bluuebunny/crossref_metadata_2025 huggingface dataset:
Prosocial and Antisocial Students’ Behaviour in the Context of School Safety
Authors: Tadić Violeta , Kordić Boris
Published: January 2025

Prosocial behaviour is recognized as a factor that contributes to adolescent socialization, psychosocial adjustment, and development. This research examined the prosocial and antisocial students’ behaviour in relation to school safety. A sample of 719 students from the 2nd to 4th grades of high school completed a self-report questionnaire (476 girls, 219 boys; Mage = 16.64). The research was conducted in person during the first semester of 2021 at nine high schools in the territory of the Republic of Serbia. The questionnaire items were chosen in cooperation with a team of psychologists and pedagogues from selected high schools. The measures included the Prosocial Behaviour Scale, which includes the factors Prosocial behaviour (α=.96) and Antisocial behaviour (α=.89); and the School Safety Scale, which includes the factors Violent behaviour (α=.92); Unsafe school environments (α=.90); Victimization (α=.89); and Violation of norms (α=.86). Discriminant analysis established the existence of differences between groups of prosocial and antisocial students in the space defined by school safety variables. Differences between groups of prosocial students were determined in relation to violent behaviour (.766), unsafe school environment (.657) and victimisation (-.480). Differences between groups of antisocial students were determined in relation to violent behaviour (.975), victimization (-.239), unsafe school environment (.155) and violation of norms (.144). The absence of violent behaviour, victimization and a higher degree of safety in the school environment characterizes schools with a higher prevalence of prosocial student behaviour than antisocial. Therefore, promoting positive behaviour patterns in the school environment is important.
Taboo Topics in Children’s Literature: Lijeve Priče (Left Stories) by Alija Isaković
Authors: Pečenković Vildana , Pašić Kodrić Mirzana
Published: January 2025

The publication of Lijeve priče (Left Stories) by Alija Isaković (1990), although nearly unnoticed by contemporary literary critics, marked a turning point in Bosniak and Bosnian-Herzegovinian children’s literature at the end of the 20th century. In this only collection intended for the youngest readers, Isaković offered unexpected themes and initiated an unusual dialogue with young readers. Addressing them as equals, the author opens up a whole range of topics that had previously been taboo, such as sexuality, death, violence, and many others, which prior literary practice had avoided, offering an idyllic portrayal of childhood where there was no place for “serious” life situations. In this way, Isaković was among the first to free children’s literature from idealization and its utilitarian pedagogical dimension. This paper examines the themes that continue to qualify Lijeve priče as “inappropriate” for young readers today, as well as the justification for taboo topics in contemporary children’s literature.
Montenegro’s Open-Door Policy Towards the Ukrainian Refugee Crisis
Authors: Blagojević Jelisaveta
Published: January 2025

The aim of this work is to highlight how Montenegro has dealt with the Ukrainian refugee crisis, considering it represents the Western Balkan country with the highest number of refugees received. The theoretical framework of the work is based on Haas’s migration theory, as well as Fitzgerald and Arar’s study on understanding the concept of refugees. Accordingly, using methods of case analysis and content analysis of available documents, there is interpreted both the normative solutions in Montenegro related to the temporary protection of individuals from Ukraine and the available data regarding their access to fundamental rights under this regime. There is concluded that Ukrainian refugees, upon arriving in Montenegro, have achieved “positive liberty,” meaning they have received protection in a self-chosen destination country in line with a Montenegro’s legal framework aligned with European legislation.
Participatory Decision-Making, Job Satisfaction and Employees’ Innovative Work Behaviour among Small Retail Stores: Roles of Organisational Citizenship Behaviour and Employees’ Competencies
Authors: Amoah-Mensah Aborampah , Amerley Okorley Edna Naa
Published: January 2025

The study aims to examine the effects of participatory decision-making (PDM) on the innovation of workers of small retail stores in Kumasi, Ghana. It is also to analyse the mediating role of job satisfaction (JS) and the moderating roles of both organisational citizenship behaviour (OCB) and employee competencies (EC) between PDM and employees’ innovative work (EIWB). Based on the social exchange theory (SET), a sample of 723 workers from small retail stores is used for the study. The Partial Least Squares (PLS) and Structural Equation Modelling (SEM) are also adopted to test eight hypotheses. The research highlights the five variable relationships entailed in the model and therefore confirms SET in the Ghanaian retail industry. It is found that PDM has a positive link with JS and EIWB while PDM has an indirect connection with EIWB through JS. Also, the association between PDM and EIWB is strengthened by EC and weakened by OCB. Again, EIWB is positively influenced by JS, OCB and EC. The findings throw light on how policymakers and practitioners can improve EIWB in the retail industry.
The Role of Religiosity on Sustainable Consumption and Consumer Welfare Among Muslim Consumers
Authors: Al Hadi M. Qoshid
Published: January 2025

