Miracle-dz/UniFAR-FTUs huggingface dataset:
Rewriting XQuery to Avoid Redundant Expressions based on Static Emulation of XML Store

Rewriting composite expressions based on eliminating intermediate results generated by redundant expressions is a traditional optimization technique (known as fusion) in both programming languages community and database community. In XQuery, composite expressions for node creation are typical in practice, for example, in data integration systems for XML with XQuery as schema mapping. We propose a fusion algorithm for this kind of composite XQuery. The XQuery fusion is more difficult than the existing fusion, because naive elimination of node creations does not preserve document order. The document order plays an important role in XQuery. An XQuery expression is evaluated against an XML store which contains XML fragments that are created as intermediate results, in addition to initial XML documents with their document order. So, the XML store is updated as the expression with node creations is evaluated. In this paper, we show that XML fragments created dynamically as intermediate results in a store can be emulated statically in such a way that rewriting XQuery to avoid redundant expressions is enabled. This emulation is achieved by using an adornment code called extended Dewey’s assigned to the occurrences of expressions. By using this static emulation, our XQuery fusion avoids unnecessary expressions including node creations while preserving the document order in XML.
Requirements comprehension: A controlled experiment on conceptual modeling methods

Several Requirements Engineering (RE) methods have been proposed to analyze and model requirements specifications. However, these methods have often been only partially evaluated and few attempts exist in literature to study and evaluate RE methods through experiments. In this paper, we document an empirical study that has been performed to evaluate the comprehension of requirements which were expressed in Tropos4AS. Tropos4AS specializes the goal-oriented software engineering methodology Tropos for the case of self-adaptive systems. In the experiment, we asked subjects to perform comprehension tasks on requirements specifications expressed in Tropos4AS and in Tropos, respectively. Results show that Tropos4AS is more effective than Tropos in describing requirements of self-adaptive systems, especially when the models are used by novice requirements engineers.
A plasmid display platform for the selection of peptides exhibiting a functional cell‐penetrating phenotype

Cell‐penetrating peptides (CPPs) represent a promising nonviral platform for the delivery of therapeutic cargos to cells and tissues. However, these peptides are often nonspecific, and their mechanism of action is still a subject of debate, which hinders the design of new CPPs. The alternative to rational protein design is the combinatorial approach to protein engineering, whereby large libraries of peptides are created and a screening or selection procedure is used to identify members with the desired phenotype(s). Here we describe a novel procedure for selecting peptides with a CPP phenotype using a plasmid display (PD) platform to link the peptides to their encoding DNA sequences. The PD system is based on genetic fusions to a DNA binding domain. The plasmid was designed to concomitantly express a fluorescent reporter protein to serve as a mock therapeutic cargo indicating its functional delivery into a cell. We have demonstrated this selection strategy using a control CPP (the TAT peptide) in the PC12 neuronal‐like cell line. In the absence of transfection reagents, TAT was unable to deliver the protein/DNA complexes. The inclusion of the HA2 peptide from the hemagglutinin protein and the addition of polyethylenimine (PEI) were similarly ineffective. The addition of Lipofectamine, however, enabled the TAT‐mediated delivery of the protein/DNA complexes, which was significantly better than control experiments without a CPP. This new PD selection platform will be a valuable new approach for use in identifying unique CPPs from randomized libraries with novel abilities and specificities. © 2010 American Institute of Chemical Engineers Biotechnol. Prog. , 2010
Typeless programming in Java 5.0 with wildcards

With the introduction of Java 5.0 [8] the type system has been extended by parameterized types, type variables, type terms, and wildcards. As a result very complex types can arise. The term Vector<? super Vector<? extends List<Integer>>> is for example a correct type in Java 5.0. Considering all that, it is often rather inconvienent to give types like this, explictly. Furthermore there are methods whose principal types would be intersection types. But intersection types are not implemented in Java 5.0. This means that Java 5.0 methods often do not have the principal type which is contradictive to the OOP-Principle of writing re-usable code. This has caused us to develop a Java 5.0 type inference system which assists the programmer by calculating types automatically. This type inference system allows us, to declare method parameters and local variables without type annotations. The type inference algorithm calculates the appropriate and principal types. In this contribution we present the ideas extending type inference for types with wildcards.
Camera orientation based on matching road networks

