La cría de caracoles, también conocida como helicicultura, es un tipo de ganadería que implica la reproducción y cultivo de caracoles para consumo humano. Aunque la cría de caracoles sigue siendo relativamente rara en muchas partes del mundo, es una industria en crecimiento que ofrece una serie de beneficios, incluido el impacto ambiental pequeño, alto potencial de beneficios y ventajas nutricionales únicas. Entre varias especies comestibles, los caracoles como Cornu aspersum y Helix pomatia han demostrado un tremendo potencial como fuentes alternativas de proteínas en las dietas animales. Tienen un perfil nutricional favorable, que contiene aminoácidos esenciales, minerales y vitaminas, lo que los convierte en valiosos suplementos o sustitutos de fuentes de proteínas tradicionales. Las técnicas y prácticas de cría de caracoles han avanzado significativamente en los últimos años, lo que ha resultado en un aumento de la productividad y mejoras en los rasgos genéticos en las poblaciones de caracoles. Además, los esfuerzos de investigación en curso están explorando el desarrollo de protocolos de cría de caracoles adaptados a requisitos veterinarios específicos. La optimización de los métodos de cría, incluida la selección artificial, el apareamiento controlado y la mejora genética, tiene un enorme potencial para mejorar los rasgos deseables en las poblaciones de caracoles. Este progreso puede contribuir al desarrollo de razas de caracoles superiores con perfiles nutricionales mejorados, resistencia a enfermedades y propiedades terapéuticas. Además, la cría de caracoles presenta una oportunidad para abordar problemas ecológicos asociados con la producción tradicional de ganado. El uso eficiente de recursos, los requisitos mínimos de espacio y el bajo impacto ambiental hacen que la cría de caracoles sea una alternativa ecológica. Los caracoles también son menos susceptibles a ciertas enfermedades infecciosas que comúnmente afectan a los animales criados tradicionalmente, lo que reduce la necesidad de antimicrobianos y promueve prácticas sostenibles. La educación continua y la investigación sobre técnicas de cría de caracoles, perfiles nutricionales y aplicaciones terapéuticas allanan el camino para prácticas veterinarias innovadoras que priorizan la sostenibilidad, el bienestar animal y mejores resultados de salud. Una mayor investigación en este campo representa una nueva oportunidad para que veterinarios y agricultores contribuyan a la salud y el bienestar de los animales al tiempo que promueven prácticas sostenibles en la industria ganadera. Este artículo de revisión tiene como objetivo proporcionar una visión general de la literatura científica sobre la cría adecuada de caracoles comestibles y los posibles desafíos de los impactos antropogénicos y climáticos negativos como un desafío potencial para los criadores.

Tekst predstavlja prilagođeno izlaganje sa naučne konferencije ZAVNOBiH u retrospektivi: evaluacija historijske važnosti i savremene relevantnosti za društvo i državu koja je organizirana povodom 80. godišnjice od Prvog zasjedanja ZAVNOBiH-a. Konferencija je održana 20. novembra 2023. godine na Univerzitetu u Sarajevu - Fakultetu političkih nauka. The text represents an adapted presentation delivered at the scientific conference ZAVNOBiH in Retrospect – Evaluating Its Historical Importance and Contemporary Relevance for Society and the State, organized on the occasion of marking the 80th Anniversary of the First Session of ZAVNOBiH. The conference was held at the University of Sarajevo - Faculty of Political Sciences, on 20 November 2023.

Working with different DBMS for programmers in their daily work represents a significant challenge in terms of choosing the appropriate way of connecting to the DBMS for the appropriate needs, given that a significant number of factors can influence the same. Although experience is usually one of the important elements that has influence on the selection of the appropriate way to connect to a DBMS, the choice can still vary from system to system and from situation to situation. For this reason, it is necessary to conduct appropriate analysis and research in accordance with various factors that can be an indicator of whether a connection with a DBMS is good or bad. In this research, an analysis was performed between the two leading methods of interaction between Java Spring Boot applications and PostgreSQL databases, namely Spring JDBC and Spring Hibernate. The results of the analysis indicate that there are certain differences in the speed of query execution in certain situations, which Java programmers should pay special attention to when choosing one of the two mentioned technologies to achieve more complex functionalities.

