Search results for: Green's function

Authors: Amer Elgerwi, Abdelrazzag El-Magdoub, Abubakr El-Mahmoudy

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There are many bacterial infections affecting sheep that necessitates antibiotic intervention. Amoxicillin is among commonly used antibiotics in such case for its broad spectrum of activity. However, the side alterations in blood and organ function that may be associated during or after treatment are questionable. Therefore, the aim of the present study was to assess the possible alterations in blood parameters and organ function bio markers of sheep that may occur following intramuscular injection of amoxicillin. Amoxicillin has been administered intramuscularly to 10 sheep at a dosage regimen of 7 mg/kg of body weight for 5 successive days. Two types of blood samples (with and without anticoagulant) were collected from the jugular vein pre- and post-administration of the drug. Amoxicillin significantly (P < 0.001) increased total leukocyte count and (P < 0.05) absolute eosinophilic count when compared with those of the control samples. Aspartate aminotransferase, alkaline phosphatase and cholesterol were significantly (P < 0.05) higher than the corresponding control values. In addition, amoxicillin significantly (P < 0.05) increased blood urea nitrogen and creatinine but decreased phosphorus level when compared with those of prior-administration samples. These data may indicate that although the side changes caused by amoxicillin are minor in sheep, yet the liver and kidney functions should be monitored during its usage in therapy and it should be used with care for treatment of sheep with renal and/or hepatic impairments.

Keywords: amoxicillin, biogram, haemogram, sheep

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Authors: Adepeju A. Opaleye, Adekunle Kolawole, Muyiwa A. Opaleye

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Consumers’ perceived quality of imported product has been an impediment to business in the Nigeria garment industry. To improve patronage of made- in-Nigeria designs, the first step is to understand what the consumer expects, then proffer ways to meet this expectation through product redesign or improvement of the garment production process. The purpose of this study is to investigate drivers of consumers’ value for typical Nigerian garment design (NGD). An integrated quality function deployment (QFD) and functional, expressive and aesthetic (FEA) Consumer Needs methodology helps to minimize incorrect understanding of potential consumer’s requirements in mass customized garments. Six themes emerged as drivers of consumer’s satisfaction: (1) Style variety (2) Dimensions (3) Finishing (4) Fabric quality (5) Garment Durability and (6) Aesthetics. Existing designs found to lead foreign designs in terms of its acceptance for informal events, style variety and fit. The latter may be linked to its mode of acquisition. A conceptual model of NGD acceptance in the context of consumer’s inherent characteristics, social and the business environment is proposed.

Keywords: Perceived quality, Garment design, Quality function deployment, FEA Model , Mass customisation

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Authors: Serge B. Provost

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Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

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Authors: Samain Sabrin, Joshua Pratt, Joshua Bryk, Maryam Karimi

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Globally, extreme heat events have led to a surge in the number of heat-related moralities. These incidents are further exacerbated in high-density population centers due to the Urban Heat Island (UHI) effect. Varieties of anthropogenic activities such as unsupervised land surface modifications, expansion of impervious areas, and lack of use of vegetation are all contributors to an increase in the amount of heat flux trapped by an urban canopy which intensifies the UHI effect. This project aims to propose a systematic approach to measure the impact of air quality and increased temperature based on urban morphology in the selected metropolitan cities. This project will measure the impact of build environment for urban and regional planning using human biometeorological evaluations (mean radiant temperature, Tmrt). We utilized the Rayman model (capable of calculating short and long wave radiation fluxes affecting the human body) to estimate the Tmrt in an urban environment incorporating location and height of buildings and trees as a supplemental tool in urban planning, and street design. Our current results suggest a strong correlation between building height and increased surface temperature in megacities. This model will help with; 1. Quantify the impacts of the built environment and surface properties on surrounding temperature, 2. Identify priority urban neighborhoods by analyzing Tmrt and air quality data at pedestrian level, 3. Characterizing the need for urban green infrastructure or better urban planning- maximizing the cooling benefit from existing Urban Green Infrastructure (UGI), and 4. Developing a hierarchy of streets for new UGI integration and propose new UGI based on site characteristics and cooling potential.

