bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heavy Metals Alter the Anti-cancer Potency of Medicinal Plants
Authors: Rizwan Amber , Aqeel Aatiquah , Idris Aisha , Farooqi Humaira 
Published: January 2025

Abstract:
This review investigates the outcome of heavy metal contamination on the anti-cancer properties of
medicinal plants. Heavy metal pollution is a significant environmental concern globally, often found in soil and
water due to industrial activities. Therapeutic plants are recognized because of their therapeutic attributes and
their ability to absorbing these contaminants. This study examines how heavy metal exposure modifies the chemical
composition and efficacy of medicinal plants against cancer cells. Through a comprehensive review of existing
literature and experimental analysis, we explore the mechanisms by which heavy metals interact with bioactive
compounds in medicinal plants, affecting their anti-cancer potency. Findings reveal intricate interactions
among heavy metals and phytochemicals, leading to variations in cytotoxicity against cancer cells. Comprehending
these interactions is crucial for optimizing the utilization of medicinal plants in cancer treatment and for developing
approaches to alleviate the impacts of heavy metal contamination on their therapeutic potential. The
urgency of this issue cannot be overstated, as it directly impacts our ability to effectively treat cancer and preserve
our environment.
Laccase-Catalyzed Cycloaddition (LaCCA) Reaction: An Efficient Green Approach for Synthesizing Mono- and Bis-(1,4-Disubstituted-1,2,3-Triazoles) via Click Chemistry—In Silico Molecular Docking and Druglikeness Assessment
Authors: Gupta Swati , Narula Anudeep Kumar 
Published: January 2025

Background:
Mono- and bis-(1,4-disubstituted-1,2,3-triazoles) were synthesized via a
laccase-catalyzed reaction using Trametes versicolor. This methodology offers a convenient and
efficient approach to triazole synthesis under mild conditions, achieving modest to good yields.
Additionally, molecular docking studies were performed using PDB IDs 2W9S (antibacterial) and
3KHM (antifungal) to evaluate biological activities. The results of drug-likeness analysis further
corroborated the findings from experimental biological evaluations.

Methods:
This study focuses on developing an eco-friendly method for synthesizing novel 1,2,3-
triazole derivatives using a green catalyst. A co-solvent buffer and organic solvent facilitate the
reaction, which performs well with various substrates, including substituted benzenes (-ortho, -meta
& para-mono & bis-(2-propynyloxy), sodium azide, and aryl halides. Laccase enzymes from
Trametes versicolor are used, leveraging naturally occurring copper metals instead of external transition
metals, bound through histidine, methionine, and cysteine linkages. This method represents
a sustainable approach to organic transformations.

Result:
New scaffolds of mono- and bis-(1,4-disubstituted-1,2,3-triazoles) were synthesized using
eco-friendly green buffer solvents and laccase catalysis with aryl halides, sodium azide, and acetylene
derivatives. Molecular docking studies revealed that the binding affinities of the synthesized
compounds (1-14) show promising interactions with antibacterial and antifungal proteins. All others
except for compounds 6, 7, 8, 12, and 13, meet Lipinski’s criteria, making them potential therapeutic
candidates.

Conclusion:
In conclusion, this methodology is valuable for developing antibacterial and antifungal
agents in medicinal chemistry. Additionally, microwave-assisted synthesis of (2-propenyloxy)benzene
derivatives significantly reduced reaction times from hours to minutes. The approach is environmentally
friendly and practical, particularly for handling flammable organic azides and hazardous
solvents, making it both efficient and safer.
HA-SCINet based Carbon Emission Prediction of the Typical Park
Authors: Zeli Wang , Zeyu Liu , Xupeng Song , Guangtao Wei , Mingchun Li , Hongjun Huang , Weiqi Shao , Yuancheng Li 
Published: January 2025

Background:
With the rapid economic growth and the accelerated process of industrialization,
the production activities of enterprises within parks have significantly increased, leading
to a continuous rise in carbon emissions. Under the context of the "dual carbon" goals, studying
the prediction of carbon emissions in typical parks holds significant practical importance. It is not
only a key measure to address climate change but also an important pathway to achieve sustainable
development.

Objective:
In order to predict the carbon emissions of the typical park more accurately, we propose
a carbon emissions prediction model HA-SCINet.

