Miracle-dz/UniFAR-FTUs huggingface dataset:
Routing Loops in DAG-Based Low Power and Lossy Networks

Directed Acyclic Graphs (DAGs), rooted at popular/default destinations, have emerged as a preferred mechanism to provide IPv6 routing functionality in large scale low power and lossy networks, that include wireless sensor networks and those based on power line communication. A DAG maintains its acyclic nature by requiring that each DAG node must have a higher ’rank’ than any of its DAG parents. While a node may decrease its DAG rank safely, increasing its DAG rank to add a new parent may result in a routing loop if the new parent is also a descendant in the DAG. In this paper, we first study via simulations the time required by the network to converge to a stable, loop-free state following a rank increase operation and the number of routing messages generated (the network ’churn’) during this time. Then, we describe the precautionary measures that can be used to avoid routing loops and evaluate via simulations how these measures affect the time and churn involved in reaching a stable state following a rank increase operation.
Nitrogen storage and remobilization in Brassica napus L. during the growth cycle: effects of methyl jasmonate on nitrate uptake, senescence, growth, and VSP accumulation.

The role of methyl jasmonate (MeJa) in promoting senescence has been described previously in many species, but it has been questioned in monocarpic species whether induced senescence is a result of a potential death hormone like MeJa, or a consequence of an increased metabolic drain resulting from the growth of reproductive tissue. In oilseed rape (Brassica napus L.), a polypeptide of 23 kDa has been recently identified as a putative vegetative storage protein (VSP). This polypeptide could be used as a storage buffer between N losses from senescing leaves putatively promoted by methyl jasmonate that might be produced by flowers, and grain filling which occurs later on, while N uptake is strongly reduced. In order to describe causal relationships during Brassica napus L. plant responses to MeJa treatment, a kinetic experiment was performed to determine the order and the amplitude with which general processes such as growth, photosynthesis, chlorophyll content, N uptake, and N storage under the form of the 23 kDa VSP are affected. One of the most immediate consequences of MeJa treatment was the strong reduction of nitrate uptake within 6 h, relative to control plants. However, this was not a specific effect as K(+) uptake was similarly affected. Photosynthesis was reduced later (after 24 h), while chlorophyll content as well as leaf growth also decreased in a similar way. Moreover, this was concomitant with a remobilization of endogenous unlabelled N from senescing leaves to roots. Accumulation of the 23 kDa VSP was induced in the taproot after 24 h of MeJa treatment and was increased 10-fold within 8 d. On the other hand, the reversible effect of a MeJa pretreatment was tested in the long term (i.e. along the growth cycle) using plants previously grown in field conditions induced for flowering. Results show that a MeJa pulse induced a reversible effect on N uptake inhibition. In parallel, protein immunologically related to the 23 kDa VSP was detected in stems with a similar molecular weight (23 kDa), and in flowers and leaves with a molecular weight of 24 kDa. This accumulation was concomitant with the remobilization of both subunits of Rubisco. During stem and pod development, this protein induced by MeJa is fully hydrolysed. The external and intermittent supply of MeJa mimic some of the plant physiological processes previously reported under natural conditions. This suggests that in oilseed rape, methyl jasmonate could be considered as a possible monocarpic senescence factor while accumulation/mobilization of the 23 kDa VSP in taproot could be a marker for the cessation of N uptake and the initiation of a massive leaf senescence.
Selective anchoring in the specific plasma membrane domain: a role in epithelial cell polarity

We have studied the role of restrictions to lateral mobility in the segregation of proteins to apical and basolateral domains of MDCK epithelial cells. Radioimmunoassay and semiquantitative video analysis of immunofluorescence on frozen sections showed that one apical and three basolateral glycoproteins, defined by monoclonal antibodies and binding of beta-2-microglobulin, were incompletely extracted with 0.5% Triton X-100 in a buffer that preserves the cortical cytoskeleton (Fey, E. G., K. M. Wan, and S. Penman. 1984. J. Cell Biol. 98:1973-1984; Nelson, W. T. and P. J. Veshnock. 1986. J. Cell Biol. 103:1751-1766). The marker proteins were preferentially extracted from the "incorrect" domain (i.e., the apical domain for a basolateral marker), indicating that the cytoskeletal anchoring was most effective on the "correct" domain. The two basolateral markers were unpolarized and almost completely extractable in cells prevented from establishing cell-cell contacts by incubation in low Ca++ medium, while an apical marker was only extracted from the basal surface under the same conditions. Procedures were developed to apply fluorescent probes to either the apical or the basolateral surface of live cells grown on native collagen gels. Fluorescence recovery after photobleaching of predominantly basolateral antigens showed a large percent of cells (28- 52%) with no recoverable fluorescence on the basal domain but normal fluorescence recovery on the apical surface of most cells (92-100%). Diffusion coefficients in cells with normal fluorescence recovery were in the order of 1.1 x 10(-9) cm2/s in the apical domain and 0.6-0.9 x 10(-9) cm2/s in the basal surface, but the difference was not significant. The data from both techniques indicate (a) the existence of mobile and immobile protein fractions in both plasma membrane domains, and (b) that linkage to a domain specific submembrane cytoskeleton plays an important role in the maintenance of epithelial cell surface polarity.
Algebraic Learning and Neural Network Models for Transitive and Non-transitive Responding

