Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequence-Based Rendezvous for Dynamic Spectrum Access

In the context of dynamic spectrum access (DSA), rendezvous refers to the ability of two or more radios to meet and establish a link on a common channel. In decentralized networks, this is often accomplished by each radio visiting potential channels in random fashion, in a process that we call blind random rendezvous. In this work, we propose the use of sequences that determine the order with which radios visit potentially available channels. Through sequence-based rendezvous, it is possible to: (i) establish an upper bound to the time to rendezvous (TTR); (ii) establish a priority order for channels in which rendezvous occurs; (Hi) reduce the expected TTR as compared to random rendezvous. We provide an example of a family of sequences and derive the expected time-to- rendezvous using this method. We also describe how the method can be adopted when one or more primary users are detected in the channels of interest.
ON-OFF ATTITUDE CONTROL USING PULSE-WIDTH PULSE-FREQUENCY MODULATED INPUT SHAPER

Kinetic kill vehicle (KKV) is actuated by on-off thrusters to adjust its atti- tude, how to modulate continuous control commands to on-off or pulse signals to meet the requirements of the thrusters is a challenging task. Pulse-width pulse-frequency (P- WPF) modulation is an effective method that provides pseudolinear operation for on-off thrusters. In this work, a new thruster configuration of the KKV and its mathematical model is proposed, good guidelines for the PWPF parameters tuning task is presented, the linear quadratic regulator (LQR) technique in combination with PWPF is used to design the optimal attitude controller. The validity of the proposed methods is demonstrated through the three-axis nonlinear numerical simulations of the KKV of this work.
The effect of temperature and selective agents on the growth of Yersinia enterocolitica serotype O:3 in pure culture

This study examined the individual and combined effects of the selective agents normally present in Yersinia‐selective agar (i.e. cefsulodin, irgasan and novobiocin) on the growth kinetics of plasmid‐bearing (P+) and plasmid‐cured (P–) Yersinia enterocolitica serotype O:3 at 25 and 37 °C. Growth studies were carried out in pure culture, and the data obtained were subjected to linear regression analysis to determine lag phase duration(s) and growth rates of the examined strains. In general, the presence of selective agents increased the duration of the lag phase at 37 °C, with longer lag phases noted in all cases in which two or more selective agents were present. Growth rates in CIN broth base (CIN NA) and CIN NA plus commercial supplement (SR 109) (CIN) were faster at 37 than 25 °C, but in some cultures of incomplete CIN NA broth with less than three supplements added, growth tended to be faster at 25 than 37 °C. Generally, plasmid‐bearing strains grew slower than plasmid‐cured strains in most media at 37 °C due to virulence plasmid expression retarding growth. In some instances at 37 °C, it was observed that the growth rates of both plasmid‐bearing and plasmid‐cured strains were comparable, indicating the influence of added selective agent/s negating any effects associated with virulence plasmid expression. The effects of selective agents, incubation temperature and virulence plasmid carriage on the growth kinetics of Y. enterocolitica are discussed.
A Voxel-based Octree Construction Approach for Procedural Cave Generation

Procedural content generation is becoming an increasingly popular research area as a means of algorithmically generating scene content for virtual environments. The automated generation of such content avoids the manual labour typically associated with creating scene content, and is extremely useful in application areas such as computer graphics, movie production and video games. While virtual 3D caves are commonly featured in these virtual environment applications, procedural cave generation is not an area that has received much attention among researchers to date. This paper presents a procedural approach to generating 3D cave structures. Other than the development of a method to effectively automate the generation of visually believable 3D cave models, this paper also investigates how to efficiently construct and store this spatial information using a voxel-based octree data structure. In addition, the proposed approach demonstrates that caves with different characteristics can be generated by adjusting certain parameters in order to facilitate the creation of diverse cave structures.
Evidence of Field-Evolved Resistance of Spodoptera frugiperda to Bt Corn Expressing Cry1F in Brazil That Is Still Sensitive to Modified Bt Toxins

