Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrinsic, identified, and controlled types of motivation for school subjects in young elementary school children.

BACKGROUND There are two approaches to the differential examination of school motivation. The first is to examine motivation towards specific school subjects (between school subject differentiation). The second is to examine school motivation as a multidimensional concept that varies in terms of not only intensity but also quality (within school subject differentiation). These two differential approaches have led to important discoveries and provided a better understanding of student motivational dynamics. However, little research has combined these two approaches. AIMS This study examines young elementary students' motivations across school subjects (writing, reading, and maths) from the stance of self-determination theory. First, we tested whether children self-report different levels of intrinsic, identified, and controlled motivation towards specific school subjects. Second, we verified whether children self-report differentiated types of motivation across school subjects. SAMPLE Participants were 425 French-Canadian children (225 girls, 200 boys) from three elementary schools. Children were in Grades 1 (N=121), 2 (N=126), and 3 (N=178). RESULTS Results show that, for a given school subject, young elementary students self-report different levels of intrinsic, identified, and controlled motivation. Results also indicate that children self-report different levels of motivation types across school subjects. Our findings also show that most differentiation effects increase across grades. Some gender effects were also observed. CONCLUSION These results highlight the importance of distinguishing among types of school motivation towards specific school subjects in the early elementary years.
Sense of Challenge, Threat, Self-Efficacy, and Motivation of Students Learning in Virtual and Blended Courses

ABSTRACT Feelings of threat, challenge, motivation, self-efficacy, and transactional distance reflect students’ struggles with the learning process. This study examined the relationship between students’ subjective feelings about the learning process in virtual and blended courses (VC and BC). This is a mixed-method study. The sample included 484 students from two academic institutions in Israel. The study found a connection between students’ subjective feelings about the learning process in VC and BC and feelings of threat/challenge, motivation, and self-efficacy. We found differences between students in different years of study and between those studying in various fields of study.
Eliminate Evading Analysis Tricks in Malware using Dynamic Slicing

In order to be a long time alive, modern malware often make anti-emulation check after launched for evading dynamic analysis. Malware authors gain fingerprint information of target environment through several API to detect whether their creations are running in monitored state or not. If an emulated analysis environment is detected, the malware will change its running to avoid malicious behavior exposing. The existing approaches are based on trace matching with a intuition that, given the same inputs, the execution of a program should be the same in simulated analysis environment and on a real hardware reference system. However those approaches are too fine-grained to be inefficient. In this paper we propose an approach to deal with anti-emulation using instruction traces and dynamic slicing. With a difference from trace matching solutions presented in existing references, our approach is performed on one instruction trace derived from our dynamic analysis platform. We evaluate our approach with 189 malware samples collected in the wild. The experience shows that our proposed approach can spot efAPI used for anti-emulation check in an efficient way.
3-Dimensional root cause diagnosis via co-analysis

With the growth of system size and complexity, reliability has become a major concern for large-scale systems. Upon the occurrence of failure, system administrators typically trace the events in Reliability, Availability, and Serviceability (RAS) logs for root cause diagnosis. However, RAS log only contains limited diagnosis information. Moreover, the manual processing is time-consuming, error-prone, and not scalable. To address the problem, in this paper we present an automated root cause diagnosis mechanism for large-scale HPC systems. Our mechanism examines multiple logs to provide a 3-D fine-grained root cause analysis. Here, 3-D means that our analysis will pinpoint the failure layer, the time, and the location of the event that causes the problem. We evaluate our mechanism by means of real logs collected from a production IBM Blue Gene/P system at Oak Ridge National Laboratory. It successfully identifies failure layer information for the failures during 23-month period. Furthermore, it effectively identifies the triggering events with time and location information, even when the triggering events occur hundreds of hours before the resulting failures.
Optimized Instrumental Arrangements for Determination of Cadmium and Lead in Human Whole Blood

A rapid graphite-furnace atomic absorption spectrophotometric procedure is described for determining cadmium and lead in heparinized human whole blood. A known auquot of the blood sample is diluted fivefold with an aqueous solution composed of 5 g each of diammonium hydrogen phosphate and Triton X-100 per liter, the solution is vigorously agitated, and a 1O-12Laliquot is injected into a pyrocoated graphite tube under optimized instrumental conditions. Values for Cd and Pb in the sample are obtained by direct comparison to linear working curves prepared from aqueous standards of the metals in the diammonium hydrogen phosphate-Triton medium; there is no need to use the method of standard addition or matrix-matched calibration curves. Also, the method is free of matrix effects. At least 30 samples can be analyzed per hour. The rapidity, simplicity, and sensitivity of the method make it attractive as a screening technique for routine environmental surveillance involving large throughput of samples.
Securing Vehicular Ad-hoc Networks Against Malicious Drivers: A Probabilistic Approach

