The relationship between the civil and business sectors has intensified in the last few years, including cross-sectoral partnerships as part of corporate social responsibility. The authors examine the impact of these partnerships on the performance of 100 of the largest businesses in Bosnia and Herzegovina. Large companies were chosen because they are most likely to be involved with corporate social responsibility activities and cooperation with civil society organizations. Methodologically, the authors analyzed the effect of these partnerships on business performance using four Balanced Scorecard components - three non-financial and one financial performance. The research results show specific influences on non-financial business performance but not financial performance.

This document presents a summary of the 2023 Terrestrial Very-Long-Baseline Atom Interferometry Workshop hosted by CERN. The workshop brought together experts from around the world to discuss the exciting developments in large-scale atom interferometer (AI) prototypes and their potential for detecting ultralight dark matter and gravitational waves. The primary objective of the workshop was to lay the groundwork for an international TVLBAI proto-collaboration. This collaboration aims to unite researchers from different institutions to strategize and secure funding for terrestrial large-scale AI projects. The ultimate goal is to create a roadmap detailing the design and technology choices for one or more kilometer--scale detectors, which will be operational in the mid-2030s. The key sections of this report present the physics case and technical challenges, together with a comprehensive overview of the discussions at the workshop together with the main conclusions.

Automating network processes without human intervention is crucial for the complex Sixth Generation (6G) environment. Thus, 6G networks must advance beyond basic automation, relying on Artificial Intelligence (AI) and Machine Learning (ML) for self-optimizing and autonomous operation. This requires zero-touch management and orchestration, the integration of Network Intelligence (NI) into the network architecture, and the efficient lifecycle management of intelligent functions. Despite its potential, integrating NI poses challenges in model development and application. To tackle those issues, this paper presents a novel methodology to manage the complete lifecycle of Reinforcement Learning (RL) applications in networking, thereby enhancing existing Machine Learning Operations (MLOps) frameworks to accommodate RL-specific tasks. We focus on scaling computing resources in service-based architectures, modeling the problem as a Markov Decision Process (MDP). Two RL algorithms, guided by distinct Reward Functions (RFns), are proposed to autonomously determine the number of service replicas in dynamic environments. Our proposed methodology is anchored on a dual approach: firstly, it evaluates the training performance of these algorithms under varying RFns, and secondly, it validates their performance after being trained to discern the practical applicability in real-world settings. We show that, despite significant progress, the development stage of RL techniques for networking applications, particularly in scaling scenarios, still leaves room for significant improvements. This study underscores the importance of ongoing research and development to enhance the practicality and resilience of RL techniques in real-world networking environments.

The cleavage of C-S bonds represents a crucial step in fossil fuel refinement to remove organosulfur impurities. Efforts are required to identify alternatives that can replace the energy-intensive hydrodesulfurization process currently in use. In this context, we have developed a series of bis-thiolato-ligated CrIII complexes supported by the L2- ligand (L2- = 2,2'-bipyridine-6,6'-diyl(bis(1,1-diphenylethanethiolate), one of them displaying desulfurization of one thiolate of the ligand under reducing and acidic conditions at ambient temperature and atmospheric pressure. While only 5-coordinated complexes were previously isolated by reaction of L2- with 3d metal MIII ions, both 5- and 6-coordinated mononuclear complexes have been obtained in the case of CrIII, viz., [CrIIILCl], [CrIIILCl2]-, and [CrIIILCl(CH3CN)]. The investigation of the reactivity of [CrIIILCl(CH3CN)] under reducing conditions led to a dinuclear [CrIII2L2(μ-Cl)(μ-OH)] compound and, in the presence of protons, to the mononuclear CrIII complex [CrIII(LN2S)2]+, where LN2S- is the partially desulfurized form of L2-. A desulfurization mechanism has been proposed involving the release of H2S, as evidenced experimentally.