Brazil ranked second only to the United States in hectares planted to genetically modified crops in 2013. Recently corn producers in the Cerrado region reported that the control of Spodoptera frugiperda with Bt corn expressing Cry1Fa has decreased, forcing them to use chemicals to reduce the damage caused by this insect pest. A colony of S. frugiperda was established from individuals collected in 2013 from Cry1Fa corn plants (SfBt) in Brazil and shown to have at least more than ten-fold higher resistance levels compared with a susceptible colony (Sflab). Laboratory assays on corn leaves showed that in contrast to SfLab population, the SfBt larvae were able to survive by feeding on Cry1Fa corn leaves. The SfBt population was maintained without selection for eight generations and shown to maintain high levels of resistance to Cry1Fa toxin. SfBt showed higher cross-resistance to Cry1Aa than to Cry1Ab or Cry1Ac toxins. As previously reported, Cry1A toxins competed the binding of Cry1Fa to brush border membrane vesicles (BBMV) from SfLab insects, explaining cross-resistance to Cry1A toxins. In contrast Cry2A toxins did not compete Cry1Fa binding to SfLab-BBMV and no cross-resistance to Cry2A was observed, although Cry2A toxins show low toxicity to S. frugiperda. Bioassays with Cry1AbMod and Cry1AcMod show that they are highly active against both the SfLab and the SfBt populations. The bioassay data reported here show that insects collected from Cry1Fa corn in the Cerrado region were resistant to Cry1Fa suggesting that resistance contributed to field failures of Cry1Fa corn to control S. frugiperda.
A shape-based object class detection model using local scale-invariant fragment feature

Detecting object in unseen images is an challenging task because of the strong clutter background, various scale of object and the deformation of class. In this paper, we present a shape-based object detection model using scale-invariant fragment feature which is approximated by conjunctive short straight segments. This is a novel shape descriptor for object detection by bypassing estimation of scale of object in natural scene. Utilizing those local and consistent segments, we improve the robustness of model to natural background and deformation of object. We experiment our model on two texture-less image datasets, INRIA horses dataset and Weizmann horses dataset. The results demonstrate our model outperform those state-of-the-art methods.
Aeroelastic De ection of NURBS Geometry

The purpose of this paper is to present an algorithm for using NonUniform Rational B-Spline (NURBS) representation in an aeroelastic loop. The algorithm is based on creating a least-squares NURBS surface representing the aeroelastic de ection. The resulting NURBS surfaces are used to update either the original ComputerAided Design (CAD) model, Computational Structural Mechanics (CSM) grid or the Computational Fluid Dynamics (CFD) grid. Results are presented for a generic High-Speed Civil Transport (HSCT).
SLOPES: Hardware–Software Cosynthesis of Low-Power Real-Time Distributed Embedded Systems With Dynamically Reconfigurable FPGAs

In this paper, we present a multiobjective hardware-software cosynthesis system, called SLOPES, for multirate low-power real-time distributed embedded systems consisting of dynamically reconfigurable field-programmable gate arrays (FPGAs), processors, and heterogeneous communication resources. This cosynthesis algorithm simultaneously optimizes system price and average power consumption. First, we present an evolutionary algorithm that automatically determines the quantities and types of system resources, assigns tasks to different potentially reconfigurable processing elements, and assigns communication events to communication resources. Second, we propose a dynamic priority multirate scheduling algorithm to determine the times at which all the tasks and communication events in the system occur. This two-dimensional scheduling algorithm determines task priorities based on real-time constraints and detailed frame-by-frame FPGA reconfiguration overhead information. Experimental results indicate that the proposed method reduces schedule length by an average of 34.3% and reconfiguration energy by an average of 40.4%, compared to a method that does not consider the effect of partial reconfiguration during synthesis. SLOPES yields multiple system architectures that tradeoff system price and average power consumption under real-time constraints
The Promises and Pitfalls of Digital Technology in Its Application to Alcohol Treatment

