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Science Get Journal
Published by CV. Get Press Indonesia
ISSN : -     EISSN : 30626595     DOI :  http://doi.org/10.69855/science
Core Subject : Science, Education,
Biochemistry, Genetics & Molecular Biology Chemistry Mathematics Physics
A Peer Reviewed Research Science Get Journal e-ISSN: 3062-6595 Science Get Journal is an Open Access and Anonymous Reviewer/Anonymous Author journal. The field of Science is a vehicle for scientific communication in the field of Science which covers the cross-fields of Mathematics, Physics, Chemistry, Biology, Geography and Mathematics,  Natural Sciences Education and Social Sciences. Science Get Journal is published by Get Press Indonesia. Science Get Journal is used to publish research published every month January, April, July, and October. The Science Get Journal template can be downloaded here (Click). Information about article submission: Articles sent by the author (author) will be seen and read by the editor, if there are still discrepancies with the applicable template and do not comply with the scope of Science Get Journal then the article will be returned to the author. If it is appropriate, the article will be forwarded to the Science Get Journal reviewer for a review process carried out by the Science Get Journal reviewer. A total of two reviewers within a two week period of evaluating the article.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 1 No 1 (2024): January, 2024" : 5 Documents clear
Marine-Derived Biodegradable Polymers for Cold-Water Marine Pollution Eka Cahya Muliawati; Titis Istiqomah
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.448

Abstract

Marine plastic pollution persists as a global environmental crisis, particularly in cold-water marine environments where low temperatures significantly inhibit the degradation of most commercial biodegradable plastics. Conventional polymers such as polyethylene (PE) and polypropylene (PP) accumulate for decades, fragmenting into microplastics that permeate marine ecosystems from coastal zones to polar and deep-sea regions. Although biodegradable polymers have been proposed as an alternative, many widely used materials, including polylactic acid (PLA), exhibit negligible degradation in cold seawater. This study experimentally evaluates the degradation and solubility behavior of selected marine-derived biodegradable polymers under cold-water marine conditions, with a specific focus on temperature-dependent mechanisms. Emphasis is placed on comparative performance among candidate polymers, including marine-derived polysaccharides and microbially produced polyhydroxyalkanoates, as well as emerging supramolecular systems designed for rapid dissolution in seawater. By integrating experimental observations with insights from marine microbiology, polymer chemistry, and material design, this study identifies key pathways and design principles for developing polymers that remain effective in cold marine environments, contributing to the development of environmentally benign plastic alternatives
Number-Theoretic Cryptographic Framework for Securing Generative Artificial Intelligence Against Adversarial Attacks Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.472

Abstract

The rapid adoption of Generative Artificial Intelligence (GenAI) has intensified concerns regarding security, privacy, and robustness against adversarial attacks. Most existing defense mechanisms rely on adversarial training, differential privacy, or cryptographic techniques applied as external protection layers, which often lack formal mathematical guarantees and are weakly coupled with the internal generative process.This study proposes a novel Number-Theoretic Cryptographic Framework that embeds cryptographic primitives directly into the GenAI lifecycle, including latent-space representations and model parameter handling. Unlike prior approaches, the proposed framework integrates number-theoretic hardness assumptions specifically lattice-based and elliptic-curve cryptography into the core generative mechanism, enabling mathematically grounded and provably secure protection against adversarial exploitation.A comprehensive synthetic dataset is constructed by jointly modeling cryptographic parameters, generative model specifications, and adversarial attack scenarios to systematically evaluate the framework. Experimental results demonstrate that number-theoretic cryptographic integration significantly reduces privacy leakage and model extraction vulnerability while preserving generative utility. Lattice-based schemes provide the strongest privacy protection, while elliptic-curve cryptography achieves a balanced trade-off between security and computational efficiency. This work introduces a new paradigm for securing GenAI by unifying generative modeling with formal number-theoretic cryptographic security, offering a robust and future-proof solution against both classical and post-quantum adversarial threats.
Direct Catalytic Conversion of Carbon Dioxide to Liquid Fuel at Ambient Temperature: A Novel Metal-Organic Framework Approach Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.450

