Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward a measure of classification complexity in gene expression signatures

Gene expression signatures identify important genes that predict a specified outcome. In several notable diseases such as leukemia and breast cancer, the results have been encouraging. In these datasets, many techniques work well when discriminating particular outcomes. However, these same methods, applied to other datasets, are unable to achieve similar levels of success. Given the small sample sizes common to these studies and the large dimensionality of the data, several key issues exist when attempting to construct reliable, reproducible gene signatures. The classifiers may not be sufficient to discriminate classes, or the data itself may not be sufficient to produce effective separation. In this paper, three simple measures of classification complexity are considered to explore a limit to the predictive accuracy that can be achieved in a dataset. Two independent gene expression datasets (lung and colorectal cancer) are considered, using three different outcomes on each dataset. Four different classifiers, using the t-test for feature selection, were tested on these datasets as a representative panel of classifiers. Our results indicate that Fisher's discriminant ratio provides a good measure of the complexity of the classification problem, with a high correlation between complexity and best classification accuracy across all problems (R2=0.78). Specifically, predicting gender is a low complexity problem as indicated both by the complexity measure and the classification results. More clinically-oriented endpoints are more complex and have lower classification accuracies. Therefore, classification complexity can be used to estimate maximum attainable accuracy for a problem reducing the need to evaluate many different classifiers.
New Views of the Learner: Implications for Instruction and Curriculum.

"If you can be moved to try these ideas with a few teachers in your school for even as short a period as three months, you can determine the validity and limits of these ideas where they really belong—in your classrooms and with your teachers and students. Even more important, I hope this conception of education and of the enormous potentials of our students and schools will inspire you and your teachers to strive toward a renewed and attainable dream of American education during the remainder of this century. '
Towards dynamic MPTCP Path control using SDN

MPTCP (MultiPath TCP) boosts application network performance by aggregating bandwidth over multiple paths. However, it may cause poor performance due to the large number of out-of-order packets especially when the paths have different delays. To resolve this issue, we propose to dynamically add or remove MPTCP paths with the leverage of software-defined networking (SDN). The key idea is to track the available capacity of connected paths and pick the most appropriate paths depending on varying network conditions. To show the feasibility of our approach, we create an SDN platform using Mininet over Wi-Fi networks. Our analysis shows that a faster download and improved quality of experience (QoE) in adaptive rate video streaming is possible with our dynamic MPTCP path control mechanism using SDN.
Comparison of 3-dimensional and 1-dimensional schemes in the calculation of atmospheric neutrinos

A 3-dimensional calculation of atmospheric neutrino flux is presented, and the results are compared with those of a 1-dimensional calculation. In this study, the interaction and propagation of particles is treated in a 3-dimensional way including the curvature of charged particles due to the geomagnetic field, which is assumed to be a dipole field. The purpose of this paper is limited to the comparison of calculation schemes. The updated flux value with a new interaction model and primary flux model will be reported in a separate paper. Except for nearly horizontal directions, the flux is very similar to the result of 1-dimensional calculations. However, for near-horizontal directions an enhancement of the neutrino flux is seen even at energies as high as 1 GeV. The production height of neutrinos is lower than the prediction of the 1-dimensional calculation for near-horizontal directions, and is a little higher for near-vertical directions. However, the difference is not evident except for near-horizontal directions.
Quantum rotations: a case study in static and dynamic machine-code generation for quantum computers

Work in quantum computer architecture has focused on communication, layout and fault tolerance, largely driven by Shor's factorization algorithm. For the first time, we study a larger range of benchmarks and find that another critical issue is the generation of code sequences for quantum rotation operations. Specifically, quantum algorithms require arbitrary rotation angles, while quantum technologies and error correction codes provide only for discrete angles and operators. A sequence of quantum machine instructions must be generated to approximate the arbitrary rotation to the required precision. While previous work has focused exclusively on static compilation, we find that some applications require dynamic code generation and explore the advantages and disadvantages of static and dynamic approaches. We find that static code generation can, in some cases, lead to a terabyte of machine code to support required rotations. We also find that some rotation angles are unknown until run time, requiring dynamic code generation. Dynamic code generation, however, exhibits significant trade-offs in terms of time overhead versus code size. Furthermore, dynamic code generation will be performed on classical (non-quantum) computing resources, which may or may not have a clock speed advantage over the target quantum technology. For example, operations on trapped ions run at kilohertz speeds, but superconducting qubits run at gigahertz speeds. We introduce a new method for compiling arbitrary rotations dynamically, designed to minimize compilation time. The new method reduces compilation time by up to five orders of magnitude while increasing code size by one order of magnitude. We explore the design space formed by these trade-offs of dynamic versus static code generation, code quality, and quantum technology. We introduce several techniques to provide smoother trade-offs for dynamic code generation and evaluate the viability of options in the design space.
The Environments of High Redshift QSOs

