bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preliminary study on Azolla cultivation and characterization for sustainable biomass source
Authors: Adzman N , Goh S J , Johari A , Zainal Alam M N H , Kamaruddin M J 
Published: April 2022

Abstract

Azolla is a freshwater fern that belongs to the Azollaceae family. It is easy to grow and is highly productive. It can fix atmospheric nitrogen due to the presence of Anabaena azollae. Azolla has been applied to the rice field as a classic fertilizer. It is a good source of protein and contains almost all essential amino acids and minerals. Various research has been done and is still ongoing to determine the capability of Azolla as a phytoremediator and to be used as a sustainable bioenergy source. This preliminary study investigated the ideal environment for Azolla cultivation in Malaysia (humid weather throughout the year with average daily temperature across Malaysia between 21°C and 32°C). To the best of our knowledge, there is no research conducted in Malaysia to study the optimum environment for Azolla cultivation. Therefore, determining the optimum condition for growing Azolla was done by manipulating parameters: water depth, nutrient concentration, pH, and sunlight exposure. Meanwhile, chemical compositions (moisture, crude protein, crude fat, ash, crude fibre, carbohydrate and energy) were determined using proximate analysis. Results obtained showed that Azolla growth was the best in water depth of 20 cm, the nutrient concentration of 812.5 ppm, pH of 7 and under 100% sunlight exposure. Dried Azolla had 6.38% moisture, 27.1% crude protein, 6.37% crude fat, 14.29% ash, 34.29% crude fibre, 45.86% carbohydrate and 349.17 kcal/100 g energy. Based on the result, Azolla cultivated in this experiment could be used as a sustainable biomass source to produce animal feed (high protein content) and bioenergy (high fibre content).
Environmental impacts of utilization of ageing fixed offshore platform for ocean thermal energy conversion
Authors: Zulkifli M A R , Husain M K Abu , Zaki N I Mohd , Jaafar A B , Mukhlas N A , Ahmad S Z A Syed , Soom E Mat , Azman N. U. 
Published: April 2022

Abstract
Most Malaysian jacket platforms have outlived their design life. As these old platforms have outlived their design life, other alternatives must be considered. As several offshore oil and gas extraction installations approach the end of their operational life, many options such as decommissioning and the development of a new source of energy such as wind farms are introduced. The objective of this paper is to investigate the environmental impacts of utilising ageing fixed offshore platform as a source for Ocean Thermal Energy Conversion (OTEC). The environmental impact of utilising an ageing fixed offshore platform as an OTEC source is discussed. OTEC produces energy by taking advantage of temperature variations between the ocean surface water and the colder deep water through cold-water intake piping, which requires a seawater depth of 700 metres. The output of this study shows that OTEC is envisioned to preserve marine life, becoming a new and reliable source of energy, assist clean water production, and reduce the negative impact of climate change. OTEC platforms utilising ageing platforms may lead to 44 % of fish catch in the ocean, remove 13 GW of surface ocean heat for every GW of electricity production per year, generate 1.3105 tonnes of hydrogen per year for each GW of electricity generated. In addition, OTEC platforms can reduce approximately 5106 tonnes of carbon dioxide from the environment for 1 GW of electricity generated per year, and supply 2 million litres of water per day for a 1 MW platform. Since Malaysia’s seawater profile allows for installing a fixed offshore platform as an OTEC power plant, Malaysia has many potentials to profit from the OTEC process.
A short review on the promotional effects of ceria-based catalyst for dry reforming methane
Authors: Liew S Y , Jalil A A , Tan J S 
Published: April 2022

Abstract
Dry reforming of methane (DRM) appears as a promising process for the industrial production of syngas in comparison to other conventional reforming technologies. However, DRM process suffers from catalyst deactivation induced by carbonaceous species which reduces the catalyst lifespan. Currently, catalytic designs in DRM have trended towards the incorporation rare-earth metals. As such, ceria (Ce) based catalyst has recently attracted research interest for its key feature to mitigate catalyst deactivation owing to its complementary redox and oxygen storage properties for the removal of surface carbon deposit. The present short review summarizes on the recent catalytic performance of Ce-based catalyst and impact of ceria redox on the DRM mechanism. The utilization of oxygen vacancies introduced by the Ce redox support enhances the catalytic activity by providing additional bifunctional sites and intermediate species to facilitate the surface reaction rate. This perspective will elucidate the role of oxygen vacancies in Ce supports and fine tune the catalytic performance of DRM for industrial applications.
Data science application in structural integrity analysis of fixed offshore jacket platform
Authors: Yak X C , Soom E Mat , Quen L K , Husain M K Abu , Azahar M A , Zaki N I Mohd , Kang H S 
Published: April 2022

