Miracle-dz/UniFAR-FTUs huggingface dataset:
An initial model for designing socially translucent systems for behavior change

Applications aiming at behavior change are gaining momentum within HCI. Much of that work has been built upon the idea of psychological empowerment. We report on a qualitative study that aimed at inquiring at an alternative path to behavior change through strengthening individuals' feelings of personal accountability. Two behavior-change-related scenarios were construed to evaluate how people perceive socially translucent systems aiding the process of behavior adaptation. We found that motivation to change is shaped by the access to information concerning one's behavior, by the type of provided feedback and the strength of the social ties accessing that information. Based on these results we propose an initial model defining possible approaches that can be considered when designing socially translucent systems supporting behavior change.
Personalized Recommendation of Research Papers by Fusing Recommendations from Explicit and Implicit Social Network

Combining social network information with collaborative filtering recommendation algorithms has helped to alleviate some drawbacks of collaborative filtering, for example, the cold start problem, and has increased the accuracy of recommendations. However, the user coverage of recommendation for social-based recommendation is low as there is often insufficient data about explicit social relationships among users. In this paper, we fuse recommendation that uses explicit social relations (friends and co-authors) with recommendations that use implicit social relations aiming to increase the user coverage with minimum recommendation accuracy loss. We found that fusing recommendations from friends with recommendations using implicit social networks increases both accuracy and user recommendation coverage while fusing recommendation from co-authors increase the coverage.
The time index+: an incremental access structure for temporal databases

1 Introduction In this paper, we propose a new indexing structure, called the Time Index+, which extends the incremental structure techuique introduced in the Time Index [E1WK90, Kour94]. The Time Index performs well for data that often overlaps and has a non– uniform distribution. However, it requires huge amounts of storage aud suffers from degradation in update p erformauce. The Time Index+ overcomes the deficiencies of the Time Index by proposing au efficient new storage model for partitioning logical buckets and by suggesting a graceful new method for handling object versions with long and very long time intervals. We validate our claims for the efficiency of our new tectilques by analyzing and comparing four indexing structures: the Time Index+, the Time Index, the Packed R-Tree [RoLe85, KaFa93], and the Parametrized R–Tree. Our experiments identify impor-taut parameters, and show how they affect the performance of the four considered indexing structures. These include meau of version lifespan, block size, query time intervaf length, aud total number of versions. Our simulation results show that: (1) The Time Index+ pre vides au improvement in searck time of 10~o over the Time Index, of au order of magnitude over the Packed R–Tree, and of at least 100~0 over the Parametrized R–Tree and (2) The Time Iudex+ requires on average 60~0 less storage than the the Time Index but 51)~o more storage than the Packed R–Tree and the Parametrized R–Tree. Permission to co y without fee all or part of this material is F granted provided t at the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association of Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. Temporal databases support both valid tin e, which records a history of changes in the real world, rmd transaction time, wh,ch records a hktory of updates made to the database. This permits users to query over the complete history of a given Universe of Discourse. However, the incorporation of time in database models has a profound impact on every facet of database implementation. An important facet that requires a complete re–evaluation is indexing techniques aud search methods, which is the topic of this paper. Current trends suggest that database systems will need to manage ever–larger volumes …
Asymptotic Distribution of the OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model

We find the asymptotics of the OLS estimator of the parameters $\beta$ and $\rho$ in the spatial autoregressive model with exogenous regressors $Y_n = X_n\beta+\rho W_nY_n+V_n$. Only low-level conditions are imposed. Exogenous regressors may be bounded or growing, like polynomial trends. The assumption on the spatial matrix $W_n$ is appropriate for the situation when each economic agent is influenced by many others. The asymptotics contains both linear and quadratic forms in standard normal variables. The conditions and the format of the result are chosen in a way compatible with known results for the model without lags by Anderson (1971) and for the spatial model without exogenous regressors due to Mynbaev and Ullah (2006).
Pengembangan Multimedia untuk Meningkatkan KualitasPembelajaran pada Mata Kuliah Media Pembelajaran

