Search results for: drivers of deforestation

Authors: Fawad Hussain, Saleh Abdullah Saleh, Mohammad Basir B Saud, Mohd Azwardi Md. Isa

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It is very important for a developing nation to develop their infrastursture on the prime priority because their infrastursture particularly their roads and transporation functions as a blood in the system. Almost 1.1 billion populations share the travel and transportation industry in India. On the other hand, the Pakistan transportation industry is also extensive and elevating about 170 million users of transportation. Indian and Pakistani specifically within bus industry have good interconnectivity within and between the urban and rural areas as well as connectivity between the two countries, which is dramatically helping the economic alleviation of both countries. Due to high economic instability, unemployment and poverty rate are among the reasons why both the governments are very committed and seriously taken further action to help boost their economy. They believe that any form of transportation development would play a vital role in the development of land, infrastructure which could indirectly support many other industries’ development, such as tourism, freighting and shipping businesses, just to mention a few. However, it seems that their previous transportation planning in the due course has failed to meet the fast growing demand. As with the spin of time, both the countries are looking forward for a reasonable, safe and economical long term solutions, which is from time to time keep appreciating and reacting according to other key economic drivers. Content analysis method and case study approach is used in this paper and secondary data from the bureau of statistic is used for case analysis. The paper centered on the mobility concerns of the lower and middle income people in India and Pakistan. The paper is aimed to highlight the weaknesses, opportunities and limitations resulting from low priority industry for government, which is making the either country's public suffer. The paper has concluded that the main issue is identified as the slow, inappropriate and unfavorable decisions which are not in favor of long term country’s economic development and public welfare as well as interest. The paper also recommends to future market sense public and private transportation, which has failed to meet the public expectations.

Keywords: bus transportation industries, transportation demand, government parallel initiatives, road and traffic congestions

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Authors: Akanksha Gupta, Vishal Dubey

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In the Neoliberal era, there has been a much-talked discourse about urban issues that arise from a narrow approach of the single rationality of market-driven planning in Indian cities. More to this, India's urban planning is already jeopardized by the captious shortage of infrastructure, a cluster of incoherent governing bodies and implementation mechanism, leading cities to lie in the plethora of urban challenges. In this context, Allahabad (now known as Prayagraj) a city in North India is not an exception. Once known as the most planned splendid Colonial city of the British regime in India collapsed phenomenally because of the incompetent approach of planning machinery, straightforward market-driven accession and lack of attention on urban equity and sustainability. Particularly Civil Lines a Colonial neighbourhood, reached to the zenith of the glorified legacy of the Colonial era, transformed into filthy and congested urban form. Contextually this study contemplates and assesses the chronological episodes of major changes in land management reforms and policies under the ad hoc approach of political economy and land use planning which radically degraded the living environment in the present context. This study would empirically showcase the selected sample area detailing some of the major consequences in terms of gradual change in urban morphology, land use, and function. Here the method of study is primarily a qualitative study implying oral history and other historical methods to exhibit the idiom of planning conundrum. This subsequently reflects the repercussions translated into major issues like unclear land titles, encroachment, and unauthorized development and mushrooming of informal and squatter settlements. In nutshell, the study seeks to distinct out the limitations of the land reform and land management policies, which impacted the general degradation to the beautiful setting of Colonial neighbourhood. The Colonial legacy of Civil Lines now exists in the traces of history- memories of people, who once took pride in its serenity have now witnessed the transformation bit by bit till neo-liberal market forces completely swallow it.

Keywords: civil lines, land reforms, policies, urban challenges

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Authors: S. Vaibhav Kant Sahu, Surabhi Bipin Seth

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Human well-being has multiple constituents including the basic material for a good life, freedom and choice, health, good social relations, and security. Poverty is also multidimensional and has been defined as the pronounced deprivation of well-being. Dhurwa tribe of Bastar (India) have symbiotic relation with nature, it provisions ecosystem service such as food, fuel and fiber; regulating services such as climate regulation and non-material benefits such as spiritual or aesthetic benefits and they are managing their forest from ages. The demand for ecosystem services is now so great that trade-off among services become rule. Aim of study to explore evidences for linkages between ecosystem services and well-being of indigenous community, how much it helps them in poverty reduction and interaction between them. Objective of study was to find drivers of change and evidence concerning link between ecosystem, human development and sustainability, evidence in decision making does it opt for multi sectoral objectives. Which means human well-being as the central focus for assessment, while recognizing that biodiversity and ecosystems also have intrinsic value. Ecosystem changes that may have little impact on human well-being over days or weeks may have pronounced impacts over years or decades; so assessments needed to be conducted at spatial and temporal scales under social, political, economic scales to have high-resolution data. Researcher used framework developed by Millennium ecosystem assessment; since human action now directly or unknowingly virtually alter ecosystem. Researcher used ethnography study to get primary qualitative data, secondary data collected from panchayat office. The responses were transcribed and translated into English, as interview held in Hindi and local indigenous language. Focus group discussion were held with group of 10 women at Tiriya village. Researcher concluded with well-being is not just gap between ecosystem service supply but also increases vulnerability. Decision can have consequences external to the decision framework these consequences are called externalities because they are not part of the decision-making calculus.

