Analyzed Data Research Articles

China's green energy growth: Economic policies, environmental economics, and strategies for resilience in the global economy

China has become a major global power due to its rapid economic growth, which is being driven by resource-intensive industries but at a considerable environmental cost. This study investigates the intricate relationships that exist between China's mining regulations, resource utilization, and environmentally friendly policies, as well as the overall impacts of these relationships on economic growth. The research uses a rigorous regression analysis approach and data from the Ministry of National Resources and the China Statistical Yearbook from 1986 to 2022. Integrating a Vector Error Correction Model (VECM) enables an investigation of the relationships among debt levels, GDP, and natural financing. Wald test estimates also reveal exact Corporate Social Responsibility (CSR) relationships. The results indicate that while China's economy has significantly benefited from mineral-intensive sectors, green measures are urgently needed to slow environmental deterioration. The focus should be redirected toward encouraging sustainable and ongoing development. These results highlight the critical role that green projects play in fostering economic growth. How China strikes a careful balance between its goals for ecological sustainability and economic growth is crucial for both China and the rest of the world in an era characterized by worries about climate change and resource shortages. The objective of this study is to analyze the complex relationship among China's mining regulations, resource utilization, and environmental policies. It will evaluate the effects of these factors on economic growth, with a particular focus on the necessity of adopting sustainable development practices in the face of environmental challenges and economic expansion. The study's goal is to examine the intricate relationships between China's resource use, environmental policies, and mining restrictions. It focuses on the importance of sustainable development methods in the face of environmental issues and economic growth. This research highlights the essential relationship between environmental stewardship and sustainable economic development, and policymakers, businesses, and environmental activists can all benefit from it.

Study of secondary charged particles produced in 12C-emulsion interactions at 4.5A GeV/c

This paper deals with the interactions of [Formula: see text]C-nucleus with the nuclear emulsion at 4.5[Formula: see text]A[Formula: see text]GeV/c, focused on distributions of multiplicity and the variation of the average multiplicities for secondary charged particles (black, gray, shower, and heavy particles) for the events released from these interactions. These averages have been calculated based on a model of modified cascade evaporation. A comparison has been made between the average multiplicities of the charged secondary particles produced from [Formula: see text]C and others from projectiles that interact with the nuclear emulsion at different energies, this comparison of [Formula: see text]C with other projectiles shows the fluctuations of the values of the average shower with gray for [Formula: see text]O and [Formula: see text]Si interactions occurring somewhat faster. The average number of shower, gray particles increases with the increasing mass number of the projectile Ap, except for black particles, which are nearly constant. The correlations of the average multiplicities for the different charged secondary particles are discussed. There is strong linear dependence in the correlations of average particles of shower, compound, and heavy on gray particles. The results of experimental and theoretical data were also verified with recent analysis data and new observations and were found to be consistent. Moreover, the results indicate that the residual target nucleus may have reached a temperature and constant excitation energy at a certain value for shower particles. The excess amount of energy at higher values of shower particles may be pumped into the system, and this energy may be expended during a transition of phase in the target nucleus system. The theoretical calculation results show good agreement with experimental data.

Understanding the Biomechanics of Musculoskeletal Injuries in High-Risk Environmental Conditions

The present study examines the biomechanics of musculoskeletal injuries in high-risk environmental conditions by thoroughly analyzing diverse data sources and employing various methodologies. This study utilizes motion analysis, force sensor measurements, computer simulations, and biomechanical testing to examine the various factors contributing to musculoskeletal injuries. The analysis of motion indicates that specific tests, namely varus test, impose considerably greater biomechanical stress, thereby emphasizing their susceptibility to causing injuries. The force sensor data reveals that pressure mapping system is responsible for exerting the highest force, raising concerns regarding its potential impact on the risk of injury. According to computer simulations, various injury risks are associated with different conditions, with load carriage exhibiting the highest risk. The analysis of joint stability during biomechanical testing reveals discrepancies in joint stability levels across different tasks. Outliers within the dataset highlight tasks that exhibit notable concerns regarding joint stability. Moreover, supplementary motion analysis data about various task variants, such as Sulcus sign and vasus stress test unveils distinct variations that lead to heightened levels of biomechanical stress. The discoveries mentioned above offer valuable perspectives on the biomechanical foundations of musculoskeletal injuries in environments with elevated risk levels. The aforementioned findings emphasize the necessity of implementing focused interventions, enhancing equipment design, and implementing heightened safety measures to reduce the risks of injury effectively. The present study establishes a fundamental basis for subsequent research endeavors and proposes approaches designed to safeguard the welfare of individuals operating in demanding contexts.

Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression signatures in six different populations using six public and two domestic cohorts (n = 1942) conducting mega-analysis and meta-analysis of the individual studies. We evaluated 12 machine learning and deep learning strategies for depression classification both in cross-validation (CV) and in hold-out tests using merged data from 8 separate batches, constructing models with both biased and unbiased feature selection. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level, and the associated genes were nominally related to axon guidance and immune pathways based on enrichment analysis and eQTM data. Random forest classifiers achieved the highest performance (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data. In contrast, the methylation showed low predictive power (all AUCs < 0.57) for all classifiers in CV and no predictive power in hold-out tests when used with harmonized data. All models achieved significantly better performance (>14% gain in AUCs) with pre-selected features (selection bias), with some of the models (joint autoencoder-classifier) reaching AUCs of up to 0.91 in the final testing regardless of data preparation. Different algorithmic feature selection approaches may outperform limma, however, random forest models perform well regardless of the strategy. The results provide an overview over potential future biomarkers for depression and highlight many important methodological aspects for DNA methylation-based depression profiling including the use of machine learning strategies.

The Violence of Peace: Post Good Friday Agreement Paramilitary Vigilantism in Northern Ireland

ABSTRACT This paper focuses on post Belfast/Good Friday Agreement paramilitary violence in Northern Ireland, specifically the vigilantism of paramilitary style attacks (PSAs) carried out by the loyalist and republican paramilitaries. This localised form of violence, formerly referred to as punishment attacks, has been the most persistent form of paramilitary violence in a post-conflict Northern Ireland. This paper critically analyses the broad criminological literature on the emergence of vigilantism, including consideration of factors impacting police confidence. The findings are applied to Northern Irish PSAs from 1998 to 2023. The author analyses data relating to Freedom of Information (FOI) requests to the Police Service of Northern Ireland. The results of these FOIs indicate that loyalist and republican paramilitaries combined have been responsible for 3,260 PSAs from 1998 to February 2023. Paramilitary republicans have been responsible for 1,196 attacks and loyalists responsible for 2,064. The article considers the post-Agreement evolution of this violence in terms of victims, injuries, geographical location, and police response. The most recent data indicate a downturn in PSAs. However, there are still significant challenges faced in the development of broader trust for the criminal justice system, within certain areas of Northern Ireland.

The Rivalry between Intramolecular Tetrel Bonds and Intermolecular Hydrogen Bonds in (O-Si) Chelates of N-Silylmethylamides and -ureas. A Theoretical Study.

The comparison of the results of theoretical calculations of (O-Si) chelates of N-silylmethylated amides and ureas with the axial chlorine or fluorine atom at silicon to the data of X-ray analysis of related compounds revealed the formation of covalent O-Si tetrel bonds (TB) or noncovalent O⋅⋅⋅Si tetrel bonds (NTB). The nature of the formed tetrel bond depends on the substituents at silicon and the polarity of the medium. The competition between the intramolecular TB and intermolecular hydrogen bonds (HB) with proton donors depends on the center of basicity involved in the formation of HB, which could be either oxygen or halogen. The hydrogen bonding can result in changing the nature of the tetrel bonds from covalent to noncovalent and vice versa by varying their lengths and energies. The O-Si bond energies estimated by QTAIM analysis of N-[(chlorodimethylsilyl)methyl]-N-methylacetamide and its H-complexes vary within the range of 7.2 and 12 kcal/mol in gas and solution, respectively, and correlate with the O-Si bond lengths.

Comparative Analysis of the Mitochondrial Genomes of Three Species of Yangiella (Hemiptera: Aradidae) and the Phylogenetic Implications of Aradidae

The mitochondrial genomes of three species of Yangiella were sequenced, annotated, and analyzed. The genome length of the three species of the genus is 15,070–15,202 bp, with a typical gene number, including a control region, 2 ribosomal RNA genes (rRNAs), 22 transfer RNA genes (tRNAs), and 13 protein-coding genes (PCGs). It was found that the mitochondrial genome of Yangiella had AT bias. Except for the lack of a DHU arm of the trnS1 gene, the other tRNAs had a typical cloverleaf structure, and the codon usage preferences of the three species exhibited high similarity. In addition, tRNA gene rearrangements were observed among the three subfamilies of Aradidae (Mezirinae, Calisiinae, Aradinae), and it was found that codon usage preferences appeared to be less affected by base mutation and more by natural selection. The Pi and Ka/Ks values indicated that cox1 was the most conserved gene in the mitochondrial genome of Aradidae, while atp8 and nad6 were rapidly evolved genes. Substitution saturation level analysis showed that the nucleic acid sequence of mitochondrial protein-coding genes in Aradidae did not reach saturation, suggesting the rationality of the phylogenetic analysis data. Bayesian and maximum likelihood methods were used to analyze the phylogeny of 16 species of Hemiptera insects, which supported the monophyly of Aneurinae, Carventinae, and Mezirinae, as well as the monophyly of Yangiella. Based on fossils and previous studies, the differentiation time was inferred, indicating that Yangiella diverged about 57 million years ago.

