Search results for: artificial stock markets

Authors: Malihe Ahmadi

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Nowadays, stress, tension and neural problems are among the most important concerns of the present age. The environment plays key role on improving mental health and reducing stress of citizens. Establishing balance and appropriate relationship between city and natural environment is of the most important approaches of present century. Type of approach and logical planning for urban green spaces as one of the basic sections of integration with nature, not only plays key role on quality and efficiency of comprehensive urban planning; but also it increases the system of distributing social activities and happiness and lively property of urban environments that leads to permanent urban development. The main purpose of recovering urban identity is considering culture, history and human life style in past. This is a documentary-library research that evaluates the historical properties of Iranian gardens in compliance with climate condition. Results of this research reveal that in addition to following Iranian gardens from common principles of land lot, structure of flowers and plants, water, specific buildings during different ages, the role of climate at different urban areas is among the basics of determining method of designing green spaces and different buildings located at diverse areas i.e. Iranian gardens are a space for merging natural and artificial elements that has inseparable connection with semantic principles and guarantees different functions. Some of the necessities of designing present urban gardens are including: recognition and recreation.

Keywords: historical gardens, climate, properties of Iranian gardens, Iran

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Authors: Ahmad Alsheikh Kaddour

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Herbal medicine has been a long-standing phenomenon in Arab countries since ancient times because of its breadth and moderate temperament. Therefore, it possesses a vast natural and economic wealth of medicinal and aromatic herbs. This prompted ancient Egyptians and Arabs to discover and exploit them. The economic importance of the plant is not only from medicinal uses; it is a plant of high economic value for its various uses, especially in food, cosmetic and aromatic industries. It is also an ornamental plant and soil stabilization. The main objective of this research is to study the chemical changes that occur in the plant during the growth period, as well as the production of plant buds, which were previously considered unwanted plants. The research was carried out in the period 2021-2022 in the valley of Al-Shaflah (common caper), located in Qumhana village, 7 km north of Hama Governorate, Syria. The results of the research showed a change in the percentage of chemical components in the plant parts. The ratio of protein content and the percentage of fatty substances in fruits and the ratio of oil in the seeds until the period of harvesting of these plant parts improved, but the percentage of essential oils decreased with the progress of the plant growth, while the Glycosides content where improved with the plant aging. The production of buds is small, with dimensions as 0.5×0.5 cm, which is preferred for commercial markets, harvested every 2-3 days in quantities ranging from 0.4 to 0.5 kg in one cut/shrubs with 3 years’ age as average for the years 2021-2022. The monthly production of a shrub is between 4-5 kg per month. The productive period is 4 months approximately. This means that the seasonal production of one plant is 16-20 kg and the production of 16-20 tons per year with a plant density of 1,000 shrubs per hectare, which is the optimum rate of cultivation in the unit of mass, given the price of a kg of these buds is equivalent to 1 US $; however, this means that the annual output value of the locally produced hectare ranges from 16,000 US $ to 20,000 US $ for farmers. The results showed that it is possible to transform the cultivation of this plant from traditional random to typical areas cultivation, with a plant density of 1,000-1,100 plants per hectare according to the type of soil to obtain production of medicinal and nutritious buds, as well as, the need to pay attention to this national wealth and invest in the optimal manner, which leads to the acquisition of hard currency through export to support the national income.

Keywords: common caper, medicinal plants, propagation, medical, economic importance

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Authors: Nawal Yacoub Halim Abdelmasih