Keywords: air quality, heat mitigation, human-biometeorological indices, increased temperature, mean radiant temperature, radiation flux, sustainable development, thermal comfort, urban canopy, urban planning

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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Authors: Weichao Yu, Kai Wen, Weihe Huang, Yang Yang, Jing Gong

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Metal-loss corrosion is a major threat to the safety and integrity of gas pipelines as it may result in the burst failures which can cause severe consequences that may include enormous economic losses as well as the personnel casualties. Therefore, it is important to ensure the corroding pipeline integrity and efficiency, considering the value of wall thickness, which plays an important role in the failure probability of corroding pipeline. Actually, the wall thickness is controlled during pipe purchase stage. For example, the API_SPEC_5L standard regulates the allowable tolerance of the wall thickness from the specified value during the pipe purchase. The allowable wall thickness tolerance will be used to determine the wall thickness distribution characteristic such as the mean value, standard deviation and distribution. Taking the uncertainties of the input variables in the burst limit-state function into account, the reliability approach rather than the deterministic approach will be used to evaluate the failure probability. Moreover, the cost of pipe purchase will be influenced by the allowable wall thickness tolerance. More strict control of the wall thickness usually corresponds to a higher pipe purchase cost. Therefore changing the wall thickness tolerance will vary both the probability of a burst failure and the cost of the pipe. This paper describes an approach to optimize the wall thickness tolerance considering both the safety and economy of corroding pipelines. In this paper, the corrosion burst limit-state function in Annex O of CSAZ662-7 is employed to evaluate the failure probability using the Monte Carlo simulation technique. By changing the allowable wall thickness tolerance, the parameters of the wall thickness distribution in the limit-state function will be changed. Using the reliability approach, the corresponding variations in the burst failure probability will be shown. On the other hand, changing the wall thickness tolerance will lead to a change in cost in pipe purchase. Using the variation of the failure probability and pipe cost caused by changing wall thickness tolerance specification, the optimal allowable tolerance can be obtained, and used to define pipe purchase specifications.

Keywords: allowable tolerance, corroding pipeline segment, operation cost, production cost, reliability approach

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Authors: Tapas Kumar Sinha, Joseph Mathew

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At the moment earth is in grave danger due to threats of global warming. The temperature of the earth has risen by almost 20C. Glaciers in the Arctic have started to melt. It would be foolhardy to think that this is a small effect and in time it would go away. Global warming is caused by a number of factors. However, one sure and simple way to totally eliminate this problem is to put programmable shields in space. Just as an umbrella blocks sunlight, a programmable shield in space will block sun rays from reaching the earth as in a solar eclipse and cause cooling in the penumbral region just as it happens during an eclipse.

Keywords: glaciers, green house, global warming space, satellites

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Authors: R. M. Chandler, A. J. Stringer

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In adults, short bursts of high-intensity exercise (intensities between 80-95% of maximum heart rates) increase cardiovascular and metabolic function without the time investment of traditional aerobic training. Similar improvements in various health indices are also becoming increasingly evident in children in countries other than the United States. In the United States, physical education programs have become shorter in length and fewer in frequency. With this in the background, it is imperative that health and physical educators delivered well-organized and focused fitness programs that can be tolerated across many different somatotypes. Perhaps the least effective lag-time in a US physical education (PE) class is the first 10 minutes, a time during which children warm up. Replacing a traditional PE warmup with a 10 min high-intensity excise protocol is a time-efficient method to impact health, leaving as much time for other PE material such as skill development, motor behavior development as possible. This supplemented 10 min high-intensity exercise increases cardiovascular function as well as induces favorable body composition changes in as little as six weeks with further enhancement throughout a semester of activity. The supplemental high-intensity exercise did not detract from the PE lesson outcomes.

Keywords: cardiovascular fitness, high intensity interval training, high intensity exercise, pediatric

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Authors: Abdul Matin, Muhammad Ajmal, Uzma Yunus, Noaman-ul Haq, Hafiz M. Shohaib, Ambreen G. Muazzam

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Carbon nanoparticles (CNPs) have unique properties that are useful for the diagnosis and treatment of cancer due to their precise properties like small size (ideal for delivery within the body) stability in solvent and tunable surface chemistry for targeted delivery. Here, highly fluorescent, monodispersed and water-soluble CNPs were synthesized directly from a suitable carbohydrate source (glucose and sucrose) by one-step acid assisted ultrasonic treatment at 35 KHz for 4 hours. This method is green, simple, rapid and economical and can be used for large scale production and applications. The average particle sizes of CNPs are less than 10nm and they emit bright and colorful green-blue fluorescence under the irradiation of UV-light at 365nm. The CNPs were characterized by scanning electron microscopy, fluorescent spectrophotometry, Fourier transform infrared spectrophotometry, ultraviolet-visible spectrophotometry and TGA analysis. Fluorescent CNPs were used as fluorescent probe and nano-carriers for anticancer drug. Functionalized CNPs (with ethylene diamine) were attached with anticancer drug-Methotrexate. In vitro bioactivity and biocompatibility of CNPs-drug conjugates was evaluated by LDH assay and Sulforhodamine B assay using human lung carcinoma cell lines (H157). Our results reveled that CNPs showed biocompatibility and CNPs-anticancer drug conjugates have shown potent cytotoxic effects and high antitumor activities in lung cancer cell lines. CNPs are proved to be excellent substitute for conventional drug delivery cargo systems and anticancer therapeutics in vitro. Our future studies will be more focused on using the same nanoparticles in vivo model system.

