Search results for: online processing service

Authors: Kenji Tanaka, Kazumi Sugita, Yuto Mizushima

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This paper introduces a noteworthy form of English communication training for the officers and operators of the Osaka-Bay Marine Traffic Information Service (Osaka MARTIS) of the Japan Coast Guard working in the congested area at the Akashi Strait in Hyogo Prefecture, Japan. The authors of this paper, Marine Technical College’s (MTC) English language instructors, have been holding about forty lectures and exercises in basic and normal Maritime English (ME) for several groups of MARTIS personnel at Osaka MARTIS annually since they started the training in 2005. Trainees are expected to be qualified Maritime Third-Class Radio Operators who are responsible for providing safety information to a daily average of seven to eight hundred vessels that pass through the Akashi Strait, one of Japan’s narrowest channels. As of 2022, the instructors are conducting 55 remote lessons at MARTIS. One lesson is 90 minutes long. All 26 trainees are given oral and written assessments. The trainees need to pass the examination to become qualified operators every year, requiring them to train and maintain their linguistic levels even during the pandemic of Corona Virus Disease-19 (COVID-19). The vessel traffic information provided by Osaka MARTIS in Maritime English language is essential to the work involving the use of very high frequency (VHF) communication between MARTIS and vessels in the area. ME is the common language mainly used on board merchant, fishing, and recreational vessels, normally at sea. ME was edited and recommended by the International Maritime Organization in the 1970s, was revised in 2002, and has undergone continual revision. The vessel’s circumstances are much more serious at the strait than those at the open sea, so these vessels need ME to receive guidance from the center when passing through the narrow strait. The imminent and challenging situations at the strait necessitate that textbooks’ contents include the basics of the phrase book for seafarers as well as specific and additional navigational information, pronunciation exercises, notes on keywords and phrases, explanations about collocations, sample sentences, and explanations about the differences between synonyms especially those focusing on terminologies necessary for passing through the strait. Additionally, short Japanese-English translation quizzes about these topics, as well as prescribed readings about the maritime sector, are include in the textbook. All of these exercises have been trained in the remote education system since the outbreak of COVID-19. According to the guidelines of ME edited in 2009, the lowest level necessary for seafarers is B1 (lower individual users) of The Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR). Therefore, this vocational ME language training at Osaka MARTIS aims for its trainees to communicate at levels higher than B1. A noteworthy proof of improvement from this training is that most of the trainees have become qualified marine radio communication officers.

Keywords: akashi strait, B1 of CEFR, maritime english communication training, osaka martis

Procedia PDF Downloads 123

Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani

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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.

Keywords: material point method, woven fabric composites, forming, material handling

Procedia PDF Downloads 181

Authors: Stephanie Al Otaiba, Kyle Roberts

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Background and Significance Globally far too many students read below grade level; thus improving literacy outcomes is vital. Research suggests that non-cognitive factors, including Social and Emotional Learning (SEL) are linked to success in literacy outcomes. Converging evidence exists that early interventions are more effective than later remediation; therefore teachers need strategies to support early literacy while developing students’ SEL and their vocabulary, or language, for learning. This presentation describe findings from a US federally-funded project that trained teachers to provide an evidence-based read-aloud program for young children, using commercially available books with multicultural characters and themes to help their students “GROW”. The five GROW SEL themes include: “I can name my feelings”, “I can learn from my mistakes”, “I can persist”, “I can be kind to myself and others”, and “I can work toward and achieve goals”. Examples of GROW vocabulary (from over 100 words taught across the 5 units) include: emotions, improve, resilient, cooperate, accomplish, responsible, compassion, adapt, achieve, analyze. Methodology This study used a mixed methods research design, with qualitative methods to describe data from teacher feedback surveys (regarding satisfaction, feasibility), observations of fidelity of implementation, and with quantitative methods to assess the effect sizes for student vocabulary growth. GROW Intervention and Teacher Training Procedures Researchers trained classroom teachers to implement GROW. Each thematic unit included four books, vocabulary cards with images of the vocabulary words, and scripted lessons. Teacher training included online and in-person training; researchers incorporated virtual reality videos of instructors with child avatars to model lessons. Classroom teachers provided 2-3 20 min lessons per week ranging from short-term (8 weeks) to longer-term trials for up to 16 weeks. Setting and Participants The setting for the study included two large urban charter schools in the South. Data was collected across two years; during the first year, participants included 7 kindergarten teachers and 108 and the second year involved an additional set of 5 kindergarten and first grade teachers and 65 students. Initial Findings The initial qualitative findings indicate teachers reported the lessons to be feasible to implement and they reported that students enjoyed the books. Teachers found the vocabulary words to be challenging and important. They were able to implement lessons with fidelity. Quantitative analyses of growth for each taught word suggest that students’ growth on taught words ranged from large (ES = .75) to small (<.20). Researchers will contrast the effects for more and less successful books within the GROW units. Discussion and Conclusion It is feasible for teachers of young students to effectively teach SEL vocabulary and themes during shared book reading. Teachers and students enjoyed the books and students demonstrated growth on taught vocabulary. Researchers will discuss implications of the study and about the GROW program for researchers in learning sciences, will describe some limitations about research designs that are inherent in school-based research partnerships, and will provide some suggested directions for future research and practice.

Keywords: early literacy, learning science, language and vocabulary, social and emotional learning, multi-cultural

Procedia PDF Downloads 43

Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

Procedia PDF Downloads 109

Authors: Vilma Sasyte, Vilma Viliene, Agila Dauksiene, Asta Raceviciute-Stupeliene, Romas Gruzauskas, Saulius Alijosius

