bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential Display Reverse Transcription Polymerase Chain Reaction (DDRT-PCR) for Grey Oyster Mushroom Samples Grown with Acoustic Sound Treatment
Authors: Song Tham Khai , Zamri Norsahira Ezrin Mohd , Ibrahim Roshita , Mohtar Johan Ariff , Abbas Hartinee , Rahman Ahmad Mukhlis Abdul 
Published: July 2023

Abstract
Grey oyster mushroom is the most often farmed and marketed type of mushroom for household consumption in Malaysia. The mushroom cultivation takes a long time due to its complicated mycelium growth. Several treatments were introduced such as acoustic sound treatment to increase the growth rate and quality of the crop, but there is no in-depth study regarding the genetic expression of the genes affected. This study aims to evaluate the Differential Display Reverse Transcriptase-Polymerase Chain Reaction (DDRT-PCR) for grey oyster mushroom samples grown with acoustic sound treatment. The mushroom was subjected to the treatment and the RNA was extracted from the mushroom samples and converted into cDNA before undergoing DDRT-PCR. Ten Differential Expressed Transcripts (DETs) that were successfully identified based on the differences between the intensity and absence of amplicons were sent for gene sequencing and BLAST through the NCBI database to obtain relevant results regarding the possible gene annotation. Seven out of ten DETs hit potential genes encoding for housekeeping and structural and development functions. The results showed that acoustic sound treatment did affect the expression of certain genes differently as captured by DDRT-PCR analyses and offers new ideas for the development of ecological agriculture.
Viability Study on Fly Ash and Bottom Ash from Combustion Waste
Authors: Ibrahim Norlia Mohamad , Mohamed Syakirah Afizah , Amat Roshazita Che , Rahim Nur Liza , Zailani Warid Wazien Ahmad , Rahim Mustaqqim Abdul , Laslo Lucian , Ismail Khairul Nizar 
Published: July 2023

Abstract
The substitution or addition of new supplementary cementitious materials (SCM) in the production of variety of construction materials has gained much interest. One of the examples of SCM is incineration ash which consist of fly ash (FA) and bottom ash (BA) which are the residues from the ignition of biomass and can brings applicable ecological advantages. However, the properties of this new materials need to be investigated to ensure its full potential can be developed. Therefore, this study is initiated to identify the characteristics of incineration ash from local source in Malaysia. To identify the elemental components of ashes, most widely method was adopted which is using X-Ray Fluorescence (XRF). The quantity of unburned carbon in fly ash is measured by loss on ignition, which has a major influence on the product’s characteristics. In addition, specific gravity and density were also determined and comparison has been made with cement. In this study it was found out that XRF results shows that both FA and BA consist of the same mineral composition with OPC majorly in silica, aluminium, calcium, and iron which makes is suitable to be used in the concrete. For LOI, the value for BA is much higher compared with FA due to the amount of unburnt carbon in its original compositions and the incomplete burning due to insufficient contact time in the furnace. Based on the result obtained for LOI, the average LOI value for FA and BA is 17.33 % and 44.67 %, respectively. As expected, for the specific gravity and density, FA having the lowest specific gravity and density. The density obtained for FA is 755 kg/m3 and for BA is 593 kg/m3. Overall, the use of incineration ash can be fully investigated by exploring other parameter that influence the performance of construction materials.
Building Information Modelling (BIM) Application as Risk Mitigation Strategies in Building Refurbishment Project Life Cycle
Authors: Ishak Nurfadzillah , Azizan Muhammad Azizi , Ibrahim Fazdliel Aswad , Rahim Nur Soleha Abdul , Zawawi Emma Marinie Ahmad , Anuar Nur Hidayah Khairul , Shohime Nor Suraya 
Published: July 2023

