Miracle-dz/UniFAR-FTUs huggingface dataset:
E-Dating: The Five Phases on Online Dating

Online dating continues to grow in popularity as a way for individuals to locate a potential romantic partner. Researchers have examined how people present themselves on these sites, which presentations are more likely to lead to success, the effectiveness of the matchmaking tools that some companies employ, the stigma attached to using these sites and the types of people who are drawn to online dating. However, there is an absence of scholarly work on how these relationships progress compared to traditional models of courtship. This chapter sets out a model for the phases of online dating and compares this model with Givens’ (1979) work on a traditional model of courtship. It is argued here the phases of online dating are very different to other courtship models. These differences pose new challenges and create new benefits to those who elect to find a partner via one of these sites. WHere can one FInd a romantIc Partner on tHe net? Before moving on to consider online dating sites, it is important to understand that these sites emerged because it became obvious that there was a need and a market for such sites. As is well-known, the Internet was not originally set up as a social space, but rather as a space to transfer data. However, not long after (even in its most primitive textual form), friendships and romances began to blossom. People were meeting each other in all sorts of places, MUDs and MOOs (multi-users dungeons or domains, which are essentially role-playing sites), bulletin boards, chat rooms, newsgroups and gaming sites. Bulletin board systems (BBs) were possibly the first place where romances initiated on the Internet. DeVoss (2007) has succinctly described how these relationships initiated in these sites and quite rightly points out that one could not escape gender roles in these spaces (even when people swapped DOI: 10.4018/978-1-60566-104-9.ch016
On the Universality of Quantum Logical Neural Networks

In this paper we investigate the computational power of the quantum weightless neural networks (q-WNN) and propose a novel quantum weightless neural node. The new quantum neuron is derived from the quantum probabilistic logic node (qPLN), which is a mathematical quantisation of the weightless neural node PLN. By a slight modification on the input lines of the qPLN node it is possible to define the quantum psi-neuron. We show in this paper that psi-neurons can be used to approximate any quantum circuit.
Gait Retraining in Parkinson’s Disease: A Cognitive Cueing Approach

Parkinson's disease (PD) is characterized by resting tremor, bradykinesia, rigidity, and postural instability. These cardinal symptoms commonly affect gait performance and therefore researchers have been investigating techniques to manage and treat gait impairment in individuals with PD. This thesis explores a progressive approach to gait rehabilitation using a novel intervention that combines traditional gait cueing techniques with motor learning approaches to facilitate self-cued gait improvement. Five participants with PD-related gait impairment completed the home-based gait training intervention. This intervention included video footage of each individual participant walking with and without verbal instructional cues, audio coaching, and practice periods. Participants were given the video to practice at home for two-weeks. Kinematic parameters of gait were assessed pre-intervention, at two weeks post-intervention, and at two months post-intervention. Results indicate that individuals with PD are capable of learning verbal-cueing strategies and utilizing these to generate long-term gait improvements through self-cueing. Each of the three co-authors contributed to designing the research methodology used to test the gait retraining intervention highlighted in Chapter 2, and facilitated the process of data collection. Dr. Spaulding also made valuable contributions to the process of data analysis and both Dr. Spaulding and Dr. Jenkins offered valuable improvement to this thesis through the process of iterative editing. Participants in the study (Chapter 2) were recruited from the outpatient neurology practice of Dr. Jenkins, without whose support this project would not have been possible.
Targeted deletion of miR-182, an abundant retinal microRNA

Purpose MicroRNA-182 (miR-182) is expressed abundantly in the mammalian retina and is therefore thought to perform important roles for the retinal development and the function. To test this hypothesis, we generated miR-182 knockout mice. Methods northern blotting was performed to confirm the robust expression of miR-182 in the eye. The precursor sequence of miR-182 was replaced by the neomycin resistance gene under the control of the phosphoglycerate kinase 1 promoter in a targeting construct. The targeting vector was linearized and transfected into embryonic stem (ES) cells. Recombinant ES clones were selected and injected into blastocysts to generate male chimeras. Heterozygous and homozygous mice were obtained after five generations of backcrossing and were confirmed using genotyping and northern blotting. Results Heterozygous (+/−) and homozygous (−/−) knockout mice were morphologically normal, viable, and fertile. Immunohistochemical analysis of the miR-182–deficient retinas did not reveal any apparent structural abnormalities in the retinas. Consistently, global expression profiling using a repeated microarray did not identify significant fluctuations for potential target genes. Conclusions We successfully generated miR-182 knockout mice and characterized the resulting miR-182–depleted retina. This is the first report describing the targeted deletion of a single miRNA that is highly expressed in the retina. The absence of significant transcriptional and phenotypic changes in miR-182–depleted retinas suggests that miR-182 is not a major determinant of retinal development or delamination. Further studies are required to elucidate any functional changes in the retina.
Salt and pepper noise removal in video using adaptive decision based median filter

