bluuebunny/crossref_metadata_2025 huggingface dataset:
Epidermal keratinocyte-specific STAT3 deficiency aggravated atopic dermatitis-like skin inflammation in mice through TSLP upregulation
Authors: Wang Zhao-Yuan , Zheng Yu-Xin , Xu Fan , Cui Ying-Zhe , Chen Xue-Yan , Chen Si-Qi , Yan Bing-Xi , Zhou Yuan , Zheng Min , Man Xiao-Yong
Published: November 2023

Atopic dermatitis (AD) is one of the most common inflammatory skin diseases with complex pathogenesis involving epidermal barrier dysfunction, skin microbiome abnormalities and type-2-skewed immune dysregulation. Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that plays critical roles in various biological processes. However, the role of STAT3 in epidermal keratinocytes in AD remains unclear. In this study, we generated an epidermal keratinocyte-specific Stat3-deficient mouse strain (termed Stat3 cKO mice). After topical 2,4-dinitrochlorobenzene (DNCB) treatment, Stat3 cKO mice developed worsened AD-like skin inflammation with increased Ki67+ cells, decreased filaggrin and loricrin expression, and downregulated S100A9 and LL37. The dominant microbial population in Stat3 cKO mice changed from Ralstonia to Staphylococcus. DNCB-treated Stat3 cKO mice displayed more infiltrating type-2 inflammatory cells, including mast cells, eosinophils, and CD4+T cells, accompanied by increased skin IL-4 and serum IgE levels. Moreover, thymic stromal lymphopoietin (TSLP), mainly produced by keratinocytes, was highly expressed in the ear skin of Stat3 cKO mice and chemoattracted more TSLPR+ cells. TSLP blockade significantly alleviated DNCB-induced AD-like skin inflammation in Stat3 cKO mice. Thus, epidermal keratinocyte-specific STAT3 deficiency can aggravate AD-like skin inflammation in mice, possibly through TSLP dysregulation.
Human adipose tissue as a major reservoir of cytomegalovirus-reactive T cells
Authors: Redruello-Romero Anaïs , Benitez-Cantos Maria S. , Lopez-Perez David , García-Rubio Jesús , Tamayo Francisco , Pérez-Bartivas Daniel , Moreno-SanJuan Sara , Ruiz-Palmero Isabel , Puentes-Pardo Jose D. , Vilchez Jose R. , López-Nevot Miguel Á. , García Federico , Cano Carlos , León Josefa , Carazo Ángel
Published: November 2023

Introduction

Cytomegalovirus (CMV) is a common herpesvirus with a high prevalence worldwide. After the acute infection phase, CMV can remain latent in several tissues. CD8 T cells in the lungs and salivary glands mainly control its reactivation control. White adipose tissue (WAT) contains a significant population of memory T cells reactive to viral antigens, but CMV specificity has mainly been studied in mouse WAT. Therefore, we obtained blood, omental WAT (oWAT), subcutaneous WAT (sWAT), and liver samples from 11 obese donors to characterize the human WAT adaptive immune landscape from a phenotypic and immune receptor specificity perspective.

Methods

We performed high-throughput sequencing of the T cell receptor (TCR) locus to analyze tissue and blood TCR repertoires of the 11 donors. The presence of TCRs specific to CMV epitopes was tested through ELISpot assays. Moreover, phenotypic characterization of T cells was carried out through flow cytometry.

Results

High-throughput sequencing analyses revealed that tissue TCR repertoires in oWAT, sWAT, and liver samples were less diverse and dominated by hyperexpanded clones when compared to blood samples. Additionally, we predicted the presence of TCRs specific to viral epitopes, particularly from CMV, which was confirmed by ELISpot assays. Remarkably, we found that oWAT has a higher proportion of CMV-reactive T cells than blood or sWAT. Finally, flow cytometry analyses indicated that most WAT-infiltrated lymphocytes were tissue-resident effector memory CD8 T cells.

Discussion

Overall, these findings postulate human oWAT as a major reservoir of CMV-specific T cells, presumably for latent viral reactivation control. This study enhances our understanding of the adaptive immune response in human WAT and highlights its potential role in antiviral defense.
Numerical study of tidal effect on the water flux across the Korea/Tsushima Strait
Authors: Jiang Wenxin , Yang Dezhou , Xu Lingjing , He Zhiwei , Cui Xuan , Yin Baoshu
Published: November 2023