Due to global challenges related to sustainability and environmental protection, Indonesian consumers, especially Muslims, are increasingly considering religiosity in their consumption decisions. This study aims to examine the role of religiosity on sustainable consumption and consumer welfare among Muslim consumers. Data were collected from 10 provinces in Indonesia with a majority Muslim population of 340 respondents. The results of the analysis through SmartPLS 3.0 show that extrinsic religiosity can moderate the relationship between sustainable consumption and consumer welfare. However, this is not the same as intrinsic religiosity which has a positive but insignificant relationship. Moreover, this study also found factors that build sustainable consumption, including product perception and consumer commitment to the environment among Muslim consumers in Indonesia. The findings suggest marketers to focus on strategies that integrate consumer religiosity and green product perceptions to support sustainable consumption. Marketers also need to educate consumers about green products for the sake of prosperity.
PENGARUH MODEL PEMBELAJARAN SNOWBALL THROWING TERINTEGRASI SAINS TERHADAP MOTIVASI BELAJAR FIQIH DI MADRASAH IBTIDIAYAH
Authors: Nadhiroh Yulsiva Anissatun , Soraya Irma , Hamdani Asep Saepul
Published: January 2025

it because this science studies about sharia, siyasah, mamalah, ubudiyah, akhwal syaksiyah. Moreover, in matters of worship such as prayer, teachers should be able to correlate this with science. So that students can understand it completely by using their reason and faith in learning something. In the implementation of learning in the classroom, it was found that the value of the learning outcomes of Fiqh in class III decreased. Therefore, the teacher used a snowball throwing model of learning integrated with science to improve the learning outcomes of Fiqh in class III MI Hidayatullah, Blitar City. This study uses a quantitative method with descriptive data analysis and the Wilcoxon test. The results of this study were that 22 students out of 25 students in class III experienced an increase in their scores on the post-test. While the other 3 students still got the same score during the post-test. The average result of the fiqh score before being given treatment with the science-integrated snowball throwing method was 58.40 while the average score after being given treatment was 84.20. In the average section, the increase in the score was 11.50 and the number of positive rankings (Sum Ranks) was 253.00.
Effect of polysaccharide-coatings on the physicochemical properties and nutritional composition of deep-fried chicken breasts.
Authors: Okon Utibe Mfon , Nuamah Emmanuel , Jonathan Precious Peter , Essien Comfort Abel , Tushar Zahidul Hasan , Gardezi Zahra
Published: January 2025

Background: The consumption of deed-fried foods has been a topic of considerable debate in nutritional science due to its potential adverse effects on health. In this context, the method of coating deep-fried chicken breasts has garnered increasing attention.
Aims: This study aimed to provide valuable insights into the effects of alternative plant-based coatings on the physicochemical and nutritional properties of deep-fried chicken breast, with the broader objective of promoting healthier food options for consumers.
Materials and Methods: Pre-weighed, marinated chicken breast chunks were immersed in treatment batter made from various edible flour coatings, including wheat, sweet potato, cassava, and cocoyam. The samples were refrigerated and subsequently deep-fried. The fried products were analyzed for proximate and mineral composition, while breaded samples were examined for physicochemical properties.
Results: While coating did not affect the coating yield, it significantly increased frying yield (p < 0.0001) and pH (p = 0.0105). However, edible coatings did not significantly influence the lightness (p = 0.1481), redness (p = 0.3596), or yellowness (p = 0.6852) of the meat. Among proximate components, crude fiber and energy levels remained unchanged, but other parameters varied significantly across treatments (p < 0.05). Likewise, most mineral parameters, except magnesium, exhibited significant differences among coatings (p < 0.05). Notably, sweet potato coatings enhanced the physicochemical and proximate attributes more effectively than the other coatings, while cocoyam coatings yielded superior mineral composition compared to wheat flour.
Conclusion: Alternative plant-based coatings significantly influenced the physicochemical properties, nutrient composition, and mineral content of deep-fried chicken breasts. These findings suggest that utilizing such coatings could result in healthier fried chicken products. Further research is necessary to optimize these coatings for enhanced consumer acceptability and to support their integration into healthier dietary options.

Keywords: Frying medium, frying yield, meat color, mineral content, wheat flour substitutes.
СӨЙЛЕУ ТІЛІ ЖАЛПЫ ДАМЫМАҒАН ОҚУШЫЛАРДЫҢСӨЙЛЕМ ҚҰРАСТЫРУ ДАҒДЫЛАРЫН ҚАЛЫПТАСТЫРУ ЖОЛДАРЫ
Authors: Сабденова Б.А. , Олжабай Л.Д.
Published: January 2025

