Miracle-dz/UniFAR-FTUs huggingface dataset:
On estimating testing effort needed to assure field quality in software development

In practical software development, software quality is generally evaluated by the number of residual defects. To keep the number of residual defects within a permissible value, too much effort is often assigned to software testing. We try to develop a statistical model to determine the amount of testing effort which is needed to assure the field quality. The model explicitly includes design, review, and test (including debug) activities. Firstly, we construct a linear multiple regression model that can clarify the relationship among the number of residual defects and the efforts assigned to design, review, and test activities. We then confirm the applicability of the model by statistical analysis using actual project data. Next, we obtain an equation based on the model to determine the test effort. As parameters in the equation, the permissible number of residual defects, the design effort, and the review effort are included. Then, the equation determines the test effort that is needed to assure the permissible residual defects. Finally, we conduct an experimental evaluation using actual project data and show the usefulness of the equation.
An Essential Role ofS-Adenosyl-l-Methionine:l-MethionineS-Methyltransferase in Selenium Volatilization by Plants. Methylation of Selenomethionine to Selenium-Methyl-l-Selenium- Methionine, the Precursor of Volatile Selenium1

Selenium (Se) phytovolatilization, the process by which plants metabolize various inorganic or organic species of Se (e.g. selenate, selenite, and Se-methionine [Met]) into gaseous Se forms (e.g. dimethylselenide), is a potentially important means of removing Se from contaminated environments. Before attempting to genetically enhance the efficiency of Se phytovolatilization, it is essential to elucidate the enzymatic pathway involved and to identify its rate-limiting steps. The present research tested the hypothesis thatS-adenosyl-l-Met:l-MetS-methyltransferase (MMT) is the enzyme responsible for the methylation of Se-Met to Se-methyl Se-Met (SeMM). To this end, we identified and characterized an Arabidopsis T-DNA mutant knockout for MMT. The lack of MMT in the Arabidopsis T-DNA mutant plant resulted in an almost complete loss in its capacity for Se volatilization. Using chemical complementation with SeMM, the presumed enzymatic product of MMT, we restored the capacity of the MMT mutant to produce volatile Se. Overexpressing MMT from Arabidopsis in Escherichia coli, which is not known to have MMT activity, produced up to 10 times more volatile Se than the untransformed strain when both were supplied with Se-Met. Thus, our results provide in vivo evidence that MMT is the key enzyme catalyzing the methylation of Se-Met to SeMM.
Tuberous sclerosis complex as a model disease for developing new therapeutics for epilepsy

ABSTRACT An unmet need in the treatment of epilepsy has been targeted therapies that prevent the onset or progression of seizures in the susceptible individual. We have no treatments that target the process of epileptogenesis, through which the genetically predisposed or injured brain becomes capable of generating unprovoked, recurrent seizures. Tuberous Sclerosis Complex (TSC) is a multiorgan disorder caused by a defect in the mTOR (mechanistic/mammalian target of rapamycin) pathway. Epilepsy is a prominent feature of TSC, with seizures often occurring after the diagnosis of TSC has already been made. The mTOR pathway has been studied in animal models, with evidence suggesting that downstream effectors may contribute to the mechanisms leading to seizure generation, making the mTOR pathway an attractive candidate for potentially novel and rational antiepileptogenic therapies.
Instruments to measure behavioural and psychological symptoms of dementia: changing use over time

Reliable and valid measurement of behavioural and psychological symptoms of dementia (BPSD) is important for research and clinical practice. Here we provide an overview of the different instruments and discuss issues involved in the choice of the most appropriate instrument to measure BPSD in research. A list of BPSD instruments was generated. For each instrument Pubmed and SCOPUS were searched for articles that reported on their use or quality. Eighty-three instruments that are used to measure BPSD were identified. Instruments differ in length and detail, whether the interview is with participants, informants or by observation, the target sample and the time frames for use. Reliability and validity is generally good, but reported in few independent samples. When choosing a BPSD instrument for research the research question should be carefully scrutinised and the symptoms of interest, population, quality, detail, time frame and practical issues should be considered. Copyright © 2014 John Wiley & Sons, Ltd.
Automatic scale and image selection for panoramic images

