bluuebunny/crossref_metadata_2025_split huggingface dataset:
GuardianAI: Smart Intrusion Detection for Modern Threats
Authors: SAIRAJKUMAR MAJETI 
Published: January 2024

Abstract
Finding and stopping breaches is now essential in the rapidly evolving world of cybersecurity. This work involves a range of machine learning algorithms for intrusion detection systems (IDS) as well as a detailed examination and use of sophisticated feature engineering techniques. The study enhances intrusion detection's accuracy and efficacy to counteract the ever-changing nature of cyber threats. We handle missing values, encode categorical characteristics, and prepare and balance datasets as part of our strategy. By examining them, one can have a thorough understanding of the benefits and drawbacks of several machine learning models, including Decision Trees, Random Forests, Naive Bayes, and XGBoost, in the context of intrusion detection. Furthermore, we provide a novel approach that combines Recursive Feature Elimination (RFE) with Random Forests to show how well it maintains high classification accuracy while reducing dimensionality. We test the models on a publically available dataset, and we meticulously evaluate the models based on key performance metrics like accuracy, precision, recall, and training time. A comparison analysis of the models makes it clear if they are suitable for real-world application.
Our findings indicate that the XGBoost classifier outperforms other models when paired with a well-selected feature set. This demonstrates how well the model detects common intrusions as well as backdoors. In addition, the Random Forest Classifier with RFE modifications exhibits potential as a feature selection technique, offering a balance between accuracy and computational economy. The work adds to the body of knowledge on intrusion detection and provides cybersecurity experts and system developers with valuable information. The strategy being offered offers a reliable and adaptable means of fending off the always changing cyberthreats, thereby bolstering the ongoing effort to fortify digital systems against malicious activity. This work highlights the importance of combining state-of-the-art feature engineering approaches with intricate machine learning algorithms to produce robust and effective cybersecurity defenses, laying a solid foundation for future advancements in intrusion detection.
Augmenting Large Language Models for Enhanced Interaction with Government Data Repositories
Authors: Trust Paul , Omala Kizito , Minghim Rosane 
Published: January 2024

Abstract
In the modern digital landscape, government agencies globally are shifting services online to enhance transparency and public engagement. However, the vast digital content can be daunting for citizens seeking information. Addressing this, our research evaluates the efficacy of Large Language Models (LLMs), like ChatGPT, in the public sector, highlighting their potential in extracting relevant insights and optimizing information navigation. Our approach integrates non-parametric data from various sources focusing on information posted on three irish websites; the government publications, health services, and the Citizens Information websites, using retrieval-augmented models. Empirical evaluations show that the llama2 model, with $13$ billion parameters, achieves up to 90% for government publication releases and up to 96.12% for health information enhancement when complemented with retrieval augmentation, with other models also showing substantial improvements. These results emphasize the transformative potential of retrieval-augmented frameworks in keeping LLMs updated with the evolving public information domain.
Armored Terrestrial Tardigrades use Cryptogam-Host Cues of Pending Environmental Deterioration to Initiate Cryptobiosis.
Authors: Momeni Sogol , Phillipi Evan , Bushman Timothy , Fuentes-González Jesualdo A. , Perezsanchez Ana P. , Rosario Justin R. , Earley Ryan E. , Ciesla Lukasz M. , Pienaar Jason 
Published: January 2024

Abstract

The mechanisms of the induction of extremotolerant states, a.k.a. cryptobiosis, in tardigrades are beginning to be explored. Armored tardigrades (Class: Heterotardigrada) living in limnoterrestrial environments are highly associated with desiccation-tolerant moss or lichen substrates that themselves produce numerous specialized metabolites during desiccation. Here we show that some of these metabolites can induce reversible cryptobiosis in their coexisting heterotardigrades in a dose-dependent manner. Coexisting eutardigrades, nematodes and rotifers however, show no such response to these molecules. The response-inducing metabolites belong to a class of soft-electrophilic flavonoid compounds, suggesting that they possibly interact with electrophile-responsive heterotardigrade proteomes related to their specific cryptobiotic traits. The ability to control when biological material enters a protective state increases the scope of bioengineering avenues to mitigate increasing environmental unpredictability on Earth and to inform near-future space-travel endeavors.
Process Simulation of Carbon Dioxide Gas Stream Dehydration from Flue Gas
Authors: Rahman Md. Shafiur , Aich Jotirmoy , Basak Roni , Islam Md. Mirazul 
Published: January 2024