Individuals seeking to change their alcohol use form a heterogeneous group with varied treatment goals—including moderation and abstinence—that therefore requires flexible treatment options. The availability of alcohol in the United States, and the pervasive social pressure to drink, warrant treatments that support individuals outside the treatment environment and that foster coping and self-regulation in the face of these demands. Emerging digital technologies show promise for helping both to hone therapies to clients’ individual needs and to support clients in settings beyond the clinic. In the broader health care arena, digital health technologies (DHTs) are transforming how health professionals assess, prevent, and treat both physical and mental health problems. DHTs include assessments and interventions delivered via computer, Internet, mobile phone, and wireless or wearable device technologies. The emerging literature examining within-treatment and mobile DHTs highlights an opportunity to create personalized alcohol treatments for every person seeking care. Despite the promises DHTs may hold, however, there still are many potential risks to using them and a number of challenges regarding how to integrate them into treatment successfully. This article will review the current and potential advantages of DHTs in alcohol treatment and the technological, personal, organizational, and systemic limitations of integrating various technology-based assessment and intervention programs into care.
CH-01 is a Hypoxia-Activated Prodrug That Sensitizes Cells to Hypoxia/Reoxygenation Through Inhibition of Chk1 and Aurora A

The increased resistance of hypoxic cells to all forms of cancer therapy presents a major barrier to the successful treatment of most solid tumors. Inhibition of the essential kinase Checkpoint kinase 1 (Chk1) has been described as a promising cancer therapy for tumors with high levels of hypoxia-induced replication stress. However, as inhibition of Chk1 affects normal replication and induces DNA damage, these agents also have the potential to induce genomic instability and contribute to tumorigenesis. To overcome this problem, we have developed a bioreductive prodrug, which functions as a Chk1/Aurora A inhibitor specifically in hypoxic conditions. To achieve this activity, a key functionality on the Chk1 inhibitor (CH-01) is masked by a bioreductive group, rendering the compound inactive as a Chk1/Aurora A inhibitor. Reduction of the bioreductive group nitro moiety, under hypoxic conditions, reveals an electron-donating substituent that leads to fragmentation of the molecule, affording the active inhibitor. Most importantly, we show a significant loss of viability in cancer cell lines exposed to hypoxia in the presence of CH-01. This novel approach targets the most aggressive and therapy-resistant tumor fraction while protecting normal tissue from therapy-induced genomic instability.
The role of schemata

Some discrimination studies (e.g., Miller, 1966) with humans have reported that learning withoutknowledge of results (NKR) was superior to learning with KR. However, Edmonds & Mueller (1967) and Edmonds, Mueller, & Evans (1966) used redundant stimuli equated in information content and found that, in several different discrimination tasks, KR facilitated initial performance but resulted in no better terminal performance than NKR. These investigators concluded that the effect of KR in a discrimination task is to facilitate selection of the relevant stimulus variables rather than to assist schema learning per se. Other studies (Edmonds & Evans, 1966a; Edmonds, Evans, & Mueller, 1966), using a reproduction task, also found that humans readily abstract the common characteristics (schema) of a set of stimuli without external reinforcement. These results support the Gibsons' (1955) view that perceptual learning consists in an abstraction of relevant aspects of the stimuli without need for any event which can be identified as reinforcement. A more direct test of "what is learned" in discrimination learning has been suggested by Wohlwill (1958). He pointed out that if discrimination is dimensional, learning should transfer to a new sample of stimuli, whereas no transfer would occur if learning consists of the isolation of specific cues. The present study used quantitatively defined stimuli in a transfer design to investigate this problem. A transfer group was trained by having each S discriminate instances of a single schema family from random (no schema) patterns. In the testing phase, this group discriminated among patterns representing several new schema families. A control group received random patterns in the training phase and had the same task as the transfer group in the testing phase. In this design, the learning of dimensional differences (concept of a schema) would be evidenced by the transfer group's performing significantly better than the control group in the testing phase. Subjects The Ss were 66 undergraduates enrolled in psychology courses at Augusta College. They were randomly assigned to the transfer and control groups.
Adaptive Synchronization of the Modified Chua's Circuit Systems