Future development of Intelligent Transportation Systems (ITS) depends on Vehicular Ad-hoc Networks (VANETs) in which communications will help to improve traffic safety and efficiency through exchanging information among vehicles. As each vehicle cannot be a source of all messages in VANET, most communications depend on the information received from other vehicles. To protect VANET from malicious action, each vehicle must be able to evaluate, decide and react locally on information received from other vehicles. Message verification is more challenging in VANETs since the security and privacy of the participating vehicles, in general, and of the drivers and passengers specifically is of major concern. Each vehicle needs to verify the accuracy of the message and needs to verify that the received message is from a legitimate vehicle. In this paper, we propose a new algorithm to secure vehicular communication with the help of trust measured for the given period using a probabilistic approach. The proposed algorithm secures VANETs against the untrustworthy drivers. The proposed algorithm is illustrated through numerical results obtained from simulations.
Tumor invasion after treatment of glioblastoma with bevacizumab: radiographic and pathologic correlation in humans and mice

Patients with recurrent malignant glioma treated with bevacizumab, a monoclonal antibody to vascular endothelial growth factor (VEGF), alone or in combination with irinotecan have had impressive reductions in MRI contrast enhancement and vasogenic edema. Responses to this regimen, as defined by a decrease in contrast enhancement, have led to significant improvements in progression-free survival rates but not in overall survival duration. Some patients for whom this treatment regimen fails have an uncharacteristic pattern of tumor progression, which can be observed radiographically as an increase in hyperintensity on T2-weighted or fluid-attenuated inverse recovery (FLAIR) MRI. To date, there have been no reports of paired correlations between radiographic results and histopathologic findings describing the features of this aggressive tumor phenotype. In this study, we correlate such findings for 3 illustrative cases of gliomas that demonstrated an apparent phenotypic shift to a predominantly infiltrative pattern of tumor progression after treatment with bevacizumab. Pathologic examination of abnormal FLAIR areas on MRI revealed infiltrative tumor with areas of thin-walled blood vessels, suggesting vascular “normalization,” which was uncharacteristically adjacent to regions of necrosis. High levels of insulin-like growth factor binding protein-2 and matrix metalloprotease-2 expression were seen within the infiltrating tumor. In an attempt to better understand this infiltrative phenotype associated with anti-VEGF therapy, we forced a highly angiogenic, noninvasive orthotopic U87 xenograft tumor to become infiltrative by treating the mice with bevacizumab. This model mimicked many of the histopathologic findings from the human cases and will augment the discovery of alternative or additive therapies to prevent this type of tumor recurrence in clinical practice.
Social Network Analysis on Communications for Knowledge Collaboration in OSS Communities

Knowledge collaboration is the key for success of open source software (OSS) communities, because not all members have knowledge and skills necessary for software development. Generally, members in OSS communities communicate for knowledge collaboration using communication tools (e.g. mailing lists, discussion forums, bug tracking systems, and so on) so that geographically distributed members collaborate and coordinate their work. In this paper, we apply social network analysis to the data accumulated in communication tools. We analyzed relationships between the density of social networks and OSS releases by time series analysis of 4 OSS communities in SourceForge.net in order to investigate the quality of communications for knowledge collaboration. The analysis results showed that communications among community members with a variety of roles are active before/after OSS released in communities where knowledge collaboration is going well.
4-D evolution of anticlines and implications for hydrocarbon exploration within the Zagros Fold-Thrust Belt, Kurdistan Region, Iraq

The Zagros Fold-Thrust Belt, extending from southern Iran, through northern Iraq and into Turkey, is characterized by elongate NW-trending anticlines that house large hydrocarbon accumulations. In recent years, the Kurdistan region of northern Iraq has become an area of interest for both structural studies and petroleum exploration-related investigation. Key questions to be answered concern the nature of the anticlines and whether the geometry of any associated thrusts can be predicted from surface geomorphology, as well the 4-D evolution of the area and along-strike continuity of the anticlines. To address these questions, this study combines field data, remote-sensing data concerning the structure and geomorphology of the anticlines, and structural modeling in order to produce robust interpretations of the geometries of the reverse fault structures that core the majority of these anticlines. Results indicate that this methodology can be used to constrain potential thrust configurations at depth and the probable style of fold amplification and lateral propagation. In addition, this study shows that the growth of the anticlines can be considered in 4-D, with consideration given to the interaction of the Zagros-age deformation with the pre-existing basement fabric. We demonstrate that combining both structural and geomorphological methodologies can lead to a better understanding of the geometry and evolution of the trap-forming structures in the Kurdistan region of Iraq and thus is expected to be of interest to the petroleum industry.
Flexible and modular support for multicast rate adaptation in WLANs

