bluuebunny/crossref_metadata_2025 huggingface dataset:
The Substitution of Fishmeal with Yeast Culture in the Yellow Catfish (Pelteobagrus fulvidraco) Diet: Growth, Serum Biochemical Indices, and Intestinal and Hepatopancreatic Histology
Authors: Huang Hongfei , Li Xiaoqin , Guo Beibei , Zhang Yugui , Yang Xu , Liu Yan , Leng Xiangjun
Published: March 2024

Yeast culture is a complex fermentation product consisting of fermentation substrate, yeast cells and their metabolites. This study investigated the potential of yeast culture in replacing fishmeal in the diet of yellow catfish (Pelteobagrus fulvidraco). First, a basal diet was formulated to contain 160 g/kg fishmeal (CON), and then the dietary fishmeal was decreased to 120, 80, 40 and 0 g/kg via yeast culture inclusion, respectively, to form another four isonitrogenous and isolipidic diets (YC-12, YC-8, YC-4 and YC-0). Yellow catfish (3.00 ± 0.10 g) were fed with the above five diets with triplicates per treatment and 40 fish per replicate. After 8 weeks of feeding, the weight gain (WG), protein efficiency rate and protein retention in the YC-12 group and the feed conversion ratio (FCR) in the YC-12 and YC-8 groups showed no significant differences to the CON group (p > 0.05), but the WG in the YC-8, YC-4 and YC-0 groups was significantly lower, and the FCR in the YC-4 and YC-0 groups was significantly higher than in the CON group (p < 0.05). In terms of the whole-body composition, only the crude lipid content in the YC-0 group decreased significantly (p < 0.05). Compared with the CON group, the aspartate aminotransferase and alanine aminotransferase activities and D-lactic acid content in the YC-0 group were significantly increased, and the total cholesterol content was significantly reduced (p < 0.05). The activities of catalase, superoxide dismutase, and alkaline phosphatase, as well as the content of complement C3 and immunoglobulin M, were significantly increased, while the MDA content was significantly reduced in the YC-12 and YC-8 groups (p < 0.05). There were no significant differences in the intestinal amylase and lipase activity among all the groups (p > 0.05), while the trypsin activity in the YC-12 and YC-8 groups, as well as the diamine oxidase in the YC-4 and YC-0 groups, were significantly higher than those in the CON group (p < 0.05). In the intestine histology, there was a significant decrease in the intestinal villus height in the YC-4 and YC-0 groups as well as in the villus width in the YC-0 group (p < 0.05). In the hepatopancreas histology, lipid droplets appeared in the YC-4 and YC-0 groups, and severe cell vacuolation was observed in the YC-0 group. As a summary, in a practical diet containing 160 g/kg fishmeal, yeast culture can effectively replace 40 g/kg fishmeal without negatively affecting the growth performance, nutrient utilization, serum immune and antioxidant, intestinal and hepatopancreas histology of yellow catfish.
Fetal Programming Influence on Microbiome Diversity and Ruminal and Cecal Epithelium in Beef Cattle
Authors: Dias Evandro Fernando Ferreira , de Carvalho Felipe Eguti , Polizel Guilherme Henrique Gebim , Cançado Fernando Augusto Correia Queiroz , Furlan Édison , Fernandes Arícia Christofaro , Schalch Júnior Fernando José , Santos Gianluca Elmi Chagas , Ferraz José Bento Sterman , Santana Miguel Henrique de Almeida
Published: March 2024

We explored the influence of maternal nutritional strategies on the development of the rumen and cecum in offspring. Additionally, we investigated the potential repercussions of prenatal nutrition on the rumen and fecal microbiota composition, utilizing metagenomic 16S techniques, to understand the effects of fetal programming (FP) in Nellore cattle. A total of 63 bulls submitted to different prenatal nutrition strategies, namely, non-programming (NP), partial programming (PP), and complete programming (CP), were evaluated. The rumen epithelium was methodically evaluated based on the presence of rumenitis and structural irregularities. The assessment of cecum lesions was conducted post-evisceration, whereby all thoroughly cleaned ceca were methodically evaluated. Samples from 15 animals of rumen fluid at slaughter and feces during the finishing phase were collected, respectively. All DNA extraction were carried out using the Macherey Nagel NucleoSpin Tissue®, and 16S sequencing was conducted using the V4 primers on the MiSeq platform. Within the ruminal ecosystem, an estimated range of 90 to 130 distinct amplicon sequence variants was discerned, as distributed across 45,000 to 70,000 sequencing reads. Our metagenomic exploration unveils microbial communities that distinctly mirror gastrointestinal tract microenvironments and dietary influences. In sum, this comprehensive study advances our comprehension of FP, highlighting the interplay of maternal nutrition, gastrointestinal development, and microbial communities, contributing significantly to the fields of animal science.
Dietary Hydroxytyrosol Supplementation on Growth Performance, Gut Morphometry, and Oxidative and Inflammatory Status in LPS-Challenged Broilers
Authors: Dias Kelly M. M. , Oliveira Carlos H. , Calderano Arele A. , Rostagno Horacio S. , Gomes Kaique M. , O’Connor Kevin E. , Davis Reeta , Walsh Meg , Britton James , Altieri Enrico A. , Albino Luiz F. T.
Published: March 2024