The following paper shows an approach to measure orientation data of sensors during an airplane flight for traffic data acquisition. This orientation data is necessary for georegistration of any taken aerial images and extracted features. Since an inertial measurement unit is a very costly component, alternative methods for orientation determination should be considered. In this paper we present an approach achieving this only by using a GPS position and a database of the road network around. It is shown how the roads are extracted in the image considering their color hue and how they are matched to the given database segments. To adjust the rotation angles a simplex optimization algorithm is used. The approach yields convergence rates of more than 96 percent with a rotation error of around 1/4 degree for pitch and roll, which is sufficient for traffic surveillance purpose.
Multisensor image registration

We describe an approach for registration of images from diierent sensors that may generate local polarity reversals and inconsistent features. The developed technique is based on modifying the objective function by transforming the images into a representation that is less dependent on the local image intensity, and using an iterative process that reduces the eeect of inconsistent features.
Toward a Taxonomy and Computational Models of Abnormalities in Images

The human visual system can spot an abnormal image, and reason about what makes it strange. This task has not received enough attention in computer vision. In this paper we study various types of atypicalities in images in a more comprehensive way than has been done before. We propose a new dataset of abnormal images showing a wide range of atypicalities. We design human subject experiments to discover a coarse taxonomy of the reasons for abnormality. Our experiments reveal three major categories of abnormality: object-centric, scene-centric, and contextual. Based on this taxonomy, we propose a comprehensive computational model that can predict all different types of abnormality in images and outperform prior arts in abnormality recognition.
Further generalizations of Wythoff ’ s game and minimum excludant function

Given non-negative integer a and b, let us consider the following game WY T (a, b). Two piles contain x and y matches. Two players take turns. By one move, it is allowed to take x′ and y′ matches from these piles such that 0 ≤ x′ ≤ x, 0 ≤ y′ ≤ y, 0 < x′ + y′, and [min(x′, y′) < b or |x′ − y′| < a]. The player who takes the last match is the winner (respectively, loser) in the normal (respectively, misere) version of the game. It is easy to verify that cases (a = 0, b = 1), (a = b = 1), and (b = 1, ∀ a) correspond to the two-pile NIM, Wythoff, and Fraenkel games, respectively. The concept of the minimum excludant function mex is known to be instrumental in solving the last two games. We generalize this concept by introducing a function mexb such that mex = mex1 and solve the normal and misere versions of game WY T (a, b).
Biomechanical evaluation of microbial cellulose (Zoogloea sp.) and expanded polytetrafluoroethylene membranes as implants in repair of produced abdominal wall defects in rats.

PURPOSE To evaluate the Load of Rupture of implants of membranes of microbial cellulose (Zoogloea sp.) and extended polytetrafuoroethylene in sharp defects of abdominal wall of rats. METHODS Sixty Wistar male rats, with a mean weight of 437,7 g +/- 40,9, anesthetized by a mixture of ketamine (5mg/100g) and xylazine (2mg/100g), were submitted to a rectangular (2 x 3 cm) excision of the abdominal wall, including fascia, muscle and peritoneum, and treated with membranes of microbial cellulose (MC) (MC Group- 30 animals) or extended polytetrafluoroethylene (ePTFE) (ePTFE Group- 30 animals). Each group was subdivided in 14th POD, 28th POD and 60th POD Subgroups. Under anesthesia, animals were submitted to euthanasia at 14th POD, 28th POD and 60th POD for evaluation of Load of Rupture. RESULTS Load of Rupture levels were significantly elevated (p<0, 05) among 14th, 28th and 60th postoperative days from each Group. When compared between groups, values of Load of Rupture were significantly larger (p<0, 05) in ePTFE Group than in MC Group. CONCLUSION Resistance to strength at implant/host interface was more pronounced in PTFEe Group than in MC Group.
Predicting Readmission Risk with Institution Specific Prediction Models