We present a sample of $i_{775}$-dropout candidates identified in five Hubble Advanced Camera for Surveys fields centered on Sloan Digital Sky Survey QSOs at redshift $z\sim 6$. Our fields are as deep as the Great Observatory Origins Deep Survey (GOODS) ACS images which are used as a reference field sample. We find them to be overdense in two fields, underdense in two fields, and as dense as the average density of GOODS in one field. The two excess fields show significantly different color distributions from that of GOODS at the 99% confidence level, strengthening the idea that the excess objects are indeed associated with the QSO. The distribution of $i_{775}$-dropout counts in the five fields is broader than that derived from GOODS at the 80% to 96% confidence level, depending on which selection criteria were adopted to identify $i_{775}$-dropouts; its width cannot be explained by cosmic variance alone. Thus, QSOs seem to affect their environments in complex ways. We suggest the picture where the highest redshift QSOs are located in very massive overdensities and are therefore surrounded by an overdensity of lower mass halos. Radiative feedback by the QSO can in some cases prevent halos from becoming galaxies, thereby generating in extreme cases an underdensity of galaxies. The presence of both enhancement and suppression is compatible with the expected differences between lines of sight at the end of reionization as the presence of residual diffuse neutral hydrogen would provide young galaxies with shielding from the radiative effects of the QSO.
A Cyclic Vernier TDC for ADPLLs Synthesized From a Standard Cell Library

This paper presents a cyclic Vernier time-to-digital converter (TDC) with digitally controlled oscillators (DCOs), targeted for a synthesizable all-digital phase locked loop (ADPLL). All functional blocks in the TDC are implemented with digital standard cells and placed-and-routed (P&R) by automatic design tools; thus, the TDC is portable and scalable to other process technologies. The effect of P&R mismatch is characterized in calibration mode, and utilized to achieve a minimum TDC resolution of 5.5 ps. The TDC was fabricated in a 65 nm CMOS process, and occupies 0.006 mm2.
DEVELOPMENT OF THE GONIO RADIOMETRIC SPECTROMETER SYSTEM TO CONDUCT MULTI-ANGULAR MEASUREMENTS OF TERRESTRIAL SURFACES

The requirement for reliability and confidence in Earth Observation data is being recognised by many international organisations e.g. WMO and CEOS, the latter of which endorsed two recommendations at its 14 th plenary, which stated that; pre-launch calibration should be performed using equipment and techniques that can be demonstrably traceable to, and consistent with, the SI system of units, and traceability should be maintained throughout the lifetime of the mission, and more recently in a white paper submitted to CEOS plenary 19 summarising CEOS WGCV activities and plans in support of GEOSS. Increasingly, satellites have the capability of measuring surfaces at multiple angles. Due to the variations in slope angle and aspect, there are only a few remotely sensed data sets which are immune to multi-angular effects. To improve the accuracy and traceability of multi-angular field measurements, a new instrument has been designed, in conjunction with the Natural Environmental Research Council (UK) Field Spectroscopy Facility (FSF). The Gonio RAdiometric Spectrometer System (GRASS) is being developed at the National Physical Laboratory, in the Optical Technologies and Scientific Computing Team. It is intended to provide quasi-simultaneous, multi-angle, multi-spectral measurements of Earth surface reflected sunlight to support vicarious calibration of satellite sensors operating in the optical region. The GRASS instrument was first deployed in June 2006 as part of an experiment organised by Network for the Calibration and Validation of Earth Observation data (NCAVEO), this paper will summarise the recent developments of the GRASS instrument, and its initial deployment at the NCAVEO Field Experiment. * Corresponding author.
Automatic Acronym Recognition

This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym recognition task and compares and evaluates the results of different machine learning algorithms on the same task. The method proposed is based on the approach that acronym-definition pairs follow a set of patterns and other regularities that can be usefully applied for the acronym identification task. Supervised machine learning was applied to monitor the performance of the rule-based method, using Memory Based Learning (MBL). The rule-based algorithm was evaluated on a hand tagged acronym corpus and performance was measured using standard measures recall, precision and f-score. The results show that performance could further improve by increasing the training set and modifying the input settings for the machine learning algorithms. An analysis of the errors produced indicates that further improvement of the rule-based method requires the use of syntactic information and textual pre-processing.
Discovery Mechanisms for the Sensor Web