The flexibility and virtualization capabilities provided by wireless cards have received significant attention as a means to reduce development costs. In this paper we present a modular architecture that exploits the features provided by emerging PHY and MAC implementations to rapidly develop new rate adaptation algorithms for multicast transmission in wireless LANs. We validate our solution by developing three rate adaptation algorithms that use an innovative sensing mechanism to evaluate the frame reception correlation of the members of the multicast group. The experimental results obtained on a real-life testbed show that our solutions permit to increase the performance of multicast transmissions up to 3x and 5x in terms of throughput and delay with respect to the standard fixed rate approach, reducing losses at the same time.
AIS Electronic Library (AISeL)

“Levels of analysis” has been a controversial topic in group research and has often been ignored by IS researchers leading to “cross-level fallacies” and “aggregation biases. ” While the predominant practice in IS research is to assess group behavior by computing the “arithmetic mean of individual members’ behaviors,” recent studies have argued that groups should be treated separate from the individuals who constitute them, and group behavior should be measured using “global” constructs. This study examines the applicability of these two divergent practices in the context of technology adoption by groups, a phenomenon of growing importance in organizations that has not been investigated in-depth in IS research. Preliminary results from an experimental study provide some resolution to the debate surrounding the appropriateness of these two approaches, and highlight the contexts in which aggregation of individual-level measures may not be suitable for understanding group behavior.
Quality-biased Ranking of Short Texts in Microblogging Services

The abundance of user-generated content comes at a price: the quality of content may range from very high to very low. We propose a regression approach that incorporates various features to recommend short-text documents from Twitter, with a bias toward quality perspective. The approach is built on top of a linear regression model which includes a regularization factor inspired from the content conformity hypothesis - documents similar in content may have similar quality. We test the system on the Edinburgh Twitter corpus. Experimental results show that the regularization factor inspired from the hypothesis can improve the ranking performance and that using unlabeled data can make ranking performance better. Comparative results show that our method outperforms several baseline systems. We also make systematic feature analysis and find that content quality features are dominant in short-text ranking.
Global optimization of explicit strong-stability-preserving Runge-Kutta methods

Strong-stability-preserving Runge-Kutta (SSPRK) methods are a type of time discretization method that are widely used, especially for the time evolution of hyperbolic partial differential equations (PDEs). Under a suitable stepsize restriction, these methods share a desirable nonlinear stability property with the underlying PDE; e.g., positivity or stability with respect to total variation. This is of particular interest when the solution exhibits shock-like or other nonsmooth behaviour. A variety of optimality results have been proven for simple SSPRK methods. However, the scope of these results has been limited to low-order methods due to the detailed nature of the proofs. In this article, global optimization software, BARON, is applied to an appropriate mathematical formulation to obtain optimality results for general explicit SSPRK methods up to fifth-order and explicit low-storage SSPRK methods up to fourth-order. Throughout, our studies allow for the possibility of negative coefficients which correspond to downwind-biased spatial discretizations. Guarantees of optimality are obtained for a variety of third- and fourth-order schemes. Where optimality is impractical to guarantee (specifically, for fifth-order methods and certain low-storage methods), extensive numerical optimizations are carried out to derive numerically optimal schemes. As a part of these studies, several new schemes arise which have theoretically improved time-stepping restrictions over schemes appearing in the recent literature.
CARTESIAN CLOSED TOPOLOGICAL HULL OF THE CONSTRUCT OF CLOSURE SPACES

A cartesian closed topological hull of the construct Cls of closure spaces and continuous maps is constructed. The construction is performed in two steps. First a cartesian closed extension L of Cls is obtained. We apply a method worked out by J. Adamek and J. Reiterman (3) for constructing extensions of constructs that in some sense "resemble" the construct of uniform spaces. Secondly, within this extension L the cartesian closed topological hull L ∗ of Cls is characterized as a full subconstruct. In order to find the internal characterization of the objects of L ∗ we produce a concrete functor to the category of power closed collections based on Cls as introduced by J. Adamek, J. Reiterman and G.E. Strecker in (4).
ASIC DSP compiler for optimized synthesis

