Search results for: similarity search

Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Athanasia Kouroupa

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Existing research highlights the effect of employing robots in sessions with children and young people on the autism spectrum to develop and practice skills important to independent and functional living. The systematic review aimed to explore the way robots has been used with children and young people on the autism spectrum and the effect of using robots as a therapeutic interface. An electronic bibliographic database search using a combination of expressions was conducted. Data were extracted in relation to robot types, session characteristics, and outcomes and analysed using narrative synthesis. Forty studies were selected in the review. Humanoid robots were predominantly used to practice a range of social and communication skills. On average, children and young people on the autism spectrum had five sessions, twice a week, for approximately half an hour. Having sessions with a robot was commonly equal to or more effective than 'traditional' interventions delivered by a human therapist or having no therapy. The review reported encouraging outcomes to practice and develop a range of skills with children and young people on the autism spectrum. These findings suggest that some form of intervention is favourable over no intervention. However, there is little evidence for the relative effectiveness of the robot-based intervention as an innovative alternative option. Many of the studies had methodological weaknesses that make them vulnerable to bias. There is a need for further research that adheres to strict scientific methods making direct comparisons between different treatment options.

Keywords: autism, children, robots, outcomes

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Authors: Vladyslav Povoroznyuk, Oksana Ivanyk, Nataliia Dzerovych

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In the diagnostics of osteoporosis, the gold standard is considered to be bone mineral density; however, X-ray densitometry is not an accurate indicator of osteoporotic fracture risk under all circumstances. In this regard, the search for new methods that could determine the indicators not only of the mineral density, but of the bone tissue quality, is a logical step for diagnostic optimization. One of these methods is the evaluation of trabecular bone quality. The aim of this study was to examine the quality and mineral density of spine bone tissue, femoral neck, and body composition of women depending on the duration of the postmenopausal period, to determine the correlation of body fat with indicators of bone mineral density and quality. The study examined 179 women in premenopausal and postmenopausal periods. The patients were divided into the following groups: Women in the premenopausal period and women in the postmenopausal period at various stages (early, middle, late postmenopause). A general examination and study of the above parameters were conducted with General Electric X-ray densitometer. The results show that bone quality and mineral density probably deteriorate with advancing of postmenopausal period. Total fat and lean mass ratio is not likely to change with age. In the middle and late postmenopausal periods, the bone tissue mineral density of the spine and femoral neck increases along with total fat mass.

Keywords: osteoporosis, bone tissue mineral density, bone quality, fat mass, lean mass, postmenopausal osteoporosis

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Authors: Meaghan Bowman

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Soldiers are taught about the importance of effective communication with repetition of the phrase, “Communication is key.” They receive training in preparing for, and carrying out, interactions between foreign and domestic leaders to gain crucial information about a mission. These interactions are known as Key Leader Engagements (KLEs). For the training of KLEs, doctrine mandates the skills needed to conduct these “engagements” such as how to: behave appropriately, identify key leaders, and employ effective strategies. Army officers in training learn how to confront leaders, what information to gain, and how to ask questions respectfully. Unfortunately, soldiers rarely learn how to formulate questions optimally. Since less complex questions are easier to understand, we hypothesize that semantic complexity affects content understanding, and that age and education levels may have an effect on one’s ability to form paraphrases and judge their quality. In this study, we looked at paraphrases of queries as well as judgments of both the paraphrases’ naturalness and their semantic similarity to the query. Queries were divided into three complexity categories based on the number of relations (the first number) and the number of knowledge graph edges (the second number). Two crowd-sourced tasks were completed by Amazon volunteer participants, also known as turkers, to answer the research questions: (i) Are more complex queries harder to paraphrase and judge and (ii) Do age and education level affect the ability to understand complex queries. We ran statistical tests as follows: MANOVA for query understanding and two-way ANOVA to understand the relationship between query complexity and education and age. A probe of the number of given-level queries selected for paraphrasing by crowd-sourced workers in seven age ranges yielded promising results. We found significant evidence that age plays a role and marginally significant evidence that education level plays a role. These preliminary tests, with output p-values of 0.0002 and 0.068, respectively, suggest the importance of content understanding in a communication skill set. This basic ability to communicate, which may differ by age and education, permits reproduction and quality assessment and is crucial in training soldiers for effective participation in KLEs.