Abstract
Accuracy in analysing the integrity of a structure is critical for determining the structure’s fitness for service and reliability status. Today, a variety of techniques and approaches are applied, including the use of data science applications. Data science is a synthesis of computer science, mathematics, and statistics. Meanwhile, the integrity of a structure is susceptible to a mix of statistical and technical design uncertainties that may remain flexible as long as the structure is capable of successfully managing the encountered load. Numerous applications are used in the oil and gas sector to estimate the probability of failure (POF), but they all have a particular restriction. Integral interference equations based on load versus strength are reliable for determining the POF of fixed offshore structures. This study is a quantitative risk assessment, emphasising the Python application, an improved and reliable method for calculating the POF value. A representative sample of the monopod offshore structure was chosen and subjected to global non-linear analysis in this study. The most reliable form of distribution was predetermined, and the algorithm created using Python was used to apply and compute the suitable integral equation depending on the load and strength conditions. The Python method’s result demonstrated a high degree of confidence in calculating the new POF in intact condition from a design perspective, inspection interval, and risk to consider.
Improving time and position resolutions of RPC detectors using time over threshold information
Authors: John J.M. , Pethuraj S. , Majumder G. , Mondal N.K. , Ravindran K.C. , Datar V.M. , Satyanarayana B. 
Published: April 2022

Abstract
INO-ICAL is a proposed underground experiment to study the oscillation parameters of neutrinos by detecting those produced in the atmospheric air showers. The Iron CALorimeter (ICAL) is to have 151 layers of iron plates stacked vertically corresponding to a height of ∼14.5 m, with active detector elements inserted between the iron layers. The iron layers will be magnetized with a maximum magnetic field of 1.5 T to enable the measurement of the charge and momentum of the μ
- (or μ
+) produced by ν

μ
(or ν̅

μ
) interactions inside the detector throughout the operation. Resistive Plate Chambers (RPCs) have been chosen as the active detector elements as they are amenable to large area coverage, as well as due to their high particle detection efficiency, long-term performance and low cost of production. The major factors that weigh in on the physics potential of the ICAL detector are the efficiency, position resolution and time resolution of the large area RPCs. A prototype detector called mini-ICAL (with 11 iron layers) was commissioned in order to understand the engineering challenges in building the large-scale electromagnet and its ancillary systems, and also to study the performance of the RPC detectors and readout electronics developed by the INO collaboration. As part of the performance study of the RPC detectors, an attempt is made to improve their position and time resolutions. The designed position resolution for the ICAL detector is of the order of 1 cm and the required time resolution is ∼1 ns. Even a small improvement in the position and time resolution will help to improve the measurements of momentum and directionality of the neutrinos in the ICAL detector. In ICAL detector simulation, where muons traverse in all directions with on average 20 RPC layers, a 30 % improvement in position resolution results in ∼10 % improvement in the momentum resolution at 3 GeV. Due to large iron materials in between two RPCs, the resolution is dominated by the effect of multiple scattering at this momentum. Also for a muon with 10 layer hit, the charge ambiguity reduces from 0.04 % to 0.001 % when the time resolution improves from 1 ns to 0.7 ns. The Time-over-Threshold (ToT) of the RPC pulses is recorded by the readout electronics. ToT is a measure of the pulse width and consequently the pulse amplitude. This information is used to improve the time and position resolution of RPCs and consequently INO's physics potential.
Dental resin composites with improved antibacterial and mineralization properties via incorporating zinc/strontium-doped hydroxyapatite as functional fillers
Authors: Li Yechen , Zhang Daixing , Wan Zhuo , Yang Xiaoping , Cai Qing 
Published: April 2022

