bluuebunny/crossref_metadata_2025 huggingface dataset:
Rapid charging of graphite negative electrode by acetonitrile localized high-concentration electrolyte
Authors: Zhang Fan , cao yang , Lv Lulu , Feng Yuanyuan , Li Jiachen , Yu Haotian , Wang Tao , Xu Mengyao , Zhao Bin , Han Xiaogang
Published: August 2024

Lithium ion batteries using traditional carbonate electrolytes do not show excellent fast charging performance, while acetonitrile (AN) exhibits excellent reduction stability and fast charging ability in high concentration electrolytes (HCEs) system. In this paper, a localized high-concentration eletrolyte (LHCE) was formed by using AN as solvent, lithium bis(fluorosulfonyl) imide (LiFSI) as lithium salt and fluorine-containing solvent (1, 1, 2, 2-tetrafluoroethyl-2, 2, 3, 3-tetrafluoropropyl ether (TTE)) as diluent, and applied to graphite anode to explore its fast charging ability. The solvation structure of electrolyte was analyzed by Raman spectroscopy, and the appearance of graphite anode was observed by scanning electron microscope(SEM). At the same time, linear sweep voltammetry (LSV) and cyclic voltammetry (CV) were used to investigate the electrochemical characteristics of the electrolyte. Based on the excellent electrochemical stability and multiplication of the localized high-concentration eletrolyte (LHCE) , the graphite/Li half battery can reach a high capacity of 388 mAh g-1 at 0.2 C and still reach 205 mAh g-1 at a high magnification of 5 C , what’s more the capacity retention rate is about 90% after 100 cycles at 5C. This study provides a high reference value for the design of localized high-concentration eletrolyte（LHCE） system with high concentration effect of acetonitrile group on graphite electrode.
Functional role of fatty acid synthase for signal transduction in Core binding factor-AML with activating c-Kit mutation
Authors: Zhuang Ruimeng , Siebels Bente , Hoffer Konstantin , Worthmann Anna , Horn Stefan , Bubnoff Nikolas , Khandanpour Cyrus , Gebauer Niklas , Gorantla Sivahari Prasad , Voss Hanna , Schlüter Hartmut , Kriegs Malte , Fiedler Walter , Bokemeyer Carsten , Jücker Manfred , Kebenko Maxim
Published: August 2024

Background
AML is a rare hematological malignancy still associated with poor prognosis. 5% of de novo AML and 30% of core binding factor (CBF) AML (translocation t(8;21)(q22;q22) or invasion (16)(p13;q22)), respectively, harbor activating c-Kit (CD117) mutations leading to an adverse clinical outcome. Posttranslational protein modifications, especially by myristolic and palmitic acid, are known to be important for diverse cell functions such as membrane organization, transduction signaling or regulation of apoptosis. However, most data come from solid tumor studies while its role in AML is still poorly understood. Fatty acid synthase (FASN) is one of the key palmitoyl-acyltransferases which controls subcellular localization, trafficking and degradation of various target proteins. H-Ras, N-Ras or FLT3-ITDmut receptors are known to be important target proteins for FASN in AML.
Methods
In this study, we investigated the role of FASN in two c-Kit-N822K mutated AML cell lines. Using FASN knockdown via shRNA and the FASN inhibitor TVB-3166. Functional implications including cell viability and proliferation were tracked in a combined approach integrating western blotting, mass spectrometry PamGene.
Results
In FASN-knockdown cells, we observed an increase in phosphorylation of c-Kit (p-c-Kit), Lyn kinase (pLyn) as well as of S6 kinase (pS6). Moreover, a downregulation of cathepsin Z (CTSZ), which belongs to endo-lysosomal proteases and is hence essential for degradation of cellular proteins within lysosomes was found.
Conclusion
Recent studies have suggested potential roles for palmitoylation in lysosomal function indirectly through its effects on proteins involved in lysosomal trafficking, membrane fusion, and signaling pathways. Therefore, our observation of the reduced expression of CTSZ due to the inhibition of FASN offers an explanation for the increased c-Kit, Lyn, and S6 kinase activity in CBF-AML with activating c-Kit mutation.
Dynamic functional connectivity and gene expression correlates in temporal lobe epilepsy: insights from hidden markov models
Authors: Qin Lu , Zhou Qin , Sun Yuting , Pang Xiaomin , Chen Zirong , zheng jinou
Published: August 2024