This paper aimed to explore ways to organize Spotify playlists, relying on clustering algorithms. Clustering algorithms were performed on playlists with extracted and standardized audio features obtained from the Spotify API, and the algorithms used were KMeans, DBSCAN, Affinity Propagation, and Spectral Clustering. Their performances were measured with the silhouette score, execution time, and inspection of clustered tracks, where it was determined that KMeans was the best algorithm in this case. Even though the execution time of KMeans is the third best, its silhouette score is the highest with 0.263. With this model, it is possible to effectively perform a mood-based organization of one's Spotify playlist, by dividing it into multiple smaller ones that share similar audio features.

Abstract Histologic transformation to small cell lung cancer (tSCLC) is a rare but increasingly recognised mechanism of acquired resistance to tyrosine kinase inhibitors (TKI) in patients with epidermal growth factor receptor (EGFR)-positive non-small cell lung cancer (NSCLC). Beyond its acknowledged role in TKI resistance, histologic transformation to SCLC might be an important, yet under-recognised, mechanism of resistance in NSCLC treated with immunotherapy. Our review identified 32 studies that investigated tSCLC development in patients with EGFR-mutated NSCLC treated with TKI therapy and 16 case reports of patients treated with immunotherapy. It revealed the rarity of tSCLC, with a predominance of EGFR exon 19 mutations and limited therapeutic options and outcomes. Across all analysed studies in EGFR-mutated NSCLC treated with TKI therapy, the median time to tSCLC development was ∼17 months, with a median overall survival of 10 months. Histologic transformation of EGFR-mutated NSCLC to SCLC is a rare, but challenging clinical problem with a poor prognosis. A small number of documented cases of tSCLC after immunotherapy highlight the need for rebiopsies at progression to diagnose this potential resistance mechanism. Further research is needed to better understand the mechanisms underlying this phenomenon and to develop more effective treatment strategies for patients with tSCLC.

With the growing requirements to keep the security of supply higher than ever the room for failures is getting smaller in today's power systems, while the increased integration of distributed renewable energy sources is additionally complicating fault detection. By using big data that is collected in modern power systems, artificial intelligence algorithms can significantly improve the capabilities of traditional protection schemes. However, the choice of the artificial intelligence algorithm can significantly impact the scheme accuracy. This paper analyses a novel approach for power system fault detection and classification by using automated machine learning procedure that iterates over different data transformations, machine learning algorithms, and hyperparameters to select the best model. By simulating and testing tens of thousands of fault scenarios on a realistic test system, the suggested approach resulted with robustness and high accuracy.

Recognizing the increasing importance of renewable energy sources, specifically wind farms, in today's power environments, this paper aims to clarify the complex interactions between these renewable energy facilities and distribution grids functioning under low-demand conditions. This particular case comes with inherent limitations that must be considered by taking into account all the factors that can influence the performance of the wind farm under these conditions. The modelling procedure and the simulation of the connection of the wind farm to the power system in rural area was performed using EMTP-RV software. The mean annual production of the wind power plant and the behaviour of the wind power plant in the event of failure in a real power system were calculated. Also, the power quality was examined in agreement with the Network Code of the transmission system of Bosnia and Herzegovina.

In the era of Industry 4.0, service robot path planning has emerged as a pivotal element in the optimization of logistic tasks within manufacturing, warehousing and service applications. In this context, the adoption of advanced path planning algorithms, such as the Grey Wolf Optimizer (GWO) swarm algorithm, play a key role in enabling these robots to navigate through complex environments with precision and agility. Harnessing the power of bio-inspired algorithms, our framework establishes a methodical and effective approach to the intricate task of service robot path planning.

Denial of Service (DoS) attacks, particularly the distributed variant known as DDoS, are easily initiated but pose significant challenge in terms of mitigation, especially in the case of DDoS. These attacks involve the use of a vast number of packets, often generated by specialized programs and scripts, crafted for specific attack types like SYN flood, ICMP Smurf, and similar. Malicious DoS packets share similar attributes, such as packet length, interval time, destination port, TCP flags, and the number of connections to the same host or service. To rapidly identify anomalous packets amidst legitimate traffic, we propose a system that incorporates the Newcombe-Benford power law and Kolmogorov-Smirnov test. This approach enables the detection of matching first occurrences of leading digits, such as packet size indicating the use of automated scripts for malicious purposes, and the count of connections to the same host or service.