Abstract
This study intends to improve the antibacterial and mineralization performance of photocurable dental resin composites (DRCs) to reduce the possibility of repair failure caused by secondary caries. To the end, functionalized hydroxyapatite (HAp), including Zn-doped (Zn/HAp) and Sr-doped HAp (Sr/HAp), were added into the bisphenol A glycidyl methacrylate and triethylene glycol dimethacrylate mixture, providing the DRCs with antibacterial and mineralization capacity, respectively. By controlling the total amount of inorganic filler at 70 wt%, these HAp powders were introduced into the resin matrix with barium glass powder (BaGP), while the ratios of HAp to aGP varied from 0:70 to 8:62. And the 8 wt% of HAp could be pure HAp, Zn/HAp, Sr/HAp, or Zn/HAp +Sr/HAp in different ratios (i.e. 2:6, 4:4, 6:2). Though the fillers varied, the obtained DRCs displayed similar micro-morphology, flexural strength (∼110 MPa) and modulus (∼7 GPa), and Vickers hardness (∼65). When the doping amounts of Sr2+/Zn2+ reached 15 mol% of Ca2+ in the Sr/HAp and Zn/HAp, the DRCs displayed a high antibacterial activity by killing ∼95% Staphylococcus aureus, and induced rich mineral deposition on surface in simulated body fluid. The incorporation of the Zn/HAp and Sr/HAp into the DRCs did not cause significant cytotoxicity, with L929 fibroblasts remaining >99% viability as cultured in extracts made from the DRCs. Therein, the DRC preparations containing both Zn/HAp and Sr/HAp have achieved improvements in both the biomineralization and antibacterial performance, as well as, having sufficient mechanical properties and excellent biocompatibility for dental restoration.
Integrability breaking in the Rule 54 cellular automaton
Authors: Lopez-Piqueres Javier , Gopalakrishnan Sarang , Vasseur Romain 
Published: April 2022

Abstract
Cellular automata have recently attracted a lot of attention as testbeds to explore the emergence of many-body quantum chaos and hydrodynamics. We consider the Rule 54 model, one of the simplest interacting integrable models featuring two species of quasiparticles (solitons), in the presence of an integrability-breaking perturbation that allows solitons to backscatter. We study the onset of thermalization and diffusive hydrodynamics in this model, compute perturbatively the diffusion constant of tracer particles, and comment on its relation to transport coefficients.
Engineering cryoelectrospun elastin-alginate scaffolds to serve as stromal extracellular matrices
Authors: Ramesh Pujhitha , Moskwa Nicholas , Hanchon Zachary , Koplas Adam , Nelson Deirdre A , Mills Kristen L , Castracane James , Larsen Melinda , Sharfstein Susan T , Xie Yubing 
Published: April 2022

Abstract
Scaffold-based regenerative strategies that emulate physical, biochemical, and mechanical properties of the native extracellular matrix (ECM) of the region of interest can influence cell growth and function. Existing ECM-mimicking scaffolds, including nanofiber (NF) mats, sponges, hydrogels, and NF-hydrogel composites are unable to simultaneously mimic typical composition, topography, pore size, porosity, and viscoelastic properties of healthy soft-tissue ECM. In this work, we used cryoelectrospinning to fabricate 3D porous scaffolds with minimal fibrous backbone, pore size and mechanical properties similar to soft-tissue connective tissue ECM. We used salivary glands as our soft tissue model and found the decellularized adult salivary gland (DSG) matrix to have a fibrous backbone, 10–30 μm pores, 120 Pa indentation modulus, and ∼200 s relaxation half time. We used elastin and alginate as natural, compliant biomaterials and water as the solvent for cryoelectrospinning scaffolds to mimic the structure and viscoelasticity of the connective tissue ECM of the DSG. Process parameters were optimized to produce scaffolds with desirable topography and compliance similar to DSG, with a high yield of >100 scaffolds/run. Using water as solvent, rather than organic solvents, was critical to generate biocompatible scaffolds with desirable topography; further, it permitted a green chemistry fabrication process. Here, we demonstrate that cryoelectrospun scaffolds (CESs) support penetration of NIH 3T3 fibroblasts 250–450 µm into the scaffold, cell survival, and maintenance of a stromal cell phenotype. Thus, we demonstrate that elastin-alginate CESs mimic many structural and functional properties of ECM and have potential for future use in regenerative medicine applications.
Innovation for forming aluminum alloy thin shells at ultra-low temperature by the dual enhancement effect
Authors: Xiaobo Fan , Shijian Yuan 
Published: April 2022