Keywords: Bastar, Dhurwa tribe, ecosystem services, millennium ecosystem assessment, sustainability

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Authors: Ahmad Haidar

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This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

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Authors: Kishor Prasad Bhatta, Suman Ghimire, Durga Prasad Joshi

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Invasive Alien Species (IAS) are considered waste forest resources in Nepal. The rapid expansion of IAS is one of the nine main drivers of forest degradation, though the extent and distribution of this species are not well known. Further, the knowledge of the impact of IAS removal on forest plant diversity is hardly known, and the possibilities of income generation from them at the grass-root communities are rarely documented. Systematic sampling of 1% with nested circular plots of 500 square meters was performed in IAS removed and non-removed area, each of 30 hectares in Udayapur Community Forest User Group (CFUG), Chitwan, central Nepal to observe whether the removal of IAS contributed to an increase in plant diversity. In addition, ten entrepreneurs of Udaypur CFUG, involved in the charcoal production, briquette making and marketing were interviewed and interacted as well as their record keeping booklets were reviewed to understand if the charcoal production contributed to their income and employment. The average annual precipitation and temperature of the study area is 2100 mm and 34 degree Celsius respectively with Shorea robusta as main tree species and Eupatorium odoratum as dominant IAS. All the interviewed households were from the ̔below-poverty-line’ category as per Community Forestry Guidelines. A higher Shannon-Weiner plant diversity index at regeneration level was observed in IAS removed areas (2.43) than in control site (1.95). Furthermore, the number of tree seedlings and saplings in the IAS harvested blocks were significantly higher (p < 0.005) compared to the unharvested one. The sale of charcoal produced through the pyrolysis of IAS in ̔ Bio-energy kilns’ contributed for an average increased income of 30.95 % (Nepalese rupees 31,000) of the involved households. Despite above factors, some operational policy hurdles related to charcoal transport and taxation existed at field level. This study suggests that plant diversity could be increased through the removal of IAS, and considerable economic benefits could be achieved if charcoal is substantially produced and utilized.

Keywords: briquette, economic benefits, pyrolysis, regeneration

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Authors: Amina Akhtar, Rory O'Connor

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Introduction: There remains significant morbidity and mortality in young pedestrians hit by motor vehicles, even in the era of pedestrian crossings and speed limits. The aim of this study was to compare incidence and injury severity of motor vehicle-related pedestrian trauma according to time of day and season in a young population, based on the supposition that injuries would be more prevalent during dusk and dawn and during autumn and winter. Methods: Data was retrieved for patients between 10-25 years old from the National Trauma Audit and Research Network (TARN) database who had been involved as pedestrians in motor vehicle accidents between 2015-2020. The incidence of injuries, their severity (using the Injury Severity Score [ISS]), hospital transfer time, and mortality were analysed according to the hours of daylight, darkness, and season. Results: The study identified a seasonal pattern, showing that autumn was the predominant season and led to 34.9% of injuries, with a further 25.4% in winter in comparison to spring and summer, with 21.4% and 18.3% of injuries, respectively. However, visibility alone was not a sufficient factor as 49.5% of injuries occurred during the time of darkness, while 50.5% occurred during daylight. Importantly, the greatest injury rate (number of injuries/hour) occurred between 1500-1630, correlating to school pick-up times. A further significant relationship between injury severity score (ISS) and daylight was demonstrated (p-value= 0.0124), with moderate injuries (ISS 9-14) occurring most commonly during the day (72.7%) and more severe injuries (ISS>15) occurred during the night (55.8%). Conclusion: We have identified a relationship between time of day and the frequency and severity of pedestrian trauma in young people. In addition, particular time groupings correspond to the greatest injury rate, suggesting that reduced visibility coupled with school pick-up times may play a significant role. This could be addressed through a targeted public health approach to implementing change. We recommend targeted public health measures to improve road safety that focus on these times and that increase the visibility of children combined with education for drivers.

Keywords: major trauma, paediatric trauma, road traffic accidents, diurnal pattern

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Authors: Gashaw Gismu Chakilu

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Climate and land cover change are very important issues in terms of global context and their responses to environmental and socio-economic drivers. The dynamic of these two factors is currently affecting the environment in unbalanced way including watershed hydrology. In this paper individual and combined impacts of climate change and land use land cover change on hydrological processes were evaluated through applying the model Soil and Water Assessment Tool (SWAT) in Gumara watershed, Upper Blue Nile basin Ethiopia. The regional climate; temperature and rainfall data of the past 40 years in the study area were prepared and changes were detected by using trend analysis applying Mann-Kendall trend test. The land use land cover data were obtained from land sat image and processed by ERDAS IMAGIN 2010 software. Three land use land cover data; 1973, 1986, and 2013 were prepared and these data were used for base line, model calibration and change study respectively. The effects of these changes on high flow and low flow of the catchment have also been evaluated separately. The high flow of the catchment for these two decades was analyzed by using Annual Maximum (AM) model and the low flow was evaluated by seven day sustained low flow model. Both temperature and rainfall showed increasing trend; and then the extent of changes were evaluated in terms of monthly bases by using two decadal time periods; 1973-1982 was taken as baseline and 2004-2013 was used as change study. The efficiency of the model was determined by Nash-Sutcliffe (NS) and Relative Volume error (RVe) and their values were 0.65 and 0.032 for calibration and 0.62 and 0.0051 for validation respectively. The impact of climate change was higher than that of land use land cover change on stream flow of the catchment; the flow has been increasing by 16.86% and 7.25% due to climate and LULC change respectively, and the combined change effect accounted 22.13% flow increment. The overall results of the study indicated that Climate change is more responsible for high flow than low flow; and reversely the land use land cover change showed more significant effect on low flow than high flow of the catchment. From the result we conclude that the hydrology of the catchment has been altered because of changes of climate and land cover of the study area.

