Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Resource Consumption Attack over MANET using an Artificial Immune Algorithm

The Human Immune System (HIS) is considered as a bank of models, functions, and concepts from where Artificial Immune algorithms are inspired. These algorithms are used to secure both host-based and network-based systems. However, it is not only important to utilize the HIS in producing AIS-based algorithms as much as it is important to introduce an algorithm with high performance. Therefore, creating a balance between utilizing HIS on one side and introducing the required AIS-based intrusion detection algorithm on the other side is a crucial issue which would be valuable to investigate. Securing the mobile ad hoc network (MANET) which is a collection of mobile, decentralized, and self organized nodes is another problem, which adds more challenges to the research. This is because MANET properties make it harder to be secured than the other types of static networks. We claim that AISs' properties such as being self-healing, self-defensive and self-organizing can meet the challenges of securing the MANET environment. This paper's objective is to utilize the biological model used in the dendritic cell algorithm (DCA) to introduce a Dendritic Cell Inspired Intrusion Detection Algorithm (DCIIDA). DCIIDA is introduced to detect the Resource Consumption Attack (RCA) over MANET. Furthermore, this study proposes a DCIIDA architecture which should be applied by each node in MANET.
A Critical Analysis of the Literature Regarding Surgical Approach and Outcome for Adult Low-Grade Isthmic Spondylolisthesis

Objective: A systematic review of the radiographic and clinical outcomes of adult patients undergoing surgery for low-grade isthmic spondylolisthesis was performed to determine whether conclusions could be made regarding the optimal choice of surgically managing adult low-grade isthmic spondylolisthesis. Methods: We tabulated the radiographic and clinical outcomes of patients who underwent a posterior procedure alone, an anterior procedure alone, or a combined anterior and posterior procedure. We also evaluated the influence of covariates such as laminectomy, spinal internal fixation, smoking, and secondary gain issues on these outcomes. Patients were pooled, and a χ2 analysis was performed to determine the relationship between surgical approach and patient outcome. A covariate analysis was performed to determine the influence of a laminectomy, spinal fixation, smoking, and secondary gain issues on these outcomes. Results: The available literature consisted primarily of retrospective case series, with only 4 of 34 reports being prospective randomized controlled studies. Patients with combined anterior and posterior procedures were most likely to achieve a solid fusion and a successful clinical outcome. The use of spinal fixation also increased the chance of fusion and successful clinical outcome. Conclusions: A pooling of the surgical literature on adult low-grade spondylolisthesis indicates that a combined anterior and posterior procedure most reliably achieves fusion and a successful clinical outcome. The literature, however, is primarily retrospective and heterogeneous with respect to indications for surgery and methods of evaluating outcome, providing a compelling rationale for a prospective randomized controlled trial of the various surgical approaches to this problem.
Enhanced Classification Accuracy on Naive Bayes Data Mining Models

paradigm is a data mining framework containing all the concepts extracted from the training dataset to differentiate one class from other classes existed in data. The primary goal of the classification frameworks is to provide a better result in terms of accuracy. However, in most of the cases we can not get better accuracy particularly for huge dataset and dataset with several groups of data . When a classification framework considers whole dataset for training then the algorithm may become unusuable because dataset consisits of several group of data. The alternative way of making classification useable is to identify a similar group of data from the whole training data set and then training each group of similar data. In our paper, we first split the training data using k- means clustering and then train each group with Naive Bayes Classification algorithm. In addition, we saved each model to classify sample or unknown or test data. For unknown data, we classify with the best match group/model and attain higher accuracy rate than the conventional Naive Bayes classifier.
Effects of sharing information on drug administration errors in pediatric wards: a pre–post intervention study