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The intersection between development and human rights has been the factor of scholarly debate for a long term. therefore, some of standards, which enlarge from the proper to development to the human rights-based totally method to development, had been adopted to apprehend the dynamics among the two standards. no matter these attempts, the exact relationship among improvement and human rights has not been completely determined but. however, the inevitable interdependence between the two notions and the idea that improvement efforts ought to be undertaken with the aid of giving due regard to human rights ensures has won momentum in recent years. then again, the emergence of sustainable development as a extensively common technique in development dreams and policies makes this unsettled convergence even extra complicated. The vicinity of sustainable improvement in human rights regulation discourse and the function of the latter in making sure the sustainability of development applications name for a scientific observe. as a result, this newsletter seeks to discover the relationship among development and human rights, particularly focusing at the location given to sustainable development principles in international human proper regulation. it'll similarly quest whether or not there is a proper to sustainable improvement diagnosed therein. as a result, the item asserts that the ideas of sustainable improvement are immediately or circuitously diagnosed in diverse human rights contraptions, which affords an affirmative response to the question raised hereinabove. This paintings, therefore, will make expeditions via international and regional human rights devices in addition to case legal guidelines and interpretative hints of human rights bodies to show this speculation.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Muhammad Umair, Yasir Nawab, Khubab Shaker, Muhammad Maqsood, Adeel Zulfiqar, Danish Mahmood Baitab

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Fabric is a flexible woven material consisting of a network of natural or artificial fibers often referred to as thread or yarn. Today fabrics are produced by weaving, braiding, knitting, tufting and non-woven. Weaving is a method of fabric production in which warp and weft yarns are interlaced perpendicular to each other. There is infinite number of ways for the interlacing of warp and weft yarn. Each way produces a different fabric structure. The yarns parallel to the machine direction are called warp yarns and the yarns perpendicular to the machine direction are called weft or filling yarns. Air jet weaving is the modern method of weft insertion and considered as high speed loom. The twist loss in air jet during weft insertion affects the strength. The aim of this study was to investigate the effect of twist change in weft yarn during air-jet weft insertion. A total number of 8 samples were produced using 1/1 plain and 3/1 twill weave design with two fabric widths having same loom settings. Two different types of yarns like cotton and PC blend were used. The effect of material type, weave design and fabric width on twist change of weft yarn was measured and discussed. Twist change in the different types of weft yarn and weave design was measured and compared the twist change in the weft yarn with the yarn before weft yarn insertion and twist loss is measured. Wider fabric leads to higher twist loss in the yarn.

Keywords: air jet loom, twist per inch, twist loss, weft yarn

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Authors: Ozgu Hafizoglu

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Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.

Keywords: analogy, analogical reasoning, cognitive model, brain and glials

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Safia Asif, Saadia Bano

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In a world with rapidly depleting resources, using artificial lighting during daytime is an act of human ignorance. Imitated light is the major source of energy consumption in public buildings. Despite, the fact that substantial working hours of these buildings usually persist in natural daylight time; there is a trend of isolated, un-fenestrated and a-contextual interiors majorly dependent on active energy sources. On the contrary, if direct and un-controlled sunlight is allowed inside the building, it will create visual and thermal discomfort. Controlled daylighting with appropriate design mechanisms is one of the important aspects of achieving thermal and visual comfort. The natural sunlight can be utilized intelligently with the help of architectural thermal controlling mechanisms to achieve a healthy and productive environment. This paper is an attempt to investigate and analyze the importance of daylighting with reference to energy efficiency and thermal comfort. For this purpose, three public buildings including two educational institutions and one general post office are selected, as case-studies in the context of Karachi, Pakistan. Various parameters of visual and thermal comfort are analyzed which includes orientation, ceiling heights, overall building profile along with daylight controlling mechanisms in terms of penetration, distribution, protection, and control. In the later part of the research, a questionnaire survey is also conducted to evaluate the user experience in terms of adequate daylighting and thermal comfort.

Keywords: daylight, public buildings, sustainable architecture, visual and thermal comfort

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Eusèbe Gnonlonfoun, Xavier Framboisier, Michel Fick, Emmanuel Rondags

