bluuebunny/crossref_metadata_2025 huggingface dataset:
First direct observations of interplanetary shock impact angle effects on actual geomagnetically induced currents: The case of the Finnish natural gas pipeline system
Authors: Oliveira Denny M. , Zesta Eftyhia , Vidal-Luengo Sergio
Published: July 2024

The impact of interplanetary (IP) shocks on the Earth’s magnetosphere can greatly disturb the geomagnetic field and electric currents in the magnetosphere-ionosphere system. At high latitudes, the current systems most affected by the shocks are the auroral electrojet currents. These currents then generate ground geomagnetically induced currents that couple with and are highly detrimental to ground artificial conductors including power transmission lines, oil/gas pipelines, railways, and submarine cables. Recent research has shown that the shock impact angle, the angle the shock normal vector performs with the Sun-Earth line, plays a major role in controlling the subsequent geomagnetic activity. More specifically, due to more symmetric magnetospheric compressions, nearly frontal shocks are usually more geoeffective than highly inclined shocks. In this study, we utilize a subset (332 events) of a shock list with more than 600 events to investigate, for the first time, shock impact angle effects on the subsequent GICs right after shock impact (compression effects) and several minutes after shock impact (substorm-like effects). We use GIC recordings from the Finnish natural gas pipeline performed near the Mäntsälä compression station in southern Finland. We find that GIC peaks (> 5 A) occurring after shock impacts are mostly caused by nearly frontal shocks and occur in the post-noon/dusk magnetic local time sector. These GIC peaks are presumably triggered by partial ring current intensifications in the dusk sector. On the other hand, more intense GIC peaks (> 20 A) generally occur several minutes after shock impacts and are located around the magnetic midnight terminator. These GIC peaks are most likely caused by intense energetic particle injections from the magnetotail which frequently occur during substorms. The results of this work are relevant to studies aiming at predicting GICs following solar wind driving under different levels of asymmetric solar wind forcing.
How strenuous is esports? Perceived physical exertion and physical state during competitive video gaming
Authors: Tholl Chuck , Soffner Markus , Froböse Ingo
Published: July 2024

Introduction

Esports or competitive video gaming is a rapidly growing sector and an integral part of today's (youth) culture. Esports athletes are exposed to a variety of burdens, that can potentially impact an athlete's health and performance. Therefore, it is important that esports athletes are aware of (physical) burden and exertion associated with esports. For this purpose, a study was conducted to evaluate the influence of competitive video gaming on the perceived physical exertion and the perceived physical state (PEPS).

Methods

Thirty-two healthy male esports athletes participated in two competitive video gaming sessions lasting 90–120 min, interrupted by a 10-minute passive sitting break. Repeated measures of perceived physical exertion (Borg Categorial Ratio-10 scale) and perceived physical state were recorded before, during, and after each video game session. Repeated measures ANOVA and Friedman's test were used for statistical analysis.

Results

The results showed a significant difference in all dimensions of the PEPS (p < 0.05) as well as in Borg scale (p < 0.001). Post-hoc tests revealed significant increases in Borg scale between baseline measurements (T0: 1.0 ± 1.0) and after the first competitive video gaming session (T1: 2.4 ± 1.3, p < 0.001), as well as after the second competitive video gaming session (T3: 3.0 ± 1.7, p < 0.001). Furthermore, there was a significant reduction in perceived exertion between the measurement time after the first competitive video gaming session (T1) and the break (T2: 1.3 ± 1.2, p < 0.001). The PEPS dimensions activation, trained, and mobility showed similar significant changes in post-hoc analysis.

Discussion

The results indicate that the perceived physical burden significantly increases during esports participation. As the duration of competitive video gaming extends, the perceived physical state decreases and perceived physical exertion increases. A passive break between two video game sessions can at least partially restore physical exertion and physical state. However, this break neither returns the scores to their baseline levels nor prevents a further decline in scores during the second video game session. Over time and with a lack of observation, this could result in health and performance limitations.
Innovation in isolation: diffusion of local foods purchasing and online shopping methods during the pandemic
Authors: Yang Cheng-Xian , Baker Lauri M. , Mattox Anissa M. , Peterson Hikaru H.
Published: July 2024

Introduction

The COVID-19 pandemic caused mainstream food supply chain disruptions, increased food security concerns, and impacted agri-food production and distribution systems. Short food supply chains provided consumers with an alternative method to acquire food outside conventional food supply chains. In this paper, innovation was seen as a solution to external challenges or problems in global food supply chains during a pandemic crisis. The solution was analyzed in the context of the United States and changes in the consumers’ behavior and purchasing patterns in the direction of more accepting short supply chains, which led to the successful overcoming of crisis or adaptation of consumers to crisis circumstances.

Methods

The Diffusion of Innovations was selected as the theoretical framework. Data were collected from 1,002 American adults from July 13 to August 18, 2021, through an online survey.

