Miracle-dz/UniFAR-FTUs huggingface dataset:
A new multi-mode multifunction filter using CDBA

A new multi-mode multifunction filter using CDBA is proposed. The original filter has a single current input and three voltage outputs and operates in transimpedance-mode. It can generate all biquadratic filter functions of low-pass, high-pass and band-pass, and also band-reject and all-pass filter responses by selecting different output signal combinations. This filter can be converted into voltage-mode by an additional input resistor. It can also be used in current-mode at the output by using one extra load resistor at each output. With these additional resistors at the input and outputs the filter operates in transadmittance-mode. The structure of the new filter proposed contains two capacitors, three resistors and three CDBAs.
Security Enhanced Dynamic Routing using Quasigroups Mr .

Security has become one of the major issues for data communication over wired and wireless networks. The dynamic routing algorithm is used to randomize delivery paths for data transmission which is compatible with popular routing protocols, such as the Routing Information Protocol in wired networks and Destination-Sequenced Distance Vector protocol in wireless networks, without introducing extra control messages. This paper proposes the dynamic routing algorithm with cryptography-based system design for more security in data transmission. Key words—Security, Quasigroup cryptography-based system, dynamic routing, RIP, DSDV.
Electromyographic Analysis of the Shoulder Girdle Musculature During External Rotation Exercises

Background: Implementation of overhead activity, a key component of many professional sports, requires an effective and balanced activation of the shoulder girdle muscles, particularly during forceful external rotation (ER) motions. Purpose: To identify activation strategies of 16 shoulder girdle muscles/muscle segments during common shoulder ER exercises. Study Design: Descriptive laboratory study. Method: Thirty healthy subjects were included in this study, and 16 shoulder girdle muscles/muscle segments were investigated (surface electrode: anterior, middle, and posterior deltoid; upper, middle, and lower trapezius; serratus anterior; teres major; upper and lower latissimus dorsi; and upper and lower pectoralis major; fine wire electrodes: supraspinatus, infraspinatus, subscapularis, and rhomboid major) using a telemetric electromyography (EMG) system. Five ER exercises (standing ER at 0° and 90° of abduction, with underarm towel roll, prone ER at 90° of abduction, side-lying ER with underarm towel) were studied. Exercise EMG amplitudes were normalized to EMG at maximum ER force in a standard position. Univariate analysis of variance and post hoc analysis applied on EMG activity of each muscle were used to assess the main effect of the exercise condition. Results: Muscular activity differed significantly among the ER exercises (P < .05 to P < .001). The greatest activation for anterior and middle deltoid, supraspinatus, upper trapezius, and serratus anterior occurred during standing ER at 90° of abduction; for posterior deltoid, middle trapezius, and rhomboid during side-lying ER with underarm towel; for lower trapezius, upper and lower latissimus dorsi, subscapularis, and teres major during prone ER at 90° of abduction; and for the clavicular and sternal part of the pectoralis major during standing ER with underarm towel. Conclusion: Key glenohumeral and scapular muscles can be optimally activated during specific ER exercises, particularly in positions that stimulate athletic overhead motions. Clinical Relevance: These results enable sports medicine professionals to target specific muscles during shoulder rehabilitation protocols while minimizing the effect of others, providing a foundation for optimal evidence-based exercise prescription. They also provide information for tailored muscle training and injury prevention in overhead sports.
Do Silent Brain Infarctions Predict the Development of Dementia After First Ischemic Stroke?

Abstract Background: Silent brain infarctions (SBI) are common findings in advanced age, but their relationship to dementia is still uncertain. Aim The present study was designed to evaluate whether SBI predict the development of dementia after first clinical ischemic stroke. Methods: We blindly studied admission CT scans of 102 consecutive nondemented patients presenting with ischemic stroke that clinically was their first stroke episode. SBI were defined as CT evidence of infarcts not compatible with the acute event. The patients were subsequently followed for their mental state for 2 years. Survival analysis, wherein onset of dementia was the end point, was performed on the total sample population and conducted separately on those with and without SBI at admission. Results: Dementia developed in 33 patients (32.3%), including 17 of the 37 (45.9%) with SBI and 16 of the 65 (24.6%) without SBI. Thus, dementia was strong related to SBI. Conclusion: Elderly people with silent brain infarcts and stroke have an increased risk of dementia and a steeper decline in cognitive function than those without such lesions
Alloyed Global and Local Branch History : A Robust Solution to Wrong-History Mispredictions