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Pathogenic fungi represent a generic problem for cereals, including barley, as they can produce a number of thermostable toxic metabolites such as mycotoxins that contaminate plants and food products, leading to serious health issues for humans and animals and causing significant losses in global food production. In addition, mycotoxins represent a significant technological concern for the malting and brewing industries, as they may affect the quality and safety of raw materials (barley and malt) and final products (beer). Moreover, this situation is worsening due to the highly variable climatic conditions that favor microbial development and the societal desire to reduce the use of phytosanitary products, including fungicides. In this complex environmental, regulatory and economic context for the French barley-malt-beer industry, this project aims to develop an innovative biocontrol process by using technological bacteria, isolated from infection-resistant barley cultures, that are able to reduce the development of spoilage fungi and the associated mycotoxin production. The experimental approach consists of i) coculturing bacterial and pathogenic fungal strains in solid and liquid media to access the growth kinetics of these microorganisms and to evaluate the impact of these bacteria on fungal growth and mycotoxin production; then ii) the results will be used to carry out a micro-malting process in order to develop the aforementioned process, and iii) the technological and sanitary properties of the generated barley malts will finally be evaluated in order to validate the biocontrol process developed. The process is expected to make it possible to guarantee, with controlled costs, an irreproachable hygienic and technological quality of the malt, despite the increasingly complex and variable conditions for barley production. Thus, the results will not only make it possible to maintain the dominant world position of the French barley-malt chain but will also allow it to conquer emerging markets, mainly in Africa and Asia. The use of this process will also contribute to the reduction of the use of phytosanitary products in the field for barley production while reducing the level of contamination of malting plant effluents. Its environmental impact would therefore be significant, especially considering that barley is the fourth most-produced cereal in the world.

Keywords: barley, pathogenic fungi, mycotoxins, malting, bacterial biocontrol

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Authors: Nothando Gwazani, K. R. Marembo

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An increase in the atmospheric concentration of carbon dioxide (CO₂) from fossil fuel and land use change necessitates identification of strategies for mitigating threats associated with global warming. Oceans are insufficient to offset the accelerating rate of carbon emission. However, the challenges of oceans as a source of reducing carbon footprint can be effectively overcome by the storage of carbon in terrestrial carbon sinks. The gases with special optical properties that are responsible for climate warming include carbon dioxide (CO₂), water vapors, methane (CH₄), nitrous oxide (N₂O), nitrogen oxides (NOₓ), stratospheric ozone (O₃), carbon monoxide (CO) and chlorofluorocarbons (CFC’s). Amongst these, CO₂ plays a crucial role as it contributes to 50% of the total greenhouse effect and has been linked to climate change. Because plants act as carbon sinks, interest in terrestrial carbon sequestration has increased in an effort to explore opportunities for climate change mitigation. Removal of carbon from the atmosphere is a topical issue that addresses one important aspect of an overall strategy for carbon management namely to help mitigate the increasing emissions of CO₂. Thus, terrestrial ecosystems have gained importance for their potential to sequester carbon and reduce carbon sink in oceans, which have a substantial impact on the ocean species. Field data and electromagnetic spectrum bands were analyzed using ArcGIS 10.2, QGIS 2.8 and ERDAS IMAGINE 2015 to examine the vegetation distribution. Satellite remote sensing data coupled with Normalized Difference Vegetation Index (NDVI) was employed to assess future potential changes in vegetation distributions in Eastern Cape Province of South Africa. The observed 5-year interval analysis examines the amount of carbon absorbed using vegetation distribution. In 2015, the numerical results showed low vegetation distribution, therefore increased the acidity of the oceans and gravely affected fish species and corals. The outcomes suggest that the study area could be effectively utilized for carbon sequestration so as to mitigate ocean acidification. The vegetation changes measured through this investigation suggest an environmental shift and reduced vegetation carbon sink, and that threatens biodiversity and ecosystem. In order to sustain the amount of carbon in the terrestrial ecosystems, the identified ecological factors should be enhanced through the application of good land and forest management practices. This will increase the carbon stock of terrestrial ecosystems thereby reducing direct loss to the atmosphere.

Keywords: remote sensing, vegetation dynamics, carbon sequestration, terrestrial carbon sink

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Authors: Irfan Arikan, George Christian Steckenbauer