Keywords: climate, LULC, SWAT, Ethiopia

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: Tiisetso Mpai, Sanjay K. Jaiswal, Felix D. Dakora

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The South African Cape fynbos biome is a global biodiversity hotspot. This biome contains a diversity of endemic shrub legumes, including Polhillia, Wiborgia, and Wiborgiella species, which are important for ecotourism as well as for improving soil fertility status. This is due to their proven N₂-fixing abilities when in association with compatible soil bacteria. In fact, Polhillia, Wiborgia, and Wiborgiella species have been reported to derive over 61% of their needed nitrogen through biological nitrogen fixation and to exhibit acid and alkaline phosphatase activity in their rhizospheres. Thus, their interactions with soil microbes may explain their survival mechanisms under the continued summer droughts and acidic, nutrient-poor soils in this region. However, information regarding their rhizosphere microbiome is still unavailable, yet it is important for Fynbos biodiversity management. Therefore, the aim of this study was to assess the microbial community structures associated with rhizosphere soils of Polhillia pallens, Polhillia brevicalyx, Wiborgia obcordata, Wiborgia sericea, and Wiborgiella sessilifolia growing at different locations of the South African Cape fynbos, during the wet and dry seasons. The hypothesis is that the microbial communities in these legume rhizospheres are the same type and are not affected by the growing season due to the restricted habitat of these wild fynbos legumes. To obtain the results, DNA was extracted from 0.5 g of each rhizosphere soil using PowerSoil™ DNA Isolation Kit, and sequences were obtained using the 16S rDNA Miseq Illumina technology. The results showed that in both seasons, bacteria were the most abundant microbial taxa in the rhizosphere soils of all five legume species, with Actinobacteria showing the highest number of sequences (about 30%). However, over 19.91% of the inhabitants in all five legume rhizospheres were unclassified. In terms of genera, Mycobacterium and Conexibacter were common in rhizosphere soils of all legumes in both seasons except for W. obcordata soils sampled during the dry season, which had Dehalogenimonas as the major inhabitant (6.08%). In conclusion, plant species and season were found to be the main drivers of microbial community structure in Cape fynbos, with the wet season being more dominant in shaping microbial diversity relative to the dry season. Wiborgia obcordata had a greater influence on microbial community structure than the other four legume species.

Keywords: 16S rDNA, Cape fynbos, endemic legumes, microbiome, rhizosphere

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Authors: Sideri Katerina, Chanania Eleni

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The reasons why people remain unvaccinated, especially health workers, are complex. In Greece, 2 percent of health workers (around 7,000) remain unvaccinated, despite the fact that for this group of people vaccination against COVID-19 is mandatory. In April 2022, the Greek health minister repeated that unvaccinated health care workers will remain suspended from their jobs ‘for as long as the pandemic lasts,’ explaining that the suspension of the workers in question was ‘entirely their choice’ and that health professionals who do not believe in vaccines ‘do not believe in their own science.’ Although policy circles around the world often link vaccine hesitancy to ignorance of science or misinformation, various recently published qualitative studies show that vaccine hesitancy is the result of a combination of factors, which include distrust towards elites and the system of innovation and distrust towards government. In a similar spirit, some commentators warn that labeling hesitancy as “anti-science” is bad politics. In this paper, we worked within the tradition of STS taking the view that people draw upon personal associations to enact and express civic concern with an issue, the enactment of public concern involves the articulation of threats to actors’ way of life, personal values, relationships, lived experiences, broader societal values and institutional structures. To this effect, we have conducted 27 in depth interviews with unvaccinated Greek health workers and we are in the process of conducting 20 more interviews. We have so far found that rather than a question of believing in ‘facts’ vaccine hesitancy reflects deep distrust towards those charged with the making of decisions and pharmaceutical companies and that emotions (rather than rational thinking) play a crucial role in the formation of attitudes and the making of decisions. We need to dig deeper so as to understand the causes of distrust towards technical government and the ways in which public(s) conceive of and want to be part in the politics of innovation. We particularly address the question of the effectiveness of mandatory vaccination of health workers and whether such top-down regulatory measures further polarize society, to finally discuss alternative regulatory approaches and governance structures.

Keywords: vaccine hesitancy, innovation, trust in vaccines, sociology of vaccines, attitude drivers towards scientific information, governance

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Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal

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Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: cost forecasting, earned value management, project control, project management, risk analysis, simulation

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Authors: Emilia K. H. Danielsson-Waters, Malaz Elsaddig, Kevin Jones

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Unfortunately, it is well known that neonatal deaths are a common and potentially preventable occurrence across the world. Neonatal resuscitation is a simple and inexpensive intervention that can effectively reduce this rate, and can be taught and implemented globally. This project is a follow-on from one in 2012, which found that neonatal resuscitation simulation was valuable for education, but would be better improved by being delivered by local staff. Methods: This study involved auditing the neonatal admission and death records within a rural Ugandan hospital, alongside implementing a Train-The-Trainer teaching scheme to teach Neonatal Resuscitation. One local doctor was trained for simulating neonatal resuscitation, whom subsequently taught an additional 14 staff members in one-afternoon session. Participants were asked to complete questionnaires to assess their knowledge and confidence pre- and post-simulation, and a survey to identify barriers and drivers to simulation. Results: The results found that the neonatal mortality rate in this hospital was 25% between July 2016- July 2017, with birth asphyxia, prematurity and sepsis being the most common causes. Barriers to simulation that were identified predominantly included a lack of time, facilities and opportunity, yet all members stated simulation was beneficial for improving skills and confidence. The simulation session received incredibly positive qualitative feedback, and also a 0.58-point increase in knowledge (p=0.197) and 0.73-point increase in confidence (0.079). Conclusion: This research shows that it is possible to create a teaching scheme in a rural hospital, however, many barriers are in place for its sustainability, and a larger sample size with a more sensitive scale is required to achieve statistical significance. This is undeniably important, because teaching neonatal resuscitation can have a direct impact on neonatal mortality. Subsequently, recommendations include that efforts should be put in place to create a sustainable training scheme, for example, by employing a resuscitation officer. Moreover, neonatal resuscitation teaching should be conducted more frequently in hospitals, and conducted in a wider geographical context, including within the community, in order to achieve its full effect.