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The eight-week feeding trial was conducted involving 27-wk-old Isa brown laying hens to study the effect of dry extrusion processing on partial reduction in total glucosinolates content of locally produced rapeseed and on productivity and eggs quality parameters of laying hens. Thirty-six hens were randomly assigned one of three treatments (CONTR, AERS and HERS), each comprising 12, individual caged layers. The main composition of the diets was the same, but extruded soya bean seed were replaced with 2.5% of the extruded rapeseed in the AERS group and 4.5 % in the HERS group. Rapeseed was extruded together with faba beans. Due to extrusion process the glucosinolates content was reduced by 7.83 µmol/g of rapeseed. The results of conducted trial shows, that during all experimental period egg production parameters, such as the average feed intake (6529.17 vs. 6257 g/hen/14 day; P < 0.05) and laying intensity (94.35% vs. 89.29; P < 0.05) were statistically different for HERS and CONTR laying hens respectively. Only the feed conversion ratio to produce 1 kg of eggs, kg in AERS group was by 11 % lower compared to CONTR group (P < 0.05). By analysing the effect of extruded rapeseed on egg mass, the statistical differences between treatments were no determined. The dietary treatments did not affect egg weight, albumen height, haugh units, albumen and yolk pH. However, in the HERS group were get eggs with the more intensive yolk color, higher redness (a) and yellowness (b) values. The inclusion of full-fat extruded rapeseed had no effect on egg shell quality parameters, i.e. shell breaking strength, shell weight with and without coat and shell index, but in the experimental groups were get eggs with the thinner shell (P < 0.05). The internal egg quality analysis showed that with higher content of extruded rapeseed (4.5 %) level in the diet, the total cholesterol in the eggs yolk decreased by 1.92 mg/g in comparison with CONTR group (P < 0.05). Eggs laid by hens fed the diet containing 2.5% and 4.5% had increasing ∑PNRR/∑SRR ratio and decreasing ∑(n-6)/∑(n-3) ratio values of eggs yolk fatty acids than in CONTR group. Eggs of hens fed different amount of extruded rapeseed presented an n-6 : n-3 ratio changed from 5.17 to 4.71. The analysis of the relationship between hypocholesteremia/ hypercholesterolemia fatty acids (H/H), which is based on the functional properties of fatty acids, found that the value of it ratio is significant higher in laying hens fed diets supplemented with 4.5% extruded rapeseed than the CONTR group, demonstrating the positive effects of extruded rapeseed on egg quality. The results of trial confirmed that extruded full fat rapeseed to the 4.5% are suitable to replace soyabean in the compound feed of laying hens.

Keywords: egg quality, extruded full-fat rapeseed, laying hens, productivity

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Authors: Erickson Bernardo, Caridad Pineda

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The project Adolescent Reproductive Health Information and Services (ARHIS) is a nine-month pilot project which intends to bridge the existing gap between reproductive health information and services, particularly with regard to family planning and HIV, among adolescent boys and girls aged 10-19 years in the 2nd Congressional District of Quezon City, in the Philippines. It aims to increase adolescents' and young people's awareness about their reproductive health concerns and at the same time make a wide range of reproductive health (RH) services accessible and available to them. A number of methodologies were utilized in the implementation of the project. At the onset, a baseline survey was conducted by community mobilizers to gather a situational analysis of adolescents' and young people's issues and concerns. The results of this survey were then presented in a multi-stakeholders' meeting to gather community support and foster their involvement. Further, interactive learning sessions (ILS) on a variety of reproductive health topics, among young people, parents and community leaders based on the results of the baseline survey was conducted. With regard to reproductive health service provision, both facility-based delivery and conduct of outreach activities were employed. In the span of nine months, the project was able to yield the following results: • A total of 521 adolescents and youth (AY) were reached by ILS on puberty, responsible relationships, teenage pregnancy, family planning, as well as HIV & AIDS. • A total of 218 parents and community leaders were informed of AY RH-related issues and concerns. • More than 350 AYs availed of a wide range of FP services including pills – both combined oral and progestin-only, and progestin-only injectables and implants. • More than 380 AYs availed of condoms as means of STI and HIV prevention. A noble initiative of the project is the utilization of a "condom distributor", a youth leader who has been educated about STI and HIV prevention as well as correct condom use, as the focal point for condom access in the community. • A total of 25 young people, parents, and community leaders were identified as ARHIS champions who have been instrumental in the achievement of project deliverables through their dedication and commitment to support the project. The concept of adolescent sexual and reproductive health (ASRH) remains to be a major challenge in the Philippine context. This is due to the fact that majority of Filipinos are still not keen on discussing issues and concerns related to ASRH, albeit the alarming number of teenage pregnancies and the rapid increase of HIV cases among 15- 24 year olds. In addition, Republic Act 10354 or the Responsible Parenthood and Reproductive Health Act of 2012, requires minor adolescents to present a written parental consent prior to accessing RH services. However, with the involvement and support of parents and key community stakeholders, these barriers may be addressed. The project has demonstrated how adolescents and young people yearn for reproductive health information and services.

Keywords: adolescent sexual reproductive health, barriers to access, reproductive health information and services, teenage pregnancies

Procedia PDF Downloads 177

Authors: Jerome Joshi

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The paper presents the modelling of financial markets using the Stochastic Pi Calculus model. The Stochastic Pi Calculus model is mainly used for biological applications; however, the feature of this model promotes its use in financial markets, more prominently in high frequency trading. The trading system can be broadly classified into exchange, market makers or intermediary traders and fundamental traders. The exchange is where the action of the trade is executed, and the two types of traders act as market participants in the exchange. High frequency trading, with its complex networks and numerous market participants (intermediary and fundamental traders) poses a difficulty while modelling. It involves the participants to seek the advantage of complex trading algorithms and high execution speeds to carry out large volumes of trades. To earn profits from each trade, the trader must be at the top of the order book quite frequently by executing or processing multiple trades simultaneously. This would require highly automated systems as well as the right sentiment to outperform other traders. However, always being at the top of the book is also not best for the trader, since it was the reason for the outbreak of the ‘Hot – Potato Effect,’ which in turn demands for a better and more efficient model. The characteristics of the model should be such that it should be flexible and have diverse applications. Therefore, a model which has its application in a similar field characterized by such difficulty should be chosen. It should also be flexible in its simulation so that it can be further extended and adapted for future research as well as be equipped with certain tools so that it can be perfectly used in the field of finance. In this case, the Stochastic Pi Calculus model seems to be an ideal fit for financial applications, owing to its expertise in the field of biology. It is an extension of the original Pi Calculus model and acts as a solution and an alternative to the previously flawed algorithm, provided the application of this model is further extended. This model would focus on solving the problem which led to the ‘Flash Crash’ which is the ‘Hot –Potato Effect.’ The model consists of small sub-systems, which can be integrated to form a large system. It is designed in way such that the behavior of ‘noise traders’ is considered as a random process or noise in the system. While modelling, to get a better understanding of the problem, a broader picture is taken into consideration with the trader, the system, and the market participants. The paper goes on to explain trading in exchanges, types of traders, high frequency trading, ‘Flash Crash,’ ‘Hot-Potato Effect,’ evaluation of orders and time delay in further detail. For the future, there is a need to focus on the calibration of the module so that they would interact perfectly with other modules. This model, with its application extended, would provide a basis for researchers for further research in the field of finance and computing.

