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Underwater Sensor Networks have been proposed to monitor underwater regions. One of the major problems with underwater communication is the limited power supply of the underwater nodes, leading to costly transmission collisions. In this work, we propose an any-cast transmission scheduling algorithm for Underwater networks. Moreover, we propose a location-based algorithm that schedules transmissions between sensor nodes and sink nodes, where each sensor node is matched with exactly one sink and it sends its data to this sink only to minimize the possibility of collision. This reduces the number of costly re-transmissions and leads to efficient energy consumption. The proposed algorithm is evaluated using NS2 Aqua-Sim simulator, where the experiment results show that the proposed algorithm can provide up to 25% in energy savings, decrease the transmission collisions up to 31%, decrease the average delay up to 16%, and increase the delivery ratio up to 40% compared with a simple greedy algorithm. [ABSTRACT FROM AUTHOR]

After the Three Mile Island Unit 2 accident, regulatory bodies were concerned about the safety measures in design and operation corresponding to the operator's decisions and procedures for handling such off-normal transients. Several recommendations were proposed to analyze transients and accidents, improve and revise emergency operating procedures (EOPs), and conduct functional training. In this work, procedural paths were systematically studied to identify the problems in the diagnosis associated with a pilot-operated relief valve (PORV)-break loss-of-coolant accident (LOCA) as well as to suggest new indications for improving the EOPs. Operational parameters during PORV-break LOCA and pipeline-break small-break LOCA were analyzed using a generic pressurized water reactor simulator to compare and justify the symptoms between these two events. It was found that suggesting further indications mainly in the reactor cooling system and containment symptoms may improve the diagnosis of a PORV-break LOCA from the pipeline-break small-break LOCA. This paper presents a practical approach to evaluating diagnostic procedures to better understand operator recovery actions corresponding to reactor system response in dealing with a PORV-break LOCA. [ABSTRACT FROM AUTHOR]

Several foodborne illness outbreaks caused by Salmonella enterica have been associated with the presence of biofilms, particularly on food contact surfaces. The objectives of the current study were: i) to assess the minimum inhibitory (MIC) and minimum bactericidal concentrations (MBC) of Aleppo pine essential oil (APEO) against 5 S. enterica serotypes and their mixture in Tryptone Soy broth at 37 °C and, ii) investigate the antibiofilm activity of two mixtures of 3 hydrolytic enzymes (5% protease, 2.5% α-amylase, and 0.5% lipase or 10% protease, 5% α-amylase, and 1% lipase at 50 °C for 30 min, and APEO at 1, 2 and 4 MIC at 25 °C for 10, 20 or 30 min) as well as sequential use of enzyme mixtures and APEO against S. enterica on stainless steel and plastic surfaces. The results showed that the MIC and MBC values of APEO against S. enterica strains and their mixture were 250–500 μg/ml and 1000-4000 μg/ml, respectively. In general, the antibiofilm activity of enzymes and APEO increased as the concentration increased and exposure time was extended. The results showed that a 1.8 log CFU/coupon reduction (p < 0.05) was obtained using 4 MIC APEO for 30 min at 25 °C. The enzyme-based mixture containing 10% protease, 5% amylase and 1% lipase at 50 °C for 30 min reduced the microbial load of S. enterica in biofilms on stainless steel and plastic surfaces by 2.1 log CFU/coupon (p < 0.05). However, a sequential two-step treatment based on a mixture of 10% protease, 5% α-amylase, and 1% lipase for 30 min at 45 °C followed by 4 MIC APEO for 30 min at room temperature reduced the S. enterica cells in biofilms on stainless steel by 4.6 log CFU/coupon (p < 0.05). These results indicated that enzyme-APEO treatments may be applied as a natural alternative to overcome biofilm formation by S. enterica in the food industry. • MIC and MBC of APEO against Salmonella were 250–500 and 1000-4000 μg/ml, respectively. • Washing surfaces with 4MIC APEO for 30 min at 25 °C reduced S. enterica biofilm by 1.8 log. • Use of enzyme mixture for 30 min at 50 °C reduced S. enterica biofilm on surfaces by 2.1 log. • Sequential use of enzyme mixture and 4MIC APEO yielded 4.6 log reduction in biofilm. • Enzyme-APEO treatments may be used to overcome biofilm formed by S. enterica. [ABSTRACT FROM AUTHOR]