Keywords: neonatal resuscitation, sustainable medical education, train-the-trainer, Uganda

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Authors: Ngoc-Hieu Vu

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Dairy production in Vietnam is a relatively new agricultural activity and milk production increased remarkably in recent years. Smallholders are still the main drivers for this development, especially in the southern part of the country. However, information on the farming practices is very limited. Therefore, this study aimed to determine factors influencing milk yield and quality (milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count) and revenue of dairy farms in Southern Vietnam. The collection of data was at the farm level; individual animal records were unavailable. The 539 studied farms were located in the provinces Lam Dong (N=111 farms), Binh Duong (N=69 farms), Long An (N=174 farms), and Ho Chi Minh city (N=185 farms). The dataset included 9221 monthly test-day records of the farms from January 2013 to May 2015. Seasons were defined as rainy and dry. Farms sizes were classified as small (< 10 milking cows), medium (10 to 19 milking cows) and large (≥ 20 milking cows). The model for each trait contained year-season and farm region-farm size as subclass fixed effects, and individual farm and residual as random effects. Results showed that year-season, region, and farm size were determining sources of variation affecting all studied traits. Milk yield was higher in dry than in rainy seasons (P < 0.05), while it tended to increase from years 2013 to 2015. Large farms had higher yields (445.6 kg/cow) than small (396.7 kg/cow) and medium (428.0 kg/cow) farms (P < 0.05). Small farms, in contrast, were superior to large farms in terms of milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count than large farms (P < 0.05). Revenue per cow was higher in large compared with medium and small farms. In conclusion, large farms achieved higher milk yields and revenues per cow, while small farms were superior in milk quality. Overall, milk yields were low and better training, financial support and marketing opportunities for farmers are needed to improve dairy production and increase farm revenues in Southern Vietnam.

Keywords: farm size, milk yield and quality, season, Southern Vietnam

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

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Authors: Ahmad Mohammad Sharqi, Mohamed Hechmi El Ouni, Saleh Alsulamy

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Due to the emerging technologies revolution worldwide, the need to exploit and employ innovative technologies for other functions and purposes in different aspects has become a remarkable matter. Saudi Arabia is considered one of the most powerful economic countries in the world, where the construction sector participates effectively in its economy. Thus, the construction sector in KSA should convoy the rapid digital revolution and transformation and implement smart devices on sites. A Smart Construction Site (SCS) includes smart devices, artificial intelligence, the internet of things, augmented reality, building information modeling, geographical information systems, and cloud information. This paper aims to study the level of implementation of SCS in KSA, analyze the obstacles and challenges of adopting SCS and find out critical success factors for its implementation. A survey of close-ended questions (scale and multi-choices) has been conducted on professionals in the construction sector of Saudi Arabia. A total number of twenty-nine questions has been prepared for respondents. Twenty-four scale questions were established, and those questions were categorized into several themes: quality, scheduling, cost, occupational safety and health, technologies and applications, and general perception. Consequently, the 5-point Likert scale tool (very low to very high) was adopted for this survey. In addition, five close-ended questions with multi-choice types have also been prepared; these questions have been derived from a previous study implemented in the United Kingdom (UK) and the Dominic Republic (DR), these questions have been rearranged and organized to fit the structured survey in order to place the Kingdom of Saudi Arabia in comparison with the United Kingdom (UK) as well as the Dominican Republic (DR). A total number of one hundred respondents have participated in this survey from all regions of the Kingdom of Saudi Arabia: southern, central, western, eastern, and northern regions. The drivers, obstacles, and success factors for implementing smart devices and technologies in KSA’s construction sector have been investigated and analyzed. Besides, it has been concluded that KSA is on the right path toward adopting smart construction sites with attractive results comparable to and even better than the UK in some factors.

Keywords: artificial intelligence, construction projects management, internet of things, smart construction sites, smart devices

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Authors: Roseliza Mat Alipiah, David Raffaelli, J. C. R. Smart

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This research is a new approach as it integrates information from both environmental and social sciences to inform effective management of the wetlands. A three-stage research framework was developed for modelling the drivers and pressures imposed on the wetlands and their impacts to the ecosystem and the local communities. Firstly, a Bayesian Belief Network (BBN) was used to predict the probability of anthropogenic activities affecting the delivery of different key wetland ecosystem services under different management scenarios. Secondly, Choice Experiments (CEs) were used to quantify the relative preferences which key wetland stakeholder group (aquaculturists) held for delivery of different levels of these key ecosystem services. Thirdly, a Multi-Criteria Decision Analysis (MCDA) was applied to produce an ordinal ranking of the alternative management scenarios accounting for their impacts upon ecosystem service delivery as perceived through the preferences of the aquaculturists. This integrated ecosystem management approach was applied to a wetland ecosystem in Setiu, Terengganu, Malaysia which currently supports a significant level of aquaculture activities. This research has produced clear guidelines to inform policy makers considering alternative wetland management scenarios: Intensive Aquaculture, Conservation or Ecotourism, in addition to the Status Quo. The findings of this research are as follows: The BBN revealed that current aquaculture activity is likely to have significant impacts on water column nutrient enrichment, but trivial impacts on caged fish biomass, especially under the Intensive Aquaculture scenario. Secondly, the best fitting CE models identified several stakeholder sub-groups for aquaculturists, each with distinct sets of preferences for the delivery of key ecosystem services. Thirdly, the MCDA identified Conservation as the most desirable scenario overall based on ordinal ranking in the eyes of most of the stakeholder sub-groups. Ecotourism and Status Quo scenarios were the next most preferred and Intensive Aquaculture was the least desirable scenario. The methodologies developed through this research provide an opportunity for improving planning and decision making processes that aim to deliver sustainable management of wetland ecosystems in Malaysia.

