The targeted use of social robots for the family demands a better understanding of multiple stakeholders’ privacy concerns, including those of parents and children. Through a co-learning workshop which introduced families to the functions and hypothetical use of social robots in the home, we present preliminary evidence from 6 families that exhibits how parents and children have different comfort levels with robots collecting and sharing information across different use contexts. Conversations and booklet answers reveal that parents adopted their child’s decision in scenarios where they expect children to have more agency, such as in cases of homework completion or cleaning up toys, and when children proposed what their parents found to be acceptable reasoning for their decisions. Families expressed relief when they shared the same reasoning when coming to conclusive decisions, signifying an agreement of boundary management between the robot and the family. In cases where parents and children did not agree, they rejected a binary, either-or decision and opted for a third type of response, reflecting skepticism, uncertainty and/or compromise. Our work highlights the benefits of involving parents and children in child- and family-centered research, including parental abilities to provide cognitive scaffolding and personalize hypothetical scenarios for their children.

This study aims to analyze the opinions of Bosnia and Herzegovina (BiH) citizens regarding mandatory pension insurance and the possibility of incorporating private insurance in future reforms. The research involves evaluating the satisfaction of BiH residents with the current pension system, understanding their perception of the pension fund’s risks, and identifying their attitudes towards possible pension system reforms, including the potential involvement of private insurance. The study also seeks to highlight any differences in attitudes towards socio-demographic characteristics, such as gender, employment, length of service, professional qualification, and monthly income. A survey of 812 BiH adults (representative but potentially not fully capturing the entire population) explored these aspects. While acknowledging limitations, the study reveals significant differences in attitudes based on demographics. For example, men are more optimistic about future pensions, while employed individuals are more inclined towards reform. The findings suggest general public support for pension system reform and openness to private insurance. However, the study highlights the need to consider these varying attitudes across different population groups when designing future reforms. This research provides the first quantitative data on BiH residents’ views on private insurance reform, contributing to public discourse and informing future policy changes.

This paper explores the legal regulations on the termination of pregnancy in comparative law, a sensitive topic that, although it does represent the exclusive domain of state regulation, encroaches into human rights as well. The basic research question is how selected modern democratic states legally regulate the issue of the termination of pregnancy. Hence, the research goal is to prove that the trend of modern democratic states is to allow the termination of pregnancy even on request, but also to determine the existence of recent retrograde trends in this area. In this paper and research, except for the comparative method, the analytic, dogmatic, normative, and axiological methods are utilized. Although the core of the research is comparative legal, the historic and international legal segments are presented in short in this paper. In researching the following selected states, BiH, Serbia, Croatia, Germany, USA and Ireland, it is determined that the termination of pregnancy is currently largely allowed even on the request of a pregnant woman, especially for justified reasons, with regards to a specific legal regime (Germany), a sudden shift in complete liberalization (Ireland), and even for retrograde changes towards absolute prohibition (USA). In the argument section, the right of the state to ban a medical procedure out of arbitrary reasons (at least in modern discourse) is considered (even disputed). The conclusion is, considering the practice and development of democratic states, the trend of allowing the termination of pregnancy in early stages on demand of a pregnant woman without a reason, and in later stages with a reason, is evident. Concerning the region, the situation is relative satisfactory, although in greater parts of Bosnia and Herzegovina as well as Croatia the outdated legislation needs innovations, as well as certain improvements, which at this point is inevitable.

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 article aims to show the potential contribution of high-yielding rice varieties to achieve sustainable intensification in paddy farming, by focusing on a developing country. A comparative life cycle assessment of traditional vs. high-yielding varieties is carried out by comparing the area-based and yield-based results. Primary data are collected through a farm survey (49 farms in the Mazandaran province, Iran; spring 2018). The results highlight that high-yielding varieties can reduce the yield-scaled impacts. However, area-scaled impacts are subject to increase for most impact categories. Statistically significant trade-offs involve global warming potential (+13% per ha and −28% per t in high-yielding varieties) and fossil resource depletion (+15% per ha and −26% per t in high-yielding varieties). Pesticide management is the most alarming practice. High-yielding varieties increase pesticide consumption and related toxicity impacts both per t and per ha. This study is a new contribution to the literature by improving and broadening the mainstream productivity perspective of current life cycle assessment research about crop varieties. The lessons learnt from this study suggest that the trade-offs between yield-scaled and area-scaled impacts should be carefully considered by decision-makers and policymakers, especially in developing countries that, like Iran, are affected by the overexploitation of natural resources. Targeted policy and the development of farmer education and advisory services are needed to create the enabling conditions for farm management changes, including conscious use of production inputs while avoiding heuristics.

This paper describes a new smartphone-based colorimetric method for the determination of N-acetyl-L-cysteine and glutathione using a reaction with the Cu(II)–neocuproine complex. The reaction resulted in the formation of a yellow Cu(I)–neocuproine complex. Reaction solutions, prepared according to the selected optimal conditions, are placed in front of a light blue background, and a smartphone camera is used for digital image acquisition. The intensity of the blue RGB canal was selected for analytical response and determined using the free Color Grab mobile app. Also, absorbance at a wavelength of 450 nm was measured for all reaction solutions using a UV–Vis spectrophotometer. The proposed procedures allow the determination of both thiols in the linear dynamic range from 3.0 × 10–6 to 2.0 × 10–4 mol L−1 for a spectrophotometer as a detector, or from 6.0 × 10–6 to 2.0 × 10–4 mol L−1 for a smartphone as a detector. The obtained results indicate that the proposed method is accurate, simple, cost-effective, and applicable to the determination of thiols in pharmaceuticals.

Waste water in the galvanic process contains high concentrations of heavy metals that pose a direct danger to humans and the environment. Conventional methods for their removal are quite expensive and generate a large amount of waste. The development of new and improvement of existing methods for the removal of heavy metals from galvanic wastewater are the subject of many studies. Compared to other purification methods, the adsorption is becoming an increasingly popular method of wastewater purification, especially if the adsorbent is cheap, easily available and does not require any other treatment before use. Therefore, the aim of the work was to investigate the possibility of using natural bentonite for the removal of heavy metal ions from multi-component water systems of the galvanic industry. For this purpose, the physico-chemical characterization of natural bentonite was performed, and then the influence of pH value, time and temperature on the adsorption efficiency was examined. The results of adsorption showed that natural bentonite can be used as an adsorbent for the removal of heavy metal ions from waste galvanic waters, and that at pH 5 it achieves the maximum removal efficiency for Cu(II):Cr(III):Ni(II) ions in the percentage ratio 100 : 99.990 : 99.998. The results showed that the highest removal efficiency for Cu (II) ions was achieved in the first 10 minutes, and 20 minutes for Cr (III) and Ni (II) ions. The maximum efficiency of Cu (II) removal was achieved at all temperatures, while for Cr (III) 99.99% and Ni (II) 100% maximum efficiency was achieved at 35°C, which indicates that the adsorption process is endothermic. The experimental results of the adsorption of Cu (II) metal ions are in good agreement with the Langmuir and Freundlich theoretical models, while for Cr (III) and Ni (II) ions they are in better agreement with the Langmuir adsorption model.

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.

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.

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.

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.

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.