Abstract
Since many decades, global warming & subsequent sea level rise has been a major issue for the nations. Flue gas from fossil fuel burning industrial processes have always been a prime contributor to carbon footprint. Recent approaches to mitigate this issue include the application of carbon capture & sequestration (CCS) in fossil fuel-burning power plants. In this work, ASPEN HYSYS software was used to simulate the dehydration of a CO2- containing flue gas stream to look into potential process improvements. The dehydration technique is conducted to prevent corrosion and hydrate buildup in pipelines. Having a maximum water content of 200 ppmv was the objective dried stream purity. Glycol package has been used as a thermodynamic property package to simulate the process. Water removal & solvent regeneration have been considered the main building blocks for this process. Parameters investigated in this study were water removal rate, dehydrated gas purity, solvent circulation rate etc. Higher solvent circulation rate (>15 kg mole/h) does not decrease water content or water flow rate in dehydrated gas stream. This study revealed that improving the reboiler temperature, solvent circulation rate increases the water removal rate. On the other side, raising the feed gas temperature, the solvent circulation rate, and the absorber pressure reduces dehydration performance. Case study on the effect of temperature & pressure suggest lower feed gas temperature (<1200C) & higher feed gas pressure (>5800kPa) favors dehydration performance. Solvent regeneration has been identified as the major energy-consuming process where energy consumption can be further reduced by changing process chemistry.
Study by computational methods of the electronic structure of a series of organic molecules and their charge transfer complexes
Authors: Belaidi Salah , Kerassa Aicha 
Published: January 2024

Abstract
This work explored a series of organic molecules belonging to the tetrathiafulvalene (TTF) family and their charge transfer complexes (TTF-TCNQ), involving asymmetric molecules (donors) complexed with the acceptor molecule tetracyanoquinodimethane (TCNQ). This study was carried out by several in silico methods (molecular mechanics, DFT, PM3 and EHT). A structural study of the donors showed that the majority of the structures of these molecules are pseudo planar and exhibit Cs symmetry. The diagonal angles of the average planes of this series vary from 0.028° to 0.544°, with a calculation error of 0.001°. We found good correlation between the computational values and the experimental values. Charge transfer complexes (CTCs), which have a specific conductivity between 7.6 and 10.6 W -1 cm-1, correspond to a charge transfer between 0.61 and 0.72 e/mol and have a restricted gap of 1.58 to 1.71 eV.
Language planning in the context of complex multilingual schools
Authors: Mabiletja Matome , Ngcobo Mtholeni 
Published: January 2024

Object of research: This article discusses language planning and multilingualism in complex environments such as in education.
Investigated problem: The failure in language-in-education policy has raised arguments about the approach that is applied by schools. Using a context-based approach it is argued that success in multilingual education is constrained by various micro, meso and macro factors, usually also referred to as immediate, proximal, and distal circumstances. These are based on language planning and policy.
The main scientific results: The research uses data from three different types of government/public schools. The study involved learners, teachers, parents’ representatives, principals and an educational official through interviews and observations. The study found that there were challenges in the implementation of a schools’ language policy based on different types of schools.
The area of practical use of the research results: The results benefits schools and policy makers since the study recommends a development of a holistic approach and a diversified model that will address specific contexts rather than using one-size-fits-all approach.
Innovative technological product: The language planning approaches in multilingual schools that are investigated in this study provide advise and relevant innovative methods to policy makers, teachers, and parents. There will be an improvement in various learning settings and schools.
Scope of the innovative technological product: The development of Language-in-education policy in 1996 provided a new outlook in language learning and teaching approach in schools. This has created grounds to produce aligned language policies by schools to give effect to the democratic constitution of the country and to provide the choice of language of learning by learners. This shows how the policy is conceptualized and implemented in a multilingual school environment such as in South Africa
Development of a method for increasing the efficiency of decision-making in special purpose systems
Authors: Gaman Oleksandr 
Published: January 2024