The need for accurate conditional-branch prediction is well known: mispred ictions waste large numbers of cycles, inhibit out-of-order execution, and waste power on mis-sp eculated computation. Prior work on branch-predictor organization has focused mainly on how to reduce conflicts i n the branch-predictor structures, while relatively little work has explored other causes of mispred ictions. Some prior work has identified other categories of mispredictions, but this paper organizes these cat egories into a broad taxonomy of misprediction types. Using the taxonomy, this paper goes on to sho w t at other categories—especially wrong-history mispredictions —are oftenmoreimportant than conflicts. This is true even if just a very simple conflict-reduction technique is used. Wrong-history mispredictions arise because current two-level, hist ory-based predictors provide only global or only local history. Their contribution to the overall misp rediction rate is substantial because most programs have some branches that require global history and also some t hat r quire local history. If only one or the other type of history is available, many branches are therefore penal ized. For SPECint95 programs using a global-history predictor, wrong-history misprediction s account for 35–50% of the total misprediction rate. By comparison, conflicts only account for 15-20%. Hybrid predictor s are one proposed solution; they use both a global-history and a local-history component. Unfortun ately, hybrid predictors only work well with large hardware budgets, because they must subdivide the availabl e area into subcomponents. Based on these observations, this paper proposes alloying local and global history together in a twolevel branch predictor structure. This is a simple but superior techniq ue for making global and local history simultaneously available and eliminating wrong-history mispredict ions. Unlike hybrid prediction, alloying gives robust performance for branch-predictor hardware budgets ranging from very large to very small. Alloying also consistently outperforms other two-level organizatio ns. In fact, a small alloyed predictor often performs as well as a much larger global-history predictor.
Optimization of a Geman-McClure like criterion for sparse signal deconvolution

This paper deals with the problem of recovering a sparse unknown signal from a set of observations. The latter are obtained by convolution of the original signal and corruption with additive noise. We tackle the problem by minimizing a least-squares fit criterion penalized by a Geman-McClure like potential. The resulting criterion is a rational function, which makes it possible to formulate its minimization as a generalized problem of moments for which a hierarchy of semidefinite programming relaxations can be proposed. These convex relaxations yield a monotone sequence of values which converges to the global optimum. To overcome the computational limitations due to the large number of involved variables, a stochastic block-coordinate descent method is proposed. The algorithm has been implemented and shows promising results.
The fine-grained realization of role-based access control

Role-based access control is now recognized as an effective way to solve large-scale enterprises uniform resource access control, It is basically meet the security requirements of the traditional closed system, With the constant expansion of the system, the RBAC model used in traditional web application has been seriously hampered the expansion of the system and improvement of the performance in the retrieval efficiency, permissions maintenance and other aspects, and in SOA model, it was difficult to meet the authorization in the process of different nodes and systems to request services and share resources with each other. To solve the above problems, Using REST-style architecture, Based on Struts 2 interceptors to implement a fine-grained role-based access control, The implementations have good flexibility and scalability.
Postprandial Hypertriglyceridemia Increases Circulating Levels of Endothelial Cell Microparticles

Background—This study evaluated a possible relationship between levels of endothelial microparticles (EMPs), known to be a sensitive indicator of endothelial disturbance, and changes in postprandial lipid levels in healthy volunteers after a low- or high-fat meal. Methods and Results—Eighteen healthy subjects without known cardiovascular risk factors were evaluated. Lipid and EMP levels were measured before and 1 and 3 hours after a single low- or high-fat isocaloric meal. The low-fat meal had no significant postprandial effect on EMPs or lipids compared with fasting levels. In contrast, a single high-fat meal significantly increased EMP levels after 1 and 3 hours, from 389±54 (thousands per milliliter) when fasting to 541±139 (P=0.0002) and 677±159 (P<0.0001), respectively, and correlated with a postprandial elevation in serum triglycerides. Conclusions—A single high-fat meal led to a significant elevation of plasma EMP levels in healthy, normolipidemic subjects and correlated with a postprandial elevation of serum triglycerides. EMPs may be an indirect marker of endothelial dysfunction or injury induced by postprandial triglyceride-rich lipoproteins.
A Novel Model for Evaluating Performance of IT Department based on Balanced Scorecard and Artificial Neural Network Approach

In this ever-changing world, the function of information technology (IT) department is becoming increasingly important. The objective of this study is to construct an approach based on balanced scorecard (BSC) and artificial neural network (ANN) for evaluating an IT department in the manufacturing industry. A novel hybrid particle swarm optimization (HPSO)-based learning method is utilized in the ANN. The reliability of the ANN model is tested by a practical example. The results show that the ANN model learned by HPSO algorithm has relative high accuracy and is better than the back propagation algorithm. The empirical findings suggest that the ANNs model can be a persuasive analytical tool for the performance evaluation of the IT department.
Mathematical analysis of steady walking states in underactuated limit cycle walking

