Search results for: weighted frequent patterns
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4123

Search results for: weighted frequent patterns

1303 Identification of Viruses Infecting Garlic Plants in Colombia

Authors: Diana M. Torres, Anngie K. Hernandez, Andrea Villareal, Magda R. Gomez, Sadao Kobayashi

Abstract:

Colombian Garlic crops exhibited mild mosaic, yellow stripes, and deformation. This group of symptoms suggested a viral infection. Several viruses belonging to the genera Potyvirus, Carlavirus and Allexivirus are known to infect garlic and lower their yield worldwide, but in Colombia, there are no studies of viral infections in this crop, only leek yellow stripe virus (LYSV) has been reported to our best knowledge. In Colombia, there are no management strategies for viral diseases in garlic because of the lack of information about viral infections on this crop, which is reflected in (i) high prevalence of viral related symptoms in garlic fields and (ii) high dispersal rate. For these reasons, the purpose of the present study was to evaluate the viral status of garlic in Colombia, which can represent a major threat on garlic yield and quality for this country 55 symptomatic leaf samples were collected for virus detection by RT-PCR and mechanical inoculation. Total RNA isolated from infected samples were subjected to RT-PCR with primers 1-OYDV-G/2-OYDV-G for Onion yellow dwarf virus (OYDV) (expected size 774pb), 1LYSV/2LYSV for LYSV (expected size 1000pb), SLV 7044/SLV 8004 for Shallot latent virus (SLV) (expected size 960pb), GCL-N30/GCL-C40 for Garlic common latent virus (GCLV) (expected size 481pb) and EF1F/EF1R for internal control (expected size 358pb). GCLV, SLV, and LYSV were detected in infected samples; in 95.6% of the analyzed samples was detected at least one of the viruses. GCLV and SLV were detected in single infection with low prevalence (9.3% and 7.4%, respectively). Garlic generally becomes coinfected with several types of viruses. Four viral complexes were identified: three double infection (64% of analyzed samples) and one triple infection (15%). The most frequent viral complex was SLV + GCLV infecting 48.1% of the samples. The other double complexes identified had a prevalence of 7% (GCLV + LYSV and SLV + LYSV) and 5.6% of the samples were free from these viruses. Mechanical transmission experiments were set up using leaf tissues of collected samples from infected fields, different test plants were assessed to know the host range, but it was restricted to C. quinoa, confirming the presence of detected viruses which have limited host range and were detected in C. quinoa by RT-PCR. The results of molecular and biological tests confirm the presence of SLV, LYSV, and GCLV; this is the first report of SLV and LYSV in garlic plants in Colombia, which can represent a serious threat for this crop in this country.

Keywords: SLV, GCLV, LYSV, leek yellow stripe virus, Allium sativum

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1302 Dietary Habits and Cardiovascular Risk factors Among the Patients of the Coronary Artery Disease: A Case Control Study

Authors: Muhammad Kamran Hanif Khan, Fahad Mushtaq

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Globally, the death rate from cardiovascular disease has risen over the past 20 years, but especially in low and middle-income countries (LMICS), reports the World Health Organization (WHO). Around 17.5 million deaths, or 31% of all deaths worldwide in 2012, were attributed to CVD, 80% of which occurred in low- and middle-income nations, and eighty five percent of all worldwide disability is attributable to cardiovascular disease. This study assessed the dietary habit and Cardiovascular Risk factors among the patients of coronary artery disease against matched controls. The research was a case-control study. Sample size for this case-control study was 410 CAD cases and 410 healthy controls. The case-control ratio was 1:1. Patients diagnosed with coronary artery disease were recruited from the outpatient departments and emergency rooms of four hospitals in Pakistan. The ages of people who were diagnosed with coronary artery disease were not significantly different from (mean 57.97 7.39 years) the healthy controls (mean 57.12 6.73 years). In order to determine the relationship between food consumption and the two binary outcomes, logistic regression analysis was carried out. Chicken (0.340 (0.245-0.47), p-value 0.0001), beef (0.38 (0.254-0.56), p-value 0.0001), eggs (0.297 (0.208-0.426), p-value 0.0001), and junk food (0.249 (0.167-0.372), p-value 0.0001)) were protective, while yogurt consumption more than twice weekly was risk. Conclusion: In conclusion, poor dietary habits are closely linked to the risk of CAD. Investigations based on dietary trends offer vital and practical knowledge about societal patterns.

Keywords: dietary habbits, cardiovasculardisease, CVD risk factors, hypercholesterolemia

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1301 Current Judicial Discourse Regarding the Impact of Alcohol Use Disorders on Crime in Canada

Authors: Ellen McClure

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It is generally well-known that a number of inmates suffer from some form of substance or alcohol use disorder. This study identifies, analyses, classifies and codifies the most recent Canadian criminal judgments involving an accused diagnosed with an alcohol use disorder specifically. From this research, patterns in judicial discourse and sentencing norms can be established, and these findings can be juxtaposed with existing relevant academic literature, particular attention will be given to this discussion at the sentencing stage, and the subsequent incarceration of those with alcohol use disorders. This topic will be explored with an overarching emphasis on the effects that a lack of conversation regarding a possible correlation between alcohol consumption and crime may have. Although comparisons may be made in order to clarify or highlight certain issues, particular attention will be paid to jurisdictions within Canada. This paper explores the existing judicial discourse in sentencing regarding the relationship between alcohol and crime, and how this might explain the higher incarceration rates of those suffering from alcohol use disorders in Canada. The research questions are as follows: (1) What are the existing judicial discourses in sentencing around the relationship between alcohol and crime? (2) To what extent has the current discourse on alcohol addiction among judges and legal academics contributed to the incarceration of alcoholics?The major findings of this research indicate a strong correlation between a lack of judicial discussion regarding the accused’s alcohol use disorder and an increased tendency to consider an alcohol use disorder as an aggravating factor. Furthermore, it was found that an 82% of judges who discussed the alcohol use disorder meaningfully referred to the disorder as a mitigating factor. This can be compared with 6.7% of judges who referred to the alcohol use disorder as a mitigating factor in cases where the disorder was not meaningfully discussed.