This study addresses the synchronization of the modified Chua circuit systems with fully unknown parameters and nonlinearity in the control input. A simple robust controller with a single-state variable feedback and a nonlinear compensating mechanism is derived, such that the states of two modified chaotic systems are asymptotically synchronized. According to the Lyapunov stability theorem, the asymptotic stability of the solutions of the state error system is studied. A series of numerical simulations are given to explain the effectiveness and robustness of the designed simple robust controller. In simulation the Mento-Carlo method used to evaluate the robustness of the control system.
Finding bugs in software with a constraint solver

We present a static technique for finding bugs in object-oriented procedures. It is capable of checking complex user-defined structural properties—that is, of the configuration of objects on the heap—and generates counterexample and is fully automatic. It is based on the Alloy modelling language and analyzer. The method relies on a three-step translation: from code to a formula in Alloy, which is a first-order relational logic, then to a propositional formula, and finally to conjunctive normal form. An off-the-shelf SAT solver is then used to find a solution that constitutes a counterexample. Modularity comes at the price of intermediate specifications. To minimize such annotations, the analysis contains a suite of optimizations that allow checking larger procedures with fewer annotations. The optimizations are based on a special treatment of relations that are known to be functional, and target all steps of the translation to CNF. Their effect is demonstrated with a prototype tool that can handle a subset of Java, by analyzing real code. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Effects of Prior Knowledge on Memory: Implications for Education.

The encoding, consolidation, and retrieval of events and facts form the basis for acquiring new skills and knowledge. Prior knowledge can enhance those memory processes considerably and thus foster knowledge acquisition. But prior knowledge can also hinder knowledge acquisition, in particular when the to-be-learned information is inconsistent with the presuppositions of the learner. Therefore, taking students' prior knowledge into account and knowing about the way it affects memory processes is important for optimization of students' learning. Recent behavioral and neuroimaging experiments have shed new light on the neural mechanisms through which prior knowledge affects memory. However, relatively little is known about developmental differences in the ability to make efficient use of one's knowledge base for memory purposes. In this article, we review and integrate recent empirical evidence from developmental psychology and cognitive neuroscience about the effects of prior knowledge on memory processes. In particular, this may entail an extended shift from processing in the medial temporal lobes of the brain toward processing in the neocortex. Such findings have implications for students as developing individuals. Therefore, we highlight recent insights from cognitive neuroscience that call for further investigation in educational settings, discussing to what extent these novel insights may inform teaching in the classroom.
An architecture for ink annotations on Web documents

There have been recent improvements in document technologies like the standardization of object interfaces to access and manipulate the properties of Web documents. There has also been significant progress in pen based computing for recognition of digital ink in desktops, tablets and handheld devices. These have necessitated a need for further research on annotation architectures for digital documents, specifically pen-based annotation systems. This paper presents an attempt to leverage the new standards of DHTML and W3C DOM that are being gradually implemented by popular browsers, to build a prototype of an ink annotation system with common components across browsers. One of the primary goals in this study is to semantically link ink data with underlying document elements like text and images. The system has three components: a) ink capture and rendering b) Ink Understanding, which recognizes and associates ink with the underlying document; and c) Ink storage and retrieval.
Sympathetic Activation in Adipose Tissue and Skeletal Muscle of Hypertensive Rats