The object of the research is special purpose systems.
Investigated problem: The experience of operations (combat operations) of recent years shows the growing role of information influence measures on the systems of collection, processing and transmission of special purpose information and decision-making officials.
The main scientific results: The specificity of measures to ensure the information security of the state is that, on the one hand, it is necessary to solve the task of collecting, processing and transmitting information, and on the other hand, it is necessary to counteract measures of information influence on the systems of collecting, processing and transmitting information and decision-making officials.
Victory over a quantitatively superior opponent is possible only if there is a technological advantage over it. One of such technological approaches is the use by the defense forces of Ukraine of the concept of the Internet of Things (IoT)
The essence of this concept involves the use of a large number of sensors, sensors, unmanned aerial vehicles, as well as other technical means (tablets, communication means) combined into a single network, which are united by a common goal of functioning.
The area of practical use of the research results: It is advisable to use the proposed scientific results when conducting research and development works on the creation of intelligent systems for collecting, processing and analyzing information about the special purpose systems, and developing requirements for hardware and software of this type of systems.
Innovative technological product: the proposed method is recommended to be used as part of the software of special-purpose systems. This method is advisable to apply at the stage of assessing the state of special-purpose systems and further making managerial decisions by the persons taking them. Also, the proposed method should be incorporated as an integral part of decision support systems at the stage of analyzing the state of complex technical systems.
Field of application: software, special purpose systems, decision support systems.
Kebertahanan Bangunan dengan Adaptif terhadap Lingkungan
Authors: Kusyanto Mohhamad , Koesmartadi Christophorus , Nurhayati B. Resti 
Published: January 2024

Title: The Resilience of Buildings with Adaptability to the Environment (Case Study: Tomb of Syekh Mudzakir in Bedono, Sayung, Demak)

Coastal areas have the potential to be affected by abrasion and tidal floods. Syekh Mudzakir's grave is in Tambaksari Subvillage, Bedono Village, Sayung Subdistrict, Demak District, and in the coastal area of the North Coast (Pantura) of Java Island. However, the existence of the tomb and its buildings to this day still survives amidst the marine environment that surrounds it. This tomb has become a religious tourism destination in Demak Regency, with the number of tourists increasing. This research aims to determine and explore the resilience of tomb buildings that are adaptive to abrasion and tidal flood environments. This research is field research. Research data uses primary data and secondary data through the results of observations, interviews, and documentation. The research analysis uses qualitative descriptive analysis. This research shows that Syekh Mudzakir's tomb does not float in the middle of the sea. However, the tomb survives adaptively to the environment by adapting the area, building development, building structural systems, and expanding the site to be robust against abrasion and tidal floods. This research concludes that the family and community survive the grave by adapting to the environment and mitigating disasters that befall the grave area.
Strategic Lines in the Development of Printing Market Entities in the Russian Federation
Authors: Skrug V. S. , Tishkina A. V. 
Published: January 2024

The topic of the research is acute, which is envisaged by the demand for printing products in all spheres of society: political, cultural, economic, etc. During the last decades serious changes took place on printing market, which made entities of the market revise their strategies. The article studies dynamics of printing market development and itsspecific features in the Russian Federation. The current trends on the printing service market were identified and key reasons for changing the situation on the market were investigated. The authors came to the conclusion that Russian printing houses gained serious experience in overcoming crisis situations, such as the system crisis connected with replacement of periodicals and books by e-publications and the crisis caused by COVID-19 epidemic and large-scale economic sanctions introduced in 2022. They put forward strategic lines in the development of printing market entities with regard to identified trends of market development.
Association between Plasma Brain-derived Neurotrophic Factor Level and Alzheimer’s Disease: A Mendelian Randomization Study
Authors: You Jiaxing , Wang Yinan , Chang Xinyue , Liu Yi , He Yu , Zhou Xiya , Zou Jinyan , Xiao Meng , Shi Mengyao , Guo Daoxia , Shen Ouxi , Zhu Zhengbao 
Published: January 2024

Background:
High brain-derived neurotrophic factor (BDNF) concentrations have
been found to be associated with a decreased risk of Alzheimer’s disease (AD) in observational
studies, but the causality for this association remains unclear. Therefore, we aimed to examine
the association between genetically determined plasma BDNF levels and AD using a two-sample
Mendelian randomization (MR) method.