Backgroud
Temporal lobe epilepsy (TLE) is associated with abnormal dynamic functional connectivity patterns, but the dynamic changes in brain activity at each time point remain unclear, as does the potential molecular mechanisms associated with the dynamic temporal characteristics of TLE.
Methods
Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 84 TLE patients and 35 healthy controls (HCs). The data was then used to conduct HMM analysis on rs-fMRI data from TLE patients and an HC group in order to explore the intricate temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI). Additionally, we aim to examine the gene expression profiles associated with the dynamic modular characteristics in TLE patients using the Allen Human Brain Atlas (AHBA) database.
Results
Five HMM states were identified in this study. Compared with HCs, TLE and TLE-CI patients exhibited distinct changes in dynamics, including fractional occupancy, lifetimes, mean dwell time and switch rate. Furthermore, transition probability across HMM states were significantly different between TLE and TLE-CI patients (p < 0.05). The temporal reconfiguration of states in TLE and TLE-CI patients was associated with several brain networks (including the high-order default mode network (DMN), subcortical network (SCN), and cerebellum network (CN). Furthermore, a total of 1580 genes were revealed to be significantly associated with dynamic brain states of TLE, mainly enriched in neuronal signaling and synaptic function.
Conclusions
This study provides new insights into characterizing dynamic neural activity in TLE. The brain network dynamics defined by HMM analysis may deepen our understanding of the neurobiological underpinnings of TLE and TLE-CI, indicating a linkage between neural configuration and gene expression in TLE.
Subversion of kindlin-3 function in PTEN null T-cell acute lymphoblastic leukemia
Authors: Tan Suet-Mien , Lee Bernard , Teo Seok-Yee , Li Yinghui , Bhattacharjya Surajit
Published: August 2024

Kindlin-3 is an adapter protein that promotes cell adhesion and migration. Kindlin-3 binds phosphatidylinositol (3,4,5)-triphosphate (PIP3), which is a lipid product of PI3K that drives AKT signaling. The tumor suppressor PTEN phosphatase metabolizes and limits the level of PIP3. T-cell acute lymphoblastic leukemia (T-ALL) is a type of blood cancer that is highly aggressive. In pediatric T-ALL, PTEN-loss-of-function is a frequent occurrence that leads to dysregulated PIP3 turnover and aberrant AKT activation and signaling. Here we show for the first time that the function of kindlin-3 is subverted to promote Ras-B-Raf-MEK-ERK signaling in PTEN null T-ALL cells that does not require the binding of kindlin-3 to integrins. Mechanistically, we uncovered a novel preformed complex comprising kindlin-3, the scaffold protein RACK1 and MEK that is recruited to the PIP3-enriched plasma membrane via the pleckstrin homology (PH) domain of kindlin-3. This contributes to the assembly of B-Raf-MEK-ERK signaling components downstream of activated Ras. Consequently, the loss of kindlin-3 reduces ERK1/2 activation that dampens DNA damage response, leading to mitotic delay affecting cell proliferation. Taken together, our data show a central role of kindlin-3 in PTEN-null T-ALL progression.
Choroid Plexus Free-Water Correlates with Glymphatic function in Alzheimer Disease: The RJNB-D Study
Authors: Li Binyin , Xu Xiaomeng , Yang Xinyuan , Zhang Junfang , Wang Yan , Selim Magdy , Zheng Yingting , Shen Ruinan , Huang Qi , Wang Wenjing , Xu Wei , Guan Yihui , Liu Jun , Deng Yulei , Xie Fang Fang
Published: August 2024

The free water imaging of choroid plexus (CP) may improve the evaluation of Alzheimer's disease (AD). Our study investigated the role of free water fraction (FWf) of CP in AD by including 216 participants (133 Aβ + participants and 83 Aβ- controls) continuously enrolled in the NeuroBank-Dementia cohort at Ruijin Hospital (RJNB-D). At baseline, Aβ + participants showed higher CP free water fraction (FWf), increased white matter hyperintensity (WMH) volume, and decreased diffusion tensor image analysis of the perivascular space (DTI-ALPS). In Aβ + participants, DTI-ALPS mediated the association between CP FWf and periventricular WMH. CP FWf was associated with cortical Tau accumulation, synaptic loss, hippocampal and cortical atrophy, and cognitive performance. During follow-up, CP FWf increased faster in Aβ + participants than in controls. The findings suggest that elevated CP FWf may indicate impaired glymphatic function and AD neurodegeneration, potentially serving as a valuable biomarker for AD evaluation and progression.
Evaluating urine volume and host depletion methods to enable genome-resolved metagenomics of the urobiome
Authors: Lewis Zachary J. , Scott Angela , Madden Christopher , Vik Dean , Zayed Ahmed A. , Smith Garrett J. , Justice Sheryl S. , Rudinsky Adam , Hokamp Jessica , Hale Vanessa L.
Published: August 2024

Background: The gut microbiome has emerged as a clear player in health and disease, in part by mediating host response to environment and lifestyle. The urobiome (microbiota of the urinary tract) likely functions similarly. However, efforts to characterize the urobiome and assess its functional potential have been limited due to technical challenges including low microbial biomass and high host cell shedding in urine. Here, to begin addressing these challenges, we evaluate urine sample volume (100 ml – 5 mL), and host DNA depletion methods and their effects on urobiome profiles in healthy dogs, which are a robust large animal model for the human urobiome. We collected urine from seven dogs and fractionated samples into aliquots. One set of samples was spiked with host (canine) cells to model a biologically relevant host cell burden in urine. Samples then underwent DNA extraction followed by 16S rRNA gene and shotgun metagenomic sequencing. We then assembled metagenome assembled genomes (MAGs) and compared microbial composition and diversity across groups. We tested six methods of DNA extraction: QIAamp BiOstic Bacteremia (no host depletion), QIAamp DNA Microbiome, Molzym MolYsis, NEBNext Microbiome DNA Enrichment, Zymo HostZERO, and Propidium Monoazide.
Results: In relation to urine sample volume, ³ 3.0 mL resulted in the most consistent urobiome profiling. In relation to host depletion, individual (dog) but not extraction method drove overall differences in microbial composition. DNA Microbiome yielded the greatest microbial diversity in 16S rRNA sequencing data and shotgun metagenomic sequencing data, and maximized MAG recovery while effectively depleting host DNA in host-spiked urine samples. As proof-of-principle, we then mined MAGs for core metabolic functions and environmental chemical metabolism. We identified long chain alkane utilization in two of the urine MAGs. Long chain alkanes are common pollutants that result from industrial combustion processes and end up in urine.
Conclusions: This is the first study, to our knowledge, to demonstrate environmental chemical degradation potential in urine microbes through genome-resolved metagenomics. These findings provide guidelines for studying the urobiome in relation to sample volume and host depletion, and lay the foundation for future evaluation of urobiome function in relation to health and disease.
A New Dynamic Model of Supply Boundary at Low Pressure in Tight Gas Reservoir
Authors: Li Jinbu , Liu Lili , Zhu Yuan , Zhao Lian , Chai Xiaolong , Tian Leng
Published: August 2024