Results and discussion

Results showed that consumers with higher educational attainment and financial status, from non-rural areas, and with more conservative viewpoints had higher innovation adoption levels, and they were more likely to embrace short food supply chains as an alternative during disruptions to conventional supply chains. Recommendations provide strategies to increase the use of short supply chains during the crisis to better meet the needs of consumers in the food system and improve marketing and communication efforts. Marketing and communication initiatives should engage these food innovators as opinion leaders to increase the adoption of short food supply chains to stabilize food supply in preparation for future crises.
Review of the slaughter wastes and the meat by-products recycling opportunities
Authors: Alibekov Ravshanbek S. , Alibekova Zaripa I. , Bakhtybekova Asem R. , Taip Farah S. , Urazbayeva Klara A. , Kobzhasarova Ziba I.
Published: July 2024

In the ancient times, the Kazakhstan population were considered as nomadic people, where a cult of all types of cattle breeding had a leading position. However, currently the processing approaches of livestock slaughter wastes and secondary meat raw materials are weakly developed. The presented review of waste-free technologies considers the utilization processes of following: carcasses, skins, bones, meat scraps, blood, adipose tissue, horns, feet, hooves, and internal organs. These substances are an important source of animal protein, collagen, bioactive peptides, blood plasma, minerals, and fats that can be applied in various industries: food, feed, medical, and technological. When slaughtering livestock, meat on bones makes up almost half of the total weight of livestock, yet the remaining half contains offal and inedible raw materials. Blood consists of: erythrocytes, leukocytes, platelets, and plasma. Animal bones have mostly proteins (30–50%) and lipids (13–20%) from bone tissues. Tendons, bones and skins contain a large amount of collagen. Animal fat and adipose tissue have 54.9% saturated acids, 40.9% unsaturated fatty acids and 4.2% polyunsaturated fatty acids. Bioactive peptides from collagen derivatives contain from 2 to 20 amino acids and have various biological (antihypertensive, antioxidant, and antimicrobial) activity. This review considers a world current status, modern prospects and opportunities in the slaughter wastes and the meat by-products recycling technologies. Overview of existing approaches for waste processing with the subsequent use of the final product in the food industry, the production of feed, medicines and technical products is considered. The complete processing within the slaughtering livestock and the secondary meat raw materials allows to expand the wide-range products with a low prime cost, thereby promoting to the sustainable development of agroecology by applying the waste hierarchy: Reducing, Reusing, and Recycling.
Research Progress in the Establishment of Sterile Hosts and Their Usage in Conservation of Poultry Genetic Resources
Authors: Du Hongfeng , Li Yunlei , Ni Aixin , Liu Shengjun , Chen Jilan , Sun Yanyan
Published: July 2024

Many local chicken breeds are rapidly declining and even facing extinction due to a variety of factors such as indiscriminate crossbreeding, climate fluctuations, epidemic outbreak, and environmental changes. Developing effective preservation strategies is important to address this situation. The special reproductive characteristics and gamete morphology of chickens pose challenges for preserving genetic heritage through the cryopreservation of genetic materials. Currently, gonad and primordial germ-cell cryopreservation and transplantation are the most promising approaches, especially for the genetic information in the W chromosome of female birds. The study of establishing sterile recipients is crucial for increasing the efficiency of the colonization of transplanted donor tissues and cells. Several classical methods, including ovariectomy and testectomy, busulfan, and irradiation, have been employed to deplete endogenous germ cells in recipient males before transplantation. These methods rely on the toxicity of chemical reagents and physical stimulation to kill germ cells. Recent advances in gene-editing technology have introduced sterile hosts via the knocking out of genes relevant to germ cells’ development. This review explores state-of-the-art technologies for preparing infertile avian recipients (mainly chickens) and aims to provide guidance for the conservation of poultry genetic material and breed restoration.
Open-Set Sheep Face Recognition in Multi-View Based on Li-SheepFaceNet
Authors: Li Jianquan , Yang Ying , Liu Gang , Ning Yuanlin , Song Ping
Published: July 2024

Deep learning-based sheep face recognition improves the efficiency and effectiveness of individual sheep recognition and provides technical support for the development of intelligent livestock farming. However, frequent changes within the flock and variations in facial features in different views significantly affect the practical application of sheep face recognition. In this study, we proposed the Li-SheepFaceNet, a method for open-set sheep face recognition in multi-view. Specifically, we employed the Seesaw block to construct a lightweight model called SheepFaceNet, which significantly improves both performance and efficiency. To enhance the convergence and performance of low-dimensional embedded feature learning, we used Li-ArcFace as the loss function. The Li-SheepFaceNet achieves an open-set recognition accuracy of 96.13% on a self-built dataset containing 3801 multi-view face images of 212 Ujumqin sheep, which surpasses other open-set sheep face recognition methods. To evaluate the robustness and generalization of our approach, we conducted performance testing on a publicly available dataset, achieving a recognition accuracy of 93.33%. Deploying Li-SheepFaceNet on an open-set sheep face recognition system enables the rapid and accurate identification of individual sheep, thereby accelerating the development of intelligent sheep farming.
Inversion of Soybean Net Photosynthetic Rate Based on UAV Multi-Source Remote Sensing and Machine Learning
Authors: Lu Zhen , Yao Wenbo , Pei Shuangkang , Lu Yuwei , Liang Heng , Xu Dong , Li Haiyan , Yu Lejun , Zhou Yonggang , Liu Qian
Published: July 2024

