Miracle-dz/UniFAR-FTUs huggingface dataset:
ELEC-419 Final Report OWLympics : A Platform for Smarter Self-reporting

Tracking health related behaviors regularly helps in forming good health habits, which greatly improve our health status in the long run. Self-reporting is the most acceptable behavior tracking method, but it suffers from issues like recall bias and low consistency. We propose a novel platform to mitigate these issues: It can send smart reminders to the user’s smartphone soon after completion of an activity to be reported; the reminders are based on smart-phone context information such as location, time and historical information. Additionally, to test the effectiveness of the smart reminders in our self-reporting platform, we conducted experiments to quantitatively analyze the effectiveness of our platform.
Active Stereo-matching for One-shot Dense Reconstruction

Stereo-vision in computer vision represents an important field for 3D reconstruction. Real time dense reconstruction, however, is only achieved for high textured surfaces in passive stereo-matching. In this work an active stereo-matching approach is proposed. A projected pattern is used to artificially increase the texture of the measuring object, thus enabling dense reconstruction for one-shot stereo techniques. Results show that the accuracy is similar to other active techniques, while dense reconstruction is obtained.
iSulf-Cys: Prediction of S-sulfenylation Sites in Proteins with Physicochemical Properties of Amino Acids

Cysteine S-sulfenylation is an important post-translational modification (PTM) in proteins, and provides redox regulation of protein functions. Bioinformatics and structural analyses indicated that S-sulfenylation could impact many biological and functional categories and had distinct structural features. However, major limitations for identifying cysteine S-sulfenylation were expensive and low-throughout. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor iSulf-Cys which incorporated 14 kinds of physicochemical properties of amino acids was proposed. With the 10-fold cross-validation, the value of area under the curve (AUC) was 0.7155 ± 0.0085, MCC 0.3122 ± 0.0144 on the training dataset for 20 times. iSulf-Cys also showed satisfying performance in the independent testing dataset with AUC 0.7343 and MCC 0.3315. Features which were constructed from physicochemical properties and position were carefully analyzed. Meanwhile, a user-friendly web-server for iSulf-Cys is accessible at http://app.aporc. org/iSulf-Cys/.
Using Path Label Routing in Wide Area Software-Defined Networks with OpenFlow

Separating the control and data planes has brought many advantages such as greater control plane programmability, more vendor independence, and lower operational expenses in Software-Defined Networking (SDN). SDN deployments are possible in a variety of contexts including Wide Area Networks (WANs). However, the large propagation delays between the controller and switches raise several concerns for WANs such as performance limitations, longer routing time for flows and sensitivity of the controller placement. To address this issue, we propose a path label routing approach in SDN-based WANs using OpenFlow. Through hybridizing traditional hop-by-hop routing with path label routing, we reduce flow routing time and controller state distributions. In addition, we present an implement method without modifications to OpenFlow. Finally a prototype is implemented as a proof of the method in OPNET simulator. Experimental results demonstrate that the approach can bring significant performance gains such as the reduction of state distribution and the sensitivity of controller placement in SDN-based WANs.
A Microserver View of HTMT : New Benchmarks and Applications for HTMT Technical Report

HTMT is an ambitious new architecture combining cutting edge technologies to reach peta op performance sooner than current technology trends allow. It is a massively parallel architecture with multi-threaded hardware and a multi-level memory hierarchy. Microservers provide a new perspective for viewing this memory hierarchy whereby memory is actively involved in process execution. This work discusses the microserver memory semantics and initial HTMT execution models to analyze applications at each level of the system hierarchy and to develop user-level functions for expressing this inherent concurrency and parallelism. In order to do this we studied several applications to model the control and data ow within the HTMT hierarchy and developed pseudo-code representing the user-level functions necessary to express application concurrency and parallelism.
Wealth of Immigrant and Native-Born Americans 1

This study hypothesizes nativity differences in the process of wealth accumulation with regards to accumulation rates, dissaving rates, the role of human capital, saving intention for children, and structural barriers to wealth accumulation. Based on an analysis of the 1992 and 1993 panels of the Survey of Income and Program Participation (SIPP), it reports four major findings. First, levels of net worth, life cycle patterns, and wealth components are primarily stratified by national origin and race-ethnicity rather than by nativity. Second, when immigrants’ adult years in the United States are taken into account, the life cycle pattern of wealth of the post-1965 immigrants catches up with that of natives within 22 years of arrival and then overtakes natives. Third, the process of wealth accumulation is similar for immigrants and natives in all but two respects – for immigrants, education is discounted and adult years in the United States matter. Lastly, spatial segregation has a uniform negative effect on wealth for both immigrants and natives.
Addition of vitamin D status to prognostic scores improves the prediction of outcome in community-acquired pneumonia.