Tremendous amounts of materials and energy are transported from the East China Sea (ECS) to the East/Japan Sea (EJS) through the Korea/Tsushima Strait (KTS). Tides undoubtedly play an important role in regulating ocean circulation on the broad continental shelf of the ECS, while the effects of tides on the water exchange between the ECS and EJS remain unclear. Using a three-dimensional Regional Oceanic Modeling System (ROMS) circulation model, we conducted numerical experiments with tides, without tides, and only barotropic tides. The results showed that the water flux across the KTS can increase by up to 13% (in summer) when excluding tides from the numerical simulation. To understand how tidal forcing regulates the KTS water flux, we performed a dynamic diagnostic analysis and revealed that the variation in sea surface height under tidal effect is the main reason for the water flux variation across the KTS. The tidal effect can adjust the sea surface height, weaken the pressure gradient and reduce the water flux across the KTS, which affect the intensity of water exchange between the ECS and EJS. The tidal effect can alter sea level difference between the Taiwan Strait and the KTS, which influences the KTS water flux. Tides can also influence the KTS water flux by altering the sea surface height through interaction with topography and stratification. We also found that tidal effect weakens the northward intrusion of the Yellow Sea Warm Current in winter and in turn enhances the water flux across the KTS according to volume conservation. These modeling results imply that tides must be considered when simulating the ocean environment of the northwestern Pacific Ocean.
Genome sequencing and metabolic network reconstruction of a novel sulfur-oxidizing bacterium Acidithiobacillus Ameehan
Authors: Wu Peng , Yuan Qianqian , Cheng Tingting , Han Yifan , Zhao Wei , Liao Xiaoping , Wang Lu , Cai Jingyi , He Qianqian , Guo Ying , Zhang Xiaoxia , Lu Fuping , Wang Jingjing , Ma Hongwu , Huang Zhiyong
Published: November 2023

Sulfur-oxidizing bacteria play a crucial role in various processes, including mine bioleaching, biodesulfurization, and treatment of sulfur-containing wastewater. Nevertheless, the pathway involved in sulfur oxidation is highly intricate, making it complete comprehension a formidable and protracted undertaking. The mechanisms of sulfur oxidation within the Acidithiobacillus genus, along with the process of energy production, remain areas that necessitate further research and elucidation. In this study, a novel strain of sulfur-oxidizing bacterium, Acidithiobacillus Ameehan, was isolated. Several physiological characteristics of the strain Ameehan were verified and its complete genome sequence was presented in the study. Besides, the first genome-scale metabolic network model (AMEE_WP1377) was reconstructed for Acidithiobacillus Ameehan to gain a comprehensive understanding of the metabolic capacity of the strain.The characteristics of Acidithiobacillus Ameehan included morphological size and an optimal growth temperature range of 37-45°C, as well as an optimal growth pH range of pH 2.0-8.0. The microbe was found to be capable of growth when sulfur and K2O6S4 were supplied as the energy source and electron donor for CO2 fixation. Conversely, it could not utilize Na2S2O3, FeS2, and FeSO4·7H2O as the energy source or electron donor for CO2 fixation, nor could it grow using glucose or yeast extract as a carbon source. Genome annotation revealed that the strain Ameehan possessed a series of sulfur oxidizing genes that enabled it to oxidize elemental sulfur or various reduced inorganic sulfur compounds (RISCs). In addition, the bacterium also possessed carbon fixing genes involved in the incomplete Calvin-Benson-Bassham (CBB) cycle. However, the bacterium lacked the ability to oxidize iron and fix nitrogen. By implementing a constraint-based flux analysis to predict cellular growth in the presence of 71 carbon sources, 88.7% agreement with experimental Biolog data was observed. Five sulfur oxidation pathways were discovered through model simulations. The optimal sulfur oxidation pathway had the highest ATP production rate of 14.81 mmol/gDW/h, NADH/NADPH production rate of 5.76 mmol/gDW/h, consumed 1.575 mmol/gDW/h of CO2, and 1.5 mmol/gDW/h of sulfur. Our findings provide a comprehensive outlook on the most effective cellular metabolic pathways implicated in sulfur oxidation within Acidithiobacillus Ameehan. It suggests that the OMP (outer-membrane proteins) and SQR enzymes (sulfide: quinone oxidoreductase) have a significant impact on the energy production efficiency of sulfur oxidation, which could have potential biotechnological applications.
Nitrogen addition strengthens the stabilizing effect of biodiversity on productivity by increasing plant trait diversity and species asynchrony in the artificial grassland communities
Authors: Suonan Ji , Lu Xuwei , Li Xiaona , Hautier Yann , Wang Chao
Published: November 2023

Background and aims

Nitrogen (N) enrichment usually weakens the stabilizing effect of biodiversity on productivity. However, previous studies focused on plant species richness and thus largely ignored the potential contributions of plant functional traits to stability, even though evidence is increasing that functional traits are stronger predictors than species richness of ecosystem functions.

Methods

We conducted a common garden experiment manipulating plant species richness and N addition levels to quantify effects of N addition on relations between species richness and functional trait identity and diversity underpinning the ‘fast–slow’ economics spectrum and community stability.

Results

Nitrogen addition had a minor effect on community stability but increased the positive effects of species richness on community stability. Increasing community stability was found in the species-rich communities dominated by fast species due to substantially increasing temporal mean productivity relative to its standard deviation. Furthermore, enhancement in ‘fast–slow’ functional diversity in species-rich communities dominated by fast species under N addition increased species asynchrony, resulting in a robust biodiversity–stability relationship under N addition the artificial grassland communities.