Keywords: engagement, key leader, paraphrasing, query complexity, understanding

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Authors: Jun Gao

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This paper combines the corpus-based and contrastive approaches, seeking to provide a systematic account of cataphora in English and Chinese natural conversations. Based on spoken corpus data, the first part of the paper examines a range of characteristics of cataphora in the two languages, including frequency of occurrence, patterns, and syntactic features. On the basis of this exploration, cataphora in the two languages are contrasted in a structured way. The analysis shows that English and Chinese share a similar distribution of cataphora in natural conversations in terms of frequency of occurrence, with repeat identification cataphora higher than first mention cataphora and intra-sentential cataphora much higher than inter-sentential cataphora. In terms of patterns, three types are identified in English, i.e. P+N, Ø+N, and it+Clause, while in Chinese, two types are identified, i.e., P+N and Ø+N. English and Chinese are similar in terms of syntactic features, i.e., cataphor and postcedent in the intra-sentential cataphora mainly occur in the initial subject position of the same clause, with postcedent immediately followed or delayed, and cataphor and postcedent are mostly in adjacent sentences in inter-sentential cataphora. In the second part of the paper, the motivations of cataphora are investigated. It is found that cataphora is primarily motivated by the speaker and hearer’s different knowledge states with regard to the referent. Other factors are also involved, such as interference, word search, and the tension between the principles of Economy and Clarity.

Keywords: cataphora, contrastive study, motivation, pattern, syntactic features

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Authors: Shahnam Behnam Malekzadeh, Ian Kerr, Tyson Kaempffer, Teague Harper, Andrew Watson

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The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and bedding planes at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including bedding plane elevations and coordinates. Thirteen (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ±55cm, while the actual results showed that 69% of predicted elevations were within ±79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ±99cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: case-based reasoning, geological feature, geology, piezometer, pressure sensor, core logging, dam construction

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Authors: Asma Rashid, Shazia Iram, Iftikhar Ahmad

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Mango sudden death is an emerging problem in Pakistan. As its prevalence is observed in almost all mango growing areas and severity varied from 2-5% in Punjab and 5-10% in Sindh. Symptoms on affected trees include bark splitting, discoloration of the vascular tissue, wilting, gummosis and at the end rapid death. Total of n= 45 isolates were isolated from different mango growing areas of Punjab and Sindh. Pathogenicity of these fungal isolates was tested through artificial inoculation method on different hosts (potato tubers, detached mango leaves, detached mango twigs and mango plants) under controlled conditions and all were proved pathogenic with varying degree of aggressiveness in reference to control. The findings of the present study proved that out of these four methods, potato tubers inoculation method was the most ideal as this fix the inoculums on the target site. Increased fungal growth and spore numbers may be due to soft tissues of potato tubers from which Ceratocystis isolates can easily pass. Lesion area on potato tubers was in the range of 7.09-0.14 cm2 followed by detached mango twigs which were ranged from 0.48-0.09 cm2). All pathological results were proved highly significant at P<0.05 through ANOVA but isolate to isolate showed non-significant behaviour but they have the positive effect on lesion area. Re-isolation of respective fungi was achieved with 100 percent success which results in the verification of Koch’s postulates. DNA of fungal pathogens was successfully extracted through phenol chloroform method. Amplification was done through ITS, b-tubulin gene, and Transcription Elongation Factor (EF1-a) gene primers and the amplified amplicons were sequenced and compared from NCBI which showed 99-100 % similarity with Ceratocystis manginecans. Fungus Ceratocystis manginecans formed one of strongly supported sub-clades through phylogenetic tree. Results obtained through this work would be supportive in establishment of relation of isolates with their region and will give information about pathogenicity level of isolates that would be useful to develop the management policies to reduce the afflictions in orchards caused by mango sudden death.

Keywords: artificial inoculation, mango, Ceratocystis manginecans, phylogenetic, screening

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Authors: Faith Fang Xi Ooi, Kam-Fong Lee

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Headlines are generally the summary of the content of news articles. With the added influence of hectic lifestyles, readers may rely solely on the headlines for information. In the media, what is reported concerning health issues are government responses and community involvement. There is a need for a call to action to curb health issues and not just reporting on what the government is doing about these health-related issues. In other words, linguistic elements of persuasive communicative function should be realized when reporting on health issues. Hence, this paper aims at identifying and analyzing the transitivity, Mood and Modality systems in two hundred news headlines from two Malaysian online news portals, namely The Star Online and New Straits Times. This study employs the purposive sampling method to obtain the news headlines on healthy eating using the search keyword ‘healthy eating’ and is based on Halliday’s Systemic Functional Linguistics (SFL) framework. The results show that the Material process dominates the process types along with its participants of Scope and Goal. The mood type that constitutes most of the headlines in the two newspapers is the declarative mood. Moreover, for Modality, the median Probability constitutes the highest in the headlines on healthy eating. This study contributes to the implications of being a source of reference for news writers and producers in constructing news headlines and for health campaign strategists to realize the persuasive appeals to influence behaviors and attitudes of the public towards healthy eating.