This paper proposes a new algorithm to remove salt and pepper noise in video. The adaptive decision algorithm first checks whether the selected pixel in the video sequence is noisy or noise free. Initially the window size is selected as 3 × 3. If the selected pixel within the window is 0's or 255's, and some of other pixels within the window are noise free, then the selected pixel value is replaced by trimmed median value. If the selected pixel is 0 or 255 and other pixel values in a selected window (3 × 3) all are 0's and 255's, then change the selected window size as 5 × 5, then the selected pixel value is replaced by trimmed median value. In the selected new window (5 × 5), all the elements are 0's or 255's then the processing pixel is replaced by the previous resultant pixel. Finally, the performance of the proposed algorithm is compared with the existing algorithms like Median Filter; Decision Based Filter and Progressive Switched Median Filter. The proposed algorithm gives better PSNR and IEF results than the existing algorithms.
Synthetic Benchmark Generator for the MOLEN Processor

Most of current embedded processor designs utilize programmable processor cores augmented with specialized hardwired units. Recently, we are witnessing a shift in this design methodology towards the utilization of reconfigurable hardware (e.g., field-programmable gate arrays (FPGAs)) instead of fixed hardware. In this light, the MOLEN processor has been proposed that employs reconfigurable microcode (ρμ-code) to control both the reconfiguration and execution processes of the reconfigurable hardware. The ρμ-code is an extension to the traditional microcode which includes support for reconfigurable hardware. In this paper, we propose an extension to the generally accepted hardware/software co-design methodology that accomplishes the intended augmentation of reconfigurable hardware to programmable processors. Additionally, the utilization of ρμ-code requires on-chip storage for which the storage size, the organization, and other design parameters must be investigated. To this end, we propose to generate synthetic ρμ-code that only exhibit those characteristics that are relevant in the mentioned investigation. Keywords— field-programmable gate array, synthetic benchmarks, reconfigurable computing, reconfigurable microcode.
Automated ImmunochemicalProceduresfor Measurementof ImmunoglobulinsIgG , IgA , and 1 gMin Human Serum

From the Department of Pathology, College of Medicine, University of Florida, Gainesville, Fla. 32601. 1 NIH Academic Pathology trainee, Department of Pathology, College of Medicine, University of Florida, Gainesville, Fla. 32601. 2 The 1970 Technicon International Congress included the following: Alper, C. A. , Automated nephelometric determination of serum haptoglobin,C’3 and a1-antitrypsin, Abstract #43. Fish, M. G. , Aronson, S. B. , and Wegfhart, P., Specific quantitation of serum albumin by continuous flow immupoprecipitation, Abstract #40. Larson, C. , and Orenstein, P., An automated method forquantitationofproteinsinbody fluids, Abstract#38. Received May 17,1971;acceptedJune 15,1971.
Machine learning classification model for Network based Intrusion Detection System

With an enormous increase in number of mobile users, mobile threats are also growing rapidly. Mobile malwares can lead to several cybersecurity threats i.e. stealing sensitive information, installing backdoors, ransomware attacks and sending premium SMSs etc. Previous studies have shown that due to the sophistication of threats and tailored techniques to avoid detection, not every antivirus system is capable of detecting advance threats. However, an extra layer of security at the network side can protect users from these advanced threats by analyzing the traffic patterns. To detect these threats, this paper proposes and evaluates, a Machine Learning (ML) based model for Network based Intrusion Detection Systems (NIDS). In this research, several supervised ML classifiers were built using data-sets containing labeled instances of network traffic features generated by several malicious and benign applications. The focus of this research is on Android based malwares due to its global share in mobile malware and popularity among users. Based on the evaluation results, the model was able to detect known and unknown threats with the accuracy of up to 99.4%. This ML model can also be integrated with traditional intrusion detection systems in order to detect advanced threats and reduce false positives.
Managing a Large Shared Bank of Unstructured Data by Using Free-Table

This paper presents a reference framework, called BUD, to manage a large shared bank of unstructured data. This paper lists several important issues on managing or maintaining the unstructured data in BUD. BUD stores and manages the ever-growing unstructured data by introducing a novel technique called free-table, which is a conceptual view for end-users and a physical entity maintained by transactional storage manager of BUD. Free-table is cell-oriented but not column-oriented as relational table. It can store various types of unstructured data in cell with different versions. Additionally, we study two cases, VMP and PXRDB, to show that our proposal is feasible and tractable.
An automated assessment and reporting tool for introductory Java programs

