bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential of integrating Solid Oxide Fuel Cell based on biomass in power generation in Malaysia: A feasibility study
Authors: Ravi R , Shieela Kalib N , Muchtar A , Rao Somalu M 
Published: October 2022

Abstract
Although many initiatives have been launched to achieve the ambitious Net Zero 2050 target, Malaysia is still struggling to control carbon emissions, particularly from electricity and heat generation. Fortunately, the potential to generate electricity from biomass in Malaysia reduces reliance on fossil fuels for power generation. Combining biomass gasification with a solid oxide fuel cell (SOFC) promises sustainable and more efficient performance than the traditional approach. To ensure optimal operation, the biomass-derived fuel should be compatible with the gasification system. A numerical simulation was carried out to gain insight into the feasibility of integrating hybrid gasification (GT) with SOFC based on selected biomass-derived fuels (i) palm oil mill effluent (POME) and (ii) refuse-derived fuel. A detailed anode-based planar SOFC model is developed and adopted into a gasification system that operates with an ideal gas under steady-state conditions. The other components considered in this study are a recuperator, combustor, and high-pressure turbine. A comprehensive energy balance for each stage was prepared to determine the overall performance of the system with higher accuracy. A detailed analysis shows that POME gave better results owing to its higher calorific value, resulting in higher thermal energy production. Reducing the required fuel flow rate has a positive effect on the overall performance compared with increasing the injected air flow rate. Furthermore, reducing the fuel flow rate tends to increase the combined efficiency. The study concludes that the fuel flow rate has a significant impact on the performance of the SOFC-GT hybrid system, particularly on combined efficiency and overall performance.
Decomposition and decoupling analyses of CO2 emissions and economic growth: A comparative study between Malaysia and Vietnam
Authors: Kiwan B , Kalib N S , Muchtar A 
Published: October 2022

Abstract
During the COVID-19 pandemic, Malaysia and Vietnam has managed to show a strong positive growth domestic product (GDP) growth indicator – with both countries recording an average increase of more than 4% annually. However, there was a strong positive correlation between GDP and carbon dioxide (CO2) emissions worldwide. As the impact of climate change becomes more evident, especially in Southeast Asia, it is crucial to assess the relationship between these two indicators caused by gross electricity generation, especially in the post-pandemic period. In this study, we compared the decoupling performance of CO2 emissions and GDP growth between Malaysia and Vietnam. The data for Malaysia and Vietnam were quantified by the decoupling method based on the Tapio decoupling model. The data were then decomposed using the Kaya identity into the driving factors affecting decoupling. This was then used to form the decomposition index using the Logarithmic Mean Divisia Index-I (LMDI-I). Data were generated based on three scenarios: i) 2017-2019, i.e. pre-pandemic, ii) 2019-2020, peri-pandemic and iii) 2021-2025, to predict post-pandemic. In terms of the overall decoupling trend, the study shows that: (1) the change in CO2 emissions in both sovereign states decreased dramatically at the beginning of the COVID-19 pandemic. However, Malaysia experienced negative change in CO2 emissions, while Vietnam still experienced a positive change. This is due to Vietnam’s slightly higher reliance on coal for power generation than Malaysia. (2) A strong decoupling in the projected decoupling between the change in CO2 emissions and GDP in Vietnam, while the two indicators remain coupled for Malaysia. This is due to Vietnam’s more aggressive policy in the adoption of renewable energy - especially through the mass installation of rooftop photovoltaic systems. In contrast, Malaysian policy remains conservative, emphasising reliability at the cost of a huge year-on-year change in CO2 emissions.
Accelerated Weathering of Limestone Bicarbonate Induced CaCO3 Precipitation in A Mixture of Sand, Fly Ash and CaO
Authors: Chai S Y W , Ngu L H 
Published: October 2022

