Search results for: event extraction and understanding

Authors: Mariko Hara, Mari Aoki, Takako Ito, Masao Sugita

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Social distancing measures due to the COVID-19 crisis had a severe impact on music and art practices based in community settings. They had to re-think how to connect with their dispersed community using online tools. As the social distancing continues, there is an urgent need to investigate the possibilities of online community music and art practices. Are they sustainable actions that can have positive impacts on the community and the quality of lives of people over time? The Online Lindgren Café (hereafter ‘OLC’) is a monthly online literature event which started in June 2020. In the OLC, up to 14 members meet online to discuss the works of Astrid Lindgren and similar authors. Members come from various places in Japan and Norway, with a variety of expertise from music therapy, music education, psychotherapy, music sociology, storytelling, and theatre, and their family members join them. In these meetings, music and arts activities emerged in response to interests among the members. The resources and experiences of the members helped to develop these activities further. This paper first introduces one of the music and art activities in one specific event, a collaborative picture book-making with music, which was initiated and led by the second author. The third author chose the music, and the activity itself was recorded. This is followed by the description of a reflecting event, where the recording of the collaborative picture book-making activity was shared to facilitate further creations (drawings, haiku, and fabric weaving) as well as group reflections on the trajectories of the Online Lindgren Café. Finally, we will discuss the preliminary findings using the data collected at the reflecting event. Key findings suggest that the resource-driven approach of the OLC leveled the relationships among the intergenerational, multi-cultural, and interdisciplinary members. This enabled the members to set aside their professional and/or predominant identities, which allowed them to discover their own and others’ resources. The relaxed, unstructured, and liminal phenomenon at OLC can be regarded as a form of communitas, where members gain a sense of liberation and belonging in a different way from in-person communications. Participation from one’s home, as well as a video conferencing function that allowed the members to position themselves among the other participants in equal-sized windows, seems to have enabled members to feel safe to express themselves openly at the same time feel a sense of belonging. Furthermore, in the OLC, music and arts activities acted to inclusively connect and re-connect dispersed, intergenerational members with each other. For instance, in a music and drawing activity, music acted as a means for each member to engage in their own ‘drawing space’ while still feeling connected with the others. The positive experiences from these activities inspired the members to use similar approaches outside of the OLC. The finding suggests that, because of its resource-driven approach supported by the music and arts activities, the OLC could be developed further as a permeable and sustainable action even after any current social distancing measures are lifted.

Keywords: communitas, COVID-19, musical affordances, online community of practices, resource-driven approach

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Claudio Díaz, Mabel Ortiz

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An EFL teacher education programme in Chile takes five years to train a future teacher of English. Preservice teachers are prepared to learn an advanced level of English and teach the language from 5th to 12th grade in the Chilean educational system. In the context of their first EFL Methodology course in year four, preservice teachers have to create a five-minute digital story that starts from a critical incident they have experienced as teachers-to-be during their observations or interventions in the schools. A critical incident can be defined as a happening, a specific incident or event either observed by them or involving them. The happening sparks their thinking and may make them subsequently think differently about the particular event. When they create their digital stories, preservice teachers put technology, teaching practice and theory together to narrate a story that is complemented by still images, moving images, text, sound effects and music. The story should be told as a personal narrative, which explains the critical incident. This presentation will focus on the creation process of 50 Chilean preservice teachers’ digital stories highlighting the critical incidents they started their stories. It will also unpack preservice teachers’ beliefs and reflections when approaching their teaching practices in schools. These beliefs will be coded and categorized through content analysis to evidence preservice teachers’ most rooted conceptions about English teaching and learning in Chilean schools. The findings seem to indicate that preservice teachers’ beliefs are strongly mediated by contextual and affective factors.

Keywords: beliefs, digital stories, preservice teachers, practicum

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Authors: Muhammad Ahmad

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In this research, Chrysanthemum (morifolium) flowers are used as a natural dye to reduce synthetic dyes and take a step toward sustainability in the fashion industry. The aqueous extraction method is utilized for natural dye extraction and then applied to silk and cotton fabric samples. The color of the dye extracted from dried chrysanthemum flowers is originally a shade of rich green, but after being washed with detergent, it turns to a shade of yellow. Traditional salt and vinegar are used as a natural mordant to fix the dye color. This study also includes a phenolic and chemical analysis of the natural dye (Chrysanthemum flowers) and the textiles (cotton and silk). Compared to cotton fabric, silk fabric has far superior chemical qualities to use in natural dyeing. The results of this study show that the Chrysanthemum flower offers a variety of colors when treated with detergent, without detergent, and with mordants. Chrysanthemum flowers have long been used in other fields, such as medicine; therefore, it is time to start using them in the fashion industry as a natural dye to lessen the harm that synthetic dyes cause.