Keywords: concurrent computing, high frequency trading, financial markets, stochastic pi calculus

Procedia PDF Downloads 77

Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

Procedia PDF Downloads 337

Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

Procedia PDF Downloads 88

Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

Procedia PDF Downloads 43

Authors: Chinedu F. Anochie

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The presence of gangue particles in recovered metal concentrates has been a serious challenge to ore dressing engineers. Middlings lower the quality of concentrates, and in most cases, drastically affect the smelter terms, owing to exorbitant amounts paid by Mineral Processing industries as treatment charge. Models which encourage optimization of liberation operations have been utilized in most ore beneficiation industries to reduce the presence of locked particles in valuable concentrates. Moreover, methods such as incorporation of regrind mills, scavenger, rougher and cleaner cells, to the milling and flotation plants has been widely employed to tackle these concerns, and to optimize the grade–recovery relationship of metal concentrates. This work compared the crushing and grinding method of liberation, to the mine to mill route, by evaluating the proportion of middlings present in selectively processed complex Pb-Zn ore samples. To establish the effect of size reduction operations on the percentage of locked particles present in recovered concentrates, two similar samples of complex Pb- Zn ores were processed. Following blasting operation, the first ore sample was ground directly in a ball mill (Mine to Mill Route of Comminution), while the other sample was manually crushed, and subsequently ground in the ball mill (Crushing and Grinding Route of Comminution). The two samples were separately sieved in a mesh to obtain the desired representative particle sizes. An equal amount of each sample that would be processed in the flotation circuit was then obtained with the aid of a weighing balance. These weighed fine particles were simultaneously processed in the flotation circuit using the selective flotation technique. Sodium cyanide, Methyl isobutyl carbinol, Sodium ethyl xanthate, Copper sulphate, Sodium hydroxide, Lime and Isopropyl xanthate, were the reagents used to effect differential flotation of the two ore samples. Analysis and calculations showed that the degree of liberation obtained for the ore sample which went through the conventional crushing and grinding route of comminution, was higher than that of the directly milled run off mine (ROM) ore. Similarly, the proportion of middlings obtained from the separated galena (PbS) and sphalerite (ZnS) concentrates, were lower for the crushed and ground ore sample. A concise data which proved that the mine to mill method of size reduction is not the most ideal technique for the recovery of quality metal concentrates has been established.

Keywords: comminution, degree of liberation, middlings, mine to mill

Procedia PDF Downloads 133

Authors: Igor Jerkovic

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Biodiversity of flora provides many different nectar sources for the bees. Unifloral honeys possess distinctive flavours, mainly derived from their nectar sources (characteristic volatile organic components (VOCs)). Specific or nonspecific VOCs (chemical markers) could be used for unifloral honey characterisation as addition to the melissopalynologycal analysis. The main honey volatiles belong, in general, to three principal categories: terpenes, norisoprenoids, and benzene derivatives. Some of these substances have been described as characteristics of the floral source, and other compounds, like several alcohols, branched aldehydes, and furan derivatives, may be related to the microbial purity of honey processing and storage conditions. Selection of the extraction method for the honey volatiles profiling should consider that heating of the honey produce different artefacts and therefore conventional methods of VOCs isolation (such as hydrodistillation) cannot be applied for the honey. Two-way approach for the isolation of the honey VOCs was applied using headspace solid-phase microextraction (HS-SPME) and ultrasonic solvent extraction (USE). The extracts were analysed by gas chromatography and mass spectrometry (GC-MS). HS-SPME (with the fibers of different polarity such as polydimethylsiloxane/ divinylbenzene (PDMS/DVB) or divinylbenzene/carboxene/ polydimethylsiloxane (DVB/CAR/PDMS)) enabled isolation of high volatile headspace VOCs of the honey samples. Among them, some characteristic or specific compounds can be found such as 3,4-dihydro-3-oxoedulan (in Centaurea cyanus L. honey) or 1H-indole, methyl anthranilate, and cis-jasmone (in Citrus unshiu Marc. honey). USE with different solvents (mainly dichloromethane or the mixture pentane : diethyl ether 1 : 2 v/v) enabled isolation of less volatile and semi-volatile VOCs of the honey samples. Characteristic compounds from C. unshiu honey extracts were caffeine, 1H-indole, 1,3-dihydro-2H-indol-2-one, methyl anthranilate, and phenylacetonitrile. Sometimes, the selection of solvent sequence was useful for more complete profiling such as sequence I: pentane → diethyl ether or sequence II: pentane → pentane/diethyl ether (1:2, v/v) → dichloromethane). The extracts with diethyl ether contained hydroquinone and 4-hydroxybenzoic acid as the major compounds, while (E)-4-(r-1’,t-2’,c-4’-trihydroxy-2’,6’,6’-trimethylcyclo-hexyl)but-3-en-2-one predominated in dichloromethane extracts of Allium ursinum L. honey. With this two-way approach, it was possible to obtain a more detailed insight into the honey volatile and semi-volatile compounds and to minimize the risks of compound discrimination due to their partial extraction that is of significant importance for the complete honey profiling and identification of the chemical biomarkers that can complement the pollen analysis.

Keywords: honey chemical biomarkers, honey volatile compounds profiling, headspace solid-phase microextraction (HS-SPME), ultrasonic solvent extraction (USE)

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Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

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Drying technologies for various food processing operations shares an inevitable linkage with energy, cost and environmental sustainability. Hence, solar drying of food grains has become imperative choice to combat duo challenges of meeting high energy demand for drying and to address climate change scenario. But performance and reliability of solar dryers depend hugely on sunshine period, climatic conditions, therefore, offer a limited control over drying conditions and have lower efficiencies. Solar drying technology, supported by Photovoltaic (PV) power plant and hybrid type solar air collector can potentially overpower the disadvantages of solar dryers. For development of such robust hybrid dryers; to ensure quality and shelf-life of paddy grains the optimization of process parameter becomes extremely critical. Investigation of the moisture distribution profile within the grains becomes necessary in order to avoid over drying or under drying of food grains in hybrid solar dryer. Computational simulations based on finite element modeling can serve as potential tool in providing a better insight of moisture migration during drying process. Hence, present work aims at optimizing the process parameters and to develop a 3-dimensional (3D) finite element model (FEM) for predicting moisture profile in paddy during solar drying. COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Furthermore, optimization of process parameters (power level, air velocity and moisture content) was done using response surface methodology in design expert software. 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed and validated with experimental data. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Furthermore, optimized process parameters for drying paddy were found to be 700 W, 2.75 m/s at 13% (wb) with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product. PV-integrated hybrid solar dryers can be employed as potential and cutting edge drying technology alternative for sustainable energy and food security.