This study assessed the effects of hydroxytyrosol (HT) on 8- to 20-day-old broilers challenged with lipopolysaccharide (LPS); 180 Cobb500™ male chicks were randomly assigned to 3 treatment groups, each comprising 10 replicates with 6 birds per replicate. Treatments included a control diet (CON), CON with LPS administration, and CON + LPS supplemented with 10 mg of HT/kg of feed. LPS was administered intraperitoneally on days 14, 16, 18, and 20. Body weight (BW), body weight gain (BWG), and the feed conversion ratio (FCR) were measured. On day 20, ten birds per treatment were slaughtered for analysis. Bursa, spleen, and liver were collected, and their respective relative weight was determined. The jejunum was destined for morphological analyses of villus height (VH), crypt depth (CD), and their ratio (VH:CD), and for mRNA expression of nuclear factor kappa B (NF-κB), catalase (CAT), glutathione peroxidase (GPx), superoxide dismutase (SOD), and interleukins 10 (IL-10), 1 beta (IL-1β), and 8 (IL-8). HT improved BW, BWG, and FCR, and reduced crypt depth (CD) while increasing the VH:CD ratio in the jejunum. Moreover, HT downregulated mRNA expression of CAT, GPx, IL-10, and IL-1β. In conclusion, HT enhances broiler growth performance, mitigates jejunal mucosa damage from LPS, and modulates antioxidant and immune responses.
Protection of Chickens against H9N2 Avian Influenza Isolates with a Live Vector Vaccine Expressing Influenza Hemagglutinin Gene Derived from Y280 Avian Influenza Virus
Authors: Zhang Jun-Feng , Kim Sang-Won , Shang Ke , Park Jong-Yeol , Choi Yu-Ri , Jang Hyung-Kwan , Wei Bai , Kang Min , Cha Se-Yeoun
Published: March 2024

Since the outbreak of the H9N2/Y439 avian influenza virus in 1996, the Korean poultry industry has incurred severe economic losses. A novel possibly zoonotic H9N2 virus from the Y280-like lineage (H9N2/Y280) has been prevalent in Korea since June 2020, posing a threat to the poultry sector. Rapid mutation of influenza viruses urges the development of effective vaccines against newly generated strains. Thus, we engineered a recombinant virus rHVT/Y280 to combat H9N2/Y280. We integrated the hemagglutinin (HA) gene of the H9N2/Y280 strain into the US2 region of the herpesvirus of turkeys (HVT) Fc126 vaccine strain, utilizing CRISPR/Cas9 gene-editing technology. The successful construction of rHVT/Y280 was confirmed by polymerase chain reaction and sequencing, followed by efficacy evaluation. Four-day-old specific pathogen-free chickens received the rHVT/Y280 vaccine and were challenged with the H9N2/Y280 strain A21-MRA-003 at 3 weeks post-vaccination. In 5 days, there were no gross lesions among the vaccinated chickens. The rHVT/Y280 vaccine induced strong humoral immunity and markedly reduced virus shedding, achieving 100% inhibition of virus recovery in the cecal tonsil and significantly lowering tissue viral load. Thus, HVT vector vaccines expressing HA can be used for protecting poultry against H9N2/Y280. The induction of humoral immunity by live vaccines is vital in such cases. In summary, the recombinant virus rHVT/Y280 is a promising vaccine candidate for the protection of chickens against the H9N2/Y280.
Advanced Oxidation Protein Products Are Strongly Associated with the Serum Levels and Lipid Contents of Lipoprotein Subclasses in Healthy Volunteers and Patients with Metabolic Syndrome
Authors: Klobučar Iva , Hofmann Lidija , Habisch Hansjörg , Lechleitner Margarete , Klobučar Lucija , Trbušić Matias , Pregartner Gudrun , Berghold Andrea , Madl Tobias , Frank Saša , Degoricija Vesna
Published: March 2024

The association between advanced oxidation protein products (AOPPs) and lipoprotein subclasses remains unexplored. Therefore, we performed comprehensive lipoprotein profiling of serum using NMR spectroscopy and examined the associations of lipoprotein subclasses with the serum levels of AOPPs in healthy volunteers (HVs) and patients with metabolic syndrome (MS). The serum levels of AOPPs were significantly positively correlated with the serum levels of very-low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and low-density lipoprotein (LDL); however, they were significantly negatively correlated with high-density lipoprotein (HDL). These lipoproteins (and their subclasses) differed markedly regarding the direction of correlations between their lipid contents and AOPPs. The strength of the correlations and the relative contributions of the subclasses to the correlations were different in the HVs and patients with MS. As revealed by orthogonal partial least squares discriminant analyses, the serum levels of IDL were strong determinants of AOPPs in the HVs, whereas the serum levels of VLDL and the lipid content of LDL were strong determinants in both groups. We conclude that IDL, VLDL, and LDL facilitate, whereas HDL diminishes the bioavailability of serum AOPPs. The presence of MS and the lipid contents of the subclasses affect the relationship between lipoproteins and AOPPs.
Investigating Micro-Driving Behavior of Combined Horizontal and Vertical Curves Using an RF Model and SHAP Analysis
Authors: Wang Xiaomeng , Wei Xuanzong , Wang Xuesong
Published: March 2024