It is a clean, low-carbon energy source for tight gas that has gained popularity in the energy sector for its ability to significantly cut greenhouse gas emissions. On the other hand, low formation pressure, low gas well production, and high water saturation are features of tight gas reservoirs that have been developed and produced over an extended period of time. In order to improve the assessment of the supply boundary and production capacity features of tight gas wells at low pressure, a new coupling model of gas-water two-phase was established in this paper and the threshold pressure gradient, stress sensitivity and slip effect are taken into account the built model. Subsequently, the steady-state substitution method and the material balance method were used to develop the supply boundary calculation model. Finally, an analysis is done on how the supply boundary is affected by the threshold pressure gradient production, stress sensitivity and production pressure difference. The results demonstrate that, in contrast to the slower propagation observed in the matrix zone, the supply boundary propagates relatively quickly within the fracture modification zone. The threshold pressure gradient and stress-sensitive increase the resistance of gas seepage and delay the propagation of the supply boundary, which reduces the production of gas well. The propagation of the supply boundary accelerates with increasing production pressure difference, but the pressure difference's effect decreases. The production of gas is significantly impacted by the threshold pressure gradient, stress sensitivity and production pressure difference. Efficient production of tight gas reservoirs necessitates minimizing water production and preserving formation pressure.
Growth and Polyphenol Content of Ashwagandha (Withania somnifera L.Dunal) under Combined Moisture Stress and Salicylic Acid Treatment
Authors: Jayathilaka M. S. , Subasinghe Siripala , Rajawatta KMW , Karunarathna K. H.T.
Published: August 2024

Ashwagandha is a medicinal herb that has very high demand in the global market. Root is the main part harvested from this plant because of its rejuvenating properties. This study investigates the effects of moisture stress and salicylic acid on the growth yield and polyphenol content of Ashwagandha. A polyhouse experiment was conducted where Ashwagandha plants were grown under four levels of soil moisture that included 50%, 60%, 80%, and 100% of field capacity (FC) and four Salicylic acid (SA) levels as 10 mM,1 mM,0.1 mM and control was applied as a foliar spray as treatments to induce the secondary metabolite production. Plant height, number of leaves, number of fruits, number of fallen leaves, SPAD value and leaf area, root dry of the root, free proline content and total polyphenol content were measured. The highest root dry weight (7.62g) and total polyphenol content (3.78 GAE mg/g d.w.b) was reported with the interaction effect of 50% of FC and 10− 3M SA application. Under the combined application of 50% of FC and 1 mM SA the dry weight and total polyphenol content was increased by 2.7 folds and 12.49 folds respectively compared to control (100% FC and without SA). These findings suggest that a moisture stress level of 50% field capacity combined with a 1 mM SA foliar spray can significantly enhance the root yield and polyphenol content of Ashwagandha.
Integrated metabolomic and transcriptomic analyses of flavonoid accumulation in different cultivars of Platostoma palustre
Authors: You Jiankai , Zeng Lishan , Wang Zhongdong , Xia Yimeng , Lin Ying , Zhan Ruoting , Zhang Guifang
Published: August 2024

Background Platostoma palustre
is a kind of plant resource with medicinal and food value, which has been differentiated into many different varieties after a long period of breeding. The cultivars of Taiwan(TW) and Pingyuan(PY) are widely grown in Guangdong, but a clear basis for species differentiation has not yet been established, resulting in the mixing of different species which limits their production and application.
Results
Regarding leaf surface morphology, the TW exhibited greater leaf area, non-glandular hairs, and the number of stomata than the PY. Regarding chemical activities, the TW exhibited higher total flavonoid content and antioxidant activity than the PY. In metabolomics, a total of 85 DAMs were detected, among which four flavonoid DAMs were identified, all of which were up-regulated in TW expression. Transcriptome analysis identified 2503 DEGs, which were classified according to their functional roles. The results demonstrated that the DEGs were primarily involved in amino acid metabolism, carbohydrate metabolism, sorting and degradation. Combined analysis of metabolome and transcriptome indicated that the phenylpropanoid pathway plays a significant role in flavonoid synthesis. Furthermore, real-time fluorescence qrt-PCR validation demonstrated that the expression trend of 10 DEGs was consistent with the transcriptomics data.
Conclusion
The phenylpropanoid pathway affects the synthesis of secondary metabolites, resulting in functional differences. In this study, metabolomic and transcriptomic analyses were performed to elucidate the regulatory mechanisms of flavonoid synthesis in P. palustre and to provide a theoretical basis for the identification, differentiation and breeding cultivation of different cultivars of P. palustre.
Experimental analysis on hardness and compression strength of Al6061 reinforced by silicon carbide hybrid composite using bagasse fly-ash and aloe vera ash
Authors: Demisie Leul Fenta , Rengiah Robinson Gnanadurai , Takele Tayachew Nega , Ayalew Yewondwosen Gizat , Berihun Ermias Aswossie
Published: August 2024

