Miracle-dz/UniFAR-FTUs huggingface dataset:
Social work and service learning : partnerships for social justice

Chapter 1 Service Learning and Social Work Education: A Natural but Tenuous Connection Chapter 2 The Components of Service Learning as Pedagogy in Social Work Education Chapter 3 Service Learning Across the Social Work Curriculum Chapter 4 Social Welfare Policy and Services: Service Learning through Social Policy Projects in Human Service Organizations Chapter 5 Social Work Practice: Beginning Practice Skill Development in Introduction to Social Work Courses: Mobilizing Partnerships between Youth Development Agencies and Social Work Education through Service Learning Chapter 6 Research: Infusing Service Learning into Research, Social Policy, and Community-Based Practice Chapter 7 Human Behavior and the Social Environment: An Oral History Service-Learning Project Chapter 8 Human Diversity: Service Learning and Gender Studies within a Gay, Lesbian, Bisexual, and Transgender (GLBT) Context Chapter 9 Populations-at-Risk/Immersion Experience: Social Work in the Sun: Service Learning at Summer Camp Chapter 10 General Education: Herding Cats and Making History: Service Learning in a Large General Education Social Welfare Course Chapter 11 Developing Partnerships between Community and Curriculum: How Does the Team Assess Student Outcomes? Chapter 12 Service Lerning for Social Justice: Mandate for Long-Term Evaluation? Chapter 13 Service Learning in Social Work: A Curricular and Evaluative Model Chapter 14 Social Work, Service Learning, and the American Democracy Project: The Creation of a More Socially Conscious Campus Community
A Bespoke Approach For Face-Recognition Using PCA

In this paper we have developed a bespoke approach to face recognition with Eigenfaces using principal component analysis. We have focused on the effects of taking the number of significant eigenfaces. Eigenfaces approach is a principal component analysis method, in which a small set of characteristic pictures are used to describe the variation between face images. Experimental results using MATLAB are demonstrated in this paper to verify the viability of the proposed face recognition method. It shows that only 15% of Eigenfaces with the largest eigen values are sufficient for the recognition of a person. It also shows that if the minimum Euclidian distance of the test image from other images is zero, then the test image completely matches the existing image in the database. If minimum Euclidian distance is non-zero but less than threshold value, then it is a known face but having different face expression else it is an unknown face.
Pediatric Balance Scale: A Modified Version of the Berg Balance Scale for the School‐Age Child with Mild to Moderate Motor Impairment

Purpose: The Pediatric Balance Scale (PBS), a modification of Berg's Balance Scale, was developed as a balance measure for school‐age children with mild to moderate motor impairments. The purpose of this study was to determine the test‐retest and interrater reliability of the PBS. Methods: To determine test‐retest reliability, 20 children (aged five to 15 years) with known balance impairments were tested by one examiner on the PBS. Ten pediatric physical therapists independently scored 10 randomly selected videotaped test sessions. Results: There was no significant difference in total test scores [intraclass correlation coefficient (ICC) model 3,1 = 0.998] or individual items (Kappa Coefficients, k = 0.87 to 1.0; Spearman Rank Correlation Coefficients, r = 0.89 to 1.0) measured by one therapist on two occasions. No significant difference among ratings by different physical therapists was found on the PBS for total test score (ICC 3,1 = 0.997). Conclusion: The PBS has been demonstrated to have good test‐retest and interrater reliability when used with school‐age children with mild to moderate motor impairments. (Pediatr Phys Ther 2003;15:114‐128)
Radial Density Profiles of Time-Delay Lensing Galaxies

