bluuebunny/crossref_metadata_2025 huggingface dataset:
Peran Guru Pendidikan Agama Katolik dalam Mengatasi Kecanduan Gadget pada Siswa
Authors: Bukit Friska Natalia , Sembiring Mimpin
Published: August 2024

Purpose – Gadget addiction is a condition where a person is said to be a gadget addict when they spend most of their time playing gadgets. Gadget addiction is a condition in which a person experiences excessive dependence on the use of electronic devices, such as cell phones or tablets, thus disrupting their daily life and health. The purpose of this study is to find out how the condition of gadget addiction in students and to find out the role of Catholic religious education teachers in overcoming gadget addiction in students.Method – The research method conducted by the author is Using qualitative methods, data was collected through observation, interviews, and documentation.The result of observations and interviews Data processing techniques through data reduction, data display, and conclusion drawing.Findings – The research findings show the high level of gadget addiction in students and in overcoming students' gadget addiction, teachers play five roles, namely as role models by giving examples of deactivating gadgets before learning, as learning managers by making lesson plans and using methods that are suitable for students, as motivators by motivating students such as giving positive praise and punishment, as facilitators by preparing books, and as facilitators by preparing books for students. Research Implications – The implication of this study shows that the high gadget addiction among SMA Negeri 1 Delitua students affects their academic productivity, mental health, and social interaction. PAK teachers act as role models, learning managers, motivators, facilitators, and mentors, which are effective in reducing gadget addiction in students.
Efektivitas Model Pembelajaran QODE dan Discovery Learning untuk Meningkatkan Berpikir Kritis Siswa SMP dalam Pelajaran IPA
Authors: Rizkia Anisa , Zahrotin Anis , Agnafia Desi Nuzul
Published: August 2024

Purpose – The purpose of this research is to find out how well students' critical thinking skills are in learning science, especially in mixed materials, by using the QODE (Questioning, Organizing, Doing, and Evaluating) and Discovery Learning models.Method – This research method applies quantitative methods. This study involved 49 students from class VIII A and VIII B as subjects with details of 25 students of class VIII A and 24 students of VIII B from SMP Negeri 2 Paron. The data analysis technique used prerequisite test analysis. The data analysis technique uses prerequisite analysis in the form of validity, reliability, normality, and homogeneity tests, while the hypothesis test uses an independent sample t-test.Findings – The QODE learning model is more effective in improving critical thinking skills compared to the Discovery Learning learning model on mixed materials at SMP Negeri 2 Paron with an average posttest value of 81.96> 78.00. The results of the hypothesis test of the posttest value proved that the tcount> ttable (1.677) while the tcount (QODE) was 2.138 and the tcount (Discovery Learning) was 2.128. This indicates a significant difference in the post-test results, which leads to the rejection of H0 and acceptance of H1 which indicates the effectiveness of the model. The result of the t-test value of QODE > Discovery Learning is 2.138 > 2.128 so it can be concluded that the QODE learning model is more effective than Discovery Learning in improving critical thinking in science lessons, especially mixed material for students of SMP Negeri 2 Paron. Research Implications – Students' critical thinking skills can be improved with QODE and Discovery Learning when learning science, especially mixed materials at SMP Negeri 2 Paron where the QODE model is more effective than Discovery Learning.
Penggunaan Media Ritatoon untuk Meningkatkan Pengetahuan Seksual Anak Usia Dini
Authors: Amanda Yosi Nur Annisa , Indryani Indryani , Utami Winda Sherly
Published: August 2024

Purpose – Knowledge of sexuality is crucial from an early age because it can help children avoid sexual harassment and prevent gender bias. This study aims to find out whether Ritatoon media can affect sexual knowledge of children aged 5 to 6 years in PAUD Melati 2 in Jambi City.Method – The research was conducted using a pre-experimental design of One-Group Pretest-Posttest Design, total sampling, and a non-probability approach, purposive sampling type. The data analysis techniques used included t-test hypothesis testing with prerequisite tests of homogeneity and normality..Findings – The research results show that the average pre-test score is 15.111 and the average post-test score is 21.889 with a total score of 197. The t test results show that the value of t count is 30,500, which is the same as the t table of 2.365, so t count > t table shows that there is The influence is on strong interpretation with a value of 3.17 which is in the range > 1.00 with strong interpretation (Strong Effect). Calculated results showed that the average pre-test score was 15.111 with a total score of 136, and the average post-test score was 21.889 with a total score of 197. The average final test score was higher than the average initial test score of 6.778, which shows that Ritatoon media has an impact on children's sexual educationResearch Implications – The study's findings suggest that ritatoon media can be utilized as a teaching tool to help kids between the ages of five and six build their sexual literacy by giving them more insight into and information about learning activities that can help them become more sexually knowledgeable. via media and education, and serve as a resource for educators doing exercises aimed at promoting early sexual education.
Penerapan Model Kirkpatrick dalam Evaluasi Program Pelatihan Kepemimpinan Perempuan di Pusat Pengembangan Sumber Daya Wanita Pasoendan Digdaya
Authors: Gouvany Ayu Laras , Siregar Herlina , Darmawan Dadan
Published: August 2024