The ability to predict patient readmission risk is extremely valuable for hospitals, especially under the Hospital Readmission Reduction Program (HRRP) of the Center for Medicare and Medicaid Services (CMS) which went into effect starting October 1, 2012. There is a plethora of work in the literature that deals with developing readmission risk prediction models, but most of them do not have sufficient prediction accuracy to be deployed in a clinical setting, partly because different hospitals may have different characteristics in their patient populations. In this work we experimented with a generic framework for institution-specific readmission risk prediction, which takes patient data from a single institution and produces a statistical risk prediction model optimized for that particular institution and optionally condition specific. This provides great flexibility in model building, and is also able to provide institution-specific insights in its readmitted patient population. We showcase some initial results at three institutions for Heart Failure (HF), Acute Myocardial Infarction (AMI) and Pneumonia (PN) patients. The developed models yield better prediction accuracy than the ones present in the literature.
Coping With Strong Fairness

We consider the verification of linear temporal logic (LTL) properties of Petri nets, where the transitions can have both weak and strong fairness constraints. Allowing the transitions to have weak or strong fairness constraints simplifies the modeling of systems in many cases. We use the automata theoretic approach to model checking. To cope with the strong fairness constraints efficiently we employ Streett automata where appropriate. We present memory efficient algorithms for both the emptiness checking and counterexample generation problems for Streett automata.
Identification of interferon-gamma as the lymphokine that activates human macrophage oxidative metabolism and antimicrobial activity

Human blood mononuclear leukocytes stimulated with toxoplasma antigen, concanavalin A, mezerein plus lentil lectin, or staphylococcal enterotoxin A secreted a factor (macrophage-activating factor, or MAF) that enhanced the capacity of human macrophages to release H2O2 and to kill toxoplasmas. The same lymphoid supernatants contained IFN gamma but not IFN alpha or IFN beta. The MAF activity of six of seven unfractionated supernatants was completely eliminated by a monoclonal antibody that neutralizes IFN gamma, and MAF in the remaining supernatant was almost completely neutralized. Native IFN gamma partially purified by two independent protocols to specific activities of 1 X 10(6) and 10(7) U/mg protein was enriched in MAF activity at least as much as in antiviral activity. The capacity of macrophages to secrete H2O2 after incubation in partially purified native IFN gamma (mean peak stimulation, 8.8-fold) was greater than with unpurified lymphokines (3.8-fold) and sometimes equaled or exceeded the capacity of freshly harvested monocytes. The MAF activity of the partially purified native IFN gamma preparations was abolished by monoclonal anti- IFN gamma. Finally, IFN gamma of greater than 99% estimated purity was isolated (at Genentech, Inc.) from bacteria transformed with the cloned human gene for this lymphokine. Recombinant IFN gamma had potent MAF activity, stimulating the peroxide-releasing capacity of macrophages an average of 19.8-fold at peak response and enhancing their ability to kill toxoplasmas from 2.6 +/- 1.3% for untreated cells to 54 +/- 0.4% for treated cells. Attainment of 50% of the maximal elevation in peroxide-releasing capacity required a geometric mean concentration of 0.1 antiviral U/ml of recombinant IFN gamma, which is estimated to be approximately 6 picomolar for this preparation. Peroxide secretory capacity and toxoplasmacidal activity of macrophages peaked 2-4 d after exposure to IFN gamma. Peroxide-secretory capacity remained elevated during at least 6 d of continuous exposure, but the effect of IFN gamma was reversed within about 3 d of its removal. Activation was usually but not invariably accompanied by characteristic changes in cell morphology. Thus, IFN gamma activates human macrophage oxidative metabolism and antimicrobial activity, and appeared to be the only factor consistently capable of doing so in the diverse LK preparations tested.
Promoter Hypermethylation in White Blood Cell DNA and Breast Cancer Risk