Keywords: finite element modeling, moisture migration, paddy grain, process optimization, PV integrated hybrid solar dryer

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Authors: T. Santiboon, S. Tongbu, P. S. Saihong

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This study focuses on investigating students' perceptions of their physics classroom learning environments of their individualizations and their interactions with the instructional practicum in teaching physics of the master science trainee educational students for improving and creating attitude skills’ sustainable development toward physics for upper secondary educational students in Thailand. Associations between these perceptions and students' attitudes toward physics were also determined. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI) modified from the original Science Laboratory Environment Inventory. The 25-item Individualized Classroom Environment Questionnaire (ICEQ) was assessed those dimensions which distinguish individualized physics classrooms from convention on individualized open and inquiry-based education Teacher-student interactions were assessed with the 48-item Questionnaires on Teacher Interaction (QTI). Both these questionnaires have an Actual Form (assesses the class as it actually is) and a Preferred Form (asks the students what they would prefer their class to be like - the ideal situation). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) modified from the original Test Of Science-Related Attitude (TOSRA) The questionnaires were administered in three phases with the Custer Random Sampling technique to a sample consisted of 989 students in 28 physics classes from 10 schools at the grade 10, 11, and 12 levels in the Secondary Educational Service Area 26 (Maha Sarakham Province) and Area 27 (Roi-Et). Statistically significant differences were found between the students' perceptions of actual-1, actual-2 and preferred environments of their physics laboratory and distinguish individualized classrooms, and teacher interpersonal behaviors with their improving and creating attitudes skills’ sustainable development to their physics classes also were found. Predictions of the monitoring and evaluation of master science trainee educational students of their practicum in teaching physics; students’ skills developments of their physics achievements’ sustainable for the set of actual and preferred environments as a whole and physics related attitudes also were correlated. The R2 values indicate that 58%, 67%, and 84% of the variances in students’ attitudes to their actuale-1, actual-2 and preferred for the PLEI; 42%,science trainee educational students of their practicum in teaching physics; students’ skill developments of their physics achievements’ sustainable for the set of actual and preferred environments as a whole and physics related attitudes also were correlated. The R2 values indicate that 58%, 67%, and 84% of the variances in students’ attitudes to their actuale-1, actual-2 and preferred for the PLEI; 42%, 63%, and 72% for the ICEQ, and 38%, 59%, and 68% for the QTI in physics environment classes were attributable to their perceptions of their actual and preferred physics environments and their developing creative science skills’ sustainable toward physics, consequently. Based on all the findings, suggestions for improving the physics laboratory and individualized classes and teacher interpersonal behaviors with students' perceptions are provided of their improving and creating attitude skills’ sustainable development by the master science trainee educational students ’ instructional administrations.

Keywords: promotion, instructional model, qualitative method, reflective thinking, trainee teacher student

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Authors: Mohd Suhaizan Shamsuddin

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Urbanization exacerbates the environment quality and pressures of matured urban trees' growth and development in changing environment. The growth of struggled matured urban tree-roots by spreading within the existences of infrastructures, resulting in large damage to the structured and declined growth. Many physiological growths declined or damages by the present and installations of infrastructures within and nearby root zone. Afford to remain both matured urban tree and infrastructures as a service provider causes damage and death, respectively. Inasmuch, spending more expenditure on fixing both or removing matured urban trees as risky to the future environment as the mitigation methods to reduce the problems are unconcerned. This paper aims to explain mitigation method practices of reducing the encountered problems of matured urban tree-roots settling and infrastructures while modified urban soil to sustain at an optimum level. Three categories capturing encountered conflicts growth of matured urban tree-roots growth within and nearby infrastructures by mitigating the problems of limited soil spaces, poor soil structures and soil space barrier installations and maintenance. The limited soil space encountered many conflicts and identified six methods that mitigate the survival tree-roots, such as soil volume/mounding, soil replacement/amendment for the radial trench, soil spacing-root bridge, root tunneling, walkway/pavement rising/diverted, and suspended pavement. The limited soil spaces are mitigation affords of inadequate soil-roots and spreading root settling and modification of construction soil media since the barrier existed and installed in root trails or zones. This is the reason for enabling tree-roots spreading and finds adequate sources (nutrients, water uptake and oxygen), spaces and functioning to stability stand of root anchorage since the matured tree grows larger. The poor soil structures were identified as three methods to mitigate soil materials' problems, and fewer soil voids comprise skeletal soil, structural soil, and soil cell. Mitigation of poor soil structure is altering the existing and introducing new structures by modifying the quantities and materials ratio allowing more voids beneath for roots spreading by considering the above structure of foot and vehicle traffics functioning or load-bearing. The soil space barrier installations and maintenance recognized to sustain both infrastructures and tree-roots grown in limited spaces and its benefits, the root barrier installations and root pruning are recommended. In conclusion, these recommended methods attempt to mitigate the present problems encountered at a particular place and problems among tree-roots and infrastructures exist. The combined method is the best way to alleviates the conflicts since the recognized conflicts are between tree-roots and man-made while the urban soil is modified. These presenting methods are most considered to sustain the matured urban trees' lifespan growth in the urban environment.

