Study Resistance of (C. tropicalis and C. glabrata) to Some Heavy Metals and Oil Compounds Laboratory

Present study showed that  the isolated of yeast (C. tropicalis and C. glabrata) were resistance for growth in different concentrations of heavy metals (lead, cobalt, cadmium).So too that isolates of  yeast are  resistance  for growth in different concentrations of  oil compacts ( phenol , naphthalene, biphenyl). These are results showed of capacity of some species of yeasts on growth in different concentrations from environment pollutants .The last the yeasts are ability of bioremediation of pollutants. Keywords: Yeasts , heavy metals , oil compact

UAV-Empowered Disaster-Resilient Edge Architecture for Delay-Sensitive Communication

The fifth-generation (5G) communication systems will enable enhanced mobile broadband, ultra-reliable low latency, and massive connectivity services. The broadband and low-latency services are indispensable to public safety (PS) communication during natural or man-made disasters. Recently, the third generation partnership project long term evolution (3GPPLTE) has emerged as a promising candidate to enable broadband PS communications. In this article, first we present six major PS-LTE enabling services and the current status of PS-LTE in 3GPP releases. Then, we discuss the spectrum bands allocated for PS-LTE in major countries by international telecommunication union (ITU). Finally, we propose a disaster resilient three-layered architecture for PS-LTE (DR-PSLTE). This architecture consists of a software-defined network (SDN) layer to provide centralized control, an unmanned air vehicle (UAV) cloudlet layer to facilitate edge computing or to enable emergency communication link, and a radio access layer. The proposed architecture is flexible and combines the benefits of SDNs and edge computing to efficiently meet the delay requirements of various PS-LTE services. Numerical results verified that under the proposed DR-PSLTE architecture, delay is reduced by 20% as compared with the conventional centralized computing architecture.Comment: 9,

Two Level Disambiguation Model for Query Translation

Selection of the most suitable translation among all translation candidates returned by bilingual dictionary has always been quiet challenging task for any cross language query translation. Researchers have frequently tried to use word co-occurrence statistics to determine the most probable translation for user query. Algorithms using such statistics have certain shortcomings, which are focused in this paper. We propose a novel method for ambiguity resolution, named ‘two level disambiguation model’. At first level disambiguation, the model properly weighs the importance of translation alternatives of query terms obtained from the dictionary. The importance factor measures the probability of a translation candidate of being selected as the final translation of a query term. This removes the problem of taking binary decision for translation candidates. At second level disambiguation, the model targets the user query as a single concept and deduces the translation of all query terms simultaneously, taking into account the weights of translation alternatives also. This is contrary to previous researches which select translation for each word in source language query independently. The experimental result with English-Hindi cross language information retrieval shows that the proposed two level disambiguation model achieved 79.53% and 83.50% of monolingual translation and 21.11% and 17.36% improvement compared to greedy disambiguation strategies in terms of MAP for short and long queries respectively

Interaction Strength of Hanger and Horizontal Steel Reinforcement of Dapped End Beams

The dapped end beam members have a special end with low depth at the support area, which results in a weak area against shear stresses. Classical structural analysis doesn’t capture the precise steel reinforcement interaction at the dapped zone area. The main objectives of this study are to investigate the strength of the dapped end area and to analyze stresses in the steel reinforcement to evaluate the shear failure mechanism at the re-entrant corner. The experimental tests conducted on RC beam samples, in addition to the numerical simulation of these samples by a finite element program, have been compared with a mathematical model. The experimental program highlighted the strains in the steel reinforcement in the dapped region to calculate the magnitude of the stresses in the steel reinforcement. In the experimental program, six dapped beams were fabricated with a length of 3 m, a width of 150 mm, and a depth of 300 mm. The notched end has a 150-mm depth and 150-mm height. These beams were loaded by a concentrated load near support to investigate the shear strength capacity. From the results for steel reinforcement strain, it is found that hanger and horizontal steel reinforcements interact to provide dapped end shear strength. The study proposes a new approach to computing shear strength capacity at the re-entrant corner by adding the contributions of the horizontal and hanger steel reinforcement using an appropriate proportion strain factor. This method revealed greater carrying capacity for the dapped end beam compared with other common structural methods. The results of the numerical analysis were done by the ABAQUS finite element program, showing the same behavior as the experimental work. This study proved the common contribution of hanger and horizontal re-entrant corner steel reinforcement and proposed a new formula to determine the updated nominal shear strength. Doi: 10.28991/CEJ-2023-09-12-015 Full Text: PD

Few-layer graphene as an ‘active’ conductive additive for flexible aqueous supercapacitor electrodes

We demonstrate that few layer graphene (FLG), formed by high-shear exfoliation into an aqueous suspension, can be successfully employed as an ‘active’ conductive additive in flexible activated carbon-based aqueous electric double layer capacitor (supercapacitor) electrodes if introduced by a novel ‘vacuum infiltration’ technique. The effectiveness of the FLG can be optimised by tailoring its size distribution and loading. It is found that best performance is achieved using FLG with the broadest size distribution and, moreover, that the larger size distribution is effective over the broadest range of loading. With optimum size distribution and loading, FLG is shown to outperform a commercial carbon black conductive additive (Timcal C65). Electrodes containing 8 wt% infiltrated FLG have an equivalent series resistance (ESR) of 1 . 3 ± 0 . 4 Ω , and a specific capacitance of 142 . 3 ± 0 . 1 F g−1 over a voltage window of 1.2 V, compared with an ESR of 3 ± 1 Ω and a specific capacitance of 96 . 81 ± 0 . 02 F g−1 for equivalent electrodes produced with an optimal loading of carbon black additive. As a result, the specific energy density of electric double layer capacitors (EDLCs) produced with a vacuum infused FLG additive is demonstrated to be an average of 47 ± 3 % superior to those containing carbon black measured at similar power densities. In contrast to vacuum infusion, direct mixing of FLG suspension into the electrodes is found to be ineffective, resulting in limited improvement relative to electrodes without conductive additive, the reasons for which are discussed

Assess the performance of the diagnosis ways of diabetic retinopathy

Considered the diagnosis of diseases using image processing is one of the most important areas of image processing techniques used in the medical field, where is the digital data in the field of ophthalmology focus of researchers for automatic detection of some important diseases such as diabetic retinopathy (DR). And is defined as damage to the retina of the eye comes as serious complications and on the human body complications resulting from diabetes in the long term and is considered one of the most important causes of blindness in the world and cause serious damage to the retina. The research aims to Assess the performance of some of the methods used in the diagnosis of diabetic retinopathy by revealing one of the most important accompanying pests him in the retina of the eye and is the exudates and through diagnosed in images digital fundus through image processing techniques where this detection process contributes in helping to early detection

Joint optimization of Age of Information and Energy Efficiency in IoT Networks

Age of information (AoI) refers to the freshness of data generated by a status-update system. It is a crucial metric in networks such as Internet of things (IoT), specially when the underlying application demands fresh update. In environmental monitoring and smart agriculture, apart from the importance of AoI, energy efficiency (EE) becomes inevitable owing to network longevity. This paper studies an IoT network where the end devices transfer their information to a central gateway residing on a moving platform such as a tractor, which collects information from a large number of sensors in an agri-field. An optimal trajectory of the mobile reader is proposed using a modified nearest neighbor algorithm to gather the information from randomly distributed sensors. A clustering algorithm is also used to cluster the data in such a way that the overall EE of the network is maximized keeping a desired AoI and outage probability