Keywords: carbon nanoparticles, carbon nanoparticles-methotrexate conjugates, human lung carcinoma cell lines, lactate dehydrogenase, methotrexate

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Authors: Hatem A. El-Mezayen, Ahmed Abdelmajeed, Fatehya Metwally, Usama Elsaly, Salwa Atef

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Tumor metastasis involves the dissemination of malignant cells into the basement membrane and vascular system contributes to the circulating pool of these markers. In this context our aim has been focused on development of a non-invasive. Circulating tumor cells (CTCs) represent a unique liquid biopsy carrying comprehensive biological information of the primary tumor. Herein, we sought to develop a novel score based on the combination of the most significant CTCs biomarkers with and routine laboratory tests for accurate detection of metastatic breast cancer. Methods: Cytokeratin 18 (CK18), Cytokeratin 19 (CK19), and CA15.3 were assayed in metastatic breast cancer (MBC) patients (75), non-MBC patients (50) and healthy control (20). Results: Areas under receiving operating curve (AUCs) were calculated and used for construction on novel score. A novel score named MBC-CTCs = CA15.3 (U/L) × 0.08 + CK 18 % × 2.9 + CK19 × 3.1– 510. That function correctly classified 87% of metastatic breast cancer at cut-off value = 0.55. (i.e great than 0.55 indicates patients with metastatic breast cancer and less than 0.55 indicates patients with non-metastatic breast cancer). Conclusion: MBC-CTCs is a novel, non-invasive and simple can applied to discriminate patients with metastatic breast cancer.

Keywords: metastatic breast cancer, circulating tumor cells, cytokeratin, EpiCam

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Authors: Peng Guo

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Objective: This study investigates the clinical characteristics of sleep disorders (SD) in patients with Alzheimer's disease (AD) and their relationship with cognitive impairment. Methods: According to the inclusion and exclusion criteria of AD, 460 AD patients were consecutively included in Beijing Tiantan Hospital from January 2016 to April 2022. Demographic data, including gender, age, age of onset, course of disease, years of education and body mass index, were collected. The Pittsburgh sleep quality index (PSQI) scale was used to evaluate the overall sleep status. AD patients with PSQI ≥7 was divided into AD with SD (AD-SD) group, and those with PSQI < 7 were divided into AD with no SD (AD-nSD) group. The overall cognitive function of AD patients was evaluated by the scales of Mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA), memory was evaluated by the AVLT-immediate recall, AVLT-delayed recall and CFT-delayed memory scales, the language was evaluated by BNT scale, visuospatial ability was evaluated by CFT-imitation, executive function was evaluated by Stroop-A, Stroop-B and Stroop-C scales, attention was evaluated by TMT-A, TMT-B, and SDMT scales. The correlation between cognitive function and PSQI score in AD-SD group was analyzed. Results: Among the 460 AD patients, 173 cases (37.61%) had SD. There was no significant difference in gender, age, age of onset, course of disease, years of education and body mass index between AD-SD and AD-nSD groups (P>0.05). The factors with significant difference in PSQI scale between AD-SD and AD-nSD groups include sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleeping medication and daytime dysfunction (P<0.05). Compared with AD-nSD group, the total scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales in AD-SD group were significantly lower（P＜0.01，P＜0.01，P＜0.01，P＜0.05）. In AD-SD group, subjective sleep quality was significantly and negatively correlated with the scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales (r=-0.277，P=0.000; r=-0.216，P=0.004; r=-0.253，P=0.001; r=-0.239, P=0.004), daytime dysfunction was significantly and negatively correlated with the score of AVLT-immediate recall scale (r=-0.160，P=0.043). Conclusion The incidence of AD-SD is 37.61%. AD-SD patients have worse subjective sleep quality, longer time to fall asleep, shorter sleep time, lower sleep efficiency, severer nighttime SD, more use of sleep medicine, and severer daytime dysfunction. The overall cognitive function, immediate recall and visuospatial ability of AD-SD patients are significantly impaired and are closely correlated with the decline of subjective sleep quality. The impairment of immediate recall is highly correlated with daytime dysfunction in AD-SD patients.

Keywords: Alzheimer's disease, sleep disorders, cognitive impairment, correlation

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: K. K. Soundra Pandian, Bhupendra Gupta

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In the modern era, as the application data’s are massive and complex, it needs to be secured from the adversary attack. In this context, a non-recursive key based integrated spritz stream cipher with the circulant hash function using delayed feedback with carry shift register (d-FCSR) is proposed in this paper. The novelty of this proposed stream cipher algorithm is to engender the improved keystream using d-FCSR. The proposed algorithm is coded using Verilog HDL to produce dynamic binary key stream and implemented on commercially available FPGA device Virtex 5 xc5vlx110t-2ff1136. The implementation of stream cipher using d-FCSR on the FPGA device operates at a maximum frequency of 60.62 MHz. It achieved the data throughput of 492 Mbps and improved in terms of efficiency (throughput/area) compared to existing techniques. This paper also briefs the cryptanalysis of proposed circulant hash value based spritz stream cipher using d-FCSR is against the adversary attack on a hardware platform for the hardware based cryptography applications.