This paper addresses the discovery of sensors within the OGC Sensor Web Enablement framework. Whereas services like the OGC Web Map Service or Web Coverage Service are already well supported through catalogue services, the field of sensor networks and the according discovery mechanisms is still a challenge. The focus within this article will be on the use of existing OGC Sensor Web components for realizing a discovery solution. After discussing the requirements for a Sensor Web discovery mechanism, an approach will be presented that was developed within the EU funded project “OSIRIS”. This solution offers mechanisms to search for sensors, exploit basic semantic relationships, harvest sensor metadata and integrate sensor discovery into already existing catalogues.
LIMES - A Time-Efficient Approach for Large-Scale Link Discovery on the Web of Data

The Linked Data paradigm has evolved into a powerful enabler for the transition from the document-oriented Web into the Semantic Web. While the amount of data published as Linked Data grows steadily and has surpassed 25 billion triples, less than 5% of these triples are links between knowledge bases. Link discovery frameworks provide the functionality necessary to discover missing links between knowledge bases. Yet, this task requires a significant amount of time, especially when it is carried out on large data sets. This paper presents and evaluates LIMES, a novel time-efficient approach for link discovery in metric spaces. Our approach utilizes the mathematical characteristics of metric spaces during the mapping process to filter out a large number of those instance pairs that do not suffice the mapping conditions. We present the mathematical foundation and the core algorithms employed in LIMES. We evaluate our algorithms with synthetic data to elucidate their behavior on small and large data sets with different configurations and compare the runtime of LIMES with another state-of-the-art link discovery tool.
Latent max-margin metric learning for comparing video face tubes

Comparing “face tubes” is a key component of modern systems for face biometrics based video analysis and annotation. We present a novel algorithm to learn a distance metric between such spatio-temporal face tubes in videos. The main novelty in the algorithm is based on incorporation of latent variables in a max-margin metric learning framework. The latent formulation allows us to model, and learn metrics to compare faces under different challenging variations in pose, expressions and lighting. We propose a novel dataset named TV Series Face Tubes (TSFT) for evaluating the task. The dataset is collected from 12 different episodes of 8 popular TV series and has 94 subjects with 569 manually annotated face tracks in total. We show quantitatively how incorporating latent variables in max-margin metric learning leads to improvement of current state-of-the-art metric learning methods for the two cases when the testing is done with subjects that were seen during training and when the test subjects were not seen at all during training. We also give results on a challenging benchmark dataset: YouTube faces, and place our algorithm in context w.r. t. existing methods.
A Comprehensive Survey of Recent Advancements in Molecular Communication

With much advancement in the field of nanotechnology, bioengineering, and synthetic biology over the past decade, microscales and nanoscales devices are becoming a reality. Yet the problem of engineering a reliable communication system between tiny devices is still an open problem. At the same time, despite the prevalence of radio communication, there are still areas where traditional electromagnetic waves find it difficult or expensive to reach. Points of interest in industry, cities, and medical applications often lie in embedded and entrenched areas, accessible only by ventricles at scales too small for conventional radio waves and microwaves, or they are located in such a way that directional high frequency systems are ineffective. Inspired by nature, one solution to these problems is molecular communication (MC), where chemical signals are used to transfer information. Although biologists have studied MC for decades, it has only been researched for roughly 10 year from a communication engineering lens. Significant number of papers have been published to date, but owing to the need for interdisciplinary work, much of the results are preliminary. In this survey, the recent advancements in the field of MC engineering are highlighted. First, the biological, chemical, and physical processes used by an MC system are discussed. This includes different components of the MC transmitter and receiver, as well as the propagation and transport mechanisms. Then, a comprehensive survey of some of the recent works on MC through a communication engineering lens is provided. The survey ends with a technology readiness analysis of MC and future research directions.
Assessment of anti-CarP antibodies, disease activity and quality of life in rheumatoid arthritis patients on conventional and biological disease-modifying antirheumatic drugs

Objective Good biomarkers are important to guide decisions in the clinical management of rheumatoid arthritis (RA). RA patients harbor antibodies directed against carbamylated proteins which may predict joint damage. This study investigated whether antibodies against carbamylated proteins (anti-CarP) may serve as surrogate prognostic markers. Material and methods Fifty-three patients with a diagnosis of rheumatoid arthritis according to ACR 1987 criteria were included. Blood samples were analyzed for CarP antibody levels using the ELISA method. Quality of life (QoL) was assessed by the WHO SF-36 questionnaire, and disease activity was assessed using the DAS28 calculator. Newly diagnosed patients were assessed at the first visit and at 12 weeks of treatment, while a single assessment was made for patients already on maintenance therapy. Results Out of 53 patients, 22 had titers of anti-CarP above the cut-off range and considered as positive for anti-CarP antibodies. Anti-CarP antibody serum level was significantly higher in patients with deformity of joints and with erosions in comparison to those without any destructive changes (p < 0.05). There was a weak positive correlation between anti-CarP and DAS 28 (p > 0.05). Also there was a weak negative correlation in all domains of quality of life with anti-CarP antibody titers (p > 0.05). There was no significant correlation between titers of anti-CarP antibodies and presence or absence of rheumatoid factor. Conclusions Serum levels of anti-CarP antibodies in RA patients with joint erosions/deformities were much higher than in those without any joint damage. Anti-CarP antibodies may have good prognostic value in RA patients with erosions. Disease activity and QoL of RA patients improved during treatment, but no correlation was found between DAS 28/QoL and anti-CarP antibody serum levels.
A solution of missing value in collaborative filtering recommendation algorithm