The activation of the sympathetic nervous system is a common feature of arterial hypertension and other cardiovascular diseases. This activation might be dependent on an altered baroreflex control of vascular resistance of which the inhibitory response on sympathetic activity appears impaired. The aim of the study was to monitor during the natural course of arterial hypertension in spontaneously hypertensive (SHR) and age-matched Wistar Kyoto (WKY) rats (5, 16, 30, and 54 weeks of age) the peripheral sympathetic activity expressed as interstitial norepinephrine (NE) release and as tyrosine hydroxylase (TH) activity, the rate-limiting enzyme of NE synthesis, in the differently baroreflex-controlled subcutaneous adipose tissues and skeletal muscles. Blood pressure and plasma NE in SHR were similar to WKY at 5 weeks of age but increased at all other ages. Body weight was similar in both 5-week-old rats but reduced in SHR at all other ages. The interstitial NE levels were greater in both SHR tissues at all ages as compared with WKY. In adipose tissue of SHR, TH activity was higher at all ages as compared with WKY, whereas TH activity in skeletal muscle was higher only after the development of hypertension. These data show that in both SHR tissues, an increase of interstitial NE release is always present during its lifespan. This suggests that increased sympathetic activation in the SHR model is not specific to baroreflex-controlled tissues such as skeletal muscle but involves also subcutaneous adipose tissue, the sympathetic efferents of which are independent from baroreflexes.
Tumor necrosis factor-α serum levels in healthy smokers and nonsmokers

Background: Tobacco smoking is the most important risk factor for chronic obstructive pulmonary disease (COPD) development. Inhaled cigarette smoke can induce tumor necrosis factor-α (TNF-α) production by alveolar macrophages, which in turn may enhance the production of metalloproteinases (MMPs). MMPs have been involved in mediating airway inflammation and lung destruction. Objectives: We aimed to measure the TNF-α serum levels in healthy heavy smokers and healthy nonsmokers to determine the dose-response relationship based on the cigarette smoke exposure. Subjects and methods: We included in our study 43 healthy heavy smokers and 19 healthy nonsmokers (the control group). The smokers group was classified as less than one pack, one pack, and more than one pack per day. A clinical and paraclinical evaluation was performed in both groups, without any evidence of infection or COPD. The serum levels of TNF-α were assessed by ELISA. Results: The TNF-α serum levels were significantly higher for the group of smokers compared to the group of nonsmokers (P < 0.004). We also noticed an increased TNF-α concentration in the serum of smokers with more than one pack per day compared with those with less than one pack per day (P < 0.03). There was a positive correlation between the serum level of TNF-α and tobacco smoke exposure. Conclusions: The high levels of TNF-α in the serum of smokers suggest an imbalance between the proinflammatory and anti-inflammatory factors as a result of tobacco smoke exposure. The concentration of TNF-α is elevated in the serum of healthy heavy smokers in a cigarette dose-dependent manner. We speculate that the serum level of TNF-α might be a useful biomarker for the selection of heavy smokers with a high risk of developing smoke induced pulmonary diseases.
An Associative Generated Model for Multi-signals Based on Deep Learning

During exploring the emergence of language, we found that the brain can extract some common features from the same thing in different representations by pattern recognition and association. Consequently, the brain would establish a connection for identical concept from multi-signals. An associative generated model primarily based on Restricted Boltzmann Machine (RBM) and Deep Belief Network (DBN) is set up for multi-signals to simulate the brain's ability. The first step is to use the DBNs for extracting features from multiple input signal sources. The second is using top-level RBM to achieve the goal of associating and generating mutually by fusing each feature. Finally, we verify the feasibility of the model through the realization of generating Arabic digital pictures and Chinese characters digital images reciprocally.
A Secure Data Aggregation Approach in Hierarchical Wireless Sensor Networks

As wireless sensor networks (WSNs) are employed in many applications, security of these networks must be ensured. Considering the limited resources of nodes in WSNs, it is a critical challenge. Meanwhile, the deployed nodes are separated and they need to cooperatively transmit the sensed data to the base station. To reduce the amount of sending data, an aggregation approach can be applied along the path from sensors node to the sink. However, usually the carried information contains confidential data. Therefore, a security aggregation approach is required. An efficient security data aggregation scheme using the renewable hash chain is proposed in this paper. The scheme provides data authentication, confidentiality and integrity for the WSNs. The system is implemented with the real nodes. The result shows that the proposed scheme is secure and efficient.