Conclusion

The findings demonstrate mechanistic links between plant species richness, ‘fast–slow’ functional traits, and community stability under N addition, suggesting that dynamics of biodiversity–stability relations under global changes are the results of species-specific responses of ‘fast–slow’ traits on the plant economics spectrum.
Lexical diversity in kinship across languages and dialects
Authors: Khalilia Hadi , Bella Gábor , Freihat Abed Alhakim , Darma Shandy , Giunchiglia Fausto
Published: November 2023

Languages are known to describe the world in diverse ways. Across lexicons, diversity is pervasive, appearing through phenomena such as lexical gaps and untranslatability. However, in computational resources, such as multilingual lexical databases, diversity is hardly ever represented. In this paper, we introduce a method to enrich computational lexicons with content relating to linguistic diversity. The method is verified through two large-scale case studies on kinship terminology, a domain known to be diverse across languages and cultures: one case study deals with seven Arabic dialects, while the other one with three Indonesian languages. Our results, made available as browseable and downloadable computational resources, extend prior linguistics research on kinship terminology, and provide insight into the extent of diversity even within linguistically and culturally close communities.
The Spanish Olive Oil with Quality Differentiated by a Protected Designation of Origin
Authors: García-Moral Ana , Moral-Pajares Encarnación , Gallego-Valero Leticia
Published: November 2023

The Protected Designation of Origin (PDO), part of the EU’s quality policy for agri-food products, aims to provide consumers with reliable information on the quality of a food, linked to its origin. Olive oil has perceptible qualities derived from its place of production, which create a link between the product and its place of origin, and which can influence consumer preferences. Spain, the world’s leading producer of this vegetable fat, had 29 PDOs at the end of 2020, 25.84% of the EU total for this industry. Based on the arguments drawn from the literature and the information provided by the Spanish Ministry of Agriculture, Fisheries and Food (MAPA), this paper first analyses the importance of olive oil with differentiated quality certified by a PDO for the Spanish olive oil industry. Secondly, the t-test is applied to identify positive differences in the income earned by farmers who produce olive oil certified by a PDO. Thirdly, the international competitiveness of extra virgin olive oil (EVOO) bearing a PDO label is analysed using the Revealed Comparative Advantage (RCA) index. The evidence confirms that PDO certification adds value to the product and promotes exports. However, the Spanish olive oil industry does not perform well enough to harness the potential offered by this quality label, it as it does not manage to sell all the PDO-certified EVOO. This situation merits further investigation in future studies, and should be taken into account in the design of actions and campaigns organised by institutions involved in the industry. This article contributes to the evaluation of the quality policy for EU agri-food products and examines the recent evolution of the Spanish PDO-certified olive oil industry.
Increase in Soil Carbon Pool Stability Rather Than Its Stock in Coastal Saline—Alkali Ditches following Reclamation Time
Authors: Li Xiangrong , Liu Zhen , Li Jing , Gong Huarui , Zhang Yitao , Sun Zhigang , Ouyang Zhu
Published: November 2023

Extensive drainage ditches are constructed to reduce soil salinity in reclaimed saline–alkali farmland, consequently forming plant growth hotspots and impacting soil carbon stocks therein. However, the investigation into changes in soil carbon stocks remains limited in these ditches. To address this, soil samples were collected from drainage ditches, which originated from the reclamation of saline–alkali farmland, at different reclamation years (the first, seventh, and fifteenth year). Moreover, fractions were separated from soil samples; a particle size separation method (particulate organic matter, POM; mineral–associated organic matter, MAOM) and a spatio–temporal substitution method were conducted to analyze the variations in soil carbon components and the underlying mechanisms. The results indicate that there were no significant variations in the contents and stocks of soil organic carbon (SOC) and soil inorganic carbon (SIC) following the increase in reclamation time. However, in the POM fraction, the SOC content (SOCPOM) and stock significantly decreased from 2.24 to 1.12 g kg−1 and from 19.02 to 12.71 Mg ha−1, respectively. Conversely, in the MAOM fraction, the SOC content (SOCMAOM) and stock significantly increased from 0.65 to 1.70 g kg−1 and from 5.30 to 12.27 Mg ha−1, respectively. The different changes in SOCPOM and SOCMAOM, as well as the result of the structural equation model, showed a possible transformation process from SOCPOM to SOCMAOM in the soil carbon pool under the driving force of reclamation time. The results in terms of the changes in soil carbon components demonstrate the stability rather than the stock of the soil carbon pool increase in coastal saline–alkali ditches following the excavation formation time. Although more long time series and direct evidence are needed, our findings further provide a case study for new knowledge about changes in the soil carbon pool within saline–alkali ditches and reveal the potential processes involved in the transformation of soil carbon components.
The Purple leaf (Pl) Alleles, Plw and Pli, Regulate Leaf Color Development Independently from the Pb Gene of Purple pericarp (Prp) in Rice
Authors: Kang Sang Gu , Lee Kyung Eun , Cho Jegeun , Lee Jeong Wook , Do Geum Sook , Matin Mohammad Nurul
Published: November 2023

