Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Gender Participation in Forest Resources Management in the Cross River National Park Enclave Communities , Nigeria

This study was designed to assess factors/constrains to gender participation in the exploitation and management of forest resources within the protected areas of the Cross River National Park enclave communities. The quantitative research design was adopted for the study. A null hypothesis of no factors/constrains to gender participation in the management of forest resources was formulated. 638 respondents were sampled using the stage-wise random sampling technique from a population of about 4249 people living within the six enclave communities of Okwangwo, Okwa 1 and 2, Mkpot, Abung and Iku all within Boki and Akamkpa local government areas of Cross River National Park, of Okwangwo and Oban respectively(15%). The instrument for data collection was a well structured questionnaire divided into two sections with four point likert scale response options. Data collected using the instrument was coded and transformed into SPSS version 16 and analyzed using the multiple regressions analysis. Ten factors: Sex, age, marital status, educational status, cultural factors, religion, household income, occupational status, household heads and property rights were suggested as being responsible for gender participation in the management of forest resources. The result of the regression analysis shows a yielded coefficient of regression correlation (R) of . 351 and a multiple regression R-square (R 2 ) of . 123, and adjusted R 2 of . 109, at . 01 significant level, the result is significant, the result also shows that an analysis of variance (ANOVA) of the multiple regressions produced an F-ratio of 8.817, while the f-critical value is 1.91 (2-tailed). The standardized regression beta weight ranged from -. 021 to -3.980, the beta weight of four factors (sex, -3.980, marital status, -2.056, educational status,-3.111 and occupational status, -2.618) were significant at 0.05 level of significance, while the other six factors (age, .462, cultural factors, .395, religion, 1.052, household income, -.123, household heads, -.021 and property rights, -.660) were not significant at 0.05 significant level, meaning that they might not necessarily contribute to gender participation in forest resources management. It was therefore recommended that women in every society should be given free hands to participate in management activities and all cultural and social barriers acting as hindrance to gender participation in management activities should be removed to allow women contribute their ideas in situation and decisions that may affect them most.
Design and Implementation of a High Speed Low Power Flash ADC

A 4-bit Flash Analog to Digital Converter (ADC) is designed and implemented in 90nm CMOS process is presented in this paper. The proposed flash ADC employs resistive ladder logic network, comparators and encoder logic to convert the given continuous input signal into output digital code. The flash ADC utilizes a novel encoder realized using pseudo dynamic CMOS logic which has been implemented with fewer transistors compared to the previous other techniques. The designed flash ADC consumes 0.46mW when operated from a 1.2V power supply voltage. The operating speed of the design is 10GHz and the simulated integral non-linearity error (INL) and differential non-linearity error (DNL) are between 0.14/-0.03LSB and 0.41/0.18LSB respectively. Keywords— Comparator, Low voltage, Calibration, Low power, Inverter, Least Significant Bit, Most Significant Bit and CMOS.
What Factors Sustain Professional Growth among School Counselors

This study examined relationships among self-reported professional expertise, organizational support of evidence-based practices (EBP), and professional growth. Data were collected from 85 members of American School Counseling Association (ASCA). School counselors with higher self-reported expertise reported that they were more likely to improve their school counseling skills. Those with more years of experience supervising school counselors also reported greater professional expertise. No linear relationship was found between organizational support of EBP and perceived professional expertise, which may be attributed to lack of adequate structural and organizational school supports. Implications for future research, counselor development, and supervision are discussed.
Security Challenges and Countermeasures for the Heterogeneity of IoT Applications

The Internet of Things (IoT) enables the integration of data from virtual and physical worlds. It involves smart objects that can understand and react to their environment in a variety of industrial, commercial and household settings. As the IoT expands the number of connected devices, there is the potential to allow cyber-attackers into the physical world in which we live, as they seize on security holes in these new systems. New security issues arise through the heterogeneity of IoT applications and devices and their large-scale deployment.
Wagner ' s law vs . Keynesian hypothesis : New Evidence from Egypt

In this paper, we tested the Wagner’s Law against the Keynesian proposition for the Egyptian economy over the period of 1980-2012. After conducting theoretical and empirical literature, we used the Mann (1980) notation to test for the cointegration between government expenditure and GDP. Using ADF-breakpoint unit root test, Pesaran, Shin et al. (2001) bounds test for cointegration and ARDL model we estimated the long-run relationship between both variables. We found a cointegration between government expenditure and GDP with elasticity of the former to the latter equal 2.55 and the causality runs from the GDP to the government expenditure, which indicates that the Egyptian economy is Wagnerian. The paper provides some policy implication too.
econstor Make Your Publications Visible . A Service of zbw