We are presenting our work on automatic zoom level detection and minimal representative input frames subset selection for panoramic image applications. Thanks to the proposed techniques, the user can record videos from a single vantage point with free rotation and zooming motions, without a prohibitive recording time limit. The zoom level (or scale) of the input video frames are computed by mean-shift algorithm in a hierarchical structure. In order to select a minimal representative subset for excessive frames on a given zoom level, a greedy iterative algorithm is devised. Image matching is achieved by local image features and projective transformations. In addition to our recently proposed “Multi-scale Panoramic Augmented Reality” system, we expect the approach to be useful for other panoramic applications.
Segregation of eye and antenna fates maintained by mutual antagonism in Drosophila

A general question in development is how do adjacent primordia adopt different developmental fates and stably maintain their distinct fates? In Drosophila melanogaster, the adult eye and antenna originate from the embryonic eye-antenna primordium. These cells proliferate in the larval stage to form the eye-antenna disc. The eye or antenna differs at mid second instar with the restricted expression of Cut (Ct), a homeodomain transcriptional repressor, in the antenna disc and Eyeless (Ey), a Pax6 transcriptional activator, in the eye disc. In this study, we show that ey transcription in the antenna disc is repressed by two homeodomain proteins, Ct and Homothorax (Hth). Loss of Ct and Hth in the antenna disc resulted in ectopic eye development in the antenna. Conversely, the Ct and Hth expression in the eye disc was suppressed by the homeodomain transcription factor Sine oculis (So), a direct target of Ey. Loss of So in the eye disc caused ectopic antenna development in the eye. Therefore, the segregation of eye and antenna fates is stably maintained by mutual repression of the other pathway.
Categorial expert systems

Abstract: Expert systems can be used to determine some objects or consequences from uncertain knowledge by hierarchical categorization. Categorical representation is psychologically motivated and also offers an explanation of how to deal with uncertain knowledge based on counting during approximate reasoning. It is an alternative to other well‐known uncertainty calculi. A knowledge base which is used during approximate reasoning is represented by a taxonomical arrangement of verbal categories. Priming eases the formation of the final hypothesis, as more exact possible hypotheses are formed. The approximate reasoning is demonstrated on an expert system ‘Jurassic’ from the field of paleontology for the determination of a dinosaur species. It helps the paleontologist to determine creatures from uncertain knowledge. The system is composed of 423 rules arranged in a directed acyclic graph with a depth of 5. This knowledge is represented by a taxonomical arrangement of verbal categories represented by associative memories.
MOLECULAR ALTERATIONS ASSOCIATED WITH ANEURYSMAL REMODELING ARE LOCALIZED IN THE HIGH HEMODYNAMIC STRESS REGION OF A CREATED CAROTID BIFURCATION

OBJECTIVEAlthough elevated hemodynamics has been speculated to play a key role in intracranial aneurysm (IA) initiation, little is known about the specific hemodynamic microenvironment that triggers aneurysmal vascular degradation. We previously demonstrated maladaptive remodeling characteristic of IA initiation occurring in hemodynamic regions of combined high wall shear stress (WSS) and high WSS gradient near the apex of an experimentally created carotid bifurcation. This study examines whether this remodeling recapitulates the molecular changes found in IAs and whether molecular changes also correspond to specific hemodynamic environments. METHODSDe novo bifurcations were surgically created using both native common carotid arteries in each of 6 dogs. Bifurcations were imaged 2 weeks or 2 months after surgery by high-resolution 3-dimensional angiography, from which flow fields were obtained by computational fluid dynamics simulations. Subsequently, harvested tissues, demonstrating early aneurysmal changes near the apex, were immunostained for interleukin-1β, endothelial and inducible nitric oxide synthases, nitrotyrosine, and matrix metalloproteinase-2 and -9. Spatial distributions of these molecules were comapped with computational fluid dynamics results. RESULTSThe aneurysmal wall showed decreased endothelial nitric oxide synthase expression compared with surrounding segments, the feeding artery, and native controls, whereas all other markers increased. Anti-CD68 staining indicated the absence of inflammatory cells in the aneurysmal wall. Comapping molecular marker distributions with flow fields revealed confinement of these molecular changes within the hemodynamic region of high WSS and high, positive WSS gradient. CONCLUSIONAneurysm-initiating remodeling induced by combined high WSS and high, positive WSS gradient is associated with molecular changes implicated in IAs.
Predicting Rating of Amazon Fine Food from Reviews CSE 190 Assignment 2