Keywords: natural dyes, Chrysanthemum flower, sustainability, textile fabrics, chemical and phenolic analysis

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Authors: Khandoker Akib Mohammad

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While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

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Authors: Nuo Xu, Sijing Chen

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Background: Childbirth is considered a critical traumatic event throughout our lives, positively or negatively impacting the mother's physiology, psychology, and even the whole family. Adverse birth experiences, such as labor pain, anxiety, and fear can negatively impact the mother. Studies had shown that the immersive nature of VR can distract attention from pain and increase focus on interventions for pain relief. However, the existing studies that applied VR to maternal delivery were still in their infancy and showed disparate results, and the small sample size is not representative, so this review analyzed the effects of VR in labor, such as on maternal pain and anxiety, with a view to providing a basis for future applications. Search strategy: We searched Pubmed, Embase, Web of Science, the Cochrane Library, CINAHL, China National Knowledge Infrastructure, Wan-Fang database from the building to November 17, 2021. Selection Criteria: Randomized controlled trials (RCTs) that intervened the pregnant women aged 18-35 years with gestational >34 weeks and without complications with VR technology were contained within this review. Data Collection and Analysis: Two researchers completed the study selection, data extraction, and assessment of study quality. For quantitative data we used MD or SMD, and RR (risk ratio) for qualitative data. Random-effects model and 95% confidence interval (95% CI) were used. Main Results: 12 studies were included. Using VR could relieve pain during labor (MD=-1.81, 95% CI (-2.04, -1.57), P< 0.00001) and active period (SMD=-0.41, 95% CI (-0.68, -0.14), P= 0.003), reduce anxiety (SMD=-1.39, 95% CI (-1.99, -0.78), P< 0.00001) and improve satisfaction (RR = 1.32; 95% CI (1.10, 1.59); P = 0.003), but the effect on the duration of first (SMD=-1.12, 95% CI (-2.38, 0.13), P=0.08) and second (SMD=-0.22, 95% CI (-0.67, 0.24), P=0.35) stage of labor was not statistically significant. Conclusions: Compared with conventional care, VR technology can relieve labor pain and anxiety and improve satisfaction. However, extensive experimental validation is still needed.

Keywords: virtual reality, delivery, labor pain, anxiety, meta-analysis, systematic review

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Authors: Afiq Mohd Fahmi, Tony Gutierrez, Sebastian Hennige

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Increasing amounts of CO₂ entering the marine environment, also known as ocean acidification, is documented as having harmful impacts on a variety of marine organisms. When considering the future risk of hydrocarbon pollution, which is generally detrimental to marine life as well, this needs to consider how OA-induced changes to microbial communities will compound this since hydrocarbon degradation is influenced by the community-level microbial response. This study aims to evaluate the effects of increased atmospheric CO₂ conditions and oil enrichment on the phytoplankton-associated bacterial communities. Faroe Shetland Channel (FSC) is a subarctic region in the northeast Atlantic where crude oil extraction has recently been expanded. In the event of a major oil spill in this region, it is vital that we understand the response of the bacterial community and its consequence on primary production within this region—some phytoplankton communities found in the ocean harbor hydrocarbon-degrading bacteria that are associated with its psychosphere. Surface water containing phytoplankton and bacteria from FSC were cultured in ambient and elevated atmospheric CO₂ conditions for 4 days of acclimation in microcosms before introducing 1% (v/v) of crude oil into the microcosms to simulate oil spill conditions at sea. It was found that elevated CO₂ conditions do not significantly affect the chl a concentration, and exposure to crude oil detrimentally affected chl a concentration up to 10 days after exposure to crude oil. The diversity and richness of the bacterial community were not significantly affected by both CO₂ treatment and oil enrichment. The increase in the relative abundance of known hydrocarbon degraders such as Oleispira, Marinobacter and Halomonas indicates potential for biodegradation of crude oil, while the resilience of dominant taxa Colwellia, unclassified Gammaproteobacteria, unclassified Rnodobacteria and unclassified Halomonadaceae could be associated with the recovery of microalgal community 13 days after oil exposure. Therefore, the microbial community from the subsurface of FSC has the potential to recover from crude oil pollution even under elevated CO₂ (750 ppm) conditions.