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Turkey and Austria are examples for highly developed tourism destinations, where tourism providers use cultural heritage and regional natural resources to develop modern tourism products in order to be successful on increasingly competitive international tourism markets. The use and exploitation of these resources follow on the one hand international standards of tourism marketing (as ‘sustainability’). Therefore, we find highly comparable internationalized products in these destinations (like hotel products, museums, spas etc.). On the other hand, development standards and processes strongly depend on local, regional and national cultures, which influence the way how people work, cooperate, think and create. Thus, cultural factors also influence the attitude towards cultural heritage and natural resources and the way, how these resources are used for the creation of tourism products. This leads to differences in the development of tourism products on several levels: 1. In the selection of cultural heritage and natural resources for the product development process 2. In the processes, how tourism products are created 3. In the way, how providers and marketing organisations work with tourism products based on cultural heritage or natural resources. Aim of this paper is to discover differences in these dimensions by analysing and comparing examples of tourism products in Turkey and Austria, both countries with a highly developed, high professional tourism industry and rich experience of stakeholders in tourism industry in the field of product development and marketing. The cases are selected from the following fields: + Cultural tourism / heritage tourism + City tourism + Industrial heritage tourism + Nature and outdoor tourism + Health tourism The cases are analysed based on available secondary data (as several cases are scientifically described) and expert interviews with local and regional stakeholders of tourism industry and tourism experts. The available primary and secondary data will be analysed and displayed in a comparative structure that allows to derive answers to the above stated research question. The result of the project therefore will be a more precise picture about the influence of cultural differences on the use and exploitation of resources in the field of tourism that allows developing recommendations for tourism industry, which must be taken into consideration to assure cultural and natural resources are treated in a sustainable and responsible way. The authors will edit these culture-cross recommendations in form of a ‘check-list’ that can be used as a ‘guideline’ for tourism professionals in the field of product development and marketing and therefore connects theoretical research to the field of practical application and closes the gap between academic research and the field of tourism practice.

Keywords: cultural heritage, natural resources, Austria, Turkey

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Authors: Filipa Lancastre, Carmen Lages, Filipe Santos

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The concept of social entrepreneurship (SE) remains ambiguous and deprived of a widely accepted operational definition. We argue that an awareness about the consensual constituent elements of SE from all key players from its ecosystem as well as a deeper understanding of apparently divergent perspectives will allow the different stakeholders (social entrepreneurs, corporations, investors, policymakers, the beneficiaries themselves) to bridge and cooperate for societal value co-creation in trying to solve our most pressing societal issues. To address our research question –what are the dimensions of SE that are consensual and controversial across existing perspectives? – We designed a two-step qualitative study. In a first step, we conducted an extensive literature review, collecting and analyzing 155 different SE definitions. From this initial step, we extracted and characterized three consensual and six controversial dimensions of the SE concept. In a second step, we conducted 20 semi-structured interviews with practitioners that are actively involved in the SE field. The goal of this second step was to verify if the literature did not capture any key dimension, understand how the dimensions related to each other and to understand the rationale behind them. The dimensions of the SE concept were extracted based on the relevance of each theme and on the theoretical relationship among them. To identify the relevance, we used as a proxy the frequency of each theme was referred to in our sample of definitions. To understand relationships, as identified in the previous section, we included concepts from both the management and psychology literature, such as the Entrepreneurial Orientation concept from the entrepreneurship literature, the Subjective Well Being construct from psychology literature, and the Resource-Based Theory from the strategy literature. This study has two main contributions; First, the identification of (consensual and controversial) dimensions of SE that exist across scattered definitions from the academic and practitioner literature. Second, a framework that parsimoniously synthesizes four dominant perspectives of SE and relates them with the SE dimensions. Assuming the contested nature of the SE concept, it is not expected that these views will be reconciled at the academic or practitioner field level. In future research, academics can, however, be aware of the existence of different understandings of SE and avoid bias towards a single view, developing holistic studies on SE phenomena or comparing differences by studying their underlying assumptions. Additionally, it is important that researchers make explicit the perspective they are embracing to ensure consistency among the research question, sampling procedures and implications of results. At the practitioner level, individuals or groups following different logics are predictably mutually suspicious and might benefit from taking stock of other perspectives on SE, building bridges and fostering cross-fertilization to the benefit of the SE ecosystem for which all contribute.