The development of the Internet changed the way people eat and responding for food. Amazon is a biggest website where users can easily purchase all kind of food they need with only a mouse-click as well as there are many supportive ways for decision making. Most of the food have the ratings and reviews from other customers who have different backgrounds, cultures, eating habits, personalities, and prefer flavors. We, as the data analysis scientists, aim to create a predictive model, which is designed for predicting the rating of different food based on the data given, such as the time when the review was written, number of helpfulness voting, as well as the length of the review. In order to achieve the goal, we utilize the Amazon Fine Food Reviews dataset, which has some necessary features for us to analyze. We mine and analyze the data using the models, such as linear regression, ridge regression, and Latent-factor models, all of which we have learned from our CSE 190 Data Mining course. Eventually we want to build an acceptable model which helps us better understand how customers rate the food they purchased.
Generalized 2D Fisher Discriminant Analysis

To solve the Small Sample Size (SSS) problem, the recent linear discriminant analysis using the 2D matrix-based data representation model has demonstrated its superiority over that using the conventional vector-based data representation model in face recognition [7]. But the explicit reason why the matrix-based model is better than vectorized model has not been given until now. In this paper, a framework of Generalized 2D Fisher Discriminant Analysis (G2DFDA) is proposed. Three contributions are included in this framework: 1) the essence of these ’2D’ methods is analyzed and their relationships with conventional ’1D’ methods are given, 2) a Bilateral and 3) a Kernel-based 2D Fisher Discriminant Analysis methods are proposed. Extensive experiment results show its excellent performance.
On the Normalization of the Minimum Free Energy of RNAs by Sequence Length

The minimum free energy (MFE) of ribonucleic acids (RNAs) increases at an apparent linear rate with sequence length. Simple indices, obtained by dividing the MFE by the number of nucleotides, have been used for a direct comparison of the folding stability of RNAs of various sizes. Although this normalization procedure has been used in several studies, the relationship between normalized MFE and length has not yet been investigated in detail. Here, we demonstrate that the variation of MFE with sequence length is not linear and is significantly biased by the mathematical formula used for the normalization procedure. For this reason, the normalized MFEs strongly decrease as hyperbolic functions of length and produce unreliable results when applied for the comparison of sequences with different sizes. We also propose a simple modification of the normalization formula that corrects the bias enabling the use of the normalized MFE for RNAs longer than 40 nt. Using the new corrected normalized index, we analyzed the folding free energies of different human RNA families showing that most of them present an average MFE density more negative than expected for a typical genomic sequence. Furthermore, we found that a well-defined and restricted range of MFE density characterizes each RNA family, suggesting the use of our corrected normalized index to improve RNA prediction algorithms. Finally, in coding and functional human RNAs the MFE density appears scarcely correlated with sequence length, consistent with a negligible role of thermodynamic stability demands in determining RNA size.
Towards a Framework for Supporting Professional Teamwork: Modelling Human Actions in Small Group Meetings

Research into computer support for colocated small group meetings has not delivered any significant benefit in spite of significant investment and decades of research. We suggest that the focus has been on the wrong problem. Each time a process is enacted in small group work it will different (even if only slightly different) due to the situational context. Therefore the process for supporting the process should also be different each time and prescriptive, systematised support will be of little value in this situation. We propose that the processes must be exposed and identified dynamically so that useful support can be provided when it is required and one of the first steps is to understand what people are doing in these processes. The main contribution of this paper is a framework for helping researchers to understand the problem before considering a solution.
On the optimality of OFDM in multiuser multicarrier MIMO systems