This paper presents a graph-based grading system for Java introductory programming courses, eGrader. The assessment process undergoes two stages in succession. Namely, dynamically and statically. This analysis leads to producing detailed feedback reports to both students and instructors. The student report provides a detailed feedback on the submitted code with a total mark break down. In addition to showing the model solution, specific comments on syntax and semantic errors (if any) are provided. On the other hand, the automated class report is a comprehensive document that provides detailed analysis on all students' submissions. The success of eGrader is measured by four performance measures which are sensitivity (97.37%), specificity (98.1%), precision (98.04%) and accuracy (97.07%).
Can the Attention Training Technique Reduce Burnout in Junior Elite Athletes

The primary purpose of the present study was to investigate the effects of the attention training technique on junior elite athletes’ level of burnout. We also examine an ancillary question of whether the technique impact on mindfulness. The results showed that there was a significant decrease in in burnout amongst the ATT group but not the control group. In the ATT group, but not the control, mindfulness increased. The results are discussed based on the changes in the athletes’ attentional awareness and control.
Guaranteed Tensor Decomposition: A Moment Approach

We develop a theoretical and computational framework to perform guaranteed tensor decomposition, which also has the potential to accomplish other tensor tasks such as tensor completion and denoising. We formulate tensor decomposition as a problem of measure estimation from moments. By constructing a dual polynomial, we demonstrate that measure optimization returns the correct CP decomposition under an incoherence condition on the rank-one factors. To address the computational challenge, we present a hierarchy of semidefinite programs based on sums-of-squares relaxations of the measure optimization problem. By showing that the constructed dual polynomial is a sum-of-squares modulo the sphere, we prove that the smallest SDP in the relaxation hierarchy is exact and the decomposition can be extracted from the solution under the same incoherence condition. One implication is that the tensor nuclear norm can be computed exactly using the smallest SDP as long as the rank-one factors of the tensor are incoherent. Numerical experiments are conducted to test the performance of the moment approach.
Social Isolation Blunted the Response of Mesocortical Dopaminergic Neurons to Chronic Ethanol Voluntary Intake

Previous studies have shown that stress can increase the response of mesolimbic dopaminergic neurons to acute administration of drugs of abuse included ethanol. In this study, we investigated the possible involvement of the mesocortical dopaminergic pathway in the development of ethanol abuse under stress conditions. To this aim we trained both socially isolated (SI) and group housed (GH) rats to self administer ethanol which was made available only 2 ha day (from 11:00 to 13:00 h). Rats have been trained for 3 weeks starting at postnatal day 35. After training, rats were surgically implanted with microdialysis probes under deep anesthesia, and 24 hlater extracellular dopamine concentrations were monitored in medial prefrontal cortex (mPFC) for the 2 hpreceding ethanol administration (anticipatory phase), during ethanol exposure (consummatory phase) and for 2 hafter ethanol removal. Results show that, in GH animals, dopamine extracellular concentration in the mPFC increased as early as 80 min before ethanol presentation (+50% over basal values) and remained elevated for 80 min during ethanol exposure. In SI rats, on the contrary, dopamine extracellular concentration did not show any significant change at any time point. Ethanol consumption was significantly higher in SI than in GH rats. Moreover, mesocortical dopaminergic neurons in SI animals also showed a decreased sensitivity to an acute administration of ethanol with respect to GH rats. Our results show that prolonged exposure to stress, as in social isolation, is able to induce significant changes in the response of mesocortical dopaminergic neurons to ethanol exposure and suggest that these changes might play an important role in the compulsivity observed in ethanol addiction.
Can real-time local area network protocols be made robust?

This paper proposes a formal definition of the robustness property which, we believe, developers of future real-time (RT) local area network (LAN) protocols must aim to realize. As a demonstration of the utility of this definition, the carrier sense multiple access with deterministic collision resolution (CSMA/DCR) protocol is then analyzed for its robustness and an extension of the CSMA/DCR protocol that is highly attractive for use in RT, fault-tolerant, bus-connected LAN systems is presented. CSMA/DCR is one of the few major RT bus LAN protocols, striking a good balance between the CSMA/CD protocol with weakly predictable timing behavior, and the TDMA protocol that has a tightly bounded worst-case delay but is inflexible. We show that the ordinary CSMA/DCR and several other LAN protocols are not very robust in that the protocols lose their real-time delivery properties when various types of faults occur. The extension to the CSMA/DCR protocol that we present in this paper maintains real-time delivery properties in the presence of multiple faults. Since robustness is implemented at the medium access control (PAAC) layer level, this version of CSMA/DCR is capable of delivering frames in bounded time when permanent and transient faults occur, thereby providing to the upper logical link control (LLC) layer a reliable RT service.
Fifteen degrees of separation: Latitudinal gradients of rocky intertidal biota along the California Current