Keywords: alcohol use disorder, addiction, criminal justice, judicial discourse

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1300 Mikrophonie I (1964) by Karlheinz Stockhausen - Between Idea and Auditory Image

Authors: Justyna Humięcka-Jakubowska

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1. Background in music analysis. Traditionally, when we think about a composer’s sketches, the chances are that we are thinking in terms of the working out of detail, rather than the evolution of an overall concept. Since music is a “time art’, it follows that questions of a form cannot be entirely detached from considerations of time. One could say that composers tend to regard time either as a place gradually and partially intuitively filled, or they can look for a specific strategy to occupy it. In my opinion, one thing that sheds light on Stockhausen's compositional thinking is his frequent use of 'form schemas', that is often a single-page representation of the entire structure of a piece. 2. Background in music technology. Sonic Visualiser is a program used to study a musical recording. It is an open source application for viewing, analysing, and annotating music audio files. It contains a number of visualisation tools, which are designed with useful default parameters for musical analysis. Additionally, the Vamp plugin format of SV supports to provide analysis such as for example structural segmentation. 3. Aims. The aim of my paper is to show how SV may be used to obtain a better understanding of the specific musical work, and how the compositional strategy does impact on musical structures and musical surfaces. I want to show that ‘traditional” music analytic methods don’t allow to indicate interrelationships between musical surface (which is perceived) and underlying musical/acoustical structure. 4. Main Contribution. Stockhausen had dealt with the most diverse musical problems by the most varied methods. A characteristic which he had never ceased to be placed at the center of his thought and works, it was the quest for a new balance founded upon an acute connection between speculation and intuition. In the case with Mikrophonie I (1964) for tam-tam and 6 players Stockhausen makes a distinction between the "connection scheme", which indicates the ground rules underlying all versions, and the form scheme, which is associated with a particular version. The preface to the published score includes both the connection scheme, and a single instance of a "form scheme", which is what one can hear on the CD recording. In the current study, the insight into the compositional strategy chosen by Stockhausen was been compared with auditory image, that is, with the perceived musical surface. Stockhausen's musical work is analyzed both in terms of melodic/voice and timbre evolution. 5. Implications The current study shows how musical structures have determined of musical surface. My general assumption is this, that while listening to music we can extract basic kinds of musical information from musical surfaces. It is shown that an interactive strategies of musical structure analysis can offer a very fruitful way of looking directly into certain structural features of music.

Keywords: automated analysis, composer's strategy, mikrophonie I, musical surface, stockhausen

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1299 Effect of Barium Doping on Structural, Morphological, Optical, and Photocatalytic Properties of Sprayed ZnO Thin Films

Authors: Halima Djaaboube, Redha Aouati, Ibtissem Loucif, Yassine Bouachiba, Mouad Chettab, Adel Taabouche, Sihem Abed, Salima Ouendadji, Abderrahmane Bouabellou

Abstract:

Thin films of pure and barium-doped zinc oxide (ZnO) were prepared using spray pyrolysis process. The films were deposited on glass substrates at 450°C. The different samples are characterized by X-ray diffraction (XRD) and UV-Vis spectroscopy. X-ray diffraction patterns reveal the formation of a single ZnO Wurtzite structure and the good crystallinity of the films. The substitution of Ba ions influences the texture of the layers and makes the (002) plane a preferential growth plane. At concentrations below 6% Ba, the hexagonal structure of ZnO undergoes compressive stresses due to barium ions which have a radius twice of the Zn ions. This result leads to the decrees of a and c parameters and therefore the volume of the unit cell. This result is confirmed by the decrease in the number of crystallites and the increase in the size of the crystallites. At concentrations above 6%, barium substitutes the zinc atom and modifies the structural parameters of the thin layers. The bandgap of ZnO films decreased with increasing doping, this decrease is probably due to the 4d orbitals of the Ba atom due to the sp-d spin-exchange interactions between the band electrons and the localized d-electrons of the substituted Ba ion. Although, the Urbache energy undergoes an increase which implies the creation of energy levels below the conduction band and decreases the band gap width. The photocatalytic activity of ZnO doped 9% Ba was evaluated by the photodegradation of methylene blue under UV irradiation.

Keywords: barium, doping, photodegradation, spray pyrolysis, ZnO.

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1298 Linking Enhanced Resting-State Brain Connectivity with the Benefit of Desirable Difficulty to Motor Learning: A Functional Magnetic Resonance Imaging Study

Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

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Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

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1297 Sergei Prokofiev and Ukraine: The Influence of the Ukrainian Musical Tradition

Authors: Khrystyna Zai

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This research delves into the profound impact of Ukrainian musical traditions on the life and works of the renowned composer Sergei Prokofiev. Sergei Prokofiev's formative years in Ukraine, particularly in Sontsivka(Eastern Ukraine), allowed him to immerse himself in the local music. He encountered Ukrainian folk songs and dances, which left an indelible mark on his musical sensibilities. With a focus on the early 20th century, a period of significant cultural transformation in both Ukraine and Europe, this study examines how Prokofiev's exposure to Ukrainian folk music, its melodic motifs, and rhythmic patterns influenced his compositions. Prokofiev’s works showcase his deliberate efforts to fuse Ukrainian elements with his distinctive modernist style. This study analyzes Prokofiev's engagement with Ukrainian themes in his music, such as the "Semen Kotko”, “The Love of Three Oranges”, “On the Dnieper”, “Scythian Suite”, “Sinfonia Concertante" for cello and orchestra, "Sonata No. 9,", “Partisans in the steppes of Ukraine” (where Prokofiev uses texts in Ukrainian). The scientific work mentions his interactions and collaborations with Ukrainian musicians and cultural figures during Prokofiev’s career. Notably, his association with Ukrainian pianist Sviatoslav Richter and conductor Kirill Karabits led to interpretations of his compositions with a Ukrainian perspective. This research illuminates the nuances of cross-cultural influences in Prokofiev's oeuvre, contributing to a deeper understanding of the interplay between national identities and artistic expression during a pivotal period in history, based on the fact that the composer himself considered Ukraine to be his homeland, calling himself “steppe boy”.