We present nonparametric radial mass profiles for 10 QSO strong-lensing galaxies. Five of the galaxies have profiles close to ρ(r) ∝ r-2, while the rest are closer to r-1, consistent with an NFW profile. The former are all relatively isolated early types and dominated by their stellar light. The latter—although the modeling code did not know this—are either in clusters, or have very high mass-to-light ratios, suggesting dark matter-dominant lenses (one is actually a pair of merging galaxies). The same models give H = 15.2 Gyr (H0 = 64 km s-1 Mpc-1), consistent with a previous determination. When tested on simulated lenses taken from a cosmological hydrodynamical simulation, our modeling pipeline recovers both H0 and ρ(r) within estimated uncertainties. Our result is contrary to some recent claims that lensing time delays imply either a low H0 or galaxy profiles much steeper than r-2. We diagnose these claims as resulting from an invalid modeling approximation: that small deviations from a power-law profile have a small effect on lensing time delays. In fact, as we show using both perturbation theory and numerical computation from a galaxy formation simulation, a first-order perturbation of an isothermal lens can produce a zeroth-order change in the time delays.
PrimeTile: A Parametric Multi-Level Tiler for Imperfect Loop Nests

Tiling is a crucial loop transformation for generating high-performance code on modern architectures. Efﬁcient generation of multilevel tiled code is essential to maximize data reuse in deep memory hierarchies. Tiled loops with parameterized tile sizes (not compile time constants) facilitate runtime feedback and dynamic optimizations used in iterative compilation and automatic tuning. Previous parametric multi-level tiling approaches have been restricted to perfectly nested loops, where all assignment statements are contained inside the innermost loop of a loop nest. Previous solutions to tiling for imperfect loop nests have been limited to the case where tile sizes are ﬁxed. In this paper, we present an approach to parameterized multilevel tiling for imperfectly nested loops. The tiling technique generates loops that iterate over full rectangular tiles, making them suitable for compiler optimizations such as register tiling. Experimental results using a number of computational benchmarks demonstrate the effectiveness of the developed tiling approach.
Design of Multidimensional Franchise Auctions by an Ignorant Principal

The paper’s main aim is to identify under which conditions the criterion of prior-independent optimality is applicable in the design of multidimensional franchise auctions. We first establish an impossibility result for second-score auctions by showing that in single-crossing environments necessary and sufficient condition for score functions to be optimal in this sense is that bidders have equal variable cost functions. Then we show that the result is not confined to the second-score format but holds for any scoring auction under stochastic independence. Therefore, a regulator who has no information at all about firms’ costs cannot in such circumstances avail himself of prior-independent optimality as choice criterion. Conversely, if variable cost functions are equal across potential contractors, as is likely in certain public services markets, and the regulator knows it, it is possible for him to implement a prior-independent optimum by scoring bids according to the social welfare function under various auction formats, including first- and second-score auctions. This simple prescription however no longer applies if the regulator is ignorant about market demand too. In this case a fully rational choice of the score function is precluded, though it may be possible to make a reasonable one: a brief discussion of this point closes the paper.
HAS: Hidden anti-theft system based on wireless sensor networks

Wireless sensor networks(WSNs) are being widely deployed for many monitoring applications, of which a popular one is anti-theft. However, current WSN technologies for anti-theft are either very susceptible to the environment interference or easily compromised by the thieves. Hence, they fail to achieve the desired effectiveness in many anti-theft scenarios. To address these limitations, this paper proposes a novel Hidden Anti-theft System (HAS) to monitor theft intrusion, which is based on the influences of theft intrusion on signal strength according to the shadowing effect in wireless communication. The theft intrusion is detected by finding abnormal RSSI samples of a wireless link compared with the stable range of signal strength in the link's normal state. Through the proposed monitoring approach, HAS can effectively detect intrusion while keeping invisible. In HAS system, to achieve load balance for detection task, we propose an efficient algorithm to determine the set of links that each node monitors. To reduce the response time, a dual-layer scanning solution with dual-radio nodes is proposed to scan the monitoring area more intensively. The experiment results show that the efficiency of HAS. HAS achieves very low false positive and false negative rates, and the response time of dual-layer scanning is 54.2% less than single layer scanning.
Prevalence of Metformin Use and the Associated Risk of Metabolic Acidosis in US Diabetic Adults With CKD