This paper studies the interaction of a minimum quality standard and exports in a vertical product di¤erentiation model when rms sell global products. If ex ante quality of foreign rms is lower (higher) than the quality of exporting rms, a mild minimum quality standard in the home market hinders (supports) exports. The minimum quality standard increases quality in both markets. A welfare maximizing minimum quality standard is always lower under trade than under autarky. A Minimum quality standard reduces pro ts for the exporting rm. It increases domestic welfare, but reduces welfare in the export market. JEL Classi cation: F12, L13, L50
Trajectory-aware three-stream CNN for video action recognition

Abstract. Video-based human action recognition is a challenging task in computer vision. In recent years, the convolution neural network (CNN) and its extended versions have shown promising results for video action recognition. However, most of the existing methods cannot deal with the global motion information effectively, especially for long-term motion which is crucial to represent complex none-periodic actions. To address this issue, a stacked trajectory energy image (STEI) is proposed by extracting trajectories from motion saliency regions and stacked them onto one grayscale image. This will result in an STEI with discriminative texture feature which can effectively characterize the global motion from multiple consecutive frames. Then, a three-stream CNN framework is proposed to simultaneously capture spatial, temporal, and global motion information of the action from RGB frames, optical flow, and STEI. Moreover, a trajectory-aware convolution strategy is introduced by incorporating local and long-term motion information so as to learn the motion features directly and effectively from three complementary action-related regions. Finally, the learned features are aggregated and categorized by a linear support vector machine. The experimental results on two challenging datasets (i.e., HMDB51 and UCF101) demonstrate that our approach statistically outperforms a number of state-of-the-art methods.
Augmenting Mobile Data Networks using WiFi Offloading: A Measurement Study

The growing popularity and proliferation of mobile devices has resulted in an exponential growth of mobile data traffic or also known as mobile data explosion. Cellular network providers are struggling to address the challenges of bandwidth scarcity and also to meet end user’s expectation of high network capacity. Due to the abundance of existing WiFi infrastructure and significantly inexpensive deployment compared to cellular network upgrade, WiFi offloading seems the most viable solution at the moment. The Malaysian Communications and Multimedia Commission (MCMC) reported in Internet User Survey 2016 that more than half (59.6%) of Internet users in Malaysia used free Wi-Fi to go online. This work presents a real trace of quantitative study on the role of WiFi networks in augmenting mobile data offloading in Malaysia scenario. The research investigated how much traffic load WiFi offloading takes away from cellular network and its utilization pattern according to a different group of users. An extensive measurement study was conducted by collecting statistics of WiFi connectivity from 100 Android platform users for 18 days. Findings from the preliminary results showed that WiFi offloaded a significant amount of data traffic in user’s daily mobile data consumption. Therefore, it is an interesting alternative for cellular network operators in to accommodate and augmenting the current traffic growth as well as providing insights into their network planning or creative price plans.
Sheet 1 of 5 US 9 , 328 , 397 B 2 pSheB 8 : 88 : 8 :

U.S. C. CPC. C22B3/18 (2013.01); C02F 3/34 (2013.01); C02F 3/342 (2013.01); C07K 14/195 (2013.01); C12N 9/0004 (2013.01); C12N 9/14 (2013.01); CI2P3/00 (2013.01): CI2R I/01 (2013.01); C12Y 120/99001 (2013.01); C12Y 306/03016 (2013.01); C22B I/II (2013.01): (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) (2006.01) C02F 3/28 (2013.01); C02F 2101/103 (2013.01); C12Y 120/04001 (2013.01); Y02P 20/52 (2015.11) (58) Field of Classification Search None See application file for complete search history.
Hamburg Bit-Bots and WF Wolves Team Description for RoboCup 2019 – Humanoid TeenSize –

This team description paper presents the developments made by the joint team Hamburg Bit-Bots & WF-Wolves. We present new software approaches we programmed and evaluated, like the Dynamic Stack Decider (DSD), our advances in image processing and our improvements to the walking engine. Additionally the newly developed foot pressure sensors as well as our progress towards a reliable and fast servo control are introduced. We, the joint team of Hamburg Bit-Bots and WF Wolves, hereby apply for participation in the RoboCup 2019 in Sydney, Australia in the Humanoid TeenSize Team Competition . The content of this paper is the same as the application for the KidSize [5].
Anticancer Activity of Allium sativum ( Bulb ) Polyphenolic Compound

International Journal of Pharmaceutical Sciences Review and Research Available online at www.globalresearchonline. net © Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited. © Copyright protected. Unauthorised republication, reproduction, distribution, 131 Rajeev Nema, Sarita Khare, Alka Pradhan Sarojini Naidu Government Girls Post Graduate (Autonomous) College, Shivaji Nagar, Bhopal, M.P., India. *Corresponding author’s E-mail: rrsht.nema@gmail.com
A Machine Learning Approach Based on Automotive Engine Data Clustering for Driver Usage Profiling Classification