Abstract
Excessive generation of CO2 and industrial wastes has sparked environmental concerns around the globe. In this research, Accelerated Weathering of Limestone (AWL) process uses calcium carbonate (CaCO3) to capture CO2 from ambient air. It achieved an absorption efficiency of 31.88 %. The calcium bicarbonate effluent produced via AWL is used to precipitate calcium carbonate in lime mortar (LM) mixture containing sand and calcium oxide (CaO) with fly ash, an industrial waste. This helps develop a novel utilization pathway for the respective wastes via production of a novel green construction material termed bicarbonate lime mortar infused with fly ash (BLMFA). The fly ash addition percentage in bicarbonate lime mortar (BLM) mix are 12.12, 17.15 and 21.63 wt.%. This project also studies the effect of curing time (7, 28 and 88 days) on development of BLMFA strength. Experimental results found that at 7 days, the strength of BLMFA (0.44 to 0.48 MPa) is lower than the conventional LM, which has a strength of 0.52 MPa. However, on 88 days, 17.15 wt.% BLMFA achieved a strength of 0.82 MPa, which is 0.060 MPa higher than the conventional LM sample. In addition, BLMFA also possesses high CaCO3 content of 36.7 to 44 wt.% out of the targeted 54.37 wt.% compared to conventional LM, which could only achieve 27.14 wt.% CaCO3. This indicates that infusion of fly ash can enhance the carbonation efficiency of calcium sources to CaCO3. All in all, AWL process and BLMFA precipitation possess the capability to diminish anthropogenic CO2 while beneficially utilizing industrial waste.
Synthesis of Integrated Flower Waste Biorefinery: Optimisation with Economic Consideration
Authors: Chong EHY , Ng DKS , Andiappan V , Ng LY , Shivaprasad P 
Published: October 2022

Abstract
Disposal of flower waste is a major environmental issue especially in India. Improper disposal of flower waste from heritage and cultural activities has resulted in an imbalance natural ecosystem causing water, soil, and air pollution. Hence, it is critical to minimise the amount of flower waste produced on daily basis by converting the flower waste into value-added products. These value-added products can be formed in an integrated flower waste biorefinery. Hence in this work, a systematic optimisation model for the synthesise of an integrated flower waste biorefinery with maximum economic performance is presented.
Model Predictive Control – Sliding Mode Control of a pH system
Authors: Ooi W X , Hermansson A W , Lim C H 
Published: October 2022

Abstract
This paper studies the feasibility of using discrete sliding mode controller (SMC) to achieve offset-free control of nonlinear processes in the presence of disturbances. The performance of the SMC is compared to a multiple model predictive controller (MMPC) studying the ability of set-point tracking using the pH system as a case study. The results presented from the comparison show that SMC can perform offset-free control of a pH system, with the major drawback being slow response as well as oscillation at some pH values. Finally, a design of a combination between MMPC and SMC (MMPC-SMC) is proposed, with MMPC carrying out basic control response while the SMC fulfils the role of eliminating the offset. However, the inaccurate reading in the MATLAB simulation model does not generate the expected results on the pH control. Therefore, the modification on the MATLAB models is required to achieve the improved control system on the offset-free behaviour for the set-point tracking.
Comparative of alginate/graphene oxide and alginate/magnetite graphene oxide aerogel as adsorbents
Authors: Marzuki A S , Mustapa A N , Othman N H , Hanipah S H , Martin Á , Cocero M J 
Published: October 2022

Abstract
Magnetite graphene oxide (MGO) has gained attention as a potential adsorbent in wastewater treatment. In this study, incorporation of MGO into biopolymer matrix and dried by supercritical CO2 to improve the adsorption efficiency is presented. Alginate/MGO aerogel was prepared by blending the MGO with alginate and formed hydrogel by ionic crosslinking through external gelation. The blend ratio of MGO and alginate studied are comprised of 2 and 3 wt%, respectively. The hydrogel was dried by supercritical CO2 at 110 ± 5 bar and 40 °C in 4h. The physical-chemical properties of alginate/MGO adsorbent and its adsorption efficiency via removal of methylene blue (MB) are studied. The sharp curve for 30% weight loss for both types of adsorbents has been shown around 200 °C in TGA correspond to the exothermic peak form in DSC analysis. Alginate/GO and alginate/MGO are stable over temperatures of 300 and 700 °C, respectively. Alginate/GO successfully adsorbed 90% of MB concentration meanwhile the alginate/MGO had removed up to 84% of MB. Another highlighted technique is supercritical CO2 drying which considered as one of the most promising techniques to preserve the structure of aerogel with minimal shrinkage as low as 15% in comparison to ambient drying (50%).
Flexible and ultralight MXene paper as a current collector for microsized porous silicon anode in high-energy lithium-ion batteries
Authors: Wang Jingyan , An Yongling , Shen Hengtao , Man Quanyan , Feng Jinkui 
Published: October 2022