Арнайы білім беруді модернизациялау, сөйлеу бұзылыстарын түзетудің оңтайлы жолдарын үнемі ізденіп дәстүрлі және инновациялық жұмыс түрлерін қолдануды көздейді. Қазіргі кезде педагогтердің тәжірибелік қоржыны түзету жұмыстарында жоғары нәтижеге жеткізетін түрлі технология, әдістер мен құралдардың арсеналымен толыққан. Сөйлеу тілі жалпы дамымаған оқушылар сөйлем құрауда бірнеше қиындықтарға кездеседі, олар сөйлем құрылымы, сөздің орналасу тәртібі, сөйлемдердің аяқталмай қалуы мен грамматикалық қателіктердің жіберілуінде көрініс табады. СТЖД оқушылар негізінен қарапайым, аз ақпараттандырылған сөйлемдерді қолданады. Осыдан келе маңызды міндет - баланы сөйлемдерді дұрыс құрып және сөз арасындағы семантикалық және грамматикалық байланыстар туралы қарапайым түсінік қалыптастыру. Осы мақсатта арнайы түзету бағдарламалары мен әдістемелер қолданылып, сөйлем құрастыруға арналған жаттығулар жиынтығы оқушылардың сөйлеу тілінің дамуындағы бұзылыстарды түзету үшін маңызды рөл атқарады. Мұндай түзету жұмыстарының тиімділігі баланың жеке ерекшеліктерін ескере отырып жүргізілетін жүйелі және жан-жақты жұмысқа байланысты. Бұл жұмыстардың нәтижесінде оқушылар грамматикалық құрылымдарды меңгеріп, сөйлеу тілін еркін әрі дұрыс пайдалану дағдыларын игереді. Сондай-ақ, мектептегі оқыту бағдарламалары мен арнайы әдістемелер оқушылардың сөйлеу тілін дамытудың негізі болып табылады. Мұғалімдер бұл жұмыстарды жеке, топтық және сыныптық жаттығулар арқылы жүзеге асырып, әр баланың жеке көзқарасын қалыптастыруға ықпал етеді. Мұндай кешенді тәсілдер сөйлем құрастыру дағдыларын қалыптастырып, оқушылардың коммуникацияда ауызша және жазбаша сөйлеу тілін жақсартуға ықпал етеді.
Aerosol impacts on regional climate: chaotic or physical effect?
Authors: Feng Jiawang , Zhao Chun , Gu Jun , Li Gudongze , Xu Mingyue , Lin Shengfu , Feng Jie
Published: January 2025

Abstract. Aerosols have significant impacts on regional climate, which has been widely investigated with numerical experiments. However, uncertainties of simulated aerosol impact due to long-standing chaotic effect remain unclear. Here we propose a diagnostic method based on large ensemble simulations and random sampling algorithm to unveil the chaos-induced uncertainties in simulated aerosol climatic impacts that is overlooked in previous studies. Taking dust impacts on Indian summer monsoon system as a demonstration, our findings reveal that, while dust generally enhances the large-scale summer monsoon circulation consistently among ensemble members, its impacts on regional systems, such as monsoon depressions, exhibit significant chaotic effect: the simulated aerosol impacts on precipitation from individual ensemble member differ substantially, even inversely. Through quantitative analysis, we demonstrate that the magnitude of these chaotic effects diminishes following a N-½ relationship with ensemble size N. Furthermore, our results indicate that statistical significance testing alone may be insufficient for robust attribution of dust impacts, as even small ensembles can yield statistically significant yet contradictory results. This study emphasizes the necessity of employing adequate ensemble sizes to capture reliable physical impacts of aerosol on regional climate.
Aquatic metabolism influences temporal variations of water carbon and atmospheric carbon dioxide fluxes in a temperate salt marsh
Authors: Mayen Jérémy , Polsenaere Pierre , Regaudie de Gioux Aurore , Deborde Jonathan , Collin Karine , Le Merrer Yoann , Foucault Élodie , Ouisse Vincent , André Laurent , Arnaud Marie , Kostyrka Pierre , Lamaud Éric , Abril Gwenaël , Souchu Philippe
Published: January 2025

Abstract. Salt marshes are blue carbon (C) ecosystems characterized by intense atmospheric CO2 uptake and C sequestration but also organic and inorganic C exports through the tide. However, uncertainties on main biotic factors controlling vertical and horizontal C fluxes imply studying simultaneously terrestrial and aquatic metabolisms at small timescales (diurnal and tidal) and distinguish their contributions to net ecosystem CO2 exchanges (NEE). Within a temperature salt marsh, four sampling 24-h cycles were performed to measure water biogeochemical parameters (carbon and nutrients) and planktonic metabolism simultaneously to NEE successively at high tide (imported coastal waters influenced by the continental shelf) and low tide (exported channel waters influenced by the marsh). At high tide, water CO2 oversaturation due to aquatic heterotrophy was able to significantly reduce marsh atmospheric CO2 uptake at the ecosystem scale (NEE) during the highest immersion levels. At low tide, water pCO2 were also mainly controlled by marsh biological activity inducing large water CO2 oversaturation in winter due to heterotrophy and large water CO2 undersaturation in spring and summer due to autotrophy. In winter, the highest increases of dissolved inorganic carbon (DIC; from 2354 to 3963 µmol kg-1), total alkanity (TA; from 2508 to 4016 µmol kg-1) and dissolved inorganic nitrogen (DIN; from 27.7 to 68.4 µM) were measured at low tide night probably due to intense anaerobic respiration processes in channel waters and/or sediments resulting in the highest water pCO2 (up to 1461 ppmv). On the contrary, in spring and summer, large water pCO2 decreases and dissolved organic carbon (DOC) increases from high to low tide could be related to intense autochthonous and allochthonous aquatic primary production. Over the 24-h cycles, planktonic metabolism strongly influenced water pCO2 variations, especially at low tide, though planktonic communities did not play a major role in the atmospheric C balances at the ecosystem scale (NEE), accounting for only 10 % in spring.
Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts
Authors: Matthews Gwyneth , Cloke Hannah L. , Dance Sarah L. , Prudhomme Christel
Published: January 2025