Purpose – The purpose of this study was to evaluate how participants responded to the women's Leadership Training Program held by the Pasoendan Digdaya women's Resource Development Center (PPSW) in Lebak regency, Banten. To measure participants ' satisfaction with the training program, this evaluation used the Kirkpatrick reaction Level Model.Method – This study was designed to use descriptive qualitative methods. Data were collected through interviews with 10 trainees. The questionnaire addresses various things, such as the relevance of the material, instructor performance, and training facilities. To determine the level of satisfaction of participants, descriptive was used to analyze the data.Findings – The results indicated that participants were generally satisfied with the training program. The training and consumption schedules have been adjusted to meet the needs of the trainees, and the material presented is considered relevant and applicable. However, the instructor is considered to have strong presentation skills. Additionally, the media and facilities used received positive responses, although there are some suggestions for improvements. Research Implications – Providing women with leadership opportunities significantly advances gender equality by ensuring equal access for both women and men. The findings indicate that while the overall training program effectively meets participants' needs, there is room for improvement in the facilitators' skills and the customization of training materials. It is recommended that PPSW Pasoendan Digdaya enhance facilitator competencies and tailor training content more closely to the specific needs of the participants. This study also highlights the potential for further research into effective teaching methods to bolster women's leadership capabilities.
Evaluasi Program Literasi Membaca Sekolah Dasar di SD Negeri 1 Kedungjati Menggunakan Model Goal Free Evaluation
Authors: Nugroho Christopher Dean Arfie , Mawardi Mawardi
Published: August 2024

Purpose – Based on a survey conducted by the Program for International Student Assessment (PISA) released in 2019, Indonesia is ranked 62nd out of 70 countries, placing it among the bottom 10 countries with low literacy levels. In response, the Indonesian government promoted the School Literacy Movement (GLS), a comprehensive initiative aimed at transforming schools into learning organizations where all members are literate for life, with the involvement of the community. The purpose of this study was to evaluate the reading literacy movement program at SD Negeri 1 Kedungjat.Method – This research employs a descriptive qualitative design. The study employs the Goal-Free Evaluation model, which enables researchers to evaluate the program without concentrating on its specific goals. Data collection techniques include document studies, observations, and interviews. Data analysis techniques used in this research follow the Miles and Huberman approach, which involves data collection, data reduction, data presentation, and conclusion drawing, with the data presented in descriptive text form.Findings – According to the study findings, the reading literacy movement involves instilling a 15-minute reading habit before commencing lessons. Supporting factors within this movement include a diverse range of reading materials, a conducive environment, and well-equipped libraries. The research indicates that the implementation of the reading literacy movement has been successful and has yielded positive outcomes, despite not being uniformly distributed across all classes. Research Implications – This study outlines the beneficial effects of the school literacy movement on students' reading interest, leading to an increased enthusiasm for reading. Furthermore, it demonstrates that the literacy movement enhances students' comprehension levels.
Transformasi Kompetensi Profesional Guru Melalui Supervisi Akademik Model Artistik di Kabupaten Pidie
Authors: Salminawati Salminawati , Sariakin Sariakin , Novita Rita
Published: August 2024

Purpose – The purpose of this research is to determine how to enhance the professional skills of teachers at SDN Keune, Pidie Regency, through the application of an artistic model in academic supervision, as observed in teachers' abilities to develop lesson plans/modules and conduct teaching.Method – The research method applied is School Action Research (SAR), aimed at addressing issues related to teachers' abilities in developing lesson plans/modules, conducting teaching, and their professional competencies which are still low within the school environment, while simultaneously seeking solutions to resolve them. Three teachers were selected as research subjects due to their relatively low professional competency levels, with an average professional competency score of 62.44. The selected teachers are from grades II, IV, and V at SDN Keune, Pidie Regency. This research follows a four-stage cycle: planning, action, observation, and reflection.Findings – The artistic model of academic supervision effectively improved teachers' professional competence. Initially, lesson plans/modules were inadequate, scoring 70.83 in Cycle I and improving to 86.11 in Cycle II. Teacher performance in lesson delivery scored 73.81 in Cycle I, rising to 86.90 in Cycle II. Professional competence increased from 71.67 in Cycle I to 88.33 in Cycle II. Research Implications – School supervisors play a crucial role in enhancing teachers' professional competencies through academic supervision. However, this study is limited in its applicability beyond SDN Keune and may be influenced by the researcher's biases in interpreting qualitative data and observations. Additionally, the focus on a small number of teachers limits the generalizability of the findings. Future research should consider a larger sample size and a more diverse range of schools to validate and expand upon these findings.
Foliar application of nutrient formulation enhances the post-harvest quality of tuberose (Agave amica Medik.) cv. Arka Prajwal
Authors: Arunkumar M , Keisar Lourdusamy D , Chitra R , Pazhanivelan S , Raju M , Vakeswaran V
Published: August 2024

A study was conducted at the Department of Floriculture and Landscape Architecture Laboratory to investigate the influence of various nutrient formulations on the post-harvest quality of tuberose using a knapsack sprayer and drone. The treatments involved spraying macro and micronutrients along with growth regulators at different concentrations. Throughout the experiment, all parameters were recorded at 2 days intervals. Drone spray of MN mixture + 0.5 % poly feed + 0.6 % humic acid + 150 ppm GA3 recorded the maximum plant post-harvest quality attributes over other treatments. It showed increased post-harvest quality attributes, including relative water content percentage of flower (95.15 %), physiological loss of weight percentage of flower (14.83 %), shelf life at room temperature (3.79 days) and vase life (12.45 days). Additionally, the treatment was found to be the best for parameters of water uptake (38.45 g) and percentage of floret opened (27.02). Plots treated with drone spray of MN mixture + 0.5 % poly feed + 0.6 % humic acid + GA3 at 150 ppm showed a reduced rate of transpiration loss of water (14.89 g) and electrolyte leakage (12.52). The experimental findings demonstrated that foliar application of nutrients along with growth regulators at different concentrations using drones improved the post-harvest quality of tuberose.
A column study on Cu (II) adsorption from synthetic solutions using phyto-mineral hybrid adsorbents: RSM optimization, regression modeling and isotherm studies
Authors: Rehman Hafeez-u- , Akhter Faheem , Ahmed Jawad , Lakhmir Mansoor Ahmed , Arain Haris Jawad , Ahsan Muhammad Junaid , Bhurgri Shareen , Laghari Niaz Muhammad
Published: August 2024