Keywords: phytoplankton, bacteria, crude oil, ocean acidification

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Authors: Sharad Kumar Kulshreshtha

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India is a great land of cultural and traditional diversity. Its spectrums create a unique ambiance in all over the country. Specially, fairs and festivals are ancient phenomena in Indian culture. In India, there are thousands of such religious, spiritual, cultural fairs organized on auspicious occasions. These fairs reflect the effective and efficient role of social governance and responsibility of Indian society. In this context a mega event known as ‘Kumbha Mela’ literally mean ‘Kumbha Fair’ which is organize after every twelve years at (Prayaag) Allahabad an ancient city of India, now is in the state of Uttar Pradesh. Kumbh Mela is one of the largest human congregations on the Earth. The Kumbha Mela that is held here is considered to be the largest and holiest city among the four cities where Kubha fair organize. According to the Hindu religious scripture a dip for possessing the holy confluence, known as Triveni Sangam, which is a meeting point of the three sacred rivers of India i.e., –Ganges, Yamuna and Saraswati (mythical). During the Kumbha fair the River Ganges is believed to turn to nectar, bringing great blessing to everyone who bathes in it. Other activities include religious discussions, devotional singings and mass feedings pilgrims and poor. The venue for Kumbh Mela (fair) depends on the position Sun, Moon, and Jupiter which holds in that period in different zodiac signs. More than 120 Millions (12 Crore) people visited in the Kumbha Fair-2013 in Allahabad. A temporary tented city was set up for the pilgrims over an area of 2 hectares of the land along the river of Ganges. As many as 5 power substations, temporary police stations, hospitals, bus terminals, stalls were set up for providing various facilities to the visitors and thousands of volunteers participated for assistance of this event. All efforts made by fair administration to provide facility to visitors, such security and sanitation, medical care and frequent water and power supply. The efficient and timely arrangement at the Kumbha Mela attracted the attention of many government and institutions. The Harvard University of USA conducted research to find out how it was made possible. This paper will focuses on effective and efficient planning and preparation of Kumbha Fair which includes facilitation process, role of various coordinating agencies. risk management crisis management strategies Prevention, Preparedness, Response, and Recovery (PPRR Approach), emergency response plan (ERP), safety and security issues, various environmental aspects along with health hazards and hygiene crowd management, evacuation, monitoring, control and evaluation.

Keywords: event planning and facility arrangement, risk management, crowd management, India

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Authors: Chen Wang, Qiuxiao Chen

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With the advent of the information age and the era of big data, urban planning research is no longer satisfied with the analysis and application of traditional data. Because of the limitations of traditional urban commercial center system research, big data provides new opportunities for urban research. Therefore, based on the quantitative evaluation method of big data, the commercial center system of the main city of Hangzhou is analyzed and evaluated, and the scale and hierarchical structure characteristics of the urban commercial center system are studied. In order to make up for the shortcomings of the existing POI extraction method, it proposes a POI extraction method based on adaptive adjustment of search window, which can accurately and efficiently extract the POI data of commercial business in the main city of Hangzhou. Through the visualization and nuclear density analysis of the extracted Point of Interest (POI) data, the current situation of the commercial center system in the main city of Hangzhou is evaluated. Then it compares with the commercial center system structure of 'Hangzhou City Master Plan (2001-2020)', analyzes the problems existing in the planned urban commercial center system, and provides corresponding suggestions and optimization strategy for the optimization of the planning of Hangzhou commercial center system. Then get the following conclusions: The status quo of the commercial center system in the main city of Hangzhou presents a first-level main center, a two-level main center, three third-level sub-centers, and multiple community-level business centers. Generally speaking, the construction of the main center in the commercial center system is basically up to standard, and there is still a big gap in the construction of the sub-center and the regional-level commercial center, further construction is needed. Therefore, it proposes an optimized hierarchical functional system, organizes commercial centers in an orderly manner; strengthens the central radiation to drive surrounding areas; implements the construction guidance of the center, effectively promotes the development of group formation and further improves the commercial center system structure of the main city of Hangzhou.