Keywords: florida atlantic university, ukrainian music, ukrainian composer, sergei prokofiev

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1296 Efficacy and Safety of Computerized Cognitive Training Combined with SSRIs for Treating Cognitive Impairment Among Patients with Late-Life Depression: A 12-Week, Randomized Controlled Study

Authors: Xiao Wang, Qinge Zhang

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Background: This randomized, open-label study examined the therapeutic effects of computerized cognitive training (CCT) combined with selective serotonin reuptake inhibitors (SSRIs) on cognitive impairment among patients with late-life depression (LLD). Method: Study data were collected from May 5, 2021, to April 21, 2023. Outpatients who met diagnostic criteria for major depressive disorder according to the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria (i.e., a total score on the 17-item Hamilton Depression Rating Scale (HAMD-17) ≥ 18 and a total score on the Montreal Cognitive Assessment scale (MOCA) <26) were randomly assigned to receive up to 12 weeks of CCT and SSRIs treatment (n=57) or SSRIs and Control treatment (n=61). The primary outcome was the change in Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores from baseline to week 12 between the two groups. The secondary outcomes included changes in the HAMD-17 score, Hamilton Anxiety Scale (HAMA) score and Neuropsychiatric Inventory (NPI) score. Mixed model repeated measures (MMRM) analysis was performed on modified intention-to-treat (mITT) and completer populations. Results: The full analysis set (FAS) included 118 patients (CCT and SSRIs group, n=57; SSRIs and Control group, n =61). Over the 12-week study period, the reduction in the ADAS-cog total score was significant (P < 0.001) in both groups, while MMRM analysis revealed a significantly greater reduction in cognitive function (ADAS-cog total scores) from baseline to posttreatment in the CCT and SSRIs group than in the SSRI and Control group [(F (1,115) =13.65, least-squares mean difference [95% CI]: −2.77 [−3.73, −1.81], p<0.001)]. There were significantly greater improvements in depression symptoms (measured by the HAMD-17) in the CCT and SSRIs group than in the control group [MMRM, estimated mean difference (SE) between groups −3.59 [−5.02, −2.15], p < 0.001]. The least-squares mean changes in the HAMA scores and NPI scores between baseline and week 8 were greater in the CCT and SSRIs group than in the control group (all P < 0.05). There was no significant difference between groups on response rates and remission rates by using the last-observation-carried-forward (LOCF) method (all P > 0.05). The most frequent adverse events (AEs) in both groups were dry mouth, somnolence, and constipation. There was no significant difference in the incidence of adverse events between the two groups. Conclusions: CCT combined with SSRIs was efficacious and well tolerated in LLD patients with cognitive impairment.

Keywords: late-life depression, cognitive function, computerized cognitive training, SSRIs

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1295 Combining Laser Scanning and High Dynamic Range Photography for the Presentation of Bloodstain Pattern Evidence

Authors: Patrick Ho

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Bloodstain Pattern Analysis (BPA) forensic evidence can be complex, requiring effective courtroom presentation to ensure clear and comprehensive understanding of the analyst’s findings. BPA witness statements can often involve reference to spatial information (such as location of rooms, objects, walls) which, when coupled with classified blood patterns, may illustrate the reconstructed movements of suspects and injured parties. However, it may be difficult to communicate this information through photography alone, despite this remaining the UK’s established method for presenting BPA evidence. Through an academic-police partnership between the University of Warwick and West Midlands Police (WMP), an integrated 3D scanning and HDR photography workflow for BPA was developed. Homicide scenes were laser scanned and, after processing, the 3D models were utilised in the BPA peer-review process. The same 3D models were made available for court but were not always utilised. This workflow has improved the ease of presentation for analysts and provided 3D scene models that assist with the investigation. However, the effects of incorporating 3D scene models in judicial processes may need to be studied before they are adopted more widely. 3D models from a simulated crime scene and West Midlands Police cases approved for conference disclosure are presented. We describe how the workflow was developed and integrated into established practices at WMP, including peer-review processes and witness statement delivery in court, and explain the impact the work has had on the Criminal Justice System in the West Midlands.

Keywords: bloodstain pattern analysis, forensic science, criminal justice, 3D scanning

Procedia PDF Downloads 75
1294 Effect of Leptin Gene Methylation on Colorectal Cancer Chemoresistance

