Search results for: waste processing

Authors: Chiyoung Kim, Jaegeol Yim

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Bus service is often either main or the only public transportation available in cities. In metropolitan areas, both subways and buses are available whereas in the medium sized cities buses are usually the only type of public transportation available. Bus Information Systems (BIS) provide current locations of running buses, efficient routes to travel from one place to another, points of interests around a given bus stop, a series of bus stops consisting of a given bus route, and so on to users. Thanks to BIS, people do not have to waste time at a bus stop waiting for a bus because BIS provides exact information on bus arrival times at a given bus stop. Therefore, BIS does a lot to promote the use of buses contributing to pollution reduction and saving natural resources. BIS implementation costs a huge amount of budget as it requires a lot of special equipment such as road side equipment, automatic vehicle identification and location systems, trunked radio systems, and so on. Consequently, medium and small sized cities with a low budget cannot afford to install BIS even though people in these cities need BIS service more desperately than people in metropolitan areas. It is possible to provide BIS service at virtually no cost under the assumption that everybody carries a smartphone and there is at least one person with a smartphone in a running bus who is willing to reveal his/her location details while he/she is sitting in a bus. This assumption is usually true in the real world. The smartphone penetration rate is greater than 100% in the developed countries and there is no reason for a bus driver to refuse to reveal his/her location details while driving. We have developed a mobile app that periodically reads values of sensors including GPS and sends GPS data to the server when the bus stops or when the elapsed time from the last send attempt is greater than a threshold. This app detects the bus stop state by investigating the sensor values. The server that receives GPS data from this app has also been developed. Under the assumption that the current locations of all running buses collected by the mobile app are recorded in a database, we have also developed a web site that provides all kinds of information that most BISs provide to users through the Internet. The development environment is: OS: Windows 7 64bit, IDE: Eclipse Luna 4.4.1, Spring IDE 3.7.0, Database: MySQL 5.1.7, Web Server: Apache Tomcat 7.0, Programming Language: Java 1.7.0_79. Given a start and a destination bus stop, it finds a shortest path from the start to the destination using the Dijkstra algorithm. Then, it finds a convenient route considering number of transits. For the user interface, we use the Google map. Template classes that are used by the Controller, DAO, Service and Utils classes include BUS, BusStop, BusListInfo, BusStopOrder, RouteResult, WalkingDist, Location, and so on. We are now integrating the mobile app system and the web app system.

Keywords: bus information system, GPS, mobile app, web site

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Authors: Pankaj Dhiman, Simranjeet Kaur

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This research paper presents a comprehensive sentiment analysis of social media responses to videos on Facebook, YouTube, Twitter, and Instagram during the 2024 Indian general elections. The study focuses on the sentiment patterns of voters towards the National Democratic Alliance (NDA) and The Indian National Developmental Inclusive Alliance (INDIA) on these platforms. The analysis aims to understand the impact of social media on voter sentiment and its correlation with the election outcome. The study employed a mixed-methods approach, combining both quantitative and qualitative methods. With a total of 200 posts analysed during general election-2024 final phase, the sentiment analysis was conducted using natural language processing (NLP) techniques, including sentiment dictionaries and machine learning algorithms. The results show that NDA received significantly more positive sentiment responses across all platforms, with a positive sentiment score of 47% compared to INDIA's score of 38.98 %. The analysis also revealed that Twitter and YouTube were the most influential platforms in shaping voter sentiment, with 60% of the total sentiment score coming from these two platforms. The study's findings suggest that social media sentiment analysis can be a valuable tool for understanding voter sentiment and predicting election outcomes. The results also highlight the importance of social media in shaping public opinion and the need for political parties to engage effectively with voters on these platforms. The study's implications are significant, as they indicate that social media can be a key factor in determining the outcome of elections. The findings also underscore the need for political parties to develop effective social media strategies to engage with voters and shape public opinion.

Keywords: Indian Elections-2024, NDA, INDIA, sentiment analysis, social media, democracy

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Authors: Michal Brazda, Miroslav Urbanek, Martina Koukolikova

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This work focuses on the development of functional surfaces and edges for cutting and forming tools created through the Directed Energy Deposition (DED) technology. In the context of growing challenges in modern engineering, additive technologies, especially DED, present an innovative approach to manufacturing tools for forming and cutting. One of the key features of DED is its ability to precisely and efficiently deposit Fully dense metals from powder feedstock, enabling the creation of complex geometries and optimized designs. Gradually, it becomes an increasingly attractive choice for tool production due to its ability to achieve high precision while simultaneously minimizing waste and material costs. Tools created using DED technology gain significant durability through the utilization of high-performance materials such as nickel alloys and tool steels. For high-temperature applications, Nimonic 80A alloy is applied, while for cold applications, M2 tool steel is used. The addition of ceramic materials, such as tungsten carbide, can significantly increase the tool's resistance. The introduction of functionally graded materials is a significant contribution, opening up new possibilities for gradual changes in the mechanical properties of the tool and optimizing its performance in different sections according to specific requirements. In this work, you will find an overview of individual applications and their utilization in the industry. Microstructural analyses have been conducted, providing detailed insights into the structure of individual components alongside examinations of the mechanical properties and tool life. These analyses offer a deeper understanding of the efficiency and reliability of the created tools, which is a key element for successful development in the field of cutting and forming tools. The production of functional surfaces and edges using DED technology can result in financial savings, as the entire tool doesn't have to be manufactured from expensive special alloys. The tool can be made from common steel, onto which a functional surface from special materials can be applied. Additionally, it allows for tool repairs after wear and tear, eliminating the need for producing a new part and contributing to an overall cost while reducing the environmental footprint. Overall, the combination of DED technology, functionally graded materials, and verified technologies collectively set a new standard for innovative and efficient development of cutting and forming tools in the modern industrial environment.

