The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers novel insights into the causative mechanisms of ground fissures in the northern North China Plain, providing valuable scientific evidence for mitigating ground fissure disasters during the urbanization process in the region.

Telemedicine has been increasingly considered an effective strategy to support patients with several diagnosis and therapies, avoiding the on-site visit and drastically reducing the risks to share infections. In the recent years, a number of different technologies have been developed and applied to clinical studies, with the aim to investigate new ways for increase the early diagnoses and monitor the clinical evolution of the most predictable diseases directly from the patients’ home. Telemedicine refers to all those technological interfaces used to remotely perform clinical procedures. Telemedicine applications could be useful in several medical fields, such as preventive medicine, home patient care, education for healthcare professionals and patients, research, public health, and health management. On the other hand, the synergy of these different technologies has a significant impact on the clinical risks analysis, particularly useful in frail patients. Although Telemedicine shows to have important advantages, undoubtedly important issues still remain. The present work aims to shed light on the main advantages and disadvantages related to of each application’s features, which may serve as a useful tool for researchers.

The geographical environment, food culture, and dietary habits are substantially different between the southern and northern regions in China. We investigated the associations with dietary patterns and metabolic syndrome between Chinese adult from the southern and northern regions (North: 1249; South: 1849) using data from the Chinese Health and Nutrition 2009 survey. Respectively, four dietary patterns were identified by factor analysis in the two regions. Each dietary pattern of factor score was calculated for three groups by tertile (T1<T2<T3). In the northern region, the association between the Alcohol and Western pattern and the risk of abdominal obesity (OR: 1.31; 95%:1.01, 1.68), hypertriglyceridemia (OR: 1.35; 95%:1.05, 1.74), high fasting blood glucose (OR: 1.37; 95%: 1.05, 1.80), and hypertension (OR: 1.55; 95%: 1.45, 1.99) was increased. In the southern region, the Convenience Food pattern was positively associated with hypertriglyceridemia (OR: 1.53; 95%: 1.03, 2.26), low HDL-cholesterol (OR: 1.96; 95%: 1.12, 3.43), and metabolic syndrome (OR: 1.79; 95%: 1.03, 3.11). The Alcohol dietary pattern was positively associated with high fasting blood glucose (OR: 1.83, 95%: 1.13, 2.97). There are some dietary pattern differences in the two regions. It is necessary to consider the factors of food culture and food intake habits in order to provide nutrition education to Chinese individuals from different regions in the future.

This article examines the integration of artificial intelligence (AI) and robotic process automation (RPA) in financial accounting and management, underscoring their role in driving the digital transformation of corporate finance. It discusses the shortcomings of traditional financial processes and highlights the potential of AI and RPA technologies to enhance efficiency, accuracy, and cost-effectiveness. The paper also explores the limitations of RPA, such as its challenges in processing unstructured data and handling complex decision-making scenarios. Looking forward, it considers the future trends in AI and RPA, emphasizing the benefits of cloud technology in scaling automated systems and addressing associated challenges.

Considering characteristics of high river density, special underlying surface in plain river network region, and municipal drainage system function, river network drainage unit model is proposed, which is defined as a region surrounded by main river or embankment. Flood storage variety and control projects regulation of small rivers in each unit is simulated. With drainage catchment as an object, according to its drainage capacity, simplified municipal drainage model was developed. Coupling river network drainage unit model, simplified municipal drainage model and 2D flood routing model, urban flood analysis model for plain tidal river network region was developed, which could be applied to analyzing flood from upstream river, storm surge and local rainfall. Demonstration research was carried out in Puxi flood protected area in Shanghai.

Local food has continued to become more popular in both the home and as featured ingredients in all segments of food service. Numerous studies have explored the motivating factors for consumer purchasing motivators. However, no known study has explored if there is a correlation between ego and intent to buy local foods. This study adopted a modified version of the Theory of Trying and surveyed a sample of 237 food service buying agents in South Carolina to examine their perceptions of buying local. Results suggest that ego is a predictor of trying to purchase local foods for restaurants. It was also found that the modified model is an acceptable model for predicting buyer intent. These findings support the majority of the studies looking at ego-centric behaviors with green purchases and could potentially help local food suppliers to better market their products to foodservice establishments. This study could also act as the foundation for future studies to explore the full extent of ego’s motivational effect on purchasing intentions in the food service industry.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

Laser-Powder Directed Energy Deposition (DED-LB/Powder) is an additive manufacturing process that is gaining popularity in the manufacturing industry due to its numerous advantages, particularly in repairing operations. However, its application is often limited to case studies due to some critical issues that need to be addressed, such as the degree of internal porosity. This paper investigates the effect of the most relevant process parameters of the DED-LB/Powder process on the level and distribution of porosity. Results indicate that, among the process parameters examined, porosity is less affected by travel speed and more influenced by powder mass flow rate and laser power. Additionally, a three-dimensional finite element transient model was introduced, which was able to predict the development and location of lack-of-fusion pores along the building direction.

The Estimation of systemic risk in India is still in its infancy stage. There are several methods which are available but none of the methods are fully compatible to forecast the systemic risk since under different circumstances the factors responsible for the risk differs. In this paper the systemic risk estimation in India being carried out based on spread in daily stock market price(Difference between the bid and ask price of a share) of the top 100 firms in India according to market capitalization for the period of July2007 to March 2016. The results were compared with the Financial Stability Report published by Reserve Bank Of India for the period of March 2010 to June 2016.The results clearly indicates that there exits relationship between market illiquidity represented by spread and risks associated with the Financial System. In most of the cases the Z score (deviation from the mean/Standard Deviation) of the spread has become negative which provides the spread which is farther from the mean, also a good indicator of volatility in market and risk to financial system. It is also seen that the Systemic Risk Survey conducted by Reserve Bank of India which started during October 2011 has supported the results.

Background/Objectives: Vitamin B12 deficiency can cause variable symptoms, which may be irreversible if not diagnosed and treated in a timely manner. We aimed to develop a widely accepted expert consensus to guide the practice of diagnosing and treating B12 deficiency. Methods: We conducted a scoping review of the literature published in PubMed since January 2003. Data were used to design a two-round Delphi survey to study the level of consensus among 42 experts. Results: The panelists agreed on the need for educational and organizational changes in the current medical practices for diagnosing and treating B12 deficiency. Recognition of clinical symptoms should receive the highest priority in establishing the diagnosis. There is agreement that the serum B12 concentration is useful as a screening marker, whereas methylmalonic acid or homocysteine can support the diagnosis. Patient lifestyle, disease history and medications can provide clues to the cause of B12 deficiency. Regardless of the cause of the deficiency, initial treatment with parenteral B12 was regarded as the first choice for patients with acute and severe manifestations of B12 deficiency. The use of high-dose oral B12 at different frequencies may be considered for long-term treatment. Prophylactic B12 supplementation should be considered for specific high-risk groups. Conclusions: There is a consensus that clinical symptoms need to receive more attention in establishing a diagnosis. B12 laboratory markers can support the diagnosis. The severity of clinical symptoms, the causes of B12 deficiency and the treatment goals govern decisions regarding the route and dose of B12 therapy.

In the construction business, which is known for its intricate and strategic nature, it is crucial to have efficient risk management in place. This is because various internal and external elements can cause disruptions to projects. Although the industry has had a historically negative reputation for risk analysis, the methodical process of identifying, analyzing, and managing risks has been more widely recognized and respected. This paper examines the historical progression of construction risk management, highlighting the need to identify and classify risks promptly. The study examines various risk factors related to finance, law, environment, and logistics. The study explores various risk management strategies, such as contract management, risk distribution, evaluation, mitigation, and sharing. The article discusses the significant impact of risk management software, such as Procore, PlanGrid, e-Builder, Autodesk BIM 360, and Oracle Primavera, on improving project results. The study finishes by highlighting the importance of proactive risk management in protecting against financial losses and maintaining a reputation in the construction business.

The Internet-of-Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state-of-the-art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

Despite energy-related financial concerns and the growing demand for sustainability, many energy efficiency measures are not being implemented in industrial practice. There are a number of reasons for this, including a lack of knowledge about energy efficiency potentials and the assessment of energy savings as well as the high workloads of employees. This article describes the systematic development of an expert system, which offers a chance to overcome these obstacles and contribute significantly to increasing the energy efficiency of production machines. The system employs data-driven regression models to identify inefficient parameter settings, calculate achievable energy savings, and prioritize actions based on a fuzzy rule base. Proposed measures are first applied to an analytical real-time simulation model of a production machine to verify that constraints required for the specified product quality are met. This provides the machine operator with the expert means to apply proposed energy efficiency measures to the physical entity. We demonstrate the development and application of the system for a throughput parts cleaning machine in the metalworking industry.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

Splines and quasi-interpolation operators are important both in approximation theory and applications. In this paper, we construct a family of quasi-interpolation operators for the bivariate quintic spline spaces S₅³ (∆_mn⁽²⁾). Moreover, the properties of the proposed quasi-interpolation operators are studied, as well as its applications for solving two-dimensional Burgers’ equation and image reconstruction. Some numerical examples show that these methods, which are easy to implement, provide accurate results.

The Great Reset has been presented by the World Economic Forum (WEF) in response to the COVID-19 pandemic in 2022 as a model through which a “stakeholder economy” would achieve “resilient, equitable and sustainable” economic, social and environmental goals. A more equitable distribution of resources, better working conditions, and ecological transitions are included in a social, economic and environmental reform agenda. This article raises the question of whether the Great Reset project should be interpreted as a “realistic utopia” and what is its reform potential. In an attempt to answer the question of whether the Great Reset as a realist utopia is consistent with the current state of science and philosophy, the article re-examines the idea of utopia in the light of recent philosophical and scientific approaches, such as critical realism in philosophy, so-cial systems theory in sociology and complexity theory in science. A comparative conceptual analysis is carried out and discussed introducing the idea of a realist utopia in Rawls' theory of justice as fairness. In the final discussion, some doubts are raised about the logical coherence, rigor of scientific theorizing, policy prescriptions, and predictive potential of the Great Reset emerging paradigm. It is concluded that utopian projects of radical reform can become realistic when they offer explanations of the deep structural changes that underlie social and economic evolution, drawing from these explanations the policy implications and prescription that can support struc-tural changes, rather than from assumed long-term effects of exogenous shocks or “black swan” events such as the COVID-19 pandemic.

This comparative study aims to investigate environmental awareness, knowledge, and safety among students in Montenegro and North Macedonia, considering the unique socio-cultural and environmental contexts of both countries. A mixed-methods approach involving surveys and interviews was employed to gather data from students in educational institutions across Montenegro and North Macedonia. The study assessed various factors, including students' awareness of environmental issues, their perceived level of knowledge, and their attitudes towards safety measures. A comprehensive series of 400 face-to-face interviews was carried out and these interviews encompassed 200 students from Montenegro and an equal number from North Macedonia, taking place at two esteemed academic institutions: The University of Montenegro in Podgorica and The University of St. Clement of Ohrid, Bitola, Republic of North Macedonia. Our hypothetical conceptual framework proposes that a combination of variables, including gender (H1), age (H2), year of study (H3), and rate of study (H4), significantly influences the attitudes of students from Montenegro and North Macedonia towards environmental awareness, safety, and knowledge. Research findings indicate significant variations in environmental awareness and knowledge perception among students in the two countries. While both Montenegro and North Macedonia face environmental challenges, differences in educational systems and socio-economic factors contribute to distinct attitudes and behaviors towards environmental issues and safety practices. This study sheds light on the importance of understanding regional differences in environmental awareness and knowledge perception among students. By identifying areas of strength and areas needing improvement, policymakers and educators can develop targeted interventions to enhance environmental education and foster a culture of sustainability in both Montenegro and North Macedonia.

