Search results for: exergy losses

Authors: Rahil Bahrami, Kaveh Ashenayi

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This paper presents a systematic classification and comparative analysis of non-isolated bi-directional DC-DC converters. The increasing demand for efficient energy conversion in diverse applications has spurred the development of various converter topologies. In this study, we categorize bi-directional converters into three distinct classes: Inverting, Non-Inverting, and Interleaved. Each category is characterized by its unique operational characteristics and benefits. Furthermore, a practical comparison is conducted by evaluating the results of simulation of each bi-directional converter. BDCs can be classified into isolated and non-isolated topologies. Non-isolated converters share a common ground between input and output, making them suitable for applications with minimal voltage change. They are easy to integrate, lightweight, and cost-effective but have limitations like limited voltage gain, switching losses, and no protection against high voltages. Isolated converters use transformers to separate input and output, offering safety benefits, high voltage gain, and noise reduction. They are larger and more costly but are essential for automotive designs where safety is crucial. The paper focuses on non-isolated systems.The paper discusses the classification of non-isolated bidirectional converters based on several criteria. Common factors used for classification include topology, voltage conversion, control strategy, power capacity, voltage range, and application. These factors serve as a foundation for categorizing converters, although the specific scheme might vary depending on contextual, application, or system-specific requirements. The paper presents a three-category classification for non-isolated bi-directional DC-DC converters: inverting, non-inverting, and interleaved. In the inverting category, converters produce an output voltage with reversed polarity compared to the input voltage, achieved through specific circuit configurations and control strategies. This is valuable in applications such as motor control and grid-tied solar systems. The non-inverting category consists of converters maintaining the same voltage polarity, useful in scenarios like battery equalization. Lastly, the interleaved category employs parallel converter stages to enhance power delivery and reduce current ripple. This classification framework enhances comprehension and analysis of non-isolated bi-directional DC-DC converters. The findings contribute to a deeper understanding of the trade-offs and merits associated with different converter types. As a result, this work aids researchers, practitioners, and engineers in selecting appropriate bi-directional converter solutions for specific energy conversion requirements. The proposed classification framework and experimental assessment collectively enhance the comprehension of non-isolated bi-directional DC-DC converters, fostering advancements in efficient power management and utilization.The simulation process involves the utilization of PSIM to model and simulate non-isolated bi-directional converter from both inverted and non-inverted category. The aim is to conduct a comprehensive comparative analysis of these converters, considering key performance indicators such as rise time, efficiency, ripple factor, and maximum error. This systematic evaluation provides valuable insights into the dynamic response, energy efficiency, output stability, and overall precision of the converters. The results of this comparison facilitate informed decision-making and potential optimizations, ensuring that the chosen converter configuration aligns effectively with the designated operational criteria and performance goals.

Keywords: bi-directional, DC-DC converter, non-isolated, energy conversion

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Authors: José Silvestre Mendoza Figueroa, Anders Kvarnheden, Jesús Méndez Lozano, Edgar Antonio Rodríguez Negrete, Manuel Soriano García

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Agroindustrial plants such as cereals and pseudo cereals offer a substantial source of biomacromolecules, as they contain large amounts per tissue-gram of proteins, polysaccharides and lipids in comparison with other plants. In particular, Amaranthus hypochondriacus seeds have high levels of proteins in comparison with other cereal and pseudo cereal species, which makes the plant a good source of bioactive molecules such as peptides. Geminiviruses are one principal class of pathogens that causes important economic losses in crops, affecting directly the development and production of the plant. One such virus is the Tomato yellow leaf curl virus (TYLCV), which affects mainly Solanacea family plants such as tomato species. The symptoms of the disease are curling of leaves, chlorosis, dwarfing and floral abortion. The aim of this work was to get peptides derived from enzymatic hydrolysis of globulins and albumins from amaranth seeds with specific recognition of the replication origin in the TYLCV genome, and to test the antiviral activity on host plants with the idea to generate a direct control of this viral infection. Globulins and albumins from amaranth were extracted, the fraction was enzymatically digested with papain, and the aromatic peptides fraction was selected for further purification. Six peptides were tested against the replication origin (OR) using affinity assays, surface resonance plasmon and fluorescent titration, and two of these peptides showed high affinity values to the replication origin of the virus, dissociation constant values were calculated and showed specific interaction between the peptide Ampep1 and the OR. An in vitro replication test of the total TYLCV DNA was performed, in which the peptide AmPep1 was added in different concentrations to the system reaction, which resulted in a decrease of viral DNA synthesis when the peptide concentration increased. Also, we showed that the peptide can decrease the complementary DNA chain of the virus in Nicotiana benthamiana leaves, confirming that the peptide binds to the OR and that its expected mechanism of action is to decrease the replication rate of the viral genome. In an infection assay, N. benthamiana plants were agroinfected with TYLCV-Israel and TYLCV-Guasave. After confirming systemic infection, the peptide was infiltrated in new infected leaves, and the plants treated with the peptide showed a decrease of virus symptoms and viral titer. In order to confirm the antiviral activity in a commercial crop, tomato plants were infected with TYLCV. After confirming systemic infection, plants were infiltrated with peptide solution as above, and the symptom development was monitored 21 days after treatment, showing that tomato plants treated with peptides had lower symptom rates and viral titer. The peptide was also tested against other begomovirus such as Pepper huasteco yellow vein virus (PHYVV-Guasave), showing a decrease of symptoms in N. benthamiana infected plants. The model of direct biochemical control of TYLCV infection shown in this work can be extrapolated to other begomovirus infections, and the methods reported here can be used for design of antiviral agrochemicals for other plant virus infections.