Methods:
The model uses a recursive downsampling-convolution-interaction architecture. In each
layer, the long-term dependence in time series data is extracted by HyperAttention. Then through
the L-layer SCI-Block of the binary tree structure, the down-sampling interactive learning extracts
both short-term and long-term dependencies. These extracted features are merged and reorganized,
and added to the original time series to generate a new sequence with enhanced predictability.
Finally, employ a fully connected network for forecasting the enhanced sequence. The carbon
emission data of the typical park serve as input, leading to higher accuracy prediction results
through the Stacked K-layer stacked HA-SCINet.

Results:
The mean square error (MSE) and mean absolute error (MAE) of HA-SCINet prediction
model are 0.0819 and 0.204 respectively, outperforming the mainstream Dlinear and Nlinear models

Conclusion:
The experimental results show that the devised model outperforms in predicting carbon
emissions, and is better suited for forecasting carbon emissions within the context of the typical
park.
Short-term Load Forecasting Method Based on VNCMD-TiDE Model
Authors: Sun Bohao , Pei Yuting , Wang Zesen , Han Junjie 
Published: January 2025

Background:
Extreme weather conditions exert a considerable influence on power
load, leading to increasingly erratic fluctuations. Consequently, the dependable and precise forecasting
of power load assumes paramount importance in power system planning.

Objective:
Given the inadequacy of traditional forecasting approaches in handling long-term series
load forecasting, this paper introduces a short-term power load forecasting model rooted in
VNCMD-TiDE, aiming to enhance forecasting precision.

Method:
Initially, the XGBoost algorithm is employed to perform nonlinear coupling analysis
between load and meteorological data, identifying crucial features. Following this, the VNCMD
method is utilized to handle the nonlinear and non-stationary load data, decomposing it into multiple
components with distinct frequencies. Building upon this decomposition, a TiDE-Bayesian
model is constructed, wherein the decomposed components serve as inputs for prediction. Simultaneously,
Bayesian optimization is leveraged to fine-tune hyperparameters. Ultimately, the prediction
outcomes of each component are amalgamated to derive the final prediction.

Results:
The proposed model's performance is assessed through comparison with traditional machine
learning models, such as LSTM. Achieving a noteworthy reduction in Root Mean Square
Error (RMSE) by 4.14 underscores its exceptional predictive prowess.

Conclusion:
Through the analysis of actual power load data in a specific location, the model
proposed in this article demonstrates superior prediction accuracy, particularly evident during extreme
weather conditions like snow and rain.
Optimizing Cloud Traffic Offloading and Cloudlet Resource Usage in Cloud-Integrated WOBAN (CIW)
Authors: Verma Mausmi , Bhatt Uma Rathore , Upadhyay Raksha , Bhat Vijay 
Published: January 2025

Background:
Integration of cloud components in a wireless mesh network of Wireless-
Optical Broadband Access Network (WOBAN) contributes to enhancing network performance.

Aim:
This study aims to deploy the minimum cloudlets at the optimum location and to offload
excess traffic from overloaded cloudlets to underloaded ones.

Objective:
The objective of this study is to optimize cloudlet positioning and traffic offloading for
cost-effective deployment, better resource utilization, reduced blocking probability, and lower
delays.

Method:
The proposed methodology introduces a Cluster-Based Heuristic Approach (CBHA) for
efficient cloudlet placement along with a traffic offloading mechanism using a Customized Donkey-
Smuggler Optimization (CDSO) to enhance the overall network performance.

Result:
Simulations show the effectiveness of the proposed approach for resource utilization,
blocking probability, delay, and cost.

Conclusion:
The problem in position optimization of the cloudlet, along with traffic offloading, is
solved using the proposed approaches to get better network performance in a cost-efficient manner.
Exploring Speech Biosignatures for Traumatic Brain Injury and Neurodegeneration: Pilot Machine Learning Study
Authors: Rubaiat Rahmina , Templeton John Michael , Schneider Sandra L , De Silva Upeka , Madanian Samaneh , Poellabauer Christian 
Published: January 2025

Abstract

Background
Speech features are increasingly linked to neurodegenerative and mental health conditions, offering the potential for early detection and differentiation between disorders. As interest in speech analysis grows, distinguishing between conditions becomes critical for reliable diagnosis and assessment.