Keywords: urban tree-roots, limited soil spaces, poor soil structures, soil space barrier and maintenance

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Authors: Michael J. Haslip

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Character strength application improves performance and well-being in adults across industries, but the potential impact of character strength training among early childhood educators is mostly unknown. To explore how character strengths are applied by early childhood educators at work, a qualitative study was completed alongside professional development provided to a group of in-service teachers of children ages 0-5 in Philadelphia, Pennsylvania, United States. Study participants (n=17) were all female. The majority of participants were non-white, in full-time lead or assistant teacher roles, had at least ten years of experience and a bachelor’s degree. Teachers were attending professional development weekly for 2 hours over a 10-week period on the topic of social and emotional learning and child guidance. Related to this training were modules and sessions on identifying a teacher’s character strength profile using the Values in Action classification of 24 strengths (e.g., humility, perseverance) that have a scientific basis. Teachers were then asked to apply their character strengths to help resolve current workplace challenges. This study identifies which character strengths the teachers reported using most frequently and the nature of the workplace challenges being resolved in this context. The study also reports how difficult these challenges were to the teachers and their success rate at resolving workplace challenges using a character strength application plan. The study also documents how teachers’ own use of character strengths relates to their modeling of these same traits (e.g., kindness, teamwork) for children, especially when the nature of the workplace challenge directly involves the children, such as when addressing issues of classroom management and behavior. Data were collected on action plans (reflective templates) which teachers wrote to explain the work challenge they were facing, the character strengths they used to address the challenge, their plan for applying strengths to the challenge, and subsequent results. Content analysis and thematic analysis were used to investigate the research questions using approaches that included classifying, connecting, describing, and interpreting data reported by educators. Findings reveal that teachers most frequently use kindness, leadership, fairness, hope, and love to address a range of workplace challenges, ranging from low to high difficulty, involving children, coworkers, parents, and for self-management. Teachers reported a 71% success rate at fully or mostly resolving workplace challenges using the action plan method introduced during professional development. Teachers matched character strengths to challenges in different ways, with certain strengths being used mostly when the challenge involved children (love, forgiveness), others mostly with adults (bravery, teamwork), and others universally (leadership, kindness). Furthermore, teacher’s application of character strengths at work involved directly modeling character for children in 31% of reported cases. The application of character strengths among early childhood educators may play a significant role in improving teacher well-being, reducing job stress, and improving efforts to model character for young children.

Keywords: character strengths, positive psychology, professional development, social-emotional learning

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: A. Shakoor, M. Arshad

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The utilization of groundwater resources in irrigation has significantly increased during the last two decades due to constrained canal water supplies. More than 70% of the farmers in the Punjab, Pakistan, depend directly or indirectly on groundwater to meet their crop water demands and hence, an unchecked paradigm shift has resulted in aquifer depletion and deterioration. Therefore, a comprehensive research was carried at central Punjab-Pakistan, regarding spatiotemporal variation in groundwater level and quality. Processing MODFLOW for window (PMWIN) and MT3D (solute transport model) models were used for existing and future prediction of groundwater level and quality till 2030. The comprehensive data set of aquifer lithology, canal network, groundwater level, groundwater salinity, evapotranspiration, groundwater abstraction, recharge etc. were used in PMWIN model development. The model was thus, successfully calibrated and validated with respect to groundwater level for the periods of 2003 to 2007 and 2008 to 2012, respectively. The coefficient of determination (R2) and model efficiency (MEF) for calibration and validation period were calculated as 0.89 and 0.98, respectively, which argued a high level of correlation between the calculated and measured data. For solute transport model (MT3D), the values of advection and dispersion parameters were used. The model used for future scenario up to 2030, by assuming that there would be no uncertain change in climate and groundwater abstraction rate would increase gradually. The model predicted results revealed that the groundwater would decline from 0.0131 to 1.68m/year during 2013 to 2030 and the maximum decline would be on the lower side of the study area, where infrastructure of canal system is very less. This lowering of groundwater level might cause an increase in the tubewell installation and pumping cost. Similarly, the predicted total dissolved solids (TDS) of the groundwater would increase from 6.88 to 69.88mg/L/year during 2013 to 2030 and the maximum increase would be on lower side. It was found that in 2030, the good quality would reduce by 21.4%, while marginal and hazardous quality water increased by 19.28 and 2%, respectively. It was found from the simulated results that the salinity of the study area had increased due to the intrusion of salts. The deterioration of groundwater quality would cause soil salinity and ultimately the reduction in crop productivity. It was concluded from the predicted results of groundwater model that the groundwater deteriorated with the depth of water table i.e. TDS increased with declining groundwater level. It is recommended that agronomic and engineering practices i.e. land leveling, rainwater harvesting, skimming well, ASR (Aquifer Storage and Recovery Wells) etc. should be integrated to meliorate management of groundwater for higher crop production in salt affected soils.

Keywords: groundwater quality, groundwater management, PMWIN, MT3D model

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Authors: Martina Katalin Szabó, István Üveges

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In this paper, the usage of negative emotive words is examined on the basis of a large Hungarian twitter-database via NLP methods. The data is analysed from a gender point of view, as well as changes in language usage over time. The term negative emotive word refers to those words that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g. rohadt jó ’damn good’) or a sentiment expression with positive polarity despite their negative prior polarity (e.g. brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’. Based on the findings of several authors, the same phenomenon can be found in other languages, so it is probably a language-independent feature. For the recent analysis, 67783 tweets were collected: 37818 tweets (19580 tweets written by females and 18238 tweets written by males) in 2016 and 48344 (18379 tweets written by females and 29965 tweets written by males) in 2021. The goal of the research was to make up two datasets comparable from the viewpoint of semantic changes, as well as from gender specificities. An exhaustive lexicon of Hungarian negative emotive intensifiers was also compiled (containing 214 words). After basic preprocessing steps, tweets were processed by ‘magyarlanc’, a toolkit is written in JAVA for the linguistic processing of Hungarian texts. Then, the frequency and collocation features of all these words in our corpus were automatically analyzed (via the analysis of parts-of-speech and sentiment values of the co-occurring words). Finally, the results of all four subcorpora were compared. Here some of the main outcomes of our analyses are provided: There are almost four times fewer cases in the male corpus compared to the female corpus when the negative emotive intensifier modified a negative polarity word in the tweet (e.g., damn bad). At the same time, male authors used these intensifiers more frequently, modifying a positive polarity or a neutral word (e.g., damn good and damn big). Results also pointed out that, in contrast to female authors, male authors used these words much more frequently as a positive polarity word as well (e.g., brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’). We also observed that male authors use significantly fewer types of emotive intensifiers than female authors, and the frequency proportion of the words is more balanced in the female corpus. As for changes in language usage over time, some notable differences in the frequency and collocation features of the words examined were identified: some of the words collocate with more positive words in the 2nd subcorpora than in the 1st, which points to the semantic change of these words over time.