Herein we report a novel approach to synthesize hybrid adsorbents using moringa oleifera and zeolite. Three variants were prepared using zeolite mass fractions % of 0.25 %, 0.5 % and 0.75 % respectively. The hybrid adsorbents were investigated for Cu (II) removal from synthetic wastewater using fixed bed column. The lab-scale fixed bed column was designed for Cu (II) removal and optimized using Response Surface Methodology (RSM). The variable parameters included bed height, flow rate, metallic concentration and zeolite mass fraction %. As per results, higher zeolite mass fraction resulted in higher Cu (II) removal. Similarly, the higher bed height increased the removal % of Cu (II). On the other hand, both higher flow rate and metallic concentrations resulted in a declined removal. The highest removal of Cu (II) ions was indicated by hybrid adsorbent with zeolite mass fraction of 0.75 % with 96 % at 1 mL/min flow rate, bed height of 3 cm and metallic concentration of 5 ppm respectively. The maximum adsorption capacities (Qm) indicated by hybrid adsorbents were 19 mg/g (0.25 % Mass Fraction Z), 21.5 mg/g (0.5 % Mass Faction Z) and 24.5 mg/g (0.75 % Mass Fraction Z). The adsorption data best fitted Langmuir Isotherm with R2 value of 0.99 for all variants. When the adsorption data was analyzed using isotherms, data by all three variants best fitted Langmuir isotherm with R2 values of 0.99 for all the variants. Conclusively, higher mass fraction % of zeolite enhanced the removal capacity of Phyto-mineral hybrid adsorbents for Cu (II), whereas higher flow rates and metal concentrations resulted in a declined adsorption of the respective metal ions.
Yugoslav Youth Labor Actions in Documentary Film: Organization, Internationalism, and Reminiscing
Authors: Matošević Andrea
Published: August 2024

This article analyzes several documentary films on youth labor actions in socialist Yugoslavia, covering different stages of their organization. The analysis begins with educational films that outline recommended practices for the successful organization of youth labor actions. It continues with two films, shot 20 years apart, portraying international experiences of youth labor actions. These films, “Witnesses to the truth” (Svjedoci istine) from 1950 and “American woman” (Amerikanka) from 1970, articulate criticism in different ways, in keeping with when the films were made. The last film analyzed, Ho-Ruk! Ho-Ruk! Ho-Ruk! – filmed in 1974 – reflects on 30 years of experience of youth labor actions. Periodizing the films in this way presents three different views of youth labor actions, namely what they should become, what they are, and what they used to be.
A Moderate Blood Flow Restriction Pressure Does Not Affect Maximal Strength or Neuromuscular Responses
Authors: Lubiak Sean M. , Lawson John E. , Gonzalez Rojas David H. , Proppe Christopher E. , Rivera Paola M. , Hammer Shane M. , Trevino Michael A. , Dinyer-McNeely Taylor K. , Montgomery Tony R. , Olmos Alex A. , Sears Kylie N. , Bergstrom Haley C. , Succi Pasquale J. , Keller Joshua L. , Hill Ethan C.
Published: August 2024

Lubiak, SM, Lawson, JE, Gonzalez Rojas, DH, Proppe, CE, Rivera, PM, Hammer, SM, Trevino, MA, Dinyer-McNeely, TK, Montgomery, TR, Olmos, AA, Sears, KN, Bergstrom, HC, Succi, PJ, Keller, JL, and Hill, EC. A moderate blood flow restriction pressure does not affect maximal strength or neuromuscular responses. J Strength Cond Res XX(X): 000–000, 2024—The purpose of this study was to examine the acute effects of blood flow restriction (BFR) applied at 60% of total arterial occlusion pressure (AOP) on maximal strength. Eleven college-aged female subjects completed two testing sessions of maximal unilateral concentric, isometric, and eccentric leg extension muscle actions performed with and without BFR. Separate 3 (mode [isometric, concentric, eccentric]) × 2 (condition [BFR, no BFR]) × 2 (visit [2, 3]) repeated-measures analysis of variances were used to examine mean differences in maximal strength, neuromuscular function, rating of perceived exertion (RPE), and pain. For maximal strength (collapsed across condition and visit), isometric (128.5 ± 22.7 Nm) and eccentric (114.5 ± 35.4 Nm) strength were greater than concentric maximal strength (89.3 ± 22.3 Nm) (p < 0.001–0.041). Muscle excitation relative (%) to isometric non-BFR was greater during the concentric (108.6 ± 31.5%) than during the eccentric (86.7 ± 29.2%) (p = 0.045) assessments but not different than isometric (93.4 ± 17.9%) (p = 0.109) assessments, collapsed across condition and visit. For RPE, there was an interaction such that RPE was greater during non-BFR (4.3 ± 1.7) than during BFR (3.7 ± 1.7) (p = 0.031) during the maximal concentric strength assessments. Furthermore, during maximal strength assessments performed with BFR, isometric RPE (5.8 ± 1.9) was greater than concentric (3.7 ± 1.7) (p = 0.005) and eccentric (4.6 ± 1.9) (p = 0.009) RPE. Finally, pain was greater during the isometric (2.8 ± 2.1 au) than during the concentric (1.8 ± 1.5 au) (p = 0.016), but not eccentric, maximal strength assessments (2.1 ± 1.6 au) (p = 0.126), collapsed across condition and visit. The application of BFR at 60% AOP did not affect concentric, isometric, or eccentric maximal strength or neuromuscular function. Trainers, clinicians, and researchers can prescribe exercise interventions relative to a restricted (when using a moderate AOP) or nonrestricted assessment of maximal strength.
Huber, M. (2019). "An Introduction to Flexible Methods for Policy Evaluation"
Authors: Peralta Gonzales Carmen Patricia
Published: August 2024

