Miracle-dz/UniFAR-FTUs huggingface dataset:
Communicating Agricultural Information for Development: The Role of the Media in Zimbabwe

Abstract The success of agricultural development programmes in developing countries largely depends on the nature and extent of the use of mass media in the mobilisation of people for development. The media, which offers unique opportunities to disseminate information, can play an important role in informing citizens about social, academic, and economic issues, amongst others. This is also true in the agricultural sector. Radio for example, is an inexpensive medium, and therefore enjoys a wide range of diffusion, even among rural and less literate people who have access to fewer information resources. The purpose of this study was to investigate how the print and electronic media sources are contributing to the communication of information relating to agricultural development in Zimbabwe. A questionnaire was distributed to all media houses in Zimbabwe. The results indicate that there is a significant coverage, by the media, of issues relating to agriculture and the agriculture industry. The broadcast media in particular, make efforts to reach out to a range of audiences who speak minority languages such as Kalanga, Venda, Sotho, Doma, Yao, and Shangaan. However, the media face challenges, including a lack of subject specialists, language barriers, constraints on financial and material resources, and poor road infrastructure that inhibits travelling. This study recommends training, short courses on agriculture reporting, and courses that provide information on the available resources to improve the quality of news and information regarding agriculture-related issues reaching mainly rural audiences of farmers in Zimbabwe.
Linking Essential Learning Outcomes and Interprofessional Collaborative Practice Competency in Health Science Undergraduates.

Abstract Assessing student learning outcomes and determining achievement of the Interprofessional Collaborative Practice (IPCEP) Core Competency of Values/Ethics in a generic pre-professional Bachelor of Science in Health Science (BSHS) program is challenging. A course level Student Learning Outcome (SLO) is: “…. articulate the impact of personal values and professional ethics in healthcare decision-making”. A program level terminal learning outcome is to “…. critically discuss the interface of values/ethics on health outcomes”. One university level Essential Learning Outcome (ELOs) that all baccalaureate students are expected to achieve by graduation is Ethical Reasoning. This was equivalent to the IPCEP Values/Ethics core competency. This paper describes a strategy to simultaneously measure the Values/Ethics competency at course, program, and university levels. A narrative analysis (n=94) using required ethical decision making BSHS student papers was conducted to determine achievement of SLOs/ELOs and the IPCEP Values/Ethics core competency. Eleven items in the grading criteria were linked to outcome criteria for university ELO competency. A point value was assigned to each of these items using a scoring rubric indicating level of achievement. Results indicated that most students were at the Skilled level for the majority of students, and demonstrated adequate achievement of university, program, and course level learning outcomes as well as achievement of the IPCEP Values/Ethics core competency. Keywords: Assessment; Essential Learning Outcomes; Ethics; Rubrics; Values; Student Learning Outcomes; Competency
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Research on obstacles avoidance technology For UAV based on improved PTAM algorithm

When used in counter-terrorism and disaster rescue, UAVs may possibly fly in buildings. In an indoor closed environment, GPS signal may be blocked, which will make UAVs difficult to obtain their location. In addition, a complex indoor environment also brings challenges to the safety of flight. Therefore, it is necessary to identify complex environments and avoid obstacles in real-time. This paper introduces the PTAM algorithm to the UAV ground control module. To deal with poor illumination of indoor environment, less feature points and other issues, we improve the algorithm and design a self-adaptive map feature point generating mechanism, reducing the dependency of the algorithm on the number of feature points and illumination conditions. On this basis, this paper proposes an obstacle recognition algorithm and designs a warning mechanism for the ground control module. Finally, we use a small quad-rotor UAV to test this algorithm. The results show that the proposed method can provide warning to the obstacles during flight in unknown indoor environments with self-localization. The experiments demonstrate that this algorithm is effective in real-time, which has great significance to explore autonomous positioning and flight safety for UAVs in GPS denied environments.
Suppression of impulse noise using adaptive filters

The electrical activity of muscles is usually modeled using Gaussian probability distribution function. Such assumption is not always true, because real-life muscle noise has impulse character as well. Adaptive threshold technique is one important step in the detection of QRS Complexes. However, presence of impulse noise may trigger false positives. The proposed system uses adaptive filters to suppress impulse noise in ECG signal and avoid the false positives. It was observed that despite the noise, the algorithm identifies the system and adjusts coefficients accordingly. Significant improvement in Signal-to-Noise ratio is achieved after suppressing impulse noise.
Instance Matching with COMA++

Schema matching is the process of identifying semantic correspondences between schemas. COMA++ is a matching prototype which uses several characteristics of schemas to determine similarities between them, for example the names and data types of the schema elements and structural information. In this paper we propose two instance-based matchers for COMA++ to gain a further quality improvement. The features of the matchers and first results are described.
Improved Concentric Clustering Routing Scheme adapted to various environments of sensor networks