Abstract
Towards the implementation of inclusive sustainable cities development as one of the Sustainable Development Goals, the imbalance ratio of existing buildings to new construction became overwhelming challenges. Therefore, refurbishment of existing buildings is considered the possible solution to minimizes the environmental impact and upgrading the performance of an existing building to meet new requirements. However, building refurbishment is well-known as a project that comprehends riskier compared to new building projects which lead to limited applicability in current risk management implementation. Thus, in line with an era of digitization construction of the fourth industrial revolution (IR 4.0), the traditional risk management needs improvement from a manual basis to magnifying efficiency using integration of Building Information Modelling (BIM) application. BIM is defined as an advanced technology that assists construction players to produce, communicate, and analyse building models by providing visual tools and a set of data. Therefore, the objective of this research is to identify the potential building refurbishment risk categories and to determine the most critical project lifecycle phase in implementing the BIM applications in order to mitigate the potential building refurbishment project risk. Also, to discover the relationship strength between these two variables. The quantitative method is applied by using a questionnaire form to the certified BIM experts. This research contributes a solid understanding and useful guideline for future practice reference and improvement within the Building Refurbishment Project.
Electronic materials for solution-processed TFTs
Authors: Acharya Vishwas , Agarwal Kushagra , Mondal Sandip 
Published: July 2023

Abstract
Sol–gel processed thin-film transistors (TFTs) have emerged as a promising technology for next-generationelectronics. TFTs are widely used as switching devices in a various applications, like sensors, displays, memory, and logic circuits. The use of solution process technology offers several advantages, such as low cost, simple process, high throughput, homogeneity, and excellent compositional control. The solution-based fabrication process enables the deposition of thin films on a wide range of substrates, including flexible and curved surfaces. Recently, significant progress has been made in the field of oxide semiconductors and oxide dielectrics for solution-processed TFTs. These developments have led to improved device performance, including higher operating voltage, mobility, and on/off current ratio, among other factors. In this article, we discuss the progress made in the development of oxide semiconductors and oxide dielectrics for sol–gel processed TFTs. This study aims to present a comprehensive understanding of the latest advancements in sol–gel processed TFTs. First, we present comprehensive summary of the key parameters of solution-processed metal oxides that are critical for building high-performance thin film transistors (TFTs), including sol–gel derived binary and ternary metal oxide dielectrics and semiconductors. Following that a detailed performance analysis of solution-processed TFTs in terms of their operating voltage, mobility, and on/off current ratio (Ion/Ioff), among other factors has been summarized. Afterward, the applications of solution-processed TFTs fabricated using various techniques (e.g., spin coating, screen printing, and inkjet printing) are also discussed. We explore the function of sol–gel processed high-k dielectrics and the challenges associated with their growth for fabrication of high-performance TFTs. Finally, the future perspectives on how to improve the performance of solution-processed TFTs. Overall, this study provides valuable insights into the potential of solution-processed materials for use in next-generation portable electronics.
Public preferences for phasing-out fossil fuels in the german building and transport sectors
Authors: Tröndle Tim , Annaheim Jasmin , Hoppe Janna , Hanger-Kopp Susanne , Patt Anthony 
Published: July 2023

Abstract
In most of Europe, the decarbonisation of the building and transport sectors lags behind emission targets. Achieving full decarbonisation requires not only the diffusion of net-zero emission technologies but also the phase-out of technologies that emit greenhouse gases (GHG). However, implementing policy changes in these sectors can have an immediate and significant impact on people’s day-to-day life, leading to a higher risk of political backlash, as exemplified by the yellow vest movement in France. In this study, we investigate public preferences for phase-out policy packages in both sectors in Germany by conducting two conjoint experiments with 1,777 respondents in March 2022. Respondents collectively evaluated a total of 17,770 policy packages per sector, specifically targeting the phase-out of fossil fuel-based heating systems and internal combustion engine vehicles (ICEVs). We find that respondents favour earlier phase-out dates for both technologies, but the type of preferred instruments varies: while regulatory instruments like bans are preferred for heating systems, economic instruments like taxes are preferred for ICEVs. These preferences are even more pronounced in people most concerned about climate change. In addition, we find that people with higher knowledge about sector emissions tend to demonstrate higher acceptance of policy interventions and that supportive measures significantly enhance the attractiveness of policy packages. Our findings can inform the design of phase-out policy packages, potentially increasing their acceptability and political feasibility.
Pollen viabilities and gene expression profiles across Musa genomes
Authors: Mingmanit Yonlada , Boonsrangsom Thanita , Sujipuli Kawee , Ratanasut Kumrop , Inthima Phithak 
Published: July 2023