Net photosynthetic rate (Pn) is a common indicator used to measure the efficiency of photosynthesis and growth conditions of plants. In this study, soybeans under different moisture gradients were selected as the research objects. Fourteen vegetation indices (VIS) and five canopy structure characteristics (CSC) (plant height (PH), volume (V), canopy cover (CC), canopy length (L), and canopy width (W)) were obtained using an unmanned aerial vehicle (UAV) equipped with three different sensors (visible, multispectral, and LiDAR) at five growth stages of soybeans. Soybean Pn was simultaneously measured manually in the field. The variability of soybean Pn under different conditions and the trend change of CSC under different moisture gradients were analysed. VIS, CSC, and their combinations were used as input features, and four machine learning algorithms (multiple linear regression, random forest, Extreme gradient-boosting tree regression, and ridge regression) were used to perform soybean Pn inversion. The results showed that, compared with the inversion model using VIS or CSC as features alone, the inversion model using the combination of VIS and CSC features showed a significant improvement in the inversion accuracy at all five stages. The highest accuracy (R2 = 0.86, RMSE = 1.73 µmol m−2 s−1, RPD = 2.63) was achieved 63 days after sowing (DAS63).
Effects of Drip Irrigation Flow Rate and Layout Designs on Soil Salt Leaching and Cotton Growth under Limited Irrigation
Authors: Chang Yurong , Li Dongwei , He Shuai
Published: July 2024

Optimal drip irrigation management in shallow groundwater areas needs to clarify the effects of flow rate and layout designs on the soil moisture, salt distribution, cotton root length density, plant height, leaf area, and yield. In this study, a one-year field experiment was conducted from April to October 2018 in the fifth company of the 16th Regiment in Alar City, Xinjiang, to investigate the effects of various drip flow rates and layout designs of cotton growth. Two drip flow rates (2.8 and 5.6 L·h−1) and two layout designs (one film, two drip tapes, and six rows; one film, three drip tapes, and six rows) were applied to explore the optimal combination, resulting in a total of four treatments that were irrigated three times in the whole growth period. Soil moisture, salt distribution, cotton root length density, plant height, and leaf area were measured. The main results were as follows: (1) Under the same layout designs, the soil moisture content was higher and the soil salinity was lower when the drip flow rate was 5.6 L·h−1, and the cotton root length density, plant height, leaf area, and yield were significantly higher than that of 2.8 L·h−1. (2) Under the same drip flow rate, the soil desalination rate, cotton growth indexes, and yield under the three-tapes treatment were significantly higher than the values of the two-tapes treatment. The actual yield of treatment D was 21.56%, 19.23%, and 11.71% higher than that of treatments A, B, and C, respectively. (3) The crop evapotranspiration of cotton during the two irrigation cycles showed an increasing trend, and the groundwater contribution showed a smaller and then increasing trend. Overall, the combination of three tapes and a drip flow rate of 5.6 L·h−1 had the highest cotton yield and net income, which were 6211.36 kg·hm−2 and 4820.21 kg·hm−2 for the theoretical and actual yields. The results of this study can provide a reference for the management of limited irrigation leaching soil salinity and cotton cultivation in shallow groundwater areas.
An Integrated Numerical Study of CO2 Storage in Carbonate Gas Reservoirs with Chemical Interaction between CO2, Brine, and Carbonate Rock Matrix
Authors: Yao Jiangyuan , Chen Zhuoheng , Jiang Chunqing , Peng Xiaolong
Published: July 2024

In light of the burgeoning interest in mitigating anthropogenic CO2 emissions, carbonate reservoirs have emerged as promising sequestration sites due to their substantial storage potentials. However, the complexity of CO2 storage in carbonate reservoirs exceeds that in conventional sandstone reservoirs, predominantly due to the rapid interactions occurring between the injected CO2, brine, and carbonate rock matrix. In this study, a numerical model integrated with the chemical CO2–brine–rock matrix interaction was developed to analyze the carbonate rock dissolution process and the physical property variations of different carbonate gas reservoirs during the CO2 injection and sequestration process. More specifically, a total of twenty scenarios were simulated to examine the effects of lithology, pore size, pore–throat structures, and CO2 injection rate on carbonate rock matrix dissolution and reservoir property variation. Calcite is significantly easier and quicker to react with CO2-solvated brine than dolomite; as a result, limestones exhibit an expedited rock dissolution and pore volume increase, along with a slower pressure buildup in comparison to dolomites. Also, the carbonate reservoir with a smaller pore size has a higher rock dissolution rate than one with a larger pore size. Furthermore, the simulation results show injected CO2 can modify the pore-dominant carbonate reservoir to a more pronounced extent than the fracture-dominant carbonate reservoir. Lastly, the carbonate rock dissolution is more obvious at a lower CO2 injection rate. The insights derived from this research aid evaluations related to CO2 injectivity, storage capacity, and reservoir integrity, thereby paving the way for environmentally and structurally sound carbon sequestration strategies.
Domain Decomposition and Model Order Reduction for Electromagnetic Field Simulations in Carbon Fiber Composite Materials
Authors: Lou Suyang , Pierquin Antoine , Wasselynck Guillaume , Trichet Didier , Bracikowski Nicolas
Published: July 2024