Large language models (LLMs) have revolutionized Natural Language Processing (NLP), but their size creates computational bottlenecks. We introduce a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full accuracy recovery for fine-tuning tasks at up to 70% sparsity. We achieve this for the LLaMA-2 7B model by combining the SparseGPT one-shot pruning method and sparse pretraining of those models on a subset of the SlimPajama dataset mixed with a Python subset of The Stack dataset. We exhibit training acceleration due to sparsity on Cerebras CS-3 chips that closely matches theoretical scaling. In addition, we establish inference acceleration of up to 3x on CPUs by utilizing Neural Magic's DeepSparse engine and 1.7x on GPUs through Neural Magic's nm-vllm engine. The above gains are realized via sparsity alone, thus enabling further gains through additional use of quantization. Specifically, we show a total speedup on CPUs for sparse-quantized LLaMA models of up to 8.6x. We demonstrate these results across diverse, challenging tasks, including chat, instruction following, code generation, arithmetic reasoning, and summarization to prove their generality. This work paves the way for rapidly creating smaller and faster LLMs without sacrificing accuracy.

Background and Objectives There is uncertainty whether patients with large vessel occlusion (LVO) presenting in the late 6-hour to 24-hour time window can be selected for endovascular therapy (EVT) by noncontrast CT (NCCT) and CT angiography (CTA) for LVO detection. We evaluated the clinical outcomes of patients selected for EVT by NCCT compared with those medically managed in the extended time window. Methods This multinational cohort study was conducted at 66 sites across 10 countries. Consecutive patients with proximal anterior LVO stroke selected for EVT by NCCT or medically managed and presenting within 6–24 hours of time last seen well (TSLW) from January 2014 to May 2022 were included. The primary end point was the 90-day ordinal shift in the modified Rankin Scale (mRS) score. Inverse probability treatment weighting (IPTW) and multivariable methods were used. Results Of 5,098 patients screened, 839 patients were included, with a median (interquartile range) age of 75 (64–83) years; 455 (54.2%) were women. There were 616 patients selected to undergo EVT by NCCT (73.4%) and 223 (26.6%) who were medically managed. In IPTW analyses, there was a more favorable 90-day ordinal mRS shift in patients selected by NCCT to EVT vs those who were medically managed (odds ratio [OR] 1.99, 95% CI 1.53–2.59; p < 0.001). There were higher rates of 90-day functional independence (mRS 0–2) in the EVT group (40.1% vs 18.4%, OR 3.31, 95% CI 2.11–5.20; p < 0.001). sICH was nonsignificantly higher in the EVT group (8.5% vs 1.4%, OR 3.77, 95% CI 0.72–19.7, p = 0.12). Mortality at 90 days was lower in the EVT vs MM group (23.9% vs 32.3%, OR 0.61, 95% CI 0.45–0.83, p = 0.002). Discussion In patients with proximal anterior LVO in the extended time window, there was a lower rate of disability and mortality in patients selected with NCCT and CTA to EVT compared with those who were medically managed. These findings support the use of NCCT as a simpler and more inclusive approach to patient selection in the extended window. Trial Registration Information This study was registered at ClinicalTrials.gov under NCT04096248. Classification of Evidence This study provides Class III evidence that for patients with proximal anterior circulation occlusion presenting with ischemic stroke from 6 to 24 hours, compared with medical management, those undergoing thrombectomy based on NCCT have reduced disability and mortality at 90 days.

With the increasing adoption of IoT devices and applications, significant research and development efforts have been centered around engineering novel ecosystems referred to as the IoT-edge-cloud compute continuum. In this article, we implement, analyze and present a case study for performance benchmarking of five well known and select open source MQTT broker implementations in an open-source compute continuum testbed. The proposed MQTT broker implementations are evaluated in terms of response time, different payload sizes and throughput. Measurements and results show that the hardware platform used, the message size, as well as the network parameters (latency, packet loss and jitter) have a significant impact on the resulting performance of various broker implementations and therefore have to be carefully considered in the selection process for the building blocks of the continuum. All implementations and measurements are made to be fully reproducible and free and open source.