Keywords: Bayesian belief network (BBN), choice experiments (CE), multi-criteria decision analysis (MCDA), aquaculture

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Authors: Patrizia Firmani, Sara Perucchini, Irene Rapone, Raffella Borrelli, Stefano Chiaberge, Manuela Grande, Rosamaria Marrazzo, Alberto Savoini, Andrea Siviero, Silvia Spera, Fabio Vago, Davide Deriu, Sergio Fanutti, Alessandro Oldani

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According to the Renewable Energy Directive II, the use of palm oil in diesel will be gradually reduced from 2023 and should reach zero in 2030 due to the deforestation caused by its production. Eni aims at finding alternative feedstocks for its biorefineries to eliminate the use of palm oil by 2023. Therefore, the ideal vegetable oils to be used in bio-refineries are those obtainable from plants that grow in marginal lands and with low impact on food-and-feed chain; hence, Eni research is studying the possibility of using oleaginous seeds, such as castor, croton, and cotton, to extract the oils to be exploited as feedstock in bio-refineries. To verify their suitability for the upgrading processes, an analytical protocol for their characterization has been drawn up and applied. The analytical characterizations include a step of water and ashes content determination, elemental analysis (CHNS analysis, X-Ray Fluorescence, Inductively Coupled Plasma - Optical Emission Spectroscopy, ICP– Mass Spectrometry), and total acid number determination. Gas chromatography coupled to flame ionization detector (GC-FID) is used to quantify the lipid content in terms of free fatty acids, mono-, di- and triacylglycerols, and fatty acids composition. Eventually, Nuclear Magnetic Resonance and Fourier Transform-Infrared spectroscopies are exploited with GC-MS and Fourier Transform-Ion Cyclotron Resonance to study the composition of the oils. This work focuses on the GC-FID analysis of the lipid fraction of these oils, as the main constituent and of greatest interest for bio-refinery processes. Specifically, the lipid component of the extracted oil was quantified after sample silanization and transmethylation: silanization allows the elution of high-boiling compounds and is useful for determining the quantity of free acids and glycerides in oils, while transmethylation leads to a mixture of fatty acid esters and glycerol, thus allowing to evaluate the composition of glycerides in terms of Fatty Acids Methyl Esters (FAME). Cotton oil was extracted from cotton oilcake, croton oil was obtained by seeds pressing and seeds and oilcake ASE extraction, while castor oil comes from seed pressing (not performed in Eni laboratories). GC-FID analyses reported that the cotton oil is 90% constituted of triglycerides and about 6% diglycerides, while free fatty acids are about 2%. In terms of FAME, C18 acids make up 70% of the total and linoleic acid is the major constituent. Palmitic acid is present at 17.5%, while the other acids are in low concentration (<1%). Both analyzes show the presence of non-gas chromatographable compounds. Croton oils from seed pressing and extraction mainly contain triglycerides (98%). Concerning FAME, the main component is linoleic acid (approx. 80%). Oilcake croton oil shows higher abundance of diglycerides (6% vs ca 2%) and a lower content of triglycerides (38% vs 98%) compared to the previous oils. Eventually, castor oil is mostly constituted of triacylglycerols (about 69%), followed by diglycerides (about 10%). About 85.2% of total FAME is ricinoleic acid, as a constituent of triricinolein, the most abundant triglyceride of castor oil. Based on the analytical results, these oils represent feedstocks of interest for possible exploitation as advanced biofuels.

Keywords: analytical protocol, biofuels, biorefinery, gas chromatography, vegetable oil

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: Mandy Wilson, Emma Vieira, Jocelyn Jones, Alice V. Brown, Lindey Andrews, Louise Southalan, Jackie Oakley, Dorothy Bagshaw, Patrick Egan, Laura Dent, Duc Dau, Lucy Spanswick

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Alcohol and drug dependency are pertinent issues for those experiencing homelessness. This includes Aboriginal and Torres Strait Islander people, Australia’s traditional owners, living in Perth, Western Australia (WA). Societal narratives around the drivers behind drug and alcohol dependency in Aboriginal communities, particularly those experiencing homelessness, have been biased and unchanging, with little regard for complexity. This can include the idea that Aboriginal people have ‘chosen’ to use alcohol or other drugs without consideration for intergenerational trauma and the trauma of homelessness that may influence their choices. These narratives have flow-on impacts on policies and services that directly impact Aboriginal people experiencing homelessness. In 2021, we commenced a project which aimed to listen to and elevate the voices of 70-90 Aboriginal people experiencing homelessness in Perth. The project is community-driven, led by an Aboriginal Community Controlled Organisation in partnership with a university research institute. A community-ownership group of Aboriginal Elders endorsed the project’s methods, chosen to ensure their suitability for the Aboriginal community. In this paper, we detail these methods, including semi-structured interviews influenced by an Aboriginal yarning approach – an important style of conversation for Aboriginal people which follows cultural protocols; and photovoice – supporting people to share their stories through photography. Through these engagements, we detail the reasons Aboriginal people in Perth shared for using alcohol or other drugs while experiencing homelessness. These included supporting their survival on the streets, managing their mental health, and coping while on the journey to finding support. We also detail why they sought to discontinue alcohol and other drug use, including wanting to reconnect with family and changing priorities. Finally, we share how Aboriginal people experiencing homelessness have said they are impacted by their family’s alcohol and other drug use, including feeling uncomfortable living with a family who is drug and alcohol-dependent and having to care for grandchildren despite their own homelessness. These findings provide a richer understanding of alcohol and drug use for Aboriginal people experiencing homelessness in Perth, shedding light on potential changes to targeted policy and service approaches.