The computation of the electric field in composite materials at the microscopic scale results in an immense number of degrees of freedom. Consequently, this often leads to prohibitively long computation times and extensive memory requirements, making direct computation impractical. In this study, one employs an innovative approach that integrates domain decomposition and model order reduction to retain local information while significantly reducing computation time. Domain decomposition allows for the division of the computational domain into smaller, more manageable subdomains, enabling parallel processing and reducing the overall complexity of the problem. Model order reduction further enhances this by approximating the solution in a lower-dimensional subspace, thereby minimising the number of unknown variables that need to be computed. Comparative analysis between the results obtained from the reduced model and those from direct resolution demonstrates that our method not only reduces computation time but also maintains accuracy. The new method effectively captures the essential characteristics of the electric field distribution in composite materials, ensuring that the local phenomena are accurately represented. This study provides a contribution to the field of computational electromagnetics by presenting a feasible solution to the challenges posed by the high computational demands of simulating composite materials at the microscopic scale. The proposed methodology offers a promising direction for future research and practical applications, enabling more efficient and accurate simulations of complex material systems.
Analysis, Design, and Experimental Validation of a High-Isolation, Low-Cross-Polarization Antenna Array Demonstrator for Software-Defined-Radar Applications
Authors: Ricciardella Nicholas , Fuscaldo Walter , Mattei Tito , Fiorello Anna Maria , Infante Leopoldo , Galli Alessandro
Published: July 2024

In a software-defined radar (SDR) system, most of the signal processing usually implemented in hardware is implemented by software, thus allowing for higher flexibility and modularity compared to conventional radar systems. However, the majority of SDR demonstrators and proofs of concept reported in the open literature so far have been based on simple antenna systems. As a result, the full potentialities of an SDR approach have not been completely exploited yet. In this work, we propose a flexible antenna module to be integrated into an active electronically scanning array (AESA) with controlled sidelobe level over a wide angular range, exhibiting polarization reconfigurability with a low cross-polarization level and high isolation. For this purpose, analytical and numerically efficient techniques for the synthesis of the aperture distribution and the correct evaluation of the radiating features (e.g., beamwidth, pointing angle, sidelobe levels, etc.) are presented in order to grant real-time control of the digital beamforming network. A sub-array module demonstrator is fabricated and measured to corroborate the concept.
Machine Learning for Evaluating Hospital Mobility: An Italian Case Study
Authors: Santamato Vito , Tricase Caterina , Faccilongo Nicola , Iacoviello Massimo , Pange Jenny , Marengo Agostino
Published: July 2024

This study delves into hospital mobility within the Italian regions of Apulia and Emilia-Romagna, interpreting it as an indicator of perceived service quality. Utilizing logistic regression alongside other machine learning techniques, we analyze the impact of structural, operational, and clinical variables on patient perceptions of quality, thus influencing their healthcare choices. The analysis of mobility trends has uncovered significant regional differences, emphasizing how the regional context shapes perceived service quality. To further enhance the analysis, SHAP (SHapley Additive exPlanations) values have been integrated into the logistic regression model. These values quantify the specific contributions of each variable to the perceived quality of service, significantly improving the interpretability and fairness of evaluations. A methodological innovation of this study is the use of these SHAP impact scores as weights in the data envelopment analysis (DEA), facilitating a comparative efficiency analysis of healthcare facilities that is both weighted and normative. The combination of logistic regression and SHAP-weighted DEA provides a deeper understanding of perceived quality dynamics and offers essential insights for optimizing the distribution of healthcare resources. This approach underscores the importance of data-driven strategies to develop more equitable, efficient, and patient-centered healthcare systems. This research significantly contributes to the understanding of perceived quality dynamics within the healthcare context and promotes further investigations to enhance service accessibility and quality, leveraging machine learning as a tool to increase the efficiency of healthcare services across diverse regional settings. These findings are pivotal for policymakers and healthcare system managers aiming to reduce regional disparities and promote a more responsive and personalized healthcare service.
Generative Aspect Sentiment Quad Prediction with Self-Inference Template
Authors: Qin Yashi , Lv Shu
Published: July 2024

Aspect Sentiment Quad Prediction is a research topic of paramount significance and complexity within the Aspect-Based Sentiment Analysis task. Leveraging the generative paradigm of the T5 model, we achieve end-to-end extraction of aspect sentiment elements by paraphrasing the original text into sentences predefined by templates. Current research predominantly confines templates to single sentences or directly concatenates sentiment elements using a few symbols, limiting the model’s reasoning opportunities. In this work, we introduce a Self-Inference Template (SIT) to guide the model in thoughtful reasoning, facilitating a step-by-step inference generation process. This approach enables the model to more accurately identify aspect sentiment elements and their interdependencies. Experimental results demonstrate a significant improvement in quadruplet prediction performance under constant time costs, effectively mitigating overfitting issues caused by limited data volume to some extent.
One Method for Predicting Satellite Communication Terminal Service Demands Based on Artificial Intelligence Algorithms
Authors: Zeng Lingchao , Zhang Cheng , Qin Pengfei , Zhou Yejun , Cai Yaxing
Published: July 2024