Methods:
Twenty single-nucleotide polymorphisms associated with plasma BDNF concentrations
were identified as genetic instruments based on a genome-wide association study with
3301 European individuals. Summary-level data on AD were obtained from the International
Genomics of Alzheimer’s Project, involving 21,982 AD cases and 41,944 controls of European
ancestry. To evaluate the relationship between plasma BDNF concentrations and AD, we employed
the inverse-variance weighted method along with a series of sensitivity analyses.

Results:
The inverse-variance weighted MR analysis showed that genetically determined BDNF
concentrations were associated with a decreased risk of AD (odds ratio per SD increase, 0.91;
95% confidence interval, 0.86-0.96; p =0.001). The association between plasma BDNF concentrations
and AD was further confirmed through sensitivity analyses using different MR methods,
and MR-Egger regression suggested no directional pleiotropy for this association.

Conclusion:
Genetically determined BDNF levels were associated with a decreased risk of AD,
suggesting that BDNF was implicated in the development of AD and might be a promising target
for the prevention of AD.
Correlation of Circadian Rhythms and Improvement of Depressive
Symptoms in Acute Ischemic Stroke Patients
Authors: Ding Yue , Chen Shengnan , Sun Qian , Han Fei , Chen Rui , Li Jie 
Published: January 2024

Objectives:
To investigate the correlation between evening melatonin timing secretion,
dim light melatonin onset (DLMO), and post-stroke depression (PSD) in acute ischemic
stroke patients and their influence on the improvement of depressive symptoms.

Materials and Methods:
120 patients with a recent magnetic resonance imaging confirmed
stroke were included. Salivary melatonin samples were collected at 5 time points within 1 week
after hospitalization (7 p.m.-11 p.m., 1 sample per hour). The circadian phase was defined by
calculating DLMO secretion. Post-stroke depressive symptoms were evaluated by the 17-item
Hamilton Rating Scale for Depression (HRSD) both on day 7 of hospitalization and 3 months
after stroke. Patients were divided into PSD and non-PSD groups based on whether the acute
phase HRSD score was ≥8. Similarly, patients were divided into the improved depressive symptoms
(IDS) and no improvement in depressive symptoms (non-IDS) groups based on whether
the HRSD score at 3 months was lower than at baseline. Neurological recovery at 3 months was
assessed using the modified Rankin Scale (mRS).

Results:
The difference in DLMO between PSD and non-PSD patients was not statistically significant
(p =0.173). In the non-IDS group, there was a significant decrease in melatonin secretion
at 10 p.m. (p =0.012), and DLMO was significantly later than in the IDS group (p =0.017).
Logistic regression analysis showed that DLMO (OR 1.91, 95%CI:1.13-3.23, p = 0.016) was an
independent risk factor for persistent no improvement in depressive symptoms, which was associated
with a markedly worse prognosis (p < 0.001).