BACKGROUND Vitamin D plays a role in host defense against infection. Vitamin D deficiency is common worldwide. The prognostic value of vitamin D levels in pneumonia is unknown. In this study, we aimed to investigate the impact of vitamin D status on outcome in community-acquired pneumonia (CAP). METHODS We conducted a prospective cohort study in 272 hospitalized patients with CAP. Levels of 25-hydroxyvitamin D, leukocytes, C-reactive protein, and total cortisol and the Pneumonia Severity Index (PSI) and CURB-65 scores were measured on admission. Major outcome measures were intensive care unit (ICU) admission and 30-day mortality. RESULTS One hundred forty-three patients (53%) were vitamin D deficient (<50 nmol/L), 79 patients (29%) were vitamin D insufficient (50-75 nmol/L), and 50 patients (18%) were vitamin D sufficient (>75 nmol/L). Vitamin D deficiency was associated with an increased risk of ICU admission and 30-day mortality. Vitamin D status was an independent predictor of 30-day mortality (area under the curve [AUC] =0.69; 95% confidence interval [CI], .57-.80). Multivariate regression analysis including all predictors for outcome resulted in a final model including vitamin D status and the PSI score, with a significantly higher prognostic accuracy compared with the PSI score alone (AUC=0.83; 95% CI, .71-.94). CONCLUSIONS Vitamin D deficiency is associated with adverse outcome in CAP. Vitamin D status is an independent predictor of 30-day mortality and adds prognostic value to other biomarkers and prognostic scores, in particular the PSI score. CLINICAL TRIALS REGISTRATION NCT00471640.
The Effects of Acute Stress on Memory, Attention and Cognition in Healthy Human Volunteers

The study was designed to investigate the effects of an acute naturalistic stressor, namely, examination of stress on memory, attention and cognition in healthy human volunteers. Fifty-three students participated in this study. All the volunteers were assessed for their neuropsychological states, which are memory, attention and cognition, during non-examination and examination period. The neuropsychological tests used in this study were- logical memory test, digit span test, letter cancellation test, trail making test and Stroop test. It was revealed that there was significant difference (p<0.05) in the score of logical memory II, backward and total score of digit span, time taken to complete letter cancellation test and score in part C of Stroop test in the exam period. The present study thus demonstrated that acute naturalistic stress improves attention while impairs delayed memory retrieval and cognition. Bangladesh Pharmaceutical Journal 20 (1): 14-19, 2017
Towards the reliable integration testing: UML-based scenario analysis using an automatic prototype generation tool

One key to success for high quality enterprise information systems development is to validate the customers' requirements sufficiently at the early stage. Scenarios are an effective means to an end because they make it possible to represent various situations of system usage. Most scenarios are defined by using a natural language or such a formal language as Unified Modeling Language (UML) and describe normal, alternative, and exceptional service flows from the point of view of system usage. As a result, scenarios make it easy for the customers to confirm their requirements intuitively because of the concreteness. On the other hand, based on the V-model, which is well-known software development process and denotes the correspondence of requirement analysis stage to integration test stage, it is desirable that the testers should test the system by using the test cases derived from the validated scenarios. We have proposed a UML-based requirements analysis (RA) model with automatic prototype system generation for enterprise Web application development. This paper proposes a way to efficiently create reliable test cases from the scenarios that have been validated by the customers using the prototype system which was generated by the RA model.
Node addition and removal in the presence of don't cares

This paper presents a logic restructuring technique named node addition and removal (NAR). It works by adding a node into a circuit to replace an existing node and then removing the replaced node. Previous node-merging techniques focus on replacing one node with an existing node in a circuit, but fail to replace a node that has no substitute node. To enhance the node-merging techniques on logic restructuring and optimization, we propose an NAR approach in this work. We first present two sufficient conditions that state the requirements of added nodes for safely replacing a target node. Then, an NAR approach is proposed to fast detect the added nodes by performing logic implications based on these conditions. We also apply the NAR approach to circuit minimization together with two techniques: redundancy removal and mandatory assignment reuse. We conduct experiments on a set of IWLS 2005 benchmarks. The experimental results show that our approach can enhance the state-of-the-art ATPG-based node-merging approach. Additionally, our approach has a competitive capability of circuit minimization with 44 times speedup compared to a SAT-based node-merging approach.
On the capacity of multihop device-to-device caching networks