Keywords: business center system, business format, main city of Hangzhou, POI extraction method

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Authors: O. R. Razanakoto, L. Temple

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Living in a least developed country, the Malagasy society has a weak capacity to internalize progress, including health concerns. Since the arrival in the fifteenth century of Arabic script, called Sorabe, that was mainly dedicated to the aristocracy, until the colonial era beginning at the end of the nineteenth century and that has popularized the current usual script of the occidental civilization, the upcoming manuscripts that deal with apparent scientific or at least academic issue have been slowly established. So that, the Malagasy communities’ way of life is not well documented yet to allow a precise understanding of the major concerns, reason, and purpose of the existence of the farmers that compose them. A question arises, according to literature, how does Malagasy community that is dominated by agrarian society conceive the conservation of its wellbeing? This study aims to emphasize the scope and the limits of the « One Health » concept or of the Health Integrated Approach (HIA) that evolves at global scale, with regard to the specific context of local Malagasy smallholder farms. It is expected to identify how this society represents linked risks and the mechanisms between human health, animal health, plant health, and ecosystem health within the last 100 years. To do so, the framework to conduct systematic review for agricultural research has been deployed to access available literature. This task has been coupled with the reading of articles that are not indexed by online scientific search engine but that mention part of a history of agriculture and of farmers in Madagascar. This literature review has informed the interactions between human illnesses and those affecting animals and plants (breeded or wild) with any unexpected event (ecological or economic) that has modified the equilibrium of the ecosystem, or that has disturbed the livelihoods of agrarian communities. Besides, drivers that may either accentuate or attenuate the devasting effects of these illnesses and changes were revealed. The study has established that the reasons of human worries are not only physiological. Among the factors that regulate global health, food system and contemporary medicine have helped to the improvement of life expectancy from 55 to 63 years in Madagascar during the last 50 years. However, threats to global health are still occurring. New human or animal illnesses and livestock / plant pathology or enemies may also appear, whereas ancient illnesses that are supposed to have disappeared may be back. This study has highlighted how much important are the risks associated to the impact of unmanaged externalities that weaken community’s life. Many risks, and also solutions, come from abroad and have long term effects even though those happen as punctual event. Thus, a constructivist strategy is suggested to the « One Health » global concept throughout the record of local facts. This approach should facilitate the exploration of methodological pathways and the identification of relevant indicators for research related to HIA.

Keywords: agrarian system, health integrated approach, history, madagascar, resilience, risk

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Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

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Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

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We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

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Authors: Lorena Coelho, David Ramada, Catarina Nobre, Joaquim Gaião, Juliana Duarte

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The development of processes that allows the valorization of waste and by-products generated by industries is crucial to promote symbiotic relationships between different sectors and is mandatory to “close the loop” in the circular economy paradigm. In recent years, by-products and waste from agro-food and forestry sector have attracted attention due to their potential application and technical characteristics. The extraction of bio-based active compounds to be reused is in line with the circular bioeconomy concept trends, combining the use of renewable resources with the process’s circularity, aiming the waste reduction and encouraging reuse and recycling. Among different types of bio-based materials, which are being explored and can be extracted, proteins fractions are becoming an attractive new raw material. Within this context, BioTrace4Leather project, a collaboration between two Technological Centres – CeNTI and CTIC, and a company of Tanning and Finishing of Leather – Curtumes Aveneda, aims to develop innovative and biologically sustainable solutions for leather industry and accomplish the market circularity trends. Specifically, it aims to the valorisation of waste and by-products from the tannery industry through proteins extraction and the development of an innovative and biologically sustainable materials. The achieved results show that keratin, gelatine, and collagen fractions can be successfully extracted from hair and leather bovine waste. These products could be reintegrated into the industrial manufacturing process to attain innovative and functional textile and leather substrates. ACKNOWLEDGEMENT This work has been developed under BioTrace4Leather scope, a project co-funded by Operational Program for Competitiveness and Internationalization (COMPETE) of PORTUGAL2020, through the European Regional Development Fund (ERDF), under grant agreement Nº POCI-01-0247-FEDER-039867.