The traditional statistical approach in synonyms extraction is time-consuming. It is necessary to develop a new model to improve the efficiency and accuracy. This research presents a new model in synonyms extraction called Noun Based Distinctive Verbs (NBDV). During the documents' numerical representation phase, the NBDV replaces the traditional tf-idf weighting scheme with a novel weighting scheme called the Orbit Weighing Scheme (OWS). The OWS links the nouns to their semantic space by examining the singular verbs in each context. The weight of the term is determined by considering the three parameters: Verb_Noun Frequency, Verb_Noun Distribution, and Verb_Noun Distance. The Verb_Noun Distribution parameter is mathematically formulated to depict the semantic relation between the noun and a certain set of verbs that only appear in the context of this noun. We compared the new models with important models in the field, such as the Skip-Gram, the Continuous Bag of Words, and the GloVe model. The NBDV model was tested on both Arabic and English languages, and the results showed 47% recall and 51% precision in the dictionary-based evaluation and 57.5% precision in the human experts' evaluation. Comparing with the synonyms extraction based on tf.idf, the NBDV obtained 11% higher recall and 10% higher precision. Regarding the efficiency, we found that on average, the synonyms extraction of a single noun requires the process of 186 verbs, and in 63% of the runs; the number of singular verbs was less than 200. It is concluded that the developed method is efficient and processes the single run in linear time. [ABSTRACT FROM AUTHOR]

Sensor deployment positions play an important factor in determining target location estimation error performance in sensor networks employing received signal strength indicator measurements. The problem we investigate is as follows: Given a deployment area that has possibly non-uniform estimation error requirements and some initial sensor positions, then how can these sensors be deployed such that requirements are met as best as possible? We propose three variants of a low-complexity distributed strategy that require little information exchange between neighboring sensors. Each sensor locally calculates both the direction and magnitude of movement necessary to reduce the difference between achieved and required estimation errors at points within it sensing radius. The direction of movement is calculated as a weighted combination of these points. The weights can incorporate the error difference, number of sensors covering a point, the distance to a sensor and sensor density. Depending on the parameters chosen, three different weighing methods (namely, the density weighted centroid, error weighted centroid (EWC) and modified EWC) are proposed in this paper. We also provide an analytic derivation of the necessary distance a sensor should move. The proposed strategy is compared against a the RELOCATE algorithm and centralized generic genetic algorithm (GA) relocation method. Simulation results demonstrate that using the distributed strategy can achieve a comparable performance (within 10%) of the GA's performance and significantly outperform that of the RELOCATE. Sensor movement for different k. [ABSTRACT FROM AUTHOR]

Station Black Out (SBO) is an accident situation that refers to the total loss of offsite power, along with the unavailability of onsite power, which results from the failure of all Diesel Generators (DG). Probabilistic Safety Assessment (PSA) spans a number of methods that include modeling of event-trees and simulation of accidents scenarios, aimed to quantify risk and ensure safety in nuclear power plants. PSA also deals with prediction of future accidents and calculation of failure probabilities that has been done in this study. A SBO accident was simulated using a Generic Pressurized Water Reactor (GPWR) simulator from KEYMASTER™. The accident scenario consists of two stages; the first stage belongs to normal SBO, in second stage SBO accident with additional failure of Pilot Operated Relief Valve (PORV) opens and it stuck open has been considered for the pressurizer. A comparison of the two stages was made by plotting variables on the same graph. The research has been carried out to analyze the hot and cold leg temperatures, Steam Generator (SG) pressure, SG Narrow Range (NR) level, SG water-level-percentage (PCT), Pressurizer pressure, Fuel Temperature, and containment pressure. Simulation results suggest that failure in closing PORV has negligible impact on hot and cold leg temperatures, results in an overall less pressure in SGs, but higher pressure in the pressurizer. Additionally, containment pressure did not exceed the maximum approved pressure of 8.7 kg/cm 2 , but was approaching the Advanced Pressurized Water Reactor’s (APR-1400) design pressure of 4.218 kg/cm 2 . Finally, nuclear fuel temperature exceeded Probabilistic Risk Assessment (PRA) limit of 726.7 °C for both scenarios. The research results will provide help in future for better understanding of accidents in APR-1400 reactors. [ABSTRACT FROM AUTHOR]