The free-flowing traffic environment of the freeway is an important application scenario for automatic driving. In this scenario, the freeway’s geometric design is an important factor because no other vehicle affects the driving process of the target vehicle. The freeway’s combined curves have more safety problems, but there are no quantitative guidelines for their geometric design. They present more challenges for automatic driving or driver assistance functions. If the relationship between human-drivers’ micro-behavior and the geometric design of combined curves is examined, it could provide theoretical support for the enhancement of automated driving and driver assistance functions as well as the quantitative design of combined curves. The paper analyzed the speed change and lane departure behaviors of combined curves, considering downslope curves, upslope curves, sag curves, and crest curves. The relationship between micro-driving behaviors and combined curves’ geometric design were determined using random forest models. The SHAP values of each variable were calculated. The results showed that (1) on a downslope curve and sag curve the speed change behavior should be paid more attention; on an upslope curve and crest curve, the lane departure behavior should be paid more attention; (2) the priority of geometric design parameters for four types of combined curves were different. Based on the results, drivers and autonomous vehicles can pay different levels of attention to their speed change and departure behavior on different combination curves, and take targeted improvement measures in time according to the driving status of the vehicles. Road designers can also prioritize more important road design parameters in the design process to avoid serious accidents caused by excessive speed changes and departures.
Computerized Optical Impression Making of Fully Dentate Upper and Lower Jaws: An In Vitro Study
Authors: Droste Lukas , Vach Kirstin , Kohal Ralf J. , Patzelt Sebastian B. M.
Published: March 2024

Objectives: The aim of this experimental study was to evaluate the accuracy of five intraoral scanners for digitizing fully dentate unprepared maxillae and mandibulae in vitro. Materials and Methods: One maxillary and one mandibular reference model with acrylic teeth, an industrial grade reference scanner, 3D evaluation software and the intraoral scanners CS 3500, iTero HD2.9, Planmeca PlanScan, TRIOS Standard and 3M True Definition were used. Scans of the entire arches, one front and two side segments of each arch scan of maxilla and mandibula were evaluated separately for trueness and precision. In addition, visual analyses of deviation patterns, surface properties and approximal areas were performed with the aid of 3D evaluation software. Results: The intraoral scanners CS 3500, TRIOS Standard and iTero HD2.9 showed a similar level of trueness. The True Definition scanner showed lower full arch trueness compared to the TRIOS Standard and to the iTero HD2.9 (p < 0.05). Full arch trueness of the PlanScan was lower compared to the other scanners. Video-based systems showed higher numbers of datapoints per scan (127,300–169,730) compared to single image-based systems (64,115–88,124). The acquisition of interproximal areas was insufficient across all scanners. Limitations: The intraoral scanners were not tested under clinical conditions in this study. Conclusions: Apart from interproximal areas, clinically acceptable full arch trueness was achieved by the CS 3500, the iTero HD2.9 and the TRIOS Standard.
Deep Learning Regressors of Surface Properties from Atomic Force Microscopy Nanoindentations
Authors: Pacheco Luís R. L. , Ferreira João P. S. , Parente Marco P. L.
Published: March 2024

Atomic force microscopy (AFM) is a powerful technique to study the nanomechanical properties of a wide range of materials at the piconewton level. AFM force–indentation curves can be fitted with appropriate contact models, enabling the determination of material properties for a given sample. However, the analysis of large datasets comprising thousands of curves using conventional methods presents a time-intensive challenge. As a result, there is an increasing interest in exploring alternative methodologies, such as integrating machine learning (ML) models to streamline and improve the efficiency of this process. In this work, two data-driven regressors were tuned to predict the Young’s modulus and adhesion energy from force–indentation curves of soft samples (Young’s modulus up to 10 kPa). Both models were trained exclusively on synthetic data derived from the contact theories developed by Hertz as well as Johnson, Kendall and Roberts (JKR). The PyTorch library was employed to build and train the models; then, the key hyperparameters were refined by implementing the optimization framework Optuna. The first model was successfully tested with synthetic and experimental curves from AFM nanoindentations, and the second presented promising results on the synthetic data. Our work suggests that experimental data may not be essential for training data-driven models to predict surface properties from AFM nanoindentations. By delivering accurate predictions in a computationally efficient way, our regressors validate the potential of a deep learning approach in exploring AFM nanoindentations and motivate further development of similar strategies to overcome current limitations in AFM postprocessing.
Farmed Insect Frass as a Future Organic Fertilizer
Authors: Nogalska Anna , Przemieniecki Sebastian Wojciech , Krzebietke Sławomir Józef , Kosewska Agnieszka , Załuski Dariusz , Kozera Wojciech Jan , Żarczyński Piotr Jarosław
Published: March 2024

The aim of this incubation experiment was to evaluate the effect of Tenebrio molitor L. frass on selected chemical and microbiological properties of acid peat. The optimal rate of mealworm frass in the substrate for growing ornamental trees and shrubs was determined. Acid peat was fertilized with frass or urea at five nitrogen (N) rates: 0, 50, 100, 200, and 400 mg dm−3. Mineral N content and electrical conductivity increased, and calcium content decreased in peat with increasing N rates. Similarly to urea, frass increased the ammonification rate at the beginning of incubation and the nitrification rate from the second week of incubation. Higher frass rates increased the abundance of plant-available nutrients (N, P, Mg, K, and Na) in acid peat. Frass undesirably decreased the counts of bacteria with antagonistic activity against soil-borne plant pathogens. Regarding the abundance of functional genes, the optimal N rate was 100 mg dm−3, which promoted the growth of N-fixing and chitinolytic bacteria. Higher N rates promoted the development of aerobic spore-forming bacteria, which produce antibiotics that can be used as biocontrol agents. Moderate fertilizer rates contributed to N accumulation in bacterial biomass. These preliminary findings, which indicate that insect frass can partially replace mineral fertilizers, are promising and can be used in pot and field experiments testing various plant species.
Designing and Developing an Advanced Drone-Based Pollution Surveillance System for River Waterways, Streams, and Canals Using Machine Learning Algorithms: Case Study in Shatt al-Arab, South East Iraq
Authors: Al-Battbootti Myssar Jabbar Hammood , Marin Iuliana , Al-Hameed Sabah , Popa Ramona-Cristina , Petrescu Ionel , Boiangiu Costin-Anton , Goga Nicolae
Published: March 2024