The region of the eastern North Pacific coastline dominated by the California Current was surveyed annually from 2001‐2003 to examine (1) benthic macro‐invertebrate and algal populations, (2) the magnitude and patterns of key environmental variables, and (3) how dynamic populations and communities of macroalgae and invertebrates respond to spatial differences in nearshore geomorphology, wave dynamics, and oceanography of the coastal shelf. We used a highly replicated spatially nested sampling design consisting of 144 shore segments (bedrock platforms longer than 50 m) with three replicate segments per site (~1 km), three sites per area (~10 km), and sixteen areas (>10 km) grouped into six domains (hundreds of kilometers). Results suggest that (1) low zone diversity was higher at northern latitudes when measured at segment, site, and area scales, but at domain scales there were more species at southern latitudes; (2) community structure showed high fidelity to geographic location with community similarity inversely related to separation distance, and the only regional scale biological discontinuity in community structure was centered near Pt. Conception; and (3) wave runup was the most significant physical parameter affecting overall community structure, however, tidal range, precipitation, air and water temperature, upwelling, salinity, and sand were significant mechanisms forcing differences in community structure within the region.
Effect of sex on torque, recovery, EMG, and MMG responses to fatigue

Objective: The purpose of the present investigation was to examine the effect of sex on maximal voluntary isometric contraction (MVIC) torque and the EMG and MMG responses as a result of fatiguing, intermittent, submaximal (65% of MVIC), isometric elbow flexion muscle contractions. Methods: Eighteen men and women performed MVIC trials before (pretest), after (posttest), and 5-min after (5-min recovery) performing 50 intermittent, submaximal isometric muscle contractions. Surface electromyographic (EMG) and mechanomyographic (MMG) signals were simultaneously recorded from the biceps brachii muscle. Results: As a result of the fatiguing workbout torque decreased similarly from pretest to posttest for both the men (24.0%) and women (23.3%). After 5-min of recovery, torque had partially recovered for the men, while torque had returned to pretest levels for the women. For both sexes, from pretest to posttest EMG mean power frequency and MMG amplitude decreased, but returned to pretest levels after 5-min of recovery. Conclusions: In the present study, there were sex-related differences in muscle fatigue that were not associated with the EMG or MMG responses.
Modular Veri cation of Software Units ?

A variety of assume-guarantee model checking approaches have been proposed in the literature. In this paper, we adapt those approaches to checking guarantees (written in LTL and 8CTL) of software units in isolation. We propose to synthesize program fragments that implement the behavior speciied by assumptions written in LTL. We justify the safety of such synthesized environments and provide empirical data that encoding assumptions in the state space is more eecient than encoding them in the formula for assume-guarantee model checking of software units.
A Systematic Mapping Study on Cloud Computing

Cloud Computing emerges from the global economic crisis as an option to use computing resources from a more rational point of view. In other words, a cheaper way to have IT resources. However, issues as security and privacy, SLA (Service Layer Agreement), resource sharing, and billing has left open questions about the real gains of that model. This study aims to investigate state-of-the-art in Cloud Computing, identify gaps, challenges, synthesize available evidences both its use and development, and provides relevant information, clarifying open questions and common discussed issues about that model through literature. The good practices of systematic map- ping study methodology were adopted in order to reach those objectives. Al- though Cloud Computing is based on a business model with over 50 years of existence, evidences found in this study indicate that Cloud Computing still presents limitations that prevent the full use of the proposal on-demand.
Compound stress assignment by analogy: the constituent family bias

Abstract This paper tests the hypothesis that stress assignment to English compounds works on the basis of analogy. In particular, the role of the constituent family, i.e. the set of compounds that share the same right or left constituent with a given compound, is investigated. On the basis of large amounts of data from three different corpora it is shown that the tendency towards a certain kind of stress pattern within the constituent families of a given compound is a strong predictor for stress assignment. This challenges rule-based approaches to compound stress assignment and lends independent evidence to exemplar-based approaches to language structure.
Specific, Sensitive, and Quantitative Enzyme-Linked Immunosorbent Assay for Human Immunoglobulin G Antibodies to Anthrax Toxin Protective Antigen

The bioterrorism-associated human anthrax epidemic in the fall of 2001 highlighted the need for a sensitive, reproducible, and specific laboratory test for the confirmatory diagnosis of human anthrax. The Centers for Disease Control and Prevention developed, optimized, and rapidly qualified an enzyme-linked immunosorbent assay (ELISA) for immunoglobulin G (IgG) antibodies to Bacillus anthracis protective antigen (PA) in human serum. The qualified ELISA had a minimum detection limit of 0.06 µg/mL, a reliable lower limit of detection of 0.09 µg/mL, and a lower limit of quantification in undiluted serum specimens of 3.0 µg/mL anti-PA IgG. The diagnostic sensitivity of the assay was 97.8%, and the diagnostic specificity was 94.2%. A competitive inhibition anti-PA IgG ELISA was also developed to enhance diagnostic specificity to 100%. The anti-PA ELISAs proved valuable for the confirmation of cases of cutaneous and inhalational anthrax and evaluation of patients in whom the diagnosis of anthrax was being considered.