Keywords: Aboriginal and Torres Strait Islander peoples, alcohol and other drugs, homelessness, community-led research

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Authors: Osamede Asowata, Christo Pienaar, Johan Bekker

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Photovoltaic (PV) modules may become a trend for future PV systems because of their greater flexibility in distributed system expansion, easier installation due to their nature, and higher system-level energy harnessing capabilities under shaded or PV manufacturing mismatch conditions. This is as compared to the single or multi-string inverters. Novel residential scale PV arrays are commonly connected to the grid by a single DC–AC inverter connected to a series, parallel or series-parallel string of PV panels, or many small DC–AC inverters which connect one or two panels directly to the AC grid. With an increasing worldwide interest in sustainable energy production and use, there is renewed focus on the power electronic converter interface for DC energy sources. Three specific examples of such DC energy sources that will have a role in distributed generation and sustainable energy systems are the photovoltaic (PV) panel, the fuel cell stack, and batteries of various chemistries. A high-efficiency inverter using Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs) for all active switches is presented for a non-isolated photovoltaic and AC-module applications. The proposed configuration features a high efficiency over a wide load range, low ground leakage current and low-output AC-current distortion with no need for split capacitors. The detailed power stage operating principles, pulse width modulation scheme, multilevel bootstrap power supply, and integrated gate drivers for the proposed inverter is described. Experimental results of a hardware prototype, show that not only are MOSFET efficient in the system, it also shows that the ground leakage current issues are alleviated in the proposed inverter and also a 98 % maximum associated driver circuit is achieved. This, in turn, provides the need for a possible photovoltaic panel switching technique. This will help to reduce the effect of cloud movements as well as improve the overall efficiency of the system.

Keywords: grid connected photovoltaic (PV), Matlab efficiency simulation, maximum power point tracking (MPPT), module integrated converters (MICs), multilevel converter, series connected converter

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Authors: Abrehet Kahsay Mehari

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Aquatic plants provide the physical structure of wetlands and increase their habitat complexity and heterogeneity, and as such, have a profound influence on other biotas. In this study, we investigated how human disturbance activities influenced the species richness and community composition of aquatic plants in the wetlands of Lake Tana, Ethiopia. Twelve wetlands were selected: four lacustrine, four river mouths, and four riverine papyrus swamps. Data on aquatic plants, environmental variables, and human activities were collected during the dry and wet seasons of 2018. A linear mixed effect model and a distance-based Redundancy Analysis (db-RDA) were used to relate aquatic plant species richness and community composition, respectively, to human activities and environmental variables. A total of 113 aquatic plant species, belonging to 38 families, were identified across all wetlands during the dry and wet seasons. Emergent species had the maximum area covered at 73.45 % and attained the highest relative abundance, followed by amphibious and other forms. The mean taxonomic richness of aquatic plants was significantly lower in wetlands with high overall human disturbance scores compared to wetlands with low overall human disturbance scores. Moreover, taxonomic richness showed a negative correlation with livestock grazing, tree plantation, and sand mining. The community composition also varied across wetlands with varying levels of human disturbance and was primarily driven by turnover (i.e., replacement of species) rather than nestedness resultant(i.e., loss of species). Distance-based redundancy analysis revealed that livestock grazing, tree plantation, sand mining, waste dumping, and crop cultivation were significant predictors of variation in aquatic plant communities’ composition in the wetlands. Linear mixed effect models and distance-based redundancy analysis also revealed that water depth, turbidity, conductivity, pH, sediment depth, and temperature were important drivers of variations in aquatic plant species richness and community composition. Papyrus swamps had the highest species richness and supported different plant communities. Conservation efforts should therefore focus on these habitats and measures should be taken to restore the highly disturbed and species poor wetlands near the river mouths.

Keywords: species richness, community composition, aquatic plants, wetlands, Lake Tana, human disturbance activities

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Authors: Petra Suchovska

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The spirit of post-modernity remains chaotic and obscure. Geopolitical rivalries raging at the more extreme levels and the ability of intellectual community to explain the entropy of global affairs has been diminishing. The Western-led idea of globalisation imposed upon the world does not seem to bring the bright future for human progress anymore, and its architects lose much of global control, as the strong non-western cultural entities develop new forms of post-modern establishments. The overall growing cultural misunderstanding and mistrust are expressions of political impotence to deal with the inner contradictions within the contemporary phenomenon (capitalism, economic globalisation) that embrace global society. The drivers and effects of global restructuring must be understood in the context of systems and principles reflecting on true complexity of society. The purpose of this paper is to set out some ideas about how cybernetics can contribute to understanding international system structure and analyse possible world futures. “IS Cybernetics” would apply to system thinking and cybernetic principles in IR in order to analyse and handle the complexity of social phenomena from global perspective. “IS cybernetics” would be, for now, the subfield of IR, concerned with applying theories and methodologies from cybernetics and system sciences by offering concepts and tools for addressing problems holistically. It would bring order to the complex relations between disciplines that IR touches upon. One of its tasks would be to map, measure, tackle and find the principles of dynamics and structure of social forces that influence human behaviour and consequently cause political, technological and economic structural reordering, forming and reforming the international system. “IS cyberneticists” task would be to understand the control mechanisms that govern the operation of international society (and the sub-systems in their interconnection) and only then suggest better ways operate these mechanisms on sublevels as cultural, political, technological, religious and other. “IS cybernetics” would also strive to capture the mechanism of social-structural changes in time, which would open space for syntheses between IR and historical sociology. With the cybernetic distinction between first order studies of observed systems and the second order study of observing systems, IS cybernetics would also provide a unifying epistemological and methodological, conceptual framework for multilateralism and multiple modernities theory.