The role of gene-specific methylation in white blood cells (WBC) as a marker of breast cancer risk is currently unclear. We determined whether promoter hypermethylation in blood DNA of candidate tumor suppressor genes frequently methylated in breast tumors can be used as a surrogate biomarker for breast cancer risk. Promoter methylation of BRCA1, CDH1 and RARβ was analyzed in WBC DNA from a population-based sample of 1,021 breast cancer patients and 1,036 controls by the MethyLight assay. Gene-specific promoter methylation in the DNA of 569 tumor tissue samples was also analyzed to determine the correlation of methylation levels with blood from the same individual. Hypermethylation of BRCA1 (OR: 1.31; 95% CI: 0.98-1.75) in WBC was associated with an increased risk of breast cancer when positive methylation was defined as ≥0.1% methylated. There was lack of concordance between tumor tissue and paired WBC DNA methylation. These results provide limited support that hypermethylation of BRCA1 in WBC DNA may be useful for determination of breast cancer risk. Additional studies with larger numbers of genes are needed to fully understand the relationship between WBC methylation and breast cancer risk.
Adolescent extracurricular activity and levels of alcohol use in regional and metropolitan locations: The mediational role of peers.

This study takes a bioecological approach to examine whether the association between adolescents’ extracurricular activity participation and levels of alcohol use would be moderated by gender and location; and explores the mediational role of peers’ alcohol use between adolescents’ sport participation and their levels of alcohol use. A representative sample of 1,158 year nine and 658 year eleven students from metropolitan and regional schools across Western Australia responded to a computer-administered self-report survey. Location moderated the portfolio-activity link to adolescent drinking; regional students participating in sports-only or sports-plus-activities reported significantly higher levels of alcohol use compared to students in activities-only or non-participants whereas for metropolitan students participating in sports-only reported significantly higher levels of alcohol use. Males and females reported similar experiences related to profile participation and adolescent alcohol use. Peers’ level of alcohol use significantly mediated the positive relation between sport participation and adolescent alcohol use for regional but not for metropolitan adolescents. Peers’ level of alcohol use significantly mediated the negative relation between non-sporting activities participation and lower levels of adolescent alcohol use for metropolitan but not for regional adolescents. Keywords: adolescence, sport, alcohol, location, peers
Fuzzy Model Based Recognition of Handwritten Hindi Characters

This paper presents the recognition of handwritten Hindi Characters based on the modified exponential membership function fitted to the fuzzy sets derived from features consisting of normalized distances obtained using the Box approach. The exponential membership function is modified by two structural parameters that are estimated by optimizing an objective function that includes the entropy and error function. A Reuse Policy that provides guidance from the past policies is utilized to improve the reinforcement learning. This relies on the past errors exploiting the past policies. The Reuse Policy improves the speed of convergence of the learning process over the strategies that learn without reuse and combined with the use of the reinforcement learning, there is a 25-fold improvement in training. Experimentation is carried out on a database of 4750 samples. The overall recognition rate is found to be 90.65%.
The effects of trust on online Malaysian students buying behavior

The objective of this study is to explore three dimensions of trust that affect consumers’ attitude towards online shopping and online shopping intention in Malaysia. Data was collected from students’ samples in Malaysia. SEM (Structural Equation Model) was used to test the hypotheses and confirmed the fit of the model. The researcher found that there are only two factors for explaining attitude towards online shopping, which are integrity and ability; and there is no significant in consumers’ attitude towards online shopping based on benevolence; however, there is a relationship between attitude toward online shopping and online shopping intention.
Environmental management practices and environmental performance: The roles of operations and marketing capabilities