The G-protein-coupled estrogen receptor (GPER; G protein-coupled estrogen receptor 30, also known as GPR30) is a novel estrogen receptor and has emerged as a promising target for ovarian cancer. GPER, a seven-transmembrane receptor, suppresses cellular viability and migration in studied ovarian cancer cells. However, its impact on the fallopian tube, which is the potential origin of high-grade serous (HGSC) ovarian cancer, has not been addressed. This study was conducted to evaluate the relationship of GPER, ovarian cancer subtypes, i.e., high-grade serous cell lines (OV90 and OVCAR420), as well as potential HGSC ovarian cancer origin (i.e., the fallopian tube cell line FT190). The selective ligand assessed here is the agonist G-1, which was utilized in an in vitro study to characterize its effects on cellular viability and migration. As a result, this study has addressed the effect of a specific GPER antagonist in combination with an agonist on cell viability, providing a better understanding of the effects of these compounds on our diverse group of studied cell lines. Strikingly, attenuated cell proliferation and migration behaviors were observed in the presence of G-1. Thus, our in vitro study reveals the impact of the origin of HGSC ovarian cancers and highlights the GPER agonist G-1 as a potential therapy for ovarian cancer.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. Validated through extensive offline experiments and online deployments, the model significantly outperforms existing optimal benchmark methods on real datasets, improving the location deviation squared metrics and the top-three location prediction accuracy metrics. These research results provide important support to further promote the intelligent development of the logistics industry.

The strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a Lean Learning Factory was developed in the Pitesti University Center, which allows students to learn, experiment, and research, in an environment similar to that of enterprises, the new Lean Manufacturing methods and techniques, and Industry 4.0. The research presented in this study had as its objective identifying the minimum number of repetitions necessary to train operators who serve two differently organized workstations, one classic, the other including digital techniques, but on which the same assembly operation is performed. Several indicators were considered in the analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a Lean manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

Chronic stress, culminating in burnout, evolves gradually and is notoriously difficult to detect due to vague symptoms and individuals' hesitance to acknowledge their struggles. To expedite the identification and recognition of this condition, enabling timely psychological intervention, the integration of Artificial Intelligence (AI) is increasingly considered. This research does not assert the feasibility of an AI system managing all aspects of chronic stress's impact. However, it highlights the capability of current technology to detect stress indicators based on quantifiable data like Heart Rate (HR) and organizational climate dimensions. Although other physiological markers such as oximetry, skin galvanic response, and EKG have been explored, they have not shown reliable differentiation between stress and joy. Focused on the unique context of school principals in the Bedouin regions of Israel, this study investigates the interplay between HR, organizational climate, and stress levels. It introduces a novel application of a fuzzy logic tool that combines HR and organizational climate metrics to aid in stress diagnosis. This tool incorporates the psychologist's expertise to provide real-time data crucial for developing effective coping strategies. While the AI-supported fuzzy system does not replace professional psychological intervention, it significantly enhances the speed of condition identification and intervention planning, thus shortening the response time to stress-related issues in educational leadership within culturally specific settings. The application of such AI-driven tools is pivotal for sustaining the well-being and effectiveness of educational leaders, thereby supporting the broader goal of educational sustainability.

In the drive towards environmental restoration and sustainable energy solutions, effective utilization and management of agricultural crop residues are vital to mitigate greenhouse gas (GHG) emissions and waste accumulation. Converting biogenic wastes into biofuels and bioproducts has the potential to tackle the energy crisis and contribute to environmental remediation. In this investigation, teff husk, primarily generated in Ethiopia during teff production within the agro-industrial sector, is used as the feedstock for the slow pyrolysis process. In Ethiopia, it is estimated that over 1.75 million tons of teff husk are generated annually, with a significant portion being incinerated in the fields, resulting in substantial environmental pollution. This study focuses on assessing teff husk as a potential material for slow pyrolysis, a crucial stage in biochar production, to tap into its biochar-producing potential. To determine the composition of the biomass, the teff-husk was initially analyzed by thermogravimetry. The significant presence of fixed carbon indicates that teff husk is a viable candidate for pyrolytic conversion into biochar particles. The process of slow pyrolysis took place at three varied temperatures—specifically, at 400, 450, and 500 °C. Process parameters of slow pyrolysis such as reaction time, temperature, and heating rate were enhanced to obtain maximum biochar yields. The highest biochar yield of 43.4 wt% was recorded at optimized reaction time, temperature, and heating rate of 120 min, 400 °C, and 4.2 °C/min, respectively. Furthermore, biochar's physicochemical, SEM-EDX, FTIR, and TGA characterization were performed. The thermal stability and carbon content of biochar were found to rise at higher temperatures. Unlike fuel recovery, the results suggest that teff-husk can be used as a feedstock for biochar production.

Biodiversity has become an issue of global anxiety over the past decades due to its rapid decline worldwide. Bangladesh as one of the most densely populated countries in the world is no more exception. The country, although, was once very rich in biodiversity, during the last few decades as a consequence of the rapid reduction in forest area, urbanisation, habitat modification, unsustainable natural resources use and collection and overall climate change it has decreased alarmingly. Of late, the government, as a signatory of various regional and international conservation treaties, has taken various initiatives to improve country’s dwindling biodiversity. This paper reviews the present situation of biodiversity in Bangladesh, management trends and major causes of biodiversity loss. A separate statutory body is fundamental to ensure conservation, sustainable use and equitable sharing of benefits arisen from biodiversity in the country.

The effects of climate change health impacts on urban health care systems and vulnerable populations are a researched topic with foundations on urban risk management, urban health methodologies, and sustainable urbanization. As climate change is a dynamic and transformative global issue the gap between adaptation and mitigation efforts and urban planning relies, among other things, in the limitations of previous studies of risk management structures tailored to the existing strategy to calculate the uncertainties and predict their influence on urban systems and subsystems. Moreover, as climate and health is a well-researched issue, it is also complex as the methodologies and strategic approach to minimize health risks of climate change is intrinsically contingent to risk methodologies and policy-making processes that are efficient with support of knowledge-based information. This paper emphasis the need for focusing on urban health risk management methods that serves to identify potential opportunities, and then manage and take action to prevent adverse health effects. It also emphasizes the probability of events and their consequences, which are measurable both qualitatively and quantitatively.

Motivated by empirical observations, we propose a possible extension of Gibrat's law. By applying it into the random growth theory of income distribution (Gabaix, 2009), we find that the income distribution is described by a generalized Pareto-type distribution (GPD) with three parameters. We observe that there is a parameter /elta in the GPD that plays a key role in determining the shape of income distribution. By using the Kolmogorov-Smirnov test, we empirically show that, for typical market-economy countries, /elta is close to 0 significantly, such that the income distribution is characterized by a two-class pattern in which the bottom 90% of the population is approximated by an exponential distribution and the richest 1%~3% is approximated by an asymptotic power law. However, we empirically find that, for China both in planned economy period and in early stages of market reformation (from 1978 to 1990), /elta is significantly deviated from 0, such that the bottom of the population no longer conforms to an exponential distribution.

Electricity price forecasting has become a crucial element for both private and public decision-making. This importance has been growing since the wave of deregulation and liberalization of energy sector worldwide late 1990s. Given these facts, this paper tries to come up with a precise and flexible forecasting model for the wholesale electricity price for the Italian power market on an hourly basis. We utilize artificial intelligence models such as neural networks and bagged regression trees that are rarely used to forecast electricity prices. After model calibration, our final model is bagged regression trees with exogenous variables. The selected model outperformed neural network and bagged regression with single price used in this paper, it also outperformed other statistical and non-statistical models used in other studies. We also confirm some theoretical specifications of the model. As a policy implication, this model might be used by energy traders, transmission system operators and energy regulators for an enhanced decision-making process.

The innovativeness of nongovernmental organisations, the basic institutions of civil society, is conditioned, among other things, by the endogenous potential of agency of the entities operating within them. The article attempts to answer two research questions regarding the above-mentioned issues: (1) how individual components of binding and bridging social capital (in the area of trust, norms and connections) determine innovative activity in a state of morphostasis, i.e. structural and cultural continuity, selected Silesian NGOs. (2) What type of reflexivity and the related nature of agency of the members of the NGOs surveyed dominates when undertaking innovative activities? At the theoretical level, the study was based on the concept of three components of social capital by James S. Coleman and the assumptions of Margaret Archer's morphogenetic theory of structure and agency, in particular, the types of reflexivity as a factor conditioning social agency. Based on them and using qualitative analysis of data obtained during focus group interviews (FGI) and SWOT questionnaires of surveyed organisations, a diagnosis of intraorganisational barriers to innovation was made. The Atlas.ti computer programme was used. This method allows for the examination of structural elements, cultural features of a given organisation, and the capabilities of individual entities. The dominance of bonding social capital components over bridging social capital components was noted (mainly in the dimension of trust), as the basic bond connecting members of the NGOs studied. It was accompanied by a communicative type of reflexivity of the respondents, with the aim of maintaining the existing organisational and social status quo. These key socio-cultural factors determine the morphostatic nature of the organisations studied, i.e., their focus on maintaining the organisational status quo. Such contexts petrify the existing power structure, but also the level of social tensions and distances, and limit the innovation potential.

In recent years, the scientific and technological developments led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative parts of the video content. The user’s personal preferences, often involved in the expected results, should be taken into account in the video summaries. In this paper, we provide the first comprehensive survey on personalized video summarization relevant to the techniques and datasets used. In this context, we classify and review personalized video summary techniques based on the type of personalized summary, on criteria, on the video domain, on the source of information, on the time of summarization, and on the machine learning technique. Depending on the type of methodology used by the personalized video summarization techniques for the summary production process, we classify the techniques into five major categories, which are feature-based video summarization, key frame selection, shot selection-based approach, video summarization using trajectory analysis, and personalized video summarization using clustering. We also compare personalized video summarization methods and present 37 datasets used to evaluate personalized video summarization methods. Finally, we analyze opportunities and challenges in the field and suggest innovative research lines.

We propose a novel unsupervised semantic segmentation method for fast and accurate flood area detection utilizing color images acquired from Unmanned Aerial Vehicles (UAVs). To the best of our knowledge, this is the first fully unsupervised method for flood area segmentation in color images captured by UAVs, without the need of pre-disaster images. The proposed framework addresses the problem of flood segmentation based on parameter-free calculated masks and unsupervised image analysis techniques. First, a fully unsupervised algorithm gradually excludes areas classified as non-flood utilizing calculated masks over each component of the LAB colorspace, as well an RGB vegetation index and the detected edges of the original image. Unsupervised image analysis techniques, such as distance transform, are then applied, producing a probability map for the location of flooded areas. Finally, flood detection is obtained by applying the hysteresis thresholding segmentation. The proposed method is tested and compared with variations, and other supervised methods in two public datasets, consisting of 953 color images in total, yielding high-performance results, with 87.4% and 80.9% overall accuracy and F1-Score, respectively. The results and computational efficiency of the proposed method show that it is suitable for on board data execution and decision-making during UAVs flight.