Background and purpose Drug administration errors are more likely to reach the patient than other medication errors. The main aim of this study was to determine whether the sharing of information on drug administration errors among health care providers would reduce such problems. Patients and methods This study involved direct, undisguised observations of drug administrations in two pediatric wards of a major teaching hospital in Kuala Lumpur, Malaysia. This study consisted of two phases: Phase 1 (pre-intervention) and Phase 2 (post-intervention). Data were collected by two observers over a 40-day period in both Phase 1 and Phase 2 of the study. Both observers were pharmacy graduates: Observer 1 just completed her undergraduate pharmacy degree, whereas Observer 2 was doing her one-year internship as a provisionally registered pharmacist in the hospital under study. A drug administration error was defined as a discrepancy between the drug regimen received by the patient and that intended by the prescriber and also drug administration procedures that did not follow standard hospital policies and procedures. Results from Phase 1 of the study were analyzed, presented and discussed with the ward staff before commencement of data collection in Phase 2. Results A total of 1,284 and 1,401 doses of drugs were administered in Phase 1 and Phase 2, respectively. The rate of drug administration errors reduced significantly from Phase 1 to Phase 2 (44.3% versus 28.6%, respectively; P<0.001). Logistic regression analysis showed that the adjusted odds of drug administration errors in Phase 1 of the study were almost three times that in Phase 2 (P<0.001). The most common types of errors were incorrect administration technique and incorrect drug preparation. Nasogastric and intravenous routes of drug administration contributed significantly to the rate of drug administration errors. Conclusion This study showed that sharing of the types of errors that had occurred was significantly associated with a reduction in drug administration errors.
Automatic Generation of Random Self-Checking Test Cases

A technique of automatically generating random software test cases is described. The nature of such test cases ensures that they will execute to completion, and their execution is predicted at the time of generation. Wherever possible the test cases are self-checking. At run-time their execution is compared witht he predicted execution. Also described are implementations of the technique that have been used to test various IBM programs-- PL/I language processors, sort/merge programs, and Graphical Data Display Manager alphanumeric and graphics support.
A Word-Level Finite Field Multiplier Using Normal Basis

Hardware implementations of finite field arithmetic using normal basis are advantageous due to the fact that the squaring operation can be done at almost no cost. In this paper, a new word-level finite field multiplier using normal basis is proposed. The proposed architecture takes d clock cycles to compute the product bits, where the value for d, 1 ≤ d ≤ m, can be arbitrarily selected by the designer to set the tradeoff between area and speed. When there exists an optimal normal basis, it is shown that the proposed design has a smaller critical path delay than other word-level normal basis multipliers found in the literature, while its circuit complexities are moderate and comparable to the others. Different word size multipliers were implemented in hardware, and implementation results are also presented.
Linear and Branched Glyco-Lipopeptide Vaccines Follow Distinct Cross-Presentation Pathways and Generate Different Magnitudes of Antitumor Immunity

Background Glyco-lipopeptides, a form of lipid-tailed glyco-peptide, are currently under intense investigation as B- and T-cell based vaccine immunotherapy for many cancers. However, the cellular and molecular mechanisms of glyco-lipopeptides (GLPs) immunogenicity and the position of the lipid moiety on immunogenicity and protective efficacy of GLPs remain to be determined. Methods/Principal Findings We have constructed two structural analogues of HER-2 glyco-lipopeptide (HER-GLP) by synthesizing a chimeric peptide made of one universal CD4+ epitope (PADRE) and one HER-2 CD8+ T-cell epitope (HER420–429). The C-terminal end of the resulting CD4–CD8 chimeric peptide was coupled to a tumor carbohydrate B-cell epitope, based on a regioselectively addressable functionalized templates (RAFT), made of four α-GalNAc molecules. The resulting HER glyco-peptide (HER-GP) was then linked to a palmitic acid moiety, attached either at the N-terminal end (linear HER-GLP-1) or in the middle between the CD4+ and CD8+ T cell epitopes (branched HER-GLP-2). We have investigated the uptake, processing and cross-presentation pathways of the two HER-GLP vaccine constructs, and assessed whether the position of linkage of the lipid moiety would affect the B- and T-cell immunogenicity and protective efficacy. Immunization of mice revealed that the linear HER-GLP-1 induced a stronger and longer lasting HER420–429-specific IFN-γ producing CD8+ T cell response, while the branched HER-GLP-2 induced a stronger tumor-specific IgG response. The linear HER-GLP-1 was taken up easily by dendritic cells (DCs), induced stronger DCs maturation and produced a potent TLR- 2-dependent T-cell activation. The linear and branched HER-GLP molecules appeared to follow two different cross-presentation pathways. While regression of established tumors was induced by both linear HER-GLP-1 and branched HER-GLP-2, the inhibition of tumor growth was significantly higher in HER-GLP-1 immunized mice (p<0.005). Significance These findings have important implications for the development of effective GLP based immunotherapeutic strategies against cancers.
Quantitative Proteomics of a Presymptomatic A53T α-Synuclein Drosophila Model of Parkinson Disease*S