AbstractThe use of metformin in chronic kidney disease (CKD) population has been intensely debated with conflicting evidence. Large population studies are needed to inform risk assessment and therapeutic decision-making. We evaluated the associations among metformin, metabolic acidosis, and CKD in a 10-year nationally representative noninstitutionalized civilian population in the United States.In this cross-sectional study, a total of 2279 diabetic adults aged 20 years or older in the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2012 were included and had measurements of serum bicarbonate, sodium, potassium, and chloride. The exposure was metformin use. The outcome was subclinical and severe metabolic acidosis defined by serum bicarbonate <23 mEq/L and anion gap > 16mEq/L and by serum bicarbonate < 20 mEq/L, respectively.The prevalence of metformin use decreased from 67.2% among CKD-1 and -2, 40.6% among CKD-3, to 1.3% among advanced CKD-4 and -5. Across CKD stages up to CKD-3b, we observed a tendency of lower levels of serum bicarbonate that was significant in metformin users with CKD-2 and CKD-3a and marginally significant with CKD-3b compared to nonmetformin users. The corresponding tendency of higher anion gap in metformin users with the estimated glomerular filtration rate >60 mL/min/1.73 m2 was also observed. In multiple linear regression analysis, metformin was significantly associated with decreased serum bicarbonate levels (&bgr; = −0.45, 95% CI: −0.73, −0.17) and increased serum anion gap levels (&bgr; = 0.40, 95% CI: 0.19, 0.61). The adjusted odds ratio of subclinical high anion gap and severe metabolic acidosis for metformin users was 1.68 (95% CI: 1.11, 2.55) and 1.31 (0.49, 3.47), respectively. The association between metformin and serum bicarbonate was significantly modified by CKD status. No interaction was found between metformin and CKD stages for serum anion gap and acidosis.Metformin is associated with subclinical metabolic acidosis but not with severe metabolic acidosis. The propensity of serum bicarbonate-lowering effect was intensified in advanced CKD; however, such tendency was not associated with the risk of clinically defined acidosis. Our findings highlight a potential of cautious expansion of metformin use among CKD-3b patients with diabetes meriting further investigations.
Encoding the state of integrated circuits: a proactive and reactive protection against hardware Trojans horses

Hardware Trojan Horses (HTH) are a serious threat to semiconductor industry with significant economic impact. However, most of the research in HTH focuses on detection. We propose the concept of "encoded circuit", as a technique to protect HTH insertion. Encoded circuit is based on the theory of codes. It encodes the internal state with a chosen code of security parameter d, such that knowledge of less than d bits of the encoded state reveals no information about the actual state. This parameter stems from a similar notion introduced by Ishai, Sahai and Wagner at CRYPTO 2003 for the prevention of probing attacks. Usually d < 10 in probing attacks, whereas HTH are able to connect to more than 10 nets. In this paper, we discuss the theory behind "encoded circuits" and its practical demonstration on various HDL circuits.
Tualatin: Towards network security service provision in cloud datacenters

Multi-tenant infrastructures deployed in cloud datacenters need network security protection. However, the rigid control mechanism of current security middleboxes induces inflexible orchestration, limiting the agile and on-demand security provision in virtualized datacenters. This paper presents Tualatin, a consolidated framework of delivering security services in multi-tenant datacenters. It meets security requirements of different scenarios by hardware and software co-design. Leveraging Software-Defined Networking (SDN) and OpenFlow techniques, Tualatin provides fine-grained security protection in dynamically changing network topologies, where both switches and security middleboxes are programmatically controlled by logically centralized controllers. With service-level APIs exposed, Tualatin could be easily integrated with other Cloud Management System (CMS). A proof-of-concept system has been deployed in a Tier-IV datacenter, providing customizable network security services for tenant Virtual Private Cloud (VPC) infrastructure.
Design of frequency invariant beamformers in subbands