Keywords: leather by-products, circular economy, sustainability, protein fractions

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Authors: Supakan Rattanakon, Jakkrapan Boonpimon, Akkaragiat Bhuangsaeng, Aphiwat Ratriphruek

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Rice bran oil (RBO) has been found to lower the level of serum cholesterol, has antioxidant and anti-carcinogenic property, and attenuate allergic inflammation. These properties of RBO are due to antioxidant compositions, especially, phenolic compounds. The higher amount of these active compounds in RBO, the greater value of RBO is. Thermal process of rice bran before solvent RBO extraction has been found to have a higher phenolic contents. Therefore, the purpose of this study is to using different heating methods on rice bran before the solvent extraction. Then, % yield of RBO, total phenolic content (TPC), and antioxidant property of two white Thai rice; KDML105 and RD6 were determined. The Folin-Ciocalteu colorimetric assay was used to determine TPC and scavenging of free radicals (DPPH) was used to determine antioxidant property expressed as EC50. The result showed that thermal process did not increase % yield of RBO but increase the TPC with 1.41 mg gallic acid equivalent (GAEmg-1). The highest TPC was found in KDML105 by using sonicator. The highest antioxidant activity was found in RD6 using autoclave. The EC50 of RBO was 0.04 mg/mL. Further study should be performed on different pretreatments to increase the TPC and antioxidant property.

Keywords: antioxidant, rice bran oil, total phenol content, white rice

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

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Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Tarikayehu Amanuel, Abraham Mohammed

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The production of biodiesel from waste materials is becoming an increasingly important research area in the field of renewable energy. One potential waste material source is avocado, a fruit with a large seed and peel that are typically discarded after consumption. This research aims to investigate the feasibility of using avocado waste as a feedstock for the production of biodiesel. The study focuses on extracting oil from the waste material using the transesterification technique and then characterizing the properties of oil to determine its suitability for conversion to biodiesel. The study was conducted experimentally, and a maximum oil yield of 11.583% (150g of oil produced from 1.295kg of avocado waste powder) was obtained from avocado waste powder at an extraction time of 4hr. An 87% fatty acid methyl ester (biodiesel) conversion was also obtained using a methanol/oil ratio of 6:1, 1.3g NaOH, reaction time 60min, and 65°C reaction temperature. Furthermore, from 145 ml of avocado waste oil, 126.15 ml of biodiesel was produced, indicating a high percentage of conversion (87%). Conclusively, the produced biodiesel showed comparable physical and chemical characteristics to that of standard biodiesel samples considered for the study. The results of this research could help to identify a new source of biofuel production while also addressing the issue of waste disposal in the food industry.

Keywords: biodiesel, avocado, transesterification, soxhlet extraction

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Authors: Amunupura Kiriwandeiye Gedara, Asintha Saminda Gnanaratne

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The security forces can be described as a workforce that goes beyond the role of ensuring the national security and contributes to the development process of the country. Soldiers are following combatant training courses during their tenure, they are equipped with a variety of vocational training courses to satisfy the needs of the army, to equip them with vocational training capabilities to achieve the development and reconstruction goals of the country as well as for the betterment of society in the event of emergencies. But with retirement, their relationship with the military is severed, and they are responsible for the future of their lives. The main purpose of this study was to examine how such professional capabilities can contribute to the development of the country, the current socio-economic status of the retired soldiers, and the current application of the vocational training skills they have mastered in the army to develop and rebuild the country in an effective manner. After analyzing the available research literature related to this field, a conceptual framework was developed and according to qualitative research methodology, and data obtained from Case studies and interviews are analyzed by using thematic analysis. Factors influencing early retirement include a lack of understanding of benefits, delays in promotions, not being properly evaluated for work, getting married on hasty decisions, and not having enough time to spend on family and household chores. Most of the soldiers are not aware about various programs and benefits available to retirees. They do not have a satisfactory attitude towards the retirement guidance they receive from the army at the time of retirement. Also, due to the lack of understanding about how to use their vocational capabilities successfully pursue their retirement life, the majority of people are employed in temporary jobs, and some are successful in post-retirement life due to their successful use of training received. Some live on pensions without engaging in any income-generating activities, and those who retire after 12 years of service are facing severe economic hardships as they do not get pensions. Although they have received training in various fields, they do not use them for their benefit due to lack of proper guidance. Although the government implements programs, they are not clearly aware of them. Barriers to utilization of training include an absence of a system to identify the professional skills of retired soldiers, interest in civil society affairs, exploration of opportunities in the civil and private sectors, and politicization of services. If they are given the opportunity, they will be able to contribute to the development and reconstruction process. The findings of the study further show that it has many social, economic, political, and psychological benefits not only for individuals but also for a country. Entrepreneurship training for all retired soldiers, improving officers' understanding, streamlining existing mechanisms, creating new mechanisms, setting up a separate unit for retirees, and adapting them to civil society, private and non-governmental contributions, and training courses can be identified as potential means to improve the current situation.