This paper presents mathematical analyses of steady walking states in underactuated limit cycle walking. We introduce an underactuated rimless wheel with a torso to analyze target steady walking states. Then the formula of boundary conditions are derived and the properties of the steady gaits are analyzed. The transition function of state error is derived from the properties of the steady gaits, and an optimal steady walking state is generated. In addition, we generate the target steady walking speed on the underactuated rimless wheel model and verify our results using numerical simulations. As a conclusion, optimal steady states can be discovered and generated based on the mathematical analysis of dynamic walking states.
Income Distribution Changes and their Impact in the Post-World War II Period

This paper provides a survey on studies that analyze the macroeconomic effects of intellectual property rights (IPR). The first part of this paper introduces different patent policy instruments and reviews their effects on R&D and economic growth. This part also discusses the distortionary effects and distributional consequences of IPR protection as well as empirical evidence on the effects of patent rights. Then, the second part considers the international aspects of IPR protection. In summary, this paper draws the following conclusions from the literature. Firstly, different patent policy instruments have different effects on R&D and growth. Secondly, there is empirical evidence supporting a positive relationship between IPR protection and innovation, but the evidence is stronger for developed countries than for developing countries. Thirdly, the optimal level of IPR protection should tradeoff the social benefits of enhanced innovation against the social costs of multiple distortions and income inequality. Finally, in an open economy, achieving the globally optimal level of protection requires an international coordination (rather than the harmonization) of IPR protection.
Cardiac and Respiratory Patterns Synchronize between Persons during Choir Singing

Dyadic and collective activities requiring temporally coordinated action are likely to be associated with cardiac and respiratory patterns that synchronize within and between people. However, the extent and functional significance of cardiac and respiratory between-person couplings have not been investigated thus far. Here, we report interpersonal oscillatory couplings among eleven singers and one conductor engaged in choir singing. We find that: (a) phase synchronization both in respiration and heart rate variability increase significantly during singing relative to a rest condition; (b) phase synchronization is higher when singing in unison than when singing pieces with multiple voice parts; (c) directed coupling measures are consistent with the presence of causal effects of the conductor on the singers at high modulation frequencies; (d) the different voices of the choir are reflected in network analyses of cardiac and respiratory activity based on graph theory. Our results suggest that oscillatory coupling of cardiac and respiratory patterns provide a physiological basis for interpersonal action coordination.
Firm and Employee Effects of an Enterprise Information System: Micro-Econometric Evidence

We investigate the impact of adopting an enterprise resource planning (ERP) system on performance changes and employee outcomes in a retail chain. We find that: (i) sales and inventory turnover initially drop by 7 % and recover in 6-12 months; (ii) inventory turnover recovers more quickly for establishments that adopt ERP later; (iii) employee outcomes, including increased workload, greater job difficulty and enhanced multitasking, vary significantly over time, though implications for employee welfare are ambiguous.
Means Of Achieving Business Process Management Success Factors

Business Process Management (BPM) in recent years has become a highest priority area for most organizations. Since this concept is multidisciplinary, success in this endeavour requires considering different factors. A number of studies have been conducted to identify these factors; however, most are limited to the introduction of high-level factors or to the identification of the means of success within only a specific context. This paper presents a holistic framework of success factors as well as the associated means for achieving success. This framework introduces nine factors, namely culture, leadership, communication, Information Technology, strategic alignment, people, project management, performance measurement and methodology. Each of these factors are characterized further by defining some sub-constructs and under each sub construct the means for achieving success are also introduced. This framework including means for achieving success can be useful for BPM project stakeholders in adequately planning the initiative and checking the progress during the implementation.
Diagnostic Performance of Duplex Ultrasound in Patients Suspected of Carotid Artery Disease: The Ipsilateral Versus Contralateral Artery

Background and Purpose— To evaluate duplex ultrasonographic thresholds for the determination of 70% to 99% stenosis of the ipsilateral and contralateral internal carotid artery in patients with symptoms of amaurosis fugax, transient ischemic attack (TIA), or minor stroke based on 2 criteria: maximizing accuracy and optimizing cost-effectiveness and to compare these with current recommendations. Methods— From January 1997 to January 2000, a prospective multicenter study was conducted including 350 consecutive patients with symptoms of amaurosis fugax, TIA, or minor stroke who underwent bilateral duplex ultrasonography and digital subtraction angiography. A linear regression analysis was performed to estimate the degree of angiographic stenosis as a function of the peak systolic velocity (PSV). PSV thresholds were calculated for the ipsilateral and contralateral carotid arteries based on maximizing accuracy and optimizing cost-effectiveness. Results— The PSV measurements significantly overestimated the angiographic stenosis in the contralateral artery (9.5%; 95% CI, 6.3% to 12.7%) compared with the ipsilateral carotid artery. The recommended PSV threshold for the diagnosis of 70% to 99% stenosis is 230 cm/s. Maximizing accuracy, the optimal PSV threshold for the ipsilateral artery was 280 cm/s, and for the contralateral artery, 370 cm/s for diagnosing a 70% to 99% stenosis. Optimizing cost-effectiveness, the optimal PSV threshold was 220 cm/s for ipsilateral and 290 cm/s for contralateral carotid arteries. Conclusions— PSV measurements overestimate the degree of angiographic stenosis in the contralateral carotid artery in patients with symptoms of amaurosis fugax, TIA, or minor stroke. Separate PSV thresholds should be used for the ipsilateral and contralateral carotid artery. PSV thresholds that optimize cost-effectiveness differ from the recommended thresholds and from thresholds that maximize accuracy.
“A Balance That We Walk”: Characteristics, Attributes, and Behaviors That Promote Healthy American Indian Heterosexual Couple Relationships