This study explores pollution detection and classification in the Shatt al-Arab River using advanced image processing techniques. Our proposed system integrates Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) algorithms. The Shatt al-Arab River in Basra, Iraq, faces increasing pollution from human activities, including oil spills, debris, and wastewater. We conducted extensive surveys of the river and its tributaries using a DJI Mavic drone, amassing over 1000 images to train machine learning models. The results indicate that RF excels with 94% accuracy for oil spills, 92% for wastewater, and 95% for debris. SVM also performs well, achieving 92%, 88%, and 94% accuracy for the respective pollutants. KNN, though insightful, lags with 85%, 89%, and 86% accuracy. Trained on this novel image dataset, these models show promising accuracy in detecting various pollution types from drone footage.
Agnostic Energy Consumption Models for Heterogeneous GPUs in Cloud Computing
Authors: Alnori Abdulaziz , Djemame Karim , Alsenani Yousef
Published: March 2024

The adoption of cloud computing has grown significantly among individuals and in organizations. According to this growth, Cloud Service Providers have continuously expanded and updated cloud-computing infrastructures, which have become more heterogeneous. Managing these heterogeneous resources in cloud infrastructures while ensuring Quality of Service (QoS) and minimizing energy consumption is a prominent challenge. Therefore, unifying energy consumption models to deal with heterogeneous cloud environments is essential in order to efficiently manage these resources. This paper deeply analyzes factors affecting power consumption and employs these factors to develop power models. Because of the strong correlation between power consumption and energy consumption, the influencing factors on power consumption, with the addition of other factors, are considered when developing energy consumption models to enhance the treatment in heterogeneous infrastructures in cloud computing. These models have been developed for two Virtual Machines (VMs) containing heterogeneous Graphics Processing Units (GPUs) architectures with different features and capabilities. Experiments evaluate the models through a cloud testbed between the actual and predicted values produced by the models. Deep Neural Network (DNN) power models are validated with shallow neural networks using performance counters as inputs. Then, the results are significantly enhanced by 8% when using hybrid inputs (performance counters, GPU and memory utilization). Moreover, a DNN energy-agnostic model to abstract the complexity of heterogeneous GPU architectures is presented for the two VMs. A comparison between the standard and agnostic energy models containing common inputs is conducted in each VM. Agnostic energy models with common inputs for both VMs show a slight enhancement in accuracy with input reduction.
Decision Support System Driven by Thermo-Complexity: Scenario Analysis and Data Visualization
Authors: Iovane Gerardo , Chinnici Marta
Published: March 2024

The present modelling aims to construct a computational information representation system useful for decision support system (DSS) solutions in the realization of intelligent systems or complex systems analysis solutions. Starting from an n-dimensional space (with n ≥ 7) represented by problem variables (referred to as CSF—Critical Success Factors), a dimensional embedding procedure is used to transition to a two-dimensional space. In the two-dimensional space, thanks to new lattice motion algorithms, the decision support system can determine the optimal solution with a lower computational cost based on the decision-maker’s preferences. Finally, thanks to an algorithm that takes into account the hierarchical order of importance of the seven CSFs as per the expert’s liking or according to his optimization logics, a return is made to the n-dimensional space and the final solution in the original space. As we will see, the starting and ending states in the n-dimensional space (referred to as micro-states) when projected into the two-dimensional space generate states (referred to as macro-states) which are degenerate. In other words, the correspondence between micro-states and macro-states is not one-to-one, as multiple micro-states correspond to one macro-state. Therefore, in relation to the decision-maker’s preferences, it will be the responsibility of the decision support system to provide the decision-maker with the micro-state of interest in the n-dimensional space (dimensional emergence procedure), starting from the obtained optimal macro-state. This result can be achieved starting from a flat chain of sensors capable of measuring/emulating certain specific parameters of interest. As we will see, it emerges that by considering random–exhaustive rolling value paths in order to track and potentially intervene to rebalance a dynamic system representing the state of stress/sensing of a system of interest, we are using the most general and, therefore, complex hypotheses of ergodic theory. In this work, we will focus on the representation of information in n-dimensional and two-dimensional spaces, as well as construct evaluation scenarios. We will also show the results of the decision support system in some cases of specific interest, thanks to a specific lattice motion algorithm of the realized decision-making environment.
Enhanced Conversion Efficiency in MAPbI3 Perovskite Solar Cells through Parameters Optimization via SCAPS-1D Simulation
Authors: Son Chaerin , Son Hyojung , Jeong Byoung-Seong
Published: March 2024