Abstract
Silicon (Si) is a new candidate anode material for lithium-ion batteries. The porous treatment of Si anode has been proved to be effective. In order to improve the interface performance and energy density of batteries, we start from the current collector (CC) and make further improvements. Combined with the advantages of new two-dimensional material MXene in electrochemical aspects, we make MXene replace the traditional Cu foil as CC of Si anode. The prepared MXene paper is both flexible and lightweight. After coating the Si slurry on it, the assembled half cells and 5 V-class full cells can achieve normal lithium-ion intercalation and deintercalation. Moreover, compared with the battery using Cu current collector, the volume expansion of porous silicon in the battery with MXene is further alleviated, and the cycle stability performance is also improved.
Corrosion behaviour of maize husk reinforced aluminium (1070) metal matrix composites in chloride-sulphate solution
Authors: Loto Roland Tolulope , Ajuwaeze Williams Joseph 
Published: October 2022

Abstract
The effect of maize husk (MH) particulates on the corrosion resistance of 1070 aluminium alloy (AA70) matrix at 5% and 15% wt. content, and 150 μm and 300 μm particle size (AA70/MH composites) was studied in 3.5% NaCl, 0.0125 M H2SO4 and 3.5% NaCl/0.0125 M H2SO4 solutions. Potentiodynamic polarization technique, open circuit potential measurement, weight loss analysis, optical microscopy characterization, x-ray fluorescence and x-ray diffractometry were used for the investigation. Results show increase in MH %wt. content and particle size decreases the corrosion rate of AA70/MH composite. Data from potentiodynamic polarization and weight loss analysis shows AA70/MH composite at 15% wt. content and 300 μm particle size exhibited the lowest corrosion values of 0.135 mm y−1, 0.156 mm y−1 and 1.445 mm y−1, and −0.00043 mm y−1, 0.001 04 mm y−1 and 0.00218 mm y−1 in 3.5% NaCl, 0.0125 M H2SO4 and 3.5% NaCl/0.0125 M H2SO4 solutions. Optical representative images of the composites showed the presence of micro-pits on samples from NaCl solution, macro-pits and extensive surface deterioration from H2SO4 solution, and combined localized and total surface deterioration from NaCl-H2SO4 solution. Weight loss plots showed oxide formation significantly influenced the corrosion behavior of the alloys with respect to time. Open circuit potential plots showed AA70/MH composite at 5% wt. content and 150 um particle size was the most electronegative with the highest thermodynamic tendency to corrosion. Significant X-ray diffraction peaks from AA70/MH composite at 15% wt. content and 300 μm particle size showed the presence of corrosion resistant phase compounds of Al2O3 and Al(ZnS2) before and after corrosion.
Postpartum Hospital Readmissions With and Without Severe Maternal Morbidity Within 1 Year of Birth, Oregon, 2012–2017
Authors: Kaufman Menolly , McConnell K John , Carmichael Suzan L , Rodriguez Maria I , Richardson Dawn , Snowden Jonathan M 
Published: October 2022