Purpose – The purpose of this paper is to provide an initial analysis of the roles of functional capabilities in adopting environmental management practices (EMP) and improving environmental performance from an organizational capability perspective. Design/methodology/approach – By combing survey data and archival data from 121 UK-based manufacturing firms, this study explores the relationships among functional capabilities (marketing and operations), EMP and environmental performance. Findings – The results show that marketing and operations capabilities significantly affect EMP, which in turn leads to improved environmental performance. More specifically, this study finds that EMP fully mediates the relationship between marketing capability and environmental performance. Practical implications – The results of this study provide guidance for managers considering how to develop environmental capability in order to improve environmental performance. Originality/value – This study addresses a demonstrable .
The Effect of Personalization on Smartphone-Based Fall Detectors

The risk of falling is high among different groups of people, such as older people, individuals with Parkinson's disease or patients in neuro-rehabilitation units. Developing robust fall detectors is important for acting promptly in case of a fall. Therefore, in this study we propose to personalize smartphone-based detectors to boost their performance as compared to a non-personalized system. Four algorithms were investigated using a public dataset: three novelty detection algorithms—Nearest Neighbor (NN), Local Outlier Factor (LOF) and One-Class Support Vector Machine (OneClass-SVM)—and a traditional supervised algorithm, Support Vector Machine (SVM). The effect of personalization was studied for each subject by considering two different training conditions: data coming only from that subject or data coming from the remaining subjects. The area under the receiver operating characteristic curve (AUC) was selected as the primary figure of merit. The results show that there is a general trend towards the increase in performance by personalizing the detector, but the effect depends on the individual being considered. A personalized NN can reach the performance of a non-personalized SVM (average AUC of 0.9861 and 0.9795, respectively), which is remarkable since NN only uses activities of daily living for training.
Fabrication of Annealed Gold Nanostructures on Pre-Treated Glow-Discharge Cleaned Glasses and Their Used for Localized Surface Plasmon Resonance (LSPR) and Surface Enhanced Raman Spectroscopy (SERS) Detection of Adsorbed (Bio)molecules

Metallic nanoparticles are considered as active supports in the development of specific chemical or biological biosensors. Well-organized nanoparticles can be prepared either through expensive (e.g., electron beam lithography) or inexpensive (e.g., thermal synthesis) approaches where different shapes of nanoparticles are easily obtained over large solid surfaces. Herein, the authors propose a low-cost thermal synthesis of active plasmonic nanostructures on thin gold layers modified glass supports after 1 h holding on a hot plate (~350 °C). The resulted annealed nanoparticles proved a good reproducibility of localized surface plasmon resonance (LSPR) and surface enhanced Raman spectroscopy (SERS) optical responses and where used for the detection of low concentrations of two model (bio)chemical molecules, namely the human cytochrome b5 (Cyt-b5) and trans-1,2-bis(4-pyridyl)ethylene (BPE).
Full-Band 3-D Monte Carlo Simulation of InAs Nanowires and High Frequency Analysis

In this paper, we have investigated the electron transport and frequency response of the state-of-the-art single-InAs nanowire (NW) FETs using a full-band Monte Carlo simulator. InAs transistors using a single NW as the channel reveal excellent properties such as high current densities, high transconductance, and superior mobility when compared with silicon devices. One aspect that has been neglected until now is the high-frequency (HF) response of such devices. We perform a detailed HF analysis, calibrating our simulations with the experimental measurements that are successfully reproduced. We are able to make predictions about the electron distribution inside the NW transistor, and via a small signal analysis, we determine the intrinsic cutoff frequency and maximum frequency of oscillation. We compare these with the extrinsic measured figures of merit and observe a large discrepancy, which we are able to attribute to the parasitic elements. We finally perform a large signal analysis and investigate the nonlinearity of the device and the power transfer to the harmonics.