Anonymous communication networks (ACNs) enable Internet browsing in a way that prevents accessed content from being traced back to the user. This provides a high level of privacy, protecting individuals from being tracked by advertisers, governments, and other entities. The Tor network, a prominent example of such a network, uses a layered encryption scheme to encapsulate data packets, employing Tor nodes to obscure the routing process before the packets enter the public Internet. While Tor is capable of providing substantial privacy, its encryption relies on schemes such as RSA and Diffie-Hellman for distributing symmetric keys, which are vulnerable to quantum computing attacks and are currently in the process of being phased out. To overcome this threat, we propose a quantum resistant alternative to RSA and Diffie-Hellman for distributing symmetric keys, namely, quantum key distribution (QKD). Standard QKD networks depend on trusted nodes to relay keys across long distances. However, reliance on trusted nodes in the quantum network does not meet the criteria necessary for establishing a Tor circuit in the ACN. We address this issue by developing a protocol and network architecture that integrates QKD without the need for trusted nodes, thus meeting the requirements of the Tor network and creating a quantum secure anonymous communication network.

Kinetic energy from vibrations emerging from mechanical systems such as machines and vehicles has been thoroughly studied as a power source in the last two decades. Numerous kinetic energy harvesters have been built to convert human locomotion into electrical power but haven’t been implemented on a wide commercial scale. On the other hand, energy harvesters for farm animals haven’t been studied as much. In this paper, we present a three-dimensional electromagnetic induction based kinetic energy harvester optimized specifically for cattle wearable applications. All the device parameters are obtained with an empirical optimization procedure by considering specific cattle locomotion characteristics. The prototype is 3-D printed with low friction and impact resistant materials. Finally, the device is tested in a real free grazing scenario with live cattle. The kinetic energy harvester performed well and was able to power the load and transmit animal body temperature data over long distances for up to 7 times/h.

Abstract Forensic obstetrics attracts much attention from forensic experts and the public owing to the professional, legal, public health, and not inconsiderable social-emotional aspects and directly correlates with maternal, fetoneonatal, and iatrogenic risk factors. Modern obstetrics and fetomaternal medicine must not be quantified and qualified based only on perinatal disease but also according to current obstetric problems that burden forensic obstetrics. Therefore, high-risk obstetrics as a significant medico-legal problem should be viewed from the point of view of the entire perinatal period with possible long-term consequences, hence the monitoring of complete perinatal and infant morbidity is of immediate importance for quality control and risk control in the profession. The task of forensic obstetrics is to assess the impact of risk factors on the occurrence of an adverse event and to assess whether it is an obstetric complication or obstetric malpractice. Acknowledging the mentioned facts is the only way we will develop high obstetric awareness, and we and pregnant women, birth attendants, midwives and patients, fetuses, and newborns will have professional safety with imminent but controlled obstetric risk and controlled expected complications. On the other hand, the fact that the statistics of perinatal (obstetrical) malpractice globally is not abating requires a change in obstetrical philosophy, especially the unreasonable epidemic increase of cesarean sections with a significant percentage of cesarean sections without medical indication and complications. It is necessary to introduce and maintain solid professionalism and bioethical norms in obstetrics with constant training of skills, which is emphasized by numerous authors and with which we fully agree. Forensic obstetrics is based on the principles of good clinical practice, professional guidelines of modern obstetrics, and ethical and deontological principles. It clearly shows the perfection and imperfection of biological systems that we can and cannot influence. However, we must act according to the rules of the clinical profession, deontological rules, and health laws to reduce clinical risk to the smallest possible extent. Attention should certainly be focused on reducing the disproportion between iatrogenic and maternal-fetoneonatal risk factors, which is the most common reason for litigation today.

Noncoding RNAs (ncRNAs) are pivotal for various pathological processes, impacting disease progression. The potential for leveraging ncRNAs to prevent or treat atherosclerosis and associated cardiovascular diseases is of great significance, especially given the increasing prevalence of atherosclerosis in an ageing and sedentary population. Together, these diseases impose a substantial socio‐economic burden, demanding innovative therapeutic solutions. This review explores the potential of ncRNAs in atherosclerosis treatment. We commence by examining approaches for identifying and characterizing atherosclerosis‐associated ncRNAs. We then delve into the functional aspects of ncRNAs in atherosclerosis development and progression. Additionally, we review current RNA and RNA‐targeting molecules in development or under approval for clinical use, offering insights into their pharmacological potential. The importance of improved ncRNA delivery strategies is highlighted. Finally, we suggest avenues for advanced research to accelerate the use of ncRNAs in treating atherosclerosis and mitigating its societal impact.

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.