The demand for low-density composite materials utilized for structural applications and automobile body parts, resulting in high stiffness-to-weight and strength-to-weight ratios initiated the production of this composite material. The objective of this work is to produce and assess Al6061 Silicon carbide and inexpensive reinforcements of Aloe vera and Bagasse ash. The hardness and compression strength characteristics of the composite, by altering the wt. % of reinforcements were assessed and contrasted. The stir-casting method was used to create this hybrid composite at 700°C. The parameters used to produce this hybrid composite were the composition of reinforcements, powder mixing ratio, and stirring the slurry as done at 600 rpm for 10 minutes. Eight sets of composites were prepared by varying the percentage of Silicon carbide, Bagasse ash, and Aloe vera ash. The prepared composite, compressive strength tests using (ASTM standard D 695) and micro hardness tests (ASTM E18-15 standard) were carried out. The result shows that the compression strength rose with the growth of the bagasse ash and aloe vera ash contents. The highest compression strength of Al6061-10 wt. % SiC, 10 wt. % bagasse ash, and 11 wt. % Aloe vera ash hybrid composite is 376.3 MPa. Al6061-10wt.%SiC-9wt.% bagasse ash – 9wt.% Aloe vera ash and Al6061-10wt.%SiC-10wt.% bagasse ash – 11wt.% Aloe vera ash provided the highest hardness values, measuring 91.16 HV and 91.6 HV, respectively. The hybrid composite's hardness value rose from a single reinforced Al6061/SiC composite by 16.27%. It is determined that the hardness and compression strength of Al6061 composite materials are significantly increased by the addition of bagasse and aloe vera ashes.
Short Term Efficacy of Biological Treatment for Moderate-to-Severe Plaque Psoriasis: A Systematic Review and Network Meta-Analysis
Authors: Ismail Omar , Jaber Kamel , Jaber Yazan , Froukh Ubada , Younis Ahmad , Albdour Karam , Momani Yazan , Almaani Noor
Published: August 2024

Background
Psoriasis is a chronic inflammatory disease that is debilitating, particularly in its more severe forms. Multiple systemic therapies are used in moderate-to-severe psoriasis, but the development of biological interventions has revolutionized its management and improved its outcomes.
Aim
To compare the effectiveness and safety of the different biological interventions approved for use in moderate-to-severe plaque psoriasis.
Methods
Multiple databases were searched for relevant articles and a prospectively planned network meta-analysis was conducted on randomized controlled trials that assessed biological treatments in moderate-to-severe psoriasis.
Results
The search yielded 84 trials that encompassed 39798 patients. Infliximab 5mg/kg had the highest probability of achieving 75% reduction on PASI scale in comparison to placebo (RR = 18.76, 95%CI = [12.31; 28.57], high certainty), while Ixekizumab 80mg and Brodalumab 210mg had the highest probability in achieving PASI90 and PASI100 (37.81, [28.57; 50.03] and 81.04, [26.16; 251.01], respectively, with moderate certainty) On the other hand, Risankizumab 150mg and Ustekinumab 90mg were the only regimens with significantly less withdrawal rates due to adverse events (0.41, [0.18 To 0.96], and 0.57, [0.35 To 0.91], respectively with High certainty) compared to placebo.
Conclusion
Anti-IL17 and Infliximab were among the most effective in ameliorating the symptoms of psoriasis, however, anti-IL17 were better in achieving full or almost full improvement on the PASI scale. Real life decision-making is not so clear-cut and should remain patient centered, taking into consideration factors such as safety, comorbidities, biologic naivety, dosing preferences and insurance considerations.
Intrinsic strain of defect sites steering chlorination reaction for water purification
Authors: Sijin Zuo , yinqiao Zhang , Mohan Chen , Xuanyu He , Erzhuo Zhao , Hao Liang , Jingge Shang , Kai Liu , Jianqiu Chen , Zhou Minghua
Published: August 2024