Color development in various rice organs results from the complementary expression of genes involved in anthocyanin biosynthesis. The Purple pericarp (Prp) trait and the Purple leaf (Pl) trait both display epistasis, relying on the complement of the Pb and Pp genes for pericarp coloration and the Pl and Pp genes for leaf coloration, respectively. However, there is still genetic uncertainty in identifying the genes responsible for the various color expressions and intensities of rice grain pericarp and leaves. In this study, we characterized the inheritance patterns of color development and the mode of anthocyanin pigments in rice by crossing two parental mutant lines. YUM051, exhibiting dark purple leaves (Plw) and purple pericarp (Prp), was crossed with YUM144, which displayed light purple leaves (Pli) and a white pericarp (prp). The F1 plants exhibited dark purple leaves with purple pericarps, indicating the dominant nature of the purple leaf (Pl) and purple pericarp (Prp) traits. The rice Prp traits display a complementary interaction, reflected in a 9:7 ratio of purple to white pericarp. However, the Prp trait followed Mendelian segregation with a 3:1 ratio of purple to white pericarp in this cross, indicating homozygous dominant Pp alleles in both parental plants. Meanwhile, the segregation of the purple leaf color in the F2 generation of this cross followed complementary inheritance, exhibiting a 9:7 segregation ratio between purple leaves and greenish leaves with purple leaf margins. Moreover, the co-segregation of Prp and Pl traits in the cross between YUM051 (Plw) and YUM144 (Pli) plants did not adhere to the Mendelian 9:3:3:1 independent assortment ratio, confirming that the Pl gene and Pb gene are linked on the same chromosome. Cyanidin-3-O-glucoside (C3G) was detected in the leaves of all progeny resulting from the Plw and Pli cross. However, C3G was exclusively identified in the seeds of offspring carrying the dominant Pb gene. Therefore, the Plw and Pli alleles are Pl genes responsible for purple leaf color, while the Pb gene is responsible for purple pericarp color in rice; these genes function independently of each other.
Nutritional Composition, Antioxidant Activity, Cytotoxicity, and Enzymatic Potential of Ficus nitida-Associated Tomophagus colossus
Authors: Al-Bedak Osama Abdel-Hafeez Mohamed , Moharram Ahmed Mohamed , Abdel-Raheam Hossam El-Dean Farghaly , Stephenson Steven L. , Ameen Fuad
Published: November 2023

A fruiting body of a basidiomycete fungus was discovered growing on chopped Ficus nitida tree trunks in the student housing on the Assiut University campus during the course of this inquiry and a normal collecting operation in the Assiut Governorate, Egypt. Following the growth of the basidioma’s inner tissue on PDA, fungal mycelial growth was achieved. Internal transcribed spacer region (ITS) sequencing has allowed for the identification of the fungus as Tomophagus colossus. On the dry weight basis, chemical analysis of T. colossus AUMC 14536 basidioma revealed that it contains 28.81% carbohydrates, 25.34% crude fats, 23.44% crude fibers, 20.64% crude proteins, and 3.02% ash, in addition to potassium, phosphorus, calcium, selenium, iron, and zinc (133.59, 114.46, 6.27, 3.08, 1.28, and 0.73 mg/100 g dry weight, respectively). The total phenolic compounds (39.26 mg/g) and total flavonoids (5.62 mg/g) were also evaluated. The basidioma extract’s antioxidant activity was assessed as %DPPH radical scavenging activity with an IC50 of 4.15 µg/mL compared with a 1.89 µg/mL IC50 of ascorbic acid. In solid-state fermentation (SSF), the fungus could ferment broad bean straw, palm leaf hay, rice husk, rice straw, sugarcane bagasse, and wheat bran to produce endoglucanase, exoglucanase, laccase, pectinase, and xylanase in substantial amounts. Specific activity exhibited the highest values for endoglucanase (81.48 U/mg), exoglucanase (114.35 U/mg), pectinase (81.94 U/mg), and xylanase (70.18 U/mg) on the rice husk, while the peak of laccase activity (94.27 U/mg) was gained on bean straw. This is the first assessment of the organism’s nutritional value, amino acid content, antioxidant activity, and enzymatic capabilities in Egypt.
Isolation, Identification, and Pathogenicity of Vibrio gigantis Retrieved from European Seabass (Dicentrarchus labrax) Farmed in Türkiye
Authors: Yilmaz Sevdan , Karataş Süheyla , Steinum Terje Marken , Gürkan Mert , Yilmaz Dilek Kahraman , Abdel-Latif Hany M. R.
Published: November 2023

In this study, V. gigantis strain C24 was isolated from cases of winter mortalities of hatchery-reared European seabass (Dicentrarchus labrax) broodstock in Türkiye. The first mortalities were reported in September 2016 and occurred annually in early autumn/late winter until the end of February 2019, when 15% of accumulated mortality was recorded. Diseased moribund fish exhibited general septicemic signs, including dermal ulcerations with hemorrhagic margins, distended abdomens, and hemorrhages below the pectorals, pelvic fins, and at the operculum. Postmortem findings showed congestion in several internal organs, hemorrhagic ascitic fluid, and congested prolapsed anal openings. The representative bacterial isolate V. gigantis strain C24 was characterized as Gram-negative, motile, nitrite-producing, and as vibrio static agent O/129-sensitive. The full-length 16S rRNA sequence (Accession No. ON778781) and gyrB gene sequence (Accession No. ON792326) of the C24 strain showed high similarity to V. gigantis strains. Moreover, the whole-genome average nucleotide identity (ANI) values (ANI > 97.7%) against four V. gigantis strains above the species demarcation limit unambiguously identified the C24 isolate as a member of this species. A preliminary virulence-gene analysis showed that the V. gigantis isolate C24 encoded at least three exotoxins, including two aerolysins and a thermolabile hemolysin. The experimental infection showed that the C24 isolate exhibited low to moderate virulence in experimentally infected European seabass juveniles. Interestingly, antimicrobial susceptibility testing revealed that the C24 isolate was susceptible to nalidixic acid, ciprofloxacin, and several other antibiotics but resistant to tilmicosin, kanamycin, streptomycin, and ampicillin. To our knowledge, this study is the first to report that V. gigantis could be considered an emerging bacterial pathogen in Türkiye, and it may threaten the international European seabass production.
Alteration Mechanism of Variscan Granite in a Project Area at the Northern Foot of the Tianshan Mountains, China
Authors: Wu Tong , Shi Shang , Ren Minghao , Wang Jingwen , Dong Jinyu
Published: November 2023