Abstract. Forecasting river discharge is essential for disaster risk reduction and water resource management, but forecasts of future river state often contain errors. Post-processing reduces forecast errors but is usually only applied at the locations of river gauges, leaving the majority of the river network uncorrected. Here, we present a data-assimilation-inspired method for error-correcting ensemble simulations across gauged and ungauged locations in a post-processing step. Our new method employs state augmentation within the framework of the Localised Ensemble Transform Kalman Filter (LETKF) to estimate an error vector for each ensemble member. The LETKF uses ensemble error covariances to spread observational information from gauged to ungauged locations in a dynamic and computationally efficent manner. To improve the efficiency of the LETKF we define new localisation, covariance inflation, and initial ensemble generation techniques that can be easily transferred between modelling systems and river catchments. We implement and evaluate our new error-correction method for the entire Rhine-Meuse catchment using forecasts from the Copernicus Emergency Management Service's European Flood Awareness System (EFAS). The resulting river discharge ensembles are error-corrected at every grid box but remain spatially and temporally consistent. The skill is evaluated at 89 proxy-ungauged locations to assess the ability of the method to spread the correction along the river network. The skill of the ensemble mean is improved at almost all locations including stations both up- and downstream of the assimilated observations. Whilst the ensemble spread is improved at short lead-times, at longer lead-times the ensemble spread is too large leading to an underconfident ensemble. In summary, our method successfully propagates error information along the river network, enabling error correction at ungauged locations. This technique can be used for improved post-event analysis and can be developed further to post-process operational forecasts providing more accurate knowledge about the future states of rivers.
PENDAMPINGAN PERENCANAAN PEKERJAAN JALAN LINGKUNGAN DI DESA CIPEUTEUY KECAMATAN KABANDUNGAN KABUPATEN SUKABUMI
Authors: Sukmayu Saputri Utamy , Hidayat Muhammad , Damas Permadi Dio
Published: January 2025

Desa Cipeuteuy merupakan salah satu desa di wilayah Kecamatan Kabandungan, Kabupaten Sukabumi, Provinsi Jawa Barat. Seiring dengan bertambahnya kepadatan penduduk maka pembangunan infrastruktur juga harus ditingkatkan. Pembangunan yang dimaksud salah satunya adalah pembangunan jalan lingkungan. Pembangunan jalan di beberapa titik lokasi Desa Cipeuteuy dianggap perlu karena kondisi eksisting jalan telah banyak yang rusak dan ketika hujan menyebabkan genangan yang secara tidak langsung membuat pengguna jalan menjadi tidak nyaman. Selain itu kontruksi jalan yang ada dianggap tidak memenuhi standar yang berlaku sehingga perlu adanya pendampingan dalam proses perencanaan jalan lingkungan guna meminimalisir kegagalan fungsional. Tahapan yang dilakukan pada pendampingan kali ini meliputi tahap persiapan dan tahap pelaksanaan. Pada kegiatan persiapan dilakukan diskusi dan koordinasi dengan perangkat kelurahan terkait guna memberikan masukan yang bersifat membangun untuk kegiatan ini sedangkan pada tahap pelaksanaan dilakukan pengukuran sampai dengan penggambaran detail desain guna memperkirakan besarnya anggaran biaya untuk pekerjaan jalan lingkungan di Desa Cipeuteuy. Berdasarkan hasil pendampingan dapat diketahui bahwa besarnya dana untuk pekerjaan jalan lingkungan  di Desa Cipeuteuy adalah sebesar Rp 153.846.154,00. Hasil analisa biaya tersebut untuk selanjutnya dapat digunakan sebagai dasar dalam pelaksanaan pekerjaan konstruksi.
Pelatihan senam postur bagi pekerja imigran Indonesia di PCIM Malaysia
Authors: Khabib Abdullah  , Atik Swandari  , Nor Fadhilah Mochamad  , Nur Mukarromah  , Indah Nuraini
Published: January 2025

Warga Muhammadiyah di PCIM (Pimpinan cabang Malaysia) sebagian besar beranggotakan pekerja imigran dari Indonesia yang bekerja di sektor industri. Sebanyak 14 pekerja mengalami nyeri punggung bawah. Keluhan nyeri punggung bawah memang banyak dialami oleh masyarakat pekerja akibat duduk statis dalam waktu yang lama. Salah satu upaya yang dapat dilakukan adalah dengan latihan senam postur yang sudah teruji dalam menurunkan keluhan nyeri. Tujuan kegiatan ini adalah untuk meningkatkan pemahaman pada anggota PCIM tentang keluhan nyeri punggung bawah dan meningkatkan keterampilan mereka dalam melakukan senam postur untuk mencegah dan mengobati keluhan nyeri punggung bawah. Metode kegiatan adalah dengan penyuluhan dan mengajarkan keterampilan secara langsung. Hasil PKM ini adalah terjadi peningkatan pemahaman mitra terhadap patofisiologi nyeri punggung bawah sebesar 95% anggota, dan peningkatan keterampilan melakukan senam postur sebesar 80% anggota
The influence of processing parameters on the structure and properties of the low-carbon steel
Authors:   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Lutsenko V. A. , Golubenko T. М. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Lutsenko О. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine
Published: January 2025