The Circular Bioeconomy (CBE) combines the concepts of bioeconomy and circular economy. As an alternative concept to the current fossil-based, linear economy, it de-scribes an economy based on the efficient valorization of biomass. It is regional in nature and aims to improve sustainability. An analysis of the transition process, by identifying its success criteria and assessing its impacts through the modelling of technology-specific scenarios is necessary to ensure that CBE concepts are sustainable. However, a compre-hensive consideration of regional influences on both is lacking. Based on extensive literature research and an expert survey, we (i) present a compre-hensive catalog of CBE success criteria and discuss their region-specific character and (ii) develop a methodology based on evaluation matrices that enable to match CBE technolo-gies with regions. The matrices support the evaluation of technological and regional characteristics influencing the successful CBE implementation. The results show that the success criteria "biomass resources", "technological", and "social" are perceived as highly important, and that most of the success criteria are both region- and technology-specific, highlighting the relevance of developing matrices to match them. We describe such matrices indicatively for the two broadest and most im-portant success criteria clusters “social acceptance” and “biomass supply chain”. With this, we substantiate the regional nature of CBE and raise the awareness on the importance of considering regional conditions in CBE transition processes. Furthermore, we provide practical guidance on how regional conditions can be reflected in the selection of technologies, e.g. in regional CBE technology scenarios.

The digital revolution has significantly impacted many Chinese Time-Honored businesses, particularly those slow to adapt to environmental changes, resulting in challenges related to long-term marketing capabilities and declining performance. This study explores the relationship between ambidextrous marketing capabilities and corporate performance. Utilizing a survey involving 91.8% of middle and upper-level managers across 47 Chinese time-honored firms, we construct a research model that demonstrates how the application of ambidextrous marketing capabilities can foster the development of Sustainable marketing capability, which in turn positively influence corporate performance. Sustainable marketing capability mediate the effect of ambidextrous marketing capabilities on corporate performance. Additionally, enhancements in market conditions or legislation may further amplify the impact of Sustainable marketing capability on business performance. In the context of Chinese time-honored firms, these findings offer managerial insights into building Sustainable marketing capability, enhancing performance, and achieving competitive advantages.

Iron is an essential nutrient for humans and microbes, such as bacteria. Iron deficiency occurs commonly in critically ill patients, but iron replacement therapy is not considered during the acute phase of critical illness, since it increases iron availability for invading microbes and oxidative stress. However, persistent iron deficiency in the recovery phase is harmful with potential adverse outcomes such as cognitive dysfunction, fatigue and cardiopulmonary dysfunction. Therefore, it is important to treat iron deficiency timely and efficiently. This article reviews current knowledge about iron-related biomarkers in critically ill patients and provides possible criteria to guide decision-making for iron supplementation in the recovery phase of critical illness.

Abstract: NFinFET transistors with fin channel length 90nm and a planar MOSFET transistor with channel length 180nm and 90nm are presented with characteristic curves at various gate biases. A finalized algorithm with kink effects is effectively responsible for addressing the field effect transistors. The algorithm includes the modified conventional current-voltage formula and a nonlinear heat-associated kink solution which is simplified as a Gaussian form. Three parameters in modified model includes kN (related with channel width, channel length, and gate oxide capacitor, and proportional to the mobility of carriers)Vth(Threshold Voltage), and (the inverse of Early Voltage). Those parameters are determined to minimize the discrepancies between the measured data and the fitting values, but leave kinks located at around (VGS－Vth), which are deliberately eliminated by the Gaussian form because of the agitation of thermal kink effects. The whole fitting is made to be as close as the as-measured IDS-VDS. In the mean time, those determined parameters are physically meaningful after the analysis has been done.

In the Republic of Serbia, no comprehensive scientific multimethod research has been conducted to identify weaknesses and opportunities for improving the disaster risk management system. Regarding that, in the paper, author presents project description ,,Strengthening Integrated Disaster Risk Management System in Serbia - DISARIMES” which shall enable strengthening the disaster risk management system through research, development and innovative solutions implementation in the preparation, mitigation, response, remediation and post-disaster phases. The scientific importance of the projected research is reflected in the creation of assumptions for the advancement of theoretical and empirical knowledge in the scientific field of disaster risk management, bearing in mind that it is a relatively young scientific discipline in Serbia. The results of the project research will make it easier for decision makers in Serbia to understand the shortcomings of the system, but also provide innovative opportunities to improve their functioning in conditions of increasingly frequent and serious disasters. Establishing a scientific and professional society in the field of disaster risk management will create sustainable and necessary conditions for the transfer and improvement of knowledge and experience of importance for raising the level of operability of the system of protection and rescue of the Republic of Serbia in the event of disasters. A key contribution of the research findings will be to create a sustainable knowledge base that will be supported by the relevant amount of information regarding innovative capabilities and solutions identified as necessary to raise social resilience to a much higher level. In order to achieve the set goals, DISARIMES makes it possible, through a large number of SWOT analyses and other multimethod studies, to clearly identify and systematize the objective deficiencies and barriers encountered by the disaster risk management system in Serbia in all its stages before, during and after disasters, to identify and implement the appropriate solutions based on this. The objectives of the project are: to assess and identify strengths (advantages), weaknesses (disadvantages), opportunities (innovation potential) and threats for the disaster risk management system in Serbia; to develop and update RDI (research, development, innovation) Roadmap – knowledge databases with innovative solutions and other relevant information for improvement of the disaster risk management system; to fully deploy the DISARIMES scientific-professional network involving a broad range of the disaster risk management scientists and civil protection professions and organisations; to prepare the ground for the disaster risk management policy innovations.

This paper proposes a concise literature review aimed at identifying the current body of knowledge on the adoption of Social Networks in Crisis Management. The major input is a structured research question based on the initial reading around the topic. Before the recent pan-demic, most literature has focused on local crises, with a relatively low number of exceptions. Additionally, self-organizing system are spontaneous established between people who are af-fected by a crisis. Among the identified challenges, there is the need to integrate official commu-nication by emergency agencies with citizen-generated contents in a contest of credibility and trustworthiness. In certain cases, it has been reported a lack of specific competence, knowledge, and expertise, as well as a lack of sufficient policies and guidelines in the use of Social Networks. Those challenges need to be framed by considering the classic difficulties to provide timely and accurate information, to deal with fake news, unverified or misleading information, and infor-mation overload. Bridging major gaps though advanced analytics and AI-based technology is expected to provide a key contribution to establish and safely enable in practice an effective and efficient communication, to contrast dissonant mental models, which are often fostered by Social Networks, and to enable a shared situational awareness.

The present study seeks to assess the Brand Equity in the network of new fashion designers in the Canary Islands. To this end, we have adapted the Brand Equity model to an online context and proposed a set of metrics for four dimensions: estimate, relevance, awareness, and differen-tiation. The multidimensional approach to online Brand Equity was employed to measure the online Brand Equity of 129 fashion designers from the Canary Islands. The study's findings re-vealed that the number of social media profiles significantly impacts brand awareness and dif-ferentiation. Moreover, the digital maturity level influences brand relevance and overall Brand Equity . Our study highlights the practical value of web data-driven metrics for measuring online Brand Equity , which can be utilised for diagnostic, evaluative, or predictive purposes. The study's outcomes have substantial implications for marketers in the fashion industry aimed at improving online Brand Equity

The main objective of this study was to compare the removal efficiency of nutrients using Lactuca sativa, Medicago sativa and Phragmites australis in subsurface flow constructed wetlands with horizontal flow. In order to test water quality, fabricated reactors designed and the plants cultivated in the soil while their root were inside the wastewater. A long time study carried out from spring till end of autumn (9 months) in order to evaluate the difference in removal rate based on the seasonal changes. The highest removal rate was during summer which followed by spring and autumn. Thus, the effect of plants on the removal efficiency of organic matter (COD, BOD), TSS and nutrient (P and TN) appeared to be dependent on the seasonal growth. Phragmites australis the most sensitive species in order the removal of nutrient from wastewater.

The use of haptic devices in rehabilitation of impaired limbs has become rather popular, given the proven effectiveness in promoting recovery. In a standard framework, such devices are used in rehabilitation centers, where patients interact with virtual tasks, presented on a screen. To track their sessions, kinematic/dynamic parameters or performance scores are recorded. However, as Internet access is now available at almost every home, and in order to reduce the hospitalization time of the patient, the idea of doing rehabilitation at home is gaining wide consent. Medical care programs can be synchronized with the home rehabilitation device; patient data can be sent to the central server that could redirect to the therapist laptop (tele-healthcare). The controversial issue is that the recorded data do not actually represent the clinical conditions of the patients according to the medical assessment scales, forcing them to frequently undergo clinical tests at the hospital. To respond to this demand, we propose the use of a bilateral master/slave haptic system that could allow the clinician, who interacts with the master, to assess remotely and in real time the clinical conditions of the patient that uses the home rehabilitation device as the slave. In this paper, we describe a proof of concept to highlight the main issues of such an application, limited to one degree of freedom, and to the measure of the stiffness and range of motion of the hand.

This paper represents the first investigation into the consensus problem of linear time-varying multi-agent systems utilizing an event-triggered communication scheme. First, a general event-triggered consensus control scheme is proposed for a general category of linear time-varying multi-agent systems. Under some suitable assumptions, it is demonstrated that all agents’ states will converge exponentially, with Zeno behaviour being ruled out. Second, the consensus problem in a network of linear time-varying multi-agent systems with a spanning tree is investigated using the proposed control strategy. It demonstrates that the consensus issue for the specified system can be reformulated as a stabilization problem for an error system through a time-varying linear transformation. Then, the event-triggered consensus problem is just a special instance of the general event-triggered consensus problem mentioned above. Finally, to illustrate the efficacy of the event-triggered method proposed in this study, simulation results are shown.

The economic, social and environmental benefits generated by the use of urban public transportation infrastructure constitute a complex dynamic urban public transportation infrastructure utilization benefit system. This paper evaluates the coupling coordination among these three benefits taking four Chinese autonomous municipalities as an example. These four cities have large-scale urban public transportation infrastructures but their utilization has many serious problems. The basic function of urban public transportation infrastructure has not been fully played in these cities. Whether the different benefits of urban public transportation infrastructure have been developed in harmony or not is unclear. We analyzed the coordinated development among three benefits by constructing coupling coordination degree model and used Gini coefficient to study the difference of coordinated development among three benefits of four cities. The result shows that the levels of coordinated development among three benefits of urban public transportation infrastructure were lower in these four cities and have positive correlation with it of urban public transportation infrastructure utilization benefit. Raising the level of urban public transportation infrastructure utilization benefit is the most crucial solution of promoting the coordinated development among three benefits.

The concept of a Social License to Operate (SLO) has become increasingly important in the sustainability literature in recent years. Having its origins in the business discourse of the mining industry with respect to limiting opposition to mining projects, the notion of a social contract above and beyond legal requirements has since become applied across a number of different industries. Despite the concepts adoption confusion exists over the practices and outcomes of SLO, and particularly the nature of engagement. Given this situation it is surprising that not more attention to the role of marketing, and social marketing in particular, in operationalizing the concept. The paper discusses the potential of social marketing to contribute to SLO. Economic, political and social relations are complex in SLO and exchange is intricate in such relational environments. A community-based social marketing orientation is proposed as a means to improve exchange relations and enhance engagement. Seven models of SLO related social marketing models are discussed with community-based social marketing and adaptive co-marketing models being regarded as the most positive for the achievement of an SLO. Potential barriers to adoption of these approaches are noted.