Keywords: agrochemical screening, antiviral, begomovirus, geminivirus, peptides, plasmon, TYLCV

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Authors: Tugba Altin

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In an era marked by pronounced climate change consequences, communities are observed to confront traumatic events that yield both tangible and intangible repercussions. Such events not only cause discernible damage to the landscape but also deeply affect the intangible aspects, including emotional distress and disruptions to cultural landscapes. The Lytton Creek Fire of 2021 serves as a case in point. Beyond the visible destruction, the less overt but profoundly impactful disturbance to place attachment (PA) is scrutinized. PA, representing the emotional and cognitive bonds individuals establish with their environments, is crucial for understanding how such events impact cultural identity and connection to the land. The study underscores the significance of addressing both tangible and intangible traumas for holistic community recovery. As communities renegotiate their affiliations with altered environments, the cultural landscape emerges as instrumental in shaping place-based identities. This renewed understanding is pivotal for reshaping adaptation planning. The research advocates for adaptation strategies rooted in the lived experiences and testimonies of the affected populations. By incorporating both the tangible and intangible facets of trauma, planning efforts are suggested to be more culturally attuned and emotionally insightful, fostering true resonance with the affected communities. Through such a comprehensive lens, this study contributes enriching the climate change discourse, emphasizing the intertwined nature of tangible recovery and the imperative of emotional and cultural healing after environmental disasters. Following the pronounced aftermath of the Lytton Creek Fire in 2021, research aims to deeply understand its impact on place attachment (PA), encompassing the emotional and cognitive bonds individuals form with their environments. The interpretive phenomenological approach, enriched by a hermeneutic framework, is adopted, emphasizing the experiences of the Lytton community and co-researchers. Phenomenology informed the understanding of 'place' as the focal point of attachment, providing insights into its formation and evolution after traumatic events. Data collection departs from conventional methods. Instead of traditional interviews, walking audio sessions and photo elicitation methods are utilized. These allow co-researchers to immerse themselves in the environment, re-experience, and articulate memories and feelings in real-time. Walking audio facilitates reflections on spatial narratives post-trauma, while photo voices captured intangible emotions, enabling the visualization of place-based experiences. The analysis is collaborative, ensuring the co-researchers' experiences and interpretations are central. Emphasizing their agency in knowledge production, the process is rigorous, facilitated by the harmonious blend of interpretive phenomenology and hermeneutic insights. The findings underscore the need for adaptation and recovery efforts to address emotional traumas alongside tangible damages. By exploring PA post-disaster, the research not only fills a significant gap but advocates for an inclusive approach to community recovery. Furthermore, the participatory methodologies employed challenge traditional research paradigms, heralding potential shifts in qualitative research norms.