Keywords: additive manufacturing, directed energy deposition, DED, laser, cutting tools, forming tools, steel, nickel alloy

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Authors: Omuvwie R. Ewien

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Palm oil production in Delta State, Nigeria, is a significant economic activity. However, ensuring its sustainability is crucial to mitigate environmental impacts, promote social equity, and maintain long-term economic viability. This abstract provides an overview of palm oil production sustainability in Delta State, focusing on environmental, social, and economic aspects. In terms of environmental sustainability, the impact of palm oil plantations on deforestation and biodiversity loss is explored. The adoption of sustainable land use practices and measures to reduce greenhouse gas emissions, such as conserving high conservation value areas and utilizing methane capture systems, are highlighted. Social sustainability considerations encompass the inclusion and empowerment of smallholders, ensuring fair labor practices and community engagement. Supporting small-scale farmers, promoting fair working conditions, and investing in local infrastructure and services are identified as key strategies. Economic sustainability is emphasized through yield improvement, efficiency, and value addition. Enhancing productivity and profitability for farmers, promoting downstream processing and market diversification, and building economic resilience is crucial for long-term sustainability. Government policies, including regulatory frameworks and public-private collaborations, play a pivotal role in promoting sustainable palm oil production. Enabling policies and partnerships with industry stakeholders and NGOs facilitates the adoption of sustainable practices. Challenges such as illegal activities, the need to balance economic development with environmental conservation, and leveraging technology for sustainability are discussed. The abstract concludes by emphasizing the importance of stakeholders' commitment to prioritize sustainable palm oil production in Delta State, Nigeria, for a sustainable future.

Keywords: palm oil production, environmental sustainability, community development, yield improvement, future outlook

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Authors: J. Wicks

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Aim: To develop a simple methodology to allow collected heart rate (HR) data from inexpensive wearable devices to be expressed in a suitable format (METs) to quantitate occupational (and recreational) activity. Introduction: Assessment of occupational activity is commonly done by utilizing questionnaires in combination with prescribed MET levels of a vast range of previously measured activities. However for any individual the intensity of performing a specific activity can vary significantly. Ideally objective measurement of individual activity is preferred. Though there are a wide range of HR recording devices there is a distinct lack methodology to allow processing of collected data to quantitate energy expenditure (EE). The HR index equation expresses METs in relation to relative HR i.e. the ratio of activity HR to resting HR. The use of this equation provides a simple utility for objective measurement of EE. Methods: During a typical occupational work period of approximately 8 hours HR data was recorded using a Polar RS 400 wrist monitor. Recorded data was downloaded to a Windows PC and non HR data was stripped from the ASCII file using ‘Notepad’. The HR data was exported to a spread sheet program and sorted by HR range into a histogram format. Three HRs were determined, namely a resting HR (the HR delimiting the lowest 30 minutes of recorded data), a mean HR and a peak HR (the HR delimiting the highest 30 minutes of recorded data). HR indices were calculated (mean index equals mean HR/rest HR and peak index equals peak HR/rest HR) with mean and peak indices being converted to METs using the HR index equation. Conclusion: Inexpensive HR recording devices can be utilized to make reasonable estimates of occupational (or recreational) EE suitable for large scale demographic screening by utilizing the HR index equation. The intrinsic value of the HR index equation is that it is independent of factors that influence absolute HR, namely fitness, smoking and beta-blockade.

Keywords: energy expenditure, heart rate histograms, heart rate index, occupational activity

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

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Authors: Francesca Radice

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Domestic and sexual violence provokes, on average in Australia, one female death per week due to intimate violence behaviours. 83% of couples meet online, and intercepting domestic and sexual violence at this level would be beneficial. It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: sentiment analysis, data mining, predictive policing, virtual manipulation

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Authors: Popoola I. Olayinka, Alamu E. Oladeji, B. Maziya-Dixon

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Cassava, an indigenous crop grown locally by subsistence farmers in Nigeria has potential to bring economic benefits to the country. Consumption of bread and other confectionaries has been on the rise due to lifestyle changes of Nigerian consumers. However, wheat, being the major ingredient for bread and confectionery production does not thrive well under Nigerian climate hence the huge spending on wheat importation. To reduce spending on wheat importation, the Federal Government of Nigeria intends passing into law mandatory inclusion of 20% high-quality cassava flour (HQCF) in wheat flour. While the proposed policy may reduce post harvest loss of cassava, and also increase food security and domestic agricultural productivity, there are downsides to the policy which include reduction in nutritional quality and low sensory appeal of cassava-wheat bread, reluctance of flour millers to use HQCF, technology and processing challenges among others. The policy thus presents an ethical dilemma which must be resolved for its successful implementation. While inclusion of HQCF to wheat flour in bread and confectionery is a topic that may have been well addressed, resolving the ethical dilemma resulting from the act has not received much attention. This paper attempts to resolve this dilemma using various approaches in food ethics (cost benefits, utilitarianism, deontological and deliberative). The Cost-benefit approach did not provide adequate resolution of the dilemma as all the costs and benefits of the policy could not be stated in the quantitative term. The utilitarianism approach suggests that the policy delivers greatest good to the greatest number while the deontological approach suggests that the act (inclusion of HQCF to wheat flour) is right hence the policy is not utterly wrong. The deliberative approach suggests a win-win situation through deliberation with the parties involved.

Keywords: HQCF, ethical dilemma, food security, composite flour, cassava bread

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Authors: Getinet Gezahegn Gebre

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The study examined the impact of gender differences on Crop productivity in Decha woreda of southwest Kafa zone, located 140 Km from Jimma Town and 460 km southwest of Addis Ababa, between Bonga town and Omo River. The specific objectives were to assess the extent to which the agricultural production system is gender oriented, to examine access and control over productive resources, and to estimate men’s and women’s productivity in agriculture. Cross-sectional data collected from a total of 140 respondents were used in this study, whereby 65 were female-headed and 75 were male-headed households. The data were analyzed by using Statistical Package for Social Science (SPSS). Descriptive statistics such as frequency, mean, percentage, t-test and chi-square were used to summarize and compare the information between the two groups. Moreover, Cobb-Douglas(CD) production function was used to estimate the productivity difference in agriculture between male and female-headed households. Results of the study showed that male-headed households (MHH) own more productive resources such as land, livestock, labor and other agricultural inputs as compared to female-headed households (FHH). Moreover, the estimate of CD production function shows that livestock, herbicide use, land size and male labor were statistically significant for MHH, while livestock, land size, herbicides use and female labor were significant variables for FHH. The crop productivity difference between MHH and FHH was about 68.83% in the study area. However, if FHH had equal access to the inputs as MHH, the gross value of the output would be higher by 23.58% for FHH. This might suggest that FHH would be more productive than MHH if they had equal access to inputs as MHH. Based on the results obtained, the following policy implication can be drawn: accessing FHH to inputs that increase the productivity of agriculture, such as herbicides, livestock and male labor; increasing the productivity of land; and introducing technologies that reduce the time and energy of women, especially for enset processing.