Conclusion:
Our findings suggest possible interventions for the very early identification of non-
IDS patients.
P-coumaric Acid: Advances in Pharmacological Research Based on
Oxidative Stress
Authors: Chen Feixiang , Zhang Xinxin , Wang Junxiang , Wang Fukai , Mao Jinlong 
Published: January 2024

Abstract:
P-coumaric acid is an important phenolic compound that is mainly found in fruits, vegetables,
grains, and fungi and is also abundant in Chinese herbal medicines. In this review, the
pharmacological research progress of p-coumaric acid in recent years was reviewed, with emphasis
on its role and mechanism in oxidative stress-related diseases, such as inflammation, cardiovascular
diseases, diabetes, and nervous system diseases. Studies have shown that p-coumaric acid
has a positive effect on the prevention and treatment of these diseases by inhibiting oxidative
stress. In addition, p-coumaric acid also has anti-tumor, antibacterial, anti-aging skin and other
pharmacological effects. This review will provide reference and inspiration for further research on
the pharmacological effects of p-coumaric acid.
Synthesis of Methyl N-phenylcarbamate Derivatives by Xphos Pd G2
Catalyzed Intermolecular Amidation Reaction
Authors: Shi Yan-fen , Wu Zheng , Mou Jie , Yuan Hong-hua 
Published: January 2024

Abstract:
The utilization of palladium catalysts in cross-coupling reactions has emerged as a highly
promising method for the facile formation of aryl C-N bonds, operating under mild conditions. In
this study, we present an efficient approach for the synthesis of methyl N-phenyl carbamate derivatives
through the intermolecular amidation of aryl chlorides, catalyzed by Xphos Pd G2. The developed
protocol has demonstrated remarkable efficacy, offering several advantages. Notably, the intermolecular
amidation reaction exhibited good chemoselectivity, allowing for the precise targeting
of desired C-N bond formations while maintaining the integrity of other functional groups. Additionally,
this methodology showcases exceptional functional group compatibility, accommodating a
diverse array of moieties, including sensitive groups that are traditionally challenging to handle. The
Xphos Pd G2 catalyst has proven to be instrumental in orchestrating this transformation, exhibiting
high catalytic activity and selectivity. Furthermore, this protocol stands out for its operational simplicity,
making it a practical choice for synthetic chemists seeking a straightforward and reliable
route to access methyl N-phenyl carbamate derivatives. Overall, this study not only expands the synthetic
toolbox for C-N bond formations, but also underscores the significance of palladium-catalyzed
methodologies in modern organic synthesis. The reported findings hold substantial promise for applications
in medicinal chemistry and material science, where the facile construction of aryl C-N
bonds is of paramount importance.
Structure-based Drug Design of New Cinnamic Acid Derivatives as
Tyrosinase Inhibitors
Authors: Yousefnejad Fayezeh , Sayahi Mohammad Hossein , Moazzam Ali , Gholami Fatemeh , Tanideh Nader , Irajie Cambyz , Tayebi Helia , Rasekh Fatemeh , Larijani Bagher , Tehrani Maliheh Barazandeh , Mahdavi Mohammad , Iraji Aida 
Published: January 2024

Abstract:
Tyrosinase is a critical enzyme responsible for pigmentation disorders, and tyrosinase inhibition
is an established strategy to treat hyperpigmentation. In the current study, cinnamic acidbased
derivatives were designed and synthesized. All synthesized compounds were confirmed using
IR, 1HNMR, 13CNMR, and CNH analysis. The inhibitory potencies of all derivatives against tyrosinase
were determined, and it was shown that 5m bearing para-chloro moiety exhibits an IC50 value
of 77.62 μmol/L. Analysis of enzyme kinetic studies revealed that 5m is an uncompetitive inhibitor.
In silico studies against tyrosinase predicted possible binding mode in the pocket such that 5m
formed critical interactions with both Cu co-factors within the binding site. This study presents the
potential of aryl-substituted cinnamic acids that can benefit various cosmetic formulations as depigmentation
agents.
Celecoxib Catalyzed the Coupling Reaction of Epoxide and CO2
Authors: Wu Ling , Xia Xiaocheng , An Wenying , Cui Wenshan , Liu Yue , Lv Wei , Wu Fengtian 
Published: January 2024

Abstract:
In this study, high yields of various cyclic carbonates are obtained by employing the
drug celecoxib to promote the coupling reaction of CO2 and epoxide using tetrabutylammonium
bromide. This strategy enables the synthesis of benzoic acid, phenylpropiolic acid, and 2, 4-
quinazolinedione. In addition, the model reaction mechanism is proposed.