Keywords: gender differences, negative emotive words, semantic changes over time, twitter

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Merve Yünlü, Nihat Kandemir, Aylin Ersoy

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Temperature sensors are used in home appliances not only to monitor the basic functions of the machine but also to minimize energy consumption and ensure safe operation. In parallel with the development of smart home applications and IoT algorithms, these sensors produce important data such as the frequency of use of the machine, user preferences, and the compilation of critical data in terms of diagnostic processes for fault detection throughout an appliance's operational lifespan. Commercially available thin-film resistive temperature sensors have a well-established manufacturing procedure that allows them to operate over a wide temperature range. However, these sensors are over-designed for white goods applications. The operating temperature range of these sensors is between -70°C and 850°C, while the temperature range requirement in home appliance applications is between 23°C and 500°C. To ensure the operation of commercial sensors in this wide temperature range, usually, a platinum coating of approximately 1-micron thickness is applied to the wafer. However, the use of platinum in coating and the high coating thickness extends the sensor production process time and therefore increases sensor costs. In this study, an attempt was made to develop a low-cost temperature sensor design and production method that meets the technical requirements of white goods applications. For this purpose, a custom design was made, and design parameters (length, width, trim points, and thin film deposition thickness) were optimized by using statistical methods to achieve the desired resistivity value. To develop thin film resistive temperature sensors, one side polished sapphire wafer was used. To enhance adhesion and insulation 100 nm silicon dioxide was coated by inductively coupled plasma chemical vapor deposition technique. The lithography process was performed by a direct laser writer. The lift-off process was performed after the e-beam evaporation of 10 nm titanium and 280 nm platinum layers. Standard four-point probe sheet resistance measurements were done at room temperature. The annealing process was performed. Resistivity measurements were done with a probe station before and after annealing at 600°C by using a rapid thermal processing machine. Temperature dependence between 25-300 °C was also tested. As a result of this study, a temperature sensor has been developed that has a lower coating thickness than commercial sensors but can produce reliable data in the white goods application temperature range. A relatively simplified but optimized production method has also been developed to produce this sensor.

Keywords: thin film resistive sensor, temperature sensor, household appliance, sustainability, energy efficiency

Procedia PDF Downloads 73

Authors: Yuhui Liu, Lydia Speyer, Jasmin Wertz, Ingrid Obsuth

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Childhood adversities refer to situations where a child's basic needs for safety and support are compromised, leading to substantial disruptions in their emotional, cognitive, social, or neurobiological development. Given the prevalence of adversities (8%-39%), their impact on developmental outcomes is challenging to completely avoid. Delinquency is an important consequence of childhood adversities, given its potential causing violence and other forms of victimisation, influencing victims, delinquents, their families, and the whole of society. Studying mediators helps explain the link between childhood adversity and delinquency, which aids in designing effective intervention programs that target explanatory variables to disrupt the path and mitigate the effects of childhood adversities on delinquency. The Dimensional Model of Adversity and Psychopathology suggests that threat-based adversities influence outcomes through emotion processing, while deprivation-based adversities do so through cognitive mechanisms. Thus, considering a wide range of threat-based and deprivation-based adversities and their co-occurrence and their associations with delinquency through cognitive and emotional mechanisms is essential. This study employs the Millennium Cohort Study, tracking the development of approximately 19,000 individuals born across England, Scotland, Wales and Northern Ireland, representing a nationally representative sample. Parallel mediation models compare the mediating roles of self-esteem (cognitive) and depression (affective) in the associations between childhood adversities and delinquency. Eleven types of childhood adversities were assessed both individually and through latent class analysis, considering adversity experiences from birth to early adolescence. This approach aimed to capture how threat-based, deprived-based, or combined threat and deprived-based adversities are associated with delinquency. Eight latent classes were identified: three classes (low adversity, especially direct and indirect violence; low childhood and moderate adolescent adversities; and persistent poverty with declining bullying victimisation) were negatively associated with delinquency. In contrast, three classes (high parental alcohol misuse, overall high adversities, especially regarding household instability, and high adversity) were positively associated with delinquency. When mediators were included, all classes showed a significant association with delinquency through depression, but not through self-esteem. Among the eleven single adversities, seven were positively associated with delinquency, with five linked through depression and none through self-esteem. The results imply the importance of affective variables, not just for threat-based but also deprivation-based adversities. Academically, this suggests exploring other mechanisms linking adversities and delinquency since some adversities are linked through neither depression nor self-esteem. Clinically, intervention programs should focus on affective variables like depression to mitigate the effects of childhood adversities on delinquency.

Keywords: childhood adversity, delinquency, depression, self-esteem

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Waste from the food-processing industry is produced in large amount and contains high levels of lignocellulose. Due to continuous accumulation throughout the year in large quantities, it creates a major environmental problem worldwide. The chemical composition of these wastes (up to 75% of its composition is contributed by polysaccharide) makes it inexpensive raw material for the production of value-added products such as biofuel, bio-solvents, nanocrystalline cellulose and enzymes. In order to use lignocellulose as the raw material for the microbial fermentation, the substrate is subjected to enzymatic treatment, which leads to the release of reducing sugars such as glucose and xylose. However, the inherent properties of lignocellulose such as presence of lignin, pectin, acetyl groups and the presence of crystalline cellulose contribute to recalcitrance. This leads to poor sugar yields upon enzymatic hydrolysis of lignocellulose. A pre-treatment method is generally applied before enzymatic treatment of lignocellulose that essentially removes recalcitrant components in biomass through structural breakdown. Present study is carried out to find out the best pre-treatment method for the maximum liberation of reducing sugars from spent coffee waste (SPW). SPW was subjected to a range of physical, chemical and physico-chemical pre-treatment followed by a sequential, combinatorial pre-treatment strategy is also applied on to attain maximum sugar yield by combining two or more pre-treatments. All the pre-treated samples were analysed for total reducing sugar followed by identification and quantification of individual sugar by HPLC coupled with RI detector. Besides, generation of any inhibitory compounds such furfural, hydroxymethyl furfural (HMF) which can hinder microbial growth and enzyme activity is also monitored. Results showed that ultrasound treatment (31.06 mg/L) proved to be the best pre-treatment method based on total reducing content followed by dilute acid hydrolysis (10.03 mg/L) while galactose was found to be the major monosaccharide present in the pre-treated SPW. Finally, the results obtained from the study were used to design a sequential lignocellulose pre-treatment protocol to decrease the formation of enzyme inhibitors and increase sugar yield on enzymatic hydrolysis by employing cellulase-hemicellulase consortium. Sequential, combinatorial treatment was found better in terms of total reducing yield and low content of the inhibitory compounds formation, which could be due to the fact that this mode of pre-treatment combines several mild treatment methods rather than formulating a single one. It eliminates the need for a detoxification step and potential application in the valorisation of lignocellulosic food waste.