The potential for processing car sensing data has increased in recent years due to the development of new technologies. Having this type of data is important, for instance, to analyze the way drivers behave when sitting behind steering wheel. Many studies have addressed the drive behavior by developing smartphone-based telematics systems. However, very little has been done to analyze car usage patterns based on car engine sensor data, and, therefore, it has not been been explored its full potential by considering all sensors within a car engine. Aiming to bridge this gap, this paper proposes the use of Machine Learning techniques (supervised and unsupervised) on automotive engine sensor data to discover drivers’ usage patterns, and to perform classification through a distributed online sensing platform. We believe that such platform can be useful used in different domains, such as fleet management, insurance market, fuel consumption optimization, CO2 emission reduction, among others.
Relieving nausea and vomiting in patients with cancer: a treatment algorithm.

PURPOSE/OBJECTIVES To describe a treatment algorithm for the choice of antiemetic therapy for the patient receiving chemotherapy. DATA SOURCES Published literature, data collected on an inpatient oncology unit. DATA SYNTHESIS Because little information is available to systematically guide clinicians in choosing the best antiemetic for an individual patient who is receiving a particular chemotherapy protocol, a treatment algorithm was developed. The four main variables include emetogenicity of the protocol, patient's age, previous adverse reaction to antiemetics, and failure of previous antiemetics. Other factors to consider include alcohol use, anticipatory nausea, patient health status, nausea history not related to chemotherapy, and type and availability of IV access. CONCLUSION The use of this algorithm resulted in appropriate choice of antiemetics and improved patient outcomes associated with reduced incidence of nausea and vomiting. IMPLICATIONS FOR NURSING PRACTICE Nurses can have a significant impact on a patient's experience with chemotherapy treatment by improving symptom management of nausea and vomiting.
Reynolds number effects on aerodynamics forces of Kwangyang Bridge girder

ABSTRACT: In this paper, the experimental results for twin box girder of the Kwnagyang Bridge are presented in order to investigate the sensitivity of the Reynolds numbers on aerostatic force coefficient. High speed wind tunnel testing on 1:30 scale sectional model were carried out at the aeronautical wind tunnel in Korea Air Force Academy. The drag and lift coefficients revealed significant decrease of nearby 23% at supercritical region. The safety rail prevented the Reynolds number dependency of aerostatic force coefficients at negative angles of attack. In similar way, the boundary layer trip strip attached at bottom surface of girder reduced the Reynolds number dependency of aerostatic forces by fixing the location of flow transition. The pressure coefficients at girder surface near the gap significantly changed as the Reynolds number increase because of variation of the locations of flow separation and transition. The unbalanced burden of the drag force and lift forces at each box girder appeared in subcritical region was gradually resolved, and both boxes were almost equally loaded the forces at supercritical region.
Lawrence Berkeley National Laboratory Recent Work Title DPP-PMRF : Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives Permalink

We present a new parallel algorithm for probabilistic graphical model optimization. The algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).
Heterogeneous Knowledge Transfer via Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

Heterogeneous knowledge naturally arises among different agents in cooperative multiagent reinforcement learning (MARL). Existing works have demonstrated that peer-to-peer knowledge transfer, a process referred to as teaching, accelerates individual learning speed and improves team-wide performance. Similar to recent learning to teach frameworks, we aim to learn teaching policies that decide when and what to advise to a teammate. In this work, we introduce a new learning to teach framework, called Hierarchical Multiagent Teaching (HMAT). The proposed framework solves difficulties faced by existing works when operating in domains with long horizons, large state spaces, and continuous actions. HMAT transfers heterogeneous knowledge by taking advantage of temporal abstractions of hierarchical reinforcement learning and representations of a deep neural network. Our empirical evaluations show that HMAT accelerates teamwide learning progress in complex environments.
Evaluation of physicochemical , technological and morphological characteristics of powdered yellow passion fruit peel

The aims of this study were to ascertain the physicochemical properties, technological properties, phytochemical compounds and morphology of powdered yellow passion fruit products to determine their suitability for use as natural food ingredients. Passion fruit peel powder was obtained by convective hot air-drying at 60°C, freeze-drying and compared with a commercial sample. The passion fruit peel (dried at 60°C and freeze-dried powders) could be used as an intermediate food ingredient in the development of functional foods because of its good levels of phenolic compounds and the high total dietary fiber (63.98-72.62%) content as pectin (6.98-19.6%). In addition, these fiber-rich co-products have potential applications as ingredients in products requiring hydration and viscosity development due to their high total dietary fiber content and good technological proprieties, especially their water holding (6.30-14.9 g H2O/g) and oil holding capacities (2.6–6.5 g oil/g), especially for the freeze-dried samples.
Butterfly Effects of the First and Second Kinds : New Insights Revealed by High-dimensional Lorenz Models