Authors: Wissem Abdaoui, Nizar M. Mhaidat, Ilhem Mokhtari, Adel Gouri

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Colorectal cancer (CRC) is one of the most common tumors all over the world. Obesity, considered a risk factor of CRC, is characterized by a high level of secreted cytokines from adipose tissue. Among these inflammatory molecules, leptin is considered the key mediator for CRC cancer development and progression by activation of mitogenic and anti apoptotic signaling pathways. Gene expression can be significantly modulated by alterations in DNA methylation patterns. The aim of this study is to investigate the impact of leptin gene methylation on CRC prognosis and sensitivity to chemotherapy. The study involved 70 CRC tissue samples collected from King Abdullah University Hospital (KAUH) from which only 53 was analyzed because of bisulfate fragmentation and low yield of DNA extracted from FFPE tissues. A total of 22 blood samples were collected from healthy volunteers and enrolled as a control group. Leptin promoter methylation was analyzed by methylation specific PCR after bisulfate conversion. Results revealed that the incidence of leptin gene methylation was significantly higher in CRC patients in comparison to that of controls (P < 0.05). The correlation between patient’s demographics and leptin gene methylation was not significant (P < 0.05). However, a significant correlation between leptin gene methylation status and early cancer stages (I, II and III) was found in male but not in female (p < 0.05). Moreover, a significant correlation was found between leptin promoter methylation and early tumor localization T1-2 (p < 0.05). The correlation between epigenetic regulation of leptin and chemosensitivity was not significant. Taken together, these results suggest the possibility to use leptin gene methylation as a biomarker for the evaluation of CRC prognosis and metastasis.

Keywords: colorectal cancer, obesity, leptin, DNA methylation, disease prognosis, bisulfate conversion, chemoresistance

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1293 Analyzing the Usage of Social Media: A Study on Elderly in Malaysia

Authors: Chan Eang Teng, Tang Mui Joo

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In the beginning of the prevalence of social media, it would be an obvious trend that the young adult age group has the highest population among the users on social media. However, apart from the age group of the users are becoming younger and younger, the elderly group has become a new force on social media, and this age group has increased rapidly. On top of that, the influence of social media towards the elderly is becoming more significant and it is even trending among them. This is because basic computer knowledge is not instilled into their life when they were young. This age group tends to be engrossed more than the young as this is something new for them, and they have the mindset that it is a new platform to approach things, and they tend to be more engrossed when they start getting in touch with the social media. Generally, most of the social media has been accepted and accessed by teenagers and young adult, but it is reasonable to believe that the social media is not really accepted among the elderly. Surprisingly, the elderlies are more addicted to the social media than the teenagers. Therefore, this study is to determine and understand the relationship between the elderly and social media, and how they employ social media in their lives. An online survey on 200 elderly aged 45-80 and an interview with a media expert are conducted to answer the main questions in the research paper. Uses and Gratification Approach is employed in theoretical framework. Finding revealed that majority of the respondents use social media to connect with family, friends, and for leisure purposes. The finding concluded that the elderly use social media differently according to their needs and wants which is in par with the highlight of Uses and Gratification theory. Considering the significantly large role social media plays in our culture and daily life today, the finding will shed some light on the effect of social media on the elderly or senior citizens who are usually relegated into a minority group in today’s age where the internet and social media are of great importance to our society and humanity in general. This may also serve to be useful in understanding behavioral patterns and preference in terms of social media usage among the elderly.

Keywords: elderly, Facebook, Malaysia, social media

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1292 Electricity Price Forecasting: A Comparative Analysis with Shallow-ANN and DNN

Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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1291 Medication Side Effects: Implications on the Mental Health and Adherence Behaviour of Patients with Hypertension

Authors: Irene Kretchy, Frances Owusu-Daaku, Samuel Danquah

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Hypertension is the leading risk factor for cardiovascular diseases, and a major cause of death and disability worldwide. This study examined whether psychosocial variables influenced patients’ perception and experience of side effects of their medicines, how they coped with these experiences and the impact on mental health and medication adherence to conventional hypertension therapies. Methods: A hospital-based mixed methods study, using quantitative and qualitative approaches was conducted on hypertensive patients. Participants were asked about side effects, medication adherence, common psychological symptoms, and coping mechanisms with the aid of standard questionnaires. Information from the quantitative phase was analyzed with the Statistical Package for Social Sciences (SPSS) version 20. The interviews from the qualitative study were audio-taped with a digital audio recorder, manually transcribed and analyzed using thematic content analysis. The themes originated from participant interviews a posteriori. Results: The experiences of side effects – such as palpitations, frequent urination, recurrent bouts of hunger, erectile dysfunction, dizziness, cough, physical exhaustion - were categorized as no/low (39.75%), moderate (53.0%) and high (7.25%). Significant relationships between depression (x 2 = 24.21, P < 0.0001), anxiety (x 2 = 42.33, P < 0.0001), stress (x 2 = 39.73, P < 0.0001) and side effects were observed. A logistic regression model using the adjusted results for this association are reported – depression [OR = 1.9 (1.03 – 3.57), p = 0.04], anxiety [OR = 1.5 (1.22 – 1.77), p = < 0.001], and stress [OR = 1.3 (1.02 – 1.71), p = 0.04]. Side effects significantly increased the probability of individuals to be non-adherent [OR = 4.84 (95% CI 1.07 – 1.85), p = 0.04] with social factors, media influences and attitudes of primary caregivers further explaining this relationship. The personal adoption of medication modifying strategies, espousing the use of complementary and alternative treatments, and interventions made by clinicians were the main forms of coping with side effects. Conclusions: Results from this study show that contrary to a biomedical approach, the experience of side effects has biological, social and psychological interrelations. The result offers more support for the need for a multi-disciplinary approach to healthcare where all forms of expertise are incorporated into health provision and patient care. Additionally, medication side effects should be considered as a possible cause of non-adherence among hypertensive patients, thus addressing this problem from a Biopsychosocial perspective in any intervention may improve adherence and invariably control blood pressure.