Keywords: social entrepreneurship, conceptualization, dimensions, perspectives

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Authors: Christodoulou Christos, Politis Anastasios

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The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

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Authors: Tjipta Lesmana

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Terrorist attacks quickly penetrated Indonesia following the downfall of Soeharto regime in May 1998. Reform era was officially proclaimed. Indonesia turned to 'heaven state' from 'authoritarian state'. For the first time since 1966, the country experienced a full-scale freedom of expression, including freedom of the press, and heavy acknowledgement of human rights practice. Some religious extremists previously run away to neighbor countries to escape from security apparatus secretly backed home. Quickly they consolidated the power to continue their long aspiration and dream to establish 'Shariah Indonesia', Indonesia based on Khilafah ideology. Bali bombings I which shocked world community occurred on 12 October 2002 in the famous tourist district of Kuta on the Indonesian island of Bali, killing 202 people (including 88 Australians, 38 Indonesians, and people from more than 20 other nationalities). In the capital, Jakarta, successive bombings were blasted in Marriott hotel, Australian Embassy, residence of the Philippine Ambassador and stock exchange office. A 'drunken Indonesia' is far from ready to combat nationwide sudden and massive terrorist attacks. Police Detachment 88 (Densus 88) Indonesian counter-terrorism squad, was quickly formed following 2002 Bali Bombing. Anti-terrorism Provisional Act was immediately erected, as well, due to urgent need to fight terrorism. Some Bali bombings criminals were deadly executed after sentenced by the court. But a series of terrorist suicide attacks and another Bali bombings (the second one) in Bali, again, shocked world community. Terrorism network is undoubtedly spreading nationwide. Suspicion is high that they had close connection with Al Qaeda’s groups. Even 'Afghanistan alumni' and 'Syria alumni' returned to Indonesia to back up the local mujahidins in their fights to topple Indonesia constitutional government and set up Islamic state (Khilafah). Supported by massive aids from friendly nations, especially Australia and United States, Indonesia launched large scale operations to crush terrorism consisted of various radical groups such as JAD, JAS, and JAADI. Huge energy, money, and souls were dedicated. Terrorism is, however, persistently entrenched. High ranking officials from Detachment 88 squad and military intelligence believe that terrorism is still one the most deadly enemy of Indonesia.

Keywords: counter-radicalization, de-radicalization, Khalifah, Union State, Al Qaedah, ISIS

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Authors: Marco Ferretti, Marcello Risitano, Maria Cristina Pietronudo, Lina Ozturk

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A green port is the result of a sustainable long-term strategy adopted by an entire port infrastructure, therefore by the set of actors involved in port activities. The strategy aims to realise the development of sustainable port infrastructure focused on the reduction of negative environmental impacts without jeopardising economic growth. Green technology represents the core tool to implement sustainable solutions, however, they are not a magic bullet. Ports have always been integrated in the local territory affecting the environment in which they operate, therefore, the sustainable strategy should fit with the entire local systems. Therefore, adopting a sustainable strategy means to know how to involve and engage a wide stakeholders’ network (industries, production, markets, citizens, and public authority). The existing research on the topic has not well integrated this perspective with those of sustainability. Research on green ports have mixed the sustainability aspects with those on the maritime industry, neglecting dynamics that lead to the development of the green port phenomenon. We propose an analysis of green ports adopting the lens of ecosystem studies in the field of management. The ecosystem approach provides a way to model relations that enable green solutions and green practices in a port ecosystem. However, due to the local dimension of a port and the port trend on innovation, i.e., sustainable innovation, we draw to a specific concept of ecosystem, those on local innovation systems. More precisely, we explore if a green port is a local innovation system engaged in developing sustainable innovation with a large impact on the territory or merely an innovation adopter. To address this issue, we adopt a comparative case study selecting two innovative ports in Europe: Rotterdam and Genova. The case study is a research method focused on understanding the dynamics in a specific situation and can be used to provide a description of real circumstances. Preliminary results show two different approaches in supporting sustainable innovation: one represented by Rotterdam, a pioneer in competitiveness and sustainability, and the second one represented by Genoa, an example of technology adopter. The paper intends to provide a better understanding of how sustainable innovations are developed and in which manner a network of port and local stakeholder support this process. Furthermore, it proposes a taxonomy of green ports as developers and adopters of sustainable innovation, suggesting also best practices to model relationships that enable the port ecosystem in applying a sustainable strategy.