A least squares approach to the design of frequency invariant beamformers (FIBs) in subbands is proposed. In this approach, the desired fullband beam response is first expressed as a function of the subband beamformer coefficients, and then a closed form solution is obtained based on a constrained least squares formulation. Two design examples are provided, with one based on a uniform linear array and one based on a scaled aperture.
Inter-layer FEC decoded multi-layer video streaming

Layered video coding creates multiple layers of unequal importance, where the enhancement layers will be affected when the base layer is corrupted. In this treatise, a novel inter-layer FEC scheme is investigated, where the information of the base layer1 is incorporated into the systematic bits of the enhancement layers with the aid of an exclusive-OR operation. When the base layer can be recovered independently, the soft information of the enhancement layers can be deduced by flipping the sign of the check information received. In this case, the protection strength of the enhancement layer is unaffected and no extra protection bits are required. Otherwise, the inter-layer FEC decoding philosophy related to the base layer and the enhancement layer will be activated to assist in decoding the base layer, where the protection of the enhancement layer is additionally exploited to protect the base layer. Data partitioning based experiments show that our proposed scheme outperforms the traditional unequal error protection FEC aided transmission system by about 1.8 dB of channel SNR or 7.7 dB of PSNR at an acceptable complexity.
Analgesic and Anti-Inflammatory Activities of the Methanol Extract from Pogostemon cablin

Pogostemon cablin (PC) is a herbal medicine traditionally applied to treat not only common cold, nausea and diarrhea but also headache and fever. The aim of this study was to investigate the analgesic and anti-inflammatory properties of standardized PC methanol extract (PCMeOH) in vivo. Investigations were performed in mice with two analgesic models. One was acetic acid-induced writhing response and the other formalin-induced paw licking. The anti-inflammatory effect was tested by λ-carrageenan (Carr)-induced mice paw edema. These analgesic experimental results indicated that PCMeOH (1.0 g/kg) decreased the acetic acid-induced writhing responses and PCMeOH (0.5 and 1.0 g/kg) decreased the licking time in the second phase of the formalin test. Moreover, Carr-induced paw edema inflammation was significantly reduced in a dose-dependent manner when PCMeOH (0.5 and 1.0 g/kg) was administered 3 and 4 h after the Carr injection. Mechanistic studies showed that PCMeOH decreased the levels of malondialdehyde in the edema paw by increasing the activities of anti-oxidant enzymes, such as superoxide dismutase, glutathione peroxidase and glutathione reductase, in the liver and decreasing the cyclooxygenase 2 and tumor necrosis factor-α activities in the edema paw. This study has demonstrated the analgesic and anti-inflammatory effects of PCMeOH, thus verifying its popular use in traditional medicine.
Interpretable features for meaning in context

Recently, interpretable vector spaces have been introduced, vector spaces in which individual dimensions are meaningful. For polysemous words, interpretable vectors mix features from different senses. In this paper, we propose the task of computing contextspecific interpretable representations for individual senses of a word. Focusing on computing features that describe circumstances of an event, we find that the task is feasible: The best vector contextualization model, component-wise multiplication, achieves positive ratings in 83% of all cases, compared to 58% for a baseline model.
Computational Modeling Approaches for Studying of Synthetic Biological Networks

Synthetic biology is an emerging field that strives to build increasingly complex biological networks through the integration of molecular biology and engineering. The growth of the field has been supported by progress in the design and construction of synthetic genetic and protein networks. This has led to the possibility of assembling modular components to attain novel biological functions and tools. In addition, these synthetic networks give rise to insights that facilitate the investigation of interactions and phenomena in naturally-occurring networks. Integration of well-characterized biological components into higher order networks requires computational modeling approaches to rationally construct systems that are directed towards a desired outcome. A computational approach would improve the predictability of the underlying mechanisms that would otherwise be difficult to deduce through experimentation alone. The analysis and interpretation of both qualitative and quantitative models also becomes increasingly important towards taking a systems-level perspective on synthetic genetic and protein networks. This review will first discuss the analogy of synthetic networks to circuit engineering. It will then look at computational modeling approaches that can be applied to biological systems and how synthetic biology will help to develop more accurate in silico representations of these systems.
Operations Analysis of Isolated And Connected Micro-Grid with CHP Using MIP

