Isolation and identification of some bacterial isolates from soil contaminated with crude oil and Testing Their Effectiveness

عزلت سلالات بكتيرية من التربة الملوثة بالنفط، في عام 2018، تم توصيف هذه العزلات، وذلك بهدف معرفة قدرة هذه العزلات على معالجة التربة الملوثة بالنفط. تمت قراءة تغير لون الوسط المضاف إليه العزلات بطريقة Pacto Bushnell Hans. كما درس التغيير في طبيعة المواد المكونة للنفط بواسطة كروماتوجرافيا الغاز للعزلات الأكثر فاعلية. أظهرت العزلات البكتيرية التسعة المعزولة درجات مختلفة من التغير اللوني، وتفوقت العزلات (Pseudomonas، Bacillus، Micrococcus) على باقي العزلات بكمية تغير اللون حيث بلغت النسبة المئوية للتغير اللوني  (78، 78، 77) ٪ على التوالي، مقارنة مع الشاهد، وأظهرت العزلات الثلاثة مجتمعةً أفضل تغيير للون بلغ  90.7 ٪ مقارنة بالشاهد، وأظهرت نتائج فصل المواد عن طريق كروماتوغرافيا الغاز أن هناك تغيرات في طبيعة المواد الموجودة في النفط الخام (الشاهد بدون عزلات) مقارنة بتلك الموجودة في النفط الخام بدون إضافة عزلات. كما أعطت العزلات الثلاث مجتمعة أعلى نسبة تغير في تركيب المواد الداخلة في النفط الخام مقارنة بالعزلات الثلاثة المفردة. مما يؤكد فعالية كل عزلة على حدة على تفكيك النفط الخام وقدرة هذه العزلات مع بعضها(متأزرة) على تفكيك النفط الخام.Bacterial strains were isolated from oil-contaminated soil, in 2018, these isolates were identified, and with the aim of finding out the ability of these isolates to degrede the oil compounds, the color change of medium which added to it isolates was read by the method of Pacto Bushnell Hans. Then the change in the petroleum compounds was read by gas chromatography, for the most effective isolates. The nine isolated bacterial showed different degrees of color change, and the isolates (Pseudomonas, Bacillus, Micrococcus) outperformed the color change amount (78, 78, 77) %, respectively, compared to the control, and the three isolates together showed the best color change of 90.7. % Compared to the control, and the results of separating materials by means of gas chromatography showed that there were changes in the nature of the materials present in the crude oil (control: without isolates) compared to those present in the crude oil That disintegrated by means of the three single isolates. The three isolates together showed a greater ability to change the nature of the materials present in the crude oil. Which confirms the effectiveness of each isolate separately and the ability of these isolates together to degerde crude oil

A distributed algorithm for semantic collectors election in wireless sensors networks

Semantic clustering is a recent technique for saving energy in wireless sensor networks. Its mechanism of action consists in dividing the network into groups (clusters) formed by semantically related nodes and at least one semantic collector, which acts as a bridge between its internal nodes and the sink node. Since semantic collector nodes need to perform more tasks than normal nodes, they deplete their energy budget faster, so it is necessary to use efficient mechanisms for electing semantic collectors to prolong the network lifetime. Our hypothesis is that an effective choice of semantic collectors allows a longer network lifetime. To test it, we start from a previous work of the authors of this article and we propose an algorithm for electing semantic collectors in a distributed way based on a fuzzy inference engine. The inputs of the inference engine are the residual energy of nodes and their received signal strength indicator (RSSI). Simulation results confirm our hypothesis, since the algorithm provides (i) an improvement of 17.4% in relation to another proposal of the related literature, and (ii) a gain of 68.8% over the time life of the network’s original work.Keywords: Wireless Sensors Networks, Semantic Cluster, Semantic Collector Election

Monitoramento de padrÃes tÃrmicos em colmeias de abelhas via redes de sensores sem fio

Swarming is the mass exodus of bees in a hive, whose most common causes are lack of food, stress, variations of humidity and especially high temperatures. Among the types of swarming, one in which the complete abandonment of the hive occurs has brought great harm to Brazilian beekeepers, particularly the Northeast. In the Northeast region, of great importance for the Brazilian beekeeping, and where high temperatures are common in most of the year, a large number of hives is lost due to the swarming through abandonment. In an attempt to mitigate this problem, we propose a proactive monitoring hives via a network of wireless sensors capable of identifying atypical heating indicative of a preswarming condition. By means of a sampling pattern obtained from the cyclical daily temperatures, we developed a predictive algorithm based on pattern recognition techniques capable of detecting the increase of temperature inside the beehive (microclimate) responsible for the typical stress bees culminating in swarming. Such a mechanism is also able to recognize and avoid sending redundant information over the network in order to reduce radio communication, thereby reducing costs of data transmission and energy.EnxameaÃÃo à a saÃda em massa das abelhas de uma colmeia, cujas causas mais comuns sÃo a falta de alimentos, estresse, variaÃÃes da umidade do ar e principalmente as altas temperaturas. Dentre os tipos de enxameaÃÃo, aquela em que ocorre o abandono completo da colmeia tem trazido grandes prejuÃzos aos apicultores brasileiros, particularmente aos nordestinos. Na regiÃo Nordeste, de grande importÃncia para a produÃÃo apÃcola brasileira e onde altas temperaturas sÃo comuns na maior parte do ano, um grande nÃmero de colmeias à perdido em funÃÃo da enxameaÃÃo por abandono. Na tentativa de mitigar este problema, propomos aqui um monitoramento proativo de colmeias via uma rede de sensores sem fio capaz de identificar o aquecimento atÃpico indicativo de uma condiÃÃo prÃ-enxameatÃria. Por meio de um padrÃo de coletas obtido a partir do comportamento cÃclico de temperaturas diÃrias, elaboramos um algoritmo preditivo, baseado em tÃcnicas de reconhecimento de padrÃes, capaz de detectar o aumento da temperatura no interior da colmeia (microclima) responsÃvel pelo estresse tÃpico das abelhas que culmina na enxameaÃÃo. Tal mecanismo tambÃm à capaz de reconhecer e evitar o envio de informaÃÃes redundantes pela rede de modo a diminuir a comunicaÃÃo via rÃdio, consequentemente reduzindo custos de transmissÃo de dados e energia

Occurrence of <I>Verticillium dahliae</I> defoliating pathotypes on olive trees in Tunisia

Olive trees (cv. Chemlali) showing typical symptoms of wilt and dieback were collected from several areas in Tunisia. Visual diagnostic, isolation and microscopic observations identified the causal pathogen as Verticillium dahliae. The pathotype was determined using specific primers pairs for D (defoliating) and ND (non-defolitating) . Artificial inoculation of olive plants resulted in typical wilting with defoliation, proving that the isolate tested was pathogenic on olive, and this isolate belongs to the D pathotype. This is the first report of the defoliating pathotype causing wilting disease on olive in Tunisia