A global isotopic labeling strategy combined with multidimensional liquid chromatographies and tandem mass spectrometry was used for quantitative proteome analysis of a presymptomatic A53T α-synuclein Drosophila model of Parkinson disease (PD). Multiple internal standard proteins at different concentration ratios were spiked into samples from PD-like and control animals to assess quantification accuracy. Two biological replicates isotopically labeled in forward and reverse directions were analyzed. A total of 253 proteins were quantified with a minimum of two identified peptide sequences (for each protein); 180 (∼71%) proteins were detected in both forward and reverse labeling measurements. Twenty-four proteins were differentially expressed in A53T α-synuclein Drosophila; up-regulation of troponin T and down-regulation of fat body protein 1 were confirmed by Western blot analysis. Elevated expressions of heat shock protein 70 cognate 3 and ATP synthase are known to be directly involved in A53T α-synuclein-mediated toxicity and PD; three up-regulated proteins (muscle LIM protein at 60A, manganese-superoxide dismutase, and troponin T) and two down-regulated proteins (chaoptin and retinal degeneration A) have literature-supported associations with cellular malfunctions. That these variations were observed in presymptomatic animals may shed light on the etiology of PD. Protein interaction network analysis indicated that seven proteins belong to a single network, which may provide insight into molecular pathways underlying PD. Gene Ontology analysis indicated that the dysregulated proteins are primarily associated with membrane, endoplasmic reticulum, actin cytoskeleton, mitochondria, and ribosome. These associations support prior findings in studies of the A30P α-synuclein Drosophila model (Xun, Z. Y., Sowell, R. A., Kaufman, T. C., and Clemmer, D. E. (2007) Protein expression in a Drosophila model of Parkinson's disease. J. Proteome Res. 6, 348–357; Xun, Z. Y. , Sowell, R. A. , Kaufman, T. C. , and Clemmer, D. E. (2007) Lifetime proteomic profiling of an A30P α-synuclein Drosophila model of Parkinson's disease. J. Proteome Res. 6, 3729–3738) that defects in cellular components such as actin cytoskeleton and mitochondria may contribute to the development of later symptoms.
ALMA OBSERVATIONS OF WARM MOLECULAR GAS AND COLD DUST IN NGC 34

We present Atacama Large Millimeter Array (ALMA) Cycle-0 observations of the CO (6–5) line emission (rest-frame frequency = 691.473 GHz) and of the 435 μm dust continuum emission in the nuclear region of NGC 34, a local luminous infrared galaxy at a distance of 84 Mpc (1″ = 407 pc) which contains a Seyfert 2 active galactic nucleus (AGN) and a nuclear starburst. The CO emission is well resolved by the ALMA beam (0.″26 × 0.″23), with an integrated flux of fCO(6–5) = 1004 (± 151) Jy km s−1. Both the morphology and kinematics of the CO (6–5) emission are rather regular, consistent with a compact rotating disk with a size of 200 pc. A significant emission feature is detected on the redshifted wing of the line profile at the frequency of the H13CN (8–7) line, with an integrated flux of 17.7 ± 2.1(random) ± 2.7(systematic) Jy km s−1. However, it cannot be ruled out that the feature is due to an outflow of warm dense gas with a mean velocity of 400 km s−1. The continuum is resolved into an elongated configuration, and the observed flux corresponds to a dust mass of Mdust = 106.97 ± 0.13 M☉. An unresolved central core (radius ≃ 50 pc) contributes 28% of the continuum flux and 19% of the CO (6–5) flux, consistent with insignificant contributions of the AGN to both emissions. Both the CO (6–5) and continuum spatial distributions suggest a very high gas column density (≳ 104 M☉ pc−2) in the nuclear region at radius ≲ 100 pc.
Large Granularity Cache Coherence for Intermittent Connectivity