Carbon nanotube (CT)–based chemical technologies particular in heterogenous advanced oxidation processes (AOPs) used for water purification, have been exploited over the several decades. Many strategies of CT modification have been exploited to improve the catalytic performance in the remediation processes. However, the strain fields of intrinsic defect sites on CT steering AOPs (such as chlorination) have never been reported. Here we for the first time explored the strained defect sites steering chlorination process onto high–efficient and green abatement of 2,4–dichlorophenol. Characterizations and theory analysis unveil that the strained defect sites with the elongated sp2 hybridized C–C bond displaying the larger spin–lattice relaxation boost electronic reactivity with chlorine molecules via the initial Yeager–type adsorption. As a result, the amounts and catalogs of reactive species in our chlorination are tunable on demand, such as the ratio of high–selectivity ClO• ranging from 38.8% in pure defects–based system to 87.5% in strain dominated process, which result in generating the harmless intermediates and even deep mineralization of organic. Thus, this work highlights the vital role of the strain fields on steering chlorination reaction for greener water purification even beyond.
Pan-Cancer TCGA Analysis Reveals the Potential Involvement of Lamin B2 in Dysregulating Chromosome Segregation in Human Cancer
Authors: Kundu Subhadip , Jit Bimal Prasad , Sharma Ashok
Published: August 2024

Lamins are fibrous proteins present just beneath the inner nuclear membrane and play a crucial role in shaping the genomic architecture. Several studies have reported the association of lamins with disease conditions such as cancer. Despite significant progress, the prognostic significance and underlying molecular targets of B-type lamins, especially lamin B2 in pan-cancer, have not been well studied. In this study, we have explored through bioinformatic analysis the potential functions of lamin B2 in driving cancer and its prognostic significance across pan-cancer TCGA datasets. Our results indicate the overexpression of lamin B2 in multiple human cancers, which is also correlated with poor overall and disease-free survival. Besides this, higher lamin B2 is associated with CD4+ Th1 and Th2 cell infiltration. We have identified 9 lamin B2 interacting proteins that are co-expressed with lamin B2 in cancerous conditions and, together with lamin B1, regulate cytokinesis and cell division pathways. Furthermore, we have identified specific molecular targets and independent functions of lamin B2 in dysregulating chromosome segregation and mRNA binding in multiple cancers. Our study, for the first time, has demonstrated the potential functions of lamin B2 and its prognostic significance across different cancers.
Ruptured AAA: Bridging the Gap Between International Guidelines and Local Clinical Realities
Authors: Hassan Summer , Frost Taylor , Bourchier Russell
Published: August 2024

Background: Treatment of asymptomatic Abdominal Aortic Aneurysms (AAA) presents a clinical challenge, balancing rupture risk, patient comorbidities, and intervention-related complications. International guidelines recommend intervention for specific AAA size thresholds, but these are based on historical trials with limited female representation. We aimed to analyse disease characteristics, AAA size at rupture, and intervention outcomes in patients with ruptured AAA from 2009 to 2023 to bridge the gap between guidelines and local realities.
Methods: This single-centre retrospective cohort study analysed electronic health records of patients diagnosed with ruptured AAA, assessing demographics, risk factors, comorbidities, clinical presentation, radiological characteristics, and outcomes.
Results: Of 164 patients (41 females, 123 males, median age 73.5), 93.3% presented with abdominal or back pain. The median AAA size at rupture was 8.0 cm in males and 7.6 cm in females. No significant correlations were found between demographic characteristics, risk factors, AAA size, repair modality, and outcomes. Trends show a decline in AAA prevalence and rupture rates, aligning with global health initiatives. Post-intervention survival rates at 30 days were 70.7%, and at 2 years, 65.9%.
Conclusion: Evolving AAA trends and improved post-intervention survival rates suggest a critical reassessment of existing intervention recommendations. Adjusting intervention thresholds to larger sizes may be warranted to optimize the risk-benefit ratio.
Introducing new Link Prediction Measures and an Evaluation Metric
Authors: Javan Abolfazl , Moeini Ali , Ghodousian Amin
Published: August 2024

Link prediction plays a critical role in network analysis as it tackles the task of predicting missing or future connections within a given network. A wide array of link prediction measures has been proposed to estimate the likelihood of link existence between nodes, aiming to uncover hidden relationships and anticipate the formation of new connections. This task holds particular significance in various domains, including social networks, biological networks, transportation networks, and recommender systems. Nonetheless, evaluating the effectiveness of these measures poses challenges, encompassing both the measures themselves and the employed evaluation metrics. This article offers a comprehensive overview of the existing link prediction measures, shedding light on their limitations and addressing the associated challenges in evaluating their efficacy. Moreover, we propose enhancements to overcome these challenges, entailing modifications to existing measures and the introduction of novel evaluation metrics. By tackling these issues head-on, our objective is to enhance the accuracy and reliability of link prediction in network analysis.
Study on the Optimized Layout of CO₂ Emission Devices from the Perspective of Greenhouse Flow Field Dynamics
Authors: WANG Binnan , Shang Tingyi
Published: August 2024

In the rapid development of modern agricultural technology, greenhouse facilities have become an important cornerstone of agricultural production, with increasingly wide applications and significant implications for improving agricultural production efficiency and crop quality. However, in practical applications, especially during the morning to noon period, due to the gradual increase of solar radiation, the photosynthesis activity of plants in the greenhouse also intensifies, resulting in a significant increase in carbon dioxide consumption. This phenomenon not only reduces the carbon dioxide concentration in the greenhouse, but also limits the efficiency of photosynthesis to a certain extent, thereby adversely affecting the growth of greenhouse crops and ultimately potentially affecting the economic benefits of agricultural crops. To address this challenge, this study introduces carbon dioxide release devices as a solution, and through simulation methods, comparatively analyzes the impact of carbon dioxide release devices placed in different positions on the carbon dioxide concentration distribution in the greenhouse. Through precise data collection and processing, this study aims to determine the optimal placement position of carbon dioxide release devices to achieve the optimization of airflow distribution inside the greenhouse and improve the utilization efficiency of carbon dioxide.
Historical marine ecology using non-traditional data sources reveals the impact of local and global processes over half a century
Authors: Turnbull John W. , Booth D. J. , Vergés Adriana , Clark Graeme
Published: August 2024