Keywords: biopsychosocial, hypertension, medication adherence, psychological disorders

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1290 Insects and Meteorological Inventories in a Mango-Based Agroforestry System in Bangladesh

Authors: Md. Ruhul Amin, Shakura Namni, Md. Ramiz Uddin Miah, Md. Giashuddin Miah, Mohammad Zakaria, Sang Jae Suh, Yong Jung Kwon

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Insect species abundance and diversity associated with meteorological factors during January to June 2013 at a mango-based agroforestry research field in Bangladesh, and the effects of pests and pollinator species on mango are presented in this study. Among the collected and identified insects, nine species belong to 3 orders were found as pollinator, 11 species in 5 orders as pest, and 13 species in 6 orders as predator. The mango hopper, fruit fly and stone weevil appeared as major pest because of their high levels of abundance and infestation. The hoppers caused 100% inflorescence damage followed by fruit fly (51.7% fruit) and stone weevil (31.0% mature fruit). The major pests exerted significantly higher abundance compared to pollinator, predator and minor pests. Hemipteroid insects were most abundant (60%) followed by Diptera (21%), Hymenoptera (10%), Lepidoptera (5%), and Coleoptera (4%). Insect population increased with increasing trend of temperature and humidity, and revealed peak abundance during April-May. The flower visiting insects differed in their landing duration and showed preference to forage with time of a day. Their foraging activity was found to be peaked between 11.00 am to 01.00 pm. The activity of the pollinators led to higher level of fruit set. This study provides baseline information about the phenological patterns of insect abundance in an agroforestry research field which could be an indication to incorporate some aspects of pest management.

Keywords: agroforestry, abundance, abiotic factors, insects, mango

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1289 An As-Is Analysis and Approach for Updating Building Information Models and Laser Scans

Authors: Rene Hellmuth

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring of the factory building is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A building information model (BIM) is the planning basis for rebuilding measures and becomes an indispensable data repository to be able to react quickly to changes. Use as a planning basis for restructuring measures in factories only succeeds if the BIM model has adequate data quality. Under this aspect and the industrial requirement, three data quality factors are particularly important for this paper regarding the BIM model: up-to-dateness, completeness, and correctness. The research question is: how can a BIM model be kept up to date with required data quality and which visualization techniques can be applied in a short period of time on the construction site during conversion measures? An as-is analysis is made of how BIM models and digital factory models (including laser scans) are currently being kept up to date. Industrial companies are interviewed, and expert interviews are conducted. Subsequently, the results are evaluated, and a procedure conceived how cost-effective and timesaving updating processes can be carried out. The availability of low-cost hardware and the simplicity of the process are of importance to enable service personnel from facility mnagement to keep digital factory models (BIM models and laser scans) up to date. The approach includes the detection of changes to the building, the recording of the changing area, and the insertion into the overall digital twin. Finally, an overview of the possibilities for visualizations suitable for construction sites is compiled. An augmented reality application is created based on an updated BIM model of a factory and installed on a tablet. Conversion scenarios with costs and time expenditure are displayed. A user interface is designed in such a way that all relevant conversion information is available at a glance for the respective conversion scenario. A total of three essential research results are achieved: As-is analysis of current update processes for BIM models and laser scans, development of a time-saving and cost-effective update process and the conception and implementation of an augmented reality solution for BIM models suitable for construction sites.

Keywords: building information modeling, digital factory model, factory planning, restructuring

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1288 A Comprehensive Study of Spread Models of Wildland Fires

Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

Procedia PDF Downloads 67
1287 Minimizing thought Communication Gap between Designer and Client Using the Projective Personality Tests

Authors: Hira, Nisar Bhatti, Ezza

Abstract:

Contemporary studies support the strong co-relation between psychology and design. This study elaborates how different psychological personality test can help a fashion designer to judge the needs of their clients with respect to the customized clothing. This study will also help the designer to improve the lacking in the personality and will enable him to put his effort in required areas for grooming the customer. The use of psychology test to support the choice of certain design strategies that how the right clothing can make client a better intellectual with enhanced self-esteem and confidence. Different projective personality test are being used to suggest to evaluate personality traits. The Rorschach Inkblot Test is projective mental comprising of 10 ink-blots synonymous with the clinical brain research. Lüsher Color Diagnostics measures a person’s psycho physical state, his or her ability to withstand stress to perform and communicate. HTP is a projective responsibility test measuring self-perception, attitudes. The TAT test intend to evaluate a person’s patterns of thoughts, attitudes, observation, capacity and emotional response to this ambiguous test materials. No doubt designers are already crucially redesigning the individuals by their attires, but to expose the behavioral mechanism of the customer, designers should be able to recognize the hidden complexity behind his client by using the above mentioned methods. The study positively finds the design and psychology need to become substantially contacted in order to create a new regime of norms to groom a personality under the concentration and services of a fashion designer in terms of clothing.

Keywords: projective personality tests, customized clothing, Rorschach Inkblot Test, TAT, HTP, Lüsher Color Diagnostics

Procedia PDF Downloads 537
1286 Empowering Indigenous Epistemologies in Geothermal Development

Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

Abstract:

Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

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1285 Urban Waste Management for Health and Well-Being in Lagos, Nigeria

Authors: Bolawole F. Ogunbodede, Mokolade Johnson, Adetunji Adejumo

Abstract:

High population growth rate, reactive infrastructure provision, inability of physical planning to cope with developmental pace are responsible for waste water crisis in the Lagos Metropolis. Septic tank is still the most prevalent waste-water holding system. Unfortunately, there is a dearth of septage treatment infrastructure. Public waste-water treatment system statistics relative to the 23 million people in Lagos State is worrisome. 1.85 billion Cubic meters of wastewater is generated on daily basis and only 5% of the 26 million population is connected to public sewerage system. This is compounded by inadequate budgetary allocation and erratic power supply in the last two decades. This paper explored community participatory waste-water management alternative at Oworonshoki Municipality in Lagos. The study is underpinned by decentralized Waste-water Management systems in built-up areas. The initiative accommodates 5 step waste-water issue including generation, storage, collection, processing and disposal through participatory decision making in two Oworonshoki Community Development Association (CDA) areas. Drone assisted mapping highlighted building footage. Structured interviews and focused group discussion of land lord associations in the CDA areas provided collaborator platform for decision-making. Water stagnation in primary open drainage channels and natural retention ponds in framing wetlands is traceable to frequent of climate change induced tidal influences in recent decades. Rise in water table resulting in septic-tank leakage and water pollution is reported to be responsible for the increase in the water born infirmities documented in primary health centers. This is in addition to unhealthy dumping of solid wastes in the drainage channels. The effect of uncontrolled disposal system renders surface waters and underground water systems unsafe for human and recreational use; destroys biotic life; and poisons the fragile sand barrier-lagoon urban ecosystems. Cluster decentralized system was conceptualized to service 255 households. Stakeholders agreed on public-private partnership initiative for efficient wastewater service delivery.