As human medicine is developing at a galloping pace, continuously offering new medical products, diagnostic methods and preventive programmes, there is almost no time gap between their creation and application in medical practice. All these biomedical achievements are primarily intended to improve public health and the patient’s quality of life and health. Hence, it is important to define potential risks, side effects, and unwanted outcomes when applying a medical product/treatment before integrating it into healthcare. Unlike any other product/treatment intended for human use, medical products/treatments require prior clinical testing on human subjects (sick or sound). The authors of this paper have restricted their scientific interest to the participant (human subject) of a clinical study as one of the core elements of a clinical investigation, representing at the same time its means and its aim. By analyzing relevant international as well as national legal rules and ethical principles of the Republic of Srpska related to the participation of humans in clinical studies, it will be concluded that the participants’ safety and right to self-determination, integrity, and autonomy manifested through their independent right to either consent or refuse to participate in a clinical study supersedes the interests of science or society. However, clinical trial-related statistical data obtained from randomly chosen healthcare institutions in the Republic of Srpska will show certain derogations from prescribed ethical policies. Considering this fact, the authors have paid special attention to thematising the ethicality of recruiting participants for a clinical study based on partial or no information related to the purpose, methods, potential risks and side effects of the investigation in the name of the greater good for humanity. Such practice has accentuated the discretionary powers of ethical review committees on the one side and the uncertainty of the right to informed consent on the other.

This paper analyzes the influence of foliar fertilizer based on humus extract on some of the elements central to the quality of the Polka raspberry variety in the area of the city of Bihać. The research was conducted in 2015 according to the control and treatment system. A foliar fertilizer based on humus extract was used for the treatment. A total of 12 quantitative and qualitative properties were analyzed: content of total sugars, reducing sugars, invert sugars, sucrose, water content, dry matter, total acidity, vitamin C, total phenols, total flavonoids, antioxidant capacity, and fruit mass. After the analyses were completed, it can be concluded that fruits of raspberry plants treated with humus extract have an almost identical value of total acidity (1.65%) as found in control. However, treatment with a humus extract slightly lowered the content of total phenols and vitamin C. Based on the results obtained, it was shown that the foliar fertilizer based on the humus extract did not have a positive effect on certain chemical and antioxidant properties of the raspberry fruit.

Honey is a natural product that is an excellent source of energy containing mainly carbohydrates and water, as well as small amounts of organic acids, vitamins, minerals, flavonoids, and enzymes. Due to the presence of bioactive compounds, it has been shown that honey is beneficial for many diseases, e.g. gastrointestinal diseases, skin diseases, cancer, heart diseases, and neurological degeneration. The study of the physical and chemical properties of honey and the content of bioactive compounds has been increasingly applied in order to determine the quality of honey samples. The aim of this study is to investigate physicochemical properties as well as the total phenol content and antioxidant activity of seven multifloral honey samples from the Herzegovina region. Physicochemical parameters determined in the honey samples (moisture, acidity, electrical conductivity, reducing sugars, sucrose, and insoluble matter) were within the quality standard limits of the Regulation on methods for control of honey and other bee products. Total phenolic content was determined using the Folin-Ciocalteu method and it ranged from 46.98 ± 6.36 to 152.94 ± 4.95 mg GAE/100 g of honey. To determine the antioxidant activity of the honey samples, two methods, FRAP and ABTS, were used. The total phenolic content of honey correlated positively with its antioxidant activity.