Keywords: green port, innovation, sustainability, local innovation systems

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Wayne Tarrant, Ethan Petersen

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The concept of a flat tax goes back to at least the Biblical tithe. A progressive income tax was first vociferously espoused in a small, but famous, pamphlet in 1848 (although England had an emergency progressive tax for war costs prior to this). Within a few years many countries had adopted the progressive structure. The flat tax was only reinstated in some small countries and British protectorates until Mart Laar was elected Prime Minister of Estonia in 1992. Since Estonia’s adoption of the flat tax in 1993, many other formerly Communist countries have likewise abandoned progressive income taxes. Economists had expectations of what would happen when a flat tax was enacted, but very little work has been done on actually measuring the effect. With a testbed of 21 countries in this region that currently have a flat tax, much comparison is possible. Several countries have retained progressive taxes, giving an opportunity for contrast. There are also the cases of Czech Republic and Slovakia, which have adopted and later abandoned the flat tax. Further, with over 20 years’ worth of economic history in some flat tax countries, we can begin to do some serious longitudinal study. In this paper we consider many economic variables to determine if there are statistically significant differences from before to after the adoption of a flat tax. We consider unemployment rates, tax receipts, GDP growth, Gini coefficients, and market data where the data are available. Comparisons are made through the use of event studies and time series methods. The results are mixed, but we draw statistically significant conclusions about some effects. We also look at the different implementations of the flat tax. In some countries there are equal income and corporate tax rates. In others the income tax has a lower rate, while in others the reverse is true. Each of these sends a clear message to individuals and corporations. The policy makers surely have a desired effect in mind. We group countries with similar policies, try to determine if the intended effect actually occurred, and then report the results. This is a work in progress, and we welcome the suggestion of variables to consider. Further, some of the data from before the fall of the Iron Curtain are suspect. Since there are new ruling regimes in these countries, the methods of computing different statistical measures has changed. Although we first look at the raw data as reported, we also attempt to account for these changes. We show which data seem to be fictional and suggest ways to infer the needed statistics from other data. These results are reported beside those on the reported data. Since there is debate about taxation structure, this paper can help inform policymakers of change the flat tax has caused in other countries. The work shows some strengths and weaknesses of a flat tax structure. Moreover, it provides beginnings of a scientific analysis of the flat tax in practice rather than having discussion based solely upon theory and conjecture.

Keywords: flat tax, financial markets, GDP, unemployment rate, Gini coefficient

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Marzena Tomaszewska, Beata Bilska, Danuta Kolozyn-Krajewska

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Food loss and food waste are a global problem of the modern economy. The research undertaken aimed to analyze how food is handled in catering establishments when it comes to food waste and to demonstrate main ways of management with foods/dishes not served to consumers. A survey study was conducted from January to June 2019. The selection of catering establishments participating in the study was deliberate. The study included establishments located only in Mazowieckie Voivodeship (Poland). 42 completed questionnaires were collected. In some questions, answers were based on a 5-point scale of 1 to 5 (from 'always'/'every day' to 'never'). The survey also included closed questions with a suggested cafeteria of answers. The respondents stated that in their workplaces, dishes served cold and hot ready meals are discarded every day or almost every day (23.7% and 20.5% of answers respectively). A procedure most frequently used for dealing with dishes not served to consumers on a given day is their storage at a cool temperature until the following day. In the research, 1/5 of respondents admitted that consumers 'always' or 'usually' leave uneaten meals on their plates, and over 41% 'sometimes' do so. It was found additionally that food not used in food service sector is most often thrown into a public container for rubbish. Most often thrown into the public container (with communal trash) were: expired products (80.0%), plate waste (80.0%), and inedible products (fruit and vegetable peels, egg shells) (77.5%). Most frequently into the container dedicated only for food waste were thrown out used deep-frying oil (62.5%). 10% of respondents indicated that inedible products in their workplaces is allocate for animal feeds. Food waste in the food service sector still remains an insufficiently studied issue, as owners of these objects are often unwilling to disclose data pertaining to the subject. Incorrect ways of management with foods not served to consumers were observed. There is the need to develop the educational activities for employees and management in the context of food waste management in the food service sector. This publication has been developed under the contract with the National Center for Research and Development No Gospostrateg1/385753/1/NCBR/2018 for carrying out and funding of a project implemented as part of the 'The social and economic development of Poland in the conditions of globalizing markets - GOSPOSTRATEG' program entitled 'Developing a system for monitoring wasted food and an effective program to rationalize losses and reduce food wastage' (acronym PROM).