Keywords: healthy eating, modality, mood, news headlines, SFL

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Authors: S. Fröhlich, M. Herold, M. Allmer

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Early stage quantitative analysis of host cell protein (HCP) variations is challenging yet necessary for comprehensive bioprocess development. High resolution mass spectrometry (HRMS) provides a high-end technology for accurate identification alongside with quantitative information. Hereby we describe a flexible HRMS assay platform to quantify HCPs relevant in microbial expression systems such as E. Coli in both up and downstream development by means of MVDA tools. Cell pellets were lysed and proteins extracted, purified samples not further treated before applying the SMART tryptic digest kit. Peptides separation was optimized using an RP-UHPLC separation platform. HRMS-MSMS analysis was conducted on an Orbitrap Velos Elite applying CID. Quantification was performed label-free taking into account ionization properties and physicochemical peptide similarities. Results were analyzed using SIEVE 2.0 (Thermo Fisher Scientific) and SIMCA (Umetrics AG). The developed HRMS platform was applied to an E. Coli expression set with varying productivity and the corresponding downstream process. Selected HCPs were successfully quantified within the fmol range. Analysing HCP networks based on pattern analysis facilitated low level quantification and enhanced validity. This approach is of high relevance for high-throughput screening experiments during upstream development, e.g. for titer determination, dynamic HCP network analysis or product characterization. Considering the downstream purification process, physicochemical clustering of identified HCPs is of relevance to adjust buffer conditions accordingly. However, the technology provides an innovative approach for label-free MS based quantification relying on statistical pattern analysis and comparison. Absolute quantification based on physicochemical properties and peptide similarity score provides a technological approach without the need of sophisticated sample preparation strategies and is therefore proven to be straightforward, sensitive and highly reproducible in terms of product characterization.

Keywords: process analytical technology, mass spectrometry, process characterization, MVDA, pattern recognition

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Authors: Diana Ruth Caga-Anan

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Classroom management is a critical skill but the styles are constantly evolving. It is constantly under pressure particularly in the college education level due to diversity in student profiles, modes of delivery, and marketization of higher education. This study sought to analyze the extent of implementation of classroom management practices (CMPs) of the college instructors of the Hotel, Restaurant, and Institution Management of a premier university in the Philippines. It was also determined if their length of teaching affects their classroom management style. A questionnaire with sixteen 'evidenced-based' CMPs grouped into five critical features of classroom management, adopted from the literature search of Simonsen et al. (2008), was administered to 4 instructor-respondents and to their 88 students. Weighted mean scores of each of the CMPs revealed that there were differences between the instructors’ self-scores and their students’ ratings on their implementation of CMPs. The critical feature of classroom management 'actively engage students in observable ways' got the highest mean score, corresponding to 'always' from the instructors’ self-rating and 'frequently' from their students’ ratings. However, 'use a continuum of strategies to respond to inappropriate behaviors' got the lowest scores from both the instructors and their students corresponding only to 'occasionally'. Analysis of variance showed that the only CMP affected by the length of teaching is the practice of 'prompting students to respond'. Based on the findings, some recommendations for the instructors to improve on the critical feature where they scored low are discussed and suggestions are included for future research.

Keywords: classroom management, CMPs, critical features, evidence-based classroom management practices

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Jenny Paola Forero Pachón, Sonia Cristina Gamboa Sarmiento, Luis Carlos Gómez Flórez

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The Colombian government has defined an e-government strategy to take advantage of Information Technologies (IT) in order to contribute to the building of a more efficient, transparent and participative State that provides better services to citizens and businesses. In this regard, the Justice sector is one of the government sectors where IT has generated more expectation considering that the country has a judicial processes backlog. This situation has led to the search for alternative forms of access to justice that speed up the process while providing a low cost for citizens. To this end, the Colombian government has authorized the use of Alternative Dispute Resolution methods (ADR), a remedy where disputes can be resolved more quickly compared to judicial processes while facilitating greater communication between the parties, without recourse to judicial authority. One of these methods is conciliation, which includes a special modality that takes advantage of IT for the development of itself known as virtual conciliation. With this option the conciliation is supported by information systems, applications or platforms and communications are provided through it. This paper evaluates the level of maturity in how the service of virtual conciliation is under the framework of this strategy. This evaluation is carried out considering Shahkooh's 5-phase model for e-government. As a result, it is evident that in the context of conciliation, maturity does not reach the necessary level in the model so that it can be considered as virtual conciliation; therefore, it is necessary to define strategies to maximize the potential of IT in this context.