Transitive inference is a kind of deductive reasoning. Given the premises “Anna is taller than Paul” and “Paul is taller than Mary”, adults and older children easily conclude that “Anna is taller than Mary”. However, a related transitive responding ability has also been demonstrated in younger children and some animals with non-verbal tasks. For this, the premise statements are converted into an operant discrimination task. The subjects are offered the stimulus pairs A+ B-, B+ C-, C+ D-, D+ Ewhere + signifies that the choice of the relevant stimulus is rewarded and- indicates that its choice is penalised. When the subjects responded correctly to these premises, unreinforced tests with the conclusion stimulus pair BD were conducted. If they preferentially chose B, they were said to respond transitively. Algebraic conditioning models have been shown to be capable of reproducing such transitive behaviour. We describe a particularly simple algebraic model based on instrumental conditioning and then develop a .
VIA SHARING EXPERIENCE

The goal is to contribute to the understanding, description, comparison and improvement of the different methods of research that have been employed in the information technology field by supporting the exchange of information, collaboration, and cooperation between researchers. We stress the importance of sharing knowledge through storytelling. Well-designed, well-told stories can help others learn from past situations to respond more effectively in future situation. A web-based forum is presented where PhD students and researchers are invited to collaborate by providing their stories, reading and commenting existing stories. This infrastructure is a blank paper where researchers and PhD students write the contents posing questions and finding answers on the relationship between research process and research results.
The Effectiveness of the Summer Immersion Program for Developing Time Management and Metacognitive Thinking Life Skills among Female Secondary School Students in Saudi Arabia

This research aimed at examining the effectiveness of the Saudi Aramco Research Science Initiative (SARSI) Summer Immersion training program for developing time management and meta cognitive thinking life skills among female gifted secondary school students. The research sample comprised 31 female gifted students enrolled in various Saudi secondary schools. Their ages ranged from 15 to 17 years old with an average age of 16.23. The Abdul Salam scale was used for the measuring time-management performance and metacognitive thinking skills in the pre- and post-assessment of the SARSI program. Statistical analysis revealed significant differences between the students’ pre- and post-assessments on: a) time management skills; b) the overall meta cognitive thinking life skills and c) two subcategories of metacognitive skills: planning and self-monitoring. However, no significant differences were identified in the pre- and post-assessment for self-assessment.
A Misbehavior-Tolerant Multipath Routing Protocol for Wireless Ad hoc Networks

Secure routing is a major key to service maintenance in ad hoc networks. Ad hoc nature exposes the network to several types of node misbehavior or attacks. As a result of the resource limitations in such networks nodes may have a tendency to behave selfishly. Selfish behavior can have drastic impacts on network performance. We have proposed a Misbehavior-Tolerant Multipath Routing protocol (MTMR) which detects and punishes all types of misbehavior such as selfish behavior, wormhole, sinkhole and grey-hole attacks. The protocol utilizes a proactive approach to enforce cooperation. In addition, it uses a novel data redirection method to mitigate the impact of node misbehavior on network performance. The proposed scheme promises establishing a safe route if network graph remains connected after eliminating the misbehaving nodes. We have implemented the proposed protocol in a simulation environment and have evaluated its performance in typical network configurations to demonstrate its resilience to node misbehavior.
On the Relationship between Perfectionism and College Students’ Academic Procrastination: The Moderating Role of Causality Orientations

Based on Self-determination Theory (SDT), this study attempted to explore the relationship between perfectionism and college students’ academic procrastination as well as moderating role of causality orientations. A total of 660 undergraduates in three majors from two universities in Jinan, Shandong province participated in the questionnaire survey. The results indicated that: (1) positive perfectionism was significantly negatively correlated with academic procrastination while negative perfectionism was significantly positively correlated with procrastination; (2) controlled orientation and impersonal orientation were all significantly positively correlated with academic procrastination; (3) controlled orientation moderated the relationship between negative perfectionism and college students’ academic procrastination: negative perfectionism can’t predict academic procrastination when controlled orientation was low; negative perfectionism can’t predict academic procrastination when controlled orientation was high; and (4) impersonal orientation moderated the relationship between negative perfectionism and college students’ academic procrastination: negative perfectionism can’t predict academic procrastination when impersonal orientation was low; negative perfectionism significantly positively predicted academic procrastination when impersonal orientation was high. Keywords—Perfectionism; Causality Orientation; Academic Procrastination
The Influences on Practice in Social Care: An Australian Study