Keywords: cybernetics, historical sociology, international system, systems theory

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Authors: Sven Borén, Lisiana Nurhadi, Henrik Ny

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From a theoretical perspective, electric buses can be more sustainable and can be cheaper than fossil fuelled buses in city traffic. The authors have not found other studies based on actual urban public transport in Swedish winter climate. Further on, noise measurements from buses for the European market were found old. The aims of this follow-up study was therefore to test and possibly verify in a real-life environment how energy efficient and silent electric buses are, and then conclude on if electric buses are preferable to use in public transport. The Ebusco 2.0 electric bus, fitted with a 311 kWh battery pack, was used and the tests were carried out during November 2014-April 2015 in eight municipalities in the south of Sweden. Six tests took place in urban traffic and two took place in more of a rural traffic setting. The energy use for propulsion was measured via logging of the internal system in the bus and via an external charging meter. The average energy use turned out to be 8% less (0,96 kWh/km) than assumed in the earlier theoretical study. This rate allows for a 320 km range in public urban traffic. The interior of the bus was kept warm by a diesel heater (biodiesel will probably be used in a future operational traffic situation), which used 0,67 kWh/km in January. This verified that electric buses can be up to 25% cheaper when used in public transport in cities for about eight years. The noise was found to be lower, primarily during acceleration, than for buses with combustion engines in urban bus traffic. According to our surveys, most passengers and drivers appreciated the silent and comfortable ride and preferred electric buses rather than combustion engine buses. Bus operators and passenger transport executives were also positive to start using electric buses for public transport. The operators did however point out that procurement processes need to account for eventual risks regarding this new technology, along with personnel education. The study revealed that it is possible to establish a charging infrastructure for almost all studied bus lines. However, design of a charging infrastructure for each municipality requires further investigations, including electric grid capacity analysis, smart location of charging points, and tailored schedules to allow fast charging. In conclusion, electric buses proved to be a preferable alternative for all stakeholders involved in public bus transport in the studied municipalities. However, in order to electric buses to be a prominent support for sustainable development, they need to be charged either by stand-alone units or via an expansion of the electric grid, and the electricity should be made from new renewable sources.

Keywords: sustainability, electric, bus, noise, greencharge

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Authors: Philippa Saunders, Claire Fletcher

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INTRODUCTION: Prostate cancer is the most prevalent malignancy affecting Western males. It is initially an androgen-dependent disease: androgens bind to the androgen receptor and drive the expression of genes that promote proliferation and evasion of apoptosis. Despite reduced androgen dependence in advanced prostate cancer, androgen receptor signaling remains a key driver of growth. Androgen deprivation therapy (ADT) is, therefore, a first-line treatment approach and works well initially, but resistance inevitably develops. Abiraterone and Enzalutamide are drugs widely used in ADT and are androgen synthesis and androgen receptor signaling inhibitors, respectively. The shortage of other treatment options means acquired resistance to these drugs is a major clinical problem. MicroRNAs (miRs) are important mediators of post-transcriptional gene regulation and show altered expression in cancer. Several have been linked to the development of resistance to ADT. Manipulation of such miRs may be a pathway to breakthrough treatments for advanced prostate cancer. This study aimed to validate ADT resistance-implicated miRs and their clinically relevant targets. MATERIAL AND METHOD: Small RNA-sequencing of Abiraterone- and Enzalutamide-resistant C42 prostate cancer cells identified subsets of miRs dysregulated as compared to parental cells. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was used to validate altered expression of candidate ADT resistance-implicated miRs 195-5p, 497-5p and 29a-5p in ADT-resistant and -responsive prostate cancer cell lines, patient-derived xenografts (PDXs) and primary prostate cancer explants. RESULTS AND DISCUSSION: This study suggests a possible role for miR-497-5p in the development of ADT resistance in prostate cancer. MiR-497-5p expression was increased in ADT-resistant versus ADT-responsive prostate cancer cells. Importantly, miR-497-5p expression was also increased in Enzalutamide-treated, castrated (ADT-mimicking) PDXs versus intact PDXs. MiR-195-5p was also elevated in ADT-resistant versus -responsive prostate cancer cells, while there was a drop in miR-29a-5p expression. Candidate clinically relevant targets of miR-497-5p in prostate cancer were identified by mining AGO-PAR-CLIP-seq data sets and may include AVL9 and FZD6. CONCLUSION: In summary, this study identified microRNAs that are implicated in prostate cancer resistance to androgen deprivation therapy and could represent novel therapeutic targets for advanced disease.

Keywords: microRNA, androgen deprivation therapy, Enzalutamide, abiraterone, patient-derived xenograft

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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Changes in behaviour and physiology are the most important responses of marine life to anthropogenic impacts such as climate change and over-fishing. Behavioural changes (such as a shift in distribution or changes in phenology) can ensure that a species remains in an environment suited for its optimal physiological performance. However, if marine life is unable to shift their distribution, they are reliant on physiological adaptation (either by broadening their metabolic curves to tolerate a range of stressors or by shifting their metabolic curves to maximize their performance at extreme stressors). However, since there are links between fish physiology and behaviour, changes to either of these traits may have reciprocal interactions. This paper reviews the current knowledge of the links between the behaviour and physiology of fishes, discusses these in the context of exploitation and climate change, and makes recommendations for future research needs. The review revealed that our understanding of the links between fish behaviour and physiology is rudimentary. However, both are hypothesized to be linked to stress responses along the hypothalamic pituitary axis. The link between physiological capacity and behaviour is particularly important as both determine the response of an individual to a changing climate and are under selection by fisheries. While it appears that all types of capture fisheries are likely to reduce the adaptive potential of fished populations to climate stressors, angling, which is primarily associated with recreational fishing, may induce fission of natural populations by removing individuals with bold behavioural traits and potentially the physiological traits required to facilitate behavioural change. Future research should focus on assessing how the links between physiological capacity and behaviour influence catchability, the response to climate change drivers, and post-release recovery. The plasticity of phenotypic traits should be examined under a range of stressors of differing intensity in several species and life history stages. Future studies should also assess plasticity (fission or fusion) in the phenotypic structuring of social hierarchy and how this influences habitat selection. Ultimately, to fully understand how physiology is influenced by the selective processes driven by fisheries, long-term monitoring of the physiological and behavioural structure of fished populations, their fitness, and catch rates are required.