Wireless sensor networks con sist of sink nodes and multiple sensor nodes that monitor environmental conditions such as pressure, temperature, etc. The main constraint associated with sensor nodes is energy consumption. The Extended Concentric-Clustering Routing Scheme ECCRS [1] is a hybrid mechanism that unifies the chain-based scheme PEGASIS and the clustering scheme. In this paper, we improve the energy consumption in ECCRS further by improving the energy and distance parameters. In our approach, the sensor field is divided into various levels and each level has the same node density as well as the same number of nodes, for which the radius of each level is adjusted accordingly. To improve the energy factor in ECCRS, our proposed scheme creates a set of probable candidates for cluster heads. The cluster head formation of a level from its probable candidate set takes into account the minimum distance between the higher level cluster head the nodes of the probable candidates set of the same level. The simulation results show that our approach is 13% more efficient as compared to ECCRS in terms of energy consumption.
Capacity Fade Estimation in Electric Vehicle Li-Ion Batteries Using Artificial Neural Networks

In this paper, an artificial neural network (ANN) based approach is proposed to estimate the capacity fade in lithium-ion (Li-ion) batteries for electric vehicles (EVs). Besides its robustness, stability, and high accuracy, the proposed technique can significantly improve the state-of-charge (SOC) estimation accuracy over the lifespan of the battery, which leads to more reliable battery operation and prolonged lifetime. In addition, the proposed technique allows accurate prediction of the battery remaining service time. Two identical 3.6-V/16.5-Ah Li-ion battery cells were repeatedly cycled with constant current and dynamic stress test current profiles at room temperature, and their discharge capacities were recorded. The proposed technique shows that very accurate SOC estimation results can be obtained provided enough training data are used to train the ANN models. Model derivation and experimental verification are presented in this paper.
Introduction: Discourse, grammar and intersubjectivity

This special issue includes a collection of papers on language and intersubjctivity. There are two paradigms in linguistic approaches to intersubjectivity; cognitive linguistics and interactional linguistics, but these two paradigms hardly ever meet. This is due to the fact that these paradigms have opposing views on cognition and mental events. However, both these paradigms draw from phenomenology: whereas cognitive linguistic approaches to intersubjectivity have their basis on Husserl's philosophy, interactional linguistics is influenced by ethnomethodological conversation analysis and the philosophy of Schutz. Despite the apparent differences between these approaches, there are convergences, too. Moreover, both approaches are needed for a full account of language and human intersubjectivity.
Sentiment analysis on Twitter

Social media has become an important information source with the expanding internet and ideas shared by the people. The social media raw data which is quite disordered and messy can not be processed as it is and obtain adequate results. In this study, sentiment analysis has been performed by collecting data from the Twitter. To perform this analysis an intelligent system has been created by using machine learning methods such as Naïve Bayes, Random Forest, Support Vector Machine and the compared results has been given.
Attitude similarity and attraction: Validation, positive affect, and trust as sequential mediators

Effectance motivation—an urge for certainty and a feeling of being able to know, predict, and control one's environment—was initially proposed as the mechanism underlying attitude similarity effects on attraction. However, this motivation was discarded as an explanation when positive affect was identified. The presence of alternative mechanisms did not deny a role for the validation of attitudes in attraction. Therefore, we investigated the validation of one's views by those of peers as an additional mediator and its relation with two previously known mediators of positive affect and trust. As hypothesized, validation mediated attitude similarity effects when measured alone (Experiment 1) and within sequential mediation patterns involving positive affect (Experiment 2A) and trust (Experiments 2B and 2C).
Detection Method of Blog Spam Based on Categorization and Time Series Information

Recently, a blog is well known as a tool for transmitting information easily. However, as the blog spam increases, the method of filtering spam is required to be efficient. In early researches, the method for detecting spam mails with Bayesian filter detects the spam from the characteristics of spam words appearing in spam mails with a high degree of accuracy. How-ever, there are some problems in applying the Bayesian filter to the blog spam detection. First, it takes a lot of man-hours to keep high accuracy continuously. Second, the accuracy of spam detection decreases because there are too many various words in a blog and the relative number of word occurrences de-creases. Furthermore, we have to consider the time when each word occurred. Therefore, in this paper, we acquire information to update the judgment information automatically and calculate spam probability of words with every category to cope with these problems. In addition, we use the time-series information to revise spam probability of words to cope with the problem that the words that occur change over time. With these countermeasures, we propose a method for detecting a new blog spam. With comparative experiments, the present method is better adapted to any existing method.
Proteomic Analysis of Formalin-fixed Prostate Cancer Tissue*S

Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue would enable retrospective biomarker investigations of this vast archive of pathologically characterized clinical samples that exist worldwide. These FFPE tissues are, however, refractory to proteomic investigations utilizing many state of the art methodologies largely due to the high level of covalently cross-linked proteins arising from formalin fixation. A novel tissue microdissection technique has been developed and combined with a method to extract soluble peptides directly from FFPE tissue for mass spectral analysis of prostate cancer (PCa) and benign prostate hyperplasia (BPH). Hundreds of proteins from PCa and BPH tissue were identified, including several known PCa markers such as prostate-specific antigen, prostatic acid phosphatase, and macrophage inhibitory cytokine-1. Quantitative proteomic profiling utilizing stable isotope labeling confirmed similar expression levels of prostate-specific antigen and prostatic acid phosphatase in BPH and PCa cells, whereas the expression of macrophage inhibitory cytokine-1 was found to be greater in PCa as compared with BPH cells.
A comparative study for XML change detection

Change detection is an important part of version management for databases and document archives. The success of XML has recently renewed interest in change detection on trees and semi-structured data, and various algorithms have been proposed. We study here different algorithms and representations of changes based on their formal definition and on experiments conducted over XML data from the Web. Our goal is to provide an evaluation of the quality of the results, the performance of the tools and, based on this, guide the users in choosing the appropriate solution for their applications. RÉSUMÉ. Dans le cadre des bases de données temporelles ou celui de l’archivage de documents, la détection de changements est un aspect essentiel de la gestion de versions. Le succès de XML a apporté un regain d’intérêt pour les algorithmes de diff s’appliquant à des structures arborescentes et notamment aux données semi-structurées. Récemment, plusieurs algorithmes et modèles ont été proposés, et nous avons souhaité mener une étude comparative de ces solutions. Nous étudions ici, à partir de leurs définitions formelles et des expériences conduites sur les données XML du Web, les différents algorithmes proposés ainsi que les représentations de changements. Notre objectif est d’évaluer la performance des outils et la qualité des résultats obtenus afin d’aider au choix d’une solution appropriée qui réponde aux besoins spécifiques de chaque application.
US-SOMO HPLC-SAXS module: dealing with capillary fouling and extraction of pure component patterns from poorly resolved SEC-SAXS data

The US-SOMO HPLC-SAXS (high-performance liquid chromatography coupled with small-angle X-ray scattering) module is an advanced tool for the comprehensive analysis of SEC-SAXS (size-exclusion chromatography coupled with SAXS) data. It includes baseline and band-broadening correction routines, and Gaussian decomposition of overlapping skewed peaks into pure components.
A Single E627K Mutation in the PB2 Protein of H9N2 Avian Influenza Virus Increases Virulence by Inducing Higher Glucocorticoids (GCs) Level

While repeated infection of humans and enhanced replication and transmission in mice has attracted more attention to it, the pathogenesis of H9N2 virus was less known in mice. PB2 residue 627 as the virulent determinant of H5N1 virus is associated with systemic infection and impaired TCR activation, but the impact of this position in H9N2 virus on the host immune response has not been evaluated. In this study, we quantified the cellular immune response to infection in the mouse lung and demonstrate that VK627 and rTsE627K infection caused a significant reduction in the numbers of T cells and inflammatory cells (Macrophage, Neutrophils, Dendritic cells) compared to mice infected with rVK627E and TsE627. Further, we discovered (i) a high level of thymocyte apoptosis resulted in impaired T cell development, which led to the reduced amount of mature T cells into lung, and (ii) the reduced inflammatory cells entering into lung was attributed to the diminished levels in pro-inflammatory cytokines and chemokines. Thereafter, we recognized that higher GCs level in plasma induced by VK627 and rTsE627K infection was associated with the increased apoptosis in thymus and the reduced pro-inflammatory cytokines and chemokines levels in lung. These data demonstrated that VK627 and rTsE627K infection contributing to higher GCs level would decrease the magnitude of antiviral response in lung, which may be offered as a novel mechanism of enhanced pathogenicity for H9N2 AIV.
RELIABLE INTEGRITY SECURITY AUDITING USING ISOLATION PRESERVING MODEL FOR MULTI CLOUD ENVIRONMENTS

Cloud computing is provide a dynamically scalable resources provisioned as a service over the webpage. The third-party, on-demand, self-service, pay-per-use, and seamlessly scalable computing resources and services offered by the cloud environment promise to reduce capital as well as operational expenditures for hardware and software. Various distinct architectures are introduced and discussed according to their security and privacy capabilities and prospects. It provides four distinct models in form of abstracted multicloud architectures. These developed multi cloud architectures allow to categorize the available schemes and to analyze them according to their security benefits. An assessment of the different methods 1) Replication of applications, 2) Partition of application System into tiers, 3) Partition of application logic into fragments and 4) Partition of application data into fragments is given in particular. In addition, enabling public audit ability for cloud storage is of critical importance so that users can resort to a third party auditor (TPA) to check the integrity of outsourced data and be worry-free. This paper proposes a secure cloud storage system supporting Isolation-preserving public auditing. It further extends the result to enable the TPA to perform audits for multiple users simultaneously and efficiently.
Induction of apoptosis by a potent caffeic acid derivative, caffeic acid undecyl ester, is mediated by mitochondrial damage in NALM-6 human B cell leukemia cells