The purpose of this study was to investigate the characteristics, attributes, and behaviors that promote healthy American Indian (AI) heterosexual couple relationships. Specific attention was given to the role AI men have in developing and maintaining healthy heterosexual couple relationships. In-depth interviews were conducted with 15 AI participants. Key themes to emerge from analysis of qualitative data included learning about healthy relationships from elders, demonstrating mutual respect and trust, showing respect for women, and honoring a “balance” between love and sex. Findings suggest that interventions for AI men that reinforce Native beliefs, values, and practices are needed to strengthen AI couple relationships.
Towards a standard conceptual typology of public sector performance measurement

ABSTRACT This article aims to enhance fundamental conceptualisation in performance measurement through the development of a standard conceptual typology of the field. Performance measurement is a common phenomenon in the worldwide public sector, and one that has attracted substantial academic attention. However, analysis has been hindered by confusing and inconsistent terminology, and a lack of clear and explicit classification schemes. The proposed typology is based on five explicit design considerations and three fundamenta divisionis. The typology produced has four elements: levels; measures; targets; and actuals. These elements relate to the nature, specific aspect and state of performance phenomena. It is likely that a standard conceptual approach will have benefits for academic analysis, by clarifying language and conceptual definitions. It is also likely to have beneficial practical implications.
Implementations for checking bisimulation of LTS

Bisimilarity is one of the most studied relations between behavioral equivalences proposed in the concurrency theory. Algorithms for checking bisimulation in finite state system are very useful for both theoretical aspects and practical applications. In order to give a detailed comparison on different implementation techniques for bisimilarity of LTS, this paper studies and implements two different algorithms: on-the-fly algorithm and quasi-local algorithm, by adopting both depth-first-search and width-first-search. The experimental results and discussions of the applicabilities and advantages of these algorithms are also performed, which show the usage of two algorithms. The research gives insights on further implementation of model-specific process calculi.
A Robust Mean Shift-Based Approach to Effectively Clustering Incomplete Educational Data

Data clustering is one of the popular tasks recently used in the educational data mining arena for grouping similar students by several aspects such as study performance, behavior, skill, etc. Many well-known clustering algorithms such as k-means, expectation-maximization, spectral clustering, etc. were employed in the related works for educational data clustering. None of them has taken into consideration the incompleteness of the educational data gathered in an academic credit system. If just a few records have missing values, we might ignore them in the mining task. However, as there are a large number of missing values, ignoring them may lead to the data insufficiency and ineffectiveness of the mining task. On the other hand, many research works have recently proposed several general-purpose solutions to incomplete data clustering. The main difficulties with these solutions for reuse are how to appropriately determine a pre-specified number of the clusters for each data set in a particular application domain and the non-arbitrary shapes of the resulting clusters. Hence, we focus on two parts: the first one that resolves the incomplete data clustering task in the education domain and the second one that proposes a robust effective approach to the aforementioned clustering task. Our resulting solution to clustering incomplete educational data is a mean shift-based clustering algorithm named iMS_nps using the nearest prototype strategy. iMS_nps can also overcome the aforementioned difficulties. In addition, experimental results have shown that the clusters from our proposed algorithm have better cluster quality as compared to some existing approaches.
Evaluation of visual object retrieval datasets

Recently visual object retrieval has being widely studied for its vast application prospect, and the progress is usually tracked by the performance achieved on benchmark datasets. Therefore, in order to faithfully evaluate object retrieval algorithms, the quality of datasets must be ensured by some means. In this paper, we propose a method to evaluate the quality of benchmarking visual object retrieval on two highly cited object retrieval datasets, the Oxford datasets and TrecVid instance search datasets. Our evaluation method leverages the essential differences between object retrieval and other similar image search, and digs out some unrevealed and rather interesting features from those datasets. To the best of our knowledge, this research has never been touched before. Our method is believed to be beneficial to dataset collection and algorithm evaluation of object retrieval. More importantly, we hope this work can attract more attentions on this topic in the community.