Keywords: development, reconstruction, retired soldiers, vocational capabilities

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Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

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This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Jinee Gogoi, Som K. Sharma, Kalyan Bhuyan

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The atmospheric layers are coupled to each other with the different dynamical, electrical, radiative and chemical processes. A large scale thermodynamical phenomenon in winter polar regions which affects the middle atmosphere vigorously is Sudden Stratospheric Warming (SSW). Two major SSW events were occurred during 1998-1999; one in December 1998 which is associated with vortex displacement and another in February- March 1999 associated with vortex splitting. Lidar study of these two major events from Mt. Abu (24.36⁰N, 72.45⁰E, ~1670 m amsl) has shown that though SSWs are mostly observed over high and mid latitudes, their effects can also be seen over India. We have studied ionospheric variations (primarily fₒF₂, h’F and hpF₂) over Ahmedabad (23.1⁰N, 72.58⁰E) during these events. Ionospheric disturbances have been found after four-five days of peak temperature. An increase (decrease) in critical frequency (fₒF₂) during morning (afternoon) has been noticed which may be in response to the updrift (down drift). Effects are stronger during displacement event (1998) than during the splitting event (1999). We have also studied some recent events occurred during 2006 (January), 2009 (January) and 2013 (January) using temperature data from Sounding of Atmosphere using Broadband Emission Radiometry (SABER) satellite. Though some modeling work supports the hypothesis that planetary waves are responsible for atmosphere-ionosphere coupling, there is still more significant works to do to understand how exactly the coupling can take place.

Keywords: sudden stratospheric warming (SSW), polar vortex, ionosphere, critical frequency

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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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: Sema Müge Özdemiray

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In line with the new public management approach to provide effective and efficient services necessary to achieve the social goals of public institutions, employees must have the knowledge and skills required by the age. In conjunction with the transition from personnel management to human resources management, it is seen that there is a change in the understanding of in-service training, the understanding of "required in-service training" has switched to the understanding of "continuous in-service training". However, in terms of in-service training in Turkey, it seems to be trouble at the point of adopting to change. The main purpose of this study is to primarily create a conceptual framework of in-service training and subsequently determine, analyze and discuss the developments and problems faced by in-service training in Turkey in the transition from personnel management to human resources management. In accordance with this purpose, the necessary data of this study were collected using qualitative approaches. Observation and document analysis was used and content analysis was performed on the data gathered in the study. The results of this study, according to data such as the number of institutions requesting in-service training, allocated budget of in-service training, the number of people participating in such training, transition of personnel management to human resources management should not lead to a paradigm shift in Turkey’s understanding of in-service training, although this is compulsory for public institutions in accordance with the law in Turkey. In-service training in Turkish public administration is still not implemented effectively and is seen as a social activity for employees and a formality for institutions.

Keywords: Human resources management, in service training, personnel management, public institutions

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Authors: C. Park, H. Lee, Y-J. Lee

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Aim: This study aims to present the Sustainability Innovation Capacity Building Framework (SICBF) to enable the wider public to achieve UN Sustainable Development Goals (UN SDGs) for a sustainable future. The intrinsically interwoven nature of sustainability requires systematic approaches to attain. However, there is a lack of an effective framework for capacity building that enables a systematic implementation approach for UN SDGs. The SICBF illustrates the six core components and their dynamics: 1. Momentum creation; 2. Exposure to diverse worldviews; 3. Serendipity/Eureka moment; 4. Creative problem solving; 5. Individual empowerment; 6. Systems thinking. Method: First, a structured literature review was used to synthesise existing sustainability competencies studies and generic innovation competencies. Secondly, the conceptual framework based on literature findings was tested with the participants' survey and interview data collected from four sets of MAKEathon events. The interview analysis and event observation data were used to further refine and validate the conceptual framework. Contributions: The scientific contribution of this study is to pave the way for SDGs specific capacity building framework that caters to the need for systematic approaches to allow the wider public aspiring to tackle the seemingly intractable sustainable development goals. The framework will aid sustainable development academics, educators, and practitioners in understanding the dynamics of how capacity building can be facilitated.