Long-term erosion of granite—a type of hard rock—by hydrothermal fluids and tectonic movement can lead to a fragmentation of the internal structure of the original rock, transfer/replacement of mineral elements, and alteration of the rock’s basic properties. Such changes can be problematic for the construction of water conservancy, hydropower, and road projects. This study adopted the altered Variscan granite in a water diversion project area at the northern foot of the Tianshan Mountains (China) as the research object, and explored the alteration mechanism using thin section identification, X-ray diffraction, major element analysis, and electron probe and oxygen isotope tests. Results showed that the lithology of the granite in the study area is mainly biotite granodiorite and biotite monzonitic granite. Reductions in both the K+ content in plagioclase and the K+ and Ti4+ contents in chlorite indicate that the alteration types within the study area are mainly clayization of feldspar minerals and chloritization of biotite. Biotite granodiorite and biotite monzonitic granite both have low δ18O values. The δ18O value of biotite granodiorite decreases with increase in the Loss on Ignition. The low-δ18O-value granodiorite due to an alteration by hydrothermal fluids transformed from glacier meltwater, groundwater, atmospheric precipitation, and magmatic water; whereas the monzonitic granite might be formed by the reinvasion of low-δ18O-value granodiorite formed in the early stage, which is remelted, assimilated, and rebalanced. The research findings provide a reference for similar research on altered granite at the northern foot of the Tianshan Mountains, and also lay a foundation for subsequent research on its physical/mechanical properties and engineering characteristics.
Relevance of Machine Learning Techniques in Water Infrastructure Integrity and Quality: A Review Powered by Natural Language Processing
Authors: García José , Leiva-Araos Andres , Diaz-Saavedra Emerson , Moraga Paola , Pinto Hernan , Yepes Víctor
Published: November 2023

Water infrastructure integrity, quality, and distribution are fundamental for public health, environmental sustainability, economic development, and climate change resilience. Ensuring the robustness and quality of water infrastructure is pivotal for sectors like agriculture, industry, and energy production. Machine learning (ML) offers potential for bolstering water infrastructure integrity and quality by analyzing extensive data from sensors and other sources, optimizing treatment protocols, minimizing water losses, and improving distribution methods. This study delves into ML applications in water infrastructure integrity and quality by analyzing English-language articles from 2015 onward, compiling a total of 1087 articles. Initially, a natural language processing approach centered on topic modeling was adopted to classify salient topics. From each identified topic, key terms were extracted and utilized in a semi-automatic selection process, pinpointing the most relevant articles for further scrutiny, while unsupervised ML algorithms can assist in extracting themes from the documents, generating meaningful topics often requires intricate hyperparameter adjustments. Leveraging the Bidirectional Encoder Representations from Transformers (BERTopic) enhanced the study’s contextual comprehension in topic modeling. This semi-automatic methodology for bibliographic exploration begins with a broad topic categorization, advancing to an exhaustive analysis of each topic. The insights drawn underscore ML’s instrumental role in enhancing water infrastructure’s integrity and quality, suggesting promising future research directions. Specifically, the study has identified four key areas where ML has been applied to water management: (1) advancements in the detection of water contaminants and soil erosion; (2) forecasting of water levels; (3) advanced techniques for leak detection in water networks; and (4) evaluation of water quality and potability. These findings underscore the transformative impact of ML on water infrastructure and suggest promising paths for continued investigation.
AI-Based Resource Allocation in E2E Network Slicing with Both Public and Non-Public Slices
Authors: Wang Yuxing , Liu Nan , Pan Zhiwen , You Xiaohu
Published: November 2023

Network slicing is a key technology for 5G networks, which divides the traditional physical network into multiple independent logical networks to meet the diverse requirements of end-users. This paper focuses on the resource allocation problem in the scenario where public and non-public network slices coexist. There are two kinds of resources to be allocated: one is the resource blocks (RBs) allocated to the users in the radio access network, and the other is the server resources in the core network. We first formulate the above resource allocation problem as a nonlinear integer programming problem by maximizing the operator profit as the objective function. Then, a combination of deep reinforcement learning (DRL) and machine learning (ML) algorithms are used to solve this problem. DRL, more specifically, independent proximal policy optimization (IPPO), is employed to provide the RB allocation scheme that makes the objective function as large as possible. ML, more specifically, random forest (RF), assists DRL agents in receiving fast reward feedback by determining whether the allocation scheme is feasible. The simulation results show that the IPPO-RF algorithm has good performance, i.e., not only are all the constraints satisfied, but the requirements of the non-public network slices are ensured.
The Inversion Method Applied to the Stress Field around a Deeply Buried Tunnel Based on Surface Strain
Authors: Yan Xiaobing , Hao Qiqi , Yang Rui , Peng Jianyu , Zhang Fengpeng , Tan Sanyuan
Published: November 2023