The transformation of the food chain due to technological advances has had significant implications in regard to food safety. A noteworthy trend in this evolution relates to the emergence of new or previously unseen pathogens within products, thereby altering the landscape of foodborne illness epidemiology. The escalating frequency of these events underscores the need for a comprehensive re-evaluation of preventive strategies. The occurrence of novel species of bacteria, viruses, parasites, and unusual biotoxins from unexpected sources has challenged the previous limits that had been set to prevent foodborne illness outbreaks. The repercussions, ranging from detrimental effects on public health to economic burden, are influenced by a myriad of factors affecting the evolution of foodborne pathogens and emerging ailments. Among these factors are shifts in population demographics and behaviors, especially dietary patterns, as well as climate extremes, advances in more precise pathogen detection, microbial adaptation, evolving agricultural practices, and transformative changes within the food industry. This review critically examines the impact of technological metamorphosis along the food chain, encompassing production, processing, handling, packaging, storage, transportation, and industry demographics on the dynamics influencing the emergence of foodborne pathogens. Additionally, potential solutions to mitigate and manage this escalating issue are proposed. [ABSTRACT FROM AUTHOR]

Gain and offset represent two important measures to determine the accuracy of a comparator. Thus, analysis on these parameters is very important as they offer designers better understanding of the circuit and allow exploring trade-offs during design. In this paper, two methods were presented to derive a set of design equations that describe the gain, sensitivity, offset, and systematic mismatches observed in typical comparator circuits. A three-stage, fast complementary metal-oxide semiconductor (CMOS) comparator structure is analysed and simulated in order to validate the proposed methods. A 0.13 μm CMOS technology is used for simulations with 1.5 V supply voltage. Bisection theorem was used for gain and sensitivity analysis. Simulation results show that high gain improvement can be possible by using the design equations. The input offset voltage, due to mismatch in the width of the metal oxide semiconductor field-effect transistors (MOSFET) (W) and mismatches in the threshold voltages of the N and P type MOSFETs(VTHN, VTHP), is analysed using a proposed balanced method. The same comparator structure is used for the input offset voltage analysis. Simulations show that an offset improvement can be achieved following the design equations found through the proposed method. [ABSTRACT FROM PUBLISHER]

Crohn's disease (CD) is an inflammatory bowel disease (IBD) that can affect the whole gastrointestinal tract. Theileocolonic variant of CD, an inflammation of both the ileum and the large intestine, accounts for up to 50% of the cases with CD, whereas Crohn's ileitis affecting the ileum is diagnosed in about 30%. Crohn's colitis, which is confined to the large intestine and accounts for the remaining 20%, is difficult to distinguish from the large bowel inflammation seen in patients with ulcerative colitis (UC). The pathogenesis of CD is not yet completely understood. Autoimmunity is one factor that can partake in the triggering or modulation of inflammatory processes in IBD. The major zymogen-granule membrane glycoprotein 2 (GP2) has been recently identified as a major autoantigenic target in CD. Interestingly, GP2 is mainly expressed in the pancreas and has also been demonstrated to be a membrane-anchored receptor of microfold cells in the follicle-associated epithelium. Remarkably, GP2 is overexpressed at the site of CD inflammation in contrast to the one in UC. By utilizing novel enzyme-linked immunosorbent assays for the detection of GP2-specific IgA and IgG, the loss of tolerance to GP2 has been associated with a specific clinical phenotype in CD, in particular with the ileocolonic location of the disease. [ABSTRACT FROM AUTHOR]