This paper presents a traffic demand prediction method based on deep learning algorithms, aiming to address the dynamic traffic demands in satellite communication and enhance resource management efficiency. Integrating Seq2Seq and LSTM networks, the method improves prediction accuracy and applicability, especially for mobile terminals such as aviation and maritime ones. Unlike traditional approaches, it does not require extensive statistical data and can be generalized to real-world systems, providing stable long-term traffic demand predictions. This study utilizes real-world flight data mapped to corresponding satellite beams, allowing the precise prediction of beam-specific traffic demands. The results show that aggregating historical demand data for beams with similar trends achieves an average predictive Mean Squared Error (MSE) of 0.0007 and a maximum MSE fluctuation of 0.014, significantly outperforming predictions based on average values in terms of stability and accuracy. This novel solution for resource management in satellite communication ensures efficient and accurate long-term traffic demand predictions.
Diclofenac Degradation in Aqueous Solution Using Electron Beam Irradiation and Combined with Nanobubbling
Authors: Sun Yongxia , Madureira Joana , Justino Gonçalo C. , Cabo Verde Sandra , Chmielewska-Śmietanko Dagmara , Sudlitz Marcin , Bulka Sylwester , Chajduk Ewelina , Mróz Andrzej , Wang Shizong , Wang Jianlong
Published: July 2024

Diclofenac (DCF) degradation in aqueous solution under electron beam (EB) irradiation after nanobubbling treatment was studied and compared with treatments using nanobubbling or EB irradiation alone. It was found that the removal efficiency of DCF increased by increasing the adsorbed dose, and it depended on the initial concentration of DCF in solution, being higher for the lower concentrations. Furthermore, when using the nanobubbling treatment alone, about 16% of the DCF was removed from the aqueous solution due to the OH radicals generated during the process. On the other hand, using EB treatment at 0.5 kGy, the degradation of DCF increased from 36% to 51% when adding a nanobubbling pretreatment before the EB radiation. At higher doses (5 kGy), the degradation of DCF was 96% using EB radiation and 99% using nanobubbling before EB radiation, indicating that the nanobubbling effect was not synergistic. With an increase in the adsorbed doses, EB radiation seemed to play a more important role on the degradation of DCF, probably due to the reactive species generated. Moreover, the solutions treated with nanobubbling and EB radiation presented higher COD values and radiolytic by-products with aromatic rings with chlorine. This work can support the development of innovative strategies to treat municipal wastewaters using ionizing radiation technologies.
A Novel Method for Wheat Spike Phenotyping Based on Instance Segmentation and Classification
Authors: Niu Ziang , Liang Ning , He Yiyin , Xu Chengjia , Sun Sashuang , Zhou Zhenjiang , Qiu Zhengjun
Published: July 2024

The phenotypic analysis of wheat spikes plays an important role in wheat growth management, plant breeding, and yield estimation. However, the dense and tight arrangement of spikelets and grains on the spikes makes the phenotyping more challenging. This study proposed a rapid and accurate image-based method for in-field wheat spike phenotyping consisting of three steps: wheat spikelet segmentation, grain number classification, and total grain number counting. Wheat samples ranging from the early filling period to the mature period were involved in the study, including three varieties: Zhengmai 618, Yannong 19, and Sumai 8. In the first step, the in-field collected images of wheat spikes were optimized by perspective transformation, augmentation, and size reduction. The YOLOv8-seg instance segmentation model was used to segment spikelets from wheat spike images. In the second step, the number of grains in each spikelet was classified by a machine learning model like the Support Vector Machine (SVM) model, utilizing 52 image features extracted for each spikelet, involving shape, color, and texture features as the input. Finally, the total number of grains on each wheat spike was counted by adding the number of grains in the corresponding spikelets. The results showed that the YOLOv8-seg model achieved excellent segmentation performance, with an average precision (AP) @[0.50:0.95] and accuracy (A) of 0.858 and 100%. Meanwhile, the SVM model had good classification performance for the number of grains in spikelets, and the accuracy, precision, recall, and F1 score reached 0.855, 0.860, 0.865, and 0.863, respectively. Mean absolute error (MAE) and mean absolute percentage error (MAPE) were as low as 1.04 and 5% when counting the total number of grains in the frontal view wheat spike images. The proposed method meets the practical application requirements of obtaining trait parameters of wheat spikes and contributes to intelligent and non-destructive spike phenotyping.
Diffusion on PCA-UMAP Manifold: The Impact of Data Structure Preservation to Denoise High-Dimensional Single-Cell RNA Sequencing Data
Authors: Cristian Padron-Manrique , Aarón Vázquez-Jiménez , Armando Esquivel-Hernandez Diego , Estrella Martinez-Lopez Yoscelina , Daniel Neri-Rosario , David Giron-Villalobos , Edgar Mixcoha , Paul Sánchez-Castañeda Jean , Osbaldo Resendis-Antonio
Published: July 2024