Keywords: cryptography, circulant function, field programmable gated array, hash value, spritz stream cipher

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Authors: M. Soubadra Devy, Savitha Swamy, Chethana V. Casiker

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Sustainable smart cities are emerging as an important concept in response to the exponential rise in the world’s urbanizing population. While earlier, only technical, economic and governance based solutions were considered, more and more layers are being added in recent times. With the prefix of 'sustainability', solutions which help in judicious use of resources without negatively impacting the environment have become critical. We present a case study of Bangalore city which has transformed from being a garden city and pensioners' paradise to being an IT city with a huge, young population from different regions and diverse cultural backgrounds. This has had a big impact on the green spaces in the city and the biodiversity that they support, as well as on farming/gardening practices. Edible landscapes comprising farms lands, home gardens and neighbourhood parks (NPs henceforth) were examined. The land prices of areas having NPs were higher than those that did not indicate an appreciation of their aesthetic value. NPs were part of old and new residential areas largely managed by the municipality. They comprised manicured gardens which were similar in vegetation structure and composition. Results showed that NPs that occurred in higher density supported reasonable levels of biodiversity. In situations where NPs occurred in lower density, the presence of a larger green space such as a heritage park or botanical garden enhanced the biodiversity of these parks. In contrast, farm lands and home gardens which were common within the city are being lost at an unprecedented scale to developmental projects. However, there is also the emergence of a 'neo-culture' of home-gardening that promotes 'locovory' or consumption of locally grown food as a means to a sustainable living and reduced carbon footprint. This movement overcomes the space constraint by using vertical and terrace gardening techniques. Food that is grown within cities comprises of vegetables and fruits which are largely pollinator dependent. This goes hand in hand with our landscape-level study that has shown that cities support pollinator diversity. Maintaining and improving these man-made ecosystems requires analysing the functioning and characteristics of the existing structures of governance. Social network analysis tool was applied to NPs to examine relationships, between actors and ties. The management structures around NPs, gaps, and means to strengthen the networks from the current state to a near-ideal state were identified for enhanced services. Learnings from NPs were used to build a hypothetical governance structure and functioning of integrated governance of NPs and edible landscapes to enhance ecosystem services such as biodiversity support, food production, and aesthetic value. They also contribute to the sustainability axis of smart cities.

Keywords: biodiversity support, ecosystem services, edible green spaces, neighbourhood parks, sustainable smart city

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Authors: Namrata Khatri

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The rapid growth of cities is transforming the urban environment and posing significant challenges for environmental quality. This study examines the urban environment of Belagavi in Karnataka, India, using geostatistical methods to assess the spatial pattern and land use distribution of the city and to evaluate the quality of the urban environment. The study is driven by the necessity to assess the environmental impact of urbanisation. Satellite data was utilised to derive information on land use and land cover. The investigation revealed that land use had changed significantly over time, with a drop in plant cover and an increase in built-up areas. High-resolution satellite data was also utilised to map the city's open areas and gardens. GIS-based research was used to assess public green space accessibility and to identify regions with inadequate waste management practises. The findings revealed that garbage collection and disposal techniques in specific areas of the city needed to be improved. Moreover, the study evaluated the city's thermal environment using Landsat 8 land surface temperature (LST) data. The investigation found that built-up regions had higher LST values than green areas, pointing to the city's urban heat island (UHI) impact. The study's conclusions have far-reaching ramifications for urban planners and politicians in Belgaum and other similar cities. The findings may be utilised to create sustainable urban planning strategies that address the environmental effect of urbanisation while also improving the quality of life for city dwellers. Satellite data and high-resolution satellite pictures were gathered for the study, and remote sensing and GIS tools were utilised to process and analyse the data. Ground truthing surveys were also carried out to confirm the accuracy of the remote sensing and GIS-based data. Overall, this study provides a complete assessment of Belgaum's environmental quality and emphasizes the potential of remote sensing and geographic information systems (GIS) approaches in environmental assessment and management.