En su artículo "An Introduction to Flexible Methods for Policy Evaluation", Martir Huber explora diversos enfoques de evaluación de políticas, centrándose principalmente en diseños cuasi experimentales. Destaca métodos de estimación de efecto de tratamiento flexible y algoritmos de aprendizaje automático. En una época de gran avance en el conocimiento científico y la evolución de la economía empírica en las últimas tres décadas, surgieron nuevas formas de investigación en el ámbito de las ciencias económicas. Sin embargo, la evaluación de políticas persiste como un desafío, especialmente en momentos de crisis, donde la inestabilidad económica, política y social afecta la calidad de vida de las personas, empresas y la administración pública. Este cambio de paradigma está transformando el trabajo de los economistas, gracias al avance de la inferencia causal tal como la concebimos hoy en día.
Mining and Supplier Development: The Case of Proinnóvate in Cajamarca MiningIndustry
Authors: Mendoza Vargas Oscar Manuel
Published: August 2024

The research shows the positive impact of the National Supplier Development Program, PDP, of the Peruvian Ministry of Production’s ProInnóvate on the business productivity of local mining suppliers in Cajamarca, Peru. The hypothesis was evaluated using a model of contemporary elasticities for a Cobb-Douglas production function, estimated with ordinary least squares, and a dynamic model of elasticities for business productivity, estimated by the generalized method of moments, in both cases for unbalanced panel data. For the case of both models, the beginning of the program represented a breaking point where the participation of mining suppliers generated increases in productivity between 22,1 % and 65,6 % considering the period from 2013 to 2021, controlled by other factors.
LITHIUM IN THE SUBSOIL OF UKRAINE Part 7. Genesis of lithium-bearing objects: rare-metal granites of the Ukrainian Shield
Authors: Pavlyshyn V.I. , Cherniyenko N.M. , Lunova I.M.
Published: August 2024

In the genetic sense, the following lithium-bearing objects have been characterized: vein Li-F granites and areal Liznykivsky granites of the Korosten pluton, rare-metal granites of the Kamianomohylsky complex, and ongonites of the Azov region. Most researchers consider Li-F granites as the final phase of magmatism of the Korostensky complex. Our conclusion differs from the mainstream view: vein Li-F granites of the pluton are products of crystallization of deep fluid flows that penetrated into the fissure cavities of the pluton rocks after the formation of magmatic massifs. In our opinion, the Liznykivsky granites are metasomatic formations that have developed on different-age rapakivi-like biotite-amphibole granites under the influence of deep fluid flows. The rare-metal granites of the Kamianomohylsky complex form three massifs in the Azov region: Kamiana Mohyla, Katerynivsky and Starodubivsky. Initially, all granite massifs were formed in the process of crystallization of magmatic melt, which later changed to metasomatic alteration of granites. Post-magmatic changes in granites that contributed to the development of rare metal mineralization include: 1) biotitization; 2) microclinization; 3) early albitization; 4) greisenization; 5) late albitization. According to the data of thermobarogeochemical studies, the stage-by-stage development of the post-magmatic alteration of the Kamiana Mohyla granitoids was substantiated and physicochemically characterized: microclinization (500-600 °С), albitization (430 °С), topazization (430 °С), silicification (430-440 °С), sulfidization (320 °С), late albitization (290-420 °С), crystallization of xenotime (200-210 °С), vein fluoritization and the growth of fluorite crystals (125-155 °С). The crystallization of ongonites took place at high temperature, which was 1140 °C at the final stage of quartz phenocrysts growth.
Na-Enriched Titanite in Apoquartzite Fenites From Azov Area (Ukraine)
Authors: Kryvdik S.G. , Dubyna O.V.
Published: August 2024

The Na-enriched titanite (up to 3.53 % Na2O) was found in the apoquartzite fenites of the Tunikova gully (Eastern part of the Azov megablock, Ukrainian Shield). It is observed in association with alkaline amphiboles, aegirine, low-Al and high-F phlogopites, rutile, bastnaesite-(Ce), monazite-(Ce), albite, and Ba-enriched potassium feldspar. This mineral association, as well as the agpaitic specificity of apoquartzite fenites (peralkaline index >2), is the result of the influence of undiscovered intrusion of alkaline igneous rocks (silicate or carbonatite) that were the source of alkaline fluids. In general, the Na-enriched titanite contains (wt. %): Y2O3 (up to 3.48), Ce2O3 (up to 0.98), Nd2O3 (up to 1.13), increased F (up to 1.94), but moderate Nb2O5 (0.2-2.8) and negligible content of FeO and MnO, in the almost complete absence of Al2O3. It is assumed that the Na-enriched titanite substitutes the primary rutile of quartzites and reflect high concentration of Na2O, CaO, REE, Y, F introduced by alkaline fluids. The Na → Ca isomorphism was accompanied by parallel substitution Y, REE → Ca, and partially O → F. Other schemes of substitution intrinsic for titanites of alkaline rocks, such as Na+Nb → Ca+Ti or Nb+Fe(Al) → 2Ti, are practically not manifested that obviously due to the low Nb content in the primary rutile and introduced alkaline fluids, as well as the depletion of quartzite in alumina and iron.
The Nature and Upper Age Limit of the Formation of the Rock Association of the Petrivsky Iron Ore Deposit
Authors: Stepanyuk L.M. , Dovbush T.I. , Pavlov H.H. , Vysotsky O.B. , Kovtun O.V. , Kovalenko N.O.
Published: August 2024