The purpose of this study is to analyze the causes of cost variation in natural disaster prevention projects (NDPP) in Gyeongsangbuk-do and to develop effective cost and risk management strategies. The study collected data by conducting an online survey of 244 stakeholders. Binary logistic regression was used to analyze the impact of various variables on cost deviation, in-cluding project management risk (PMR), project costing and execution risk (PCER), project exe-cution strategy risk (PESR), construction project risk (CPR), project cost and schedule risk (PCSR), project management challenges (PMC), and construction project subcontractor and safety man-agement (CPSSM). The results showed that PMR (OR=3.744, 95% C.I. [1.657, 8.457]), PCER (OR=5.068, 95% C.I. [2.236, 11.484]), PESR (OR=3.447, 95% C.I. [1. 853, 6.413]), CPR (OR=2.292, 95% C.I. [1.020, 5.151]), PCSR (OR=4.817, 95% C.I. [2.250, 10.317]), PMC (OR=2.954, 95% C.I. [1.452, 6. 013]), and CPSSM (OR=2.419, 95% C.I. [1.297, 4.515]) had statistically significant effects on cost deviation. In particular, PMR, PCER, and PESR were identified as the main causes, and the effects of additional factors such as CPSSM were also important. The developed predictive model plays an important role in helping stakeholders of NDPP to manage risks in advance and take appro-priate preventive measures to ensure the success of the project. This study empirically supports the theoretical hypotheses of previous studies and provides a clear understanding of the causes of cost deviation in NDPP, which provides important insights for strategic decision-making and provides a new perspective on risk management.

To proactively manage information security, enterprises often employ information security risk assessment techniques. Asset value - which is used to calculate the financial impact of possible threats - is one of the key parameters of information security risk. However, assets in a system are rarely independent, and their values are typically interdependent. Asset owners and IT teams may hold different views as regards these values, and there is thus the need to reduce subjectivity in a qualitative risk assessment. The research entails the development of a conceptual framework derived from the literature to minimize subjectivity, and the design of a system based on those concepts. The study uses the Unified Modeling Language as a design tool and puts forward an object-oriented model for defining asset values, in which the relationships between assets, vulnerabilities and related threats are identified. A “segregation of duties” approach is integrated into the risk management system to mitigate against subjectivity and better determine asset values. Survey responses from 16 practitioners working in the private and public sectors confirm the validity of the approach, but suggest it may be more workable in larger organisations where resources allow dedicated risk professionals to operate.

This essay review explores the concept of climate-smart forestry as an approach to mitigating and adapting to climate change. It highlights the need for a holistic approach to forestry that considers regional differences and synergies between ecosystem services. The essay discusses various management strategies at different scales, including species selection, mixed species cultivation, and the promotion of the bioeconomy. It also examines the trade-offs and synergies between different forest uses and the effects of forest management on ecosystem services. Furthermore, the review addresses major abiotic and biotic damage risks to forests, such as wildfires, windstorms, and bark beetle attacks, and proposes risk management strategies. Lastly, the review delves into the management of peatland forests, discussing the role of drainage, the impact of ditch network maintenance, and the challenges of peat ash fertilization. Overall, the review provides valuable insights into climate-smart forestry and its potential to contribute to climate change mitigation and adaptation.

The production of recombinant proteins in Escherichia coli is often challenged by cytoplasmic expression due to proteolytic degradation and inclusion body formation. Extracellular expression can overcome these problems by simplifying downstream processing and improving protein yields. This study aims to compare the efficiency of two Bacillus subtilis chitosanase signal peptides in mediating extracellular secretion in E. coli. We identified a naturally occurring mutant signal peptide (mCsn2-SP) from B. subtilis CH2 chitosanase (CH2CSN), which is characterized by a deletion of six amino acids in the N-region relative to the signal peptide (Csn1-SP) from B. subtilis CH1 chitosanase (CH1CSN). The CH1CSN and CH2CSN genes were cloned into the pET-11a vector and protein secretion was evaluated in E. coli BL21(DE3) host cells. Expression was induced with 0.1 mM and 1 mM IPTG at 30°C for one and three days. CH2CSN showed higher secretion levels compared to CH1CSN under all experimental conditions, especially with 0.1 mM IPTG induction for 3 days, which resulted in a 2.37-fold increase in secretion. These results suggest that signal peptide deletion variants may have an effect on protein secretion efficiency and help to further understand the function of signal peptides.

This research investigates the alignment of soft power and institutional skills in Montenegro's journey towards accession to the European Union (EU), with a particular focus on the environmental sector. An online survey targeting individuals employed in state institutions directly engaged in negotiation processes, notably the Ministry of Sustainable Development and Tourism and the Agency for Nature and Environmental Protection, was conducted. The research conducted an online survey, distributed before and after the summer recess to accommodate the transition of power following parliamentary elections, aimed at assessing the effectiveness of current personnel and identifying areas for improvement in staffing and negotiation strategies within Montenegro's environmental sector. Employing diverse methodologies, the survey's analysis delved into the demographic, social, and professional backgrounds of respondents. It explored their roles within institutions, involvement in environmental negotiations, and possession of relevant skills and expertise. Furthermore, respondents' knowledge of environmental issues, legislation, and challenges facing the country was assessed to gauge institutional capacity for environmental governance. Demographic data, including gender, age, education and regional origin, were collected to understand gender-specific attitudes and regional disparities in environmental perspectives. The sample of 84 individuals, comprising executives and employees from both institutions, provided insights into the age structure and regional diversity of personnel involved in negotiation tasks for Chapter 27. The selection of the Ministry of Sustainable Development and Tourism and the Agency for Nature and Environmental Protection reflects their pivotal roles in shaping Montenegro's environmental policies and addressing climate change challenges. This study aims to illuminate the dynamics of environmental governance within Montenegro's state administration, contributing to the country's path towards EU accession. The research findings highlight the critical need for Montenegro to prioritize strategic initiatives in personnel management, skill development, and institutional capacity-building within its environmental sector. The implications of this research extend beyond academia to inform policymaking and societal action, emphasizing the urgency for Montenegro to bolster its environmental sector capabilities, fostering both EU alignment and sustainable governance practices for the benefit of present and future generations.

In the context of healthcare technology management (HTM) in Saudi Arabia and the Gulf region, this study addresses a significant gap by exploring both external and internal risk factors affecting HTM performance. Previous research has primarily focused on modeling or predicting failures in medical devices, mostly examining internal (endogenous) factors that impact device performance and the development of optimal service strategies. However, a comprehensive investigation of external (exogenous) factors has been notably absent. This research introduces a novel hierarchical risk management framework, designed to accommodate the broad array of healthcare technologies, not limited to medical devices. It significantly advances the field by thoroughly investigating and validating a comprehensive set of 53 risk factors and assessing their influence on HTM. Additionally, this study embraces the perspective of enterprise risk management (ERM) and expands it to identify and incorporate a wider range of risk factors, offering a more holistic and strategic approach to risk assessment in healthcare technology management. The findings reveal that several external and internal factors previously underexplored significantly impact HTM performance. Notably, the Fuzzy AHP survey identified “design risk” under facility and environmental risks as the highest risk for HTM in the region. Furthermore, the study reveals that three out of the top ten risks are related to “facility and internal environmental” factors, six are related to technological endogenous factors, and only one is related to managerial factors. This distribution underscores the critical areas for intervention and the need for robust facility and technology management strategies. In conclusion, this research not only fills a critical void by providing a robust framework for healthcare technology risk assessment but also broadens the scope of risk analysis to include a wider array of technologies, thereby enhancing the efficacy and safety of healthcare interventions in the region. Additionally, the proposed hierarchy provides insights into the underlying risk factors for healthcare technology management, with potential applications extending beyond the regional context to a global scale. Moreover, the equation we propose offers a novel perspective on the key risk factors involved in healthcare technology management, presenting insights with far-reaching implications applicable not only regionally but also on a global level. This framework also supports sustainability goals by encouraging the efficient and responsible utilization and management of healthcare technologies, essential for ensuring the long-term economic and environmental sustainability of medical technology use.

The purpose of this research is to understand the relationship between green business ethics, green finance, and sustainable business performance, and to evaluate the role of corporate social responsibility (CSR) in this relationship. The impact of the damage inflicted on nature's functioning order is being felt much more strongly today. In light of these realities, companies are required to place greater emphasis on sustainability principles not just out of financial concerns but as a result of corporate social responsibility. In this context, focusing on the role of corporate social responsibility in sustainable business performance is the main goal of this research. Quantitative research methods, specifically the cross-sectional survey method, were employed for data collection and analysis. For this purpose, a convenience sampling method was used to select 427 white-collar employees working in industries operating in Türkiye as the sample for this study. The data collected through surveys were analyzed using the AMOS 24 statistical program. The findings underscore that green business ethics and green finance have a significant impact on corporate social responsibility and sustainable business performance. Additionally, it was determined that corporate social responsibility plays an intermediary role in shaping sustainable business performance. These findings are expected to provide an important foundation that can guide both employees and managers in developing awareness about green policies and sustainability, emphasizing the importance of green policies in the working life.

ABSTRACT After locavore was chosen as “the best word of the year” in 2007, its popularity increased gradually. Today great number of locavores consciously prefer locally produced food for the benefit of themselves and their community. Undoubtedly this conscious movement has its consequences in marketing discipline. Accordingly, this paper is purposed to examine the how locavore perceptions affect loyalty towards retailers that sell locally produced food. In this context, a survey was applied to people residing in Istanbul and Kocaeli districts to measure the robustness of these effects. Furthermore, attitude towards locavore is used as a control variable to reveal to what extend locavorism affects these proposed connections. According to results, for participants with low attitude, Social Responsibility and Health Consciousness variables have significant effect on local retailer shopping loyalty. However, for participants with high attitude, all independent variables proved to have substantial effect on local retailer shopping loyalty. As the first empirical study in Turkey on the subject, this paper will provide important insight to academia and practicioners due to today’s ever-increasing consciousness in green marketing.

The aim of this study is to investigate and determine the key factors guiding customer attitudes towards social media influencers, and on that base to explore their effects on purchase intentions towards advertised products or services. A total of 376 fulfilled questionnaires from an online survey were analysed. The main characteristics of digital influencers’ behaviour, affecting consumer perceptions have been systematized and categorized through a combination of both traditional and advanced data analysis methods. Structural Equation Modelling (SEM), machine learning and multi-criteria decision-making (MCDM) methods were selected to uncover the hidden dependencies between variables from the perspective of social media users. The developed models elucidate the underlying relationships that shape the acceptance mechanism of influencers’ messages. The results obtained provide specific recommendations for stakeholders across the social media marketing value chain. Marketers can make informed decisions and optimize influencer marketing strategies to enhance user experience and increase conversion rates. Working collaboratively, marketers and influencers can create impactful and successful marketing campaigns that resonate with the target audience and drive meaningful results. Customers benefit from more tailored and engaging influencer content that aligns with their interests and preferences, fostering a stronger connection with brands and potentially affecting their purchase decisions. As the perception of customer satisfaction is individual and evolving process, stakeholders should organize regular evaluations of influencer marketing data and explore the possibilities to ensure continuous improvement of this e-marketing channel.

Mangrove forests provide a wide range of goods and services that sustain communities around the world. This paper explores utilization patterns of extractable mangrove resources by communities within the proposed Kenya – Tanzania Transboundary Conservation Area (TBCA). Some 152 household surveys and 12 Nominal Group Technique discussions were carried out. At least 16 direct use products were reported to be extracted from the mangroves, with 90% of households found to use mangrove products. Changing patterns of mangrove use in the areas and accessibility point towards unsustainable utilization and promote illegal activities. Overharvesting of mangrove wood products was reported to be the major threat facing the forests. Patterns of mangrove use in the study site reveal a high level of mangrove-dependence by communities for their livelihood. There is a need to address the problems of open access through capacity building and awareness creation, development and implementation of harvest plans as well as introduction of alternative livelihood options to the communities in the area.