Objective
This pilot study explores speech biosignatures in two distinct neurodegenerative conditions: (1) mild traumatic brain injuries (eg, concussions) and (2) Parkinson disease (PD) as the neurodegenerative condition.

Methods
The study included speech samples from 235 participants (97 concussed and 94 age-matched healthy controls, 29 PD and 15 healthy controls) for the PaTaKa test and 239 participants (91 concussed and 104 healthy controls, 29 PD and 15 healthy controls) for the Sustained Vowel (/ah/) test. Age-matched healthy controls were used. Young age-matched controls were used for concussion and respective age-matched controls for neurodegenerative participants (15 healthy samples for both tests). Data augmentation with noise was applied to balance small datasets for neurodegenerative and healthy controls. Machine learning models (support vector machine, decision tree, random forest, and Extreme Gradient Boosting) were employed using 37 temporal and spectral speech features. A 5-fold stratified cross-validation was used to evaluate classification performance.

Results
For the PaTaKa test, classifiers performed well, achieving F1-scores above 0.9 for concussed versus healthy and concussed versus neurodegenerative classifications across all models. Initial tests using the original dataset for neurodegenerative versus healthy classification yielded very poor results, with F1-scores below 0.2 and accuracy under 30% (eg, below 12 out of 44 correctly classified samples) across all models. This underscored the need for data augmentation, which significantly improved performance to 60%‐70% (eg, 26‐31 out of 44 samples) accuracy. In contrast, the Sustained Vowel test showed mixed results; F1-scores remained high (more than 0.85 across all models) for concussed versus neurodegenerative classifications but were significantly lower for concussed versus healthy (0.59‐0.62) and neurodegenerative versus healthy (0.33‐0.77), depending on the model.

Conclusions
This study highlights the potential of speech features as biomarkers for neurodegenerative conditions. The PaTaKa test exhibited strong discriminative ability, especially for concussed versus neurodegenerative and concussed versus healthy tasks, whereas challenges remain for neurodegenerative versus healthy classification. These findings emphasize the need for further exploration of speech-based tools for differential diagnosis and early identification in neurodegenerative health.
Evaluation of a Global Initiative for Asthma Education and Implementation Program to Improve Asthma Care Quality (CARE4ALL): Protocol for a Multicenter, Single-Arm Study
Authors: Huang Kewu , Wang Wenjun , Wang Ying , Li Yanming , Feng Xiaokai , Shen Huahao , Wang Chen 
Published: January 2025

Background
Poor symptom control and exacerbations of asthma diminish quality of life and pose a significant burden to patients and society. Implementing evidence-based management as recommended by the Global Initiative for Asthma (GINA), especially introducing inhaled corticosteroid–containing treatments, has the potential to vastly reduce exacerbations and the high burden of asthma in China. However, domestic implementation of the GINA recommendations has been unsatisfactory, especially in lower-level hospitals; thus, an enhancement to the awareness of and adherence to the GINA recommendations among Chinese physicians is needed to improve patient outcomes.

Objective
This study aims to bridge the gap between the GINA recommendations and the current clinical practice in China by demonstrating the benefits of an asthma quality improvement program (QIP).

Methods
A single-arm study will be conducted at around 30 hospitals across China to assess the impact of a specially designed asthma QIP. Approximately 1500 patients with asthma aged ≥14 years will be enrolled in participating hospitals and followed up for 48 weeks. The QIP—targeted at all pulmonologists and specialist nurses—will include an initial comprehensive training (including a pretraining questionnaire and posttraining quizzes) provided by a dedicated, qualified training team based on the GINA 2021 recommendations, followed by regular reinforcement learnings (integrated into the regular department lectures delivered by department directors), with multiple offline and online approaches (eg, an online patient management platform) provided as supportive tools. During this study, GINA implementation performance will be continuously monitored to inform necessary adjustments at the hospital level. The primary end point is change from baseline in the proportion of participants with an inhaled corticosteroid–based maintenance or reliever treatment at week 48. Secondary end points and exploratory end points include changes in clinical practice and patient outcomes such as treatment patterns, asthma control, and hospitalization rates due to exacerbations.