To function in mobile computing environments, distributed file systems must cope with networks that are slow, intermittent, or both. Intermittence vitiates the effectiveness of callback-based cache coherence schemes in reducing client-server communication, because clients must validate files when connections are reestablished. In this paper we show how maintaining cache coherence at a large granularity alleviates this problem. We report on the implementation and performance of large granularity cache coherence for the Coda File System. Our measurements confirm the value of this technique. At 9.6 Kbps, this technique takes only 4-20% of the time required by two other strategies to validate the cache for a sample of Coda users. Even at this speed, the network is effectively eliminated as the bottleneck for cache validation.
MULTISCALE COMMUNITY DETECTION USING MARKOV DYNAMICS A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I AT MĀNOA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

Complex networks is an interdisciplinary research area getting attention from a variety of disciplines including sociology, biology, and computer science. It studies the properties of complex systems that may have many functional or structural subunits. Community detection algorithms are one of the major approaches to analyse complex networks by finding these intermediate-level subunits called modules or communities. Furthermore, some networks may have multilevel or overlapping community structures. InfoMap is one of the best performing algorithms that finds the communities of a network by compressing the flow of information [25, 17]. In this work, we introduced Markov Dynamics to the InfoMap in order to detect communities at multiscales. Although Markov Dynamics have been applied to the InfoMap for undirected networks before [28], this was the first application of Markov Dynamics to the InfoMap for directed networks. Additionally, we added a feature to detect overlapping nodes using the compression of flow on the boundary nodes, similar to the approach described in [9] before. These two features were combined into the InfoMap for directed networks. We evaluated these two features on synthetic networks and benchmark graphs. We have comparable results with the Hierarchical InfoMap [26] for multilevel community detection, but improvement in runtime is needed. We evaluated the overlapping feature by its own ability, and found that it can detect overlapping nodes for networks with sparse overlaps.
Acrylamide and Polyacrylamide: A Review of Production, Use, Environmental Fate and Neurotoxicity

Acrylamide is a highly water soluble vinyl monomer formed from the hydration of acrylonitrile. The major commercial use of acrylamide is the formation of polymers. In the environment acrylamide has a high mobility in soil, may travel great distances in ground-water, is biodegradable, and is not absorbed by sediments or affected by water treatment. It is absorbed by all routes of animal exposure. The main metabolite is N-acetyl-S-(3-amino-3-oxypropyl)-cysteine and is excreted predominantly in the urine. Acrylamide produces an ascending central/peripheral axonopathy in man and animals. The major histological findings are swelling of axons and/or decrease in number of large diameter axons. Acrylamide axonopathy is reversible with time, but full recovery depends upon the severity of the intoxication. All reported cases of acrylamide toxicity have been attributed to handling the monomer. Polyacrylamide is non-toxic. Specific clinical features of acrylamide intoxication are more conclusive than electrophysiological, histological or biochemical laboratory tests for diagnosis. Acrylamide can be detected by titration, colorimetry, high performance chromatography, gas chromatography and polarography in air, water, biological fluids, tissues and polyacrylamides. Present research on the effects of acrylamide focuses on developmental and reproductive effects, genotoxicity and carcinogenicity.
Antipsychotic and benzodiazepine use among nursing home residents: findings from the 2004 National Nursing Home Survey.