Single-cell transcriptomics (scRNA-seq) is revolutionizing biological research, yet it faces challenges such as inefficient transcript capture and noise. To address these challenges, methods like neighbor averaging or graph diffusion are used. These methods often rely on k-nearest neighbor graphs from low-dimensional manifolds. However, scRNA-seq data suffer from the ‘curse of dimensionality’, leading to the over-smoothing of data when using imputation methods. To overcome this, sc-PHENIX employs a PCA-UMAP diffusion method, which enhances the preservation of data structures and allows for a refined use of PCA dimensions and diffusion parameters (e.g., k-nearest neighbors, exponentiation of the Markov matrix) to minimize noise introduction. This approach enables a more accurate construction of the exponentiated Markov matrix (cell neighborhood graph), surpassing methods like MAGIC. sc-PHENIX significantly mitigates over-smoothing, as validated through various scRNA-seq datasets, demonstrating improved cell phenotype representation. Applied to a multicellular tumor spheroid dataset, sc-PHENIX identified known extreme phenotype states, showcasing its effectiveness. sc-PHENIX is open-source and available for use and modification.
Effects of Organic Xenobiotics on Tenebrio molitor Larvae and Their Parasite Gregarina polymorpha
Authors: Lazurska Viktoriia , Brygadyrenko Viktor
Published: July 2024

Environmental contamination with xenobiotics affects organisms and the symbiotic relations between them. A convenient object to study relationships between parasites and their hosts is the host–parasite system “Tenebrio molitor Linnaeus, 1758 (Coleoptera, Tenebrionidae)—Gregarina polymorpha (Hammerschmidt, 1838) Stein, 1848 (Eugregarinorida, Gregarinidae)”. For this experiment, we took 390 T. molitor larvae and 24 organic compounds. Groups of mealworms, 15 in each, were subjected to those compounds for 10 days. Then, we recorded the vitality of both the larvae of T. molitor and G. polymorpha. To assess how G. polymorpha had affected the hosts’ wellbeing, we looked for changes in the larvae’s body mass and compared them to the number of gregarines in their intestines. The vitality of the larvae was inhibited by cyclopentanol and 2-naphthol. The intensity of gregarine invasion was reduced by diphenyl ether, benzyl alcohol, catechol, and 3-aminobenzoic acid. No effect on the number of gregarines was produced by 3,4,5-trihydroxybenzoic acid, cyclohexanemethanol, phenol, benzalkonium chloride, maleic anhydride, cyclohexanol, resorcin, benzoic acid, 2-methylfuran, terpinen-4-ol, 1-phenylethylamine, dibutyl phthalate, 3-furancarboxylic acid, 5-methyl furfural, 6-aminohexanoic acid, succinic anhydride, o-xylene, and benzaldehyde. In the infected T. molitor individuals, the mean number of G. polymorpha equaled 45 specimens per host. The groups of smaller mealworms had fewer gregarines. Positive correlation was seen between growth rates of T. molitor larvae and the intensity of invasion by gregarines.
Using Stable Isotope Techniques to Analyze the Trophic Relationship between Argentine Hake (Merluccius hubbsi) and Anisakidae
Authors: Shu Yue , Wu Feiyu , Fang Zhou
Published: July 2024

The Argentine hake (Merluccius hubbsi) is a vital fishery species in the Southwest Atlantic, recognized for its substantial economic importance. Previous studies have identified Anisakidae larvae as common parasites of M. hubbsi. However, the nutritional relationships between these parasites and their host remain poorly understood. This study employs stable isotope techniques to investigate the specific nutritional relationships between Anisakidae larvae and different tissues of M. hubbsi. The findings reveal notable differences in δ13C and δ15N compositions between the parasites and their host. The lower δ13C values in parasites compared to host tissues indicate the utilization of different carbon sources. The δ15N values of the parasites partially overlap with those of the host’s stomach, indicating that the parasites primarily derive nutrients from the host’s stomach. Nutritional niche indicators show that parasites have a broad carbon range (CR) and nitrogen range (NR), suggesting a high diversity in nutritional sources. The trophic discrimination factor (ΔTDF), which represents the difference in stable isotope values between host tissues and parasites, was analyzed for both δ13C and δ15N. The ΔTDFδ13C between the host liver and the parasites showed the greatest variation, indicating a strong dependence of the parasites on the liver’s carbon sources. In contrast, variations in ΔTDFδ15N between host tissues and parasites were minimal. Analyzing ΔTDF across different stages of gonadal maturity in the host fish indicates that, as the gonads of the host fish mature, ΔTDFδ13C between host tissues and parasites significantly decreases (p < 0.01). The Kruskal–Wallis test showed significant differences in ΔTDFδ13C values among different parasite infection levels in muscle, liver, and stomach tissues, while no significant differences were found for ΔTDFδ15N values. These findings offer valuable insights into the nutritional relationships between parasites and hosts, aiding in a better understanding of the growth conditions and habitats of M. hubbsi.
Conservation of Socio-Religious Historic Buildings: A Case Study of Shah Yousuf Gardez Shrine
Authors: Imtiaz Sunera , Arif Sabahat , Nawaz Ahsan , Shah Syyed Adnan Raheel
Published: July 2024