Results
This study has been completed, with 1500 patients enrolled and 1271 patients completing the study. The last visit of the last patient was on September 3, 2024, and the database lock was on September 28, 2024. Final analysis of data has started in October 2024.

Conclusions
The Change Asthma Clinical Practice through GINA Education and Implementation for All Patients With Asthma (CARE4ALL) study will hopefully help improve asthma management and patient outcomes in China by bridging the gap between evidence-based GINA recommendations and the current clinical practice.

Trial Registration
ClinicalTrials.gov NCT05440097; https://clinicaltrials.gov/study/NCT05440097

International Registered Report Identifier (IRRID)
DERR1-10.2196/65197
Scoping Review: Study of Herbs Consumption for Self-Medication in Indonesia 2019-2022
Authors: Azzahra Fatimah , Astuti Ayun Dwi , Arifin Bustanul , Alam Gemini 
Published: January 2025

Indonesia is a country that has high biodiversity and is rich in traditional medicine from natural ingredients or herbs. One use of these natural ingredients is as a treatment for self-medication. Many previous studies have been carried out but none has reviewed it systematically, especially during the Covid-19 pandemic. This research was carried out systematically using the PRISMA statement approach using the Google Scholar data bank. Out of 2,214 papers in the 2019-2022 period, 45 articles/scientific papers papers met the criteria, including inclusion and exclusion criteria, for a description/profile of the use of natural ingredients or herbs as self-medication for traditional medicine. The central region of Java (D.I.Y Yogyakarta and Central Java) is the region with the largest number of articles. The distinctiveness of Indonesia's approach to self-medication lies in its utilization of various natural elements to address similar ailments, which can be attributed to geographical factors, cultural beliefs, and diverse knowledge across different regions. Meanwhile, Covid-related studies were very limited due to the availability or the preference for chemical self-medication.
Advocacy Coalition in Baduy Tourism Policy:
Authors: Elvita Amara 
Published: January 2025

The political participation of the Baduy indigenous community in sustainable tourism policy has led to the emergence of two advocacy coalitions with differing views: one supports tourism for its economic potential, while the other opposes it to protect local values and the environment. This division reflects the community's involvement in policy-making. The pro-tourism group believes proper regulation can yield economic benefits without harming the culture or the environment. Conversely, the anti-tourism group prioritises cultural preservation and environmental conservation. The Advocacy Coalition Framework (ACF) helps understand these interactions. Although pro-tourism advocacy dominates policy decisions, initiatives like tourist restrictions from the Baduy Customary Organisation are also recognised and implemented, indicating that political participation can result in more balanced policies. The opposing coalitions also highlight the dynamics of political participation in shaping sustainable tourism policies in an area where an indigenous community lives.
Pengaruh Coating Lidah Buaya dengan Penambahan Karagenan terhadap Umur Simpan Jambu Kristal Selama Penyimpanan
Authors: Angraeni Rini , Tamrin Tamrin , Asmara Sandi , Warji Warji 
Published: January 2025

This research was conducted to observe the effect of edible coating aloe verawith a combination of carrageenan concentration on the shelf life of crystal guava fruit. This study was designed using linear regression consisting of 2 factors. The first factor consists of 3 levels of carrageenan concentration which includes K1 = 0.1% , K2 = 0.2% , K3 = 0.3% . The second factor is the variation of storage temperature which consists of 2 levels, namely storage at room temperature 27℃ and cold temperature 11℃. The application of edible coating of crystal guava fruit with a layer of aloe vera gel and carrageenan has an effect on maintaining the quality of crystal guava fruit against weight loss, green skin color, hardness, total dissolved solids, water content and organoleptic test of storage taste (room temperature) of crystal guava fruit to age. keep 6 days and storage (low temperature) crystal guava fruit up to a shelf life of 9 days after application. K3 treatment (carrageenan concentration 0.3%) can be used to maintain the quality of crystal guava fruit during storage. Keywords: Carrageenan, Edible Coating, Stronge Temperature, Sweet Seedless Guava
Optimasi Kecepatan Putar dalam Peningkatan Mutu Biji Kemiri pada Mesin Pemecah Cangkang Biji Kemiri (Aleurites moluccana willd.)
Authors: Sutejo Agus , Fajri Rahmatul , Sucahyo Lilis 
Published: January 2025