ABSTRACT Much of the discourse regarding social care practice focuses on the differences between the various professions, practice fields, geographical, and organizational contexts involved in the provision of social care. This study surveyed Australian social care practitioners’ (N = 438) perceptions of influence on their practice and what similarities and differences existed in these perceptions. Eighteen influential factors were identified with minimal differences across the participants’ profession, practice field, organizational sector, or geographical context. These findings suggest that a common ground of experience exists that can be used as a basis for critical discussions and interdisciplinary practice and, thereby, provide a foundation for more consistent and integrated service delivery and outcomes.
Distributed Wideband Spectrum Sensing

We consider the problem of reconstructing wideband frequency spectra from distributed, compressive measurements. The measurements are made by a network of nodes, each independently mixing the ambient spectra with low frequency, random signals. The reconstruction takes place via local transmissions between nodes, each performing simple statistical operations such as ridge regression and shrinkage.
PENERAPAN THEORY OF PLANNED BEHAVIOR DALAM PEMBELIAN MAKANAN HALAL PADA MASYARAKAT DI KOTA BANDA ACEH

This study aims to examine intention to purchase halal food among community in the city of Banda Aceh by using Theory of Planned Behavior. This research uses 4 variable: intention to purchase halal food, attitude, subjective norm, and perceived behavior control. This research is a survey research using questionnaire as its instrument. The population used in this study is the community in the city of Banda Aceh. The sample in this study is 160 people who are Muslim and Non-Muslim communities in Banda Aceh City. Probability Sampling is used as a sampling technique with Cluster method. Based on the results of regression analysis showed that attitude, subjective norm, and perceived behavior control variables have positive and significant effect on intention to purchase halal food Keywords: Theory of Planned Behavior, Muslim User, Halal Food
Examining relationships among consumer participative behavior, employee role ambiguity, and employee citizenship behavior: the moderating role of employee self-efficacy

ABSTRACT Research question: This study examines (a) the effect of consumer participative behavior (CPB) levels (low vs. high) on employee role ambiguity, (b) the influence of employee role ambiguity on employee citizenship behavior (ECB), and (c) the moderating effect of employee self-efficacy in the relationship between CPB and role ambiguity. Research methods: Fitness centers were chosen as a research context in which consumer–employee dyadic data sets were drawn from one-on-one personal weight training and golf lessons, and small group exercises (i.e. yoga and swimming). Results and findings: The results indicated that a high level of CPB had a greater effect on employee role ambiguity than a low level of CPB. Employee role ambiguity negatively influenced ECB. Finally, employee self-efficacy played a significant moderating role that altered the positive association between CPB and role ambiguity to a negative one. Implications: The present study advances the theoretical, methodological, and practical understanding of consumer–employee interaction in the context of high-contact sport service setting. The current study extends previous research by bringing the burgeoning attention given to CPB into participative sport, and empirically examining the effect of CPB on frontline employees. We utilized a dyadic method, which allowed us to better understand the relationships between employees and consumers. Finally, this research provides sport service managers with strategic CPB management regarding how to harness CPB and avoid its drawbacks to create mutually beneficial service outcomes.
NGC 602 Environment, Kinematics and Origins

The young star cluster NGC 602 and its associated HII region, N90, formed in a relatively isolated and diffuse environment in the Wing of the Small Magellanic Cloud. Its isolation from other regions of massive star formation and the relatively simple surrounding HI shell structure allows us to constrain the processes that may have led to its formation and to study conditions leading to massive star formation. We use images from the Hubble Space Telescope and high resolution echelle spectrographic data from the Anglo-Australian Telescope, along with 21 cm neutral hydrogen (HI) spectrum survey data and the shell catalog derived from it to establish a likely evolutionary scenario leading to the formation of NGC 602. We identify a distinct HI cloud component that is likely the progenitor cloud of the cluster and HII region, which probably formed in blister fashion from the cloud’s periphery. We also find that the past interaction of HI shells can explain the current location and radial velocity of the nebula. The surrounding interstellar medium is diffuse and dust-poor as demonstrated by a low visual optical depth throughout the nebula and an average HI density of the progenitor cloud estimated at 1 cm-3. These conditions suggest that the NGC 602 star formation event was produced by compression and turbulence associated with HI shell interactions. It therefore represents a single star-forming event in a low gas density region.
A Comparison of Three Different Methods for Classification of Breast Cancer Data