Keywords: gender difference, crop productivity, GDP, efficiency

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Authors: Velasco-Rendón María Del Carmen, Cuéllar-Bermúdez Sara Paulina, Parra-Saldívar Roberto

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Phycocyanin is a blue pigment protein with fluorescent activity produced by cyanobacteria. It has been recently studied to determine its anticancer, antioxidant and antiinflamatory potential. Since 2014 it was approved as a Generally Recognized As Safe (GRAS) proteic pigment for the food industry. Therefore, phycocyanin shows potential for the food, nutraceutical, pharmaceutical and diagnostics industry. Conventional phycocyanin extraction includes buffer solutions and ammonium sulphate followed by chromatography or ATPS for protein separation. Therefore, further purification steps are time-requiring, energy intensive and not suitable for scale-up processing. This work presents an alternative to conventional methods that also allows large scale application with commercially available equipment. The extraction was performed by exposing the dry biomass to mechanical cavitation and salting out with NaCl to use an edible reagent. Also, isoelectric point precipitation was used by addition of HCl and neutralization with NaOH. The results were measured and compared in phycocyanin concentration, purity and extraction yield. Results showed that the best extraction condition was the extraction by salting out with 0.20 M NaCl after 30 minutes cavitation, with a concentration in the supernatant of 2.22 mg/ml, a purity of 3.28 and recovery from crude extract of 81.27%. Mechanical cavitation presumably increased the solvent-biomass contact, making the crude extract visibly dark blue after centrifugation. Compared to other systems, our process has less purification steps, similar concentrations in the phycocyanin-rich fraction and higher purity. The contaminants present in our process edible NaCl or low pHs that can be neutralized. It also can be adapted to a semi-continuous process with commercially available equipment. This characteristics make this process an appealing alternative for phycocyanin extraction as a pigment for the food industry.

Keywords: extraction, phycocyanin, precipitation, scale-up

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Authors: Yunhan Zhang, Xiaopeng Li, Zhongxiao Peng

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Additive manufacturing (AM) possesses several key characteristics, including high design freedom, energy-efficient manufacturing process, reduced material waste, high resolution of finished products, and excellent performance of finished products. These advantages have garnered widespread attention and fueled rapid development in recent decades. AM has significantly broadened the spectrum of available materials in the manufacturing industry and is gradually replacing some traditionally manufactured parts. Similar to components produced via traditional methods, products manufactured through AM are susceptible to degradation caused by wear during their service life. Given the prevalence of 316L stainless steel (SS) parts and the limited research on the tribological behavior of 316L SS samples or products fabricated using AM technology, this study aims to investigate the degradation process and wear mechanisms of 316L SS disks fabricated using AM technology. The wear mechanisms and tribological performance of these AM-manufactured samples are compared with commercial 316L SS samples made using conventional methods. Additionally, methods to enhance the tribological performance of additive-manufactured SS samples are explored. Four disk samples with a diameter of 75 mm and a thickness of 10 mm are prepared. Two of them (Group A) are prepared from a purchased SS bar using a milling method. The other two disks (Group B), with the same dimensions, are made of Gas Atomized 316L Stainless Steel (size range: 15-45 µm) purchased from Carpenter Additive and produced using Laser Powder Bed Fusion (LPBF). Pin-on-disk tests are conducted on these disks, which have similar surface roughness and hardness levels. Multiple tests are carried out under various operating conditions, including varying loads and/or speeds, and the friction coefficients are measured during these tests. In addition, the evolution of the surface degradation processes is monitored by creating moulds of the wear tracks and quantitatively analyzing the surface morphologies of the mould images. This analysis involves quantifying the depth and width of the wear tracks and analyzing the wear debris generated during the wear processes. The wear mechanisms and wear performance of these two groups of SS samples are compared. The effects of load and speed on the friction coefficient and wear rate are investigated. The ultimate goal is to gain a better understanding of the surface degradation of additive-manufactured SS samples. This knowledge is crucial for enhancing their anti-wear performance and extending their service life.

Keywords: degradation process, additive manufacturing, stainless steel, surface features

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Authors: Smruti Mahapatra, Dipankar Biswas, Richard Um, Michael Meggyesy, Riccardo Serra, Noah Gorelick, Steven Marra, Amir Manbachi, Mark G. Luciano

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Intracranial pressure (ICP) is profoundly regulated by the effects of cardiac pulsation and the volume of the incoming blood. Furthermore, these effects on ICP are incremented by the presence of a rigid skull that does not allow for changes in total volume during the cardiac cycle. These factors play a pivotal role in cerebrospinal fluid (CSF) dynamics and distribution, with consequences that are not well understood to this date and that may have a deep effect on the Central Nervous System (CNS) functioning. We designed this study with two specific aims: (a) To study how pulsatility influences local CSF flow, and (b) To study how modulating intracranial pressure affects drug distribution throughout the SAS globally. In order to achieve these aims, we built an elaborate in-vitro model of the SAS closely mimicking the dimensions and flow rates of physiological systems. To modulate intracranial pressure, we used an intracranially implanted, cardiac-gated, volume-oscillating balloon (CADENCE device). Commercially available dye was used to visualize changes in CSF flow. We first implemented two control cases, seeing how the tracer behaves in the presence of pulsations from the brain phantom and the balloon individually. After establishing the controls, we tested 2 cases, having the brain and the balloon pulsate together in sync and out of sync. We then analyzed the distribution area using image processing software. The in-sync case produced a significant increase, 5x times, in the tracer distribution area relative to the out-of-sync case. Assuming that the tracer fluid would mimic blood flow movement, a drug introduced in the SAS with such a system in place would enhance drug distribution and increase the bioavailability of therapeutic drugs to a wider spectrum of brain tissue.