The State of Health of Electrical Connectors

For modern machines, factories and electric and autonomous vehicles, the importance of vreliable electrical connectors cannot be overstated. With an increasing number of connectors being used in machines, factories and vehicles, ensuring their reliability is crucial for comfort and safety alike. One of the key indicators of reliability is the lifetime of connectors. To evaluate the lifetime of electrical connectors, a testing method and a model for calculating their lifetime based on the test data were developed. The results from these tests were compared to failure analysis data from long-term field operations. The findings indicate that the laboratory tests can accurately reproduce the main failures observed in the field. However, such lifetime tests can be time- and labor-intensive. To address this challenge, a data-driven method is proposed that predicts the lifetime of electrical connectors using statistical analysis of electrical contact resistance data collected from short-term tests. The predictions from this method were compared to actual results obtained from long-term tests. A strong correlation was observed between the contact resistance development in short-term tests and the number of failures in later stages of testing. Thus, apart from predicting the lifetime of connectors, this method can also be applied for failure prognosis in real-time operations.

Neuroimaging meta regression for coordinate based meta analysis data with a spatial model.

Coordinate-based meta-analysis combines evidence from a collection of neuroimaging studies to estimate brain activation. In such analyses, a key practical challenge is to find a computationally efficient approach with good statistical interpretability to model the locations of activation foci. In this article, we propose a generative coordinate-based meta-regression (CBMR) framework to approximate a smooth activation intensity function and investigate the effect of study-level covariates (e.g. year of publication, sample size). We employ a spline parameterization to model the spatial structure of brain activation and consider four stochastic models for modeling the random variation in foci. To examine the validity of CBMR, we estimate brain activation on 20 meta-analytic datasets, conduct spatial homogeneity tests at the voxel level, and compare the results to those generated by existing kernel-based and model-based approaches. Keywords: generalized linear models; meta-analysis; spatial statistics; statistical modeling.

Synthesis, Characterization, DNA, Fluorescence, Molecular Docking, and Antimicrobial Evaluation of Novel Pd(II) Complex Containing O, S Donor Schiff Base Ligand and Azole Derivative

Pd(II) with the Schiff base ligand 2-Hydroxy-3-Methoxy Benzaldehyde-Thiosemicarbazone (HMBATSC) (L2) and 2-aminobenzothiazole (2-ABZ) (L1) was synthesized. The Schiff base ligand and the Palladium(II) complex were characterized by C.H.N.S, FT-IR, conductance studies, magnetic susceptibility, XRD, and TGA. From the elemental analysis and spectral data, the complex was proposed to have the formula [Pd(HMBATSC)(2-ABZ)H2O]. The interaction between the Pd(II) complex and DNA was examined through various methods, including UV–Vis spectroscopy, fluorescence techniques, and DNA viscosity titrations. The findings provided strong evidence that the interaction between the Pd(II) complex and DNA occurs through the intercalation mode. The analysis yielded the following values: a Stern–Volmer quenching constant (ksv) of 1.67 × 104 M−1, a quenching rate constant (kq) of 8.35 × 1011 M−1 s−1, a binding constant (kb) of 5.20 × 105 M−1, and a number of binding the sites (n) of 1.392. DFT studies suggest that the azole derivative may act as an electron donor through pyridine nitrogen, while the Schiff base ligand may act as an electron donor via oxygen and sulfur atoms. TDDFT calculations indicate that the intramolecular charge transfer from the Schiff base to Pd(II) is responsible for the complex’s fluorescence quenching. The powder X-ray diffraction data revealed that the complex is arranged in a monoclinic system. The resulting Pd(II) complex was investigated for its antimicrobial activity and demonstrated antibacterial efficiency. Interestingly, it showed potent activity against E. coli and E. niger that was found to be more powerful than that recorded for Neomycin.

Nab-paclitaxel plus S-1 versus nab-paclitaxel plus gemcitabine in patients with advanced pancreatic cancer: a multicenter, randomized, phase II study.