Penelitian ini bertujuan: 1) menghasilkan multimedia mata kuliah Media Pembelajaran yang layak digunakan dalam pembelajaran, 2) mengetahui kelayakan multimedia mata kuliah Media Pembelajaran yang telah dihasilkan dari aspek pembelajaran, aspek isi/materi, aspek tampilan dan aspek teknis, dan 3) mengetahui kualitas pembelajaran pada mata kuliah Media Pembelajaran setelah menggunakan multimedia. Penelitian ini merupakan penelitian dan pengembangan (research and development). Setelah melalui tahap produksi dihasilkan produk awal kemudian dilakukan validasi oleh ahli materi dan ahli media. Selanjutnya, produk diujicobakan kepada mahasiswa melalui tiga tahap, yaitu uji coba perorangan, uji coba kelompok kecil, dan uji coba lapangan. Untuk mengetahui efektivitas atau fungsi produk dalam meningkatkan kualitas pembelajaran dalam bentuk peningkatan pencapaian hasil belajar, maka dilakukan evaluasi sumatif. Subjek uji coba produk adalah mahasiswa semester II Jurusan Teknologi Pendidikan Fakultas Ilmu Pendidikan Universitas Pendidikan Ganesha. Subjek uji coba penelitian ini terdiri dari 3 mahasiswa untuk uji coba perorangan, 10 mahasiswa untuk uji coba kelompok kecil, dan 23 mahasiswa untuk uji coba lapangan. Sedangkan pada evaluasi sumatif melibatkan 37 mahasiswa yang dibagi menjadi 2 kelompok. Data yang dikumpulkan dalam penelitian ini adalah data dari ahli materi, data ahli media, dan dari mahasiswa. Instrumen pengumpulan data berupa instrumen evaluasi untuk ahli materi, ahli media, untuk subjek uji coba perorangan, uji coba kelompok kecil, dan uji coba lapangan serta instrumen berupa tes hasil belajar. Analisis data menggunakan analisis deskriptif. Hasil penelitian ini adalah: 1) pengembangan multimedia pembelajaran melalui tahap analisis kebutuhan, desain pembelajaran, produksi, evaluasi formatif yang terdiri dari validasi oleh ahli materi, ahli media dilanjutkan dengan uji coba produk, revisi dan pelaksanaan evaluasi sumatif; 2) kelayakan aspek pembelajaran produk multimedia pembelajaan ini termasuk dalam kategori baik dengan skor 4,05; 3) kelayakan aspek isi/materi produk multimedia pembelajaran ini termasuk dalam kategori sangat baik dengan skor 4,22; 4) kelayakan aspek tampilan produk multimedia pembelajaran ini termasuk dalam kategori baik dengan skor 4,00; 5) kelayakan aspek teknis produk multimedia pembelajaran ini termasuk dalam kategori baik dengan skor 4,05; dan 6) produk multimedia pembelajaran dapat meningkatkan kualitas pembelajaran mata kuliah media pembelajaran, hasil belajar pada kelompok yang menggunakan multimedia lebih baik daripada kelompok yang menggunakan buku ajar dan media presentasi powerpoint, dengan perbedaan antar kelompok sebesar 14,30 poin.
Comparative studies on erythrocyte calcium, potassium, haemoglobin concentration, osmotic resistance and sedimentation rates in grey duiker (Sylvicapra grimmia), sheep and goats experimentally infected with Trypanosoma congolense