Keywords: alternative dispute resolution, e-government, evaluation of maturity, Shahkooh model, virtual conciliation

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Authors: Ehsan Yadegari

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While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

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Authors: Mennani Maha, Attak El Houssain

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Under the massive effect of the Covid-19 health crisis, marked by a loss of competitiveness, a slowdown in growth and an accumulation of the repercussions of socio-economic inequalities, a considerable effort must be combined, in Morocco, to put into perspective macro-political, macro-economic and social opportunities. The development of a new economic and social approach is essential in order to respond to the authenticity of the new development model that will be used by the country. The appropriation of strategies of solidarity and social cohesion constitutes a participatory, competitive and inclusive approach to support the functionalities of the economic, social and political system. Therefore, the search for alternative financial resources has become a necessity to achieve the objectives of sustainable socio-economic growth on the one hand; and to promote, on the other hands, the dynamics, of large scale, social investments. The zakat remains a site of the Islamic economy dedicated to stimulating the bases of a collective adhesion of the population on the economic, as well as on the social level, thanks to a fair and equitable distribution of the zakat funds. However, Morocco is one of the few Muslim countries that has not yet had an institution for collecting and distributing this Islamic duty, which makes it difficult to measure the socio-economic impact of zakat. This theoretical document essentially ensures the development of the crucial utility of institutionalizing zakat in order to reinforce the objectives of social solidarity in Morocco in line with the process of conceptualizing a new development model.

Keywords: zakat, socio-economic development, solidarity, social investment

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Authors: Aniket Kumar, Jacob Peedicayil

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Major depressive disorder (MDD) is a common and important psychiatric disorder. Several clinical features of MDD suggest an epigenetic basis for its pathogenesis. Since epigenetics (heritable changes in gene expression not involving changes in DNA sequence) may underlie the pathogenesis of MDD, epigenetic drugs such as DNA methyltransferase inhibitors (DNMTi) and histone deactylase inhibitors (HDACi) may be useful for treating MDD. The available literature indexed in Pubmed on preclinical drug trials of epigenetic drugs for the treatment of MDD was investigated. The search terms we used were ‘depression’ or ‘depressive’ and ‘HDACi’ or ‘DNMTi’. Among epigenetic drugs, it was found that there were 3 preclinical trials using HDACi and 3 using DNMTi for the treatment of MDD. All the trials were conducted on rodents (mice or rats). The animal models of depression that were used were: learned helplessness-induced animal model, forced swim test, open field test, and the tail suspension test. One study used a genetic rat model of depression (the Flinders Sensitive Line). The HDACi that were tested were: sodium butyrate, compound 60 (Cpd-60), and valproic acid. The DNMTi that were tested were: 5-azacytidine and decitabine. Among the three preclinical trials using HDACi, all showed an antidepressant effect in animal models of depression. Among the 3 preclinical trials using DNMTi also, all showed an antidepressant effect in animal models of depression. Thus, epigenetic drugs, namely, HDACi and DNMTi, may prove to be useful in the treatment of MDD and merit further investigation for the treatment of this disorder.

Keywords: DNA methylation, drug discovery, epigenetics, major depressive disorder

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Authors: R. M. Noah, N. M. Nasir, M. R. Jais, M. S. S. Wahab, M. H. Abdullah, A. S. S. Raj