OBJECTIVES To document the extent and appropriateness of use of antipsychotics and benzodiazepines among nursing home residents using a nationally representative survey. METHODS Cross-sectional analysis of the 2004 National Nursing Home Survey. Bivariate and multivariate analyses examined relationships between resident and facility characteristics and antipsychotic and benzodiazepine use by appropriateness classification among residents aged 60 years and older (N = 12,090). Resident diagnoses and information about behavioral problems were used to categorize antipsychotic and benzodiazepine use as appropriate, potentially appropriate, or having no appropriate indication. RESULTS More than one quarter (26%) of nursing home residents used an antipsychotic medication, 40% of whom had no appropriate indication for such use. Among the 13% of residents who took benzodiazepines, 42% had no appropriate indication. In adjusted analyses, the odds of residents taking an antipsychotic without an appropriate indication were highest for residents with diagnoses of depression (odds ratio [OR] = 1.31; 95% confidence interval [CI]: 1.12-1.53), dementia (OR = 1.82; 95% CI: 1.52-2.18), and with behavioral symptoms (OR = 1.97, 95% CI: 1.56-2.50). The odds of potentially inappropriate antipsychotic use increased as the percentage of Medicaid residents in a facility increased (OR = 1.08, 95% CI: 1.02-1.15) and decreased as the percentage of Medicare residents increased (OR = 0.46, 95% CI: 0.25-0.83). The odds of taking a benzodiazepine without an appropriate indication were highest among residents who were female (OR = 1.44; 95% CI: 1.18-1.75), white (OR = 1.95; 95% CI: 1.47-2.60), and had behavioral symptoms (OR = 1.69; 95% CI: 1.41-2.01). CONCLUSION Antipsychotics and benzodiazepines seem to be commonly prescribed to residents lacking an appropriate indication for their use.
Learning residential electrical wiring through computer simulation: The impact of computer-based learning environments on student achievement and cognitive load

Multimedia learning environments such as computer simulations are widely accepted as tools for supporting science learning. Although the design of multimedia learning environments can be domain specific, few studies have focused on the use of computer simulations for learning residential electrical wiring. This study aimed to determine whether students using computer simulations learned better than traditional classroom learners in the domain of residential wiring. A quasi-experiment was implemented with 169 high school students. The simulation group participated in a series of computer simulations, whereas the control group received lectures and demonstrations from an instructor. Students' cognitive load as elevated by multimedia leaning tasks was compared with that of students learning using traditional methods. The simulation group learned significantly better and reported higher cognitive load than did the control group. Moreover, the simulation group managed cognitive resources more efficiently on transfer of learning than did the control group. Having more opportunities to interact with a simulation-based learning environment could result in higher cognitive load. The higher cognitive load seemed to result in better performance on the achievement test and, therefore, the learners' mental effort was possibly invested mainly in meaning making in the virtual learning environments. Discussion of the results, instruments and research design, as well as suggestions for future studies are provided. [ABSTRACT FROM AUTHOR]
Domestic use of bleach and infections in children: a multicentre cross-sectional study

Objective To report the effects of bleach use at home on the frequency of infections in 9102 school-age children participating in the HITEA project. Methods Parents of pupils aged 6–12 years from schools in Barcelona province (Spain), Utrecht province (the Netherlands) and Eastern and Central Finland were administered a questionnaire including questions on the frequency of infections (influenza, tonsillitis, sinusitis, otitis, bronchitis and pneumonia) in the past 12 months and bleach use at home. We developed multivariable mixed-effects multilogistic regression models to obtain relative risk ratios (RRR) and their 95% CI per country, and combined the RRR using random-effects meta-analyses. Results Bleach use was common in Spain (72%, n=1945) and uncommon in Finland (7%, n=279). Overall, the prevalence of infections (recurrent or once) was higher among children of bleach users. Significant combined associations were shown for influenza only once (RRR=1.20, 95% CI 1.04 to 1.38), recurrent tonsillitis (RRR=1.35, 95% CI 1.07 to 1.71) and any infection (RRR=1.18, 95% CI 1.01 to 1.38). Conclusions Passive exposure to cleaning bleach in the home may have adverse effects on school-age children's health by increasing the risk of respiratory and other infections. The high frequency of use of disinfecting irritant cleaning products may be of public health concern, also when exposure occurs during childhood.