63 research outputs found
Sentiment Analysis System for Mapping Hate Speech Against Women in Social Media using GIS System
This study aims to map hate speech against women in the Middle East using a Geographic Information System GIS and sentiment analysis with the goal of identifying patterns The hate speech terms that were utilized in the research were gathered from more than 3600 women in the study region according to the dat
MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions
Background
The alignment of multiple protein sequences is one of the most commonly performed tasks in bioinformatics. In spite of considerable research and efforts that have been recently deployed for improving the performance of multiple sequence alignment (MSA) algorithms, finding a highly accurate alignment between multiple protein sequences is still a challenging problem.
Results
We propose a novel and efficient algorithm called, MSAIndelFR, for multiple sequence alignment using the information on the predicted locations of IndelFRs and the computed average log–loss values obtained from IndelFR predictors, each of which is designed for a different protein fold. We demonstrate that the introduction of a new variable gap penalty function based on the predicted locations of the IndelFRs and the computed average log–loss values into the proposed algorithm substantially improves the protein alignment accuracy. This is illustrated by evaluating the performance of the algorithm in aligning sequences belonging to the protein folds for which the IndelFR predictors already exist and by using the reference alignments of the four popular benchmarks, BAliBASE 3.0, OXBENCH, PREFAB 4.0, and SABRE (SABmark 1.65).
Conclusions
We have proposed a novel and efficient algorithm, the MSAIndelFR algorithm, for multiple protein sequence alignment incorporating a new variable gap penalty function. It is shown that the performance of the proposed algorithm is superior to that of the most–widely used alignment algorithms, Clustal W2, Clustal Omega, Kalign2, MSAProbs, MAFFT, MUSCLE, ProbCons and Probalign, in terms of both the sum–of–pairs and total column metrics
Moisture susceptibility of high and low compaction dry process crumb rubber modified asphalt mixtures
The field performance of dry process crumb rubber-modified (CRM) asphalt mixtures has been reported to be inconsistent with stripping and premature cracking on the surfacing. One of the concerns is that, because achieving field compaction of CRM material is difficult due to the inherent resilient nature of the rubber particle, nonuniform field compaction may lead to a deficient bond between rubber and bitumen. To assess the influence of compaction, a series of CRM and control mixtures was produced and compacted at two levels: 4% (low, optimum laboratory compaction) and 8% (high, field experience) air void content. The long-term durability, in regard to moisture susceptibility of the mixtures, was assessed by conducting repeated moisture conditioning cycles. Mechanical properties (stiffness, fatigue, and resistance to permanent deformation) were determined in the Nottingham Asphalt Tester. Results indicated that compared with conventional mixtures, the CRM mixtures, regardless of compaction effort, are more susceptible to moisture with the degree of susceptibility primarily depending on the amount of rubber in the mixture, rather than the difference in compaction. This behavior is different from that of conventional mixtures in which, as expected, poorly compacted mixtures were found to be more susceptible to moisture than were well-compacted mixtures
Positioning film tourism at the top of mental awareness: some explanatory insights from the Jordanian case.
The production of film-induced tourism has lately gained extensive support in global tourism literature and among destination promotions alike, with limited attention given to movie locations in developing countries, including reality TV programmes sets. This paper gives witness to the effect of motion pictures including Lawrence of Arabia, Indiana Jones and the Last Crusade, and The Martian movie, upon tourist visitation selection. For this purpose a conceptual 3 P’s model was developed to explore the extent and influence to position film locations in the top of mind awareness for potential tourists. This integration was conducted using a total of 35 interviews with tourists as respondents from different nationalities during their trip to a Jordanian destination, and by referring to each film’s blog site. The data received was from a content analysis from the interviews, and the frequency results indicated that film tourism is a secondary motive tourism experience due to the missing of the idea of identifying film location in narratives indicative in understood language, short time shooting of scenes, and the run of productions of films. The results do not disregard the idea that a strong perceived awareness has been achieved by watching reality TV shows as types of documentary series rather than cinema movies. Grounded on our empirical analysis, this paper proposes a research agenda that integrates the real socio-cultural attributes of the destination to film tourism production
Modeling and optimization of biogas production from a waste digester using artificial neural network and genetic algorithm
Artificial neural networks (ANNs) and genetic algorithms (GA) are considered among the latest tools that are used to solve complicated problems that cannot be solved by conventional solutions. The present study utilizes the ANN and GA as tools for simulating and optimizing of biogas production process from the digester of Russaifah biogas plant in Jordan. Operational data of the plant for a period of 177 days were collected and employed in the analysis. The study considered the effect of digester operational parameters, such as temperature (T), total solids (TS), total volatile solids (TVS), and pH on the biogas yield. A multi-layer ANN model with two hidden layers was trained to simulate the digester operation and to predict the methane production. The performance of the ANN model is verified and demonstrated the effectiveness of the model to predict the methane production accurately with correlation coefficient of 0.87.