Keywords: health, infrastructure, management, septage, well-being

Procedia PDF Downloads 155
1284 Secularization of Europe and the Rise of Nationalism

Authors: Sterling C. DeVerter

Abstract:

In recent decades, there has been continually growing concern amongst scholars and political leaders towards the global resurgence of nationalism, particularly in Europe, the United States, and China. However, very few studies have attempted to empirically examine the relationship between religion and nationalism at the level of the individual, and none are known to have done so quantitatively. Building on Tajfel's and Turner's (1978) Social Identity Theory (SIT), and Anderson (1991) and Marx (2003), this study will employ SIT and regression analysis to compare the sources and patterns of nationalistic sentiment among European respondents in eight countries to the average levels of self-reported religiosity, religious participation, age, education, and income levels. Survey reports from the International Social Survey Programme were the primary quantitative data sources. It was hypothesized that the increase in nationalism across Europe follows this same evolution as first identified by Anderson, and is positively correlated to the reduction in reported religiosity. However, this study failed to reject the null, there was no substantial ( < .035) correlation between nationalistic sentiment and any of the measures of religiosity, nor were there any substantial correlations between nationalistic sentiment and either of the three control variables ( < .008). Across all countries examined, it was discovered that inclusionary nationalism has slightly declined (-5.08%), while exclusionary nationalism had increased substantially (+17.25%). The combined trend reflected an overall rise in nationalism across the time period and a forecast that suggests the current levels are also elevated. The primary implications include the demand to readdress the notion of religion and nationalism, and the correlation between the two, as well as the current nationalism trends in terms of support or non-support for future political and social movements.

Keywords: European Union, secularization, nationalism, social identity theory

Procedia PDF Downloads 109
1283 Geochemistry and Petrogenesis of Anorogenic Acid Plutonic Rocks of Khanak and Devsar of Southwestern Haryana

Authors: Naresh Kumar, Radhika Sharma, A. K. Singh

Abstract:

Acid plutonic rocks from the Khanak and Devsar areas of southwestern Haryana were investigated to understand their geochemical and petrogenetic characteristics and tectonic environments. Three dominant rock types (grey, grayish green and pink granites) are the principal geochemical features of Khanak and Devsar areas which reflect the dependencies of their composition on varied geological environment during the anorogenic magmatism. These rocks are enriched in SiO₂, Na₂O+K₂O, Fe/Mg, Rb, Zr, Y, Th, U, REE (Rare Earth Elements) enriched and depleted in MgO, CaO, Sr, P, Ti, Ni, Cr, V and Eu and exhibit a clear affinity to the within-plate granites that were emplaced in an extensional tectonic environment. Chondrite-normalized REE patterns show enriched LREE (Light Rare Earth Elements), moderate to strong negative Eu anomalies and flat heavy REE and grey and grayish green is different from pink granite which is enriched by Rb, Ga, Nb, Th, U, Y and HREE (Heavy Rare Earth Elements) concentrations. The composition of parental magma of both areas corresponds to mafic source contaminated with crustal materials. Petrogenetic modelling suggest that the acid plutonic rocks might have been generated from a basaltic source by partial melting (15-25%) leaving a residue with 35% plagioclase, 25% alkali feldspar, 25% quartz, 7% orthopyroxene, 5% biotite and 3% hornblende. Granites from both areas might be formed from different sources with different degree of melting for grey, grayish green and pink granites.

Keywords: A-type granite, anorogenic, Malani igneous suite, Khanak and Devsar

Procedia PDF Downloads 157
1282 An Exploration of Nursing Assistants' Continuing Professional Development (CPD) Engagement in a Acute Healthcare Setting: A Qualitative Case Study Pilot in England

Authors: Ana Fouto

Abstract:

Background: Continuing Personal Development (CPD) enables professionals to keep up to date with the professional requirements, broadening their knowledge and expertise. However, much of the research explores the registered professionals’ experiences and the factors that influence their choice of engaging, despite the unregistered staff providing the majority of the direct patient care. Aim: To explore the Nursing/Midwifery Assistants’ (NAs) perception of the concept of CPD, as well as explore the factors that influence the NAs to engage (or not) with CPD experiences. Methodology: This pilot study used a qualitative approach through a case study, where a semi-structured interview was applied to three NAs to explore the factors that influence the decision-making of process of CPD engagement. Thematic analysis was used to analyse their answers and interpret patterns and associations. Findings: All the participants agreed that CPD is important and relevant to their practice and personal lives. Five main categories were identified: NAs’ scope of practice, the impact of CPD; decision-making process; challenges; changes required. Although similar findings to the registered nurses were identified, the lack of CPD regulation for NAs and the rapid evolution of their role make the CPD engagement more problematic. Conclusion: Engagement with CPD is influenced by a wide range of professional (organisational and national) and personal factors. NAs perceive lack of management support at different stages of the CPD activities as a main influence. Organisations should be more flexible in the recruitment, offer of CPD choices, content, delivery, and contractual arrangements of NAs, which may increase engagement.