Keywords: blood-brain barrier, cardiac-gated, cerebrospinal fluid, drug delivery, neurosurgery

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Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

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Authors: Q. Giraud, J. Gonçalvès, B. Paris

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Remediation of dense non-aqueous phase liquids (DNAPLs) represents a challenging issue because of their persistent behaviour in the environment. This pilot-scale study investigates, by means of in situ experiments and numerical modelling, the feasibility of the pulsed pumping process of a large amount of a DNAPL in an alluvial aquifer. The main compound of the DNAPL is hexachlorobutadiene, an emerging organic pollutant. A low-permeability keyed enclosure was built at the location of the DNAPL source zone in order to isolate a finite undisturbed volume of soil, and a 3-month pulsed pumping process was applied inside the enclosure to exclusively extract the DNAPL. The water/DNAPL interface elevation at both the pumping and observation wells and the cumulated pumped volume of DNAPL were also recorded. A total volume of about 20m³ of purely DNAPL was recovered since no water was extracted during the process. The three-dimensional and multiphase flow simulator TMVOC was used, and a conceptual model was elaborated and generated with the pre/post-processing tool mView. Numerical model consisted of 10 layers of variable thickness and 5060 grid cells. Numerical simulations reproduce the pulsed pumping process and show an excellent match between simulated, and field data of DNAPL cumulated pumped volume and a reasonable agreement between modelled and observed data for the evolution of the water/DNAPL interface elevations at the two wells. This study offers a new perspective in remediation since DNAPL pumping system optimisation may be performed where a large amount of DNAPL is encountered.

Keywords: dense non-aqueous phase liquid (DNAPL), hexachlorobutadiene, in situ pulsed pumping, multiphase flow, numerical modelling, porous media

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Authors: V. De Sandi

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In this paper, we characterize a class of rank-weighted social welfare orderings that we call ”Excessivist.” The Excessivist Social Welfare Ordering (eSWO) judges incomes above a fixed threshold θ as detrimental to society. To accomplish this, the identification of a richness or affluence line is necessary. We employ a fixed, exogenous line of excess. We define an eSWF in the form of a weighted sum of individual’s income. This requires introducing n+1 vectors of weights, one for all possible numbers of individuals below the threshold. To do this, the paper introduces a slight modification of the class of rank weighted class of social welfare function. Indeed, in our excessivist social welfare ordering, we allow the weights to be both positive (for individuals below the line) and negative (for individuals above). Then, we introduce ethical concerns through an axiomatic approach. The following axioms are required: continuity above and below the threshold (Ca, Cb), anonymity (A), absolute aversion to excessive richness (AER), pigou dalton positive weights preserving transfer (PDwpT), sign rank preserving full comparability (SwpFC) and strong pareto below the threshold (SPb). Ca, Cb requires that small changes in two income distributions above and below θ do not lead to changes in their ordering. AER suggests that if two distributions are identical in any respect but for one individual above the threshold, who is richer in the first, then the second should be preferred by society. This means that we do not care about the waste of resources above the threshold; the priority is the reduction of excessive income. According to PDwpT, a transfer from a better-off individual to a worse-off individual despite their relative position to the threshold, without reversing their ranks, leads to an improved distribution if the number of individuals below the threshold is the same after the transfer or the number of individuals below the threshold has increased. SPb holds only for individuals below the threshold. The weakening of strong pareto and our ethics need to be justified; we support them through the notion of comparative egalitarianism and income as a source of power. SwpFC is necessary to ensure that, following a positive affine transformation, an individual does not become excessively rich in only one distribution, thereby reversing the ordering of the distributions. Given the axioms above, we can characterize the class of the eSWO, getting the following result through a proof by contradiction and exhaustion: Theorem 1. A social welfare ordering satisfies the axioms of continuity above and below the threshold, anonymity, sign rank preserving full comparability, aversion to excessive richness, Pigou Dalton positive weight preserving transfer, and strong pareto below the threshold, if and only if it is an Excessivist-social welfare ordering. A discussion about the implementation of different threshold lines reviewing the primary contributions in this field follows. What the commonly implemented social welfare functions have been overlooking is the concern for extreme richness at the top. The characterization of Excessivist Social Welfare Ordering, given the axioms above, aims to fill this gap.

Keywords: comparative egalitarianism, excess income, inequality aversion, social welfare ordering

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Authors: Yvonne A. Unrau

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Social work education is a competency-based curriculum that relies mostly on cognitive frameworks and problem-solving models. Absent from the curriculum is knowledge and skills that draw from an embodiment perspective, especially somatic practice methods. Embodiment broadly encompasses the understanding that biological, political, historical, and social factors impact human development via changes to the nervous system. In the past 20 years, research has well-established that unresolved traumatic events, especially during childhood, negatively impacts long-term health and well-being. Furthermore, traumatic stress compromises cognitive processing and activates reflexive action such as ‘fight’ or ‘flight,’ which are the focus of somatic methods. The main objective of this paper is to show how embodiment perspectives and somatic methods can enhance social work practice overall. Using an exploratory approach, the author shares a decade-long journey that involved creating an education-support program for college students who exited the state foster care system. Personal experience, program outcomes and case study narratives revealed that ‘classical’ social work methods were insufficient to fully address the complex needs of college students who were living with complex traumatic stressors. The paper chronicles select case study scenarios and key program development milestones over a 10-year period to show the benefit of incorporating embodiment perspectives in social work practice. The lessons reveal that there is an immediate need for social work curriculum to include embodiment perspectives so that social workers may be equipped to respond competently to their many clients who live with unresolved trauma.