The bar sections of the round diameter from the low-carbon steels of SAE brands requires continuous improvement of the reliable quality assurance system. The processes that include temperature-rate cooling parameters after hot rolling, which ensure the formation of the homogeneity of the structure and properties, are promising. Depending on the conditions of the hot deformation in the rolled steel products, can be observed the different structural states, which are fixed by cooling and determine the properties of the metal. If the metal is subjected to holding at the temperature of the end of deformation, then it undergoes the processes of collection recrystallization, which appears as the formation of the coherent nucleus, capable of the further growth. In the steels with low carbon content, after hot deformation, the austenite grain refining leads to a decrease in the size of pearlite areas. The formation of the large austenite grains due to the collection recrystallization leads to a decrease in the amount of structurally free ferrite. The most important microstructural parameter is grain size, which is one of the most effective ways to control the structure, leading to changes in mechanical properties. Investigated the bar sections of the low-carbon steels of SAE 1008 brands after hot rolling in the cleanliness wire block and cooling with water before allocation into wire wraps to different temperatures higher than А1, and then cooling in air to ambient temperatures. The metallographic studies allowed to establish the influence of the heat treatment parameters on the structure of the studied steel, which is ferrite with small areas of lamellar pearlite. After high-speed hot deformation, the average conditional grain diameter is affected by heat treatment, namely the temperature of the end of the cooling, was established by the conducted computational and analytical studies. For the rolled steel products of the SAE brands, it is rational to perform cooling after hot deformation to temperatures of the order of А1 + 150ºС with subsequent slow cooling, during which a more uniform grain is formed, which will ensure minimal variation in the mechanical properties.
Influence of chemical composition on the phase structure and hardness of carbon steel for railway axles after deformation and heat treatment
Authors:   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Povorotnia I. R. , Safronova O. A. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Podolsky R. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Oliinyk E. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine
Published: January 2025

Given the considerable number of complex approaches using information technologies to justify the choice of the content of chemical elements in steel and the limitations inherent in them, the use of the concept of directional chemical bonding is proposed, which ensures high predictive accuracy and obtaining the necessary properties at the level demanded by the consumer. The paper analyzes the requirements of regulatory documentation regarding the chemical composition, namely the content of the main components such as carbon, manganese and silicon, in steel for railway axles of grades EA1N, F and OC. Information technologies were applied using the concept of directed interatomic interaction, when the criteria are complex and characterize the entire composition simultaneously, and linear patterns of the influence of the integral indicator of the chemical composition on hardness were obtained. The purpose of the study is to establish the patterns of the influence of chemical composition on the formation and transformation of the phase structure and hardness after deformation and thermal annealing of carbon steel for railway axles The object of research was laboratory ingots of carbon steels, which are comparable in chemical composition to steels for railway axles in accordance with state, European and American standards. The samples made from them were subjected to hot plastic deformation (HPD) followed by heat treatment (HPD+HT). A microstructural analysis of the studied steels was carried out. The regularities of the influence of chemical composition on the phase ratio and hardness of the studied steels in different states were revealed: as-cast, after HPD and HPD+HT using the concept of directional chemical bonding. It was established that for an integral parameter of the charge state (ZY) less than 1.20 e, that is, for a certain chemical composition in the studied interval of values, the hardness of steel in the state after GPA exceeds the hardness of such steel in the state after HPD+HT.
Development of the universal method for predicting the density of briquettes from dry fine-fractional materials based on the results of a comparative study of compression factors
Authors:   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Khudyakov O. Yu. , Vashchenko S. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Bayul K. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Semenov Yu. S. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Krot P. V. ,   Wroclaw University of Science and Technology
Published: January 2025

Most of the known models for predicting the density of powdered materials are empirical in nature and cannot be applied to a wide range of materials. In order to create a universal method for predicting density, a comparative study of the influence of technological factors on the compressibility of powders was performed in this paper, and the fundamental connections between compressibility and the physical and energy properties of the charge particles were established. Using the method of two-factor analysis of variance (two-way ANOVA), the influence of size and the nature of dry powder’s particles on the compression intensity factor was compared. It was found that under conditions when the size of large and small particles differs by no more than one order of magnitude, the dominant factor affecting the compression of the powder is the characteristics of the nature of the particles. Reliable connections between the compressibility of powders and thermodynamic, thermal (melting point, heat of sublimation, etc.) and mechanical (Young's modulus, shear modulus, hardness, etc.) properties of the particle substance have been obtained. We also obtained statistical correlations between the compressibility of powders and the energy characteristics of the crystalline substance of the powder particles: the energy of the crystal ion lattice, the energy of atomization, and the energy of the core-electron interaction. The maximum closeness of correlation of the dependences is estimated by the Chaddock scale as high and very high. Based on the above dependencies, a multiple regression model of the combined effect of the energy and structural characteristics of the particles’ crystal lattice of on the compressibility of a powder was developed. The coefficient of determination of the model is 0.98. Also, using the obtained dependencies, a universal method for predicting the density of dry powder compacts depending on the applied pressing pressure was developed. The prediction error when applying the method does not exceed 9.5%. The developed method can be used to perform, without conducting experimental studies, a preliminary assessment of the possibility of achieving the required briquette density, selecting technological modes, determining the energy and power characteristics of the process and technical characteristics of pressing equipment.
Pertanggungjawaban Hukum Bagi Pelaku Tindak Pidana Permufakatan Jahat Untuk Melakukan Tindak Pidana Terorisme (Studi Kasus Putusan Pengadilan Negeri Jakarta Utara Nomor 1137/Pid.Sus.Teroris/2020/PN Jkt.Utr)
Authors: Setiawan Erry , Nachrawi Gunawan
Published: January 2025