Motivated by the increasing popularity of OFDMA and MIMO, this paper studies the optimality of OFDMA in MIMO enabled multiuser multicarrier frame- work. We show that in terms of achievable sum-rate, OFDMA with Gaussian input is the optimal downlink scheme when user cooperation is not available at either transmit or receiver side. To achieve the sum-rate bound however, the computational cost for finding the optimal so- lution is exponential with respect to the number of subcarri- ers and polynomial with respect to the number of users. To alleviate the complexity, we propose two suboptimal subcar- rier allocation criteria.The computation complexity of the suboptimal approaches grow only linearly with the num- ber of users and the number of subcarriers. Numerical re- sults are presented to compare the two subcarrier alloca- tion criteria with the optimal criterion. Specifically, it is observed that the Product-criterion is near optimal in high SNR regions while the Sum-criterion approaches optimal in low SNR regions.
Is ablation appropriate for management of benign thyroid nodules?

We read, with great interest, the recent paper by Mauri et al., entitled “Benign thyroid nodules treatment using percutaneous laser ablation (PLA) and radiofrequency ablation (RFA)” [1]. Since Dupuy et al. [2] published the application of radiofrequency ablation to treat recurrent thyroid cancers, radiofrequency ablation has been widely used for the treatment of benign thyroid goitres. However, there are some issues that must be clarified in the present article as follows:
The Glutamatergic Dysfunction Hypothesis for Schizophrenia

&NA; Schizophrenia is a syndrome, undoubtedly with multiple etiologies, that variably exhibits several features including positive and negative symptoms, cognitive deficits, onset in young adulthood, and deterioration from the previous level of function. This review will examine the growing evidence that dysfunction of corticolimbic glutamatergic neurotransmission may contribute to or account for the manifestations of schizophrenia. Glutamatergic neurons represent the primary excitatory afferent and efferent systems innervating the cortex, limbic regions, and striatum. The postsynaptic actions of glutamate are mediated by a family of glutamate‐gated ion channels that permit the influx of sodium and calcium, thereby depolarizing (exciting) neurons. One of these receptors, the W‐methyl‐D‐aspartate (NMDA) receptor, is the site of action of psychotomimetics such as phencyclidine and related anesthetics, which can reproduce in normal individuals most of the symptomatic features of schizophrenia. An endogenous antagonist at the NMDA receptor, W‐acetyl‐aspartyl glutamate, appears to have enhanced activity in the frontal cortex and hippo‐campal formation in persons with this disorder. Glutamatergic dysfunction may be particularly relevant to those forms of schizophrenia in which negative symptoms, cognitive deficits, and deterioration are prominent features. In support of this inference, clinical studies have shown that drugs that enhance NMDA‐receptor function reduce negative symptoms and cognitive deficits in persons with chronic schizophrenia who are receiving neuroleptics. Thus, dysfunction of glutamatergic neurotransmission represents an important organizational focus for research on the complex manifestations of schizophrenia.
Diagnostic cues for natural killer cell lymphoma: primary nodal presentation and the role of in situ hybridisation for Epstein-Barr virus encoded early small RNA in detecting occult bone marrow involvement

Natural killer (NK) cell lymphomas are rare, and atypical features might lead to diagnostic pitfalls. This report describes an unusual patient in whom lymphoma occurred initially as isolated lymph node involvement, an exceptional presentation of an almost exclusively extranodal disease. Furthermore, during the terminal haemophagocytosis in the bone marrow, lymphoma cells lost the expression of the NK cell marker, CD56, making the histopathological diagnosis of bone marrow involvement difficult. This was resolved by in situ hybridisation for Epstein-Barr virus encoded small RNA, which detected occult bone marrow infiltration.
Validation of Scale Measuring Environmental Barriers to Diabetes-Regimen Adherence