In this study, various factors affecting the efficiency of the MAPbI3 perovskite solar cell (PSC) were analyzed using the SCAPS-1D simulation program. The basic device analyzed in this study had a structure of ITO/TiO2/MAPbI3/Cu2O/Au. The thickness of each layer (electron transport layer (ETL), perovskite absorption layer (PAL), and hole transport layer (HTL)), PAL defect density and interface defect density were investigated as parameters. The optimized parameters that yielded the highest light conversion efficiency were an ETL (TiO2) thickness of 100 nm, a PAL (MAPbI3) thickness of 1300 nm, an HTL (Cu2O) thickness of 400 nm, a PAL defect density of 1014 cm−3, and an interface defect density of 1013 cm−3 for both absorber/ETL and absorber/HTL interfaces. The optimized PSC exhibited a maximum efficiency of 19.30%. These results obtained in this study are expected to contribute considerably to the optimization and efficiency improvement of perovskite solar cells using inorganic charge-carrier transport layers.
Using Irradiation-Acquisition Interleaved Time-Integrated Imaging to Assess Delayed Luminescence and the Noise-Laden Residual Spontaneous Photon Emission of Yeast
Authors: Piao Daqing
Published: March 2024

Delayed luminescence from organisms informs oxidative stress that may be modulable by external stimulations. In the absence of external stress causing delayed luminescence, organisms may produce spontaneous ultraweak photon emission due to the residual oxygen demand. To better understand the oxidative state of an organism, it is desirable to acquire the delayed luminescence to reach the phase wherein the ultraweak photon emission resides. This, however, is challenging due to the significant difference in the order of magnitude of the photon counts between the two types of photon emission. Conventional time-gated measurement requires a high dynamic range to assess the noise-level photon emission, whereas simple long exposure can miss the kinetics of luminescence. There may be a compromise to be made between robustly acquiring the decay kinetics of the delayed luminescence and reliably acquiring the noise-laden spontaneous photon emission. We demonstrate an irradiation-acquisition interleaved time-integrated imaging approach that may enable the reliable acquisition of slow-decay delayed luminescence down to the level of ultraweak photon emission. Repetitive irradiation was interleaved with a gradually increased time of acquisition to assess the integrated time course of the post-irradiation luminescence. Such instrument configuration performed on yeast facilitated the use of time differentiation to assess the delayed luminescence down to the noise-level ultraweak photon emission at the expense of the total time of acquisition.
Determining the Algorithm of Rehabilitation Procedures in Patients with Brachial Plexus Injuries Based on the Prospective Single-Centre Clinical Neurophysiology Studies: Preliminary Results
Authors: Lewczuk Kinga , Wiertel-Krawczuk Agnieszka , Huber Juliusz
Published: March 2024

The clinical neurophysiological tests allow us to determine the type, extent, and nature of brachial plexus damage. They are crucial in decision making regarding surgical procedures or conservative treatment. This report aimed to present an algorithm for rehabilitation procedures in patients with brachial plexus injury of various origins based on the results of neurophysiology findings for the selection of procedures supporting the process of nerve and muscle regeneration. The research group consisted of patients whose medical documentation was analysed concerning the reason, level, and localization of damage to the brachial plexus structures, surgical and or rehabilitative treatment, as well as the MRI results. Among the group of fourteen patients, the clinical studies showed the greatest incidence of brachial plexus injuries of the mixed (both pre- and postganglionic), all trunks, and cervical root injuries, respectively. Results of the motor evoked potentials (MEP) and electroneurography (ENG) recordings induced at levels of spinal roots and Erb’s point showed a decrease of more than 40% in amplitudes on the symptomatic side in comparison to the asymptomatic side. This diffeence was recorded for the axillary and radial innervation and the C5, C6, and C7 root domains, ranging from 57% to 66%; the lowest decrease was recorded following electrical stimulation at Erb’s point for the ulnar nerve (34%). The latency prolongation on the symptomatic side in CMAP and MEP tests ranged from 0.2 to 1.7 ms, with the most following magnetic stimulation of the C5 cervical root for the axillary innervation. Most of the results indicated the axonotmesis and neuropraxia type of injury in motor fibers (40%) confirmed by EMG results. The sensory conduction studies (SNCS) in distal nerve branches did not confirm the severe advancement of the brachial plexus injury (63%). The proposed algorithm of the physiotherapeutic procedures should be mainly targeted for recovery of motor dysfunction as the consequence of brachial plexus injury. Rehabilitation should incorporate the treatment supporting nerve regeneration, muscle strengthening, and maintaining functional ranges of motion of the injured extremities. The rehabilitation treatment for patients with brachial plexus injuries is an individualised process, and the selection of procedures and the effectiveness of the treatment undertaken should be confronted with results of neurophysiological tests verifying the motor neural transmission from the level of the cervical motor centre to the effector, peripheral nerve function, and muscle’s motor unit activity.
Nandanar: Visibilizing Caste in Bharatanatyam Performance
Authors: Ramaprasad Preethi
Published: March 2024

