Categories as paradigms for comparative cognition

Forming categories is a basic cognitive operation allowing animals to attain concepts, i.e. to represent various classes of objects, natural or artificial, physical or social. Categories can also be formed about the relations holding among these objects, notably similarity and identity. Some of the cognitive processes involved in categorisation will be enumerated. Also, special reference will be made to a much neglected area of research, that of social representations. Here, animals conceive the natural class of their conspecifics as well as the relationships established between them in groups. Two types of social categories were mentioned: (1) intraspecies recognition including recognition of individual conspecifics; and (2) representation of dominance hierarchies and of their transitivity in linear orders

Impact of Climate Change on Plant Diseases and IPM Strategies

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases. Climate change influences the occurrence, prevalence, and severity of plant diseases. Projected atmospheric and climate change will thus affect the interaction between crops and pathogens in multiple ways. This will also affect disease management with regard to timing, preference, and efficacy of chemical, physical, and biological measures of control and their utilization within integrated pest management (IPM) strategies. Prediction of future requirements in disease management is of great interest for agro-industries, extension services, and practical farmers. A comprehensive analysis of potential climate change effects on disease control is difficult because current knowledge is limited and fragmented and due to the complexity of future risks for plant disease management, particularly if new crops are introduced in an area. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs. All these efforts and integrations will produce effective crop protection strategies using novel technologies as appropriate tools to adapt to altered climatic conditions

A Review of Barrett\u27s Esophagus

Barrett’s Esophagus is a premalignant condition that predisposes patients to the development of esophageal adenocarcinoma. •Esophageal adenocarcinoma dramatically rising over several decades; survival rates of less than 17% in a five year period. •Management and treatment continues to evolve: use of radio-frequency ablation effective to treat low grade dysplasia •Studies of risk factors and treatment options explored: Efficacy and durability of endoscopic radiofrequency ablation for treatment of low grade dysplasia as option for metaplasia eradication –Gastrointestinal pathologist expert reviews ensure identification of dysplasia prior to treatment –Appropriate endoscopic surveillance intervals –Gastroenterology guidelines for screening and surveillance for long term management –Lifelong endoscopic surveillance individualized to monitor for recurrence of metaplasiahttps://commons.und.edu/pas-grad-posters/1090/thumbnail.jp

Control of charcoal rot disease of okra plants using certain chemical plant resistance inducers

This study was aimed to determine the efficacy of certain chemical inducers on incidence of charcoal rot disease caused by Macrophomina phaseolina (Tassi) in okra okra (Abelmoschus esculentus (L.) under greenhouse and field conditions. Pathogenicity of 12 isolates of Macrophomina phaseolina was carried out on okra under greenhouse conditions. These isolates capable to infect okra plants caused charcoal rot on the basil stem with various degrees of diseases severity. Isolate No. 3 caused the highest charcoal rot severity (70.15%) followed by isolate No. 6 (58.69%). The positive effect of four inducer chemicals, i.e salicylic and ascorbic acids at concentrations 50, 100, 200 ppm; Benzothiadiazole, Bion at 200, 400, 800 ppm and humic acid at 500, 1000, 2000 ppm  on the induction of systemic resistance in okra against charcoal rot disease and its effect on growth parameters and green fruit yield components were studied. In vitro, all tested chemical inducers able to suppress growth of M. phaseolina.  The highest decrease in linear growth of M. phaseolina was noticed with Bion at concentration 800 ppm (66.96%). Under greenhouse conditions, all the tested chemical inducers significantly decreased charcoal rot severity at all concentrations compared with control.  The reduction of charcoal rot in okra was enhanced by increasing chemical inducers concentration. Ascorbic acid was the most effective chemical inducers as they greatly retarded charcoal rot caused by M. phaseolina especially at the higher concentration (200 ppm). While, salicylic acid at 50 ppm recorded the lowest protection of charcoal rot severity. Under field conditions, the percentages of charcoal rot severity were significantly reduced due to soaking the seeds before sowing in any of chemical inducers in both trial seasons (2013 and 2014). The most effective inducer was humic acid  at 2000 ppm (84.44 and 85.65% reduction of charcoal rot severity), followed by ascorbic acid at 200 ppm (79.79 and 79.28% reduction of charcoal rot severity) in the first and the second growing seasons, respectively. Also, these treatments significantly increased growth parameters i.e. plant height and number of branches plant-1 as well as, green fruit yield parameters i.e. number of green fruit plant-1; weight of green fruit plant-1 (gm); and total green fruits (ton/acre). Generally, humic acid gave the best results in all growth and green fruit yield parameters under field conditions especially at higher concentration (2000 ppm)