In order to solve the sparsity of User-Item scoring matrix in collaborative fIltering recommendation, proposed an algorithm that combining user's interests with item's quality to calculate ungraded items in matrix. By setting the weight of user and item, synthesized the value of missing value, which were used to replace the ungraded value in scoring matrix to calculate similarity. Experiment shows that the algorithm can improve the recommendation effect, and when the user's weight values 0.4, MAE reaches minimum, and recommendation quality reaches maximum.
Histone H3.3 regulates dynamic chromatin states during spermatogenesis

The histone variant H3.3 is involved in diverse biological processes, including development, transcriptional memory and transcriptional reprogramming, as well as diseases, including most notably malignant brain tumors. Recently, we developed a knockout mouse model for the H3f3b gene, one of two genes encoding H3.3. Here, we show that targeted disruption of H3f3b results in a number of phenotypic abnormalities, including a reduction in H3.3 histone levels, leading to male infertility, as well as abnormal sperm and testes morphology. Additionally, null germ cell populations at specific stages in spermatogenesis, in particular spermatocytes and spermatogonia, exhibited increased rates of apoptosis. Disruption of H3f3b also altered histone post-translational modifications and gene expression in the testes, with the most prominent changes occurring at genes involved in spermatogenesis. Finally, H3f3b null testes also exhibited abnormal germ cell chromatin reorganization and reduced protamine incorporation. Taken together, our studies indicate a major role for H3.3 in spermatogenesis through regulation of chromatin dynamics.
Direction of Arrival Based Spatial Covariance Model for Blind Sound Source Separation

This paper addresses the problem of sound source separation from a multichannel microphone array capture via estimation of source spatial covariance matrix (SCM) of a short-time Fourier transformed mixture signal. In many conventional audio separation algorithms the source mixing parameter estimation is done separately for each frequency thus making them prone to errors and leading to suboptimal source estimates. In this paper we propose a SCM model which consists of a weighted sum of direction of arrival (DoA) kernels and estimate only the weights dependent on the source directions. In the proposed algorithm, the spatial properties of the sources become jointly optimized over all frequencies, leading to more coherent source estimates and mitigating the effect of spatial aliasing at high frequencies. The proposed SCM model is combined with a linear model for magnitudes and the parameter estimation is formulated in a complex-valued non-negative matrix factorization (CNMF) framework. Simulations consist of recordings done with a hand-held device sized array having multiple microphones embedded inside the device casing. Separation quality of the proposed algorithm is shown to exceed the performance of existing state of the art separation methods with two sources when evaluated by objective separation quality metrics.
Ergosterol-Induced Sesquiterpenoid Synthesis in Tobacco Cells

Plants have the ability to continuously respond to microbial signals in their environment. One of these stimuli is a steroid from fungal membranes, ergosterol, which does not occur in plants, but acts as a pathogen-associated molecular pattern molecule to trigger defence mechanisms. Here we investigated the effect of ergosterol on the secondary metabolites in tobacco (Nicotiana tabacum) cells by profiling the induced sesquiterpenoids. Suspensions of tobacco cells were treated with different concentrations (0–1,000 nM) of ergosterol and incubated for different time periods (0–24 h). Metabolites were extracted with a selective dispersive liquid-liquid micro-extraction method. Thin layer chromatography was used as a screening method for identification of sesquiterpenoids in tobacco extracts. Liquid chromatography coupled to mass spectrometry was used for quantitative and qualitative analyses. The results showed that ergosterol triggered differential changes in the metabolome of tobacco cells, leading to variation in the biosynthesis of secondary metabolites. Metabolomic analysis through principal component analysis-scores plots revealed clusters of sample replicates for ergosterol treatments of 0, 50, 150, 300 and 1,000 nM and time-dependent variation at 0, 6, 12, 18 and 24 h. Five bicyclic sesquiterpenoid phytoalexins, capsidiol, lubimin, rishitin, solavetivone and phytuberin, were identified as being ergosterol-induced, contributing to the altered metabolome.