What are the implications of a bejeweled dancer in fine silk on the proscenium stage performing a piece that undeniably centers caste? As the Bharatanatyam field reflects on the art form’s appropriation from the hereditary dance community, analyzing choreography reveals different bodily representations of caste. Many Bharatanatyam dancers globally perform excerpts of the Nandanar Charitram, by Tamil composer Gopalakrishna Bharathi. The plot traces Nandanar, a Dalit saint who is not allowed in many temples and ends with his immolation, allowing his “purified” self to unite with the Hindu god Shiva. I study performances of the Nandanar Charitram comparing two Bharatanatyam showings and the 1942 film “Nandanar”. To recognize how caste is both articulated and understood, I analyze choreography, interviews conducted with dancers, and forums where audience members share their responses to the works. I use Judith Butler and Dwight Conquergood’s theorization of performativity, acknowledging that while Bharatanatyam choreography is often “iterative”, it has the potential to “disrupt” dominant norms on caste and politics. Nandanar remains the most prominent Dalit figure seen in the Bharatanatyam repertoire. By studying representations of his story, I highlight the relevance of bodily caste politics in the South Asian diaspora today.
A Critical Examination of the Standard Cosmological Model: Toward a Modified Framework for Explaining Cosmic Structure Formation and Evolution
Authors: Nyagisera Robert Nyakundi , Wamalwa Dismas , Rapando Bernard , Awino Celline , Mageto Maxwell
Published: March 2024

This paper explores the fundamental cosmological principle, with a specific focus on the homogeneity and isotropy assumptions inherent in the Friedmann model that underpins the standard model. We propose a modified redshift model that is based on the spatial distribution of luminous matter, examining three key astronomical quantities: light intensity, number density, and the redshift of galaxies. Our analysis suggests that the model can account for cosmic accelerated expansion without the need for dark energy in the equations. Both simulations and analytical solutions reveal a unique pattern in the formation and evolution of cosmic structures, particularly in galaxy formation. This pattern shows a significant burst of activity between redshifts 0 < z < 0.4, which then progresses rapidly until approximately z ≈ 0.9, indicating that the majority of cosmic structures were formed during this period. Subsequently, the process slows down considerably, reaching a nearly constant rate until around z ≈ 1.6, after which a gradual decline begins. We also observe a distinctive redshift transition around z ≈ 0.9 before the onset of dark-matter-induced accelerated expansion. This transition is directly related to the matter density and is dependent on the geometry of the universe. The model’s ability to explain cosmic acceleration without requiring fine tuning of the cosmological constant highlights its novelty, providing a fresh perspective on the dynamic evolution of the universe.
Assessment and Ensemble-Based Analysis of the Landfalling Typhoon Muifa (2022)
Authors: Tan Yan , Huang Wei , Zhang Xiping
Published: March 2024

By considering the uncertainties in the initial field, model physical processes, and lateral boundary conditions, the Shanghai Weather And Risk Model System-Ensemble Prediction System (SWARMS-EN) is constructed. According to the prediction results of typhoon Muifa (2022), the daily track error of SWARMS-EN within 5 days is 70.6 km, 142.2 km, 129.1 km, 174.5 km, and 203.5 km, respectively. When compared with the Typhoon Ensemble Data Assimilation and Prediction System (TEDAPS) and the Global Ensemble Forecast System (GEFS) of the National Centers for Environmental Prediction (NCEP) in homogeneous conditions, SWARMS-EN performs better than TEDAPS within 72 h and better than GEFS beyond 72 h in track forecasting. This indicates an improvement in forecasting accuracy. The ensemble spread within two days is less than the root mean square error (RMSE), according to an analysis of the relationship between ensemble RMSE and spread, which shows that SWARMS-EN has no apparent systematic bias overall. The system has improved the ensemble RMSE and spread, indicating that it can better represent the uncertainty of the forecast and produce more reliable forecasts. Additionally, SWARMS-EN provides the landfall forecast five days in advance. The ensemble-based analysis suggests that the large-scale circulation is the primary factor contributing to the forecast differences among members, and the strong steering flow provides an indication of the landfalling forecast. The analysis of the ensemble characteristics of the initial field indicates that the initial perturbation between the wind field and the temperature field in the dynamically unstable region (such as near a tropical cyclone) exhibits flow dependence, and the small perturbation shows continuity throughout the entire troposphere. The distribution of ensemble spread and disturbance energy exhibited a reasonable growth stage as the forecast lead time increased. Disturbance internal energy dominated the lower troposphere, while the upper troposphere was mainly characterized by disturbance kinetic energy. Disturbance kinetic energy played a leading role in the evolution process. This conclusion further confirms the importance of paying attention to the initial small perturbations near TC in order to optimize the initial perturbation.
Lidar Observations of the Fe Layer in the Mesopause and Lower Thermosphere over Beijing (40.5° N, 116.0° E) and Mohe (53.5° N, 122.4° E)
Authors: Wang Kexin , Wang Zelong , Wu Yuxuan , Du Lifang , Zheng Haoran , Jiao Jing , Wu Fang , Xun Yuchang , Xia Yuan
Published: March 2024