The classification of breast cancer patients is of great importance in cancer diagnosis. During the last few years, many algorithms have been proposed for this task. In this paper, we review different supervised machine learning techniques for classification of a novel dataset and perform a methodological comparison of these. We used the C4.5 tree classifier, a multilayer perceptron and a naive Bayes classifier over a large set of tumour markers. We found good performance of the multilayer perceptron even when we reduced the number of features to be classified. We found naive Bayes achieved a competitive performance even though the assumption of normality of the data is strongly violated.
Efficient Computation of Co-occurrence Statistics for Natural Language Processing Tasks

Co-occurrence matrices act as the input to many unsupervised learning algorithms, including those that learn word embeddings, and modern spectral topic models. However, the computation of these inputs often takes longer than the inference. While much thought has been given to implementing fast learning algorithms, there has been little consideration of preprocessing efficiency. Here, we compare state-of-theart methods for co-occurrence matrix computation in both the context-level and documentlevel cases. We find that both of these tasks are well suited to GPU parallelization. In the context-level case, our implementation outperforms an existing optimized single-core version by 4 times, and scales better. In the documentlevel case, we achieve significantly more than 350 times speedup over a naive, single-core baseline.
Direct chosen ciphertext security from identity-based techniques

We describe a new encryption technique that is secure in the standard model against chosen ciphertext attacks. We base our method on two very efficient Identity-Based Encryption (IBE) schemes without random oracles due to Boneh and Boyen, and Waters.Unlike previous CCA2-secure cryptosystems that use IBE as a black box, our approach is very simple and compact. It makes direct use of the underlying IBE structure, and requires no cryptographic primitive other than the IBE scheme itself. This conveys several advantages. We achieve shorter ciphertext size than the best known instantiations of the other methods, and our technique is as efficient as the Boneh and Katz method (and more so than that of Canetti, Halevi, and Katz). Further, our method operates nicely on hierarchical IBE, and since it allows the validity of ciphertexts to be checked publicly, it can be used to construct systems with non-interactive threshold decryption.In this paper we describe two main constructions: a full encryption system based on the Waters adaptive-ID secure IBE, and a KEM based on the Boneh-Boyen selective-ID secure IBE. Both systems are shown CCA2-secure in the standard model, the latter with a tight reduction. We discuss several uses and extensions of our approach, and draw comparisons with other schemes that are provably secure in the standard model.
Phase synchrony analysis for SSVEP-based BCIs

Brain-computer interfaces (BCI) based on Steady State Visual Evoked Potential (SSVEP) can provide higher throughput than other BCI modalities. For the sake of safety and comfort, the frequencies of the stimulus should be higher than 30 Hz. However, only a limited number of these frequencies can elicit SSVEPs that are strong enough for BCI purposes. In order to increase the number of available stimuli, the SSVEP phase can be taken into account. In this study, we used phase synchrony analysis to extract the phase difference between SSVEP and stimuli as a feature to identify a subject's intention. This analysis can mitigate the adverse effect brought by the phase deviation that may occur in the stimuli. Furthermore, the classification accuracy when using a single lead signal (Oz-Cz) is compared to a spatial filtered signal. The result shows that the phase synchrony analysis can effectively extract the phase difference and that spatial filtering can significantly increase the classification accuracy.
Measuring Social Interactions

This paper presents an overview of the economics that lies behind social interaction models and briefly discusses the empirical approaches to social interactions. We present a simple model with local interactions, similar to Glaeser, Sacerdote and Scheinkman (1996) but using aa continuous action space and starting with optimizing behavior. We then extend the model to include both global and local interactions. We suggest and use a methodology for using variation of intra-city aggregates to identify the relative sizes of local and global interactions. We also present a model with endogenous location choice and use the predictions of that model to identify the sources of cross-city variance that are due to sorting and interaction. Finally, we present a brief discussion of using time-series to estimate the social interactions in broad aggregates.
Landmark-Dependent Hierarchical Beta Process for Robust Sparse Factor Analysis

A computationally efficient landmark-dependent hierarchical beta process is developed as a prior for data with associated covariates. The landmarks define local regions in the covariate space where feature usages are likely to be similar. The landmark locations are learned, to which the data are linked through normalized kernels. The proposed model is well suited for local latent feature discovery, and adding a robustness term, it successfully separates out non-local sparse spiky components, as demonstrated in image denoising and document analysis applications.