A comparative study of the haemoglobin (Hb) concentration, erythrocyte sedimentation rates (ESR), osmotic resistance (EOR) and erythrocyte dynamics of calcium (Ca ++ ) and potassium (K + ) ions was carried out on 10 grey duiker (Sylvicapra grimmia), 15 female West African dwarf sheep and 15 female Yankassa goats during the course of experimental Trypanosoma congolense infection. Grey duiker developed a transient parasitaemia and mild anaemia, while sheep and goats developed progressive parasitaemia, pyrexia, anaemia and loss of condition necessitating their treatment at 49 days post-infection to prevent imminent mortality. Grey duiker maintained consistently unchanged levels of Hb concentration, ESR and erythrocyte Ca++ levels, and transiently reduced EOR and erythrocyte K + levels throughout the course of T. congolense infection. On the other hand, infected sheep and goats developed progressive decreases in Hb concentration, EOR and erythrocyte K+ levels, progressive increases in ESR and erythrocyte Ca ++ levels. These changes were much more severe in infected goats and sheep. This study has shown that the relative trypanotolerance of infected grey duiker are based on their superior ability to control parasitaemia, maintain erythrocytic structural integrity and homeostasis, and hence limit anaemia and other deleterious effects of trypanosome
Fingerprint Image Preprocessing Based on Whole-Hand Image Captured by Digital Camera

There are many biometric features in the hand images captured by digital camera, but few studies are done to extract fingerprint image from it. This paper presents some fingerprint image preprocessing approaches based on a whole-hand image captured by digital camera. The preprocessing methods include key point location, finger image segmentation and fingerprint region extraction. Firstly, the key points including fingertips and valley points, which are called key points, are located from the hand contour image. Secondly, the middle finger is cropped from the hand image based on the information of the key points' positions and the knuckle's texture near the finger root. Finally, the fingerprint is extracted from the middle finger through the first knuckle's texture. Because of the low resolution of the fingerprint images, linear projection methods such as Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used for fingerprint feature extraction. Experimental results on a database of 86 hands (10 impressions per hand) show that these approaches are effective.
Academic Library Leaders’ Challenges, Difficulties and Skills: An Analysis of Common Experiences

Abstract The purpose of this study was to explore the perceptions of academic library leaders of Pakistan about library leadership. Qualitative research design was used with phenomenology approach as the present study aims to investigate what library leaders commonly perceive to be challenges, fundamental difficulties and needed skills to be successful. Data were collected through in-depth interviews from 15 senior academic library leaders. Major challenges found were identity crises followed by communication issues, financial constraints, CPD and administrative issues. The most challenging aspects of being an academic library leader were identified as trying to create awareness, lack of self-development culture and technological issues. The required leadership skills were communication, vision, social interaction, team building, organisational understanding and knowledge sharing. The findings of the study are helpful for current, young and future chief librarians to understand the challenges they may face and to develop the leadership skills needed to cope with these challenges. The study will also be helpful to academic institutions during their recruitment processes; professional associations for training purposes; and library schools for arranging and offering leadership courses.
Subscription summaries for scalability and efficiency in publish/subscribe systems

A key issue when designing and implementing largescale publish/subscribe systems is how to efficiently propagate subscriptions among the brokers of the system. Brokers require this information in order to forward incoming events only to interested users, filtering out unrelated events, which can save significant overheads (particularly network bandwidth and processing time at the brokers). In this paper we contribute the notion of subscription summaries, a mechanism appropriately compacting subscription information. We develop the associated data structures and matching algorithms. The proposed mechanism can handle event/subscription schemata that are rich in terms of their attribute types and powerful in terms of the allowed operations on them. Our major results are that the proposed mechanism (i) is scalable, with the bandwidth required to propagate subscriptions increasing only slightly, even at huge-scales, and (ii) is significantly more efficient, up to orders of magnitude, depending on the scale, with respect to the bandwidth requirements for propagating subscriptions.
A new multiple-step particle filter based feature selection