Keywords: environmental quality, UEQ, remote sensing, GIS

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Authors: Gideon Nyuimbe Gasu

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Sub Saharan Africa is at a critical point, experiencing rapid population growth, particularly in urban areas and young growing force. At the same time, the growing risk of catastrophic global climate change threatens to weaken food production system, increase intensity and frequency of drought, flood, and fires and undermine gains on development and poverty reduction. Although the region has the lowest per capital greenhouse gas emission level in the world, it will need to join global efforts to address climate change, including action to avoid significant increases and to encourage a green economy. Thus, there is a need for the concept of 'greening the economy' as was prescribed at Rio Summit of 1992. Renewable energy is one of the criterions to achieve this laudable goal of maintaining a green economy. There is need to address climate change while facilitating continued economic growth and social progress as energy today is critical to economic growth. Fossil fuels remain the major contributor of greenhouse gas emission. Thus, cleaner technologies such as carbon capture storage, renewable energy have emerged to be commercially competitive. This paper sets out to examine how to achieve a low carbon economy with minimal emission of carbon dioxide and other greenhouse gases which is one of the outcomes of implementing a green economy. Also, the paper examines the different renewable energy sources such as nuclear, wind, hydro, biofuel, and solar voltaic as a panacea to the looming climate change menace. Finally, the paper assesses the different renewable energy and energy efficiency as a propeller to generating new sources of income and jobs and in turn reduces carbon emission. The research shall engage qualitative, evaluative and comparative methods. The research will employ both primary and secondary sources of information. The primary sources of information shall be drawn from the sub Saharan African region and the global environmental organizations, energy legislation, policies and related industries and the judicial processes. The secondary sources will be made up of some books, journal articles, commentaries, discussions, observations, explanations, expositions, suggestions, prescriptions and other material sourced from the internet on renewable energy as a panacea to climate change. All information obtained from these sources will be subject to content analysis. The research result will show that the entire planet is warming as a result of the activities of mankind which is clear evidence that the current development is fundamentally unsustainable. Equally, the study will reveal that a low carbon development pathway in the sub Saharan African region should be embraced to minimize emission of greenhouse gases such as using renewable energy rather than coal, oil, and gas. The study concludes that until adequate strategies are devised towards the use of renewable energy the region will continue to add and worsen the current climate change menace and other adverse environmental conditions.

Keywords: carbon dioxide, climate change, legislation/law, renewable energy

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Authors: M. Osman Gani, M. Ferdows, Toshiyuki Ogawa

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In this work, we proposed a modified FHN-type reaction-diffusion system for a bistable excitable system by adding a scaled function obtained from a given function. We study the existence and the stability of the periodic traveling waves (or wavetrains) for the FitzHugh-Nagumo (FHN) system and the modified one and compare the results. The stability results of the periodic traveling waves (PTWs) indicate that most of the solutions in the fast family of the PTWs are stable for the FitzHugh-Nagumo equations. The instability occurs only in the waves having smaller periods. However, the smaller period waves are always unstable. The fast family with sufficiently large periods is always stable in FHN model. We find that the oscillation of pulse widths is absent in the standard FHN model. That motivates us to study the PTWs in the proposed FHN-type reaction-diffusion system for the bistable excitable media. A good agreement is found between the solutions of the traveling wave ODEs and the corresponding whole PDE simulation.

Keywords: bistable system, Eckhaus bifurcation, excitable media, FitzHugh-Nagumo model, periodic traveling waves

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Authors: Asma AlQahtani, Jumana AlHadad, Maryam AlQallaf, Shoug AlHasan

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New product development (NPD) is the complete process of bringing a new product to the customer by integrating the two broad divisions; one involving the idea generation, product design and detail engineering; and the other involving market research and marketing analysis. It is a common practice for companies to undertake some of these tasks simultaneously (concurrent engineering) and also consider them as an ongoing process (continuous development). The current study explores the framework and methodology for a new product development process utilizing the Quality Function Deployment (QFD) tool for bringing the customer opinion into the product development process. An elaborate customer survey with focus groups in the region was carried out to ensure that customer requirements are integrated into new products as early as the design stage including identifying the recognition of need for the new product. A QFD Matrix (House of Quality) was prepared that links customer requirements to product engineering requirements and a feasibility study and risk assessment exercise was carried out for a Small and Medium Enterprise (SME) in Kuwait for development of the new product. SMEs in Kuwait, particularly in manufacturing sector are mainly focused on serving the local demand, and often lack of product quality adversely affects the ability of the companies to compete on a regional/global basis. Further, lack of focus on identifying customer requirements often deters SMEs to envisage the idea of a New Product Development. The current study therefore focuses in utilizing QFD Matrix right from the conceptual design to detail design and to some extent, extending the link this to design of the manufacturing system. The outcome of the project resulted in a development of the prototype for a new molded product which can ensure consistency between the customer’s requirements and the measurable characteristics of the product. The Engineering Economics and Cost studies were also undertaken to analyse the viability of the new product, the results of which was also linked to the successful implementation of the initial QFD Matrix.