Human impacts on earth span centuries, yet scientific studies cover a fraction of this time. Historical records and citizen scientist data are a useful resource for the long-term studies needed to understand and respond to pressures on nature, yet their quality and validity have been challenged. To explore how such non-traditional sources can be used to understand historical ecological change, we studied a site (Shiprock) with long-term citizen science activity in the Sydney, Australia region. We analysed approximately 6000 taxonomic records and reports revealing substantial ecological changes between 1965 and 2020, including the local disappearance of some fish and invertebrate species and declines in the abundance of many taxa including kelp. We found indications of potential range extensions more frequently from the north than the south, consistent with patterns expected from the global processes of climate change. We compared the relative advantages and limitations of the two main citizen science data collection modes: structured surveys and opportunistic presence records. Structured surveys provided broadly scientifically useful ecological information including species richness, populations, community structure and temporal change. Opportunistic data had the potential to provide long-term retrospective community information and species presence, but were limited in the ability to provide species absence, biomass, populations, community structure and coverage of remote areas. Our study allowed the development of scientifically- and managerially-relevant insights encompassing foundation, threatened, protected and invasive species, community shifts and the impacts of local and global processes over historical timescales.
A Multi-Layer Heterogeneous Task Scheduling Strategy in UAVs-assisted MEC Networks
Authors: Pang ShanChen , Zhu XiaoRan , Gui Haiyuan , Zhang Yanxiang
Published: August 2024

This paper studies the task scheduling problem in the multiple unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) system. In order to reflect the complexity and diversity of the system, we propose a multi-layer heterogeneous task scheduling strategy. The strategy allows system model to simulate arrival and service of tasks by applying heterogeneous M/M/1, M/M/c, and M/M/c/K classical queues. In order to better evaluate the proposed strategy, we obtain various performance measures. By trading off delay and energy consumption, a single-objective optimization problem with constraints is formulated. Then we introduce the penalty function method to transform the problem into a single-objective optimization problem without any constraints, and propose a hierarchical heterogeneous task scheduling optimization (HHTSO) algorithm to optimize the formulated problem. Theoretical analysis and simulation results show that the proposed algorithm is more effective in ensuring low delay and low energy consumption.
Transforming de novo peptide sequencing by explainable AI
Authors: Wang Yu , Liang Zhendong , Ling Tianze , Chang Cheng , Yang Tingpeng , Xie Linhai , He Yonghong
Published: August 2024

De novo peptide sequencing is crucial for identifying novel proteins, yet its broader application is constrained by the lack of a robust quality control system. In response, we developed a transformer-based model, π-xNovo, that accurately predicts peptides. By analyzing the model's attention matrix, we elucidated the contribution of spectral peaks to amino acid predictions, thus making de novo sequencing results explainable. Leveraging these insights, we designed a quality control system, π-xNovo-QC, which distinguishes peptide predictions with an accuracy exceeding 80% and a sensitivity above 90%. Applying this system to a large-scale deep human proteome dataset resulted in the identification of 1,931,761 additional peptides, marking a 137% increase over traditional database search results. These newly identified peptides with high confidence facilitated a 17.9% increase in protein identification, a 23.59% increase in the detection of single amino acid polymorphism events, and a 20.02% increase in exon-skipping splicing events. The deployment of this explainable AI system holds significant potential for expanding the application of de novo peptide sequencing, particularly in exploring the darker matter of the entire proteome universe.
Driving analysis and prediction of COD based on frequency division
Authors: Li Mei , Chen Kexing , Wang Deke , Xu Rui
Published: August 2024

COD (Chemical Oxygen Demand) is an important indicator to measure organic pollution of water body. To strengthen in-depth analysis and prediction of COD, a new method was proposed in this paper. A frequency division method, Variational Mode Decomposition (VMD) was used to complete time domain decomposition of COD data before model simulation. The original data was separated into five signals with different frequency bands, IMF1, IMF2, IMF3, IMF4 and IMF5, with which the influence of meteorological factors and water quality factors on COD were explored. The long-term COD content is mainly driven by nutrient factors phosphorus and nitrogen, while the immediate fluctuation characteristics exhibit relatively stability. Random Forest, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) were used to predict COD with the original data and the signal data processed by VMD. It is found that frequency division can improve simulation stability and accuracy of GRU and LSTM more significantly than Random Forest. VMD-GRU and VMD-LSTM models can be used reliably for COD analyzation and prediction in Chengdu area.
Feasibility of novel bigels prepared by beeswax and basil seed mucilage for 3D printing approach
Authors: Jasemi Mohammad mehdi , Noshad Mohammad , Jooyandeh Hossein , Mehdizadeh Saman Abdanan , Behbahani Behrooz Alizadeh
Published: August 2024