To identify the magnitude and direction of in situ stress in deeply buried tunnels, an inversion method for the stress field was proposed based on a finite number of measurement points of surface strain. Firstly, elastic strain data of finite points on the surface of tunnel surrounding rock were acquired using the borehole stress relief method at the engineering site. Secondly, a finite element model of the tunnel surrounding rock with plastic damage was established, and the parameters of the finite element model were substituted using the SIGINI subroutine. Then, an improved Surrogate Model Accelerated Random Search (SMARS) was developed using genetic algorithm programming on the MATLAB™ platform to invert and attain the globally optimal boundary conditions. Finally, the obtained optimal boundary conditions were applied to the numerical model to calculate the stress distribution in the engineering site. The reliability of this method was validated through a three-dimensional example. The method has been successfully applied to the stress-field analysis of deep tunnels in Macheng Iron Mine, Hebei Province, China. The research results show that this method is a low-cost, reliable approach for stress-field inversion in the rock around a tunnel.
Proactive Service Caching in a MEC System by Using Spatio-Temporal Correlation among MEC Servers
Authors: Bae Hongseob , Park Jaesung
Published: November 2023

Optimizingthe cache hit rate in a multi-access edge computing (MEC) system is essential in increasing the utility of a system. A pivotal challenge within this context lies in predicting the popularity of a service. However, accurately predicting popular services for each MEC server (MECS) is hindered by the dynamic nature of user preferences in both time and space, coupled with the necessity for real-time adaptability. In this paper, we address this challenge by employing the Convolutional Long Short-Term Memory (ConvLSTM) model, which can capture both temporal and spatial correlations inherent in service request patterns. Our proposed methodology leverages ConvLSTM for service popularity prediction by modeling the distribution of service popularity in a MEC system as a heatmap image. Additionally, we propose a procedure that predicts service popularity in each MECS through a sequence of heatmap images. Through simulation studies using real-world datasets, we compare the performance of our method with that of the LSTM-based method. In the LSTM-based method, each MECS predicts the service popularity independently. On the contrary, our method takes a holistic approach by considering spatio-temporal correlations among MECSs during prediction. As a result, our method increases the average cache hit rate by more than 6.97% compared to the LSTM-based method. From an implementation standpoint, our method requires only one ConvLSTM model while the LSTM-based method requires at least one LSTM model for each MECS. Thus, compared to the LSTM-based method, our method reduces the deep learning model parameters by 32.15%.
Lung Cancer Detection Model Using Deep Learning Technique
Authors: Wahab Sait Abdul Rahaman
Published: November 2023

Globally, lung cancer (LC) is the primary factor for the highest cancer-related mortality rate. Deep learning (DL)-based medical image analysis plays a crucial role in LC detection and diagnosis. It can identify early signs of LC using positron emission tomography (PET) and computed tomography (CT) images. However, the existing DL-based LC detection models demand substantial computational resources. Healthcare centers face challenges in handling the complexities in the model implementation. Therefore, the author aimed to build a DL-based LC detection model using PET/CT images. Effective image preprocessing and augmentation techniques were followed to overcome the noises and artifacts. A convolutional neural network (CNN) model was constructed using the DenseNet-121 model for feature extraction. The author applied deep autoencoders to minimize the feature dimensionality. The MobileNet V3-Small model was used to identify the types of LC using the features. The author applied quantization-aware training and early stopping strategies to improve the proposed LC detection accuracy with less computational power. In addition, the Adam optimization (AO) algorithm was used to fine-tune the hyper-parameters in order to reduce the training time for detecting the LC type. The Lung-PET-CT-Dx dataset was used for performance evaluation. The experimental outcome highlighted that the proposed model obtained an accuracy of 98.6 and a Cohen’s Kappa value of 95.8 with fewer parameters. The proposed model can be implemented in real-time to support radiologists and physicians in detecting LC in the earlier stages. In the future, liquid neural networks and ensemble learning techniques will be used to enhance the performance of the proposed LC detection model.
A Thorough Investigation of the Dynamic Properties of Granite under Cyclic Loading
Authors: Ding Xiaobin , Zhao Junxing , Dong Yaojun , Zhou Mi
Published: November 2023

We propose a novel inverse analysis method that utilizes shockwaves to detect the operational condition of tested rock. To achieve this back analysis, an in-depth investigation of the dynamic properties of granite specimens was conducted. The dynamic properties of the granite specimens were investigated using a triaxial cyclic loading machine, under different confining pressures, loading frequencies, stress amplitudes, and numbers of cycles, and a dynamic response model was constructed from the test data. The results show that the dynamic elastic modulus increased with the increase in confining pressure, while its damping ratio decreased. The dynamic elastic modulus and damping ratio increased with the increase in loading frequency. As the dynamic stress amplitude increased, the dynamic elastic modulus of the granite increased, but the dynamic damping ratio decreased. As the number of cycles increased, the dynamic elastic modulus and dynamic damping ratio of the granite decreased and gradually stabilized. The modified Duncan–Chang model was used to construct the dynamic response model of the specimens. It is worth saying that the correlation coefficient of the model is low at a loading frequency of 20 Hz. This indicates that the frequency has a greater effect on the dynamic response of the specimen compared with the confining pressure. The conclusions obtained from these tests can be used to study more comprehensively the interaction and causal relationship between different factors, and to prepare for the next steps of tunnel rock stress-state prediction.
Study of the Impact of Aerodynamic Model Fidelity on the Flight Characteristics of Unconventional Aircraft
Authors: Goetzendorf-Grabowski Tomasz , Kwiek Agnieszka
Published: November 2023