Background Endometrial cancer is the fourth most common type of cancer in the world. Due to the prevalence and high morbidity, it is of key importance to make a quick and accurate diagnosis and effective therapy. The use of photodynamic therapy (PDT) in the treatment of endometrial cancer is a significant challenge in conducting clinical trials. PDT is non-invasive, with few side effects, damaging only neoplastic tissue, leaving healthy adjacent structures intact. Thanks to numerous experiments (also in vitro), PDT is gaining more and more recognition as a potential tool in endometrium cancer treatment. Objective The aim of the study was to analyze the effectiveness of photodynamic therapy on endometrial cancer tissue samples Methods In the in vitro experiment of PDT, sections of endometrial cancer tissue taken from female patients were subjected to. Rose Bengal was used as a photosensitizer in order to assess the usefulness of the applied PDT and to introduce these solutions into the in vivo test procedure. Results Changes on the cellular substrate, such as: chromatin condensation, disturbed structure and shape of cell nuclei were observed in all tissues subjected to PDT. Conclusions The PDT experiment in vitro offers opportunities and hopes for using the chosen procedure also in vivo. Keywords endometrial cancer; photodynamic therapy; in vitro; treatment; rose bengal

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense industries, because they are exposed to risk already in early stages of development. This paper uses Heterogeneity and Homogeneity analysis between risk factors with Cochran’s Q test and Multidimensional scaling in order to present the complexity of the risk factors relevant to defense SoS, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense SoS shows a need to focus on three main risks faced by defense projects: insufficient human resources, changes in the original specifications, and lack of other (non-human) resources. The paper also presents some recommendations for minimizing risk factors in defense SoS.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense projects based on systems of systems (SoS), because they are exposed to risk already in early stages of development. This paper uses advanced data science tools to present the complexity of the risk factors relevant to defense systems, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense projects based on SoS shows a need to focus on three main risks faced by defense projects: uncertainty, the lack of clearly defined goals, and managing a system under constrained conditions. The paper also presents some recommendations for minimizing risk factors in SoS for defense projects.

Risk assessment management have been a hot topic for the researchers since a very long time. Software risk management is an important part of project management as it contains the identification, analysis, estimation and monitoring of different risks present in the system. This helps developers in decision making while assessing the problems that could arise in the software systems. Risk management is very complex in large scale system as these systems have very complex development. The paper describes risk management techniques for large scale system. Furthermore we have provided a detailed comparative analysis of these techniques with commonly identified risks in software systems and have provided a systematic order for risk management process to ensure risk mitigation.

Multi-stakeholder based construction projects are subject to various risk factors due to dynamic business environments. These risks affect project activities which indirectly impact construction costs, resulting in delays and poor building quality. So, managing these project risks requires suitable risk mitigation strategies to evaluate and analyse their severity. Hence, risk evaluation and assessment of construction projects is a multi-criteria decision making (MCDM) problem. In present real-life problems, evaluation of project risks is often uncertain and even incomplete, and the prevailing methodologies fail to handle such situations. To address the problem, this paper extends the analytical network process (ANP) methodology in the D number domain to handle three types of ambiguous evaluations, viz. complete, uncertain, and incomplete, and assesses the weight of risk criteria. The D number based approach overcomes the deficiencies of the exclusiveness hypothesis and completeness constraint of Dempster-Shafer (D-S) theory. Here, preference ratings of the decision matrix for each decision-maker are determined using a D number extended consistent fuzzy preference relation (D-CFPR). An extended multi-attributive border approximation area comparison (MABAC) method in D number is then developed to rank and select the best alternative risk response strategy. Finally, an illustrative example from construction sector is presented to check the feasibility of the proposed approach. For checking the reliability of alternative ranking, a comparative analysis is performed with different MCDM approaches (D-COPRAS, D-ARAS, D-MABAC, and D-TOPSIS). Based on different criteria weights, a sensitivity analysis of obtained ranking of the hybrid D-ANP-MABAC model is performed for verify the robustness of the proposed method.

During the Covid-19 pandemic in Taiwan, analytical tools of PEST (political, economic, social-cultural, and technological), SWOT (strength, weakness, opportunity, threat), nine building blocks of a business model canvas, and knowledge management were combined to develop a theoretical framework, and used to assess business, smart and sustainable management of two case companies: Tung Sheng Company Limited and its subsidiary, Strong Basic Enterprise Limited. A heuristic inquiry research design was adopted. In addition to secondary data from the two case companies, major top managers were interviewed to reveal constructive questions about the existing business models and to re-interpret strategy. The results showed that case companies own capabilities of R &amp; D (research and development) as a foundation to further apply new smart ICT (information and communication technology) and execute green manufacturing. Additionally, strong key partnerships are used to diversify business investment for leveraging on limited resources given current insufficient qualified employees. Resilient practices adopted new and green technology to help mitigate the negative impacts of the Covid-19 pandemic. This study provides a useful framework and practical information about how to examine business models, smart and sustainable management processes of the two case companies and to make adjustments in strategies for the future.

Evaluating the economic and environmental effects of farmers' green production behaviors holds important reference value for promoting sustainable agricultural development, alleviating agricultural non-point source (NPS) pollution, and achieving the organic combination of environmental protection and economic development. This paper utilizes survey data from 1,345 farm households in the main rice production areas of Jiangxi Province, China, using the example of reduced fertilizer application (RFA) among rice farmers. By constructing a DEA—SBM model with undesirable outputs to measure environmental effects, and applying an endogenous switching model to test the economic and environmental effects of farmers' adoption of green production technologies. The study found that: (1)The behavior of RFA by farmers has a significant positive impact on their net profit per mu(NPPA), helping farmers increase their income, with the increase ranging from 2.05% to 6.54%. (2)The behavior of RFA by farmers has a significant positive impact on agricultural green productivity(AGP), contributing to the improvement of the environment, with the improvement ranging from 44.09% to 45.35%. (3)Heterogeneity analysis found inconsistencies in the income-enhancing and environmental-enhancing effects at different quantiles of NPPA and AGP. Therefore, attention should be placed on improving the agricultural product quality supervision system under the market circulation mechanism, creating land scale conditions conducive to the promotion and application of fertilizer reduction technologies, and promoting the implementation of externality internalization compensation systems.

1) Landsat operational land imager (OLI) data and consequent laboratory measurements were used to predict Chlorophyll-a (Chl-a) concentration and the trophic states for an inland lake within the East Kolkata Wetland, India; 2) The most suitable band ratio was identified by performing Pearson correlation analysis between Chl-a concentrations and possible OLI band and band ratios from the study points; 3) The results showed highest correlation coefficient from the band ratio OLI5/OLI4 with an R value of 0.85. The prediction model was then developed by applying regression analysis between the band ratio OLI5/OLI4 and Chl-a concentration of the study points. The reflectance ratios of the validation points were given as input on the prediction model and the model output was considered as predicted Chl-a values of the validation points to check the efficiency of the prediction model. The regression model between laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points revealed a high correlation with an R² value of 0.78. Trophic State Index (TSI) of the lake was also calculated from laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points. The study presented a high correlation of TSI determined from predicted data with TSI from laboratory reference data (R = 0.88). The TSI values of the lake ranged from 65 to 75 which indicate that the lake is appeared to be eutrophic to hypereutrophic conditions. 4) This empirical study showed that Landsat 8 OLI imagery can be effectively applied to estimate Chl-a levels and trophic states for inland lakes.

The objective of this study was to carry out the extraction and characterization of chitin and chitosan from the exoskeletons of the Farfantepenaeus californiensis species of shrimp, as well as its application in the formulation of polymeric films plasticized with glycerol used in the process of food packaging. The characterization of the extracted polymer was made by Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and physicochemical analysis of chitin and chitosan, resulting in a theoretical performance of 29.33% and 16.46%, respectively. In terms of quality, it was determined that the extracted chitosan had a molecular weight of 1.10 x105 g/mol and a deacetylation degree of 80.23%, which classifies it as a low-molecular weight chitosan, suitable for food packaging. It was shown that the extracted chitosan is fit for the production of the films by using the casting method, presenting a tension resistance of 1 MPa. The Antibacterial analysis was carried out using Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), bacterial models commonly found in food. The results showed an effective inhibition capability of the polymeric materials. Overall, the results for both chitosan and the films indicate a high potential for application in the food packaging sector.

The rapid evolution of financial technology (fintech) has significantly transformed the financial services landscape, creating opportunities for innovation and introducing new risks. Traditional financial institutions and fintech companies operate under different paradigms, resulting in disparate risk management practices. This paper proposes a comprehensive framework for integrating operations and risk management practices between traditional financial institutions and fintech companies. By leveraging advanced technologies such as artificial intelligence (AI) and machine learning (ML), the framework aims to ensure consistent and effective risk assessment across the financial sector. The financial services industry is characterized by rapid innovation, primarily driven by fintech companies offering various services that enhance efficiency, accessibility, and customer satisfaction. However, the growth of fintech brings substantial risks, including cyber threats, data privacy concerns, regulatory compliance challenges, and operational vulnerabilities. Traditional financial institutions prioritize stability, security, and compliance within established risk management frameworks. The divergence in operational models and risk management approaches creates a fragmented risk landscape, posing significant challenges to the financial system's stability and security. This paper identifies the critical need for a unified framework integrating the risk management practices of traditional financial institutions and fintech companies. The proposed framework leverages AI and ML to enhance the accuracy and comprehensiveness of risk assessments, utilizing a centralized data repository for real-time risk assessment. Unified risk management policies covering cybersecurity, operational risk, regulatory compliance, financial crime, and real-time monitoring and reporting tools ensure robust risk management protocols and prompt response to potential risks. Aligning with regulatory requirements and incorporating best practices from both sectors, the integrated risk management approach enhances the financial ecosystem's stability, security, and public confidence.

Cardiovascular diseases (CVDs) a leading cause of mortality worldwide. Therefore, there is in-creasing interest in dietary interventions to reduce risk factors associated with these conditions. Cherries and berries are rich sources of bioactive compounds and have attracted attention for their potential cardiovascular benefits. This review summarizes the current research on the effects of cherries and berries consumption on cardiovascular health, including in vivo studies and clinical trials. These red fruits are rich in phenolic compounds, such as anthocyanins and flavonoids, which have multiple bioactive properties. These properties include antioxidant, anti-inflammatory, and vasodilatory effects. Studies suggest that regular consumption of these fruits may reducing in-flammation and oxidative stress, leading to lower blood pressure, improved lipid profiles, and enhanced endothelial function. However, interpreting findings and establishing optimal dosages is challenge due to the variability in fruit composition, processing methods, and study design. Despite these limitations, the evidence highlights the potential of cherries and berries as components of preventive strategies against CVD. Further research is needed to maximize their health benefits and improve clinical practice.

The most recent National Research Council Nutrient Requirements for Sheep and Goats was published in 2007, one of the most consequential nutrient requirement recommendations for sheep and goats in the world. It is pertinent to continue the refinement and discussion of nutrient utilization and requirements for the purposes of enhancing the efficiency of production systems, maximizing resource economy, and minimizing the carbon footprint, among others. Progress has been made in the estimation of energy and protein requirements in sheep and goats, mainly utilizing empirical feeding experimentation, comparative slaughter technique and minimum endogenous loss method. In sheep, newer estimates of energy and protein requirements for maintenance and growth and partial efficiencies had been reported since 2007. There were suggestions that energy and protein requirements could have been affected by breed, wool growth, gender and size; with these reported values being similar or lower than the recommended values in international feeding systems such as NRC, ARC, INRA and AFRC. In goats, energy and protein requirements for growing goats were reported to be either higher or lower than the established recommendations, depending upon meat or dairy breeds. Effect of gender on energy requirement appeared to be related to the stage of growth or degree of maturity. Newer data also suggested that the guidelines of the major feeding systems for the entire growth phase may not be adequate for non-pregnant and non-lactating pubertal females. In multiparous pregnant goats, energy and protein requirements for maintenance did not appear to be affected by days of pregnancy, but efficiencies of metabolizable energy and metabolizable protein utilization for pregnancy were. There were suggestions that that metabolizable protein synthesis in the rumen can be predicted from energy intake using combined equations that encompass both sheep and goats, but more data on goats were called for to account for specific differences in nutrition. In addition to sulfur, there has been progress made on the estimation of maintenance and growth requirements of calcium, phosphorus, potassium and magnesium in goats, with suggestions on the consideration of gender and breed differences. Species, level of Intake, genotype, mature size, age, gender, body composition, use of tissue energy, activity, season, and acclimatization continue to be important considerations for the estimation of nutrient requirements in sheep and goats, with emerging factors such as climate change, heat stress, parasitism and secondary plant compounds. Model equations and partial efficiencies used by NRC to predict energy and protein requirements for maintenance, growth, lactation, and fiber have been highlighted and discussed for the purpose of a more focus discussion and refinement for the future. Potential and limitation of both traditional and emerging methodologies in determining the nutrient requirements in sheep and goats were discussed. To justify the research investment, emerging methodologies such as nutrigenomics will have to be linked more directly to the improvement of production efficiency via more precise prediction of nutrient requirement.