Keywords: capacity building, sustainability innovation, sustainable development, systems thinking, UN SDGs

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Authors: Brigitte Mischler, Marget Hund, Hilfiker Roger, Clare Maguire

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Background: Brain injury is one of the main causes of permanent physical disability, and improving walking ability is one of the most important goals for patients. After inpatient rehabilitation, most do not receive long-term rehabilitation services. Physical activity is important for the health prevention of the musculoskeletal system, circulatory system and the psyche. Objective: This follow-up study measured physical activity in subacute patients after traumatic brain injury and stroke. The difference in the number of steps in the inpatient setting was compared to the number of steps 1 year after the event in the outpatient setting. Methods: This follow-up study is a cross-sectional observational study with 29 participants. The measurement of daily step count over a seven-day period one year after the event was evaluated with the StepWatch™ ankle sensor. The number of steps taken one year after the event in the outpatient setting was compared with the number of steps taken during the inpatient stay and evaluated if they reached the recommended target value. Correlations between steps-count and exit domain, FAC level, walking speed, light touch, joint position sense, cognition, and fear of falling were calculated. Results: The median (IQR) daily step count of all patients was 2512 (568.5, 4070.5). During follow-up, the number of steps improved to 3656(1710,5900). The average difference was 1159(-2825, 6840) steps per day. Participants who were unable to walk independently (FAC 1) improved from 336(5-705) to 1808(92, 5354) steps per day. Participants able to walk with assistance (FAC 2-3) walked 700(31-3080) and at follow-up 3528(243,6871). Independent walkers (FAC 4-5) walked 4093(2327-5868) and achieved 3878(777,7418) daily steps at follow-up. This value is significantly below the recommended guideline. Step-count at follow-up showed moderate to high and statistically significant correlations: positive for FAC score, positive for FIM total score, positive for walking speed, and negative for fear of falling. Conclusions: Only 17% of all participants achieved the recommended daily step count one year after the event. We need better inpatient and outpatient strategies to improve physical activity. In everyday clinical practice, pedometers and diaries with objectives should be used. A concrete weekly schedule should be drawn up together with the patient, relatives, or nursing staff after discharge. This should include daily self-training, which was instructed during the inpatient stay. A good connection to social life (professional connection or a daily task/activity) can be an important part of improving daily activity. Further research should evaluate strategies to increase daily step counts in inpatient settings as well as in outpatient settings.

Keywords: neurorehabilitation, stroke, traumatic brain injury, steps, stepcount

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Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

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The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

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Authors: Y. B. Idris, M. Sirajo, L. G. Hassan, T. Izuagie, T. Muktar, I. Lawal, A. U. Abubakar

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This study investigates the extraction, phytochemical composition, and antimicrobial activity of bioactive compounds from red millipedes using three different solvents: n-Hexane, Chloroform, and Methanol. The largest yield was obtained from the methanol extract, which had percentage yields of 0.8%, 2.2%, and 5.6%, respectively. Terpenoids and sterols were found in all extracts according to preliminary zoochemical screening, but only the methanol extract included saponins and phenols. With a maximum zone of inhibition of 9 mm at 1000 µg/ml, antimicrobial susceptibility tests revealed that the methanol extract had the strongest antibacterial activity, especially against Escherichia coli and Staphylococcus aureus. Significant activity was also shown by the n-hexane extract, although the chloroform extract had only mild antibacterial activity. Tests for minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) verified that the methanol extract was more effective than the other extracts, particularly against S. aureus and S. typhi. None of the extracts, nonetheless, showed any discernible antifungal action. The potential of red millipede extracts, especially those based on methanol, as a source of antimicrobial chemicals for use in the future is highlighted by this work.

Keywords: millipedes, defensive extraction, antibacterial, antifungal, antimicrobial, minimum inhibitory concentration (MIC), minimum bacterial concentration (MBC)

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