Over the span of 50 years, the pioneering study of Lorenz using a threedimensional (Lorenz) model (3DLM) in 1963 and follow-up studies in 1969 and 1972 have changed our view on the predictability of weather and climate by revealing the so-called butterfly effect. Although Lorenz’s ‘63 and ‘72 studies emphasized nonlinear dynamics, researchers often apply a “simple” conceptual model that contains a monotonic positive feedback instead of time-varying (positive or negative) nonlinear feedback in order to understand the characteristics of nonlinear solutions within the 3DLM. In this study, we: (1) define butterfly effects of the first and second kinds in order to indicate the sensitive dependence of solutions on initial conditions, and the hypothesized enabling role of tiny perturbations in producing an organized large-scale system (e.g., a tornado), respectively; (2) illustrate important but overlooked features (i.e., the boundedness and recurrence of solutions within the 3DLM); (3) present examples to illustrate common misunderstandings regarding butterfly effects and explain the fundamental differences between the two kinds of butterfly effects; (4) illustrate the fundamental role of nonlinearity in creating oscillatory components with incommensurate frequencies, transferring energy across scales, and providing negative or positive feedbacks; (5) discuss various types of solutions (e.g., chaotic, linearly unstable, and/or nonlinear oscillatory solutions) in Lorenz models; and (6) propose that the entirety of weather is a superset that consists of both chaotic and nonchaotic processes. Depending on the time-varying collective impact of heating, dissipations, and nonlinearity, specific weather systems may appear on a chaotic or nonchaotic orbit for a finite period of time.
Zephyr : Simple , Ready-to-use Software-based Power Evaluation for Background Sensing Smartphone Applications

Innovations in mobile hardware and software need corresponding advances in the accurate assessment of power consumption under realistic conditions. This is especially relevant for smartphone-based background sensing applications. Assessing the power consumption of such applications requires ease of use, deployment in situ and well-understood error characteristics. Existing measurement methods, based on external power meters or power models, are increasingly unable to keep up with these requirements. External power meters require access to device batteries and do not capture context-sensitive power drain. Power models must be rebuilt for each specific device, adapted to each new OS version, and require administrator access to instrument fine-grained system-level APIs. These limitations impede the inclusion of accurate, universal evaluations in the research literature. We propose a simple and portable alternative, Zephyr, which infers an application’s power drain using the relative State of Charge change rate (SoCCR) via the phone’s battery sensor. We validate our methodology through experiments that characterize SoCCR on Android and iOS devices and show that they are consistent with hardware readings, across identical phones, for the same phone over time and over both slowly and quickly varying workloads. The Zephyr implementation is modular, open source, and available for Android and iOS today. This work is supported by the National Science Foundation, under grant CPS-1239552 (SDB). Author’s addresses: K. Shankari, D. Culler, and R. Katz, Computer Science Division, University of California Berkeley; J. Fürst, and P. Bonnet, IT University of Copenhagen; Y. Wang, Cornell University.
Quantitative trait loci linked to plant production traits in rice ( Oryza sativa ) under drought stress in a target environment

Drought stress is the major constraint to rice (Oryza sativa) production and yield stability in rainfed ecosystems. Identifying genomic regions contributing to drought resistance will help to develop rice cultivars suitable for rainfed regions through molecular marker-assisted breeding. Quantitative trait loci (QTLs) linked to plant production traits under drought stress were mapped by evaluating 155 F7 recombinant inbred (RI) lines of IR58821-23-B-1-2-1/IR52561UBN-1-1-2 under rainfed and irrigated conditions in the target environment. The RI lines were subjected to water stress during grain filling by natural rainfall failure events in two successive seasons. The RI lines showed significant variation in plant phenology, plant biomass, yield, and yield components under rainfed and irrigated conditions. Grain yield under rainfed condition had a positive correlation with harvest index and negative correlations with spikelet sterility and the number of days to 50% flowering. A total of 11 QTLs, identified for various plant phenology and production traits under rainfed and irrigated conditions, accounted for 9.3–23.4% of the phenotypic variation. A genomic region identified on chromosome 2 harboured a large effect QTL for grain yield (23.4%) under rainfed conditions. The region C499-PC11M1 on chromosome 2 identified for grain yield under rainfed conditions was colocated with QTLs associated with root traits.