We consider a wireless device-to-device (D2D) network where n nodes are uniformly distributed at random over the network area. We let each node with storage capacity M cache files from a library of size m. Each node in the network requests a file from the library independently at random, according to a popularity distribution, and is served by other nodes having the requested file in their local cache via (possibly) multihop transmissions. Under the classical “protocol model” of wireless networks, we characterize the optimal per-node capacity scaling law for a broad class of heavy-tailed popularity distributions including the Zipf distribution with Zipf exponent less than one. Surprisingly, in the parameter regimes of interest, we show that decentralized random caching uniformly across the library yields optimal per-node capacity scaling of Θ(√M/m), which outperforms the single-hop caching networks whose capacity scales as Θ (M/m) [1], [2].
Continuous Experience-aware Language Model

Online review communities are dynamic as users join and leave, adopt new vocabulary, and adapt to evolving trends. Recent work has shown that recommender systems benefit from explicit consideration of user experience. However, prior work assumes a fixed number of discrete experience levels, whereas in reality users gain experience and mature continuously over time. This paper presents a new model that captures the continuous evolution of user experience, and the resulting language model in reviews and other posts. Our model is unsupervised and combines principles of Geometric Brownian Motion, Brownian Motion, and Latent Dirichlet Allocation to trace a smooth temporal progression of user experience and language model respectively. We develop practical algorithms for estimating the model parameters from data and for inference with our model (e.g., to recommend items). Extensive experiments with five real-world datasets show that our model not only fits data better than discrete-model baselines, but also outperforms state-of-the-art methods for predicting item ratings.
Kako škole vide sebe: analiza samoevaluacijskog upitnika u projektu samovrednovanja škola

The paper presents the qualitative analysis of schools' responses to self-evaluation questionnaire used in the process of school self-analysis and self-evaluation. Based on the school effectiveness model, themes covered in the questionnaire included financial and material conditions of schooling, school management, quality of teaching processes, quality of teaching plans and programmes, support programmes for pupils, presence of extracurricular activities in school, partnership with parents and local community etc. The analysis gave insight into the self-perceptions of schools and their position regarding possible steps toward school improvement.
An Efficient Feature Selection Method for Arabic Text Classification

This paper proposes an efficient, Chi-Square-based, feature selection method for Arabic text classification. In Data Mining, feature selection is a preprocessing step that can improve the classification performance. Although few works have studied the effect of feature selection methods on Arabic text classification, limited number of methods was compared. Furthermore, different datasets were used by different works. This paper improves the previous works in three aspects. First, it proposes a new efficient feature selection method for enhancing Arabic text classification. Second, it compares extended number of existing feature selection methods. Third, it adopts two publicly available datasets to encourage future works to adopt them in order to guarantee fair comparisons among the various works. Our experiments show that our proposed method outperformed the existing methods in term of accuracy.
The effects of providing a brief training package to daycare teachers to teach a child a sign for social attention

Behavioral skills training (BST) packages have been successful in increasing change agents’ correct implementation of various procedures. The current study evaluated the effects of a brief BST package to train daycare teachers to implement incidental teaching procedures with toddlers. The brief BST consisted of a set of written instructions, a two-minute video model, rehearsal, and feedback during session. Results demonstrated that teachers increased their correct implementation of incidental teaching procedures following training. In addition, two of the three toddlers increased the frequency of signs to request attention.
Utility Maximising Design of Means Tested Retirement

The design of welfare benefits is a tricky business. In this respect, James Meade placed particular emphasis on the importance of avoiding excessive distortions to the price of labour. Nevertheless, Meade noted that means testing is likely to be desirable in view of the 'hideously expensive' cost of universal benefits provision N he conjectured that a 50% withdrawal rate on welfare benefits might be appropriate. In this study we take a fresh look at the role of means testing in the provision of retirement benefits in the United Kingdom. We use an articulated rational agent model of the household to explore the effects on expected lifetime utility of alternative budgetary neutral pensions arrangements. In this context, we find that extensive means testing of retirement benefits is preferred, consistent with the conjectures stated by Meade. Our analysis highlights the importance of taking into account the distortions associated with alternative methods of benefits financing when considering pensions reform.
Feel Good, Think Smart: the role of emotion in learning