Historic buildings are considered assets for generations. The use of 3D interactive models is an excellent way to document such historic cultural heritage. Such buildings include socio-religious buildings, such as shrines and religious monuments. Digital technologies such as photogrammetry and laser scanning play a pivotal role in monitoring and safeguarding precious shrine cultural heritage. These advanced techniques allow the capture of details and accurate 3D representations of cultural artifacts, architectural structures, and even entire shrines. This study deals with research related to the conservation of the selected historic shrine of Shah Yousaf Gardez. A laser scanner methodology was used to produce a high-level detail interactive model translated into a heritage building information modeling (HBIM) prototype. This HBIM model has been designed to maintain the historical details of the shrine, especially geometric features, artwork present on the surface, and condition of structural as well as non-structural components. Data analysis of defects in structural and non-structural components was also analyzed in the study. This study was conducted fort the first time for a shrine case study. It will not only help to document and preserve historic buildings and cultural heritage but also monitor potential degradation or damage over time. Using this technology, scheduled conservation and restoration efforts ensuring the long-term preservation of these invaluable treasures can be adopted.
The Clinical Utility of the NETest in Patients with Small Intestinal Neuroendocrine Neoplasms (Si-NENs): A “Real-Life” Study
Authors: Gertner Julian , Tsoli Marina , Hayes Aimee R. , O’Mahony Luke Furtado , Laskaratos Faidon-Marios , Glover Thomas , Karia Priyesh , Butt Mohsin F. , Eastwood Oliver , Mandair Dalvinder , Caplin Martyn , Toumpanakis Christos
Published: July 2024

Current biomarkers do not adequately predict the behaviour of neuroendocrine neoplasms (NENs). This study assessed the NETest, a multianalyte blood biomarker, in patients with small intestinal NENs (Si-NENs). We studied two patient groups: Group 1: metastatic Si-NENs (n = 102) and Group 2: post-operatively disease-free according to 68Ga-DOTATATE PET (n = 16). NETest scores were ≤20% (normal), 21–40% (low), 41–79% (intermediate), or ≥80% (high). Overall survival (OS) and progression-free survival (PFS) were assessed using the Kaplan–Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards model. In Group 1, the median NETest score was 40% (IQR: 33.3–46.7%). The NETest value (HR: 1.032, 95% CI: 1.003–1.062, p = 0.033) and high-risk NETest category (HR: 10.5, 95% CI: 1.35–81.7, p = 0.025) were independent predictors of PFS, along with presence of lung metastases, CgA levels > 10 × ULN, and tumour growth rate (TGR). Independent predictors of OS were the NETest value (HR: 1.035, 95% CI: 1.005–1.066, p = 0.024) and high-risk NETest category (HR: 15.2, 95% CI: 1.52–151, p = 0.02), along with presence of lung metastases and CgA levels > 10 × ULN. In Group 2, ROC analysis identified an AUC of 0.909 (95% CI: 0.75–0.100) for prediction of local or metastatic recurrence. Blood NETest scores were associated with PFS and OS in patients with metastatic Si-NENs, along with TGR, CgA > 10 × ULN, and presence of lung metastases.
Astrocytes in Amyloid Generation and Alcohol Metabolism: Implications of Alcohol Use in Neurological Disorder(s)
Authors: Kumar Mohit , Swanson Natalie , Ray Sudipta , Buch Shilpa , Saraswathi Viswanathan , Sil Susmita
Published: July 2024

As per the National Survey on Drug Use and Health, 10.5% of Americans aged 12 years and older are suffering from alcohol use disorder, with a wide range of neurological disorders. Alcohol-mediated neurological disorders can be linked to Alzheimer’s-like pathology, which has not been well studied. We hypothesize that alcohol exposure can induce astrocytic amyloidosis, which can be corroborated by the neurological disorders observed in alcohol use disorder. In this study, we demonstrated that the exposure of astrocytes to ethanol resulted in an increase in Alzheimer’s disease markers—the amyloid precursor protein, Aβ1-42, and the β-site-cleaving enzyme; an oxidative stress marker—4HNE; proinflammatory cytokines—TNF-α, IL1β, and IL6; lncRNA BACE1-AS; and alcohol-metabolizing enzymes—alcohol dehydrogenase, aldehyde dehydrogenase-2, and cytochrome P450 2E1. A gene-silencing approach confirmed the regulatory role of lncRNA BACE1-AS in amyloid generation, alcohol metabolism, and neuroinflammation. This report is the first to suggest the involvement of lncRNA BACE1-AS in alcohol-induced astrocytic amyloid generation and alcohol metabolism. These findings will aid in developing therapies targeting astrocyte-mediated neurological disorders and cognitive deficits in alcohol users.
Structural Analysis of the ESCRT-III Regulator Lethal(2) Giant Discs/Coiled-Coil and C2 Domain-Containing Protein 1 (Lgd/CC2D1)
Authors: Breuer Thomas , Tibbe Christine , Troost Tobias , Klein Thomas
Published: July 2024

Members of the LGD/CC2D1 protein family contain repeats of the family-defining DM14 domains. Via this domain, they interact with members of the CHMP family, which are essential for the ESCRT machinery-mediated formation of intraluminal vesicles during endosome maturation. Here, we investigate the requirement of the DM14 domains for the function of Lgd in detail. We found that although both odd-numbered DM14s can act in a functionally redundant manner, the redundancy is not complete and both contribute to the full function of Lgd. Our analysis indicates that some of the AAs that form the KARRxxR motif of the onDM14s are not exchangeable by similarly charged AAs without loss of function, indicating that they not only provide charge, but also fulfil structural roles. Furthermore, we show that the region of Lgd between DM14-4 and the C2 domain as well as its C-terminal region to the C2 domain are important for protein stability/function. Moreover, we analysed the importance of AAs that are conserved in all DM14 domains. Finally, our analysis of the C. elegans ortholog of Lgd revealed that it has only one DM14 domain that is functionally equivalent to the onDM14s. Altogether, the results further the understanding of how Lgd family members regulate the ESCRT machinery.
Effect of Active Phase Precursor on Structural, Textural and Catalytic Properties of the Model NiOx/CeO2 System Active in Dry Reforming of Methane
Authors: Legutko Piotr , Kozieł Marcin , Kowalczyk Andrzej , Michalik Marek , Adamski Andrzej
Published: July 2024