Lidar observations of metal layers play a significant role in research on the chemistry and dynamics of the mesosphere and lower thermosphere. This work reports on Fe lidar observations conducted in Beijing and Mohe. Utilizing the same laser emission system, a 1064 nm seed laser was injected into an Nd: YAG laser to generate a single longitudinal-mode pulse 532 nm laser, which pumped a dye laser to produce a 572 nm laser. The 572 nm laser and the remaining 1064 nm fundamental frequency laser passed through a sum–frequency module to generate a 372 nm laser to detect the Fe layer. According to a total of 52.6 h of observations for 10 nights in Beijing, the Fe layer has an average column density of 1.24 × 1010 cm−2, an RMS width of 4.4 km and a centroid altitude of 89.4 km. In Mohe, observed for 16 nights and a total of 91.5 h, the Fe layer has an average column density of 1.08 × 1010 cm−2, an RMS width of 4.6 km and a centroid altitude of 89.5 km. The probability of the occurrence of sporadic Fe layers was 42.4% in Beijing and 29.4% in Mohe. Compared to simultaneously observed Na layers, the occurrence probabilities of sporadic Fe layers were higher than those of sporadic Na layers in both stations. Based on the two cases observed in Beijing, it is conjectured that the formation mechanism of sporadic metal layers above approximately 100 km has a more significant influence on sporadic Fe layers than on sporadic Na layers. The lower thermospheric Fe layers with densities significantly larger than those of the main layer were observed during two nights in Mohe. This work contributes to the refinement of the global distribution of Fe layers and provides abundant observational data for the modeling and study of the metal layers.
An Assessment of the GLE Alert++ Warning System
Authors: Mavromichalaki Helen , Paschalis Pavlos , Gerontidou Maria , Tezari Anastasia , Papailiou Maria-Christina , Lingri Dimitra , Livada Maria , Stassinakis Argyris , Crosby Norma , Dierckxsens Mark
Published: March 2024

Over the last years the Athens Cosmic Ray Group of the National & Kapodistrian University of Athens has implemented a warning tool called GLE Alert, which is a highly credible application that issues alerts when a ground level enhancement (GLE) starts due to very high energy solar energetic particles reaching the Earth. This application warns of a high intensity solar energetic particle event up to several minutes before it reaches near the near-Earth space environment. In this work, an assessment of the latest updated version of GLE Alert, GLE Alert++, is presented. GLE Alert++ is a federated product of the ESA S2P SWE Space Radiation Expert Service Centre, which is part of the ESA Space WEather Service NETwork (SWESNET) project. The assessment of the GLE Alert++, which was finalized in October 2022, focused on: (a) the availability of the real-time data provided by the neutron monitor stations that contribute to the GLE Alert++, (b) the behaviour of each station regarding the different Alert levels status (Watch, Warning and Alert), and (c) the definition of the real-time assessment index. The results of this work are of essential importance since they ensure a reliable and trustworthy warning tool, and can be highly useful in protecting humans during extreme solar energetic events.
Allergenic Pollen Monitoring at Sapienza University Campus (Rome, Italy): Patterns of Pollen Dispersal and Implications for Human Health
Authors: Lancia Andrea , Di Rita Federico , Ariano Renato , Vonesch Nicoletta , D’Ovidio Maria Concetta , Magri Donatella
Published: March 2024

The Campus of the Sapienza University of Rome, frequented daily by several thousands of students and workers, collects allergenic airborne pollen from many sources. Here, we report the results of detailed pollen monitoring of 49 pollen types within the University Campus, allowing us to trace the main local and regional sources of airborne pollen throughout the year. The amount of allergenic pollen has been calculated for each daily record to evaluate the risk of exposure for students and workers on Campus in relation to academic activities and to suggest possible mitigation measures. Our results show that the maximum pollen concentrations are recorded from March to May, and the highest floristic richness occurs in April–June. We distinguish massive local pollen producers from pollen of regional origin and local ornamental and invasive taxa. Pollen with extreme allergenicity is dominant from mid-January to mid-March and in May with Cupressaceae/Taxaceae, Corylus and Olea; high allergenicity from late March to late April with Platanus, Ostrya, Ginkgo and Moraceae; and medium allergenicity from late April to the beginning of May with Quercus and Pinus. In August–December, pollen concentration is relatively low. Diversified mitigation actions are suggested in relation to the provenance, allergenicity and emission period of pollen.
Simulation of Extreme Ultraviolet Radiation and Conversion Efficiency of Lithium Plasma in a Wide Range of Plasma Situations
Authors: Li Xiangdong , Rosmej Frank B. , Chen Zhanbin
Published: March 2024

Based on the detailed term accounting approach, the relationship between extreme ultraviolet conversion efficiency and plasma conditions, which range from 5 to 200 eV for plasma temperature and from 4.63 × 1017 to 4.63 × 1022 cm−3 for plasma density, is studied for lithium plasmas through spectral simulations involving very extended atomic configurations, including a benchmark set of autoionizing states. The theoretical limit of the EUV conversion efficiency and its dependence on sustained plasma time are given for different plasma densities. The present study provides the necessary understanding of EUV formation from the perspective of atomic physics and also provides useful knowledge for improving EUV conversion efficiency with different technologies.
Low-Computational Model to Predict Individual Temperatures of Cells within Battery Modules
Authors: Abbas Ali , Rizoug Nassim , Trigui Rochdi , Redondo-Iglesias Eduardo , Pelissier Serge
Published: March 2024