The Petrivsky iron ore deposit is located on the left bank of the Ingulets River, southeast of the village Petrovo, Oleksandriysky district, Kirovohrad region. Until recently, the deposit was developed of the quarry method. The quarry revealed an iron ore stratum composed of ferruginous quartzites and crystalline schists, and strongly schistulated gneisses, ore-free quartzites and carbonate rocks occur in sharply subordinate quantities. In some areas of the quarry, the crystalline slates are partially migmatized, and the bundles of ferruginous quartzite are in many places dissected by veins of aplito-pegmatoid granites and pegmatites. According to the nature of the section, the iron ore stratum belongs to the Artemivska suite of the Ingulo-Ingulets series. Optical microscopy methods revealed heterogeneous cores of relict (clastogenic) zircon within the accessory zircon crystals from gneiss, which made it possible to make an assumption about its primary sedimentary nature, and rather high isotopic ratio 87Sr/86Sr = 0.70914 ± 0.00005 in calcite from calciphyre indicates on sediment accumulation in a basin isolated from the world ocean According to the results of uranium-lead isotope dating of different-grained monazite samples (TIMS method), the granites dissect the iron ore stratum of the Petrivske deposit were rooted in the Paleoproterozoic: aplito-pegmatoid granite 2033.3 ± 2.3 million years ago and plagiopegmatite — 2028.5 ± 5.6 million oyears ago. It is proposed to take the age of 2030 million years as the upper age limit of the iron ore stratum.
Ilmenite Content of Different Genesis of Productive Sediments of the Trostyanytsky Deposit
Authors: Figura L.A. , Kovalchuk M.S.
Published: August 2024

The article presents information on the geological structure and ore content of the Trostyanytsky ilmenite deposit located in the northern part of the Volodarsk-Volynskyi massif of the Korostensky pluton bedrock. The deposit is localized in the weathering crust of the basement crystalline rocks and continental deluvial-alluvial and alluvial sediments of the Middle Jurassic-Lower Cretaceous, which were formed by erosion and redeposition of eluvium. Weathering crust together with deluvial-alluvial and alluvial sediments formed the productive deposits of the Trostyanytsky deposit. On the basis of the created target database containing conditional coordinates of wells, their description and testing results, mapping constructions (isohypses of the roof, sole, isopachites of the thickness of the weathering crust of crystalline rocks of the basement, alluvial sands and redeposited kaolins of the Middle Jurassic-Lower Cretaceous) were carried out; lateral distribution of the average ilmenite content in the weathering crust, in the Middle Jurassic-Lower Cretaceous fluvial deposits and in productive sediments, distribution of ilmenite content in the vertical section of wells). These mapping constructions were created based on the results of preliminary (1999) and detailed (2008) geological exploration. The direction and strength of correlations between the topography of the sole and the surface, topography of the sole and the thickness of ilmenite-bearing formations, sole relief and ilmenite content, sediment thickness and ilmenite content in the weathering crust, alluvial deposits of the Middle Jurassic-Lower Cretaceous and in productive deposits. The obtained results made it possible to clarify the structural and material parameters of the ore-bearing rocks, the lateral and vertical distribution of ore bearing in different genetic and different age's formations.
A stratégiai gyógyszerlista szerepe a gyógyszerhiányok megelőzésében és kezelésében hazánkban
Authors: Merész Gergő , Nagy Zsófia , Batta Balázs , Rózsa Péter
Published: August 2024