Keywords: lignocellulose, enzymatic hydrolysis, pre-treatment, ultrasound

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Authors: Yu Zhang, Jie Wu, Li Dong

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Rural tourism is the service industry which regards the agricultural production, rural life, rural nature and cultural landscape as the tourist attraction. It aims to meet the needs of the city tourists such as country sightseeing, vacation, and leisure. According to the difference of the tourist resources, the rural settlements can be divided into different types: The type of tourism resources, scenic spot, and peri-urban. In the past ten years, the rural tourism has promoted the industrial transformation and economic growth in rural areas of China. And it is conducive to the coordinated development of urban and rural areas and has greatly improved the ecological environment and the standard of living for farmers in rural areas. At the same time, a large number of buildings and sites are built in the countryside in order to enhance the tourist attraction and the ability of tourist reception and also to increase the travel comfort and convenience, which has significant influence on the spatial evolution of the village settlement. This article takes the XiangYing Subdistrict, which is in JinPu District of Dalian in China as the exemplification and uses the technology of Remote Sensing (RS), Geographic Information System (GIS) and the technology of Landscape Spatial Analysis to study the influence of the rural tourism development in the rural settlement spaces in four steps. First, acquiring the remote sensing image data at different times of 8 administrative villages in the XiangYing Subdistrict, by using the remote sensing application EDRAS8.6; second, vectoring basic maps of XiangYing Subdistrict including its land-use map with the application of ArcGIS 9.3, associating with social and economic attribute data of rural settlements and analyzing on the rural evolution visually; third, quantifying the comparison of these patches in rural settlements by using the landscape spatial calculation application Fragstats 3.3 and analyzing on the evolution of the spatial structure of settlement in macro and medium scale; finally, summarizing the evolution characteristics and internal reasons of tourism-oriented rural settlements. The main findings of this article include: first of all, there is difference in the evolution of the spatial structure between the developing rural settlements and undeveloped rural settlements among the eight administrative villages; secondly, the villages relying on the surrounding tourist attractions, the villages developing agricultural ecological garden and the villages with natural or historical and cultural resources have different laws of development; then, the rural settlements whose tourism development in germination period, development period and mature period have different characteristics of spatial evolution; finally, the different evolution modes of the tourism-oriented rural settlement space have different influences on the protection and inheritance of the village scene. The development of tourism has a significant impact on the spatial evolution of rural settlement. The intensive use of rural land and natural resources is the fundamental principle to protect the rural cultural landscape and ecological environment as well as the critical way to improve the attraction of rural tourism and promote the sustainable development of countryside.

Keywords: landscape pattern, rural settlement, spatial evolution, tourism-oriented, Xiangying Subdistrict

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Authors: Maria David, Tunde A. Tasko, Katalin Hejja-Nagy, Laszlo Dorner

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The authors have been concerned with research on learning since 1998. Recently, the focus of our interest is how prevalent use of information and communication technology (ICT) influences students' learning abilities, skills of self-regulated learning and learning efficiency. Nowadays, there are three dominant theories about the psychic effects of ICT use: According to social optimists, modern ICT devices have a positive effect on thinking. As to social pessimists, this effect is rather negative. And, regarding the views of biological optimists, the change is obvious, but these changes can fit into the mankind's evolved neurological system as did writing long ago. Mentality of 'digital natives' differ from that of elder people. They process information coming from the outside world in an other way, and different experiences result in different cerebral conformation. In this regard, researchers report about both positive and negative effects of ICT use. According to several studies, it has a positive effect on cognitive skills, intelligence, school efficiency, development of self-regulated learning, and self-esteem regarding learning. It is also proven, that computers improve skills of visual intelligence such as spacial orientation, iconic skills and visual attention. Among negative effects of frequent ICT use, researchers mention the decrease of critical thinking, as permanent flow of information does not give scope for deeper cognitive processing. Aims of our present study were to uncover developmental characteristics of self-regulated learning in different age groups and to study correlations of learning efficiency, the level of self-regulated learning and frequency of use of computers. Our subjects (N=1600) were primary and secondary school students and university students. We studied four age groups (age 10, 14, 18, 22), 400 subjects of each. We used the following methods: the research team developed a questionnaire for measuring level of self-regulated learning and a questionnaire for measuring ICT use, and we used documentary analysis to gain information about grade point average (GPA) and results of competence-measures. Finally, we used computer tasks to measure cognitive abilities. Data is currently under analysis, but as to our preliminary results, frequent use of computers results in shorter response time regarding every age groups. Our results show that an ordinary extent of ICT use tend to increase reading competence, and had a positive effect on students' abilities, though it didn't show relationship with school marks (GPA). As time passes, GPA gets worse along with the learning material getting more and more difficult. This phenomenon draws attention to the fact that students are unable to switch from guided to independent learning, so it is important to consciously develop skills of self-regulated learning.

Keywords: digital natives, ICT, learning efficiency, reading competence, self-regulated learning

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Authors: Insiya Bhalloo

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It is quite common in the Muslim faith for non-Arabic speakers to be able to convert written Arabic, especially Quranic Arabic, into a phonological code without significant semantic or syntactic knowledge. This is due to prior experience learning to read the Quran (a religious text written in Classical Arabic), from a very young age such as via enrolment in Quranic Arabic classes. As compared to native speakers of Arabic, these Arabic readers do not have a comprehensive morpho-syntactic knowledge of the Arabic language, nor can understand, or engage in Arabic conversation. The study seeks to investigate whether mere phonological experience (as indicated by the Arabic readers’ experience with Arabic phonology and the sound-system) is sufficient to cause phonological-interference during word recognition of previously-heard words, despite the participants’ non-native status. Both native speakers of Arabic and non-native speakers of Arabic, i.e., those individuals that learned to read the Quran from a young age, will be recruited. Each experimental session will include two phases: An exposure phase and a test phase. During the exposure phase, participants will be presented with Arabic words (n=40) on a computer screen. Half of these words will be common words found in the Quran while the other half will be words commonly found in Modern Standard Arabic (MSA) but either non-existent or prevalent at a significantly lower frequency within the Quran. During the test phase, participants will then be presented with both familiar (n = 20; i.e., those words presented during the exposure phase) and novel Arabic words (n = 20; i.e., words not presented during the exposure phase. ½ of these presented words will be common Quranic Arabic words and the other ½ will be common MSA words but not Quranic words. Moreover, ½ the Quranic Arabic and MSA words presented will be comprised of nouns, while ½ the Quranic Arabic and MSA will be comprised of verbs, thereby eliminating word-processing issues affected by lexical category. Participants will then determine if they had seen that word during the exposure phase. This study seeks to investigate whether long-term phonological memory, such as via childhood exposure to Quranic Arabic orthography, has a differential effect on the word-recognition capacities of native Arabic speakers and Arabic readers; we seek to compare the effects of long-term phonological memory in comparison to short-term phonological exposure (as indicated by the presentation of familiar words from the exposure phase). The researcher’s hypothesis is that, despite the lack of lexical knowledge, early experience with converting written Quranic Arabic text into a phonological code will help participants recall the familiar Quranic words that appeared during the exposure phase more accurately than those that were not presented during the exposure phase. Moreover, it is anticipated that the non-native Arabic readers will also report more false alarms to the unfamiliar Quranic words, due to early childhood phonological exposure to Quranic Arabic script - thereby causing false phonological facilitatory effects.