Keywords: Quality Function Deployment, QFD Matrix, new product development, NPD, Kuwait SMEs, prototype development

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Authors: Bambang Wispriyono, Satria Pratama, Haryoto Kusnoputranto, Faisal Yunus, Meliana Sari

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Introduction/objective: The impact of the development of motor vehicles is increasing the number of pollutants in the air. One of the substances that cause serious health problems is NO2. The health impacts arising from exposure to NO2 include pulmonary function impairment. The purpose of this study was to determine the relationship of NO2 exposure on the incidence of pulmonary function impairment. Methods: We are using a cross-sectional study design with 110 traffic police who were divided into two groups: exposed (police officers working on the highway) and the unexposed group (police officers working in the office). Election subject convenient sampling carried out in each group to the minimum number of samples met. Results: The results showed that the average NO2 in the exposed group was 18.72 ppb and unexposed group is 4.14 ppb. Pulmonary dysfunction on exposed and unexposed groups showed that FVC (Forced Vital Capacity) value are 88.68 and 90.27. And FEV1 (Forced Expiratory Volume in One) value are 94.9 and 95.16. Some variables like waist circumference, Body Mass Index, Visceral Fat, and Fat has associated with the incidence of Pulmonary Dysfunction (p < 0.05). Conclusion: Health monitoring is needed to decreasing health risk in Policeman.

Keywords: NO2, pulmonary dysfunction, police traffic, Jakarta

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Authors: Seyed Mohsen Mousavi, Ali Reza Mahjoub, Bahjat Afshari Razani

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In this work, Fe/ZnO hollow spherical structures with high surface area using the template glucose was prepared by the hydrothermal method using an ultrasonic bath at room temperature was produced and were identified by FT-IR, XRD, FE-SEM and BET. The photocatalytic activity of synthesized spherical Fe/ZnO hollow sphere were studied in the destruction of Congo Red and Methylene Blue as Azo dyes. The results showed that the photocatalytic activity of Fe/ZnO hollow spherical structures is improved compared with ZnO hollow sphere and other morphologys.

Keywords: azo dyes, Fe/ZnO hollow sphere, hollow sphere nanostructures, photocatalyst

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Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

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Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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Authors: Joanne DiFrancisco-Donoghue, Seth E. Jenny, Peter C. Douris, Sophia Ahmad, Kyle Yuen, Hillary Gan, Kenney Abraham, Amber Sousa

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Background: Guidelines for the maintenance of health of esports players and the cognitive changes that accompany competitive gaming are understudied. Executive functioning is an important cognitive skill for an esports player. The relationship between executive functions and physical exercise has been well established. However, the effects of prolonged sitting regardless of physical activity level have not been established. Prolonged uninterrupted sitting reduces cerebral blood flow. Reduced cerebral blood flow is associated with lower cognitive function and fatigue. This decrease in cerebral blood flow has been shown to be offset by frequent and short walking breaks. These short breaks can be as little as 2 minutes at the 30-minute mark and 6 minutes following 60 minutes of prolonged sitting. The rationale is the increase in blood flow and the positive effects this has on metabolic responses. The primary purpose of this study was to evaluate executive function changes following 6-minute bouts of walking and complete rest mid-session, compared to no break, during prolonged gameplay in competitive first-person shooter (FPS) esports players. Methods: This study was conducted virtually due to the Covid-19 pandemic and was approved by the New York Institute of Technology IRB. Twelve competitive FPS participants signed written consent to participate in this randomized pilot study. All participants held a gold ranking or higher. Participants were asked to play for 2 hours on three separate days. Outcome measures to test executive function included the Color Stroop and the Tower of London tests which were administered online each day prior to gaming and at the completion of gaming. All participants completed the tests prior to testing for familiarization. One day of testing consisted of a 6-minute walk break after 60-75 minutes of play. The Rate of Perceived Exertion (RPE) was recorded. The participant continued to play for another 60-75 minutes and completed the tests again. Another day the participants repeated the same methods replacing the 6-minute walk with lying down and resting for 6 minutes. On the last day, the participant played continuously with no break for 2 hours and repeated the outcome tests pre and post-play. A Latin square was used to randomize the treatment order. Results: Using descriptive statistics, the largest change in mean reaction time incorrect congruent pre to post play was seen following the 6-minute walk (662.0 (609.6) ms pre to 602.8 (539.2) ms post), followed by the 6-minute rest group (681.7(618.1) ms pre to 666.3 (607.9) ms post), and with minimal change in the continuous group (594.0(534.1) ms pre to 589.6(552.9) ms post). The mean solution time was fastest in the resting condition (7774.6(6302.8)ms), followed by the walk condition (7929.4 (5992.8)ms), with the continuous condition being slowest (9337.3(7228.7)ms). the continuous group 9337.3(7228.7) ms; 7929.4 (5992.8 ) ms 774.6(6302.8) ms. Conclusion: Short walking breaks improve blood flow and reduce the risk of venous thromboembolism during prolonged sitting. This pilot study demonstrated that a low intensity 6 -minute walk break, following 60 minutes of play, may also improve executive function in FPS gamers.