Abstract

The increasing concentration of atmospheric CO₂ has prompted the development of efficient strategies for carbon capture and utilization. In this study, a novel bimetallic Cu-Zn/ZT metal-organic framework (MOF) was synthesized and evaluated for direct hydrogenation of CO₂ to methanol and ethanol at ambient temperature (30°C) and 1 atm. The Cu-Zn/ZT catalyst exhibited superior activity compared to monometallic analogs, achieving a CO₂ conversion of 12.5% with 78% selectivity toward methanol and 15% toward ethanol. Characterization revealed a highly crystalline framework, uniform mesoporosity (~1.2 nm), and synergistic Cu⁺/Zn²⁺ active sites that facilitate H₂ activation and CO₂ adsorption. The catalyst demonstrated good stability and reusability over five cycles, retaining high selectivity. These findings highlight the potential of rationally designed bimetallic MOFs for energy-efficient CO₂-to-liquid-fuel conversion under mild conditions, offering a promising route for sustainable carbon utilization
Achieving Quantum Supremacy with Stabilized Qubits: Performance Comparison Against Classical Supercomputing Systems Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.470

Abstract

This study aims to analyze recent developments in quantum supremacy by comparing the computational performance of stabilized superconducting qubit systems with classical supercomputing capabilities. A systematic literature review was conducted on major experimental studies published between 2019 and 2024, focusing on random circuit sampling, qubit stability, gate fidelity, and computational runtime comparisons. The analysis covers key quantum processors, including Sycamore and Zuchongzhi, by evaluating three main parameters: number of qubits, circuit complexity, and performance gap relative to classical simulation.The results show that quantum processors with 50–100 qubits and high gate fidelity are able to complete specific sampling tasks within seconds to hours, whereas equivalent classical simulations would require thousands to billions of years. The findings also indicate that computational advantage increases exponentially with system scale and is strongly influenced by qubit stability and error suppression techniques. Although the demonstrated tasks remain specialized and not yet applicable to practical problems, the evidence confirms that stabilized qubit systems have achieved a measurable computational regime beyond classical feasibility.This review provides a clear synthesis of current experimental achievements and highlights that future progress toward practical quantum advantage depends on improvements in error correction, scalability, and hardware reliability.
Discovery of Active Bacterial Microbiome in Human Brain Tissue: Implications for Neurodegenerative Diseases and Depression Pratiwi Ratih Halimatus Sya'diah; Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.449

Abstract

The concept of a sterile human brain has recently been challenged by emerging evidence suggesting the presence of microbial DNA and components within brain tissue. This study aimed to investigate the presence and disease-specific patterns of microbial signatures in human brains affected by Alzheimer’s disease and depression, compared to healthy controls. Using 16S rRNA sequencing on post-mortem brain samples, we detected microbial DNA in all groups, with notable differences in diversity and composition. Alzheimer’s brains exhibited reduced microbial richness and were enriched in genera such as Cutibacterium and Streptococcus, which may contribute to neuroinflammation and amyloid aggregation. Depressive brains showed increased abundance of Eggerthella, potentially influencing neurotransmitter metabolism and systemic inflammatory pathways, while control brains had higher prevalence of Lactobacillus and Bifidobacterium, consistent with neuroprotective roles. These findings support the emerging “brain microbiome” concept and suggest that low-abundance microbial communities may reflect disease-associated processes or interactions via the microbiota-gut-brain axis. While causality and microbial viability remain to be established, the study highlights the potential relevance of brain-associated microbes in neurodegenerative and psychiatric disorders and provides a foundation for future experimental and translational research exploring microbiome-targeted diagnostic and therapeutic strategies.

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