In this research, a series of bigels were prepared by incorporating a beeswax-based oleogel and basil seed mucilage- based hydrogels in different ratios. The effect of several oleogel/hydrogel combinations on the physical features and 3D printing capability of the resulting bigels was evaluated. FTIR results of several bigels showed significant variations between 3500-3300 cm-1 (hydroxyl groups) and 1150-990 cm-1 (stretching of C-O and C-O-C bonds). The bigels displayed a shear-thinning characteristic and demonstrated enhanced mechanical properties, such as apparent viscosity, storage modulus, and firmness compared to both pure oleogel and pure hydrogel. According to the thermogravimetric analysis (TGA) results, the weight loss in bigel formulations was faster compared to hydrogels. Bigels with an oleogel/hydrogel ratio of 70:30 exhibited favorable mechanical properties suitable for 3D printing. The findings of this research demonstrate that it is possible to produce 3D printable bigels by blending beeswax (organogelators) with basil seed mucilage (hydrogelator). Furthermore, the characteristics and printing capabilities of these bigels can be customized by adusting the ratios of oleogel to hydrogel.
Screening and identification of key genes between high-grade and low-grade serous ovarian carcinomas using integrated bioinformatics
Authors: Zhang Liwei , Pan Zhenglan , Song Weiguo , Wang Wenyan , Fu Liutao , Li Jun , He Runhua , Wang Qingyuan , Wang Yue , Zhang Shenghua , Shan Wenjun , Wei Bing , Fu Juanjuan
Published: August 2024

Epithelial ovarian cancer (EOC) is one of the most aggressive tumors in women. The most common pathological type of EOC is high-grade serous carcinoma (HGSC), which is often diagnosed at an advanced stage. Low-grade serous carcinoma (LGSC) is estimated to account for 10% of all serous carcinomas. Previous studies have demonstrated that molecular and clinical characteristics differences are apparent between these two subtypes of EOC. The objective of this study was to screen and identify key genes between HGSC and LGSC, and to explore potential molecular mechanisms in the pathogenesis of EOC. The microarray datasets GSE27651 and GSE14001, with a total of 23 LGSC tissue samples and 32 HGSC tissue samples, were obtained from the Gene Expression Omnibus (GEO). The differentially-expressed genes (DEGs) were selected out through the “affy” and “limma” package in R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) analysis of DEGs was carried out through the Cytoscape software. Finally, survival analysis of some key geneswas conducted using the Kaplan Meier Plotter Online Tool. A total of 357 DEGs were found in HGSC, of which 181 were up regulated and 176 were down regulated. GO functional enrichment analysis showed that the DEGs were mainly associated with nucleus, cell proliferation and protein binding. KEGG pathway analysis showed that these genes were enriched in the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, cell cycle, microRNAs in cancer. Twelve hub genes (TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1, BUB1, RRM2 and PBK) were screened out from PPI network. The mRNA expression of TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1, BUB1, RRM2, and PBK were significantly increased in tumor tissues. The protein expression of TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1 and PBK were distinctly higher in serous ovarian cancer tissues than non-serous ovarian cancer tissues detected by immunohistochemical staining. Survival analysis showed that TOP2A, CCNB1, KIF11, AURKA, and BUB1 were significantly associated with clinical survival outcome. In addition, there is a significant correlation between the expression levels of twelve hub-genes and immune cell infiltration in serous ovarian cancer. In summary, the present study identified DEGs and hub genes by two GEO datasets mining, which might offer new insights into the molecular mechanisms of these two subtypes of EOC and provide some prognostic biomarkers for the treatment of EOC.
Transfer printing micro-assembly of silicon photonic crystal cavity arrays: beating the fabrication tolerance limit
Authors: bommer sean , Panuski Christopher , Guilhabert Benoit , Xia Zhongyi , Smith Jack , Dawson Martin , Englund Dirk , Strain Michael
Published: August 2024

Photonic crystal cavities (PhCCs) can confine optical fields in ultra-small volumes, enabling efficient light-matter interactions for quantum and non-linear optics, sensing and all-optical signal processing. The inherent nanometric tolerances of micro-fabrication platforms can induce cavity resonant wavelength shifts two-orders of magnitude larger than cavity linewidths, prohibiting fabrication of arrays of nominally identical devices. We address this device variability by fabricating PhCCs as releasable pixels that can be transferred from their native substrate to a receiver where ordered micro-assembly can overcome the inherent fabrication variance. We demonstrate the measurement, binning and transfer of 119 PhCCs in a single session, producing spatially ordered arrays of PhCCs, sorted by resonant wavelength. Furthermore, the rapid in-situ measurement of the devices enables measurements of the PhCCs dynamic response to the print process for the first time, showing plastic and elastic effects in the seconds to hours range.
The environment quality of metals in surface sediments in Hangzhou Bay
Authors: Liu Weifeng , Liu Shengfa , Zhang Hui , Jiang Wei
Published: August 2024