Risk management strategies protect the company as a whole as well as employees from unforeseen financial impacts. As in the case of personal finance, preparing for certain scenarios helps to face any difficulties that the company may encounter and allows it to get out of this impasse.For any project to be successful, the way the project executing agency will deal with potential risks must be determined so that it can identify, mitigate or avoid problems when it needs to do so. Successful project managers realize that risk management is important, because the achievement of project objectives depends on planning, preparation, results and evaluation that contribute to the achievement of strategic goals, especially the sustainable development of societies.Risk management strategies work to protect the company as a whole as well as employees from unexpected financial effects, and as is the case in personal finance, preparing for certain scenarios helps to face any difficulties that the company may face and allows it to get out of this impasse.To ensure the success of your project, determine how you will handle potential risks so that you can identify, mitigate or avoid problems when you need to do so. Successful project managers understand that risk management is important, because the achievement of project objectives depends on planning, preparation, results, and evaluation that contribute to the achievement of strategic objectives.

The uniqueness of each system stems from the fact that the risks of disasters are specific and that their presence and manifestation are not universal and the same for every country. Just as no country is the same in all other segments, their disaster risk management systems are unequal. The paper describes the systems in four different countries, through observation and comparison of four areas of activity that are implemented in dealing with disasters. First of all, in the paper, the legal basis and institutional frameworks on which these systems rest in each of the countries were considered – starting from the international level and guidelines given at international conferences, to all by-laws and local disaster activity plans. It was considered how each of the states implements risk mitigation activities and how it increases preparedness for them. When the system recognizes risks, their probability and the frequency of their occurrence, activities are planned to prepare the country and every individual in it for a potentially unwanted event. Differences in the ways of mitigating risks and preparing all elements of the system and protected values for disasters are presented. The third element of action in the event of disasters concerns the response. In this segment, questions are raised regarding institutional solutions in the system, division of responsibilities, the priority of response and mobilization of resources at all levels. The last phase, the one that occurs after the disaster, and that is the recovery from it, depends on the reaction. In the paper, it was discussed how in the end, when a disaster occurs and when damage to the population, environment, material and other goods occurred, how each of the states implements reconstruction, i.e. how it recovers - whether that recovery was previously well planned or whether ad hoc solutions are applied.

Even though the rules for free movement of machinery within the European Union market have existed for more than 30 years, accidents related to their activities have constantly been achieving significant value. When designing the machine, a designer must stem from risk assessment, whereas all stages of its life cycle and ways of its use must be taken into consideration. In industrial operations, there is old machinery, which, although fulfilling its function reliably, the safety level is not in accordance with the developing requirements for their safe operation. The proposed methodology of assessment of the machinery safety condition comes out from the presupposition of the right application of steps of risk assessment and their reduction mainly by means of implementation of both effective and efficient preventive measures. The aim of the research applied in 3 operations, was to verify the method of machinery safety management. The created methodology based on 19 requirements for safety evaluates the level of the actual measures by means of the so-called criterion of current status and total efficiency of measures. Its output is the assessment of the efficiency level of implemented safety of each machine as well as of the whole operation.

Urban tourism has witnessed significant growth in recent years, driven by various factors that foster the transformation of urban areas into tourist hotspots. These factors include a rising interest in culture and heritage, ongoing urban redevelopment and conversion processes, and the introduction of new experiences and activities. Two particularly influential factors contributing to this growth are low-cost travel, which facilitates more accessible access to urban destinations, and the emergence of new types of accommodation, such as short-term rental (also known as local accommodation or Airbnb-type accommodation). This sudden and continuous growth of this type of tourist accommodation brings new challenges to cities and local communities. On the positive side, it contributes to job opportunities, the dynamism of the local economy, and urban revitalization. On the other hand, it also represents more difficulty in retaining the local population in city centers, as more and more buildings are converted into hostels and tourist apartments. In this context, it becomes essential to conduct studies evaluating the impacts of these dynamics in urban areas and how they influence residents' and visitors' perspectives. Therefore, this study aims to identify the main transformations resulting from short-term rental (STR) development, focusing on the impacts felt by tourists and residents in Porto. A questionnaire was distributed to tourists and residents in Porto's city center in June 2023. The results reveal differences in opinions between tourists and residents, particularly concerning historical heritage preservation, local population relocation, and reduced housing availability for residents. Nevertheless, there is a similarity in their opinions regarding the stimulus that local accommodation brings to the economy and the rehabilitation of buildings and urban areas. This study reinforces the need to pay more attention to the future development of tourist accommodation in city centers, especially regarding local policies and territorial planning, to balance better tourism development and local communities' quality of life.

The aim of the article is to verify differences in the perception of selected factors of sustainability among small and medium-sized enterprises (SMEs) in Central Europe. The subjects of analysis are factors such as corporate social responsibility (CSR), business risk sources (market, financial, personnel, and operational), reputation and social media, national support, social changes, and crisis events in business. The questionnaire was completed by 1,090 SMEs from the business environments of Visegrad Group countries. Statistical hypotheses were verified using Z-scores for two population properties. The most negatively perceived factors among owners and managers in the SME segment are national support and legislative changes. The most positively perceived factor is reputation and social media. The country of doing business is a significant factor. The perception of crisis events in business is most negative among Czech SMEs. More than 80% of Hungarian SMEs perceive their companies as sustainable. In comparison with Slovak and Polish SMEs, Hungarian perceptions are more positive in the context of sustainability. The country of doing business is the strongest factor in evaluating CSR indicators. The positive perception of CSR in Czech SMEs (43.9%) is lower than in other countries.

Current trends in systemic risk literature provide new insights into multi-hazard risks that interact and compound with built environments, creating more significant impacts on socio-economic and human systems. Recurrent natural hazards and extreme weather events are more likely to compound and cascade into more impactful events, especially in vulnerable societies. In small-island communities (SICS), including large archipelagos and Small Island Developing States (SIDS), the long-term impact of multi-, compounding-, and cascading-hazards (MCC hazards) can result in persistent vulnerability and residual risks. This is due to delayed responses, limited resources, poverty, fewer evacuation options, and inadequate markets and infrastructure. Using Ternate, a densely populated small volcanic island in North Maluku, Indonesia, as a case study, this paper assesses the impacts of seven types of natural hazards: flash floods, landslides, extreme weather, extreme waves and abrasion, earthquakes, tsunamis, and volcanic eruptions. The research focuses on the multi-hazard impact on population, land use, and infrastructure exposures in 60 villages in Ternate. The findings highlight population density, land use, and infrastructure exposure to multi-hazard risks, providing valuable information on potential losses in future hazard events.

Achieving the dual development of rural revitalization and urbanization is an important strategic goal of China’s current modernization. Rural population and settlements are the main components of the countryside in traditional agricultural areas, and play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and settlements at the township level, as well as the degree and type of coupled development. A framework for urban–rural development relationships based on different types of coupled development is proposed, and a model of urban–rural forces is constructed to derive the spatial pattern of urban–rural development at the township level that may be formed in the future. Our study shows that the rural population and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of the township-level coupling measurements present four types of development in terms of the spatial pattern of urban–rural development: A-type is most likely to produce new cities or satellite towns in the Jixi–Harbin–Qiqihar area in the future; B-type is the fastest dying area in the future, located in the Harbin and Qitaihe clusters, with a tendency to merge into Harbin; C-type is the area to be focused on in the future to attract population and strictly control the growth of the rural settlement area to avoid it turning into B-type; D-type may develop regional township centers in the future in the combined area of Jiamusi City, Suihua City and Mudanjiang City. The results of the study provide experience in realizing rural revitalization according to local conditions. The new spatial pattern of urban–rural development provides an important reference for formulating land use policies, optimizing urban–rural land allocation and realizing integrated urban–rural development strategies.

During choriogenesis in insects, chorion (eggshell) is formed by surrounding follicular epithelial cells in ovarioles. However, the regulatory endocrine factor(s) activating choriogenesis and the chemical components on eggshell deserve further exploration. In two representative Coleopterans, a Coccinellid Henosepilachna vigintioctopunctata and a Chrysomelid Leptinotarsa decemlineata, genes encoding the 20-hydroxyecdysone (20E) receptor heterodimer, ecdysone receptor (EcR) and ultraspiracle (USP), and two chitin biosynthesis enzymes UDP-N-acetylglucosamine pyrophosphorylase (UAP) and chitin synthase (ChS1), were highly expressed in ovaries of the young females. RNA interference (RNAi)-aided knockdown of either HvEcR or Hvusp in H. vigintioctopunctata inhibited oviposition, suppressed the expression of HvChS1, and lessened the positive signal of Calcofluor staining on the chorions, which suggests the reduction of a chitin-like substance (CLS) deposited on eggshells. Similarly, RNAi of LdEcR or Ldusp in L. decemlineata constrained oviposition, decreased the expression of LdUAP1 and LdChS1, and declined CLS contents in the resultant ovaries. Knockdown of LdUAP1 or LdChS1 caused similar defective phenotypes, i.e., reduced oviposition and CLS contents in the L. decemlineata ovaries. These results, for the first time, indicate that 20E signaling activates choriogenesis in two Coleopteran species. Moreover, our findings propose the deposition of a CLS on the chorions.

The optimal structural design is imperative to minimize material consumption and reduce the environmental impact of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as Genetic Algorithm (GA). However, the integration of AI-based optimization together with visual programming (VP) in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps including: (i) generation of parametric trusses in Dynamo VP; (ii) performing the finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. The feasibility of the proposed workflow was tested on benchmark problems and compared with open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction.

This paper presents the design and analysis of a novel 3-degree-of-freedom (3-DOF) parallel ma-nipulator equipped with self-sensing Ni-Ti (Nitinol) actuators. The manipulator's architecture and mechanical design are elucidated, emphasizing the integration of Nitinol actuators. The self-sensing technique implemented in a previous work was extended to a 20 mm actuator length, and the actuator was used to design the 3 DOF manipulator. Kinematic analyses were conducted to eval-uate the manipulator's performance under various operating conditions. A dynamic model was implemented for the dynamic dimensioning of the actuators, which work synergistically with a bias spring. The manipulator was realized, and a control strategy was implemented. Experimental tests, although documenting some positioning accuracy issues, show the efficacy and potential applica-tions of the proposed manipulator in robotics and automation systems, highlighting the advantages of self-sensing Nitinol actuators in small parallel manipulator designs.