Keywords: food waste, inedible products, plate waste, used deep-frying oil

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Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

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A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

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Authors: Pedro Mario Gonzalez Jimenez

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The novelties introduced by the last Notice on agreements of minor importance tighten the application of the ‘De minimis’ safe harbour in the European Union. However, the undetermined legal concept of effect on trade between the Member States becomes importance at the same time. Therefore, the current analysis that the jurist should carry out in the European Union to determine if an agreement appreciably restrict competition under Article 101 of the Treaty on the Functioning of the European Union is double. Hence, it is necessary to know how to balance the significance in competition and the significance in effect on trade between the Member States. It is a crucial issue due to the negative delimitation of restriction of competition affects the positive one. The methodology of this research is rather simple. Beginning with a historical approach to the ‘De Minimis Rule’, their main problems and uncertainties will be found. So, after the analysis of normative documents and the jurisprudence of the Court of Justice of the European Union some proposals of ‘Lege ferenda’ will be offered. These proposals try to overcome the contradictions and questions that currently exist in the European Union as a consequence of the current legal regime of agreements of minor importance. The main findings of this research are the followings: Firstly, the effect on trade is another way to analyze the importance of an agreement different from the ‘De minimis rule’. In point of fact, this concept is singularly adapted to go through agreements that have as object the prevention, restriction or distortion of competition, as it is observed in the most famous European Union case-law. Thanks to the effect on trade, as long as the proper requirements are met there is no a restriction of competition under article 101 of the Treaty on the Functioning of the European Union, even if the agreement had an anti-competitive object. These requirements are an aggregate market share lower than 5% on any of the relevant markets affected by the agreement and turnover lower than 40 million of Euros. Secondly, as the Notice itself says ‘it is also intended to give guidance to the courts and competition authorities of the Member States in their application of Article 101 of the Treaty, but it has no binding force for them’. This reality makes possible the existence of different statements among the different Member States and a confusing perception of what a restriction of competition is. Ultimately, damage on trade between the Member States could be observed for this reason. The main conclusion is that the significant effect on trade between Member States is irrelevant in agreements that restrict competition because of their effects but crucial in agreements that restrict competition because of their object. Thus, the Member States should propose the incorporation of a similar concept in their legal orders in order to apply the content of the Notice. Otherwise, the significance of the restrictive agreement on competition would not be properly assessed.

Keywords: De minimis rule, effect on trade, minor importance agreements, safe harbour

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Authors: Salah Hadjout, Mohamed Zouidi

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In Algeria, several works carried out in recent years have shown the importance of fusarium head blight in durum wheat. Indeed, this disease is caused by a complex of Fusarium genus pathogens. The research carried out reports that F. culmorum is the main species infecting cereals. These informations motivated our interest in the field evaluation of the behavior of some durum wheat genotypes (parental varieties and lines) with regard to fusarium head blight, mainly caused by four F. culmorum isolates. Our research work focused on following the evolution of symptom development throughout the grain filling, after artificial inoculation of ears by Fusarium isolates in order to establish a first image on the differences in genotype behavior to fusarium haed blight. Field disease assessment criteria are: disease assessment using a grading scale, thousand grain weight measurement and AUDPC. The results obtained revealed that the varieties and lines resulting from crosses had a quite different level of sensitivity to F. culmorum species and no genotype showed complete resistance in our culture conditions. Among the material tested, some lines showed higher resistance than their parents. The results also show a slight behavioral variability also linked to the aggressiveness of the Fusarium species studied in this work. Our results open very important research perspectives on fusarium head blight, in particular the search for toxins produced by Fusarium species.