Encouraging antitumor activity of nab-paclitaxel plus S-1 (AS) has been shown in several small-scale studies. This study compared the efficacy and safety of AS versus standard-of-care nab-paclitaxel plus gemcitabine (AG) as a first-line treatment for advanced pancreatic cancer (PC). In this multicenter, randomized, phase II trial, eligible patients with unresectable, locally advanced, or metastatic PC were recruited and randomly assigned (1:1) to receive AS (nab-paclitaxel 125mg/m2 on days 1 and 8; S-1 twice daily on days 1 through 14) or AG (nab-paclitaxel 125mg/m2 on days 1 and 8; gemcitabine 1000mg/m2 on days 1 and 8) for 6 cycles. The primary endpoint was progression-free survival (PFS). Between July 16, 2019, and September 9, 2022, 62 patients (AS, n = 32; AG, n = 30) were treated and evaluated. With a median follow-up of 8.36 months at preplanned interim analysis (data cutoff, March 24, 2023), the median PFS (8.48 vs 4.47 months; hazard ratio [HR], 0.402; P = .002) and overall survival (OS; 13.73 vs 9.59 months; HR, 0.226; P < .001) in the AS group were significantly longer compared to the AG group. More patients had objective response in the AS group than AG group (37.50% vs 6.67%; P = .005). The most common grade 3-4 adverse events were neutropenia and leucopenia in both groups, and gamma glutamyl transferase increase was observed only in the AG group. The first-line AS regimen significantly extended both PFS and OS of Chinese patients with advanced PC when compared with the AG regimen, with a comparable safety profile. (ClinicalTrials.gov Identifier: NCT03636308).

Actn2 defects accelerates H9c2 hypertrophy via ERK phosphorylation under chronic stress.

In humans, ACTN2 mutations are identified as highly relevant to a range of cardiomyopathies such as DCM and HCM, while their association with sudden cardiac death has been observed in forensic cases. Although ACTN2 has been shown to regulate sarcomere Z-disc organization, a causal relationship between ACTN2 dysregulation and cardiomyopathies under chronic stress has not yet been investigated. In this work, we explored the relationship between Actn2 dysregulation and cardiomyopathies under dexamethasone treatment. Previous cases of ACTN2 mutations were collected and the conservative analysis was carried out by MEGA 11, the possible impact on the stability and function of ACTN2 affected by these mutations was predicted by Polyphen-2. ACTN2 was suppressed by siRNA in H9c2 cells under dexamethasone treatment to mimic the chronic stress in vitro. Then the cardiac hypertrophic molecular biomarkers were elevated, and the potential pathways were explored by transcriptome analysis. Actn2 suppression impaired calcium uptake and increased hypertrophy in H9c2 cells under dexamethasone treatment. Concomitantly, hypertrophic molecular biomarkers were also elevated in Actn2-suppressed cells. Further transcriptome analysis and Western blotting data suggested that Actn2 suppression led to the excessive activation of the MAPK pathway and ERK cascade. In vitro pharmaceutical intervention with ERK inhibitors could partially reverse the morphological changes and inhibit the excessive cardiac hypertrophic molecular biomarkers in H9c2 cells. Our study revealed a functional role of ACTN2 under chronic stress, loss of ACTN2 function accelerated H9c2 hypertrophy through ERK signaling. A commercial drug, Ibudilast, was identified to reverse cell hypertrophy in vitro.

Investigating cognitive and metacognitive components of WebQuest-based education in the 7&lt;sup&gt;th&lt;/sup&gt; grade work and technology curriculum according to Shannon’s entropy technique

The current research was conducted to investigate the cognitive and metacognitive components of WebQuest education in the 7&lt;sup&gt;th&lt;/sup&gt; grade work and technology curriculum using the strategy of quantitative content analysis and Shannon’s entropy technique. From the total population, it was selected as the sampling method of the research, therefore, all content elements, including activities, images, texts, and self-evaluations, were analyzed and investigated. These content elements were organized as the content analysis checklist and data collection tool. In this research, for the core components, the components obtained from the research with the title of “The application of WebQuest in teaching third-grade elementary science” were used, which included two core categories, cognitive and metacognitive, along with basic themes. The results of the examination of the cognitive components showed that in the 7&lt;sup&gt;th&lt;/sup&gt; grade work and technology curriculum, the most attention was paid to the component of “pluralistic thinking” with an importance coefficient of (0/128) and also the least attention was paid to the components of “constructive thinking” and “creative thinking” with an importance coefficient of (0/061). Also, the results of the metacognitive components analysis illustrated that in the 7&lt;sup&gt;th&lt;/sup&gt; grade work and technology curriculum, the most attention was paid to the components of “self-efficacy skills”, “self-management skills”, and “self-control skills” with an importance coefficient of (0/164) and the least attention was paid to the components of “self-directed skills” and “self-monitoring skills” with an importance coefficient of (0/109).