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Lessons learned and risk-based outcomes from modernising the Australian Standard for post-mortem inspection and disposition judgement of beef, sheep, goat and pig carcases are described. Initial Risk Profiles identified priorities for quantitative assessments. The main difficulty encountered was the paucity of quantified performance of current inspection. Resolving this involved acquiring gross abnormality data representing regional production/proportional abattoir volumes, the range of gross abnormalities appearing nationally, proportional occurrence at carcase sites, and seasonality to enable comparisons. Evidence and discussion are provided for associated challenges experienced including preventing contamination, use of food chain information to support amendment, inspection as a part of industry Quality Assurance and opportunities to improve inspector training. Criteria considered by the Competent Authority for determination of equivalence of alternative post-mortem inspection techniques included comparisons of public health risk, non-detection rates for gross abnormalities, and microbial contamination resulting from inspection activities, as appropriate. Most gross abnormalities detected arose from animal health and welfare conditions affecting wholesomeness and did not present as food safety hazards. Non-detection rates between current and alternative inspection (observation) were negligible. A Quantitative Risk Assessment for Cysticercus bovis was conducted. Carcases with multiple gross abnormalities predominantly reflected historic infections (prior septicaemia) where trimming achieved wholesomeness unless cachexic.

This survey of research literature is an overview of the current state of science addressing DSM-5 diagnostic criteria as it relates to identifying Autism Spectrum Disorder (ASD) in young children. Selected sources are of high quality and have been published since 2020 in peer-reviewed journals relevant to children’s health. The narrative is organized from the earliest to the most recent publications and is divided into sections around categories and themes that highlight the main arguments, findings, and controversies identified by researchers. There are indications in the literature that while ASD can be identified and differentiated from other developmental disorders in young children, doing so requires that clinicians who have relied on the DSM-5 should also use multiple measures, including other formalized screening tools as assessments that gather observational input from parents and caregivers, as well as findings from physical examinations, laboratory investigations, and magnetic resonance imagining (MRI). This high level of corroboration points to an emerging diagnosis paradigm through which transdiagnostic approaches to early diagnosis and intervention may exist.

As the demand of heating and air conditioning is increasing day by day due to getting a comfortable life, for that reason, the market for heat pump and air conditioning systems or both, is seeing a steady increase in low global warming potential. All researchers on heat pump and air conditioning systems are searching for environmentally friendly refrigerants. However, a significant number of contemporary refrigerants (HCFCs) have the potential to cause global warming and ozone depletion, such as those found in heat pump air conditioning systems. Using more environmentally friendly refrigerants, including hydrocarbon and blend refrigerant mixtures, is one way to lower GWP and Ozone depletion potential. This study examines the performance of several alternative refrigerants, including R32, R134A, R410A, R22, and R290. In order to examine the performance of R290, theoretical and simulation results are compared on various refrigerants while taking into account a number of performance parameters, including the refrigerant energy efficiency ratio, mass flow rate, coefficient of performance, cooling capacity, and compressor work for one ton of refrigeration (1TR) air conditioners. One player with a very low GWP is R290. However, the only drawback is that it can catch fire and is hazardous to use in split-type commercial heat pump air conditioning applications. The environmental and thermo physical properties of HC-290 are significantly better than those of other materials, according to theoretical and simulation studies utilizing Cool Pack software, hence it is a viable replacement.

Despite the demonstrated benefits of data monetization initiatives in achieving competitive advantages, many of these efforts struggle to realize their potential. Companies often find it challenging to sustain even initially successful data monetization initiatives due to significant data quality issues. This reflects a disconnect between advancements in data monetization research—spanning digitization, digitalization, and digital transformation—and practical implementation within companies. Consequently, misguided approaches to data monetization are relatively common. A critical prerequisite for successful data monetization is the establishment and maintenance of clean, high-quality data. This study underscores the importance of data quality by conducting an in-depth analysis of Medical Inc., a company engaged in preparing pristine customer master data for advanced customer analytics. The investigation aims to elucidate Medical Inc.’s approach to addressing data cleanliness challenges and to distill a general framework for the customer master data cleansing process. This framework illuminates a relatively unexplored aspect of data monetization supplementing existing literature on digitization, digitalization, and digital transformation.

Background: The last-mile delivery phase, the final stage where goods move from a distribution center to customers, is pivotal but faces significant inefficiencies and high costs due to its complexity. Recent advancements in Edge AI or Edge Intelligence (EI) offer promising solutions to these challenges. Methods: This study explores how AI-driven technologies and real-time data processing, combined with EI, can enhance last-mile delivery operations. A thorough literature review was conducted to assess technological advancements, and a Delphi method was used to systematically and empirically assess the impact of EI solutions on both operational efficiency and customer satisfaction. Results: Although EI technologies offer substantial benefits, EU companies are hesitant to adopt these innovations due to high implementation costs. However, firms that have embraced these technologies report significant improvements, including better route optimization, reduced delivery times, and enhanced service reliability. These findings highlight the need for a culture of innovation and the recruitment of experts with advanced qualifications to drive technological advancement in last-mile logistics. Conclusions: The integration of EI represents a significant step towards more efficient, cost-effective, and customer-focused last-mile delivery solutions. Future research should aim to refine these technologies and explore their long-term impacts on the logistics industry.

Small and Medium Enterprises (SMEs) are recognized as the main drivers of economic growth and development in many countries throughout the world. SMEs represent about 90% of the manufacturing sector and contribute about 14% of the total manufacturing contribution to GDP. Despite SMEs’ potential to change Nigeria’s status from a consumer economy to a production economy, policies that will ensure that environmentally- friendly manufacturing processes and production technology are not implemented or complied with. SMEs’ operational activities may be deleterious to human health and the ecosystem if environmental management practices are not adopted or prioritized. This paper evaluated the perception and adoption of the Environmental Management System, mainly ISO 14001, by SMEs in Nigeria. One hundred and fifty (150) SMEs in the manufacturing sector in Lagos and Ogun State, Southwestern Nigeria, were randomly selected for this study. The paper posits that environmental management literacy and advocacy should be carried out in SMEs. Environmental management practices involve engaging both industries and product end-users in sustainable practices. The paper concludes that the implementation of environmental management practices and culture by SMEs will abate environmental pollution and its concomitant health risks to humans, the environment, flora, and fauna. Mandatory and voluntary environmental measures are suggested as a means of engendering eco-friendly innovation for sustainable development, triggering employment, job security, and gross domestic product.

The Internet of Things (IoT) continues to grow at a rapid pace, becoming integrated into the daily operations of individuals and organisations. IoT systems automate crucial services within daily life that users may rely on, which makes the assurance of security towards entities such as devices and information even more significant. In this paper, we present a comprehensive survey of papers that model cyber risk management processes within the context of IoT, and provide recommendations for further work. Using 39 collected papers, we studied IoT cyber risk management frameworks against four research questions that delve into cyber risk management concepts and human-orientated vulnerabilities. The importance of this work being human-driven is to better understand how individuals can affect risk and the ways that humans can be impacted by attacks within different IoT domains. Through the analysis, we identified open areas for future research and ideas that researchers should consider.

Risk management of electric power transmission lines requires knowledge from different areas such as environment, land, investors, regulations, and engineering. Despite the widespread availability of databases for most of those areas, integrating them into a single database or model is a challenging problem. Instead, in this paper, we use a single source, the Brazilian National Electric Energy Agency’s (ANEEL) weekly reports, which contains decisions about the electrical grid, comprising most of the areas. Since the data is unstructured (text), we employed NLP techniques such as stemming and tokenization to identify keywords related to common causes of risks provided by an expert group on energy transmission. Then, we used models to estimate the probability of each risk. Our results show that we were able to estimate the probability of 97 risks out of 233.

Controlling and managing risk is always a critical point for the managers, investors and even consultants. Having clear and better percepts about future can reduce the risk of fail. In addition it is important for a risk analyzer to consider the stakeholders views and senses about the risk. This research aimed at framing a comprehensive risk management model which builds up on stakeholder requirements and forecasting techniques. This conceptual model attempts to use the stakeholder’s points of view to write prefer and probable scenarios to neglect critical risks and increase the chance of success in long-term plannings. Using futures studies methods prepare decision makers for the possible upcoming events and donate them a powerful tool to handle the uncertainties cover the future.

The commercial aviation industry is constantly evolving, driven by technological innovation and the growing demand for more efficient and environmental friendly transportation solutions. In this context, the design and development of next-generation aircraft is a crucial task, with the goal of reducing environmental impact and improving flight efficiency while continuing to ensure passenger comfort and safety. This paper aims at evaluating the technical feasibility as well as economic and environmental viability of a narrow body aircraft powered by hydrogen for direct combustion. Notably, the paper offers innovative insights regarding the update of literature models for conceptual design, in order to consider the impact of hydrogen fuel on the sizing loop at aircraft level. Moreover, it also focuses on the evaluation of operating costs for the aforementioned aircraft class, highlighting the required model updates and considerations to properly match the effect on costs of the introduction of the innovative fuel. Ultimately, a preliminary analysis of upstream sustainability of the concept, considering fuel life cycle, is provided, in order to understand the overall competitiveness, not only in terms of monetary resources but also of environmental impact, beyond the pure operating life of the airplane.

The aims of this study are to measure the technical efficiency (TE) of Cambodian household’s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015 TE of household’s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household’s rice production, while disaster, education of household head, family size and other crops’ cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.

The aims of this study are to measure the technical efficiency (TE) of Cambodian household’s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of the production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015, TE of household’s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household’s rice production, while disaster, education of household head, family size and other crops’ cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.

The present study aims to measure the technical efficiency and establish core factors effecting rice production in Cambodia. Four-years dataset generated from the central government document “Profile on Economics and Social” of entire 25 provinces between 2012-2015 and the stochastic production frontier model (SFA) was applied. The results indicated that the level of output (quantity) of Cambodian rice production varied according to the different level of capital investment in agricultural machineries, total rice actual harvested area, and technically fertilizers application within provinces. Furthermore, evidence revealed the overall mean efficiency of rice production is 78.4% implies that there is still room to further improve technical efficiency by given the same level of inputs and technology. More importantly, the findings revealed that irrigation, production technique and amount of agricultural supporting staffs are being as the most important influencing factors of rice production’s technical efficiency in Cambodia. In conclusion, present study strongly recommends the development of irrigation systems and good water management practices to be considered and bring into more effective actions by the central government as well as related agencies for improving rice production in Cambodia in addition to capital investment and improving technical skills of supporting staffs and rural farmers.

Worldwide, there is a significant increase in the use of unmanned aerial vehicles (UAVs) by emergency services. They offer a lot of possibilities during the rescue operation. Such a wide application for various purposes and environments causes many threats related to their use. To minimize the risks associated with conducting air operations with UAVs, the SORA methodology will be important. Due to its level of detail, it is a methodology adapted to civilian use. In this article, the authors' team will try to develop guidelines and directions for adapting SORA to the requirements of the operational work of emergency services. Thus following article aims to present the most important risks related to conducting operations with the use of UAVs by First Responders (FRs) and to show the sample risk analysis performed for this type of operation on the example of the ASSISTANCE project. The paper describes, on the one hand, possibilities offered by UAVs in crisis or disaster management and step-by-step Specific Operations Risk Assessment (SORA) and on the other hand, presents possible threats, consequences and methods of their mitigation during FRs missions.

Natural risks encompass a range of disasters and dangers, requiring comprehensive management through assessments, anticipations, and advanced alert systems. Our specific focus is on landslides in challenging terrains. The evaluation of landslide risks employs sophisticated multicriteria models, such as the weighted sum approach, integrating qualitative parameters. Despite the challenges of the rugged terrain in Northern Algeria, it paradoxically hosts a dense population attracted by valuable hydro-agricultural resources. Our research is dedicated to studying landslide risks in these areas, particularly in the Mila region, with the aim of constructing a statistical model integrating considerations of both danger and vulnerability. This complex process identifies threats and their determining factors, including geomorphology and socio-economic conditions. The result is a valuable tool for effective risk management, strengthening safety and resilience against natural disasters. By understanding the intricate interplay of geological, environmental, and social elements, our research can contribute to the development of targeted interventions, fostering a more resilient community in the face of natural adversities.