Keywords: wildfire recovery, place attachment, trauma recovery, cultural landscape, visual methodologies

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Authors: Ziara Carmelli G. Tan, Irene Carmelle S. Tan

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Background: Trichotillomania (TTM) and Major Depressive Disorder (MDD) are two psychiatric conditions that frequently co-occur, presenting a significant challenge for treatment due to their complex interplay. TTM involves repetitive hair-pulling, leading to noticeable hair loss and distress, while MDD is characterized by persistent low mood and loss of interest or pleasure, leading to dysfunctionality. This case report examines the intricate relationship between TTM and MDD in a young adult female, emphasizing the need for a comprehensive, multifaceted therapeutic approach to address both disorders effectively. Case Presentation: The patient is a 21-year-old female college student and youth church leader who presented with chronic hair-pulling and depressive symptoms. Her premorbid personality was marked by low self-esteem and a strong need for external validation. Despite her academic and social responsibilities and achievements, she struggled with managing her emotional distress, which was exacerbated by her family dynamics and her role within her church community. Her hair-pulling and mood symptoms were particularly triggered by self-esteem threats and feelings of inadequacy. She was diagnosed with Trichotillomania, Scalp and Major Depressive Disorder. Intervention/Management: The patient’s treatment plan was comprehensive, incorporating both pharmacological and non-pharmacological interventions. Initial pharmacologic management was Fluoxetine 20mg/day up, titrated to 40mg/day with no improvement; hence, shifted to Escitalopram 20mg/day and started with N-acetylcysteine 600mg/day with noted significant improvement in symptoms. Psychotherapeutic strategies played a crucial role in her treatment. These included supportive-expressive psychodynamic psychotherapy, which helped her explore and understand underlying emotional conflicts. Cognitive-behavioral techniques were employed to modify her maladaptive thoughts and behaviors. Grief processing was integrated to help her cope with significant losses. Family therapy was done to address conflicts and collaborate with the treatment process. Psychoeducation was provided to enhance her understanding of her condition and to empower her in her treatment journey. A suicide safety plan was developed to ensure her safety during critical periods. An interprofessional approach, which involved coordination with the Dermatology service for co-management, was also a key component of her treatment. Outcome: Over the course of 15 therapy sessions, the patient demonstrated significant improvement in both her depressive symptoms and hair-pulling behavior. Her active engagement in therapy, combined with pharmacological support, facilitated better emotional regulation and a more cohesive sense of self. Her adherence to the treatment plan, along with the collaborative efforts of the interprofessional team, contributed to her positive outcomes. Discussion: This case underscores the significance of addressing both TTM and its comorbid conditions to achieve effective treatment outcomes. The intricate interplay between TTM and MDD in the patient’s case highlights the importance of a comprehensive treatment plan that includes both pharmacological and psychotherapeutic approaches. Supportive-expressive psychodynamic psychotherapy, Cognitive-behavioral techniques, and Family therapy were particularly beneficial in addressing the complex emotional and behavioral aspects of her condition. The involvement of an interprofessional team, including dermatology co-management, was crucial in providing holistic care. Future practice should consider the benefits of such a multidisciplinary approach to managing complex cases like this, ensuring that both the psychological and physiological aspects of the disorders are adequately addressed.

Keywords: cognitive-behavioral therapy, interprofessional approach, major depressive disorder, psychodynamic psychotherapy, trichotillomania

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Authors: Carlotta D’Alessandro, Giuseppe Ioppolo, Katarzyna Szopik-Depczyńska