Circular Economy (CE) and Artificial Intelligence (AI) are two key concepts that can significantly contribute to sustainable development. The first is based on the goal of maximizing resource utilization and minimizing waste, creating conditions for sustainable and environmentally friendly economic development. On the other hand, AI aims to optimize various processes and improve efficiency in the application of CE, providing tools for innovation and enhancement of business processes. The focus of this research is the analysis of performance indicators for the application of Circular Economy (CE), Artificial Intelligence (AI), and Sustainable Development Goals (SDGs) in countries with different levels of economic development and within the context of global territorial coverage. Circular Economy is crucial for sustainable development through waste reduction and maximum resource utilization. Countries such as the Netherlands, Denmark, and Germany demonstrate high recycling rates and use of secondary raw materials, while Romania, Bosnia and Herzegovina, and Albania lag in these aspects. Artificial Intelligence plays an important role in economic growth and innovation. The United States, China, and Japan lead in investments, number of patents, and number of experts in this field, making them leaders in AI technologies. Less developed countries have limited capacities and need international support for the development of this field. Sustainable Development Goals represent a comprehensive approach to economic, social, and environmental progress. Countries with high SDG indices, such as the Netherlands, Denmark, and Germany, successfully implement sustainable development strategies. In contrast, the least developed countries face significant challenges in achieving these goals. This research shows that developed countries are successful in applying Circular Economy and Artificial Intelligence, while less developed countries lag behind and need additional support. Global cooperation and the exchange of knowledge and technologies are crucial for achieving sustainable development and technological advancement in all countries.

Although often presented as a revolutionary innovation, the circular economy is not a new idea. It is another reconciliation and compromise between economic and environmental problems expressed by the terms "sustainable growth", "green growth" and "sustainable development". The various strategies aimed at prolonging the use of resources gathered under the banner of the circular economy are not individually new, and if the concept offers any novelty, it is by offering a new framing of these strategies, as well as the possibility of connecting them. The circular economy is built on a heterogeneous collection of scientific and semi-scientific concepts, such as: ecological economy, industrial ecology, cradle-to-cradle design, blue economy, biomimicry, ecological efficiency, cleaner production, etc. Over a hundred definitions of circularity can be found in the literature, which means that the term means different things to different people. This could be because the concept and its application were almost exclusively developed and led by practitioners, i.e. policy makers, companies, business consultants, business associations, business foundations, etc. The result is a perception that the circular economy does not address the ontological and epistemological questions, such as what counts as ethical value, that underlie the complex and interconnected environmental, social and economic issues we face today. It's really easier to say what the circular economy isn't than to say what it is. The circular economy "is not a theory but a new approach to industrial production and consumption." Rather, it is a multiplicity, an umbrella concept that generates enthusiasm because it seemingly provides a new framework capable of solving many problems, but comes under increased scrutiny when attempts at operationalization surface unresolved questions about its definition. The variety of meanings given to the circular economy may explain the appeal of the term, but it also makes it difficult to know what it is really about. The main advantage of the circular economy is the optimal method of production in various industrial sectors: (1) It implies the lowest possible level of waste material that can no longer be recycled, (2) Each activity of the production process produces the smallest possible amount of waste for a specific activity. The key shortcomings of the circular economy are: (1) It is much more expensive to produce a long-lasting product than a larger quantity of equivalent disposable products,(2)- He does not pay attention to people as factors of production.