Keywords: social work practice, social work curriculum, embodiment, traumatic stress

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Authors: Amelia Frickey, Timothy (TJ) Sheridan, Angelica Rossi, Bahar Aliakbarian

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The growth of large food supply chains demanded improved end-to-end traceability of food products, which has led to companies being increasingly interested in using smart technologies such as Radio Frequency Identification (RFID)-enabled packaging to track items. As technology is being widely used, there are several technological or economic issues that should be overcome to facilitate the adoption of this track-and-trace technology. One of the technological challenges of RFID technology is its sensitivity to different environmental form factors, including packaging materials and the content of the packaging. Although researchers have assessed the performance loss due to the proximity of water and aqueous solutions, there is still the need to further investigate the impacts of food products on the reading range of RFID tags. However, to the best of our knowledge, there are not enough studies to determine the correlation between RFID tag performance and food beverages properties. The goal of this project was to investigate the effect of the solution properties (pH and conductivity) and different packaging materials filled with food-like water-based solutions on the performance of an RFID tag. Three commercially available ultra high-frequency RFID tags were placed on three different bottles and filled with different concentrations of water-based solutions, including sodium chloride, citric acid, sucrose, and ethanol. Transparent glass, Polyethylneterephtalate (PET), and Tetrapak® were used as the packaging materials commonly used in the beverage industries. Tag readability (Theoretical Read Range, TRR) and sensitivity (Power on Tag Forward, PoF) were determined using an anechoic chamber. First, the best place to attach the tag for each packaging material was investigated using empty and water-filled bottles. Then, the bottles were filled with the food-like solutions and tested with the three different tags and the PoF and TRR at the fixed frequency of 915MHz. In parallel, the pH and conductivity of solutions were measured. The best-performing tag was then selected to test the bottles filled with wine, orange, and apple juice. Despite various solutions altering the performance of each tag, the change in tag performance had no correlation with the pH or conductivity of the solution. Additionally, packaging material played a significant role in tag performance. Each tag tested performed optimally under different conditions. This study is the first part of comprehensive research to determine the regression model for the prediction of tag performance behavior based on the packaging material and the content. More investigations, including more tags and food products, are needed to be able to develop a robust regression model. The results of this study can be used by RFID tag manufacturers to design suitable tags for specific products with similar properties.

Keywords: smart food packaging, supply chain management, food waste, radio frequency identification

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Authors: Jeffrey A. Lavarias, Jessie C. Elauria, Arnold R. Elepano, Engelbert K. Peralta, Delfin C. Suministrado

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Shelling process is one of the primary processes and critical steps in the processing of chocolate or any product that is derived from cocoa beans. It affects the quality of the cocoa nibs in terms of flavor and purity. In the Philippines, small-scale food processor cannot really compete with large scale confectionery manufacturers because of lack of available postharvest facilities that are appropriate to their level of operation. The impact of this study is to provide the needed intervention that will pave the way for cacao farmers of engaging on the advantage of value-adding as way to maximize the economic potential of cacao. Thus, provision and availability of needed postharvest machines like mechanical cacao sheller will revolutionize the current state of cacao industry in the Philippines. A mechanical cacao sheller was developed, fabricated, and evaluated to establish optimum shelling conditions such as moisture content of cocoa beans, clearance where of cocoa beans passes through the breaker section and speed of the breaking mechanism on shelling recovery, shelling efficiency, shelling rate, energy utilization and large nib recovery; To establish the optimum level of shelling parameters of the mechanical sheller. These factors were statistically analyzed using design of experiment by Box and Behnken and Response Surface Methodology (RSM). By maximizing shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization, the optimum shelling conditions were established at moisture content, clearance and breaker speed of 6.5%, 3 millimeters and 1300 rpm, respectively. The optimum values for shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization were recorded at 86.51%, 99.19%, 21.85kg/hr, 89.75%, and 542.84W, respectively. Experimental values obtained using the optimum conditions were compared with predicted values using predictive models and were found in good agreement.

Keywords: cocoa beans, optimization, RSM, shelling parameters

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Authors: Zoi Konsoula

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The increasing prevalence of Alzheimer’s disease (AD) and diabetes mellitus (DM) constitutes them major global health problems. Recently, the inhibition of key enzyme activity is considered a potential treatment of both diseases. Specifically, inhibition of acetylcholinesterase (AChE), the key enzyme involved in the breakdown of the neurotransmitter acetylcholine, is a promising approach for the treatment of AD, while inhibition of α-amylase retards the hydrolysis of carbohydrates and, thus, reduces hyperglycemia. Unfortunately, commercially available AChE and α-amylase inhibitors are reported to possess side effects. Consequently, there is a need to develop safe and effective treatments for both diseases. In the present study, pomegranate peel (PP) was extracted using various solvents of increasing polarity, while two extraction methods were employed, the conventional maceration and the ultrasound assisted extraction (UAE). The concentration of bioactive phytoconstituents, such as total phenolics (TPC) and total flavonoids (TFC) in the prepared extracts was evaluated by the Folin-Ciocalteu and the aluminum-flavonoid complex method, respectively. Furthermore, the anti-neurodegenerative and anti-hyperglycemic activity of all extracts was determined using AChE and α-amylase inhibitory activity assays, respectively. The inhibitory activity of the extracts against AChE and α-amylase was characterized by estimating their IC₅₀ value using a dose-response curve, while galanthamine and acarbose were used as positive controls, respectively. Finally, the kinetics of AChE and α-amylase in the presence of the most inhibitory potent extracts was determined by the Lineweaver-Burk plot. The methanolic extract prepared using the UAE contained the highest amount of phytoconstituents, followed by the respective ethanolic extract. All extracts inhibited acetylcholinesterase in a dose-dependent manner, while the increased anticholinesterase activity of the methanolic (IC₅₀ = 32 μg/mL) and ethanolic (IC₅₀ = 42 μg/mL) extract was positively correlated with their TPC content. Furthermore, the activity of the aforementioned extracts was comparable to galanthamine. Similar results were obtained in the case of α-amylase, however, all extracts showed lower inhibitory effect on the carbohydrate hydrolyzing enzyme than on AChE, since the IC₅₀ value ranged from 84 to 100 μg/mL. Also, the α-amylase inhibitory effect of the extracts was lower than acarbose. Finally, the methanolic and ethanolic extracts prepared by UAE inhibited both enzymes in a mixed (competitive/noncompetitive) manner since the Kₘ value of both enzymes increased in the presence of extracts, while the Vmax value decreased. The results of the present study indicate that PP may be a useful source of active compounds for the management of AD and DM. Moreover, taking into consideration that PP is an agro-industrial waste product, its valorization could not only result in economic efficiency but also reduce the environmental pollution.