The article presents a study on the influence of aerodynamic model fidelity on dynamic characteristics. The Simulation and Dynamic Stability Analysis (SDSA) package was used to calculate the dynamic characteristics, using both eigenvalues (linearized model) and a time history approach (nonlinear model). The tests were carried out for a rocket aircraft designed in a tailless configuration with a leading edge extension and rotating side plates. Due to these features, the rocket plane can be classified as an unconventional configuration, which requires special attention. Aerodynamic characteristics of the rocket plane were measured in a subsonic wind tunnel and calculated using Euler model equations-based software (MGAERO) and low-order potential-flow code (PANUKL). The paper presents the results of dynamic analysis in the form of standard modes of motion characteristics. A comparison of dynamic characteristics calculated using a set of aerodynamic data with different fidelity is shown and discussed. Both longitudinal and lateral cases were included. The presented results show that the potential methods, considered old-fashioned and despite many simplifications, are still an attractive tool and can be used to analyze even complex, unconventional configurations.
New Interval Improved Fuzzy Partitions Fuzzy C-Means Clustering Algorithms under Different Distance Measures for Symbolic Interval Data Analysis
Authors: Chang Sheng-Chieh , Chuang Wei-Ching , Jeng Jin-Tsong
Published: November 2023

Symbolic interval data analysis (SIDA) has been successfully applied in a wide range of fields, including finance, engineering, and environmental science, making it a valuable tool for many researchers for the incorporation of uncertainty and imprecision in data, which are often present in real-world scenarios. This paper proposed the interval improved fuzzy partitions fuzzy C-means (IIFPFCM) clustering algorithm from the viewpoint of fast convergence that independently combined with Euclidean distance and city block distance. The two proposed methods both had a faster convergence speed than the traditional interval fuzzy c-means (IFCM) clustering method in SIDA. Moreover, there was a problem regarding large and small group division for symbolic interval data. The proposed methods also had better performance results than the traditional interval fuzzy c-means clustering method in this problem. In addition, the traditional IFCM clustering method will be affected by outliers. This paper also proposed the IIFPFCM algorithm to deal with outliers from the perspective of interval distance measurement. From experimental comparative analysis, the proposed IIFPFCM clustering algorithm with the city block distance measure was found to be suitable for dealing with SIDA with outliers. Finally, nine symbolic interval datasets were assessed in the experimental results. The statistical results of convergence and efficiency on performance revealed that the proposed algorithm has better results.
Characteristic Analysis and Short-Impending Prediction of Aircraft Bumpiness over Airport Approach Areas and Flight Routes
Authors: Ding Jin , Zhang Guoping , Wang Shudong , Xue Bing , Wang Kuoyin , Yu Tingzhao , Jiang Ruijiao , Chen Yu , Huang Yan , Li Zhimin , Yang Ruyi , Liu Xiaodan , Tian Ye
Published: November 2023

Based on the Quick Access Recorder (QAR) data covering over 9000 routes in China, the monthly and intra-day distribution characteristics of aircraft bumpiness at different levels were analyzed, and the relationships between the eddy dissipation rate (EDR) and other aircraft flight status elements during bumpiness occurrence were also analyzed. Afterward, aircraft bumpiness routes were constructed using 19 machine learning models. The analyses show that (1) aircraft bumpiness was mainly concentrated between 0:00 a.m. and 17:00 p.m. Severe aircraft bumpiness occurred more frequently in the early morning in January, especially between 5:00 a.m. and 6:00 a.m., and moderate bumpiness always occurred from 3:00 a.m. to 11:00 a.m. (2) The relationship between the left and right attack angles and aircraft bumpiness on the routes was more symmetrical, with a center at 0 degrees, unlike in the approach area where the hotspots were mainly concentrated in the range of −5 to 0 degrees. In the approach area, the larger the Mach number, the more severe the bumpiness. (3) The performances of the Automatic Relevance Determination Regression (ARD), Partial Least Squares Regression (PLS), Elastic-Net Regression (ENR), Classification and Regression Tree (CART), Passive Aggressive Regression (PAR), Random Forest (RF), Stochastic Gradient Descent Regression (SGD), and Tweedie Regression (TWD) based models were relatively good, while the performances of the Huber Regression (HUB), Least Angle Regression (LAR), Polynomial Regression (PLN), and Ridge Regressor (RR) based models were very poor. The aircraft bumpiness prediction models performed best over the approach area of ZBDT (airport in Datong), ZULS (airport in Lhasa), ZPPP (airport in Kunming), and ZLQY (airport in Qingyang). The model performed best in predicting the ZLLL-ZBDT air route (flight routes for Lanzhou to Datong) with different prediction times.
Heteroplasmy and Individual Mitogene Pools: Characteristics and Potential Roles in Ecological Studies
Authors: Wang Wenhui , Lin Lijun , Zhang Qi , Yang Jincheng , Kamili Elizabeth , Chu Jianing , Li Xiaoda , Yang Shuhui , Xu Yanchun
Published: November 2023