Abstract
Banana (Musa spp.) is a major global economic fruit crop. However, cross-pollination from other Musa cultivars grown in nearby plantations results in seeded fruit that exceeds market demand. This study investigated pollen viability and germination and examined the expression profiles of pollen development-related genes across seven Musa genomes (AA, BB, AAA, BBB, AAB, ABB and ABBB). Twenty-three Musa cultivars were assessed for pollen viability using lacto-aceto-orcein and triphenyltetrazolium chloride staining methods. Results revealed that pollen viability obtained from both methods was significantly different among all the studied cultivars. Cultivars carrying BB (diploid) genomes had higher viability percentages than AA (diploid), AAA, BBB, AAB and ABB (triploid) and ABBB (tetraploid) genomes. Germination of the studied cultivars was also investigated on pollen culture medium, with results showing significant differences between the pollen of each cultivar. The best germinating cultivar was TKM (11.0 %), carrying BB genome. Expression profiles of pollen development-related genes by RT–qPCR indicated that both TPD1A and MYB80 genes were highly expressed in triploid Musa genomes but the PTC1 gene showed down-regulated expression, resulting in non-viable pollen. Pollen viability, pollen germination and pollen development-related genes differed across Musa cultivars. This knowledge will be useful for the selection of male parents for Musa cross-breeding programs. Pollen viability should also be considered when planning Musa production to avoid seeded fruit.
Smaller Hippocampal Volume Is Associated With Reduced Posttraumatic Stress Symptoms in Children With Cancer and Survivors Following a Brief Novel Martial Arts-Based Intervention
Authors: Evanski Julia M , Iadipaolo Allesandra , Ely Samantha L , Zundel Clara G , Gowatch Leah C , Bhogal Amanpreet , Owens Zazai , Cohen Cindy , Goldberg Elimelech , Bluth Martin H , Taub Jeffrey , Harper Felicity W K , Rabinak Christine A , Marusak Hilary A 
Published: July 2023

Abstract

Purpose
Children with cancer and survivors frequently report posttraumatic stress symptoms (PTSS), which are associated with volumetric changes in stress-sensitive brain regions, including the hippocampus.

Methods
We examined the impact of a novel, 4-week martial-arts-based meditative intervention on cancer-related PTSS in 18 pediatric patients and survivors and whether baseline hippocampal volumes correlate with PTSS severity and/or PTSS changes over time.

Results
Overall, PTSS did not significantly change from baseline to post-intervention. Smaller hippocampal volume was correlated with more severe re-experiencing PTSS at baseline, and greater reductions in PTSS post-intervention.

Conclusions
Together, hippocampal volume may be a biomarker of PTSS severity and intervention response. Identifying hippocampal volume as a potential biomarker for PTSS severity and intervention response may allow for more informed psychosocial treatments.
scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning
Authors: Jia Shangru , Lysenko Artem , Boroevich Keith A , Sharma Alok , Tsunoda Tatsuhiko 
Published: July 2023

Abstract
Annotation of cell-types is a critical step in the analysis of single-cell RNA sequencing (scRNA-seq) data that allows the study of heterogeneity across multiple cell populations. Currently, this is most commonly done using unsupervised clustering algorithms, which project single-cell expression data into a lower dimensional space and then cluster cells based on their distances from each other. However, as these methods do not use reference datasets, they can only achieve a rough classification of cell-types, and it is difficult to improve the recognition accuracy further. To effectively solve this issue, we propose a novel supervised annotation method, scDeepInsight. The scDeepInsight method is capable of performing manifold assignments. It is competent in executing data integration through batch normalization, performing supervised training on the reference dataset, doing outlier detection and annotating cell-types on query datasets. Moreover, it can help identify active genes or marker genes related to cell-types. The training of the scDeepInsight model is performed in a unique way. Tabular scRNA-seq data are first converted to corresponding images through the DeepInsight methodology. DeepInsight can create a trainable image transformer to convert non-image RNA data to images by comprehensively comparing interrelationships among multiple genes. Subsequently, the converted images are fed into convolutional neural networks such as EfficientNet-b3. This enables automatic feature extraction to identify the cell-types of scRNA-seq samples. We benchmarked scDeepInsight with six other mainstream cell annotation methods. The average accuracy rate of scDeepInsight reached 87.5%, which is more than 7% higher compared with the state-of-the-art methods.
Modelling and optimization of combined heat and power system in microgrid based on renewable energy
Authors: Smaisim Ghassan F , Abed Azher M , Hadrawi Salema K , Majdi Hasan Sh. , Shamel Ali 
Published: July 2023