One of the most exciting developments in recent brain research is the better understanding of emotions. Basically they are a preparation for action – they motivate us to do things crucial for our survival, often related to food, love, sex, or achievement. They include typically less intense ones such as interest, enjoyment, contentment, anticipation, boredom, frustration or disappointment. Emotions should be moderately activated for optimal learning, but when emotions become too strong, learning is inhibited.
Comparative Analysis of IEEE 802.11p and IEEE 802.16-2004 Technologies in a Vehicular Scenario

A major challenge of the automobile industry and safety authorities is how to improve the way cars can communicate either among themselves or with infrastructure designed to assist drivers. Sichitiu and Kihl in [1] describe a taxonomy based on the way nodes (in this case, cars) exchange data. Their work involves two forms of vehicular communication: vehicle-to-vehicle communication (IVC) and vehicle to roadside communication (RVC). IVC can employ either a one hop strategy between two cars (SICV) or multi-hop strategy between many cars (MIVC). It is important to note that multi-hop strategies begin with one car but use several other cars to relay the information to the car requiring the information. Furthermore, the communication strategy can also be either ubiquitous (URVC) or scarce (SRVC). Because of the highly dynamic nature and multiple demands inherent in Vehicular Communication Networks (VCN), these networks have their own very unique requirements:  The radio transceiver technology must provide omni-directional coverage.  Rapid vehicle-to-vehicle communications must keep track of dynamic topology changes.  Highly efficient routing algorithms need to fully exploit network bandwidth. The increased interest in vehicle-to-vehicle (IVC) and vehicle-to-roadside communication (RVC) is due, in part, to the need to expand the amount of information relayed to vehicles. As previously mentioned, the information relayed today is no longer limited to cellular telephone service. As the need to transmit more information grows, so must the technology used to carry that information from car to car or from communications tower to tower. Some applications are more suitable for vehicle-to-roadside communications in applications that involve automatic payment, route guidance, cooperative driving and parking management, just to name just a few. However, there are other applications that are more appropriate for vehicle-to-vehicle communications, including intelligent cruise control, intelligent maneuvering control, lane access and emergency warning, among others. Basically, there are three main categories of applications that have been targeted: (i) road safety applications, (ii) traffic efficiency applications, and (iii) value-added applications. Each
Institutions are neither autistic maximizers nor flocks of birds: self-organization, power and learning in human organizations

In this work we shall attempt an excursus across fundamentally different streams of modern interpretations of the 'primitive entities' constituting the social fabrics of economic systems. Behind each specific interpretative story, there is a set of ceteris paribus assumptions and also some fictitious tale on a 'once upon a time' reconstruction of the theoretical primitives of the story itself. Pushing it to the extreme, as we see it, there are in the social sciences two archetypal (meta) tales. The first says, more or less, that 'once upon a time' there were individuals with reasonably structured and coherent preferences, with adequate cognitive algorithms to solve the decision-action problems at hand, and with self-seeking restrictions on preferences themselves. They met in some openings in the forest and, conditional on the technologies available, undertook some sort of general equilibrium trading or, as an unavoidable second best, built organizations in order to deal with technological non-convexities, trading difficulties, contract enforcements, etc. In the alternative tale, 'once upon a time' there were immediately factors of socialization and preference-formation of individuals, including some institutions like families shaping desires, representations and, possibly, cognitive abilities. Non-exchange mechanisms of interactions appear in the explanation from the start: authority, violence and persuasion of parents upon children; obedience; schools; churches; and, generally, the adaptation to particular social roles. Here 'institutions' are the primitives, while 'preferences' and the very idea of 'rationality' are derived entities. Which of the primitive tale is chosen bears far-reaching consequences for the interpretation of socio-economic organizational forms and their dynamics, and involves different theoretical commitments on the interactions between agencies and structures in human affairs. In this work, we argue for the need of moving away from rationality-cum-equilibrium interpretations and of focusing on the varying balances between selfuorginizing dynamics and institution-shaped constraints.
Targeted Delivery of Protein Drugs by Nanocarriers

Recent advances in biotechnology demonstrate that peptides and proteins are the basis of a new generation of drugs. However, the transportation of protein drugs in the body is limited by their high molecular weight, which prevents the crossing of tissue barriers, and by their short lifetime due to immuno response and enzymatic degradation. Moreover, the ability to selectively deliver drugs to target organs, tissues or cells is a major challenge in the treatment of several human diseases, including cancer. Indeed, targeted delivery can be much more efficient than systemic application, while improving bioavailability and limiting undesirable side effects. This review describes how the use of targeted nanocarriers such as nanoparticles and liposomes can improve the pharmacokinetic properties of protein drugs, thus increasing their safety and maximizing the therapeutic effect.