Abstract
Postpartum readmissions (PPRs) represent a critical marker of maternal morbidity after hospital childbirth. Most severe maternal morbidity (SMM) events result in a hospital admission, but most PPRs do not have evidence of SMM. Little is known about PPR and SMM beyond the first 6 weeks postpartum. We examined the associations of maternal demographic and clinical factors with PPR within 12 months postpartum. We categorized PPR as being with or without evidence of SMM to assess whether risk factors and timing differed. Using the Oregon All Payer All Claims database, we analyzed hospital births from 2012–2017. We used log-binomial regression to estimate associations between maternal factors and PPR. Our final analytical sample included 158,653 births. Overall, 2.6% (n = 4,141) of births involved at least 1 readmission within 12 months postpartum (808 (19.5% of PPRs) with SMM). SMM at delivery was the strongest risk factor for PPR with SMM (risk ratio (RR) = 5.55, 95% confidence interval (CI): 4.14, 7.44). PPR without SMM had numerous risk factors, including any mental health diagnosis (RR = 2.10, 95% CI: 1.91, 2.30), chronic hypertension (RR = 2.17, 95% CI: 1.85, 2.55), and prepregnancy diabetes (RR = 2.85, 95% CI: 2.47, 3.30), all which were on par with SMM at delivery (RR = 1.89, 95% CI: 1.49, 2.40).
Temporal stability of spatial cytotype structure in mixed-ploidy populations ofCentaurea stoebe
Authors: Mráz Patrik , Španiel Stanislav , Skokanová Katarína , Šingliarová Barbora 
Published: October 2022

AbstractSpatial segregation of cytotypes reduces the negative effect of frequency-dependent mating on the fitness of minority cytotype(s) and thus allows its establishment and coexistence with the majority cytotype in mixed-ploidy populations. Despite its evolutionary importance, the stability of spatial segregation is largely unknown. Furthermore, closely related sympatric cytotypes that differ in their life histories might exhibit contrasting spatial dynamics over time. We studied the temporal stability of spatial structure at a secondary contact zone of co-occurring monocarpic diploids and polycarpic tetraploids of Centaurea stoebe, whose tetraploid cytotype has undergone a rapid range expansion in Europe and became invasive in North America. Eleven years after the initial screening, we re-assessed the microspatial distribution of diploids and tetraploids and their affinities to varying vegetation-cover density in three mixed-ploidy populations in Central Europe. We found that overall, spatial patterns and frequencies of both cytotypes in all sites were very similar over time, with one exception. At one site, in one previously purely 2x patch, diploids completely disappeared due to intensive succession by shrubby vegetation. The remaining spatial patterns, however, showed the same cytotype clumping and higher frequency of 2x despite subtle changes in vegetation-cover densities. In contrast to the expected expansion of polycarpic tetraploids having higher colonization ability when compared to diploids, the tetraploids remained confined to their former microsites and showed no spatial expansion. Spatial patterns of coexisting diploids and tetraploids, which exhibit contrasting life histories, did not change over more than a decade. Such temporal stability is likely caused by relatively stable habitat conditions and very limited seed dispersal. Our results thus imply that in the absence of a disturbance regime connected with frequent human- or animal-mediated seed dispersal, spatial patterns may be very stable over time, thus contributing to the long-term coexistence of cytotypes.
LargeMetabo: an out-of-the-box tool for processing and analyzing large-scale metabolomic data
Authors: Yang Qingxia , Li Bo , Wang Panpan , Xie Jicheng , Feng Yuhao , Liu Ziqiang , Zhu Feng 
Published: October 2022