Bevezetés: A gyógyszer-nagykereskedők számára egyes
hatóanyagokból készletezési kötelezettséget előíró, a stratégiai gyógyszerlista
kiadásáról szóló 16/2024. (III. 11.) BM rendelet hatását a gyógyszerhiányok
kezelésében eddig nem vizsgálták. Célkitűzés: Kutatásunk célja,
hogy ennek az új szakpolitikai beavatkozásnak a megfelelőségét a
gyógyszerhiányok elkerülése szempontjából értékeljük, részben kvantitatív
módszereket alkalmazva. Módszer: A stratégiai gyógyszerlistán
szereplő hatóanyagokat összevetettük az annak megjelenését megelőző 12 naptári
hónapban hiánnyal érintett készítmények hatóanyagaival. A teljes érintett
hatóanyagkörben megvizsgáltuk azok közfinanszírozott forgalmát, a hiány
fennállásának időtartamát, illetve adatokat gyűjtöttünk a hatóanyagok esetén
lezajlott áremelkedésekről, helyettesítő készítmények megjelenéséről.
Eredmények: A vizsgált időszakban az „Összes termékhiány”
listán 605 hatóanyagot azonosítottunk, míg a stratégiai gyógyszerhatóanyagok
listáján 312 hatóanyag szerepel; 190 hatóanyag mindkét listán szerepelt (415
hatóanyag csak az előbbi, 99 hatóanyag csak az utóbbi listán). A hiány
fennállásának medián-időtartama a készítmények körében 10, illetve 11 hónap
volt. Az „Összes termékhiány” listán és a stratégiai gyógyszerhatóanyagok
listáján egyaránt szereplő elemek 17,4%-a esetén történt helyettesítő készítmény
engedélyezése, 5,3% esetén került sor áremelésre, illetve 7,4% esetén történt
kontingensengedély kibocsátása. Megbeszélés: A hazánkban
bevezetett stratégiai gyógyszerlista jelentette készletezési kötelezettség
európai összevetésben nem tekinthető egyedülálló szakpolitikai beavatkozásnak.
Más tagállamok ugyanakkor egyidejűleg több eszközt (a készletezési kötelezettség
mellett például adminisztrációs, árképzési könnyítéseket, érdekegyeztetési
fórumokat) alkalmaznak a gyógyszerhiányok megelőzésére vagy kezelésére.
Következtetés: A stratégiai gyógyszerlista a készítmények
korlátozott körében képes lehet a rövid távú hiányjelenségek előfordulásának
mérséklésére. Megfelelő önszabályozási mechanizmusok nélkül a készítmények
széles körét érintő, illetve a hosszabb távon fennálló hiányok kezelésére
további beavatkozások lehetnek szükségesek. Orv Hetil. 2024; 165(34):
1325–1331.
Javaslatok és megfontolások a magyarországi pertussisesetszám-növekedéssel összefüggésben
Authors: Tróbert-Sipos Diána , Pék Tamás , Kulcsár Andrea , Farkas Ferenc Balázs , Szabó Attila
Published: August 2024

Európa-szerte a szamárköhögés robbanásszerű emelkedését figyelhetjük meg. Az idei
év első 3 hónapjában már több igazolt esetet regisztráltak, mint a tavalyi évben
összesen. Magyarországon a pertussis epidemiológiai helyzete a közelmúltban igen
kedvezően alakult, 2019 és 2023 között a bejelentett esetszámok mediánja 2 fő
volt. A növekvő incidenciát azonban hazánkban is észleljük: 2024. július 14-ig
153 jelentett pertussismegbetegedésről számolhatunk be. A fenyegető közösségi
terjedés megfékezése megváltozott prevenciós hozzáállást és fokozott
diagnosztikus aktivitást kíván. A kontaktszemélyek mihamarabbi azonosítása és
ellátása alapvető fontosságú. A betegség az oltatlan, illetve nem teljeskörűen
oltott újszülöttekre és csecsemőkre a legveszélyesebb. Esetükben a köhögési
rohamok kapcsán jelentkező apnoés epizódok keringés- és légzésleálláshoz
vezethetnek. Az elsődleges cél ennek a populációnak a védelme, melynek
leghatásosabb módja az életkor szerinti kötelező immunizáció késedelem nélküli
elvégzése, a fészekimmunitás biztosítása és a várandós nők aktív immunizálása. A
várandósok pertussisoltását évtizedek óta biztonsággal és nagy hatékonysággal
végzik világszerte. A 16–36. gestatiós hét között bármikor alkalmazható, de a
27–31. gestatiós hét között a legoptimálisabb. Közleményünkben a korszerű
nemzetközi irányelvek alapján javaslatokat teszünk a pertussis diagnosztikájára,
kezelésére, a posztexpozíciós kemoprofilaxisra, valamint az aktív immunizációra.
A klinikai gyakorlathoz adott javaslataink kizárólag a jelenlegi hazai
járványügyi helyzetben érvényesek, az aktuális hatósági ajánlás megjelenéséig.
Orv Hetil. 2024; 165(34): 1307–1318.
"Industry 4.0: Leveraging AI-Powered Big Data Analytics for Superior Decision-Making"
Authors: Sharma Saurabh , Paranjape Vishal
Published: August 2024

The intersection of Artificial Intelligence (AI) and Big Data represents a crucial advancement in the age
of digital transformation, fundamentally altering industries and fundamentally transforming organisational operations.
Artificial Intelligence (AI) has the ability to perform sophisticated data analysis and predictive modelling. This allows
for the extraction of valuable insights from large datasets, leading to better informed decision-making and promoting
innovation in various industries. This paper provides a thorough examination of the mutually beneficial connection
between Artificial Intelligence (AI) and Big Data. It emphasises important approaches and technologies, including data
mining, natural language processing, and neural networks, that enable this integration. The suggested technique
exhibits substantial enhancements in predicting performance, with an accuracy rate of 95.6%. The evaluation metrics
indicate a mean absolute error (MAE) of 0.401 and a root mean square error (RMSE) of 0.206, highlighting the success
of the approach. These measurements demonstrate the method's accuracy and dependability in practical scenarios. This
paper explores practical applications and case studies in several sectors such as healthcare, banking, retail, and
transportation, illustrating the significant influence of AI-powered Big Data analytics. The topic encompasses ethical
considerations and challenges, such as data privacy, algorithmic bias, and the imperative for openness, to ensure the
responsible and fair use of these technologies.
Assessing the Correlation between COVID-19 Mortality Rates and Testing Statistics Worldwide
Authors: Sharma Saurabh , Hasan2 Zohaib , Paranjape Vishal
Published: August 2024

