcoplasmic reticular calcium release without modifying charge movement; (c) show that the tetracaine-sensitive charge, first found in intact fibers, also exists in cut fibers; and (d) make it unlikely that tetracaine-sensitive charge transfer is a consequence of Ca2+ release as suggested on earlier occasions.
Wnts Enhance Neurotrophin-Induced Neuronal Differentiation in Adult Bone-Marrow-Derived Mesenchymal Stem Cells via Canonical and Noncanonical Signaling Pathways

Wnts were previously shown to regulate the neurogenesis of neural stem or progenitor cells. Here, we explored the underlying molecular mechanisms through which Wnt signaling regulates neurotrophins (NTs) in the NT-induced neuronal differentiation of human mesenchymal stem cells (hMSCs). NTs can increase the expression of Wnt1 and Wnt7a in hMSCs. However, only Wnt7a enables the expression of synapsin-1, a synaptic marker in mature neurons, to be induced and triggers the formation of cholinergic and dopaminergic neurons. Human recombinant (hr)Wnt7a and general neuron makers were positively correlated in a dose- and time-dependent manner. In addition, the expression of synaptic markers and neurites was induced by Wnt7a and lithium, a glycogen synthase kinase-3β inhibitor, in the NT-induced hMSCs via the canonical/β-catenin pathway, but was inhibited by Wnt inhibitors and frizzled-5 (Frz5) blocking antibodies. In addition, hrWnt7a triggered the formation of cholinergic and dopaminergic neurons via the non-canonical/c-jun N-terminal kinase (JNK) pathway, and the formation of these neurons was inhibited by a JNK inhibitor and Frz9 blocking antibodies. In conclusion, hrWnt7a enhances the synthesis of synapse and facilitates neuronal differentiation in hMSCS through various Frz receptors. These mechanisms may be employed widely in the transdifferentiation of other adult stem cells.
Atmospheric Effects on InSAR Measurements and Their Mitigation

Interferometric Synthetic Aperture Radar (InSAR) is a powerful technology for observing the Earth surface, especially for mapping the Earth's topography and deformations. InSAR measurements are however often significantly affected by the atmosphere as the radar signals propagate through the atmosphere whose state varies both in space and in time. Great efforts have been made in recent years to better understand the properties of the atmospheric effects and to develop methods for mitigating the effects. This paper provides a systematic review of the work carried out in this area. The basic principles of atmospheric effects on repeat-pass InSAR are first introduced. The studies on the properties of the atmospheric effects, including the magnitudes of the effects determined in the various parts of the world, the spectra of the atmospheric effects, the isotropic properties and the statistical distributions of the effects, are then discussed. The various methods developed for mitigating the atmospheric effects are then reviewed, including the methods that are based on PSInSAR processing, the methods that are based on interferogram modeling, and those that are based on external data such as GPS observations, ground meteorological data, and satellite data including those from the MODIS and MERIS. Two examples that use MODIS and MERIS data respectively to calibrate atmospheric effects on InSAR are also given.
Acceleration for RPM-based three-dimensional imaging for 140 GHz-band millimeter wave radar

140 GHz-band millimeter wave radars significantly expands the appilication range of three-dimensional (3-D) imaging sensors, making them suitable for short-range surveillance or watching sensors. The range points migration(RPM) is recently established as promising imaging approach for achieving an accurate and real-time 3-D imaging. However, in dealing with objects with many scattering points like human body, the RPM suffers from an expensive computational cost. This paper proposes an acceleration of the RPM method, based on the newly designed cost function for multiple small array conflagrations. The results from 140 GHz based numerical data demonstrate that our proposed algorithm remarkably reduces the computational cost without sacrificing its reconstruction accuracy.