The developed ANN model was used with genetic algorithm to optimize the methane size. The optimal amount of methane was converged to be 77%, which is greater than the maximum value obtained from the plant records of 70.1%. The operational conditions that resulted in the optimal methane production were determined as temperature at 36 °C, TS 6.6%, TVS 52.8% and pH 6.4
Intelligent traffic light flow control system using wireless sensors networks
Vehicular traffic is continuously increasing around the world, especially in large urban areas. The resulting congestion has become a major concern to transportation specialists and decision makers. The existing methods for traffic management, surveillance and control are not adequately efficient in terms of performance, cost, maintenance, and support. In this paper, the design of a system that utilizes and efficiently manages traffic light controllers is presented. In particular, we present an adaptive traffic control system based on a new traffic infrastructure using Wireless Sensor Network (WSN) and using new techniques for controlling the traffic flow sequences. These techniques are dynamically adaptive to traffic conditions on both single and multiple intersections. A WSN is used as a tool to instrument and control traffic signals roadways, while an intelligent traffic controller is developed to control the operation of the traffic infrastructure supported by the WSN. The controller embodies traffic system communication algorithm (TSCA) and the traffic signals time manipulation algorithm (TSTMA). Both algorithms are able to provide the system with adaptive and efficient traffic estimation represented by the dynamic change in the traffic signals ' flow sequence and traffic variation. Simulation results show the efficiency of the proposed scheme in solving traffic congestion in terms of the average waiting time and average queue length on the isolated (single) intersection and efficient global traffic flow control on multiple intersections. A test bed was also developed and deployed for real measurements. The paper concludes with some future highlights and useful remarks
Challenges and opportunities in designing dementia-friendly communities with local governments
Background: Communities that do not accommodate the needs and preferences of people with dementia can exacerbate disability and isolation. Although dementia-friendly communities (DFCs) were established to foster understanding and acceptance of dementia, the built environment remains underexplored. We identified the challenges and opportunities for fostering dementia-enabling environments among community planners. Method: This study is set in South-West Sydney, Australia, where a DFC is being established. The policies of seven local governments were analysed for actions that aligned with Dementia Australia’s 41 DFC recommendations: 13 for social, 14 for outdoor, and 14 for indoor environments. An online workshop was then held with 30 community planners to raise awareness for dementia-enabling environments. Participants were surveyed about their dementia beliefs and attitudes. Facilitated discussions identified challenges and opportunities for designing DFCs. Qualitative and quantitative data across all sources were triangulated. Result: Although none of the local government policies specifically mentioned dementia, up to 20/41 DFC actions were met. Most of these were in social engagement (with ≤10/13 recommendations met by each local government). Less action was taken on outdoor and indoor environments (with ≤9/14 outdoor and ≤4/14 indoor recommendations met by up to six local governments). Although beliefs and attitudes about dementia among planners were generally positive, only 48% indicated that they had a good understanding of it and nearly 80% noted they would feel anxious and depressed about a diagnosis. Key DFC challenges included a lack of awareness and conflicting priorities between government bodies. Opportunities included engaging with universities to conduct demographically relevant awareness raising, facilitate multisectoral collaboration, developing an evidence-base, and involving service providers to engage with the dementia community. Conclusion: This study triangulated data to identify gaps in community planning efforts, confirming that more action is required to design dementia-friendly communities. We are now leading a multisectoral collaboration to educate community planners and the public, and are advocating for the recognition of dementia-friendly environments in government plans. This study provides practical guidance to assist planners with DFC designs
COVID-19 presenting as intussusception in infants: A case report with literature review
From Elsevier via Jisc Publications RouterHistory: accepted 2020-12-31, issue date 2021-01-07Article version: AMPublication status: AcceptedThe novel Corona virus disease 2019 (COVID-19) first presented in Wuhan, China. The virus was able to spread throughout the world, causing a global health crisis. The virus spread widely in Jordan after a wedding party held in northern Jordan. In most cases of COVID-19 infection, respiratory symptoms are predominant. However, in rare cases the disease may present with non-respiratory symptoms. The presentation of COVID-19 as a case of intussusception in children is a strange and rare phenomenon. We present here a case of a two-and-a-half month old male baby who was brought to hospital due to fever, frequent vomiting, dehydration and blood in stool. He was diagnosed as intussusception. The child was tested for corona due to the large societal spread of the virus and because he was near his mother, who was suffering from symptoms similar to corona or seasonal flu (she did not conduct a corona test). Patient was treated without surgery and recovered quickly. The COVID-19 infection was without respiratory symptoms, and there was no need for the child to remain in hospital after treatment of intussusception. The relationship between viruses, mesenteric lymphoid hyperplasia, and intussusception is a confirmed relation. ACE2 is the key receptor required for SARA-COV-2 to enter the host cells. ACE2 has been also found in the brush border of the intestinal mucosa, as well as it is a key inflammatory regulator in the intestine. This may suggest that SARSA-COV-2 could invade the respiratory tract as well as gastrointestinal tract or both. Few case reports documented the presentation of COVID-19 as intussusception in children. In the light of the wide-spread of corona virus, performing COVID-19 tests for children with intussusception can help linking the two entities. Development of gastrointestinal symptoms in COVID-19 positive children should raise concern about the development of intussusception
- …