This study examines the COVID-19 case fatality ratios in different nations by utilising data from
Worldometer. The approach involves assessing mortality rates by considering the ratio of tests performed per
confirmed case and the overall number of reported cases. The research examines the relationship between the quality of
testing and the reported fatality rates by specifically studying nations with significant numbers of cases. The results
emphasise notable disparities in mortality rates, especially among nations with varying capabilities for conducting tests.
The study also assesses the influence of extensive testing on the precision of reported fatality rates, offering insights
into the efficacy of public health measures in managing the epidemic.
Transforming Oncology: Machine Learning Approaches for Enhancing Early Diagnosis of
Lymphoma
Authors: Vishwakarma Zeba , Singh Abhishek , Soni Priyanka , Garg Sheetal
Published: August 2024

Lymphoma, a malignancy originating in the lymphatic system, poses significant challenges in early
diagnosis due to its diverse presentations and often subtle early-stage symptoms. Early detection is critical for
improving patient outcomes, as it enables timely intervention and tailored treatment strategies. Traditional diagnostic
methods, while effective, are often invasive, time-consuming, and may lack the sensitivity needed for early-stage
detection. Recent advancements in machine learning (ML) offer promising alternatives to enhance the accuracy and
efficiency of medical diagnostics. Machine learning, a branch of artificial intelligence (AI), involves developing
algorithms that allow computers to learn from and make predictions based on data. In the realm of oncology, ML has
shown potential in identifying patterns and anomalies indicative of diseases such as lymphoma. By utilizing extensive
datasets of medical images, genomic information, and patient records, ML algorithms can be trained to recognize subtle
features associated with early-stage lymphoma. This study explores the application of ML in the early diagnosis of
lymphoma, presenting a proposed method that demonstrates notable performance metrics. The method achieved an
accuracy of 95.3%, with a mean absolute error (MAE) of 0.443 and a root mean square error (RMSE) of 0.301. These
results highlight the potential of ML to surpass traditional diagnostic capabilities and offer a transformative approach to
lymphoma detection. The paper reviews the current state of ML techniques in oncology, discusses key studies, and
outlines the challenges and future directions in this evolving field. The findings underscore the significant impact of
ML on lymphoma diagnostics and its broader implications for improving patient care and outcomes.
Applying Naive Bayes Techniques for Accurate Sentiment Analysis in Movie Reviews
Authors: Sharma Saurabh , Hasan Zohaib , Paranjape Vishal
Published: August 2024

This study examines the effectiveness of Naive Bayes and Logistic Regression classifiers in analyzing
the sentiment of movie reviews. Two feature extraction approaches, namely Bag of Words (BoW) and Term
Frequency-Inverse Document Frequency (TF-IDF), are utilized. We employed a dataset comprising 50,000 IMDB
reviews that underwent preprocessing techniques such as denoising, stop word removal, and stemming. The reviews
were transformed into vectors using Bag-of-Words (BoW) and Term Frequency-Inverse Document Frequency (TFIDF) approaches. Our investigation demonstrates that Logistic Regression surpasses Naive Bayes in terms of accuracy.
Logistic Regression achieves 89.52% accuracy for Bag-of-Words (BoW) and 89.23% accuracy for Term FrequencyInverse Document Frequency (TF-IDF), while Naive Bayes achieves 85.01% accuracy for BoW and 85.74% accuracy
for TF-IDF. Naive Bayes has consistent performance with a minimum disparity between training and testing
accuracies, indicating strong generalization skills despite its slightly lower accuracy. The results suggest that Logistic
Regression outperforms Naive Bayes in terms of accuracy. However, Naive Bayes remains a strong contender because
to its simplicity and consistent performance across various feature extraction methods. This comparison offers
significant insights for choosing suitable classifiers and feature extraction techniques for text classification problems in
sentiment analysis.
Achieving Equity in Machine Learning: Technical Solutions and Societal Implications
Authors: Pandey Divya , Hasan Zohaib , Soni Pradeep , Padit Sujeet
Published: August 2024

The rapid advancement and widespread adoption of machine learning (ML) technologies have
transformed numerous industries, including healthcare and finance. While these innovations have introduced significant
benefits and efficiencies, they have also raised critical ethical and fairness concerns. As machine learning models
increasingly influence decision-making processes, ensuring these models operate in a fair and unbiased manner has
become an essential aspect of their deployment. Ethical issues in machine learning primarily revolve around the
potential for biased outcomes, lack of transparency, and the inadvertent reinforcement of societal inequalities. This
paper explores the current state of ethical and fairness solutions in machine learning, highlighting key methodologies
and frameworks addressing these pressing issues. The proposed method demonstrates a high level of performance, with
an accuracy of 97.6%, a mean absolute error (MAE) of 0.403, and a root mean square error (RMSE) of 0.203. By
examining both the technical advancements and the broader ethical considerations, this study seeks to provide a holistic
view of the efforts being made to ensure that machine learning technologies are deployed in a manner that is both fair
and ethical.
Performance Comparison of Microstrip Antennas with Diverse Substrates at Multiple Frequencies
Authors: Mishra Prateek
Published: August 2024

Microstrip antennas are widely used in modern communication systems due to their compact size, low
cost, and ease of integration with printed circuit boards. This paper presents a detailed performance comparison of
microstrip antennas utilizing various substrate materials across multiple frequency ranges. The study investigates the
impact of different substrate materials—such as FR4, Rogers RT/Duroid, and Teflon—on key performance metrics
including return loss, bandwidth, gain, and radiation pattern. The antennas are designed and simulated using a range of
frequencies to evaluate their performance under different conditions. The results reveal significant variations in antenna
characteristics based on substrate material and frequency, providing insights into the trade-offs between material
properties and antenna performance. By analyzing these variations, the study aims to guide the selection of appropriate
substrate materials for specific applications and frequency ranges. The findings offer valuable information for
optimizing microstrip antenna designs to meet the requirements of various communication systems, from wireless
networks to satellite communications.
Evaluating the Efficacy of Generative Adversarial Networks: Performance Metrics and Applications in Synthetic Data Generation
Authors: Patel Abhishek , Verma Saurabh , Pateriya Nidhi , Tiwari Harsh , Kanojiya Sagar
Published: August 2024