Caffeic acid esters have various biological activities, and we previously reported that undecyl caffeate (caffeic acid undecyl ester, CAUE), a new caffeic acid derivative, has strong pharmacological activity. The present study investigated the cytotoxicity of both CAUE and its parent compound, caffeic acid phenethyl ester (CAPE), and characterized the mechanisms by which they induce apoptosis in the human B cell leukemia cell line NALM-6. Treatment with CAUE reduced cell survival in NALM-6 cells but had no significant effect on the survival of normal lymphocytes. When assessing the 50% inhibitory concentration (IC50) for cytotoxicity, CAUE had 10-fold higher activity than CAPE in NALM-6 cells. CAUE treatment resulted in induction of apoptotic features in NALM-6 cells, including cleaved poly (ADP-ribose) polymerase and activated caspase-3. A caspase inhibitor completely blocked CAUE-induced apoptosis. CAUE treatment resulted in a concentration- and time-dependent decrease in both mitochondrial membrane potential and downregulation of Bcl-2 expression. Moreover, CAUE-induced apoptosis was enhanced in the Bcl-2 knockdown condition induced by small interfering RNA. These data suggest that CAUE-induced apoptosis was mediated via an apoptotic intrinsic pathway including mitochondrial damage and was caspase-dependent. These data also suggest that CAUE is a powerful anti-leukemic agent that acts via induction of apoptosis by mitochondrial damage and selective action in leukemia cells.
User Interface Issues in

We discuss a number of issues relating to the development of CAD tools for systolic array design. There are now many constructive techniques that permit the systematic design of such arrays from a class of algo- rithmic specifications. It is important that the users be able to view their specifications as programs in a standard programming language, so that they are able to execute and debug the input. It is also important to provide a simulator for the derived target arrays, and to present ad- equate data representations for displaying the results.
Sensing Estrogen with Electrochemical Impedance Spectroscopy

This study demonstrates the application feasibility of electrochemical impedance spectroscopy (EIS) in measuring estrogen (17β-estradiol) in gas phase. The present biosensor gives a linear response (R 2 = 0.999) for 17β-estradiol vapor concentration from 3.7 ng/L to 3.7 × 10−4 ng/L with a limit of detection (3.7 × 10−4 ng/L). The results show that the fabricated biosensor demonstrates better detection limit of 17β-estradiol in gas phase than the previous report with GC-MS method. This estrogen biosensor has many potential applications for on-site detection of a variety of endocrine disrupting compounds (EDCs) in the gas phase.
Preliminary evidence of anxiolytic effects of the CRF1 receptor antagonist R317573 in the 7.5% CO2 proof-of-concept experimental model of human anxiety

We have validated the use of prolonged inhalation of 7.5% carbon dioxide (CO2) as a human model of anxiety and have shown that drugs from two prototypical classes of anxiolytics, benzodiazepines and a serotonin reuptake inhibitor, attenuate CO2-induced symptoms (Bailey et al., 2007a). Preclinical evidence suggests that drugs acting at the corticotropin-releasing factor (CRF) system may be useful for the treatment of depression, anxiety, and other stress-related disorders (Valdez, 2006), hence we have now examined the effects of a CRF1 receptor antagonist in the 7.5% CO2 model. In a randomized double-blind, placebo-controlled, study in 32 healthy participants we examined the effects of 7 days of treatment with the CRF1 receptor antagonist, R317573, at a dose that shows a favourable safety profile and is comparable with those effective in preclinical models (40 mg). On day 8, eight of the placebo-treated group received lorazepam (LZP) 2 mg as a positive control. All participants underwent 20 min inhalation of 7.5% CO2-enriched air. Subjective reports of peak gas effects were assessed using visual analogue scales and questionnaires. The mean age of participants was 26 years, and 13 were male. The peak effects of CO2 were expressed as a difference from baseline scores obtained while breathing air alone. Compared with placebo (PLAC), both drug groups showed a decrease in all subjective symptoms, total score on the panic symptom inventory (CRF 11 [2.6], PLAC 16.4 [3.1], LZP 2.9 [3.0]) and a generalized anxiety disorder symptom scale (CRF 2.2 [1.5], PLAC 8.2 [2.2], LZP 1.1 [1.5]). We have shown that a drug that acts to inhibit the CRF1 receptor shows efficacy in the 7.5% CO2 model of anxiety in healthy participants.