Postharvest handling of candlenut in the traditional way is less effective and efficient. A worker is only able to break as much as 9–10 kg of candlenut/day and this also causes high work fatigue, besides thas many kernels are broken and destroyed (percentage og intact round kernels is only 40–60 %) so the price of candlenut becomes cheaper. Therefore, a candlenut crushing machine is needed with an optimum rorational speed that able to provide optimal and consistent energy to candlenuts crushing result. The candlenut material was dried at at 90 ˚C for 3 and 4 hours, then put it in ice water at 5 ˚C for 15 minutes. It was drained for 20 minutes and a drop test was carried out to find the optimum energy and rotational speed in cracking the candlenut. The result of rotaional speed are set up on the candlenut shell breking machine. Optimum solving result obtained of 490,5 Joules. Equivalent to candlenut dropped from a height of 5 meters with a rotating speed of 337,88 rpm. Keywords: Candlenut, Post Harvest, Rotational Speed
Uji Simulasi Keretakan Telur dengan Alat Guncangan (Getaran)
Authors: Hanif Anwar , Tamrin Tamrin , Kuncoro Sapto , Zulkarnain Iskandar 
Published: January 2025

Eggs are livestock products that contribute greatly to the adequacy of community nutrition. . The egg composition physically consists of 10% shells (eggshells /shells), 60% egg whites, and 30% egg yolks. The purpose of this study is to test a simulation tool for egg transportation based on the amount of vibration, number of stacks and type of egg container on egg quality. a standard deviation test is performed. The results of this study showed the average physical characteristics of chicken eggs measured by 57.6 mm for the longest diameter, 44.8 mm for the shortest diameter, 63.9 grams for weight, 66.8 ml for volume, and 0.96 for density. The average physical characteristics of duck eggs measured were 57.1 mm for the longest diameter, 45.9 mm for the shortest diameter, 67 grams for weight, 69.8 ml for volume, and 0.96 for density. The average physical characteristics of quail eggs measured were 31.9 mm for the longest diameter, 24.9 mm for the shortest diameter, 10.7 grams for weight, 60.2 ml for volume, and 0.18 for density, No. there are broken eggs when dropped at a height of 5 to 20 cm from the ground surface while at a height of 25 cm there are broken eggs as many as 9.38% of the total sample for chicken eggs. Mechanical vibrations of eggs at an amplitude of 5 cm with a rotational speed of 40 rpm, 60 rpm and 76 rpm for 20 minutes do not result. mechanical damage to chicken eggs, duck eggs and quail eggs in the form of cracks or broken. Keywords: eggs, Simulation tools.
The Effect of Biochar from Oil Palm Empty Fruit Bunches (EFB) on the Efficiency of Urea Fertilizer in the Production of Chinese Cabbage (Brassica rappa var. parachinesis L.)
Authors: Agustin Sisi , Haryanto Agus , Triyono Sugeng 
Published: January 2025

This research study aims to determine proper composition of biochar, to find out the efficiency of fertilizer used, and to evaluate the effect of interaction between biochar and urea fertilizer used on the cultivation of green mustard. This study used Complete Randomized Design (CRD) consisting of 2 factors with factorial arrangement. The first factor was biochar dosage consisting of: control (without biochar), 5 tons/ha, 7.5 tons/ha, and 10 tons/ha. The second factor was urea dosage consisting of: control (without urea), 75 kg/ha, 125 kg/ha, and 200 kg/ha. All treatment combinations were replicated 3 times so there were 48 experimental units obtained. The parameters observed were: soil properties, biochar properties, plant height, leaf width, number of leaves, canopy area, shoot fresh weight, shoot dry weight, root fresh weight, root dry weight, total fresh weight, water consumption, water productivity, and fertilizer productivity.The addition of biochar is proven to increase the productivity of mustard plants. The use of urea fertilizer had no significant effect, presumably because of the low soil organic matter content. The interaction between biochar doses and urea fertilizer doses was not significant and only significant for the fertilizer productivity parameters. Research also revealed that the optimal dose of biochar for mustard greens is 5 tons/ha, giving an average yield of 88.25 g/plant and fertilizer productivity of 210.41%. Keywords: Biochar, Dose, Green Mustard, Oil Palm Empty Fruit Bunch (OPEFB), Urea Fertilizer.