Tracking moving objects in dynamic scenarios involves considerable difficulty because of occlusions. We report a novel tracker - a new multiple-step particle filter based feature selection for helicopter tracking. The objective of the proposed system is to track helicopter more efficiently and more precisely under bad environments. Color, edge, and position information are used to track stochastic moving objects. Additionally, the proposed system will handle the occlusion problem in an effective manner. Based on the experimental results obtained in MATLAB, the proposed system tracks helicopter more efficiently and correctly, especially when occlusions happen.
A Method for Optimized Deployment of a Network of Surveillance Aerial Drones

This letter considers the deployment problem for a network of aerial drones to maximize the coverage of an area for surveillance and monitoring. A distributed optimization model is proposed and a coverage maximizing algorithm is developed. It is proved that the proposed algorithm converges to a local maximum in a finite number of steps. Simulations with a real dataset demonstrate the effectiveness of the algorithm.
A Multi-clustering Hybrid Recommender System

Recommender systems have become an important research area because they have been a kind of Web intelligence techniques to search through the enormous volume of information available on the Internet. Collaborative filtering and content-based methods are two most commonly used approaches in most recommender systems. Although each of them has both advantages and disadvantages in providing high quality recommendations, a hybrid recommendation mechanism incorporating components from both of the methods would yield satisfactory results in many situations. In this paper, we present an elegant and effective framework for combining content and collaboration. Our approach uses a content-based predictor to enhance existing user data and item data, and then provides personalized suggestions through user-based collaborative filtering and item-based collaborative filtering. The proposed system clusters on content-based approach and collaborative approach then it contribute to the improvement of prediction quality of a hybrid recommender system.
Camostat Attenuates Airway Epithelial Sodium Channel Function in Vivo through the Inhibition of a Channel-Activating Protease

Inhibition of airway epithelial sodium channel (ENaC) function enhances mucociliary clearance (MCC). ENaC is positively regulated by channel-activating proteases (CAPs), and CAP inhibitors are therefore predicted to be beneficial in diseases associated with impaired MCC. The aims of the present study were to 1) identify low-molecular-weight inhibitors of airway CAPs and 2) to establish whether such CAP inhibitors would translate into a negative regulation of ENaC function in vivo, with a consequent enhancement of MCC. To this end, camostat, a trypsin-like protease inhibitor, provided a potent (IC50 ∼50 nM) and prolonged attenuation of ENaC function in human airway epithelial cell models that was reversible upon the addition of excess trypsin. In primary human bronchial epithelial cells, a potency order of placental bikunin > camostat > 4-guanidinobenzoic acid 4-carboxymethyl-phenyl ester > aprotinin >> soybean trypsin inhibitor = α1-antitrypsin, was largely consistent with that observed for inhibition of prostasin, a molecular candidate for the airway CAP. In vivo, topical airway administration of camostat induced a potent and prolonged attenuation of ENaC activity in the guinea pig trachea (ED50 = 3 μg/kg). When administered by aerosol inhalation in conscious sheep, camostat enhanced MCC out to at least 5 h after inhaled dosing. In summary, camostat attenuates ENaC function and enhances MCC, providing an opportunity for this approach toward the negative regulation of ENaC function to be tested therapeutically.
Symbolic formulation and diffusive resolution of some operational problems: theory and applications to optimal control

This paper is focused on the derivation of state-realizations of diff usive type for linear operators solutions of some operatorial equations. We first establish two general theoret- ical framework fitted respectively for regular symbols and for symbols having their singularity located on the real axis. In a second part, we treat two Lyapunov equations issued from the stabilization theory for the heat equation. We also present an example that is beyond the linear framework introduced in this paper, namely a Riccati equation. The practical interest of this work relates to the context of intensive computation in embedded systems, in particular when embedded computers have Cellular Neural Networks-like architectures.
Research on semantic information resource catalog

Finding and locating information resource can be solved by information resource catalog, while traditional catalogs are on the basis of meta data technology, by which queries have bad quality. Information found can not be shared effectively because of understanding obstacle to it. A new catalog technology is proposed, with which semantic data are used to describe characters of shared government information resource. Catalog and semantics of information resource are all recorded normatively. People can not only find and locate information resource but also understand them.
Using association statistics to rank risk of Android application