Keywords: acetylcholinesterase, Alzheimer’s disease, α-amylase, diabetes mellitus, pomegranate

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Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

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Authors: Yong Chen

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To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Grazia Disciglio, Annalisa Tarantino, Emanuele Tarantino

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The production system of Foggia province (Apulia, Southern Italy) is characterized by the presence of numerous agro-food industries whose activities include the processing of vegetables products that release large quantities of wastewater. The reuse in agriculture of these wastewaters offers the opportunity to reduce the costs of their disposal and minimizing their environmental impact. In addition, in this area, which suffers from water shortage, the use of agro-industrial wastewater is essential in the very intensive irrigation cropping systems. The present investigation was carried out in years 2009 and 2010 to monitor the physico-chemical and microbiological characteristics of the industrial wastewater (IWW) from the secondary treatment plant of the 'Industrial Area of Foggia'. The treatment plant released on average about 567,000 m3y-1 of IWW, which distribution was not uniform over the year. The monthly values were about 250,000 m3 from November to June and about 90,000 m3 from July to October. The obtained results revealed that IWW was characterized by low values of Total Suspended Solids (TSS), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Electrical Conductivity (EC) and Sodium Absorption Rate (SAR). An occasional presence of heavy metal and high concentration of total phosphorus, total nitrogen, ammoniacal nitrogen and microbial organisms (Escherichia coli and Salmonella) were observed. Due to the presence of this pathogenic microorganisms and sometimes of heavy metals, which may raise sanitary and environmental problems in order to the possible irrigation reuse of this IWW, a tertiary treatment of wastewater based on filtration and disinfection in line are recommended. Researches on the reuse of treated IWW on crops (olive, artichoke, industrial tomatoes, fennel, lettuce etc.) did not show significant differences among the irrigated plots for most of the soil and yield characteristics.

Keywords: agroindustrial wastewater, irrigation, microbiological characteristic, physico-chemical characteristics

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Authors: Bina Gupta, Rashmi Singh, Harshit Mahandra

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Molybdenum is a strategic metal and finds applications in petroleum refining, thermocouples, X-ray tubes and in making of steel alloy owing to its high melting temperature and tensile strength. The growing significance and economic value of molybdenum has increased interest in the development of efficient processes aiming its recovery from secondary sources. Main secondary sources of Mo are molybdenum catalysts which are used for hydrodesulphurisation process in petrochemical refineries. The activity of these catalysts gradually decreases with time during the desulphurisation process as the catalysts get contaminated with toxic material and are dumped as waste which leads to environmental issues. In this scenario, recovery of molybdenum from spent catalyst is significant from both economic and environmental point of view. Recently ionic liquids have gained prominence due to their low vapour pressure, high thermal stability, good extraction efficiency and recycling capacity. The present study reports recovery of molybdenum from Mo-Co spent leach liquor using Cyphos IL 102[trihexyl(tetradecyl)phosphonium bromide] as an extractant. Spent catalyst was leached with 3.0 mol/L HCl, and the leach liquor containing Mo-870 ppm, Co-341 ppm, Al-508 ppm and Fe-42 ppm was subjected to extraction step. The effect of extractant concentration on the leach liquor was investigated and almost 85% extraction of Mo was achieved with 0.05 mol/L Cyphos IL 102. Results of stripping studies revealed that 2.0 mol/L HNO3 can effectively strip 94% of the extracted Mo from the loaded organic phase. McCabe- Thiele diagrams were constructed to determine the number of stages required for quantitative extraction and stripping of molybdenum and were confirmed by countercurrent simulation studies. According to McCabe- Thiele extraction and stripping isotherms, two stages are required for quantitative extraction and stripping of molybdenum at A/O= 1:1. Around 95.4% extraction of molybdenum was achieved in two-stage counter current at A/O= 1:1 with the negligible extraction of Co and Al. However, iron was coextracted and removed from the loaded organic phase by scrubbing with 0.01 mol/L HCl. Quantitative stripping (~99.5 %) of molybdenum was achieved with 2.0 mol/L HNO₃ in two stages at O/A=1:1. Overall ~95.0% molybdenum with 99 % purity was recovered from Mo-Co spent catalyst. From the strip solution, MoO₃ was obtained by crystallization followed by thermal decomposition. The product obtained after thermal decomposition was characterized by XRD, FE-SEM and EDX techniques. XRD peaks of MoO₃ correspond to molybdite Syn-MoO₃ structure. FE-SEM depicts the rod-like morphology of synthesized MoO₃. EDX analysis of MoO₃ shows 1:3 atomic percentage of molybdenum and oxygen. The synthesised MoO₃ can find application in gas sensors, electrodes of batteries, display devices, smart windows, lubricants and as a catalyst.

Keywords: cyphos Il 102, extraction, spent mo-co catalyst, recovery

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Authors: Sastry Y. Kandukuri, Isak Andersen

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Despite recent advances in the manufacturing sector, quality issues remain a frequent occurrence, and can result in fatal accidents, equipment downtime, and loss of life. Adequate quality is of high importance in high-risk industries such as sea-going vessels and offshore installations in which third party quality assurance and product control play an important essential role in ensuring manufacturing quality of critical components. Classification societies play a vital role in mitigating risk in these industries by making sure that all the stakeholders i.e. manufacturers, builders, and end users are provided with adequate rules and standards that effectively ensures components produced at a high level of quality based on the area of application and risk of its failure. Quality issues have also been linked to the lack of competence or negligence of stakeholders in supply value chain. However, continued actions and regulatory reforms through modernization of rules and requirements has provided additional tools for purchasers and manufacturers to confront these issues. Included among these tools are updated ‘approval of manufacturer class programs’ aimed at developing and implementing a set of standardized manufacturing quality metrics for use by the manufacturer and verified by the classification society. The establishment and collection of manufacturing and testing requirements described in these programs could provide various stakeholders – from industry to vessel owners – with greater insight into the state of quality at a given manufacturing facility, and allow stakeholders to anticipate better and address quality issues while simultaneously reducing unnecessary failures that are costly to the industry. The publication introduces, explains and discusses critical manufacturing and testing requirements set in a leading class society’s approval of manufacturer regime and its rationale and some case studies.