Generative Adversarial Networks (GANs) have become a pivotal advancement in machine learning and
artificial intelligence, enabling the generation of highly realistic data. This paper provides a comprehensive overview of
GANs, focusing on their foundational principles, various techniques, and diverse applications. Emphasis is placed on
the transformative impact of GANs in image generation and data augmentation. The proposed method demonstrates
significant performance improvements, achieving an accuracy of 95.3%. Furthermore, the method shows a mean
absolute error (MAE) of 0.501 and a root mean square error (RMSE) of 0.109, highlighting its effectiveness in
producing high-quality synthetic data. Challenges associated with GANs, such as mode collapse and training
instability, are also addressed, along with innovations introduced to mitigate these issues. This paper aims to elucidate
the mechanisms behind GANs, explore their applications, and outline future research directions in this dynamic field.
Healthcare and Cloud Computing: Exploring
Opportunities, Addressing Challenges, and
Charting Future Directions
Authors: Sharma Saurabh , Singh Abhishek , Hasan Zohaib , Paranjape Vishal
Published: August 2024

Cloud computing has become a revolutionary technology in the healthcare industry, providing chances
to increase patient care, simplify operations, and promote collaboration among healthcare providers. This review paper
investigates the implementation of cloud computing in the healthcare industry, analyzing its prospective advantages,
existing obstacles, and forthcoming advancements. The text explores the potential offered by cloud technologies,
including expandable storage, data analysis, and telemedicine options, while also considering obstacles associated with
data security, regulatory adherence, and interoperability. The study assesses methods for surmounting these obstacles
and delineates prospective avenues for utilizing cloud computing to enhance healthcare provision and foster innovation.
The suggested method exhibits robust performance in evaluating and forecasting outcomes, highlighting the potential
of cloud computing to greatly revolutionize healthcare procedures, with an accuracy of 97.6%, a mean absolute error
(MAE) of 0.403, and a root mean square error (RMSE) of 0.203.
A Review Paper on Integration of Deep Learning & Data Mining Strategies
Authors: Paranjape Vishal , Sharma Saurabh , Hasan Zohaib
Published: August 2024

Cloud computing plays a crucial role in data storage and online services, offering advantages such as
easy access, on-demand storage, scalability, and cost efficiency. Its rapidly advancing technologies can improve the
security of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) against cyber threats. With the rise of
sophisticated malware, traditional detection methods are often insufficient due to advanced evasion techniques. This
article presents a comprehensive review of cloud-based malware detection technologies and examines the use of cloud
computing to protect IoT and critical infrastructure. It assesses the benefits and drawbacks of cloud environments for
malware detection and introduces a deep learning and data extraction methodology for identifying cloud-based
malware. Additionally, it discusses recent research on malware propagation issues and compares various detection
methods, highlighting their strengths and weaknesses. The study's findings provide valuable insights for addressing
current challenges in malware research.
Unlocking New Computational Paradigms: The Role of Quantum Mechanics in Algorithm Development
Authors: Pateriya Nidhi , Vishwakarma Abhishek , Rachana Rachana , Yadav Mansi
Published: August 2024

The advent of quantum computing has ushered in a new era of computational capabilities, promising to
revolutionize the resolution of complex problems. Unlike classical computers, which rely on binary digits (bits) to
process information, quantum computers utilize quantum bits (qubits) that can exist in multiple states simultaneously
due to the principles of superposition and entanglement inherent in quantum mechanics. This fundamental difference
allows quantum computers to perform certain calculations exponentially faster than their classical counterparts,
offering profound implications for fields ranging from cryptography to material science. At the heart of this
transformative potential lie quantum algorithms, specifically designed to harness the unique properties of quantum
systems to tackle problems currently intractable for classical computers. Notable examples include Shor's algorithm for
integer factorization, which threatens the security of widely used cryptographic schemes, and Grover's algorithm for
unstructured search, which provides a quadratic speedup over classical approaches. Beyond these pioneering works,
ongoing research continues to uncover new quantum algorithms capable of addressing a broad spectrum of
applications. The proposed method leverages the principles of quantum mechanics to develop efficient algorithms that
outperform classical approaches in solving complex computational problems. By harnessing the unique properties of
quantum bits (qubits), such as superposition and entanglement, the method aims to achieve superior accuracy and
efficiency in various applications. The performance of the proposed method was evaluated using several key metrics:
an accuracy of 94.8%, a Root Mean Squared Error (RMSE) of 0.208, and a Mean Absolute Error (MAE) of 0.406.
These metrics collectively underscore the robustness and reliability of the proposed quantum algorithms, highlighting
their potential to significantly enhance computational efficiency and accuracy across various domains. This study
delves into the development of quantum algorithms, exploring their theoretical foundations, practical implementations,
and the challenges faced in their realization. By leveraging the principles of quantum mechanics, these algorithms hold
the promise of not only solving existing problems more efficiently but also unlocking new computational paradigms
previously deemed unattainable. Through a comprehensive analysis, this research aims to elucidate the current state of
quantum algorithm research, highlight the advancements made, and identify the pathways forward in this rapidly
evolving field.