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Infectious diseases are getting more difficult to treat due to the resistant strains of bacteria. Current generations of antibiotics are most likely ineffective against multi-drug resistant strains bacteria. Thus, there is an urgent need in search of natural antibiotics in particular from medicinal plants. One of the common medicinal plants, Melaleuca cajuputi, has been reported to possess antibacterial properties. The study was conducted to evaluate and justify the presence of antibacterial activity of Melaleuca cajuputi essential oil (EO) against the multi-drug resistant bacteria. Clinical isolates obtained from the teaching hospital were re-assessed to confirm the exact identity of the bacteria to be tested, namely methicillin-resistant staphylococcus aureus (MRSA), carbapenem-resistant enterobacteriaceae (CRE), and extended-spectrum beta-lactamases producer (ESBLs). A well diffusion method was done to observe the inhibition zones of the essential oil against the bacteria. Minimum inhibitory concentration (MIC) was determined using the microdilution method in 96-well flat microplate. The absorbance was measured using a microplate reader. Minimum bactericidal concentration (MBC) was performed using the agar medium method. The zones of inhibition produced by the EO against MRSA, CRE, and ESBL were comparable to that of generic antibiotics used, gentamicin and augmentin. The MIC and MBC results highlighted the antimicrobial efficacy of the EO. The outcome of this study indicated that the EO of Melaleuca cajuputi had antibacterial activity on the multi-drug resistant bacteria. This finding was eventually substantiated by electron microscopy work.

Keywords: melaleuca cajuputi, antibacterial, resistant bacteria, essential oil

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Authors: Lynne Soon-Chean Park

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Critical Realism (CR) has emerged as an alternative to both the positivist and constructivist perspectives that have long dominated social work research. By unpacking the epistemic weakness of two dogmatic perspectives, CR provides a useful philosophical approach that incorporates the ontological objectivist and subjectivist stance. The CR perspective suggests an alternative approach for social work researchers who have long been looking to engage in the complex interplay between perceived reality at the empirical level and the objective reality that lies behind the empirical event as a causal mechanism. However, despite the usefulness of CR in informing social work research, little practical guidance is available about how CR can inform methodological considerations in social work research studies. This presentation aims to provide a detailed description of CR-informed thematic analysis by drawing examples from a social work doctoral research of Korean migrants’ experiences and understanding of trust associated with their settlement experience in New Zealand. Because of its theoretical flexibility and accessibility as a qualitative analysis method, thematic analysis can be applied as a method that works both to search for the demi-regularities of the collected data and to identify the causal mechanisms that lay behind the empirical data. In so doing, this presentation seeks to provide a concrete and detailed exemplar for social work researchers wishing to employ CR in their qualitative thematic analysis process.

Keywords: critical Realism, data analysis, epistemology, research methodology, social work research, thematic analysis

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Authors: Elmahdi Khalil, Saad Enniari, Mostapha Zbakh

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Cloud computing promises to increase innovation and the velocity with witch applications are deployed, all while helping any enterprise meet most IT service needs at a lower total cost of ownership and higher return investment. As the march of cloud continues, it brings both new opportunities and new security challenges. To take advantages of those opportunities while minimizing risks, we think that Intrusion Detection Systems (IDS) integrated in the cloud is one of the best existing solutions nowadays in the field. The concept of intrusion detection was known since past and was first proposed by a well-known researcher named Anderson in 1980's. Since that time IDS's are evolving. Although, several efforts has been made in the area of Intrusion Detection systems for cloud computing environment, many attacks still prevail. Therefore, the work presented in this paper proposes a multi criteria analysis and a comparative study between several IDS architectures designated to work in a cloud computing environments. To achieve this objective, in the first place we will search in the state of the art of several consistent IDS architectures designed to work in a cloud environment. Whereas, in a second step we will establish the criteria that will be useful for the evaluation of architectures. Later, using the approach of multi criteria decision analysis Mac Beth (Measuring Attractiveness by a Categorical Based Evaluation Technique we will evaluate the criteria and assign to each one the appropriate weight according to their importance in the field of IDS architectures in cloud computing. The last step is to evaluate architectures against the criteria and collecting results of the model constructed in the previous steps.

Keywords: cloud computing, cloud security, intrusion detection/prevention system, multi-criteria decision analysis

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Authors: Simona Grasso, Gabrielle Smith, Sophie Bowers, Oluseyi Moses Ajayi, Mark Swainson