Keywords: executive function, FPS, physical activity, prolonged sitting

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Authors: Sunantha Teyarachakul

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We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems.

Keywords: inventory management, Newsvendor model, order policy, worker learning

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Authors: Jang-Hwan Yin, Hae-Jeong Jeong, Hyo-Geun Jeong

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K-water (Korea Water Resources Corporation) conducted basic and working design about floating PV generation system installed above water in the upstream of dam to develop clean energy using water with importance of green growth is magnified ecumenically. PV Generation System on the ground applied considerably until now raise environmental damage by using farmland and forest land, PV generation system on the building roof is already installed at almost the whole place of business and additional installation is almost impossible. Installation space of PV generation system is infinite and efficient national land use is possible because it is installed above water. Also, PV module's efficiency increase by natural water cooling method and no shade. So it is identified that annual power generation is more than PV generation system on the ground by operating performance data. Although it is difficult to design and construct by high cost, little application case, difficult installation of floater, mooring device, underwater cable, etc. However, it has been examined cost reduction plan such as structure weight lightening, floater optimal design, etc. This thesis described basic and working design result systematically about K-water's floating PV generation system development and suggested optimal design method of floating PV generation system. Main contents are photovoltaic array location select, substation location select related underwater cable, PV module and inverter design, transmission and substation equipment design, floater design related structure weight lightening, mooring system design related water level fluctuation, grid connecting technical review, remote control and monitor equipment design, etc. This thesis will contribute to optimal design and business extension of floating PV generation system, and it will be opportunity revitalize clean energy development using water.

Keywords: PV generation system, clean energy, green growth, solar energy

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Authors: Angga S. Fajar, Y. Takahashi, J. Kiyono, S. Sawada

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The structural system concept of RC pier accompanied with multi sliding friction damping mechanism was developed based on numerical analysis approach. However in the implementation, to make design for such kind of this structural system consumes a lot of effort in case high of complexity. During making design, the special behaviors of this structural system should be considered including flexible small deformation, sufficient elastic deformation capacity, sufficient lateral force resistance, and sufficient energy dissipation. The confinement distribution of friction devices has significant influence to its. Optimization and prediction with multi function regression of this structural system expected capable of providing easier and simpler design method. The confinement distribution of friction devices is optimized with SNOPT in Opensees, while some design variables of the structure are predicted using multi function regression of ANN. Based on the optimization and prediction this structural system is able to be designed easily and simply.

Keywords: RC Pier, multi sliding friction device, optimal design, flexible small deformation

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Authors: Aysun Pınarbaşı, Béla Vizvári

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The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy, and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country. We provide an inventory policy for the pandemic period for the countries. This paper presents a deterministic model for vaccines with a demand rate variable over time for the countries. It is aimed to provide an analytical model to deal with the minimization of holding cost and develop inventory policies regarding this aim to be used for a variety of perishable products such as vaccines. The saturation process is introduced, and an approximation of the vaccination curve of the countries has been discussed. According to this aspect, a deterministic model for inventory policy has been developed.

Keywords: covid-19, vaccination, inventory policy, bounded total demand, inventory holding cost, cauchy distribution, sigmoid function

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Authors: Christina Drosou, Konstantina E. Kyriakopoulou, Andreas Bimpilas, Dimitrios Tsimogiannis, Magdalini C. Krokida

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Rationale: Agiorgitiko is one of the most widely-grown and commercially well-established red wine varieties in Greece. Each year viticulture industry produces a large amount of waste consisting of grape skins and seeds (pomace) during a short period. Grapes contain polyphenolic compounds which are partially transferred to wine during winemaking. Therefore, winery wastes could be an alternative cheap source for obtaining such compounds with important antioxidant activity. Specifically, red grape waste contains anthocyanins and flavonols which are characterized by multiple biological activities, including cardioprotective, anti-inflammatory, anti-carcinogenic, antiviral and antibacterial properties attributed mainly to their antioxidant activity. Ultrasound assisted extraction (UAE) is considered an effective way to recover phenolic compounds, since it combines the advantage of mechanical effect with low temperature. Moreover, green solvents can be used in order to recover extracts intended for used in the food and nutraceutical industry. Apart from the extraction, pre-treatment process like drying can play an important role on the preservation of the grape pomace and the enhancement of its antioxidant capacity. Objective: The aim of this study is to recover natural extracts from winery waste with high antioxidant capacity using green solvents so they can be exploited and utilized as enhancers in food or nutraceuticals. Methods: Agiorgitiko grape pomace was dehydrated by air drying (AD) and accelerated solar drying (ASD) in order to explore the effect of the pre-treatment on the recovery of bioactive compounds. UAE was applied in untreated and dried samples using water and water: ethanol (1:1) as solvents. The total antioxidant potential and phenolic content of the extracts was determined using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin-Ciocalteu method, respectively. Finally, the profile of anthocyanins and flavonols was specified using HPLC-DAD analysis. The efficiency of processes was determined in terms of extraction yield, antioxidant activity, phenolic content and the anthocyanins and flavovols profile. Results & Discussion: The experiments indicated that the pre-treatment was essential for the recovery of highly nutritious compounds from the pomace as long as the extracts samples showed higher phenolic content and antioxidant capacity. Water: ethanol (1:1) was considered a more effective solvent on the recovery of phenolic compounds. Moreover, ASD grape pomace extracted with the solvent system exhibited the highest antioxidant activity (IC50=0.36±0.01mg/mL) and phenolic content (TPC=172.68±0.01mgGAE/g dry extract), followed by AD and untreated pomace. The major compounds recovered were malvidin3-O-glucoside and quercetin3-O-glucoside according to the HPLC analysis. Conclusions: Winery waste can be exploited for the recovery of nutritious compounds using green solvents such as water or ethanol. The pretreatment of the pomace can significantly affect the concentration of phenolic compounds, while UAE is considered a highly effective extraction process.