The history of agriculture is a long chain composed of numerous revolutionary innovations that have occurred, and continue to occur, following industrial revolutions and the advancements of modern science; in the 20th and 21st centuries, this progress has been much faster than ever before. There is no specific year that marks the founding of agriculture in human civilization; it cannot be precisely determined, as it was not a singular event but rather a process that spanned centuries. Researchers agree that Homo sapiens began to abandon the nomadic way of life, domesticate wild animals, and gather and plant cereal seeds in the early Neolithic period (Neolithic Revolution), when there was a rapid retreat of glaciers to the north and a warming of the climate. Most researchers believe this occurred around 10,000 years ago, although some suggest it may have been 12,000 or even 15,000 years ago. One of the first regions where humans engaged in agriculture was the area known as the Fertile Crescent, which spans the region that today includes Israel and Lebanon in the west and Iraq and Iran in the east, around the Euphrates and Tigris rivers. The development of agriculture during the Neolithic Revolution enabled population growth, the establishment of settlements, and the rise of more complex societies. It was a period of transformation in human history that laid the foundations for modern agriculture and food systems on which today's global population relies. The development of the economy, including agriculture, from its very beginnings has been based on the use of natural resources as one of the main factors of industrial production. The increasing exploitation of these resources raises questions about how long this process can continue, considering that many of these resources are non renewable. It is estimated that by 2050, the population will reach 9 billion, for whom food must be provided! In addition to not very optimistic economic forecasts, another dark cloud, taking on increasingly negative proportions, looms over nature. Environmental degradation, as an ecological problem, has become not only relevant but also crucial for survival. The primary need to produce more food regardless of the ecological consequences, is responsible for the alarming degradation of the environment. Soil is the most important resource in food production. The increasing exploitation of soil, combined with strong industrialization and urbanization, is leading to a reduction in arable land and the contamination of cultivated land, threatening food production and biodiversity. In some areas, these relationships have reached critical levels. The degradation of agricultural land is adversely affected by many factors, with the most aggressive being: erosion (caused by wind, water, and sun), industrial pollutants, mineral fertilizers, pesticides, lack of windbreaks, illegal waste dumping, traffic impact, etc. Phosphorus fertilizers introduce heavy metals, primarily cadmium, into the soil, which then enters the human body through plants and animals, potentially causing serious diseases. Pesticides, various solvents, and packaging used for storage and transport are very dangerous substances that can negatively impact soil fertility. Additionally, conventional agriculture significantly contributes to greenhouse gas emissions and climate change. Industrial production, including conventional agriculture, operates on a linear economy model, whose principle of "take-make-use-dispose" is one of the main polluters of the environment. Modern science proposes new agricultural production concepts, such as precision, smart, regenerative, and digital agriculture, which contribute to the rational use of natural resources. In a time of unreasonable natural resource consumption, environmental degradation, and global climate change on one hand, and increasing food demand on the other, a new model in agriculture—circular agriculture—represents a promising strategy to support sustainable, restorative, and regenerative agriculture. Circular agriculture, which operates on the principle of "take make-use-return," aims to reduce waste, increase resource efficiency, and improve sustainability. Circular agriculture focuses on optimizing resource use, minimizing waste, and promoting sustainable food production. This paper provides a brief overview of the impact of the four industrial revolutions on the development of agriculture, with a more detailed analysis of the application of achievements from the third and fourth industrial revolutions. The negative impacts of linear agriculture on the environment and the contribution of circular agriculture to the rational use of natural resources, reduction of soil degradation, mitigation of climate change, and production stability are presented. The practices of the circular economy and the barriers to its implementation are also discussed.

Due to increasingly pronounced climate changes and intensified anthropogenic impacts on the environment, on one hand, and global economic growth and exploitation of scarce natural resources, on the other hand, there is a need to find a compromise solution that would ensure long-term, sustainable economic development. One of the optimal possibilities in this context is the development approach of the circular economy. This approach offers a sustainable response to environmental challenges by promoting principles such as waste reduction, reuse, and recycling. The circular economy finds its application in numerous sectors of economic activity, such as industry, agriculture, energy, water resource management, and others. The implementation of the circular economy involves meeting the four basic economic principles (4E): economy, efficiency, effectiveness, and the latest ecological principle. The realization of the basic principles of the circular economy includes various techniques for transforming natural resource management, i.e., maximizing the utility of available materials while minimizing waste production. In this context, technological innovations play a crucial role in enhancing the development of circular economic processes. New technologies are thus a prerequisite for increasing economic efficiency while simultaneously reducing the ecological footprint of the entire social community. Through examples from around the world, the chapter illustrates specific cases where the circular economy has already had a visible impact on reducing local pollution, such as reducing greenhouse gas emissions, managing industrial and agricultural waste, preserving water flows and soil, and protecting air quality. It also considers the challenges and potential solutions in implementing circular strategies in these areas. Furthermore, the role of international cooperation and the development of political frameworks that favor the expansion and adoption of circular initiatives are analyzed. The discussion is based on creating comprehensive strategies that connect different societal actors and create an efficient system of long-term sustainability and socio-economic stability. From all the above, it implies that the circular economy is a key tool for achieving long-term sustainable development, whose active application counteracts climate change and protects the planet for future generations.