Keywords: fusarium head blight, durum wheat, Fusarium culmorum, field disease assessment criteria, Algeria

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Authors: Katarzyna Neffe-Skocinska, Marzena Tomaszewska, Beata Bilska, Dorota Zielinska, Monika Trzaskowska, Anna Lepecka, Danuta Kolozyn-Krajewska

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The aim of the study was to assess Polish consumer behavior towards food waste, including knowledge of information on food labels. The survey was carried out using the CAPI (computer assisted personal interview) method, which involves interviewing the respondent using mobile devices. The research group was a representative sample for Poland due to demographic variables: gender, age, place of residence. A total of 1.115 respondents participated in the study (51.1% were women and 48.9% were men). The questionnaire included questions on five thematic aspects: 1. General knowledge and sources of information on the phenomenon of food waste; 2. Consumption of food after the date of minimum durability; 3. The meanings of the phrase 'best before ...'; 4. Indication of the difference between the meaning of the words 'best before ...' and 'use by'; 5. Indications products marked with the phrase 'best before ...'. It was found that every second surveyed Pole met with the topic of food waste (54.8%). Among the respondents, the most popular source of information related to the research topic was television (89.4%), radio (26%) and the Internet (24%). Over a third of respondents declared that they consume food after the date of minimum durability. Only every tenth (9.8%) respondent does not pay attention to the expiry date and type of consumed products (durable and perishable products). Correctly 39.8% of respondents answered the question: How do you understand the phrase 'best before ...'? In the opinion of 42.8% of respondents, the statements 'best before ...' and 'use by' mean the same thing, while 36% of them think differently. In addition, more than one-fifth of respondents could not respond to the questions. In the case of products of the indication information 'best before ...', more than 40% of the respondents chosen perishable products, e.g., yoghurts and durable, e.g., groats. A slightly lower percentage of indications was recorded for flour (35.1%), sausage (32.8%), canned corn (31.8%), and eggs (25.0%). Based on the assessment of the behavior of Polish consumers towards the phenomenon of food waste, it can be concluded that respondents have elementary knowledge of the study subject. Noteworthy is the good conduct of most respondents in terms of compliance with shelf life and dates of minimum durability of food products. The publication was financed on the basis of an agreement with the National Center for Research and Development No. Gospostrateg 1/385753/1/NCBR/2018 for the implementation and financing of the project under the strategic research and development program social and economic development of Poland in the conditions of globalizing markets – GOSPOSTRATEG - acronym PROM.

Keywords: food waste, shelf life, dates of durability, consumer knowledge and behavior

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Authors: Boukhalfa Djemouai, Belkadi Souhila, Safsaf Boubakeur

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To increase the profitability of the national herd so that it can meet the needs of the population, Algeria has proceeded to the introduction of new reproductive biotechnologies, including artificial insemination on natural heat, by induction and heat synchronization. This biotechnology uses the male way for the creation and dissemination of genetic progress. The study has focused on 30 goat kids and bucks local breed aged between 03 and 24 months, divided into 03 groups 03-06 months[Grp 1; n=9], 07-10 months [Grp 2; n=13] and 11-24 months [Grp 3; n=8], in order to determine the influence of age on testicular evolution by measurements of testis and scrotum, and the epididymis sperm parameters evaluation. These parameters are influenced by age variations (sperm and spermocytogram). The examined parameters have focused on testicular weight (grams), the scrotal circumference (cm), mass mobility (%), vitality rate (%), sperm concentration (x 109), and percentage of abnormal spermatozoa (%). The ANOVA reveals a significance effect of age on parameters: testis weight, scrotal circumference, sperm concentration, motility varying between high (p < 0.01) to very high significance (p < 0.001), while in viability and abnormalities no significance was observed between all groups. The value of these parameters increased significantly until the age of 02 years, while that of sperm abnormalities has increased in Grp2. The histological study of testicular development shows that the genetic spermatozoa function characterized by cell proliferation, which is more and more intense starting from the age of 05 months and can be considered as an age of puberty in the local breed goat Arbia and increases with animal age.

Keywords: kids and bucks, epididymis sperm, testicular measurements, Arbia breed

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