Predicting the operating temperature of lithium-ion battery during different cycles is important when it comes to the safety and efficiency of electric vehicles. In this regard, it is vital to adopt a suitable modeling approach to analyze the thermal performance of a battery. In this paper, the temperature of lithium-ion NMC pouch battery has been investigated. A new formulation of lumped model based on the thermal resistance network is proposed. Unlike previous models that treated the battery as a single entity, the proposed model introduces a more detailed analysis by incorporating thermal interactions between individual cells and tabs within a single cell scenario, while also considering interactions between cells and insulators or gaps, located between the cells, within the module case. This enhancement allows for the precise prediction of temperature variations across different cells implemented within the battery module. In order to evaluate the accuracy of the prediction, a three-dimensional finite element model was adopted as a reference. The study was performed first on a single cell, then on modules composed of several cells connected in series, during different operating conditions. A comprehensive comparison between both models was conducted. The analysis focused on two main aspects, the accuracy of temperature predictions and the computational time required. Notably, the developed lumped model showed a significant capability to estimate cell temperatures within the modules. The thermal results revealed close agreement with the values predicted by the finite element model, while needing significantly lower computational time. For instance, while the finite element model took almost 21 h to predict the battery temperature during consecutive charge/discharge cycles of a 10-cell module, the developed lumped model predicted the temperature within seconds, with a maximum difference of 0.42 °C.
Swift Prediction of Battery Performance: Applying Machine Learning Models on Microstructural Electrode Images for Lithium-Ion Batteries
Authors: Deeg Patrick , Weisenberger Christian , Oehm Jonas , Schmidt Denny , Csiszar Orsolya , Knoblauch Volker
Published: March 2024

In this study, we investigate the use of artificial neural networks as a potentially efficient method to determine the rate capability of electrodes for lithium-ion batteries with different porosities. The performance of a lithium-ion battery is, to a large extent, determined by the microstructure (i.e., layer thickness and porosity) of its electrodes. Tailoring the microstructure to a specific application is a crucial process in battery development. However, unravelling the complex correlations between microstructure and rate performance using either experiments or simulations is time-consuming and costly. Our approach provides a swift method for predicting the rate capability of battery electrodes by using machine learning on microstructural images of electrode cross-sections. We train multiple models in order to predict the specific capacity based on the batteries’ microstructure and investigate the decisive parts of the microstructure through the use of explainable artificial intelligence (XAI) methods. Our study shows that even comparably small neural network architectures are capable of providing state-of-the-art prediction results. In addition to this, our XAI studies demonstrate that the models are using understandable human features while ignoring present artefacts.
The Perpetual Vector Mosquito Threat and Its Eco-Friendly Nemeses
Authors: Miranda Leticia Silva , Rudd Sarah Renee , Mena Oscar , Hudspeth Piper Eden , Barboza-Corona José E. , Park Hyun-Woo , Bideshi Dennis Ken
Published: March 2024

Mosquitoes are the most notorious arthropod vectors of viral and parasitic diseases for which approximately half the world’s population, ~4,000,000,000, is at risk. Integrated pest management programs (IPMPs) have achieved some success in mitigating the regional transmission and persistence of these diseases. However, as many vector-borne diseases remain pervasive, it is obvious that IPMP successes have not been absolute in eradicating the threat imposed by mosquitoes. Moreover, the expanding mosquito geographic ranges caused by factors related to climate change and globalization (travel, trade, and migration), and the evolution of resistance to synthetic pesticides, present ongoing challenges to reducing or eliminating the local and global burden of these diseases, especially in economically and medically disadvantaged societies. Abatement strategies include the control of vector populations with synthetic pesticides and eco-friendly technologies. These “green” technologies include SIT, IIT, RIDL, CRISPR/Cas9 gene drive, and biological control that specifically targets the aquatic larval stages of mosquitoes. Regarding the latter, the most effective continues to be the widespread use of Lysinibacillus sphaericus (Ls) and Bacillus thuringiensis subsp. israelensis (Bti). Here, we present a review of the health issues elicited by vector mosquitoes, control strategies, and lastly, focus on the biology of Ls and Bti, with an emphasis on the latter, to which no resistance has been observed in the field.
Limonene Exerts Anti-Inflammatory Effect on LPS-Induced Jejunal Injury in Mice by Inhibiting NF-κB/AP-1 Pathway
Authors: Kathem Sarmed H. , Nasrawi Yasameen Sh. , Mutlag Shihab H. , Nauli Surya M.
Published: March 2024

The human gastrointestinal system is a complex ecosystem crucial for well-being. During sepsis-induced gut injury, the integrity of the intestinal barrier can be compromised. Lipopolysaccharide (LPS), an endotoxin from Gram-negative bacteria, disrupts the intestinal barrier, contributing to inflammation and various dysfunctions. The current study explores the protective effects of limonene, a natural compound with diverse biological properties, against LPS-induced jejunal injury in mice. Oral administration of limonene at dosages of 100 and 200 mg/kg was used in the LPS mouse model. The Murine Sepsis Score (MSS) was utilized to evaluate the severity of sepsis, while serum levels of urea and creatinine served as indicators of renal function. Our results indicated that LPS injection induced renal function deterioration, evidenced by elevated serum urea and creatinine levels compared to control mice. However, pretreatment with limonene at doses of 100 and 200 mg/kg mitigated this decline in renal function, evidenced from the reduced levels of serum urea and creatinine. Limonene demonstrated anti-inflammatory effects by reducing pro-inflammatory cytokines (TNF-α, IL-1β, COX-2), suppressing the TLR4/NF-κB/AP-1 but not IRF3 signaling pathways, and modulating oxidative stress through Nrf2 activation. The results suggest that limonene holds promise as a potential therapeutic agent for mitigating intestinal inflammation and preserving gastrointestinal health.