The mitochondrial genome (mitogenome or mtDNA), the extrachromosomal genome, is a multicopy circular DNA with high mutation rates due to replication and repair errors. A mitochondrion, cell, tissue, organ, or an individual body may hold multiple variants, both inherited and developed over a lifetime, which make up individual mitogene pools. This phenomenon is also called mtDNA heteroplasmy. MtDNA variants influence cellular and tissular functions and are consequently subjected to selection. Although it has long been recognized that only inheritable germline heteroplasmies have evolutionary significance, non-inheritable somatic heteroplasmies have been overlooked since they directly affect individual fitness and thus indirectly affect the fate of heritable germline variants. This review focuses on the characteristics, dynamics, and functions of mtDNA heteroplasmy and proposes the concept of individual mitogene pools to discuss individual genetic diversity from multiple angles. We provide a unique perspective on the relationship between individual genetic diversity and heritable genetic diversity and guide how the individual mitogene pool with novel genetic markers can be applied to ecological research.
Portable Infrared-Based Glucometer Reinforced with Fuzzy Logic
Authors: Nazha Hasan Mhd , Darwich Mhd Ayham , Ismaiel Ebrahim , Shahen Anas , Nasser Tamim , Assaad Maher , Juhre Daniel
Published: November 2023

Diabetes mellitus (DM) is a chronic metabolic condition characterized by high blood glucose levels owing to decreased insulin production or sensitivity. Current diagnostic approaches for gestational diabetes entail intrusive blood tests, which are painful and impractical for regular monitoring. Additionally, typical blood glucose monitoring systems are restricted in their measurement frequency and need finger pricks for blood samples. This research study focuses on the development of a non-invasive, real-time glucose monitoring method based on the detection of glucose in human tears and finger blood using mid-infrared (IR) spectroscopy. The proposed solution combines a fuzzy logic-based calibration mechanism with an IR sensor and Arduino controller. This calibration technique increases the accuracy of non-invasive glucose testing based on MID absorbance in fingertips and human tears. The data demonstrate that our device has high accuracy and reliability, with an error rate of less than 3%, according to the EGA. Out of 360 measurements, 97.5% fell into zone A, 2.2% into zone B, and 0.3% into zone C of the Clarke Error Grid. This suggests that our device can give clinically precise and acceptable estimates of blood glucose levels without inflicting any harm or discomfort on the user.
Fungicide Resistance in Botrytis spp. and Regional Strategies for Its Management in Northern European Strawberry Production
Authors: Weber Roland W. S. , Petridis Antonios
Published: November 2023

Grey mould, caused by Botrytis cinerea and other Botrytis spp., is a major cause of fruit rot in strawberries and other fruit crops worldwide. Repeated fungicide applications are essential in order to secure harvests. However, resistance to all currently registered single-site fungicides is widespread. The rising importance of strains with multiple resistance to most or all fungicides is of particular concern. These strains may be introduced into fields via contaminated nursery plants and/or by immigration from adjacent plots. On the basis of research conducted in northern German and Danish strawberry production, a concept to manage fungicide resistance under northern European conditions has been developed and put into regional strawberry production practice. This principally includes the testing of nursery plants for fungicide-resistant Botrytis strains prior to planting; the restricted and specific use of fungicides at flowering in the production fields, taking account of the resistance spectrum within the local Botrytis population; and crop sanitation measures such as the removal of rotting fruits at the beginning of harvest. Further options such as protected cultivation, reduced fertilisation and biological control are also discussed. The practical implementation of such a strategy in northern Germany and Denmark has been shown to reduce the occurrence of multi-resistant strains to a tolerable steady-state level.
Bridging the Divide: Brain and Behavior in Developmental Language Disorder
Authors: Abbott Noelle , Love Tracy
Published: November 2023

Developmental language disorder (DLD) is a heterogenous neurodevelopmental disorder that affects a child’s ability to comprehend and/or produce spoken and/or written language, yet it cannot be attributed to hearing loss or overt neurological damage. It is widely believed that some combination of genetic, biological, and environmental factors influences brain and language development in this population, but it has been difficult to bridge theoretical accounts of DLD with neuroimaging findings, due to heterogeneity in language impairment profiles across individuals and inconsistent neuroimaging findings. Therefore, the purpose of this overview is two-fold: (1) to summarize the neuroimaging literature (while drawing on findings from other language-impaired populations, where appropriate); and (2) to briefly review the theoretical accounts of language impairment patterns in DLD, with the goal of bridging the disparate findings. As will be demonstrated with this overview, the current state of the field suggests that children with DLD have atypical brain volume, laterality, and activation/connectivity patterns in key language regions that likely contribute to language difficulties. However, the precise nature of these differences and the underlying neural mechanisms contributing to them remain an open area of investigation.