Keywords: modern standard arabic, phonological facilitation, phonological memory, Quranic arabic, word recognition

Procedia PDF Downloads 357

Authors: C. Treadgold, S. Sivaraman

Abstract:

The Starlight Children's Foundation (Starlight) is an Australian non-profit organisation that delivers programs, in partnership with health professionals, to support children, adolescents, and their families who are living with a serious illness. While supporting children and adolescents with life-limiting conditions has always been a feature of Starlight's work, providing a dedicated program, specifically targeting and meeting the needs of the paediatric palliative population, is a recent area of focus. Recognising the challenges in providing children’s palliative services, Starlight initiated a research and development project to better understand and meet the needs of this group. The aim was to create a program which enhances the wellbeing of children, adolescents, and their families receiving paediatric palliative care in their community through the provision of on-going, tailored, positive experiences or 'moments'. This paper will present the results of the formative evaluation of this unique program, highlighting the development processes and outcomes of the pilot. The pilot was designed using an innovation methodology, which included a number of research components. There was a strong belief that it needed to be delivered in partnership with a dedicated palliative care team, helping to ensure the best interests of the family were always represented. This resulted in Starlight collaborating with both the Victorian Paediatric Palliative Care Program (VPPCP) at the Royal Children's Hospital, Melbourne, and the Sydney Children's Hospital Network (SCHN) to pilot the 'Moments' program. As experts in 'positive disruption', with a long history of collaborating with health professionals, Starlight was well placed to deliver a program which helps children, adolescents, and their families to experience moments of joy, connection and achieve their own sense of accomplishment. Building on Starlight’s evidence-based approach and experience in creative service delivery, the program aims to use the power of 'positive disruption' to brighten the lives of this group and create important memories. The clinical and Starlight team members collaborate to ensure that the child and family are at the centre of the program. The design of each experience is specific to their needs and ensures the creation of positive memories and family connection. It aims for each moment to enhance quality of life. The partnership with the VPPCP and SCHN has allowed the program to reach families across metropolitan and regional locations. In late 2019 a formative evaluation of the pilot was conducted utilising both quantitative and qualitative methodologies to document both the delivery and outcomes of the program. Central to the evaluation was the interviews conducted with both clinical teams and families in order to gain a comprehensive understanding of the impact of and satisfaction with the program. The findings, which will be shared in this presentation, provide practical insight into the delivery of the program, the key elements for its success with families, and areas which could benefit from additional research and focus. It will use stories and case studies from the pilot to highlight the impact of the program and discuss what opportunities, challenges, and learnings emerged.

Keywords: children, families, memory making, pediatric palliative care, support

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Authors: Zahra Shakoori, Farid Salmanpour

Abstract:

Pollination services are a vital service for the ecosystem to maintain environmental stability. The decline of pollinators can disrupt the ecological balance by affecting components of biodiversity. Bumble bees are crucial pollinators, playing a vital role in maintaining plant diversity. This study investigated the temporal patterns of their visitation to flowers in Kiasar National Park, Iran. Observations were conducted in Jun 2024, totaling 442 person-minutes of observation. Five species of bumble bees were identified. The study revealed that they consistently visited an average of 12-15 flowers per minute, regardless of species. The findings highlight the importance of protecting natural habitats, where their populations are thriving in the absence of human-induced stressors. This study was conducted in Kiasar National Park, located in the southeast of Mazandaran, northern Iran. The surveyed area, at an altitude of 1800-2200 meters, includes both forest and pasture. Bumble bee surveys were carried out on sunny days from June 2024, starting at dawn and ending at sunset. To avoid double-counting, we systematically searched for foraging habitats on low-sloping ridges with high mud density, frequently moving between patches. We recorded bumble bee visits to flowers and plant species per minute using direct observation, a stopwatch, and a pre-prepared form. We used statistical analysis of variance (ANOVA) with a confidence level of 95% to examine potential differences in foraging rates across different bumble bee species, flowers, plant bases, and plant species visited. Bumble bee identification relied on morphological indicators. A total of 442 person-minutes of bumble bee observations were recorded. Five species of bumble bees (Bombus fragrans, Bombus haematurus, Bombus lucorum, Bombus melanurus, Bombus terrestris) were identified during the study. The results of this study showed that the visits of bumble bees to flower sources were not different from each other. In general, bumble bees visit an average of 12-15 flowers every 60 seconds. In addition, at the same time they visit between 3-5 plant bases. Finally, they visit an average of 1 to 3 plant species per minute. While many taxa contribute to pollination, insects—especially bees—are crucial for maintaining plant diversity and ecosystem functions. As plant diversity increases, the stopping rate of pollinating insects rises, which reduces their foraging activity. Bumble bees, therefore, stop more frequently in natural areas than in agricultural fields due to higher plant diversity. Our findings emphasize the need to protect natural habitats like Kiasar National Park, where bumble bees thrive without human-induced stressors like pesticides, livestock grazing, and pollution. With bumble bee populations declining globally, further research is essential to understand their behavior in different environments and develop effective conservation strategies to protect them.

Keywords: bumble bees, pollination, pollinator, plant diversity, Iran

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Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

Abstract:

Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

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Authors: Saddam Hussain, Ghadeer Mohsen Albadrani

Abstract:

Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.

Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain

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