Terorisme bukan hanya merupakan tindakan kekerasan, tetapi juga merupakan pelanggaran hak asasi manusia, termasuk hak untuk hidup dan keamanan. Pelaku sering kali bertindak secara berkelompok, yang melibatkan dua orang atau lebih. Penelitian ini mengkaji pertanggungjawaban hukum pemufakatan jahat dalam tindak pidana terorisme dan menganalisis pertimbangan hakim dalam putusan No. 1137/Pid.Sus.Terorisme/2020/PN Jkt.Utr. Dengan menggunakan pendekatan yuridis normatif, penelitian ini didasarkan pada bahan hukum primer yang meliputi undang-undang, asas-asas hukum, dan peraturan-peraturan. Menurut Pasal 88 KUHP, pemufakatan jahat terjadi ketika dua orang atau lebih bersepakat untuk melakukan kejahatan. Pemufakatan jahat dalam tindak pidana terorisme (samenspanning) diatur dalam Pasal 15 Perpu No. 1 Tahun 2002 tentang Pemberantasan Tindak Pidana Terorisme. Undang-undang ini menyatakan bahwa mereka yang melakukan permufakatan jahat, menghasut, atau turut serta melakukan tindak pidana terorisme diancam dengan pidana maksimal pidana mati. Dalam putusan No. 1137/Pid.Sus.Terorisme/2020/PN Jkt.Utr, Abdul Kadir Afiudin alias Abu Thalha dijatuhi hukuman 3 tahun 6 bulan penjara. Perbuatannya memenuhi unsur Pasal 15 Jo Pasal 7 UU No. 5 Tahun 2018 tentang perubahan atas UU No. 15 Tahun 2003 tentang pemberantasan tindak pidana terorisme.
EVALUATION OF VENTILATED CAVITY WALL DESIGN FOR PASSIVE COOLING OF INDOOR SPACES
Authors: Akubue J. A.
Published: January 2025

The function of building facades includes the regulation of solar-radiated heat. It also includes regulating the ranges of heat transfer from the exterior to the interior of a building. The primary functions of building facades promote energy conservation, hence making the art of façade design a vital energy-efficient option in sustainable building.  The concept of a ventilated cavity wall is presented in this paper as an option that functions as a barrier for trapping excessive heat radiated naturally through building envelopes, while at the same time utilizing ventilation of the cavity space in its double layer to control the heated façade through aeration of the cavity space. A review of modern active multi-skin façade systems adopted by designers reveals the climate-responsive ideas associated with double-skin facade designs. This study emphasizes the function of the ventilated cavity wall as a climate-responsive system that passively enables the cooling of indoor spaces. For this purpose, a study of a sample of this design was conducted to ascertain the thermal control properties. The study includes an experimental evaluation and thermal simulation of the sample model using the Phoenix-VR application. The results of the interior air temperature and internal façade cavity conditions reveal that this façade system may substantially reduce the thermal effect on building walls. This is seen in the significant decrease of the indoor room temperature by up to 5oC compared to the cavity air temperature. The result provides a good premise for designers to adopt the principles of the ventilated cavity wall system in building designs. For application, residential homes that adopt the ventilated cavity wall option may further improve indoor thermal conditions through whole building orientation or by indoor space orientation. The indoor spatial orientation if properly managed during the building design process may add to the energy conservation potential
Construction of Enterprise Human Resource Information Security Management Platform Based on Data Mining Algorithms
Authors: JinZhao Song
Published: January 2025

The theoretical basis of the concept of organizational support is social exchange theory, and organizational support is actually the social exchange relationship between employees and the organization. This paper combines the data mining technology to analyze the impact of organizational support on employee creativity. Moreover, according to the characteristics of enterprise management data, this paper proposes an immune algorithm-based enterprise management data mining algorithm, and constructs an intelligent analysis model based on data mining. Through data mining, it can be found that the sense of organizational support has a certain impact on the creativity of employees, and the sense of organizational support can effectively improve employees' work communication and work efficiency, and enhance their creativity. Moreover, it plays an important role in supporting the development of the enterprise and the personal development of employees.
Robust Control of Robot Dexterity Operation Based on Harmony Search Genetic Algorithm
Authors: Zhaolan He,, Xingrong Zhu, Shuming Jia, Cong Xue
Published: January 2025

In response to the characteristics of multiple variables, uncertain parameters, complex structure, and strong coupling in the agile operation control system of robots, an adaptive genetic algorithm with cross probability and mutation probability is adopted to improve the control rate and steady-state accuracy of the control system. Integrating harmony search algorithm thinking with genetic algorithm to further optimize the parameters of the robot's agile operation controller in the initial population generation process. The simulation has verified that the optimization algorithm can effectively improve the control efficiency, steady-state accuracy, and robustness of the controller, and can ensure that the overshoot value of the system is within an appropriate range.
Blockchain Security for IoT Devices in Autonomous Vehicle Networks
Authors: T M Swathy
Published: January 2025