Abstract
Due to the short distance between the sources of production and consumption, microgrids (MGs) have received considerable attention because these systems involve fewer losses and waste less energy. And another advantage of MGs is that renewable energy sources can be widely used because these resources are not fully available and can provide a part of the required power. The purpose of this research is to model the MG considering the production sources of microturbines, gas turbines and internal combustion engines. Renewable energies such as wind turbines (WTs) and photovoltaic (PV) cells have been used to provide part of the required power and, because of the lack of access to renewable energy sources at all times, energy reserves such as batteries and fuel cells (FCs) have been considered. The power of the microturbine, gas turbine, internal combustion engine, FC and battery in this system is 162, 150, 90, 100 and 225 kW, respectively. After modelling the studied system, optimization was done using the imperialist competitive algorithm to minimize production costs and provide maximum thermal and electrical loads. The maximum production power for PVs is equal to 0.6860 MWh and at this time this value for WTs is equal to 0.3812 MWh, in which case the excess electricity produced will be sold to the grid.
Comparative study of energetic potential from anaerobic digestion and direct combustion of date palm wastes
Authors: Lahboubi Nabila , Kerrou Omar , Sarh Brahim , Boushaki Toufik , Belandria Veronica , El Khattabi Yasser , El Bari Hassan 
Published: July 2023

Abstract
This work aims to evaluate the technical and environmental feasibility of converting date palm waste from a Moroccan oasis into energy. In this study, two different scenarios were analysed. The first proposed scenario is the valorization of the date palm substrates using direct combustion (thermochemical conversion) to produce energy. The second proposed scenario is the valorization of the substrates using combined anaerobic digestion of the substrate and direct combustion of the digestate. In this study, two different date palm wastes are: empty fruit bunch (EFB) and palm leaflet (PL). The experimental lower heating values of the digestates studied are 12.93 and 12.71 MJ/kg, respectively. The results show that using Scenario 1, the estimated output energies for the EFB and PL waste were 1.13 and 1.17 MWh, respectively. Using Scenario 2, the EFB and PL output energies were 1.27 and 1.39 MWh, respectively. The study revealed that the combined process is possible as an alternative way to produce energy. Furthermore, combining anaerobic digestion and direct combustion of lignocellulosic waste can contribute to reducing greenhouse gas emissions.
Super Structure Fault-Tolerance Assessment of the Generalized Hypercube
Authors: Shu Chang , Wang Yan , Fan Jianxi , Wang Guijuan 
Published: July 2023

Abstract
Fault-tolerant performance of a network is the prerequisite and guarantee for the normal operation of a network, which is often characterized by connectivity. Let $H$ denote a connected subgraph of $G$ and $H^{*}$ denote the union of the set of all connected subgraphs of $H$ and the set of the trivial graph. Super $H$-connectivity (resp. super $H^{*}$-connectivity) satisfies the conditions of both super connectivity and $H$-structure connectivity (resp. $H$-substructure connectivity). These two kinds of new connectivity provide a new metric to measure the fault-tolerance of the network, that is, the super structure fault-tolerance. The generalized hypercube $G(m_{r}, m_{r-1},..., m_{1})$ is a universal topology of interconnection networks that contains other commonly used topologies and it has been applied in many data center networks because of its excellent qualities. In this paper, we research the super structure fault-tolerance of $G(m_{r}, m_{r-1},..., m_{1})$ by studying super $H$-connectivity $\kappa ^{\prime}(G|H)$ and super $H^{*}$-connectivity $\kappa ^{\prime}(G|H^{*})$ for $H\in \{K_{1,M},\ C_{3},\ C_{4},\ K_{4}\}$.
KEFSAR: A Solar-Aware Routing Strategy For Rechargeable IoT Based On High-Accuracy Prediction
Authors: Ma Dongchao , Wang Dongmei , Huang Xiaofu , Hu Yuekun , Ma Li 
Published: July 2023