Keywords: agiorgitico grape pomace, antioxidants, phenolic compounds, ultrasound assisted extraction

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Authors: Nicolae Pascu

Abstract:

Aside from being a fundamental tool in Complex analysis, Schwarz Lemma-which was finalized in its most complete form at the beginning of the last century-generated an important area of research in various fields of mathematics, which continues to advance even today. We present some properties of analytic functions in the half-plane which satisfy the conditions of the classical Schwarz Lemma (Carathéodory functions) and obtain a generalization of the well-known Aleksandrov-Sobolev Lemma for analytic functions in the half-plane (the correspondent of Schwarz-Pick Lemma from the unit disk). Using this Schwarz-type lemma, we obtain a characterization for the entire class of Carathéodory functions, which might be of independent interest. We prove two monotonicity properties for Carathéodory functions that do not depend upon their normalization at infinity (the hydrodynamic normalization). The method is based on conformal mapping arguments for analytic functions in the half-plane satisfying appropriate conditions, in the spirit of Schwarz lemma. According to the research findings in this paper, our main results give estimates for the modulus and the argument for the entire class of Carathéodory functions. As applications, we give several extensions of Julia-Wolf-Carathéodory Lemma in a half-strip and show that our results are sharp.

Keywords: schwarz lemma, Julia-wolf-caratéodory lemma, analytic function, normalization condition, caratéodory function

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Authors: Gu Sihao

Abstract:

The coordinated development of "ecology-production-life" in cities has been highly concerned by the country, and the transformation development and sustainable development of resource-based cities have become a hot research topic at present. As an important part of China's resource-based cities, coal resource-based cities have the characteristics of large number and wide distribution. However, due to the adjustment of national energy structure and the gradual exhaustion of urban coal resources, the development vitality of coal resource-based cities is gradually reduced. In many studies, the deterioration of ecological environment in coal resource-based cities has become the main problem restricting their urban transformation and sustainable development due to the "emphasis on economy and neglect of ecology". Since the 18th National Congress of the Communist Party of China (CPC), the Central Government has been deepening territorial space planning and development. On the premise of optimizing territorial space development pattern, it has completed the demarcation of ecological protection red lines, carried out ecological zoning and ecosystem evaluation, which have become an important basis and scientific guarantee for ecological modernization and ecological civilization construction. Grasp the regional multiple ecosystem services is the precondition of the ecosystem management, and the relationship between the multiple ecosystem services study, ecosystem services cluster can identify the interactions between multiple ecosystem services, and on the basis of the characteristics of the clusters on regional ecological function zoning, to better Social-Ecological system management. Based on this cognition, this study optimizes the spatial function zoning of Gujiao, a coal resource-based city, in order to provide a new theoretical basis for its sustainable development. This study is based on the detailed analysis of characteristics and utilization of Gujiao city land space, using SOFM neural networks to identify local ecosystem service clusters, according to the cluster scope and function of ecological function zoning of space partition balance and coordination between different ecosystem services strength, establish a relationship between clusters and land use, and adjust the functions of territorial space within each zone. Then, according to the characteristics of coal resources city and national spatial function zoning characteristics, as the driving factors of land change, by cellular automata simulation program, such as simulation under different restoration strategy situation of urban future development trend, and provides relevant theories and technical methods for the "third-line" demarcations of Gujiao's territorial space planning, optimizes territorial space functions, and puts forward targeted strategies for the promotion of regional ecosystem services, providing theoretical support for the improvement of human well-being and sustainable development of resource-based cities.

Keywords: coal resource-based city, territorial spatial planning, ecosystem service cluster, gmop model, geosos-FLUS model, functional zoning optimization and upgrading

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