The integration of Internet of Things (IoT) devices in autonomous vehicle networks (AVNs) has revolutionized transportation by enhancing communication and real-time decision-making. However, this increased connectivity also raises significant security concerns, as IoT devices are vulnerable to data breaches, tampering, and unauthorized access. Blockchain technology, with its decentralized and immutable structure, offers a promising solution for enhancing security in these networks. This paper explores the application of blockchain in securing IoT devices within AVNs, focusing on its ability to ensure data integrity, protect privacy, and provide decentralized security mechanisms. A detailed analysis of blockchain’s architecture, including its consensus mechanisms and smart contracts, is presented. The paper also highlights the challenges, such as scalability and resource constraints, associated with blockchain implementation in IoT environments. Additionally, potential solutions, including lightweight blockchain protocols and integration with edge computing, are discussed. By addressing these challenges, blockchain technology can significantly improve the security and resilience of IoT devices in AVNs, ensuring safer and more reliable autonomous transportation systems.
Experimental Study on the Effect of a Bifurcated Apex on the Vibration of a Wind Turbine Tower
Authors: Weimin Wu
Published: January 2025

Aiming at the vibration problem of wind turbine towers, an improved design method of bifurcated blade tip and end wing is proposed. By testing the vibration characteristics of the tower, the related frequency and acceleration amplitude of the tower before and after the modification design is measured, and the influence of the fork tip with different tip Angles on the vibration characteristics of the tower is studied. It is concluded that the basic amplitude and the second-order amplitude of the axial and radial acceleration corresponding to the vibration of the tower can be reduced by the split tip end wing. Therefore, the split tip end wing can effectively reduce the vibration of this wind turbine tower. Since the effect of vibration reduction is related to the tip Angle of the split tip end wing, this provides a new idea for the study of wind turbine tower vibration reduction.
The Role of AI and Machine Learning in Enhancing Cyber Security in Cloud Platforms
Authors: Nilesh P. Sable
Published: January 2025

The growing reliance on cloud platforms has introduced a heightened need for robust cybersecurity measures. Traditional security methods, while effective, struggle to keep pace with evolving cyber threats. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in enhancing cloud security, offering dynamic and automated approaches to threat detection, prevention, and response. This paper explores the critical role of AI and ML in addressing key cybersecurity challenges within cloud environments. It reviews various AI/ML techniques such as supervised learning, deep learning, and reinforcement learning, demonstrating their effectiveness in identifying vulnerabilities and responding to sophisticated cyberattacks. Through a discussion of real-world case studies, the paper highlights the advantages of integrating AI/ML models in cloud security architectures. Additionally, the paper identifies existing limitations, such as adversarial attacks on AI systems and ethical concerns related to data privacy. Finally, it outlines future directions for leveraging AI/ML in creating proactive, adaptive, and secure cloud environments.
Advanced Control System for Real-Time Regulation of Dissolved Oxygen in Aquaculture Systems
Authors: Vu Ngoc Kien, Nguyen Phuoc Tri
Published: January 2025

Dissolved oxygen (DO) is a critical characteristic in aquaculture systems, regulating the health, development, and production of aquatic species. Maintaining adequate DO levels is essential for avoiding hypoxia, which can cause stress, sickness, and even death in fish and other animals. Traditional DO regulation relies on manual interventions and fixed aeration strategies, which cannot quickly adapt to environmental changes, causing inefficiencies and potential aquaculture productivity risks. Research presents a control system for real-time regulation of dissolved oxygen in aquaculture systems. The proposed system uses Intelligent Satin Bowerbird tuned Dynamic Logistic regression (ISB-dynamicLR) to effectively forecast DO levels while addressing excessive noise and poor data quality. The sensor data are collected continuously, providing a basis for real-time monitoring of DO levels. The data was preprocessed and decomposed into multiple frequency components using Discrete Wavelet Transforms (DWT). The Control system adjusts aeration rates and water circulation in response to predicted DO levels, providing a dynamic and adaptive solution for DO regulation. The proposed system combines dynamicLR for regression-based estimation and ISB to optimize dynamicLR parameters and kernel functions, providing robust and efficient prediction. The results demonstrate that the proposed model achieved excellent accuracy, with various error parameters such as RMSE (0.0091), MSE (0.0005) and operating time (1.92s). The system also demonstrated superior computational efficiency and outperformed traditional models. The high throughput, accuracy, and real-time capability of this system make it an ideal choice for automated DO regulation in water quality monitoring systems for aquaculture.
A Hybrid Particle Swarm Optimization (PSO) and Sine Cosine Algorithm (SCA) for Feature Selection in Lung Cancer Detection
Authors: Lina Jamal. Alhashimi
Published: January 2025