Abstract
Integral thin shells made of high strength aluminum alloys are urgently needed in new generation transportation equipment. There are challenges to overcoming the co-existing problems of wrinkling and splitting by the cold forming and hot forming processes. An innovative technology of ultra-low temperature forming has been invented for aluminum alloy thin shells by the new phenomenon of ‘dual enhancement effect’. That means plasticity and hardening are enhanced simultaneously at ultra-low temperatures. In this perspective, the dual enhancement effect is described, and the development, current state and prospects of this new forming method are introduced. This innovative method can provide a new approach for integral aluminum alloy components with large size, ultra-thin thickness, and high strength. An integral tank dome of rocket with 2 m in diameter was formed by using a blank sheet with the same thickness as the final component, breaking through the limit value of thickness-diameter ratio.
Application of an Environmental Monitoring to Assess the Practices and Control the Risk of Occupational Exposure to Cyclophosphamide in Two Sites of a French Comprehensive Cancer Center
Authors: Acramel Alexandre , Fouque Julien , Blondeel-Gomes Sandy , Huguet Samuel , Rezai Keyvan , Madar Olivier , Escalup Laurence 
Published: April 2022

Abstract

Objectives
The risk of chronic exposure to antineoplastic agents in hospitals, mainly by skin contact with contaminated surfaces, is well established. The aim of this study was to assess indirectly the risk of occupational exposure to antineoplastics drugs at two hospitals by using an environmental monitoring, and to suggest ways of improving the exposure to healthcare workers.

Methods
An observational study of care practices on both sites was carried out. A wipe sampling campaign was then designed to study environmental contamination throughout the chemotherapy process: receipt, storage, compounding, transport, administration, and elimination areas. Samples were analyzed by a validated LC-MS/MS method allowing trace quantification of cyclophosphamide. A guidance ‘safe value’ of 0.10 ng/cm2 was considered.

Results
A total of 293 samples were analyzed, of which 58% were found to be positive. In the compounding units, the drug vials were contaminated before [range = (non-quantifiable [NQ]-0.71) ng/cm2] and after cleaning procedure [(NQ-0.62) ng/cm2], particularly when the flip-off lid was removed during cleaning. The contamination found on manual preparations was operator-dependent: [non-detectable (ND)-3.51] ng/cm2 on infusion bag surfaces; (780.61–24 698.98) ng/cm2 on medication ports. In the case of automated preparations, the average contamination was higher on infusion bag surfaces [(2.43–36.86) ng/cm2] and lower on medication ports [(0.43–7.65) ng/cm2] than manual preparations. Contamination of the analytical control area was also highlighted. In the daily care unit, the contamination was located near the infusion area (armchairs, infusion stands, floor, and patient toilets), and varied somewhat between the two sites, especially on the floor with (0.46–27.32) compared to (ND-0.18) ng/cm2. We did not detect contamination on the transport boxes, on the door handles or in the disposal areas.

Conclusions
The variability of contamination observed between the two sites can be explained in part by the difference in routine practices, especially training of the staff, and cleaning procedures. Findings were communicated to healthcare workers, and news interventions were implemented based on wipe sampling results. This study demonstrated a method for routine environmental monitoring and worker education as a strategy to reduce occupational exposure.
Small molecule generation via disentangled representation learning
Authors: Du Yuanqi , Guo Xiaojie , Wang Yinkai , Shehu Amarda , Zhao Liang 
Published: April 2022