This study reports on the validation of a diabetesspecific measure of environmental barriers to regimen adherence. The reliability and validity of the environmental barriers to adherence scale (EBAS) were determined for a sample of 214 insulin-dependent and non-insulin-dependent diabetic patients. The scale was shown to be a valid measure of barriers to adherence as assessed by its relationship to the barriers to adherence questionnaire and the barriers to adherence portion of the diabetes-care profile. The medication, testing, exercise, and diet subscales of the EBAS were correlated with four corresponding and three noncorresponding measures of self-care behavior from the diabetes selfcare behaviors scale. Each subscale correlated well with its corresponding self-care behavior and less well with noncorresponding self-care behavior. The internal consistency of the scale and the test-retest reliability were found to be good. The results suggest that the EBAS scale is a valid, reliable measure of barriers to diabetes-regimen adherence.
Total Electron Emission Yield of Solar Cell Coverglass and Optical Solar Reflector

Electron-induced secondary electron (SE) emission from space insulating materials is a very important factor in understanding spacecraft charging behavior. Because of the injection of primary electrons (PEs) and the emission of SEs in the surface layer of insulating materials, the target surface can be either negatively or positively charged. In the conventional measurement methods, a single short, low-density pulsed e-beam, charge neutralization using low energy flood e-gun and UV light, and charge dissipation by heating is used. In this paper, a pulsed scanning method for the total electron emission yield measurement of insulating, semiconducting or conducting solid materials is proposed. A total electron detector with large hollow space and insulating spacer was designed, and a pulsed yield scanning measurement system was developed. This method can avoid influence from the charged surface of the insulating material. Using the system, the total SE emission yields of 200 nm thick Au coating on glass, and 11 kinds of solar cell coverglasses and optical solar reflectors produced by Qioptiq have been reported, as induced by a 30 μs pulse of PEs with ~ 20 nA incident beam current and energies up to 2500 eV.
A brief review: Speckle reducing filtering for ultrasound images

Speckle noise, which more commonly occurs in coherent imaging methods like as synthetic aperture radar, sonar, optical maser and ultrasound imaging, is undesirable final result of the image formation procedure in coherent imaging. In ultrasound imaging system, the presence of speckle results degradation in image quality and makes it tough for human interpretation and analysis. Consequently for examination of ultrasound images, speckle reduction is a very primary drawback. In the current era several methods for speckle suppression were proposed till now. Nevertheless in this paper, we've discussed model of speckle noise reduction with various filters that are basically used for speckle elimination. Different filters behave differently as few filters preserve the content material within the image and few filters provide smoothening process. Similarly some are better for edge detection and can be applied for tumor segmentation and so on. In the end, we have offered some regularly used filter assessment techniques.
Spectral properties of the kernel matrix and their relation to kernel methods in machine learning

This chapter serves as a brief introduction to the supervised learning setting and kernel methods. Moreover, several results from linear algebra, probability theory, and functional analysis are reviewed which will be used throughout the thesis. 2.1 Some notational conventions We begin by introducing some basic notational conventions. The sets N, Z, R, C denote the natural, integer, real, and complex numbers. Vectors will be denoted by lowercase letters, whereas matrices will be denoted by bold uppercase letters. Random variables will be denoted by uppercase letters. The individual entries of vectors and matrices are denoted by square brackets. For example, x ∈ R is a vector with coefficients [x]i. The matrix A has entries [A]ij . Vector and matrix transpose is denoted by x>. Sometimes, the set of square n × n matrices are denoted by Mn, and the set of general n × m matrices by Mn,m. The set of eigenvalues of a square matrix A is denoted by λ(A). For a symmetric n × n matrix A, we will always assume that the eigenvalues and eigenvectors are sorted in non-increasing order with eigenvalues repeated according to their multiplicity. The eigenvalues of A are thus λ1(A) ≥ . ≥ λn(A). We use the following standard norms on finite-dimensional vector spaces. Let x ∈ R and A ∈Mn. Then, ‖x‖ = √√√√ n ∑ i=1 [x]i , ‖A‖ = max x : ‖x‖6=0 ‖Ax‖ ‖x‖ . (2.1) A useful upper bound on ‖A‖ is given by ‖A‖ ≤ n max 1≤i,j≤n |[A]ij |. (2.2) Another matrix norm we will encounter is the Frobenius norm ‖A‖F = √√√√ n ∑