The current paper is devoted to the synthesis of ceria-supported nickel-based catalysts starting from different precursors of the nickel active phase. Thermal decomposition of metal-containing precursors, deposited onto stable supports by dry impregnation, belongs to the industrially preferred, simple ways of catalyst preparation. The synthesized series of NiOx/CeO2 catalysts have been tested in dry methane reforming (DMR), in which two greenhouse gases, i.e., CO2 and CH4, are simultaneously converted into syngas. Both reaction progress and stability of the catalyst strongly depend on nickel speciation, which in turn can be determined by the nature of the chosen precursor. Contrary to relatively many studies focused on the importance of synthetic methods and conditions on nickel speciation, the effect of precursor nature on structural, textural, and functional properties of catalytic systems has neither been discussed much nor fully understood. The main goal of this paper was to elucidate the effect of precursors on the properties of NiOx/CeO2. Consequences of the use of various nickel precursors (simple inorganic salts, organometallic complexes, and chelates) have been analyzed in detail from the viewpoint of their beneficial influence on the catalytic performance of NiOx/CeO2 system (containing 3 wt. % of Ni) tested in DMR.
Effect of Acetylation on the Morphology and Thermal Properties of Maize Stalk Cellulose Nanocrystals: A Comparative Study of Green-Extracted CNC vs. Acid Hydrolysed Followed by Acetylation
Authors: Khumalo Nduduzo Lungisani , Mohomane Samson Masulubanye , Motaung Tshwafo E.
Published: July 2024

This study highlights the advantages of employing acetylation to enhance the morphology and thermal properties of cellulose nanocrystals (CNCs) derived from maize stalks. Utilizing a green synthesis approach for CNC extraction, this research presents a novel comparison between green extracted CNCs, and their acid hydrolysed, followed by their acetylated counterparts (ACCNCs). This comparison reveals significant improvements in the properties of acetylated CNCs over those produced through conventional acid hydrolysis. The study employs advanced characterization techniques, including Fourier Transform Infrared (FTIR) spectroscopy, X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Thermogravimetric Analysis (TGA), to analyze untreated maize stalk extracted cellulose, green extracted CNCs, and acetylated CNCs. FTIR spectroscopy identifies changes in functional groups, underscoring the efficacy of the extraction and modification processes. XRD analysis demonstrates a beneficial transformation from cellulose I to cellulose II allomorphs post-acetylation, with increased crystallinity index values indicating effective removal of amorphous regions. SEM imaging reveals the preservation of rod-like structures in CNCs, while acetylated CNCs exhibit advantageous morphological changes, such as reduced nanocrystal length and increased branching. TGA results show superior thermal stability in green extracted CNCs and favorable thermal degradation behavior in acetylated CNCs. Overall, this study underscores the potential of acetylation to develop sustainable nanomaterials with tailored properties, offering significant advancements for various applications. Emphasizing the advantages of the prepared ACCNCs and the green synthesis method over traditional acid hydrolysis extraction, this research paves the way for innovative applications in diverse fields.
Invasiveness of Impatiens parviflora in Carpathian Beech Forests: Insights from Soil Nematode Communities
Authors: Renčo Marek , Jurová Jana , Čerevková Andrea
Published: July 2024

Invasive plants are capable of homogenizing both aboveground and belowground biota and, along with climate change, are recognized as one of the biggest threats to global biodiversity. Soil nematode communities reflect the surroundings they inhabit and are therefore frequently employed as biological indicators of soil condition. In this study, soil properties and nematode communities in Carpathian beech forest floor covered by dense vegetation of invasive Impatiens parviflora (small balsam) were investigated over two vegetation seasons. We assumed that the spread of invasive I. parviflora could influence soil fauna through litter accumulation when established and could also change several soil properties, consequently altering soil nematode communities. A total of 52 nematode species were found in the soil samples. The mean number of species varied from 18 to 31, but did not significantly differ between invaded and uninvaded plots across all sampling dates. However, redundancy analysis indicated that the nematode community in plots with small balsam differed significantly from that in uninvaded plots, reflecting different proportions of genera in the two communities. Invasion by small balsam significantly enhanced the relative abundance of bacterivores, whereas it decreased the abundance of plant parasites and root-fungal feeders, mainly in the spring and summer season. Ordination of nematode species along the structure index and enrichment index trajectories revealed a maturing food web, low to moderately disturbed in the I. parviflora invaded soils as well as in uninvaded forest plots. Decomposition channels of soil food webs in both plots were balanced and fungal–bacterial mediated, although low values of the channel index suggested prevailing bacterial decomposition. Our study reveals that the expansion of I. parviflora moderately influenced the composition of nematode communities and the soil food web, increased soil nitrogen, carbon and C/N ratio, but did not modify soil acidity.