As energy demands around the world increase, the need for renewable energy sources, such as Micro-Grid (MG) that will not harm the environment has been increased. Micro-Grid has been extensively investigated as a promising solution to energy challenges in 21st century. The optimal generation is one of the important functions for the Micro-Grid operation. It should be noted that supplying thermal load with combined heat and power systems is one of the most evident features of the Micro-Grids which increase the efficiency of the system. In this study, the operation of Micro-Grids by considering two kinds of state i.e. isolated and connected is investigated and the results for these different states are compared together. In addition, the effect of CHP systems in a Micro-Grid and the possibility of collaboration of Micro-Grid in power supply marketing is studied. The results indicate that existences of CHP systems leads to reduction of operating cost; consequently, consumers pay less for energy. So this proposed model is used to reduce the total operating costs. The equations of Micro-Grids are solved using the mathematical analysis which is based on the application of Mixed Integer Programming (MIP).
Combine Qualitative and Quantitative Methods to Create Persona

Persona as a user archetype is widely used in interactive design process. Persona is created with qualitative methods such as user observation and interview. This approach has met some criticisms for its reliability. We propose to combine the qualitative approach with quantitative methods. We use cluster analysis to group the users into subgroups. We select subgroups of users that have similar goals. We abstract Persona with information obtained from user observations and interview. We illustrate the steps of this approach through a case study. Finally, we discuss a few key points in Persona creation and outline some future research directions.
A BP Neural Network Based Method for Upper Limb Motion Strength Evaluation

Motion intensity is a comprehensive property to reflect to the motion speed, motion frequency and motion explosive power. Motion intensity evaluation plays a very important role in both the stroke patients' rehabilitation program development and competitive athletes' daily training. The traditional motion intensity evaluation takes the heart rate or rate of perceived exertion as evaluation parameters, which can't determine the motion intensity of peoples because everyone has subtile differences in these aspects. This paper proposes a new upper limb motion intensity evaluation model based on BP neural network, whose inputs are the change rate of angle and motion amplitudes which are computed according to the measured values from the three-axis acceleration sensor, and whose output is the motion intensity grade. This new model is verified via the MATLAB neural network toolbox, and the simulation experiment shows that the model has higher efficiency in evaluating the upper motion intensity grade than the traditional method and the accuracy rate reaches 93.75%.
Concretization and animation of Finite Automata with c-cards

The paper presents a new way of introducing finite automata to classes of 10 to 12 years old, and in general to students with a limited mathematical background. Our approach builds on computational cards (or c-cards), a project aiming at scaling-down the learning complexity of computer science core contents, by presenting symbol manipulation via a tangible, physical metaphor. C-cards are still at a very early stage of development as an educational tool, yet we believe they represent a nice, intuitive mind-tool, that can be consistently applied to a variety of (theoretical) computer science concepts. Here an algorithm for mapping finite automata on c-cards is given and its educational implication discussed: the mapping provides a mean to concretize and animate automata. The algorithm works with both deterministic and non-deterministic finite automata.
Subspace Clustering via Graph Regularized Sparse Coding

—Sparse coding has gained popularity and interest due to the beneﬁts of dealing with sparse data, mainly space and time efﬁciencies. It presents itself as an optimization problem with penalties to ensure sparsity. While this approach has been studied in the literature, it has rarely been explored within the conﬁnes of clustering data. It is our belief that graph-regularized sparse coding can lead to a data space with discriminative features that can be clustered so that these clusters can be applied to various areas of interest in the ﬁeld, such as video segmentation and tracking. In this paper, we propose a framework for clustering via graph-regularized sparse coding and apply this framework to video segmentation and image patch correspondence.