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— The growing scarcity of resources and the mounting pressures of climate change, water pollution, and chemical contamination have prompted societies, governments, and businesses to seek ways to minimize their environmental impact. To combat climate change, and foster sustainability, Industrial Symbiosis (IS) offers a powerful approach, facilitating the shift toward a circular economic model. IS has gained prominence in the European Union's policy framework as crucial enabler of resource efficiency and circular economy practices. The essence of IS lies in the collaborative sharing of resources such as energy, material by-products, waste, and water, thanks to geographic proximity. It can be exemplified by eco-industrial parks (EIPs), which are natural environments for boosting cooperation and resource sharing between businesses. EIPs are characterized by group of businesses situated in proximity, connected by a network of both cooperative and competitive interactions. They represent a sustainable industrial model aimed at reducing resource use, waste, and environmental impact while fostering economic and social wellbeing. IS, combined with Artificial Intelligence (AI)-driven technologies, can further optimize resource sharing and efficiency within EIPs. This research, supported by the “CE_IPs” project, aims to analyze the potential for IS and AI, in advancing circularity and sustainability at Fosso Imperatore. The Fosso Imperatore Industrial Park in Nocera Inferiore, Italy, specializes in agriculture and the industrial transformation of agricultural products, particularly tomatoes, tobacco, and textile fibers. This unique industrial cluster, centered around tomato cultivation and processing, also includes mechanical engineering enterprises and agricultural packaging firms. To stimulate the shift from a traditional to a circular economic model, an AI-powered Local Development Plan (LDP) is developed for Fosso Imperatore. It can leverage data analytics, predictive modeling, and stakeholder engagement to optimize resource utilization, reduce waste, and promote sustainable industrial practices. A comprehensive SWOT analysis of the AI-powered LDP revealed several key factors influencing its potential success and challenges. Among the notable strengths and opportunities arising from AI implementation are reduced processing times, fewer human errors, and increased revenue generation. Furthermore, predictive analytics minimize downtime, bolster productivity, and elevate quality while mitigating workplace hazards. However, the integration of AI also presents potential weaknesses and threats, including significant financial investment, since implementing and maintaining AI systems can be costly. The widespread adoption of AI could lead to job losses in certain sectors. Lastly, AI systems are susceptible to cyberattacks, posing risks to data security and operational continuity. Moreover, an Analytic Hierarchy Process (AHP) analysis was employed to yield a prioritized ranking of the outlined AI-driven LDP practices based on the stakeholder input, ensuring a more comprehensive and representative understanding of their relative significance for achieving sustainability in Fosso Imperatore Industrial Park. While this study provides valuable insights into the potential of AIpowered LDP at the Fosso Imperatore, it is important to note that the findings may not be directly applicable to all industrial parks, particularly those with different sizes, geographic locations, or industry compositions. Additional study is necessary to scrutinize the generalizability of these results and to identify best practices for implementing AI-driven LDP in diverse contexts.

Keywords: artificial intelligence, climate change, Fosso Imperatore, industrial park, industrial symbiosis

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Authors: Pablo Reche

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Since 1980’s aquaculture has become the biggest economic activity in southern Chile, being Salmo salar and Oncorhynchus mykiss the main finfish species. High fish density makes both species prone to contract diseases, what drives the industry to big losses, affecting greatly the local economy. Three are the most concerning infective agents, the infectious salmon anemia virus (ISAv), the bacteria Piscirickettsia salmonis and the copepod Caligus rogercresseyi. To regulate the industry the government arranged the salmon farms within management areas named as barrios, which coordinate the fallowing periods and antibiotics treatments of their salmon farms. In turn, barrios are gathered into larger management areas, named as macrozonas whose purpose is to minimize the risk of disease transmission between them and to enclose the outbreaks within their boundaries. However, disease outbreaks still happen and transmission to neighbor sites enlarges the initial event. Salmon disease agents are mostly transported passively by local currents. Thus, to understand how transmission occurs it must be firstly studied the physical environment. In Chile, salmon farming takes place in the inner seas of the southernmost regions of western Patagonia, between 41.5ºS-55ºS. This coastal marine system is characterised by western winds, latitudinally modulated by the position of the South-Eats Pacific high-pressure centre, high precipitation rates and freshwater inflows from the numerous glaciers (including the largest ice cap out of Antarctic and Greenland). All of these forcings meet in a complex bathymetry and coastline system - deep fjords, shallow sills, narrow straits, channels, archipelagos, inlets, and isolated inner seas- driving an estuarine circulation (fast outflows westwards on surface and slow deeper inflows eastwards). Such a complex system is modelled on the numerical model MIKE3, upon whose 3D current fields particle-track-biological models (one for each infective agent) are decoupled. Each agent biology is parameterized by functions for maturation and mortality (reproduction not included). Such parameterizations are depending upon environmental factors, like temperature and salinity, so their lifespan will depend upon the environmental conditions those virtual agents encounter on their way while passively transported. CLIC (Connectivity-Langrangian–IFOP-Chile) is a service platform that supports the graphical visualization of the connectivity matrices calculated from the particle trajectories files resultant of the particle-track-biological models. On CLIC users can select, from a high-resolution grid (~1km), the areas the connectivity will be calculated between them. These areas can be barrios and macrozonas. Users also can select what nodes of these areas are allowed to release and scatter particles from, depth and frequency of the initial particle release, climatic scenario (winter/summer) and type of particle (ISAv, Piscirickettsia salmonis, Caligus rogercresseyi plus an option for lifeless particles). Results include probabilities downstream (where the particles go) and upstream (where the particles come from), particle age and vertical distribution, all of them aiming to understand how currently connectivity works to eventually propose a minimum risk zonation for aquaculture purpose. Preliminary results in Chiloe inner sea shows that the risk depends not only upon dynamic conditions but upon barrios location with respect to their neighbors.