Keywords: nursing assistants, engagement, factors, pilot, continuing professional development (CPD)

Procedia PDF Downloads 139
1281 Modelling the Antecedents of Supply Chain Enablers in Online Groceries Using Interpretive Structural Modelling and MICMAC Analysis

Authors: Rose Antony, Vivekanand B. Khanapuri, Karuna Jain

Abstract:

Online groceries have transformed the way the supply chains are managed. These are facing numerous challenges in terms of product wastages, low margins, long breakeven to achieve and low market penetration to mention a few. The e-grocery chains need to overcome these challenges in order to survive the competition. The purpose of this paper is to carry out a structural analysis of the enablers in e-grocery chains by applying Interpretive Structural Modeling (ISM) and MICMAC analysis in the Indian context. The research design is descriptive-explanatory in nature. The enablers have been identified from the literature and through semi-structured interviews conducted among the managers having relevant experience in e-grocery supply chains. The experts have been contacted through professional/social networks by adopting a purposive snowball sampling technique. The interviews have been transcribed, and manual coding is carried using open and axial coding method. The key enablers are categorized into themes, and the contextual relationship between these and the performance measures is sought from the Industry veterans. Using ISM, the hierarchical model of the enablers is developed and MICMAC analysis identifies the driver and dependence powers. Based on the driver-dependence power the enablers are categorized into four clusters namely independent, autonomous, dependent and linkage. The analysis found that information technology (IT) and manpower training acts as key enablers towards reducing the lead time and enhancing the online service quality. Many of the enablers fall under the linkage cluster viz., frequent software updating, branding, the number of delivery boys, order processing, benchmarking, product freshness and customized applications for different stakeholders, depicting these as critical in online food/grocery supply chains. Considering the perishability nature of the product being handled, the impact of the enablers on the product quality is also identified. Hence, study aids as a tool to identify and prioritize the vital enablers in the e-grocery supply chain. The work is perhaps unique, which identifies the complex relationships among the supply chain enablers in fresh food for e-groceries and linking them to the performance measures. It contributes to the knowledge of supply chain management in general and e-retailing in particular. The approach focus on the fresh food supply chains in the Indian context and hence will be applicable in developing economies context, where supply chains are evolving.

Keywords: interpretive structural modelling (ISM), India, online grocery, retail operations, supply chain management

Procedia PDF Downloads 190
1280 Molecular Characterization and Identification of C-Type Lectin in Red Palm Weevil, Rhynchophorus ferrugineus Oliver

Authors: Hafiza Javaria Ashraf, Xinghong Wang, Zhanghong Shi, Youming Hou

Abstract:

Insect’s innate immunity depends on a variety of defense responses for the recognition of invading pathogens. Pathogen recognition involves particular proteins known as pattern recognition receptors (PRRs). These PRRs interact with pathogen-associated molecular patterns (PAMPs) present on the surface of pathogens to distinguish between self and non-self. C-type lectins (CTLs) belong to a superfamily of PPRs which involved in insect immunity and defense mechanism. Rhynchophorus ferrugineus Olivier is a devastating pest of Palm cultivations in China. Although studies on R. ferrugineus immune mechanism and host defense have conducted, however, the role of CTL in immune responses of R. ferrugineus remains elusive. Here, we report RfCTL, which is a secreted protein containing a single-CRD domain. The open reading frame (ORF) of CTL is 226 bp, which encodes a putative protein of 168 amino acids. Transcript expression analysis revealed that RfCTL highly expressed in immune-related tissues, i.e., hemolymph and fat body. The abundance of RfCTL in the gut and fat body dramatically increased upon Staphylococcus aureus and Escherichia coli bacterial challenges, suggesting a role in defense against gram-positive and gram-negative bacterial infection. Taken together, we inferred that RfCTL might be involved in the immune defense of R. ferrugineus and established a solid foundation for future studies on R. ferrugineus CTL domain proteins for better understanding of insect immunity.

Keywords: biological invasion, c-type lectin, insect immunity, Rhynchophorus ferrugineus Oliver

Procedia PDF Downloads 134
1279 Investigating the Effect of the Psychoactive Substances Act 2016 on the Incidence of Adverse Medical Events in Her Majesty’s Prison (HMP) Leeds

Authors: Hayley Boal, Chloe Bromley, John Fairfield

Abstract:

Novel Psychoactive Substances (NPS) are synthetic compounds designed to reproduce effects of illicit drugs. Cheap, potent, and readily available on UK highstreets from so-called ‘head shops’, in recent years their use has surged and with it have emerged side effects including seizures, aggression, palpitations, coma, and death. Rapid development of new substances has vastly outpaced pre-existing drug legislation but the Psychoactive Substances Act 2016 rendered all but tobacco, alcohol, and amyl nitrates, illegal. Drug use has long been rife within prisons, but the absence of a reliable screening tool alongside the availability of NPS makes them ideal for prison use. Here we examine the occurrence of NPS-related adverse side effects within HMP Leeds, comparing May-September of 2015 and 2017 using daily reports distributed amongst prison staff summarising medical and behavioural incidents of the previous day. There was a statistically-significant rise of over 200% in the use of NPS between 2015 and 2017: 0.562 and 1.149 incidents per day respectively. In 2017, 38.46% incidents required ambulances, fallen from 51.02% in 2015. Although the most common descriptions in both years were ‘seizure’ and ‘unresponsive’, by 2017 ‘inhalation by staff’ had emerged. Patterns of NPS consumption mirrored the prison regime, peaking when cell doors opened, and prisoners could socialise. Despite limited data, the Psychoactive Substances Act has clearly been an insufficient deterrent to the prison population; more must be done to understand and address substance misuse in prison. NPS remains a significant risk to prisoners’ health and wellbeing.