Keywords: classification society, manufacturing, materials processing, materials testing, quality control

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Authors: Marike Venter de Villiers, Jessica Ramoshaba

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In recent years, the fashion industry has been associated with the exploitation of both people and resources. This is largely due to the emergence of the fast fashion concept, which entails rapid and continual style changes where clothes quickly lose their appeal, become out-of-fashion, and are then disposed of. This cycle often entails appalling working conditions in sweatshops with low wages, child labor, and a significant amount of textile waste that ends up in landfills. Although the awareness of the negative implications of ‘mindless fashion production and consumption’ is growing, fast fashion remains to be a popular choice among the youth. This is especially prevalent in South Africa, a poverty-stricken country where a vast number of young adults are unemployed and living in poverty. Despite being in poverty, the celebrity conscious culture and fashion products frequently portrayed on the growing intrusive social media platforms in South Africa pressurizes the consumers to purchase fashion and luxury products. Young adults are therefore more vulnerable to the temptation to purchase fast fashion products. A possible solution to the detrimental effects that the fast fashion industry has on the environment is the revival of the secondhand clothing trend. Although the popularity of secondhand clothing has gained momentum among selected consumer segments, the adoption rate of such remains slow. The main purpose of this study was to explore consumers’ perceptions of the secondhand clothing trend and to gain insight into factors that inhibit the adoption of secondhand clothing. This study also aimed to investigate whether consumers are aware of the negative implications of the fast fashion industry and their likelihood to shift their clothing purchases to that of secondhand clothing. By means of a quantitative study, fifty young females were asked to complete a semi-structured questionnaire. The researcher approached females between the ages of 18 and 35 in a face-to-face setting. The results indicated that although they had an awareness of the negative consequences of fast fashion, they lacked detailed insight into the pertinent effects of fast fashion on the environment. Further, a number of factors inhibit their decision to buy from secondhand stores: firstly, the accessibility to the latest trends was not always available in secondhand stores; secondly, the convenience of shopping from a chain store outweighs the inconvenience of searching for and finding a secondhand store; and lastly, they perceived secondhand clothing to pose a hygiene risk. The findings of this study provide fashion marketers, and secondhand clothing stores, with insight into how they can incorporate the secondhand clothing trend into their strategies and marketing campaigns in an attempt to make the fashion industry more sustainable.

Keywords: eco-friendly fashion, fast fashion, secondhand clothing, eco-friendly fashion

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Authors: Amir Nourbakhsh Habibabadi, Alireza Ashori

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Context: The growing concern over the management of plastic waste and the high demand for wood-based products have led to the development of wood-plastic composites. Agricultural residues, which are abundantly available, can be used as a source of lignocellulosic fibers in the production of these composites. The use of recycled polymers and nanomaterials is also a promising approach to enhance the mechanical and physical properties of the composites. Research Aim: The aim of this study was to investigate the feasibility of using recycled high-density polyethylene (rHDPE), polypropylene (rPP), and agricultural residues fibers for manufacturing wood-plastic nano-composites. The effects of these materials on the mechanical properties of the composites, specifically tensile and flexural strength, were studied. Methodology: The study utilized an experimental approach where extruders and hot presses were used to fabricate the composites. Five types of cellulosic residues fibers (bagasse, corn stalk, rice straw, sunflower, and canola stem), three levels of nanomaterials (carbon nanotubes, nano silica, and nanoclay), and coupling agent were used to chemically bind the wood/polymer fibers, chemicals, and reinforcement. The mechanical properties of the composites were then analyzed. Findings: The study found that composites made with rHDPE provided moderately superior tensile and flexural properties compared to rPP samples. The addition of agricultural residues in several types of wood-plastic nano-composites significantly improved their bending and tensile properties, with bagasse having the most significant advantage over other lignocellulosic materials. The use of recycled polymers, agricultural residues, and nano-silica resulted in composites with the best strength properties. Theoretical Importance: The study's findings suggest that using agricultural fiber residues as reinforcement in wood/plastic nanocomposites is a viable approach to improve the mechanical properties of the composites. Additionally, the study highlights the potential of using recycled polymers in the development of value-added products without compromising the product's properties. Data Collection and Analysis Procedures: The study collected data on the mechanical properties of the composites using tensile and flexural tests. Statistical analyses were performed to determine the significant effects of the various materials used. Question addressed: Can agricultural residues and recycled polymers be used to manufacture wood-plastic nano-composites with enhanced mechanical properties? Conclusion: The study demonstrates the feasibility of using agricultural residues and recycled polymers in the production of wood-plastic nano-composites. The addition of these materials significantly improved the mechanical properties of the composites, with bagasse being the most effective agricultural residue. The study's findings suggest that composites made from recycled materials can offer value-added products without sacrificing performance.

Keywords: polymer, composites, wood, nano

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Authors: Sebastiano Candamano, Antonio Iorfida, Patrizia Frontera, Anastasia Macario, Fortunato Crea

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Alkali-activated materials are promising binders obtained by an alkaline attack on fly-ashes, metakaolin, blast slag among others. In order to guarantee the highest ecological and cost efficiency, a proper selection of precursors and alkaline activators has to be carried out. These choices deeply affect the microstructure, chemistry and performances of this class of materials. Even if, in the last years, several researches have been focused on mix designs and curing conditions, the lack of exhaustive activation models, standardized mix design and curing conditions and an insufficient investigation on shrinkage behavior, efflorescence, additives and durability prevent them from being perceived as an effective and reliable alternative to Portland. The aim of this study is to develop alkali-activated cements mortars containing high amounts of industrial by-products and waste, such as ground granulated blast furnace slag (GGBFS) and ashes obtained from the combustion process of forest biomass in thermal power plants. In particular, the experimental campaign was performed in two steps. In the first step, research was focused on elucidating how the workability, mechanical properties and shrinkage behavior of produced mortars are affected by the type and fraction of each precursor as well as by the composition of the activator solutions. In order to investigate the microstructures and reaction products, SEM and diffractometric analyses have been carried out. In the second step, their durability in harsh environments has been evaluated. Mortars obtained using only GGBFS as binder showed mechanical properties development and shrinkage behavior strictly dependent on SiO2/Na2O molar ratio of the activator solutions. Compressive strengths were in the range of 40-60 MPa after 28 days of curing at ambient temperature. Mortars obtained by partial replacement of GGBFS with metakaolin and forest biomass ash showed lower compressive strengths (≈35 MPa) and shrinkage values when higher amount of ashes were used. By varying the activator solutions and binder composition, compressive strength up to 70 MPa associated with shrinkage values of about 4200 microstrains were measured. Durability tests were conducted to assess the acid and thermal resistance of the different mortars. They all showed good resistance in a solution of 5%wt of H2SO4 also after 60 days of immersion, while they showed a decrease of mechanical properties in the range of 60-90% when exposed to thermal cycles up to 700°C.