Power system stability plays a significant role in the overall power system analysis. With the high penetration level of distributed generation (DG), especially large-scale wind farms, this problem needs to be addressed. This study investigates the system stability in case of a wind park (WP) integration using doubly fed induction generators (DFIGs) to transmission grid, while focusing on WP fault ride-through ability. The system was modelled for time-domain simulations. The results indicate that WP parallel operation with the high voltage network is possible if specific conditions are met, with fault clearance time being crucial. This is shown through scenarios, in which each of the overhead lines (OHL) was disconnected due to three-phase short circuit symmetrical fault, and the network parameters were observed for each case. The predefined control and protection configurations in the DFIG-based wind farm model simplify the analysis. The introduction of a battery energy storage system (BESS) with P and Q control strategies, improves WP stability during faults. Professional software tools, PSSE, and EMTP-RV, were employed for the analysis. The study showed that simulated WP and BESS connected to a real network, paired with appropriate fault clearance time and protection settings, can operate effectively while maintaining overall system stability. This research is significant for power system planning, especially with the growing integration of large-scale wind generation.

With the development of new technologies, next-generation mobile networks have brought new services with strict performance and security requirements. One promising solution that can ensure the highest possible level of security is quantum key distribution (QKD). This technology provides information-theoretical security using the principles of quantum physics. This paper presents an extended analysis of one implementation of the QKD key delivery protocol defined in the ETSI GS QKD 014 standard, considering a multi-user environment. We propose an empirically derived model of key delivery latency in such an environment based on regression analysis of experimental results. Using the proposed model, we estimate the limitations of the implemented solution in terms of maximum number of simultaneous users connected to one key management server, considering several applications in 5G/6G networks.

Professional football players often need legal help in managing disputes with football clubs. The Professional Football Players Syndicate of Bosnia and Herzegovina is an organization founded with this purpose. Due to an increasing need for legal help and a large number of cases, their legal associates need systematic management of data. This work presents the first information system entirely intended for the usage by sports law professionals. It contains a desktop application where legal disputes are shown in the form of an organized dispute table. Real-time information about football players is acquired by using the TransferMarkt web API. The system was successfully used for two years, resulting in 103 documented cases involving 87 players and 31 clubs. As a result, 69.90% of disputes were archived and 43.69% of disputes resulted in agreements, indicating that the productivity of legal associates and the mediator role of the Syndicate were improved.

Procedural modeling is used to generate virtual content in organized layouts of exterior and interior elements. There is a large number of existing layout generation methods, and newer approaches propose the generation of multiple layout types within the same generation session. This introduces additional constraints when manually created layout elements need to be combined with the automatically generated content. Existing approaches are either designed to work with existing elements for a single layout type, or require a high amount of manual work for adding existing elements within multiple layouts. This paper presents a method that enables the application of existing subdivision methods on multiple layout types by inserting existing content into the generation result. This method can generate test cases by creating variations of partially generated layouts for procedural modeling methods that can work with existing content.

Clustering users on social media based on text involves grouping individuals with similar text patterns, language usage, or content interests. This text-based clustering provides insights into user preferences, enables personalized content recommendations, and facilitates understanding of social networking trends and user engagement. However, traditional text clustering methods rely heavily on language-specific features. This limits their applicability in multilingual media environments where linguistic diversity prevails. In this paper, the problem of clustering users on social networks, specifically focusing on text-based clustering independent of the language in which the text is written, is addressed. A practical methodology is presented, outlining an iterative procedure for clustering based solely on language-independent features such as emojis, hashtags, URLs, text length, and punctuation count. The effectiveness of the language-independent clustering approach is compared with the usual text based clustering approach. Comparison of these results shows that for the used dataset, the proposed clustering method using language independent features gives higher quality results than text clustering.

In research aimed at determining the level of interest of high school students in enrolling in colleges, predictive analysis models and comparisons are rarely applied during the classification and processing of various data. All of this leads to significant fluctuations in college admissions, where certain schools are unable to admit a large number of students who show interest in a specific field. On the other hand, high school students lose interest in certain schools, leading to the discontinuation of specific directions essential for today's job market needs. Institutions largely fail to conduct a comparison and linkage of teaching and non-teaching activities when analyzing the talents and interests of high school students from different fields. The goal of this paper is to use programming language classifiers to predict student enrollments in colleges based on the results students demonstrate during regular attendance in high schools through participation in innovation fairs.