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Hybrid meat analogues are meat products whereby a proportion of meat has been partially replaced by more sustainable protein sources. These products could bridge the gap between meat and meat-free products, providing convenience, and allowing consumers to continue using meat products as they conventionally would, while lowering their overall meat intake. The study aimed to investigate the effect of introducing texturized soy protein (TSP) at different levels (15% and 30%) with and without nutritional yeast as flavour enhancer on the sensory and instrumental quality of beef meatballs, compared to a soy and yeast-free control. Proximate analysis, yield, colour, instrumental texture, and sensory quality were investigated. The addition of soy and yeast did not have significant effects on the overall protein content, but the total fat and moisture content went down with increasing soy substitution. Samples with 30% TSP had significantly higher yield than the other recipes. In terms of colour, a* redness values tended to go down and b* yellowness values tended to go up with increasing soy addition. The addition of increasing levels of soy and yeast modified the structure of meatballs resulting in a progressive decrease in hardness and chewiness compared to control. Sixty participants assessed the samples using Check-all-that-apply (CATA) questions and hedonic scales. The texture of all TSP-containing samples received significantly higher acceptability scores than control, while 15% TSP with yeast received significantly higher flavour and overall acceptability scores than control. Control samples were significantly more often associated than the other recipes to the term 'hard' and the least associated to 'soft' and 'crumbly and easy to cut'. All recipes were similarly associated to the terms 'weak meaty', 'strong meaty', 'characteristic' and 'unusual'. Correspondence analysis separated the meatballs in three distinct groups: 1) control; 2) 30%TSP with yeast; and 3) 15%TSP, 15%TSP with yeast and 30%TSP located together on the sensory map, showing similarity. Adding 15-30% TSP with or without yeast inclusion could be beneficial for the development of future meat hybrids with acceptable sensory quality. These results can provide encouragement for the use of the hybrid concept by the meat industry to promote the partial substitution of meat in flexitarians’ diets.

Keywords: CATA, hybrid meat products, texturised soy protein, yeast

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Authors: Peter Yamoah, Frasia Oosthuizen

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Introduction: Reporting of Adverse Events Following Immunization continues to be a challenge. Pharmacovigilance centers throughout the world are mandated by the WHO to submit AEFI reports from various countries to a large pool of adverse drug reaction electronic database called Vigibase. Despite the relevant information of AEFI in Vigibase, it is unavailable to the general public. However, the WHO has an alternative website called VigiAccess which is an open access website serving as a repository of reported adverse drug reactions and AEFIs. The aim of the study was to ascertain the reporting pattern of a number of commonly used vaccines in VigiAccess. Methods: VigiAccess was thoroughly searched on the 5th of February 2018 for AEFI reports of measles vaccine, oral polio vaccine (OPV), yellow fever vaccine, pneumococcal vaccine, rotavirus vaccine, meningococcal vaccine, tetanus vaccine and tuberculosis (BCG) vaccine. These were reports from all pharmacovigilance centers in the world from the time they joined the WHO drug monitoring program. Results: After a thorough search in VigiAccess, there were 9,062 measles vaccine AEFIs, 185,829 OPV AEFIs, 24,577 yellow fever vaccine AEFIs, 317,208 pneumococcal vaccine AEFIs, 73,513 rotavirus vaccine AEFIs, 145,447 meningococcal vaccine AEFIs, 22,781 tetanus vaccine AEFIs and 35,556 BCG vaccine AEFIs. Conclusion: The study revealed that out of the eight vaccines studied, pneumococcal vaccines are associated with the highest number of AEFIs whilst measles vaccines were associated with the least AEFIs.

Keywords: vaccines, adverse reactions, VigiAccess, adverse event reporting

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Authors: Kuan-Han Lin, Kuan-Yin Lin, Ka-Chun Siu

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The purpose of this systematic review was to determine the impact of post-traumatic stress disorders (PTSD) symptom or depressive symptoms on return to work (RTW) after occupational injury. The original articles of clinical trials and observational studies from PubMed, MEDLINE, and PsycINFO between January 1980 and November 2016 were retrieved. Two reviewers evaluated the abstracts identified by the search criteria for full-text review. To be included in the final analysis, studies were required to use either intervention or observational study design to examine the association between psychiatric symptoms and RTW. A modified checklist designed by Downs & Black and Crombie was used to assess the methodological quality of included study. A total of 58 articles were identified from the electronic databases after duplicate removed. Seven studies fulfilled the inclusion criteria and were critically reviewed. The rates of RTW in the included studies were reported to be 6% to 63.6% among workers after occupational injuries. This review found that post-traumatic stress symptom and depressive symptoms were negatively associated with RTW. Although the impact of psychiatric symptoms on RTW after occupational injury remains poorly understood, this review brought up the important information that injured workers with psychiatric symptoms had poor RTW outcome. Future work should address the effective management of psychiatric factors affecting RTW among workers.