Keywords: alkali activated cement, biomass ash, durability, shrinkage, slag

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Authors: Michelle Blewitt, Scott P. Wilson, Heidi Tait, Juniper Riordan

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Rubber crumb is a physical and chemical pollutant of concern for the environment and human health, warranting immediate investigations into its pathways to the environment and potential impacts. This emerging microplastic is created by shredding end-of-life tyres into ‘rubber crumb’ particles between 1-5mm used on synthetic turf fields and soft-fall playgrounds as a solution to intensifying tyre waste worldwide. Despite having known toxic and carcinogenic properties, studies into the transportation pathways and movement patterns of rubber crumbs from these surfaces remain in their infancy. To address this deficit, AUSMAP, the Australian Microplastic Assessment Project, in partnership with the Tangaroa Blue Foundation, conducted a study to quantify crumb loss from soft-fall surfaces. To our best knowledge, this is the first of its kind, with funding for the audits being provided by the Australian Government’s Reef Trust. Sampling occurred at 12 soft-fall playgrounds within the Great Barrier Reef Catchment Area on Australia’s North-East coast, in close proximity to the United Nations World Heritage Listed Reef. Samples were collected over a 12-month period using randomized sediment cores at 0, 2 and 4 meters away from the playground edge along a 20-meter transect. This approach facilitated two objectives pertaining to particle movement: to establish that crumb loss is occurring and that it decreases with distance from the soft-fall surface. Rubber crumb abundance was expressed as a total value and used to determine an expected average of rubber crumb loss per m2. An Analysis of Variance (ANOVA) was used to compare the differences in crumb abundance at each interval from the playground. Site characteristics, including surrounding sediment type, playground age, degree of ultra-violet exposure and amount of foot traffic, were additionally recorded for the comparison. Preliminary findings indicate that crumb is being lost at considerable rates from soft-fall playgrounds in the region, emphasizing an urgent need to further examine it as a potential source of aquatic pollution, soil contamination and threat to individuals who regularly utilize these surfaces. Additional implications for the future of rubber crumbs as a fit-for-purpose recycling initiative will be discussed with regard to industry, governments and the economic burden of surface maintenance and/ or replacement.

Keywords: microplastics, toxic rubber crumb, litter pathways, marine environment

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Authors: G. Bravo, D. Lopez, A. Iriarte

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Several organizations and governments have created a demand for information about the environmental impacts of agricultural products. Today, the export oriented fruit sector in Chile is being challenged to quantify and reduce their environmental impacts. Chile is the largest southern hemisphere producer and exporter of sweet cherry fruit. Chilean sweet cherry production reached a volume of 80,000 tons in 2012. The main destination market for the Chilean cherry in 2012 was Asia (including Hong Kong and China), taking in 69% of exported volume. Another important market was the United States with 16% participation, followed by Latin America (7%) and Europe (6%). Concerning geographical distribution, the Chilean conventional cherry production is focused in the center-south area, between the regions of Maule and O’Higgins; both regions represent 81% of the planted surface. The Life Cycle Assessment (LCA) is widely accepted as one of the major methodologies for assessing environmental impacts of products or services. The LCA identifies the material, energy, material, and waste flows of a product or service, and their impact on the environment. There are scant studies that examine the impacts of sweet cherry cultivation, such as acidification and eutrophication. Within this context, the main objective of this study is to evaluate, using the LCA, the acidification and eutrophication impacts of sweet cherry production in Chile. The additional objective is to identify the agricultural inputs that contributed significantly to the impacts of this fruit. The system under study included all the life cycle stages from the cradle to the farm gate (harvested sweet cherry). The data of sweet cherry production correspond to nationwide representative practices and are based on technical-economic studies and field information obtained in several face-to-face interviews. The study takes into account the following agricultural inputs: fertilizers, pesticides, diesel consumption for agricultural operations, machinery and electricity for irrigation. The results indicated that the mineral fertilizers are the most important contributors to the acidification and eutrophication impacts of the sheet cherry cultivation. Improvement options are suggested for the hotspot in order to reduce the environmental impacts. The results allow planning and promoting low impacts procedures across fruit companies, as well as policymakers, and other stakeholders on the subject. In this context, this study is one of the first assessments of the environmental impacts of sweet cherry production. New field data or evaluation of other life cycle stages could further improve the knowledge on the impacts of this fruit. This study may contribute to environmental information in other countries where there is similar agricultural production for sweet cherry.

Keywords: acidification, eutrophication, life cycle assessment, sweet cherry production

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Authors: Choonoh Lee, Seyeon Park, Dongyun Kang, Jaehyeong Choi, Soojee Kim, Younggeun Kim

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Market Kurly is the first South Korean online grocery retailer that guarantees same-day, overnight shipping. More than 1.6 million customers place an average of 4.7 million orders and add 3 to 14 products into a cart per month. The company has sold almost 30,000 kinds of various products in the past 6 months, including food items, cosmetics, kitchenware, toys for kids/pets, and even flowers. The company is operating and expanding multiple dry, cold, and frozen fulfillment centers in order to store and ship these products. Due to the scale and complexity of the fulfillment, pick-pack-ship processes are planned and operated in batches, and thus, the planning that decides the batch of the customers’ orders is a critical factor in overall productivity. This paper introduces a metaheuristic optimization method that reduces the complexity of batch processing in a fulfillment center. The method is an iterative genetic algorithm with heuristic creation and evolution strategies; it aims to group similar orders into pick-pack-ship batches to minimize the total number of distinct products. With a well-designed approach to create initial genes, the method produces streamlined plans, up to 13.5% less complex than the actual plans carried out in the company’s fulfillment centers in the previous months. Furthermore, our digital-twin simulations show that the optimized plans can reduce 3% of operation time for packing, which is the most complex and time-consuming task in the process. The optimization method implements a multithreading design on the Spring framework to support the company’s warehouse management systems in near real-time, finding a solution for 4,000 orders within 5 to 7 seconds on an AWS c5.2xlarge instance.

Keywords: fulfillment planning, genetic algorithm, online grocery retail, optimization

Procedia PDF Downloads 64