With the development of Android system and intelligent mobile technology, Android applications have been widely used in recent years. However, the trust on these applications may be used by attackers who design malware to achieve illegal income. Therefore, to evaluate the security risk of applications is necessary. In this paper, an evaluation approach based on association statistics of application permissions is represented. By analyzing the frequency of permission combinations, the malicious features of Android applications is estimated. Meanwhile, the redundant frequency is wiped off by computing the frequency discount, and then the risk seeds are correspondingly achieved. The final risk score is calculated by the seeds from malicious and benign aspects. To verify the effectiveness of our approach, we took 1260 malware as "malicious" datasets and 10,247 valid apps collected from Android Market as "benign" datasets, and sufficient experiments show that our approach has better results compared with other traditional methods.
Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes

Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive function in subjects with type 2 diabetes (T2D). Method: In this study, EEG was recorded in 28 patients with T2D (16 aMCI patients and 12 controls) during a no-task eyes-closed resting state. Pair-wise synchronization of rsEEG signals were assessed in six frequency bands (delta, theta, lower alpha, upper alpha, beta, and gamma) using phase lag index (PLI) and grouped into long distance (intra- and inter-hemispheric) and short distance interactions. PLI-weighted connectivity networks were also constructed, and characterized by mean clustering coefficient and path length. The correlation of these features and Montreal Cognitive Assessment (MoCA) scores was assessed. Results: Main findings of this study were as follows: (1) In comparison with controls, patients with aMCI had a significant decrease of global mean PLI in lower alpha, upper alpha, and beta bands. Lower functional connection at short and long intra-hemispheric distance mainly appeared on the left hemisphere. (2) In the lower alpha band, clustering coefficient was significantly lower in aMCI group, and the path length significantly increased. (3) Cognitive status measured by MoCA had a significant positive correlation with cluster coefficient and negative correlation with path length in lower alpha band. Conclusions: The brain network of aMCI patients displayed a disconnection syndrome and a loss of small-world architecture. The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become. Hence, the complex network-derived biomarkers based on EEG could be employed to track cognitive function of diabetic patients and provide a new diagnosis tool for aMCI.
A SEQUENCE VARIATION SCAN OF THE COAGULATION FACTOR ( F ) VIII STRUCTURAL GENE AND ASSOCIATIONS WITH PLASMA FVIII ACTIVITY ( FVIII : C ) LEVELS

Plasma FVIII:C level is a highly heritable quantitative-trait that is strongly correlated with thrombosis risk. Polymorphisms within only one gene, the ABO blood-group locus, have been unequivocally demonstrated to contribute to the broad population variability observed for this trait. Because less than 2.5% of the structural FVIII gene (F8) has been examined previously, we resequenced all known functional regions in 222 potentially distinct alleles from 137 unrelated non-hemophilic individuals representing seven racial groups. Eighteen of the 47 variants identified, including 17 single-nucleotide polymorphisms (SNPs), were previously unknown. As the degree of linkage disequilibrium across F8 was weak overall, we used measured-genotype association analysis to evaluate the influence of each polymorphism on the FVIII:C levels in 398 subjects from 21 pedigrees known as the Genetic Analysis of Idiopathic Thrombophilia project (GAIT). Our results suggested that C92714G, a nonsynonymous-SNP encoding the B-domain substitution D1241E, was significantly associated with FVIII:C. After accounting for important covariates, including age and ABO-genotype, the association persisted with each C-allele additively increasing the FVIII:C level by 14.3 IU dL (p = 0.016). Nevertheless, because the alleles of G56010A, a SNP within the 3’-splice-junction of intron-7, are strongly associated with C92714G in GAIT, additional studies are required to determine whether D1241E is itself a functional variant. For personal use only. by on January 30, 2008. www.bloodjournal. org From