Keywords: depressive symptom, occupational injury, post-traumatic stress disorder, return to work

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Authors: Hassan Wajid

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Architecture design studio with all its accouterments, especially pedagogies, has been committed to awakening the students to the true meaning of the concept of Dwelling. The real task is how to make them unlearn the associations of “dwelling as a rented or owned accommodation by the road with a car parked in front of a garage door and replace it by the fundamental experiential-phenomenological manifestations of Light, Space, Gravity and Time through assigned readings and small theoretical challenges resulting in drawings and models. The primary challenge for teachers remained the introduction of the act or desire of ‘Dwelling’ philosophically. The academic link had been offered by Albert Hofstadter's Poetry, Language, through which Martin Heidegger’s fourfold concept of ‘Building Dwelling, Thinking’ primarily served to guide us through this trajectory in helping to build an intellectual framework as justification of the term “dwelling” in its various meanings. Gaston Bachelard’s Poetics of Space and Merleau-Ponti’s Phenomenology of Perception also got assigned as reading. Four fictional characters created by two master short story writers G Maupassant, and O Henry were introduced as DwellersClients in search of their respective dwellings as drawn imaginations in the studio four-fold of Light, Space, Gravity, and Time and at the same time aspire to understand thoroughly Heidegger’s Four-Fold of Earth, Sky, Divinities and Mortals. asserting its place in the corresponding story and its unique character as the Dweller.

Keywords: dwelling, imagination, architectural manifestation, phenomenological

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Feng Tao, Han Ye, Shaoyi Liao

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City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m.

Keywords: signal propagation model, centroid algorithm, localization, mixed filtering, RSSI

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Authors: Yelin Zhao, Xinxiu Li, Martin Smelik, Oleg Sysoev, Firoj Mahmud, Dina Mansour Aly, Mikael Benson

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Background: Early diagnosis of pancreatic cancer is clinically challenging due to vague, or no symptoms, and lack of biomarkers. Polygenic risk score (PRS) scores may provide a valuable tool to assess increased or decreased risk of PC. This study aimed to develop such PRS by filtering genetic variants identified by GWAS using transcriptional programs identified by single-cell RNA sequencing (scRNA-seq). Methods: ScRNA-seq data from 24 pancreatic ductal adenocarcinoma (PDAC) tumor samples and 11 normal pancreases were analyzed to identify differentially expressed genes (DEGs) in in tumor and microenvironment cell types compared to healthy tissues. Pathway analysis showed that the DEGs were enriched for hundreds of significant pathways. These were clustered into 40 “programs” based on gene similarity, using the Jaccard index. Published genetic variants associated with PDAC were mapped to each program to generate program PRSs (pPRSs). These pPRSs, along with five previously published PRSs (PGS000083, PGS000725, PGS000663, PGS000159, and PGS002264), were evaluated in a European-origin population from the UK Biobank, consisting of 1,310 PDAC participants and 407,473 non-pancreatic cancer participants. Stepwise Cox regression analysis was performed to determine associations between pPRSs with the development of PC, with adjustments of sex and principal components of genetic ancestry. Results: The PDAC genetic variants were mapped to 23 programs and were used to generate pPRSs for these programs. Four distinct pPRSs (P1, P6, P11, and P16) and two published PRSs (PGS000663 and PGS002264) were significantly associated with an increased risk of developing PC. Among these, P6 exhibited the greatest hazard ratio (adjusted HR[95% CI] = 1.67[1.14-2.45], p = 0.008). In contrast, P10 and P4 were associated with lower risk of developing PC (adjusted HR[95% CI] = 0.58[0.42-0.81], p = 0.001, and adjusted HR[95% CI] = 0.75[0.59-0.96], p = 0.019). By comparison, two of the five published PRS exhibited an association with PDAC onset with HR (PGS000663: adjusted HR[95% CI] = 1.24[1.14-1.35], p < 0.001 and PGS002264: adjusted HR[95% CI] = 1.14[1.07-1.22], p < 0.001). Conclusion: Compared to published PRSs, scRNA-seq-based pPRSs may be used not only to assess increased but also decreased risk of PDAC.

Keywords: cox regression, pancreatic cancer, polygenic risk score, scRNA-seq, UK biobank

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Authors: M. F. Amado, A. Amado, F. Poggi, J. Correia de Freitas

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Today it is widely understood that global energy consumption patterns are directly related to the ongoing urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals. In this paper, a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities, economic development, and the local and global environment while safeguarding fairness in the energy sector.