Keywords: climate change, metabolic shifts, over-fishing, phenotypic plasticity, stress response

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Authors: Yasser O. Abualnaja1, Alexandra Pavlidou2, Taha Boksmati3, Ahmad Alharbi3, Hammad Alsulmi3, Saleh Omar Maghrabi3, Hassan Mowalad3, Rayan Mutwalli3, James H. Churchill4, Afroditi Androni2, Dionysios Ballas2, Ioannis Hatzianestis2, Harilaos Kontoyiannis2, Angeliki Konstantinopoulou2, Georgios Krokkos1, 5, Georgios Pappas2, Vassilis P. Papadopoulos2, Konstantinos Parinos2, Elvira Plakidi2, Eleni Rousselaki2, Dimitris Velaoras2, Panagiota Zachioti2, Theodore Zoulias2, Ibrahim Hoteit5.

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The coastal areas along the Kingdom of Saudi Arabia on both the Red Sea and Arabian Gulf have been witnessing in the past decades an unprecedented economic growth and a rapid increase in anthropogenic activities. Therefore, the Saudi Arabian government has decided to frame a strategy for sustainable development of the coastal and marine environments, which comes in the context of the Vision 2030, aimed at providing the first comprehensive ‘Status Quo Assessment’ of the Kingdom’s coastal and marine environments. This strategy will serve as a baseline assessment for future monitoring activities; this baseline is relied on scientific evidence of the drivers, pressures, and their impact on the environments of the Red Sea and Arabian Gulf. A key element of the assessment was the cumulative pressures of the hotspots analysis, which was developed following the principles of the Driver-Pressure-State-Impact-Response (DPSIR) framework and using the cumulative pressure and impact assessment methodology. Ten hotspot sites were identified, eight in the Red Sea and two in the Arabian Gulf. Thus, multidisciplinary research cruises were conducted throughout the Red Sea and the Arabian Gulf coastal and marine environments in June/July 2021 and September 2021, respectively, in order to understand the relative impact of hydrography and the various pressures on the quality of seawater and sediments. The main objective was to record the physical and biogeochemical parameters along the coastal waters of the Kingdom, tracing the dispersion of contaminants related to specific pressures. The assessment revealed the effect of hydrography on the trophic status of the southern marine coastal areas of the Red Sea. Jeddah Lagoon system seems to face significant eutrophication and pollution challenges, whereas sediments are enriched in some heavy metals in many areas of the Red Sea and the Arabian Gulf. This multidisciplinary research in the Red Sea and the Arabian Gulf coastal waters will pave the way for future detailed environmental monitoring strategies for the Saudi Arabian marine environment.

Keywords: arabian gulf, contaminants, hotspot, red sea

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Authors: Lydia Ouma Radoli

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The paradox of documenting history through visuals that objectify gruesome images to depict the prominence of stories intrigues media researchers. In East Africa, the topic has been captured in a variety of media frames, but scantly in scholarly work. This paper adopts Visual Rhetoric and Framing Theories to tease out the drivers behind the criteria for the selection of violent visuals. The paper projects that quantitative and qualitative literature regarding journalists’ personal and work-related exposure to PSTD will give insights into the concept of trauma journalism - reporting of horrific events, e.g., violent crime and terror. The data will be collected through methods such as document analysis (photographs and videos) and in-depth interviews to summarize the informational contents with respect to the research objectives and questions. The study is hinged on the background that the criterion for news production is constructed from the idea that ‘if there’s violence, conflict, and death involved, the story gets top priority.’ The anticipated outcome is to establish trauma experiences of visual rhetors, suggest mitigations, and address gaps in academic research. The findings of the study will sustain the critical role of visual rhetors. Further, media practitioners may find the study useful in assessing the effects and values of visual witnessing. Historically, the criterion for visual news production has been that if there’s violence, conflict, and death involved, the story gets top priority. To capture the goriness of the images, media theorists and sociologists have used the expression: “If it bleeds, it leads.” The statement assumes that audiences are attracted to pictures that show violent images. Further, research on visual aspects of Television news has shown its ability to hold viewers’ attention and cause aggression. This paper samples images and narratives from Journalists who have covered trauma-related events. The samples are indicative of the problem under study, which depicts journalists exposed to traumatic events as not receiving any Psycho-social support within newsrooms. It is hoped that the study could inform policy and practice within developing countries through the interpretations of theoretical and empirical explanations of existing trauma phenomena among journalists.

Keywords: visual-witnessing, media culture, visual rhetoric, imaging violence in East Africa

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Authors: Wenqi Liu, Reginald Bailey

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This study proposes a comprehensive and effective approach to business-to-business (B2B) sales forecasting by integrating advanced machine learning models with a rule-based decision-making framework. The methodology addresses the critical challenge of optimizing sales pipeline performance and improving conversion rates through predictive analytics and actionable insights. The first component involves developing a classification model to predict the likelihood of conversion, aiming to outperform traditional methods such as logistic regression in terms of accuracy, precision, recall, and F1 score. Feature importance analysis highlights key predictive factors, such as client revenue size and sales velocity, providing valuable insights into conversion dynamics. The second component focuses on forecasting sales value using a regression model, designed to achieve superior performance compared to linear regression by minimizing mean absolute error (MAE), mean squared error (MSE), and maximizing R-squared metrics. The regression analysis identifies primary drivers of sales value, further informing data-driven strategies. To bridge the gap between predictive modeling and actionable outcomes, a rule-based decision framework is introduced. This model categorizes leads into high, medium, and low priorities based on thresholds for conversion probability and predicted sales value. By combining classification and regression outputs, this framework enables sales teams to allocate resources effectively, focus on high-value opportunities, and streamline lead management processes. The integrated approach significantly enhances lead prioritization, increases conversion rates, and drives revenue generation, offering a robust solution to the declining pipeline conversion rates faced by many B2B organizations. Our findings demonstrate the practical benefits of blending machine learning with decision-making frameworks, providing a scalable, data-driven solution for strategic sales optimization. This study underscores the potential of predictive analytics to transform B2B sales operations, enabling more informed decision-making and improved organizational outcomes in competitive markets.

Keywords: machine learning, XGBoost, regression, decision making framework, system engineering

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