An experimental model of aggressive dominance in Xiphophorus helleri (Pisces, Poeciliidae)

An experimental model was constructed using seven postulates derived from the experimental results of Zayan (1974, 1975a,b,c, 1976). The model specifies the relative importance of several asymmetries in predicting aggressive dominance in Xiphophorus helleri. These asymmetries concern differences between opponents with respect to: prior residence in the tested area (versus intrusion); immediate social experiences of dominance or submission; social isolation; individual familiarity and recognition. The predictions of the general model were checked experimentally and confirmed; a multiple orthogonal regression accounted for about 97% of the variance in our experimental results. The basic experimental results serving as postulates were confirmed and could be generalized; a new synthetic and predictive model was formulated concerning the determinants of aggressive dominance in Xiphophorus males. The following empirical generalisations were either confirmed or disclosed by the present study of opponents showing very small size differences: G1: The dominance propensity is significantly higher in resident individuals than in intruders. G2: The dominance propensity is significantly higher in previously dominant individuals than in previously submissive ones. G2 holds true for dyadic encounters between acquainted as well as between unacquainted pairmembers. G3: The dominance propensity is similar in previously dominant individuals and in previously isolated ones. G4: The dominance propensity is significantly higher in previously isolated individuals than in previously submissive ones. G5: G2 overrides G1 in both acquainted and unacquainted opponents. In general it was found that recent agonistic experience (victory or defeat) was much more important to explain future issues than familiarity with the meeting place. However, negative effects of recent defeat appeared diminished when the prior loser encountered on familiar ground a prior dominant or isolated but unacquainted opponent

Evaluation of antimicrobial activity of andrographis paniculata extract against staphylococcus aureus / Zayan Nabilah Rasyidah Abd. Razak

A.paniculata leaves are known to have antimicrobial activities and it is widely used as traditional medicine worldwide. This study investigated the antimicrobial activities of methanolic extract of Saureus (ATCC 25923) by determining the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC), time-kill assay and the effects of A.paniculata extract on Saureus in SDSPAGE analysis. Several concentration of the A.paniculata extracts were used to determine MIC value and the lowest concentration that can inhibit growth of Saureus was further tested to obtain MBC value. Time-kill assay was performed in 24 hours to determine the incubation period needed for A.paniculata extract to completely kill Saureus. The treated samples (A.paniculata extract and Saureus) and untreated samples (Saureus only) were compared in terms of appearance of cytoplasmic protein bands to determine the effect of treatment. A.paniculata extract showed high antimicrobial activity against Saureus with MIC and MBC value was O.06mglml. The MIC value was able to completely killed Saureus in 24 hours incubation time. Lipase (76 kDa) was identified on SDS-PAGE analysis which was inhibited when treated with A.paniculata extract. The observation suggests that a possible mechanism by which methanolic extract of A.paniculata inhibits Saureus by lowering production of an important protein, lipase. Future work which involves proteomics study on the effects of A.paniculata against Saureus should be pursued

Effects of Using Examples on Structural Model Comprehension: A Controlled Experiment

We present a controlled experiment for the empirical evaluation of Example-Driven Modeling (EDM), an approach that systematically uses examples for model comprehension and domain knowledge transfer. We conducted the experiment with 26 graduate and undergraduate students from electrical and computer engineering (ECE), computer science (CS), and software engineering (SE) programs at the University of Waterloo. The experiment involves a domain model, with a UML class diagram representing the domain abstractions and UML object diagrams representing examples of using these abstractions. The goal is to provide empirical evidence of the effects of suitable examples on model comprehension, compared to having model abstractions only, by having the participants perform model comprehension tasks. Our results show that EDM is superior to having model abstractions only, with an improvement of (+39%) for diagram completeness, (+30%) for study questions completeness, (+71%) for efficiency, and a reduction of (-80%) for the number of mistakes. We provide qualitative results showing that participants receiving model abstractions augmented with examples experienced lower perceived difficulty in performing the comprehension tasks, higher perceived confidence in their tasks' solutions, and asked fewer clarifying domain questions (a reduction of 90%). We also present participants' feedback regarding the usefulness of the provided examples, the number of examples, the types of examples, and the use of partial examples