Keywords: solar urban planning, solar smart city, urban development, energy efficiency

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Authors: Phillip Thebe

Abstract:

African traders in China have generated magnanimous attention from scholars because of their choices to take short-term trips to Guangzhou and other places in search of cheaper products taking advantage of the status of China as a "global manufacturing hub". Nevertheless, their activities only gained traction at the turn of the millennium, with their presence in China incrementally dwindling over the next two decades. Now, with the devastating effects of COVID-19, their journeys have had to be totally cut short by unending lockdowns and stiff migration rules due to China's zero-tolerance of COVID-19 policy. This unfortunate yet untimely occurrence has left many scholars wondering if this marks the end of African traders in China and, indeed, the end of their business careers. Between March and September 2022, 20 traders were followed back to Africa, Zimbabwe, to find out what they are doing after having been shut out of China. Data was collected through ethnographic immersion and purposive in-depth interviewing in and around the city of Bulawayo. Snowballing was employed to reach out to the traders until a saturation point was reached and interview transcripts were filed for analysis. The findings revealed that some still trading online in China, report different opinions and feelings about doing business during COVID-19. Others have left the Chinese marketplace, now pursuing European industries in Turkey and other places. Others are still getting Chinese goods but in African countries such as Tanzania, Mozambique, South Africa, and Botswana. Some are now into the second-hand clothing trade, whereas others have stopped doing business to pursue other life-course interests. These and other issues are addressed in this paper from the anthropology of migration and globalization perspectives.

Keywords: entrepreneurship, African traders, China, COVID-19, Africans in China

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Authors: L. Paulino Ferreira, M. Gomes Neto, M. Duarte, S. Serra

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Objectives: COVID-19 pandemic has caused older adults to experience a degree of social isolation and loneliness that is unprecedented. Our aim is to review state of the art regarding the consequences of social isolation due to COVID-19 in elderly people. Methods: The authors conducted a search on Medscape and PubMed with the keywords mentioned below, and the most relevant articles were selected. Results: Social isolation leads many elderlies to experience loneliness, anxiety, depression, alcohol abuse, and feelings of abandonment with a perception of being a burden on society. Thus, social isolation has increased the risk for suicide in older people. It is also noteworthy that the exacerbation of psychiatric disorders (such as depression, anxiety, and post-traumatic stress disorder) without correct treatment and follow-up also increases suicide risk. Loneliness is also associated with accelerated cognitive deterioration and dementia. Besides that, during social isolation, it could be more difficult for older people to get medication as well as proper health care. It is also noticed an increase in the risk of falls, poor nutrition, and lack of exercise. All this contributes to weakening elderlies’ immune systems leading to a higher risk of developing infections, cardiovascular events, and cancer, increasing hospitalization and morbimortality. Conclusion: Social isolation in the elderly has a significant impact on physical and mental health, as well as morbimortality and hospitalizations due to non-COVID causes. Nevertheless, further studies will be needed to assess the real dimension of the effects of social isolation due to COVID-19.

Keywords: social isolation, COVID-19, elderly, mental health

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Authors: Hatice Canan Gungor, Ahmet Akdemir

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The fields of engineering and technological sciences are increasing in quality and quantity day by day all over the world. Countries have to follow, implement and adapt these developments in order to economical empowerments. In our era, it's possible to follow the rapidly developing technology and to produce new technologies by inquisitive, curious, numerical thinking individuals who can show several approaches to problem solving. In this case, countries should develop te result oriented and need-focused curriculums in university education. As in the whole world, there are more space studies in our country as well. Universities should undertake the task of supply the need for staff of this technological race. In this context, questions about the purpose, content and learning outcomes of the space sciences and space engineering departments in our country will be researched answers to reveal the characteristic of this section. In this study, it was determined in which universities the space engineering and the departments of basic sciences educate with formal education and the contents of this education, and the universities were compared with each other as of 2017. In our country three universities provide Aeronautical and Aerospace Engineering, two universities provide Space Sciences and Technologies, two universities provide Aerospace Engineering, two universities provide Aeronautics and Astronautics Engineering education. In all universities, specialized courses are taught after basic engineering education. But the question that needs to be answered is, do the lessons benefit in practice? The answer of this question will reveal the quality of the education. This paper suggests that surveys be conducted to search for the answer to this question. It's thought to be the base for the next works.

Keywords: education, space engineering, space science, quality of systems

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Authors: Zekang Lan, Yan Xu, Yingkun Huang, Dian Huang, Shengzhong Feng

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Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective.

Keywords: high-performance computing, job allocation, neural simulated annealing, topology-aware

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