Abstract
The high energy density of solar energy gives wireless sensor networks advantages in outdoor monitoring applications. However, long-term stable monitoring is challenging due to frequent weather changes, shading by buildings and trees, etc. The existing research usually uses two technologies to solve the above problems: (1) the energy prediction algorithm, and (2) the energy-aware routing strategy. However, in an actual deployment, frequent weather changes can significantly reduce the accuracy of the existing prediction algorithms. When using the algorithms as the support for energy-aware routing, the network lifetime is less than ideal. The existing routing strategies are in need of further improvement. Because of its lack of environmental adaptability, nodes consume energy quickly and have a high mortality rate. Therefore, aiming at the long-term stability of solar wireless sensor networks, this paper proposes a prediction algorithm based on classification and recurrent neural networks, and integrates the shadow judgement method from our previous research to correct the predicted values. Furthermore, we propose a routing optimization model that can flexibly adjust the target according to the solar intensity. The experimental results show that the prediction and routing scheduling algorithm can significantly improve the energy prediction accuracy (30–50%) and prolong the network lifetime (10–42%) in outdoor small sensor scenarios.
FAM210A regulates mitochondrial translation and maintains cardiac mitochondrial homeostasis
Authors: Wu Jiangbin , Subbaiah Kadiam C Venkata , Hedaya Omar , Chen Si , Munger Joshua , Tang Wai Hong Wilson , Yan Chen , Yao Peng 
Published: July 2023

AbstractAimsMitochondria play a vital role in cellular metabolism and energetics and support normal cardiac function. Disrupted mitochondrial function and homeostasis cause a variety of heart diseases. Fam210a (family with sequence similarity 210 member A), a novel mitochondrial gene, is identified as a hub gene in mouse cardiac remodelling by multi-omics studies. Human FAM210A mutations are associated with sarcopenia. However, the physiological role and molecular function of FAM210A remain elusive in the heart. We aim to determine the biological role and molecular mechanism of FAM210A in regulating mitochondrial function and cardiac health in vivo.Methods and resultsTamoxifen-induced αMHCMCM-driven conditional knockout of Fam210a in the mouse cardiomyocytes induced progressive dilated cardiomyopathy and heart failure, ultimately causing mortality. Fam210a deficient cardiomyocytes exhibit severe mitochondrial morphological disruption and functional decline accompanied by myofilament disarray at the late stage of cardiomyopathy. Furthermore, we observed increased mitochondrial reactive oxygen species production, disturbed mitochondrial membrane potential, and reduced respiratory activity in cardiomyocytes at the early stage before contractile dysfunction and heart failure. Multi-omics analyses indicate that FAM210A deficiency persistently activates integrated stress response, resulting in transcriptomic, translatomic, proteomic, and metabolomic reprogramming, ultimately leading to pathogenic progression of heart failure. Mechanistically, mitochondrial polysome profiling analysis shows that FAM210A loss of function compromises mitochondrial mRNA translation and leads to reduced mitochondrial-encoded proteins, followed by disrupted proteostasis. We observed decreased FAM210A protein expression in human ischaemic heart failure and mouse myocardial infarction tissue samples. To further corroborate FAM210A function in the heart, AAV9-mediated overexpression of FAM210A promotes mitochondrial-encoded protein expression, improves cardiac mitochondrial function, and partially rescues murine hearts from cardiac remodelling and damage in ischaemia-induced heart failure.ConclusionThese results suggest that FAM210A is a mitochondrial translation regulator to maintain mitochondrial homeostasis and normal cardiomyocyte contractile function. This study also offers a new therapeutic target for treating ischaemic heart disease.