Following technological advances, autonomous and remote-controlled ships are performing trials in some sea areas; a mandatory goal-based MASS code, expected to enter into force on 1 January 2032, is under discussion in the International Maritime Organization (IMO). However, there are no unified standards regarding verification methods to define operating limitations for cutting-edge technologies, which are expected to be elements of MASS, so it is difficult to assess the risk factors for the management and operation of MASS. This paper outlines the regulatory framework for MASS, followed by a discussion of its application, considering the differences between MASS and automated driving, and how to develop safety management and operation using standards for automated driving. A requirements management framework developed as a system and software engineering standards to build safety management and operation of MASS is proposed. It is also suggested that the requirements management framework could be used not only for MASS development but also for regulatory review from a requirements management view.

An analysis of the physical and chemical phenomena accompanying the electrical discharges was carried out, principal factors inactivating microorganisms is studied. Characteristic factors of an electric discharge in cavitation mode providing a synergistic effect when disinfecting water with a discharge and chemical reagents are identified in order of importance. As a result of the integral action of cavitation, the inactivation of bacteria is intensified both due to the emergence of chem-ically active particles and due to local shock waves, acoustic currents and ultraviolet radiation in the area of cavitating bubbles. The similarity of cavitation processes in water systems implemented by underwater electric discharges and with the ultrasound has been experimentally proved. The main advantage of electric discharge cavitation in comparison with ultrasonic one is the wide band of ultrasonic frequencies of radiation inherent in electric discharge, high intensity and power of cav-itation processes, and, accordingly, the possibility of a significant increase in the volume of the disinfected liquid. The study enable better understanding and prediction of the effects that occur during a high-voltage underwater electrical discharge and have a bactericidal effect.

Plant growth regulators (PGRs) and deficit irrigation (DI) play a crucial strategic role in sustaining agricultural yield and reducing water stress in drought prone areas. The study was carried out in 2021-2022 to assess the impact of various PGRs (SA & NAA) & irrigation levels (60% Epan, 80 % Epan, and 100 % Epan) with DI & partial root drying (PRD) irrigation strategies. PGR application boosted fruit yields and demonstrated its significance in reducing water stress by lowering canopy temperature, maintaining higher relative water content in the leaves, modifying stomatal opening, and increasing photosynthetic rate. PGRs were used to assess the increased accumulation of total phenols, flavonoids, and improved antioxidant activity. Results indicated that exogenous use of PGRs like SA+NAA in conjunction with 80% irrigation levels increased fruit yield (31.97 and 40.38%) and water productivity (64.92 and 75.39%) for DI and PRD treatments, respectively. Thus standardizing irrigation and crop management practices including PGR application can be recommended to boost pomegranate productivity particularly in water-scarce environments.

A sustainable low cost activated carbon substitute was produced based on pretreated lignocellulosic biomass, especially spruce sawdust. A harmful liquid waste, desalination brine was used for the treatment of a solid wood industry waste, spruce sawdust. This approach is in the circular economy theory and aims to the decarbonization of the economy. The pretreated sawdust was tested as an adsorbent appropriate for the removal of a commonly used pollutant, methylene blue, from industrial wastewater. The adsorption capacity of the pretreated material was found to increased four times comparing to the untreated one in the case that the Freundlich equation was fitted to the isotherms’ data. The treatment experimental conditions with desalination brine that gave maximum adsorption capacity correspond to 1.97 combined severity factor in logarithmic form value. The same adsorption capacity was found to increase five to six times comparing to the untreated spruce sawdust in the case that the Langmuir isotherm model was applied at the same data. Moreover, kinetic experiment was cried out as regards the methylene blue adsorption process. The desalination brine pretreated sawdust adsorption capacity increased 1.4 times comparing to the untreated one, in the case of the Lagergren kinetic equation fitting. Furthermore, the adsorption capacity of the same material was increased 1.6 times when the second order kinetic model was applied to the same data. Industrial scale applications can be based on the kinetic data findings as they have to do with a very shorter adsorption period comparing to the isotherm data.

Product innovation is a crucial factor in enterprise survival. Even though there are sources from strategic theory that guides the clear comprehension towards appreciating the nexus between these two variables (product innovation and enterprise survival), there are still many lacunas that should be addressed and filled. Consequently, the need for additional empirical corroboration or support is pertinent. This study aimed at verifying the nexus between product innovation and enterprise survival, and how they are affected by the existence of antecedent variables such as competitive intensity and competitive advantage. In the methodology, this study adopts the conduct of explanatory and cross-sectional investigations through the use of structural equation modelling (SEM) to a sample of selected food and beverages enterprises in Lagos, Nigeria. Regarding the food and beverage enterprises in Lagos, Nigeria, this study discovered that competitive intensity has huge positive implication on product innovation at (0.39; t = 5.69, p < 0.05). This gives numerical evidence that, in the face of more market competition, enterprises will be pressured to adopt the model of costs reduction on products which will enhance the reduction of product prices, and will have significant impact on profit. However, the findings reveal that there is no significance between competitive advantage and product innovation at (0.002; t = 0.203, p > 0.05), and there is no significance between product innovation and enterprise survival at (-0.035; t = -1.583, p > .05). As a result, the food and beverage enterprises should concentrate more on product innovation so that they will be able to stand the intensity of competition. The results emanated from the study is germane as it make significant contribution to literature and the body of knowledge and on strategic management by enlightening that competitive intensity is a necessary inducement for product innovation.

Accelerating the green transformation of the economic development mode and promoting high-quality economic development is an international trend and the general direction. This article utilizes data from manufacturing companies listed on the Shanghai and Shenzhen stock exchanges from 2011 to 2021, based on dynamic capability theory, to explore the impact of enterprise digital transformation on green technological innovation. Furthermore, dynamic capabilities are further subdivided into absorptive capacity, innovative capacity, and adaptive capacity to investigate their mediating role. The research findings demonstrate that enterprise digital transformation has a significant positive impact on green technological innovation. Moreover, enterprise digital transformation positively influences the absorptive capacity, innovative capacity, and adaptive capacity, with these three factors playing a mediating role in the impact of enterprise digital transformation on green technological innovation. The results of the bootstrap test confirm this mediating effect. The conclusions of this study are validated through a series of robustness tests. This research not only provides theoretical support for the impact mechanism of digital transformation on green technological innovation but also offers practical insights for enterprises to achieve sustainable development.

The work safety standardization of enterprises based on the traditional work safety theory has played a significant role in reducing the number of accidents and improving work safety to some extent in China. However, some problems are coming with the work safety standardization of enterprises developing constantly in China. On the one hand, it is not combined with the actual situation of the enterprise, lacking pertinence and specificity, these defects resulted that it is not integrated with original safety production management system of enterprise and make it difficult to carry out. On the other hand, there is a lack of systematic management methods for the work safety management system of enterprise, most of enterprises only pay attention to the inspection result rather than the process control. This means after the check of the government, many enterprises will relax to carry out the system. This paper puts forward a new method for optimizing the standardization management mode of work safety based on the Viable System Model(VSM), which can solve the defects of work safety standardization of enterprises management system. An optimization model of work safety standardization based on VSM was construct for explaining the process optimization and control of work safety standardization management. It can improve the connectivity between the enterprise and the government. The conclusion of this paper can provide reference for achieving the development and optimization of work safety standardization of enterprises in China.

Strategic intelligence covers the examination of what impacts and influences the business and the related SWOT analysis, (strengths, weaknesses, opportunities, and threats mapping). Through this research, leaders will be able to properly allocate and re-route resources, identify areas of improvement, and ensure that strategic initiatives are aligned with the organization's mission. Strategic intelligence is, therefore, effective through the use of critical thought and data-driven decisions and seeing the outcomes of different positioned alternatives. It must also form and support a culture of cooperation and open communication within the organizations, stimulating employees' inputs and learning curves. The article's subject is the necessity for strategic intelligence, a crucial competence for leaders, managers, and companies striving to remain competitive, to be utilized and best leveraged in today's volatile and dynamic business contexts. It helps the leadership turn proactive, foresee trends, and make correct, agile decisions that enforce companies' long-term growth and success. This study follows a research design that includes a thorough literature review and bibliometric research, executed via VoSViewer, illustrating the concept of strategic intelligence from a leadership point of view as a driver of competitive advantage. Further, the article points out that the limitations are acknowledged because the literature on the matter is limited, as strategic intelligence is relatively new to the business sector; moreover, more research is required to fully understand and use the potential of strategic intelligence in business growth. By overcoming these limitations and continuing to study this concept, businesses can gain a competitive edge and make informed decisions that fuel their success in an ever-evolving market. As a result, this study contributes to developing strategic intelligence in leadership and business and paves the road for further research and applications of strategic intelligence theories in organizational contexts.

In Ethiopia, farmers have changed cropland to Eucalyptus globulus plantations for construction, fuelwood and economic benefits. However, it has adverse effects on soil properties. The investigation was, therefore, to evaluate the impact of Eucalyptus globulus plantations on soil properties in northwestern Ethiopia. About 30 soil samples were collected from two soil depths (0-20 and 20-40 cm) and three land uses (Eucalyptus globulus plantations, cropland and grazing land) with five replications. Soil properties were analyzed using a two-way analysis of variance (ANOVA). Based on the result, soil properties such as silt particles, moisture content (MC), organic matter (OM), total nitrogen (TN) and cation exchange capacity (CEC) were significantly higher under the soil of Eucalyptus globulus plantations than in cropland and grazing land. Whereas the lower contents of bulk density (BD), soil pH, available phosphorus (AP), electrical conductivity (EC) and exchangeable bases (Ca, Mg, K, and Na) were recorded in Eucalyptus globulus plantations. Besides, clay, BD, MC, pH, EC, CEC, percent base saturation (PBS) and basic cations increased with soil depth while decreasing sand, silt, TP, OM and AP. The basic cations ( Ca, Mg, K), PBS and AP decreased in the soil of the 25-year old Eucalyptus globulus plantation compared to cropland by 38%, 36%, 43 %, 45% and 47% and grazing land by 56%, 60%, 76 %, 60% and 56%, respectively. Therefore, appropriate and effective land use management principles should be implemented in the study area.

The article presents a model for optimizing biomass supply chains using the linear programming framework integrated with a Geographic Information System. Based on the distance from a given type of biomass resource, its calorific value, price, and transportation costs, the model identifies the optimal source of biomass, allowing it to cover the demand for the required total energy value with the lowest possible costs. The case study includes the Połaniec power plant in southeastern Poland and potential sources of forest biomass and agricultural straw within 100 km of the plant. Unit costs of biomass varied depending on biomass availability and energy demands. For energy demand on the level of 1 PJ yearly, the lowest unit costs of biomass (4.08 €/MJ) were when all kinds of biomass were available, and the highest (5.47 €/MJ) was when only stacked wood was available. As energy demand increased, unit costs increased, and the ability to meet this demand with just one type of biomass decreased. The energy biomass sector can utilize the model to benefit both biomass producers and their final buyers.

Oracles have been suggested as a vital piece of infrastructure necessary to allow blockchain-based smart contracts to reach their full potential by interacting with real-world data. This paper begins by providing an approachable entry point to the oracle problem and the current landscape of existing solutions. From there, we provide an overview of published research to narrow down unexplored research directions and derive questions for interviews. Finally, the results of 15 unstructured expert interviews are presented and discussed. The focus here is the industry landscape of oracle projects, opportunities for innovation, and challenges needing to be overcome.