This paper presents a high level DSP architecture compiler for cycle-constrained filters and datapath applications. The tool offers an easy way to get, from an equation representation of a filter, a synthetisable VHLD description of an application specific DSP architecture. Inputs of the DSP compiler are an equation file to define the filter structure and a resource definition file to specify the available resource units. The equation syntax is very comfortable. Resource mapping, scheduling, binding and furthermore the quantification of each operation is usually performed automatically, but can be controlled by the user. The result is a very fast filter synthesis time combined with highest flexibility for the users.
Improved Chemical Control for the Mexican Rice Borer (Lepidoptera: Crambidae) in Sugarcane: Larval Exposure, a Novel Scouting Method, and Efficacy of a Single Aerial Insecticide Application

ABSTRACT A three-treatment aerial application insecticide experiment was conducted in five commercial sugarcane, Saccharum spp. , fields in south Texas to evaluate the use of pheromone traps for improving chemical control of the Mexican rice borer, Eoreuma loftini (Dyar), in 2009 and 2010. A threshold of 20 moths/trap/wk was used to initiate monitoring for larval infestations. The percentage of stalks with larvae on plant surfaces was directly related to the number of moths trapped. Reductions in borer injury and adult emergence were detected when a threshold of >5% of stalks with larvae present on plant surfaces was used to trigger insecticide applications. Novaluron provided superior control compared with &bgr;-cyfluthrin; novaluron treated plots were associated with a 14% increase in sugar production. A greenhouse experiment investigating establishment and behavior of E. loftini larvae on two phenological stages of stalkborer resistant, HoCP 85–845, and susceptible, HoCP 00–950, sugarcane cultivais determined that more than half of larvae on HoCP 00–950 and >25% on HoCP 85–845 tunneled inside leaf mid-ribs within 1 d of eclosion, protected therein from biological and chemical control tactics. Exposure time of larvae averaged <1 wk for all treatments and was shortest on immature HoCP 00–950 and longest on mature HoCP 85–845. This study shows a short window of vulnerability of E. loftini larvae to insecticide applications, and demonstrates the potential utility of pheromone traps for improving insecticide intervention timing such that a single properly timed application may be all that is required.
Enabling delay-tolerant communications for partially connected vehicular ad hoc networks

The packet delivery ratio and throughput in Vehicular Ad Hoc Networks (VANETs) depend on the network connectivity and degrade as the connectivity decreases. A delay-tolerant approach increases the packet delivery ratio in partially connected networks. In the previous studies, the packet lifetime and the vehicle's packet carry time are determined to maximise the packet delivery ratio in partially connected VANETs. However, IPv6 uses the hop count in the Hop Limit field instead of using seconds in the TTL field, as in IPv4. Similarly, although IPv4 packets are designed to carry the packet lifetime in seconds in the TTL field, this field is used for the hop count in practice. In this case, there is no mechanism to determine how long vehicles will carry packets in VANETs when delivering packets in a delay-tolerant fashion. In this study, we propose approaches for the delivery of IPv6 packets in a delay-tolerant fashion in partially connected networks. We also propose another method that enhances these proposed approaches and optimises the packet delivery ratio. Our analysis shows that the proposed approaches can be easily adopted for IPv6/IPv4 packets to be delivered in a delay-tolerant fashion. Additionally, we observe that our approaches increase the packet delivery ratio in partially connected VANETs and can also be used in networks where the nodes are mobile or connections get broken frequently.
Analysis and modelling of an ozone generator using a phase-shift PWM full bridge inverter

This paper proposes the analysis and modelling of an ozone generator using a phase-shift pulse width modulation (PWM) full bridge inverter as a power supply. The circuit operation is fully described. The high frequency transformer and ozone generator mathematical models are also included for preliminarily calculating of instantaneous voltages and currents. The proposed system simulation using the MATLAB/SIMULINK software package is given. In order to ensure that zero voltage switch (ZVS) is always operated over a certain range of a frequency variation, a series-compensated resonant inductor is included. The advantage of the proposed system is a capability of varying ozone gas production quantity by varying the frequency of the converter whilst the applied voltage to the electrodes is kept constant. The correctness of the proposed technique is verified by both simulation and experimental results.
An Intelligent Email Agent

We propose an email agent that assists the user in the management of email messages. The agent is autonomous and runs in an UNIX environment. It has a learning capabilit y that permits the agent to learn the user's interests and preferences when dealing with messages, and to automatically perform the required actions. The learning algorithm is a variant of Quinlan's ID3 but the acquired knowledge is stored in a rule knowledge base. The agent can learn from several sources of knowledge, including the possibilit y to consult other similar email agents, presumably more knowledgeable than itself.