Feature selection is known to significantly improve the performance of the machine learning approach in cases of lung cancer. This research presents a PSO-SCA fusion feature selection mechanism. The proposed approach combines the advantage of the global search capacity of SCA with the local optimization capabilities of PSO to avoid premature convergence. The performance of the proposed hybrid PSO-SCA was tested using public lung cancer datasets with SVM and k-NN as benchmark classifiers. The experiments also showed a marked enhancement in the classification rate against the separate approaches as PSO, SCA, GA, as well as ACO and other feature selection methodologies. Using the SVM classifier, the proposed hybrid model of PSO-SCA yielded an overall classification accuracy of 92.8% and was found to be superior to the algorithms in terms of accuracy, precision, recall, and F1-score. It was also observed that the method proposed in this paper has also offered better computational efficiency with fewer iterations to achieve convergence. These findings show that the PSO-SCA technique can be applied in the practical diagnostic domain.
Efficient and Fine-grained Profile Matching with Privacy Preserving in Mobile Social Networks
Authors: Rohini Bhosale
Published: January 2025

The proliferation of the internet and smart devices has dramatically increased the user count of Mobile Social Networks (MSNs). Connecting with new users is the core feature of MSNs. The increased number of active users on MSNs highlights the need for efficient and effective profile-matching and recommendation mechanisms. This paper introduces a novel framework for dynamic friend matching and recommendation by using advanced classification and clustering techniques. To improve matching results in the user connection as per social characteristics and behavior, the suggested framework combines ideal clustering using the Outline Coefficient and Davies-Bouldin Record with K-Means clustering. We propose a hybrid fine-tune ensemble classifier that blends the best aspects of the Random Forest and XGBoost methods. The hybrid model of grouping users has improved the accuracy of friend recommendations. A 95.23% classification accuracy is obtained by the ensemble classifier by combining the strong feature selection and averaging of Random Forest with the gradient boosting of XGBoost. The Davies-Bouldin Index and Silhouette Coefficient are applied to the clustering step to find the ideal number of clusters to provide cohesive and well-separated groups. These well-defined groups are then used in the K-Means algorithm, providing a basic structure for future matching and recommendation processes. Experimental results have demonstrated the efficiency of the proposed hybrid model.
Identifying Ransomware Behaviour for Early Detection and Prevention: A Pre-Encryption Analysis Approach to Halt Cyber Invasions
Authors: Srijita Bhattacharjee
Published: January 2025

Ransomware might be a kind of extortion in which digital documents are rendered inaccessible until a ransom is paid. Protecting against the growing number of ransomware attacks is seen as a difficult undertaking due to the necessity for knowledge on newly discovered malware and constantly developing families or variants. As a result, there is a need to investigate convincing techniques to detecting and reducing ransomware assaults by analysing their behavioural patterns prior to encryption. Using the Pre-attack API calls, these ransomwares may be assigned to recognised malware families. Discovery avoidance strategies include making a sequence of pre-attack API calls to fingerprint the environment and avoid execution in a virtual environment. This might be the first step in recognising and mitigating such risks. Furthermore, this discovery may be used to identify ransomware and beneficial applications before encryption utilising APIs. This study also effectively found the APIs that may distinguish between ransomware and goodware. We have found twelve APIs present typically in ransomware but less in goodware and fifteen APIs were more prevalent in goodware than ransomware.
An Analysis of Emerging Cybersecurity Threats in Cloud Computing
Authors: Prerna Patil
Published: January 2025

As cloud computing becomes increasingly integral to modern infrastructures, the need for robust cybersecurity measures has grown significantly. This paper examines emerging cybersecurity threats in cloud computing, focusing on advanced attacks like data breaches, virtualization vulnerabilities, insider threats, Distributed Denial of Service (DDoS) attacks, and Advanced Persistent Threats (APTs). It explores mathematical models for assessing threat probabilities, evaluating encryption efficiency, and quantifying risk. The study also investigates key security strategies, such as encryption, identity management, and incident response, to mitigate these risks. Additionally, compliance with global standards such as ISO 27001, NIST, and GDPR is analyzed to understand the challenges of maintaining secure multi-cloud environments. Through case studies of recent cloud security incidents, this research highlights critical lessons and provides actionable insights for strengthening cloud security frameworks. The paper concludes by discussing future trends, including artificial intelligence, machine learning, and quantum computing, and their potential impacts on cloud cybersecurity. By addressing these emerging threats and trends, the study aims to provide comprehensive guidance for enhancing cloud security.
Defect Image Generation Algorithm of Commutator Based on Generative Adversarial Networks
Authors: Xianjun Tang
Published: January 2025

At present, there have been many studies on the application of deep learning algorithms in defect detection work. Based on the object detection algorithms introduced earlier, a defect image recognition system is constructed to detect various types of defects in the converter, which can save manpower and material resources and improve the safety of this work. However, deep learning algorithms require a certain amount of valid samples to be effective. However, in actual operation, it is difficult to collect defect images of the commutator, which means that there are situations where the requirements of deep learning detection algorithms cannot be met. This article aims to explore a feasible data augmentation scheme, which is to generate effective samples through generative adversarial networks. This article will investigate two classic image generation methods based on Generative Adversarial Networks (GANs). And apply it to the field of generating defect images for commutators, propose a method for generating defect images in a directional manner, and compare it with the above two methods. The experimental results show that our method has a higher FID value compared to the above two methods, and has a more similar data distribution compared to real images.