Keywords: legislation, novel psychoactive substances, prison, spice

Procedia PDF Downloads 172
1278 A Study on the Effects of Urban Density, Sociodemographic Vulnerability, and Medical Service on the Impact of COVID-19

Authors: Jang-hyun Oh, Kyoung-ho Choi, Jea-sun Lee

Abstract:

The outbreak of the COVID-19 pandemic brought reconsiderations and doubts about urban density as compact cities became epidemic hot spots. Density, though, provides an upside in that medical services required to protect citizens against the spread of disease are concentrated within compact cities, which helps reduce the mortality rate. Sociodemographic characteristics are also a crucial factor in determining the vulnerability of the population, and the purpose of this study is to empirically discover how these three urban factors affect the severity of the epidemic impacts. The study aimed to investigate the influential relationships between urban factors and epidemic impacts and provide answers to whether superb medical service in compact cities can scale down the impacts of COVID-19. SEM (Structural Equation Modeling) was applied as a suitable research method for verifying interrelationships between factors based on theoretical grounds. The study accounted for 144 municipalities in South Korea during periods from the first emergence of COVID-19 to December 31st, 2022. The study collected data related to infection and mortality cases from each municipality, and it holds significance as primary research that enlightens the aspects of epidemic impact concerning urban settings and investigates for the first time the mediated effects of medical service. The result of the evaluation shows that compact cities are most likely to have lower sociodemographic vulnerability and better quality of medical service, while cities with low density contain a higher portion of vulnerable populations and poorer medical services. However, the quality of medical service had no significant influence in reducing neither the infection rate nor the mortality rate. Instead, density acted as the major influencing factor in the infection rate, while sociodemographic vulnerability was the major determinant of the mortality rate. Thus, the findings strongly paraphrase that compact cities, although with high infection rates, tend to have lower mortality rates due to less vulnerability in sociodemographics, Whereas death was more frequent in less dense cities due to higher portions of vulnerable populations such as the elderly and low-income classes. Findings suggest an important lesson for post-pandemic urban planning-intrinsic characteristics of urban settings, such as density and population, must be taken into account to effectively counteract future epidemics and minimize the severity of their impacts. Moreover, the study is expected to contribute as a primary reference material for follow-up studies that further investigate related subjects, including urban medical services during the pandemic.

Keywords: urban planning, sociodemographic vulnerability, medical service, COVID-19, pandemic

Procedia PDF Downloads 43
1277 Analyzing Changes in Runoff Patterns Due to Urbanization Using SWAT Models

Authors: Asawari Ajay Avhad

Abstract:

The Soil and Water Assessment Tool (SWAT) is a hydrological model designed to predict the complex interactions within natural and human-altered watersheds. This research applies the SWAT model to the Ulhas River basin, a small watershed undergoing urbanization and characterized by bowl-like topography. Three simulation scenarios (LC17, LC22, and LC27) are investigated, each representing different land use and land cover (LULC) configurations, to assess the impact of urbanization on runoff. The LULC for the year 2027 is generated using the MOLUSCE Plugin of QGIS, incorporating various spatial factors such as DEM, Distance from Road, Distance from River, Slope, and distance from settlements. Future climate data is simulated within the SWAT model using historical data spanning 30 years. A susceptibility map for runoff across the basin is created, classifying runoff into five susceptibility levels ranging from very low to very high. Sub-basins corresponding to major urban settlements are identified as highly susceptible to runoff. With consideration of future climate projections, a slight increase in runoff is forecasted. The reliability of the methodology was validated through the identification of sub-basins known for experiencing severe flood events, which were determined to be highly susceptible to runoff. The susceptibility map successfully pinpointed these sub-basins with a track record of extreme flood occurrences, thus reinforcing the credibility of the assessment methodology. This study suggests that the methodology employed could serve as a valuable tool in flood management planning.

Keywords: future land use impact, flood management, run off prediction, ArcSWAT

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1276 The Impact of Neuroscience Knowledge on the Field of Education

Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

Abstract:

Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

Procedia PDF Downloads 45
1275 Land Suitability Prediction Modelling for Agricultural Crops Using Machine Learning Approach: A Case Study of Khuzestan Province, Iran

Authors: Saba Gachpaz, Hamid Reza Heidari

Abstract:

The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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1274 Symmetric Key Encryption Algorithm Using Indian Traditional Musical Scale for Information Security

Authors: Aishwarya Talapuru, Sri Silpa Padmanabhuni, B. Jyoshna

Abstract:

Cryptography helps in preventing threats to information security by providing various algorithms. This study introduces a new symmetric key encryption algorithm for information security which is linked with the "raagas" which means Indian traditional scale and pattern of music notes. This algorithm takes the plain text as input and starts its encryption process. The algorithm then randomly selects a raaga from the list of raagas that is assumed to be present with both sender and the receiver. The plain text is associated with the thus selected raaga and an intermediate cipher-text is formed as the algorithm converts the plain text characters into other characters, depending upon the rules of the algorithm. This intermediate code or cipher text is arranged in various patterns in three different rounds of encryption performed. The total number of rounds in the algorithm is equal to the multiples of 3. To be more specific, the outcome or output of the sequence of first three rounds is again passed as the input to this sequence of rounds recursively, till the total number of rounds of encryption is performed. The raaga selected by the algorithm and the number of rounds performed will be specified at an arbitrary location in the key, in addition to important information regarding the rounds of encryption, embedded in the key which is known by the sender and interpreted only by the receiver, thereby making the algorithm hack proof. The key can be constructed of any number of bits without any restriction to the size. A software application is also developed to demonstrate this process of encryption, which dynamically takes the plain text as input and readily generates the cipher text as output. Therefore, this algorithm stands as one of the strongest tools for information security.

Keywords: cipher text, cryptography, plaintext, raaga

Procedia PDF Downloads 272