Extended WIFI network design model for ubiquitous emergency events

Telecommunication is the exchange of information and data over significant distance by electronic means. During extreme events such as natural disasters and urgent events it becomes more and more important to preserve the communication devices and infrastructure to exchange information between rescue teams and persons in damaged zone based on their area. When extreme event happens, many communication scenarios can be considered. We focus on a the case of destruction of traditional communication networks during an emergency event such as natural disasters in which it is important to find an alternative network architecture to prevent the death and injury of thousands of people. The rescue teams are unable to locate and communicate with victims on right time. This work presents network architectural design model to extend the range of WIFI networks and help people access to Internet or get rescue when the damage affects the most existing telecommunication networks. This model is validated by analyzing two communication scenarios

Survey of health care context models : prototyping of healthcare context framework

HealthCare system is considered a key element in ubiquitous computing, which means health care services are recommended at any time and at any places to monitor patients based on their context. This study aims to define a simple framework that could be guidelines when you start thinking about building a health context-awareness system in ubiquitous environment. This paper starts by defining the concept of context and then presenting a comprehensive list of context models. Outcome of the work of this research is an ontology healthcare model based on current context of patient which makes monitoring process more accurate. This study includes an Android application in order to prove the concept of this hypothesis

Études des systèmes de communications sans-fil dans un environnement rural difficile

Les systèmes de communication sans fil, ayant de nombreux avantages pour les zones rurales, peuvent aider la population à bien s'y établir au lieu de déménager vers les centres urbains, accentuant ainsi les problèmes d’embouteillage, de pollution et d’habitation. Pour une planification et un déploiement efficace de ces systèmes, l'atténuation du signal radio et la réussite des liens d’accès doivent être envisagées. Ce travail s’intéresse à la provision d’accès Internet sans fil dans le contexte rural canadien caractérisé par sa végétation dense et ses variations climatiques extrêmes vu que les solutions existantes sont plus concentrées sur les zones urbaines. Pour cela, nous étudions plusieurs cas d’environnements difficiles affectant les performances des systèmes de communication. Ensuite, nous comparons les systèmes de communication sans fil les plus connus. Le réseau sans fil fixe utilisant le Wi-Fi ayant l’option de longue portée est choisi pour fournir les communications aux zones rurales. De plus, nous évaluons l'atténuation du signal radio, car les modèles existants sont conçus, en majorité, pour les technologies mobiles en zones urbaines. Puis, nous concevons un nouveau modèle empirique pour les pertes de propagation. Des approches utilisant l’apprentissage automatique sont ensuite proposées, afin de prédire le succès des liens sans fil, d’optimiser le choix des points d'accès et d’établir les limites de validité des paramètres des liens sans fil fiables. Les solutions proposées font preuve de précision (jusqu’à 94 % et 8 dB RMSE) et de simplicité, tout en considérant une multitude de paramètres difficiles à prendre en compte tous ensemble avec les solutions classiques existantes. Les approches proposées requièrent des données fiables qui sont généralement difficiles à acquérir. Dans notre cas, les données de DIGICOM, un fournisseur Internet sans fil en zone rurale canadien, sont utilisées. Wireless communication systems have many advantages for rural areas, as they can help people settle comfortably and conveniently in these regions instead of relocating to urban centers causing various overcrowding, habitation, and pollution problems. For effective planning and deployment of these technologies, the attenuation of the radio signal and the success of radio links must be precisely predicted. This work examines the provision of wireless internet access in the Canadian rural context, characterized by its dense vegetation and its extreme climatic variations, since existing solutions are more focused on urban areas. Hence, we study several cases of difficult environments affecting the performances of communication systems. Then, we compare the best-known wireless communication systems. The fixed wireless network using Wi-Fi, having the long-range option, is chosen to provide wireless access to rural areas. Moreover, we evaluate the attenuation of the radio signal, since the existing path loss models are generally designed for mobile technologies in urban areas. Then, we design a new path loss empirical model. Several approaches are then proposed by using machine learning to predict the success of wireless links, optimize the choice of access points and establish the validity limits for the pertinent parameters of reliable wireless connections. The proposed solutions are characterized by their accuracy (up to 94% and 8 dB RMSE) and simplicity while considering a wide range of parameters that are difficult to consider all together with conventional solutions. These approaches require reliable data, which is generally difficult to acquire. In our case, the dataset from DIGICOM, a rural Canadian wireless internet service provider, is used