Keywords: aquaculture zonation, Caligus rogercresseyi, Chilean Patagonia, coastal oceanography, connectivity, infectious salmon anemia virus, Piscirickettsia salmonis

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Authors: Charaia Vakhtang

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Global oil prices are seeing new bottoms every day. The prices have already collapsed beneath the psychological verge of 30 USD. This tendency would be fully acceptable for the Georgian consumers, but there is one detail: two our neighboring countries (one friendly and one hostile) largely depend on resources of these hydrocarbons. Namely, the ratio of Azerbaijan in Georgia’s total FDI inflows in 2014 marked 20%. The ratio reached 40% in the January to September 2015. Azerbaijan is Georgia’s leading exports market. Namely, in 2014 Georgia’s exports to Azerbaijan constituted 544 million USD, i.e. 19% in Georgia’s total experts. In the January to November period of 2015, the ratio exceeded 11%. Moreover, Azerbaijan is Georgia’s strategic partner country as part of many regional projects that are designated for long-term perspectives. For example, the Baku-Tbilisi-Karsi railroad, the Black Sea terminal, preferential gas tariffs for Georgia and so on. The Russian economic contribution to the Georgian economy is also considerable, despite the losses the Russian hostile policy has inflicted to our country. Namely, Georgian emigrants are mainly employed in the Russian Federation and this category of Georgian citizens transfers considerable funds to Georgia every year. These transfers account for about 1 billion USD and consequently, these funds previously equalized to total FDI inflows. Moreover, despite the difficulties in the Russian market, Russia still remains a leader in terms of money transfers to Georgia. According to the last reports, money transfers from Russia to Georgia slipped by 276 million USD in 2015 compared to 2014 (-39%). At the same time, the total money transfers to Georgia in 2015 marked 1.08 billion USD, down 25% from 1.44 billion USD in 2014. This signifies the contraction in money transfers is by ¾ dependent on the Russian factor (in this case, contraction in oil prices and the Russian Ruble devaluation directly make negative impact on money transfers to Georgia). As to other countries, it is interesting that money transfers have also slipped from Italy (to 109 million USD from 121 million USD). Nevertheless, the country’s ratio in total money transfers to Georgia has increased to 10% from 8%. Money transfers to Georgia have increased by 22% (+18 million USD) from the USA. Money transfers have halved from Greece to 117 million USD from 205 million USD. As to Turkey, money transfers to Georgia from Turkey have increased by 1% to 69 million USD. Moreover, the problems with the national currencies of Russia and Azerbaijan, along with the above-mentioned developments, outline unfavorable perspectives for the Georgian economy. The depreciation of the national currencies of Azerbaijan and Russia is expected to bring unfavorable results for the Georgian economy. Even more so, the statement released by the Russian Finance Ministry on expected default is in direct relation to the welfare of the whole region and these tendencies will make direct and indirect negative impacts on Georgia’s economic indicators. Amid the economic slowdown in Armenia, Turkey and Ukraine, Georgia should try to enhance economic ties with comparatively stronger and flexible economies such as EU and USA. In other case, the Georgian economy will enter serious turbulent zone. We should make maximum benefit from the EU association agreement. It should be noted that the Russian economy slowdown that causes both regretful and happy moods in Georgia, will make negative impact on the Georgian economy. The same forecasts are made in relation to Azerbaijan. However, Georgia has many partner countries. Enhancement and development of the economic relations with these countries may maximally alleviate negative impacts from the declining economies. First of all, the EU association agreement should be mentioned as a main source for Georgia’s economic stabilization. It is the Georgian government‘s responsibility to successfully fulfill the EU association agreement requirements. In any case the imports must be replaced by domestic products and the exports should be stimulated through government support programs. The Authorities should ensure drawing more foreign investments and money resources, accumulating more tourism revenues and reducing external debts, budget expenditures should be balanced and the National Bank should carry out strict monetary policy. Moreover, the Government should develop a long-term state economic policy and carry out this policy at various Ministries. It is also of crucial importance to carry out constitutive policy and promote perspective directions on the domestic level.

Keywords: oil prices, economic growth, foreign direct investments, international trade

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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