Hangzhou Bay is facing the environmental pressure brought by the economic development of the surrounding areas, but the comprehensive and systematic study of heavy metals in the sediments was still insufficient. In this study, heavy metals (Cu, Pb, Zn, Cr, Ni and V) in 231 surface sediments in Hangzhou Bay were analyzed to evaluate their spatial distribution and pollution status and their controlling factors. The contents of metals in sediments had a low level and were not facing serious ecological risk on the whole. However, most metals exhibited higher concentrations in the central and northeastern parts of Hangzhou Bay, while Zn and Cr showed elevated contents in the adjacent area of the Qiantang River mouth, where the environmental quality assessment of metals showed low-to-moderate pollution, which was worthy of attention. The heavy metals in the sediments were primarily from natural sources and their distribution was mainly dominated by the grain size of the sediments. However, Pb in the northern coastal areas and Cr and Zn in the Qiantang River mouth were found to have high contents and indicated relatively serious pollution potentially caused by human activities. This study is of great scientific significance for understanding the accumulation and source-sink process of heavy metals in the sediments of the Bay of intense human activities.
High-Performance Supercapacitors Utilising PEDOT Composite Electrodes; Synthesis, Characterisation and Electrochemical Performance Analysis
Authors: Ljubek Gabrijela , Roković Marijana Kraljić
Published: August 2024

The aim of this work was to prepare poly(3,4-ethylenedioxythiophene) (PEDOT) electrodes from an electrolyte containing graphene oxide (GO) and sodium dodecyl sulphate (SDS) (PEDOT/GO/SDS) or poly(4-styrene sulphonate) (PSS) (PEDOT/GO/PSS) solutions. The synthesis was also carried out without GO presence (PEDOT/SDS, PEDOT/PSS). PEDOT and PEDOT/GO were synthesised at glassy carbon support, while PEDOT/GO-R was synthesised at GO support, all were prepared by applying 1.0 V vs. SCE during 300 s. After PEDOT synthesis, the electrode with GO support was additionally polarised at -1.4 V vs. SCE in 0.1 mol dm− 3 KCl solution for 600 s, to obtain reduced graphene oxide (rGO). In this way, PEDOT/GO/SDS-R and PEDOT/GO/PSS-R electrodes were prepared. Prepared electrodes were used to assemble symmetric supercapacitors tested by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The stability of the supercapacitors was determined by charging/discharging at constant current during 1000 cycles, and the specific capacitance (Cs), energy (Ws) and power (Ps) were calculated. The presence of GO in synthesis solution or as support decreased synthesis rate and resulted in a more compact layer with a lower specific capacitance value. However, the successful reduction of GO resulted in a significant improvement of capacitive properties, making this electrode suitable for high-energy applications.
Calibrating resolver for LEO satellite ground stations utilizing Deep Neural Network
Authors: Sancar Yasin , Birdal Ramiz Görkem
Published: August 2024

Low Earth Orbit (LEO) ground stations rely on precise rotational position feedback systems, such as resolvers, to accurately track and communicate with satellites. Nevertheless, resolvers often suffer from calibration errors due to mechanical misalignments, temperature variations, and other environmental factors. This study proposes a method for calibrating 16-bit resolvers using Deep Neural Networks (DNNs) to enhance accuracy and reliability in LEO ground station applications. In traditional calibrations, known errors are compensated for by mechanically aligning the resolver. This process often requires manual intervention and periodic recalibration to maintain accuracy. Instead, proposed automated calibration reduces the need for frequent manual calibration, which saves time and resources. Error profiles and characteristics of resolver were easily revealed by DNN's multiple layers of neurons, capable of learning complex input-output mappings. As a result of this software-based error compensation method, target distortion ratio of 16-bit resolver was improved from ~ ±%10 to ~ ±%2. This means the error in the target angle, which can be as high as 1°, can be decreased to a level of 0.2° by using the DNN for calibration. It is also possible to overcome nonideal characteristics of a resolver such as amplitude imbalance, quadrature error, and inductive harmonics with the method presented in this study.
Deep Learning Applications in Orthopaedics: A Systematic Review and Future Directions
Authors: Pola Ramon Gonzalez , Lozano Alberto Herrera , Nieto Luis Felipe Graham , Garcia Gabriela Zermeño
Published: August 2024

Introduction: Artificial intelligence and deep learning in orthopaedics had gained mass interest over the last years. In prior studies, researchers have demonstrated different applications, from radiographic assessment to bone tumor diagnosis. The purpose of this review is to provide an analysis of the current literature for AI and deep learning tools to identify the most used application in risk assessment, outcomes assessment, imaging, and basic science fields. Method: Searches were conducted in Pubmed, EMBASE and Google scholar up to October 31st, 2023. We identified 717 studies, of which 595 were included in the systematic review. 281 studies about radiographic assessment, 102 about spine-oriented surgery, 95 about outcomes assessment 84 about fundamental AI orthopedic education, and 33 about basic science application were included for review. Primary outcomes were measures of diagnostic accuracy, study design and reporting standards in the literature. Estimates were pooled using random-effects meta-analysis. Results: 153 different imagenology measurements for radiographic aspects were identified. 185 different machine learning algorithms were used, being the convolutional neural network architecture the most common one (73%). To improve diagnostic accuracy and speed were the most commonly used (62%). Conclusion: Heterogeneity was high between studies and extensive variation in methodology, terminology and outcome measures were noted. This can lead to an overestimation of the diagnostic accuracy of DL algorithms on medical imaging. There is an immediate need for the development of artificial intelligence-specific guidelines, to provide guidance around key issues in this field.