Abstract
Large-scale metabolomics is a powerful technique that has attracted widespread attention in biomedical studies focused on identifying biomarkers and interpreting the mechanisms of complex diseases. Despite a rapid increase in the number of large-scale metabolomic studies, the analysis of metabolomic data remains a key challenge. Specifically, diverse unwanted variations and batch effects in processing many samples have a substantial impact on identifying true biological markers, and it is a daunting challenge to annotate a plethora of peaks as metabolites in untargeted mass spectrometry-based metabolomics. Therefore, the development of an out-of-the-box tool is urgently needed to realize data integration and to accurately annotate metabolites with enhanced functions. In this study, the LargeMetabo package based on R code was developed for processing and analyzing large-scale metabolomic data. This package is unique because it is capable of (1) integrating multiple analytical experiments to effectively boost the power of statistical analysis; (2) selecting the appropriate biomarker identification method by intelligent assessment for large-scale metabolic data and (3) providing metabolite annotation and enrichment analysis based on an enhanced metabolite database. The LargeMetabo package can facilitate flexibility and reproducibility in large-scale metabolomics. The package is freely available from https://github.com/LargeMetabo/LargeMetabo.
Alignment-free comparison of metagenomics sequences via approximate string matching
Authors: Chen Jian , Yang Le , Li Lu , Goodison Steve , Sun Yijun 
Published: October 2022

Abstract

Summary
Quantifying pairwise sequence similarities is a key step in metagenomics studies. Alignment-free methods provide a computationally efficient alternative to alignment-based methods for large-scale sequence analysis. Several neural network-based methods have recently been developed for this purpose. However, existing methods do not perform well on sequences of varying lengths and are sensitive to the presence of insertions and deletions. In this article, we describe the development of a new method, referred to as AsMac that addresses the aforementioned issues. We proposed a novel neural network structure for approximate string matching for the extraction of pertinent information from biological sequences and developed an efficient gradient computation algorithm for training the constructed neural network. We performed a large-scale benchmark study using real-world data that demonstrated the effectiveness and potential utility of the proposed method.

Availability and implementation
The open-source software for the proposed method and trained neural-network models for some commonly used metagenomics marker genes were developed and are freely available at www.acsu.buffalo.edu/~yijunsun/lab/AsMac.html.

Supplementary information
Supplementary data are available at Bioinformatics online.
AHoJ: rapid, tailored search and retrieval of apo and holo protein structures for user-defined ligands
Authors: Feidakis Christos P , Krivak Radoslav , Hoksza David , Novotny Marian 
Published: October 2022

AbstractSummaryUnderstanding the mechanism of action of a protein or designing better ligands for it, often requires access to a bound (holo) and an unbound (apo) state of the protein. Resources for the quick and easy retrieval of such conformations are severely limited. Apo–Holo Juxtaposition (AHoJ), is a web application for retrieving apo–holo structure pairs for user-defined ligands. Given a query structure and one or more user-specified ligands, it retrieves all other structures of the same protein that feature the same binding site(s), aligns them, and examines the superimposed binding sites to determine whether each structure is apo or holo, in reference to the query. The resulting superimposed datasets of apo–holo pairs can be visualized and downloaded for further analysis. AHoJ accepts multiple input queries, allowing the creation of customized apo–holo datasets.Availability and implementationFreely available for non-commercial use at http://apoholo.cz. Source code available at https://github.com/cusbg/AHoJ-project.Supplementary informationSupplementary data are available at Bioinformatics online.
Think-Aloud: Effect on Adolescent Deaf Students’ Use of Reading Comprehension Strategies
Authors: Salehomoum Maryam 
Published: October 2022

Abstract
This study examined the effect of explicit instruction of reading comprehension strategies, such as identification of unknown vocabulary and relating text to background knowledge, on four deaf and hard of hearing students’ use of strategies and reading comprehension performance pre- and post-intervention. Explicit instruction of strategies consisted of discussion of targeted strategies and think-aloud (verbalizing one’s thought processes while reading) to model strategies. The data presented is from a more in-depth study completed during the 2017–2018 academic year. Few studies have implemented think-aloud in evaluating deaf adolescents’ reading challenges and the efficacy of strategy use. This study provided insight into both of these issues. Results show an increase in the variety of strategies used by students and frequency of strategy use post-intervention. Results also indicate improved comprehension scores for two students. Close examination of the data, however, reveals ongoing metacognitive challenges (such as lack of consistent identification of key unknown words and lack of awareness of comprehension breakdowns) and inconsistency in the efficacious use of strategies. Findings indicate a need for ongoing assessment of the depth and efficacy of strategy use and individualized instruction.