AbstractMotivationExpanding our knowledge of small molecules beyond what is known in nature or designed in wet laboratories promises to significantly advance cheminformatics, drug discovery, biotechnology and material science. In silico molecular design remains challenging, primarily due to the complexity of the chemical space and the non-trivial relationship between chemical structures and biological properties. Deep generative models that learn directly from data are intriguing, but they have yet to demonstrate interpretability in the learned representation, so we can learn more about the relationship between the chemical and biological space. In this article, we advance research on disentangled representation learning for small molecule generation. We build on recent work by us and others on deep graph generative frameworks, which capture atomic interactions via a graph-based representation of a small molecule. The methodological novelty is how we leverage the concept of disentanglement in the graph variational autoencoder framework both to generate biologically relevant small molecules and to enhance model interpretability.ResultsExtensive qualitative and quantitative experimental evaluation in comparison with state-of-the-art models demonstrate the superiority of our disentanglement framework. We believe this work is an important step to address key challenges in small molecule generation with deep generative frameworks.Availability and implementationTraining and generated data are made available at https://ieee-dataport.org/documents/dataset-disentangled-representation-learning-interpretable-molecule-generation. All code is made available at https://anonymous.4open.science/r/D-MolVAE-2799/.Supplementary informationSupplementary data are available at Bioinformatics online.
Determining four confounding factors in individual cognitive traits prediction with functional connectivity: an exploratory study
Authors: Feng Pujie , Jiang Rongtao , Wei Lijiang , Calhoun Vince D , Jing Bin , Li Haiyun , Sui Jing 
Published: April 2022

AbstractResting-state functional connectivity (RSFC) has been widely adopted for individualized trait prediction. However, multiple confounding factors may impact the predicted brain-behavior relationships. In this study, we investigated the impact of 4 confounding factors including time series length, functional connectivity (FC) type, brain parcellation choice, and variance of the predicted target. The data from Human Connectome Project including 1,206 healthy subjects were employed, with 3 cognitive traits including fluid intelligence, working memory, and picture vocabulary ability as the prediction targets. We compared the prediction performance under different settings of these 4 factors using partial least square regression. Results demonstrated appropriate time series length (300 time points) and brain parcellation (independent component analysis, ICA100/200) can achieve better prediction performance without too much time consumption. FC calculated by Pearson, Spearman, and Partial correlation achieves higher accuracy and lower time cost than mutual information and coherence. Cognitive traits with larger variance among subjects can be better predicted due to the well elaboration of individual variability. In addition, the beneficial effects of increasing scan duration to prediction partially arise from the improved test–retest reliability of RSFC. Taken together, the study highlights the importance of determining these factors in RSFC-based prediction, which can facilitate standardization of RSFC-based prediction pipelines going forward.
Which criteria should we use to end isolation in hemodialysis patients with COVID-19?
Authors: Alfano Gaetano , Fontana Francesco , Ferrari Annachiara , Morisi Niccolò , Gregorini Mariacristina , Cappelli Gianni , Magistroni Riccardo , Guaraldi Giovanni , Donati Gabriele 
Published: April 2022

ABSTRACTSafe and timely discontinuation of quarantine of in-center hemodialysis (HD) patients with a previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a challenging issue for the nephrological community because current guidelines for ending isolation do not mention dialysis patients. To prevent potentially fatal outbreaks of coronavirus disease 2019 (COVID-19), a cautionary approach has been adopted by most dialysis units. The criteria for ending the isolation in the HD population generally coincide with those recommended for immunocompromised people. Thus, a test-based strategy relying on two consecutive negative reverse transcriptase-polymerase chain reaction (RT-PCR) nasopharyngeal swabs has been adopted to terminate quarantine. This strategy has the disadvantage of prolonging isolation as RT-PCR positivity does not equate to SARS-CoV-2 infectivity. Consequentially, prolonged positivity of SARS-CoV-2 results in excessive workload for the HD staff who must face an increasing number of COVID-19 patients requiring isolation. This condition leads also to serious implications for the patients and their households including work productivity loss, postponement of health-care appointments and an increased risk of COVID-19 reinfection. To counteract this problem, other diagnostic tests should be used to provide the best care to HD patients. Recent results seem to encourage the use of RT-PCR cycle threshold (Ct) values and rapid antigen tests given their better correlation with cell culture for SARS-CoV-2 than RT-PCR testing. Here, we provide an overview of the current scientific evidence on the tests used to verify the infectiousness of the virus in order to stimulate the nephrological community to adopt a streamlined and pragmatic procedure to end isolation in COVID-19 patients on HD.