Exploiting Folk Cultural Resources of Dai Binh Village, Quang Nam Province, in Tourism Development

The article systematically investigates the current status of folk cultural resource exploitation in the tourism development of Dai Binh Village, Quang Nam Province. The author employs research methods including data collection, synthesis, document analysis, and statistical data processing to evaluate the tourism development status of Dai Binh Village. Additionally, comparative analysis methods are used to analyze statistical data and make assessments, evaluations, and scientifically based forecasts. To accomplish this research, the author utilizes primary sources such as official documents, reports, articles, etc., from governmental agencies and scholars specializing in folk cultural resources of Dai Binh Village. These sources provide a critical foundation for the author to gain an overview of folk cultural resource exploitation activities in Dai Binh Village's tourism development. Based on this foundation, the author analyzes and clarifies the folk cultural resources of Dai Binh Village and the current status of their exploitation in tourism development. Furthermore, the article proposes several solutions to effectively utilize folk cultural resources in the tourism development of Dai Binh Village, Quang Nam Province.

Numerical simulation of natural convection in a differentially heated cubical cavity with solid fins

Purpose The performance of solid fins inside a differentially heated cubical cavity is numerically studied in this paper. The main purpose of the study is to make an optimization to reach the maximum heat transfer in the enclosure having the solid fins with studied parameters. Design/methodology/approach The considered domain of interest is a differentially heated cube having heat-conducting solid fins placed on the heated wall while an opposite wall is a cooled one. Other walls are adiabatic. Governing equations describing natural convection in the fluid filled cube and heat conduction in solid fins have been written using non-dimensional variables such velocity and vorticity taking into account the Boussinesq approximation for the buoyancy force and ideal solid/fluid interfaces between solid fins and fluid. The formulated equations with appropriate initial and boundary conditions have been solved by the finite difference method of the second of accuracy. The developed in-house computational code has been validated using the mesh sensitivity analysis and numerical data of other authors. Analysis has been performed in a wide range of key parameters such as Rayleigh number (Ra = 104–106), non-dimensional fins length (l = 0.2–0.8), non-dimensional location of fins (d = 0.2–0.6) and number of fins (n = 1–3). Findings From numerical methods point of view the used non-primitive variables allows to perform numerical simulation of convective heat transfer in three-dimensional (3D) regions with two advantages, namely, excluding difficulties that can be found using vector potential functions and reducing the computational time compared to primitive variables and SIMPLE-like algorithms. From a physical point of view, it has been shown that using solid fins can intensify the heat transfer performance compared to cavities without any fins. Fins located close to the bottom wall of the cavity have a better heat transfer rate than those placed close to the upper cavity surface. At high Rayleigh numbers, increasing the fins length beyond 0.6 leads to a reduction of the average Nusselt number, and one solid fin can be used to intensify the heat transfer. Originality/value The present numerical study is based on hybrid approach for numerical analysis of convective heat transfer using velocity and vorticity that has some mentioned advantages. Obtained results allow intensifying the heat transfer using solid fins in 3D chambers with appropriate location and length.

Data extension of high-resolution wind speed database by fusing meteorological observation and local objective analysis data with POD–LSE

Newly generated high-resolution meteorological reanalysis data have been published over the past few years on short records. Producing high-resolution data in long-term time scales is challenging due to high computational costs and complex weather models. In contrast, urban meteorological observations have been continuously recorded for decades, although at a low spatial resolution. This study proposes a data fusion method using Proper Orthogonal Decomposition (POD) and Linear Stochastic Estimation (LSE). It fuses meteorological observations and high spatial resolution local objective analysis (LA) data to reproduce a high-resolution and long-term fusion database for urban areas without observations. First, the accuracy of LA data was verified by comparison with meteorological observations. Subsequently, the accuracy of the generated fusion data was investigated by comparison with Doppler lidar observations. Finally, the performance of single- and multi-time LSE in data fusion is discussed. These results indicate that the proposed method generates high-resolution and long-term fusion wind speed data that are similar to the Doppler lidar observations. In addition, the fusion model built using hourly data can accurately generate a highly sampled database at 10-min intervals. The single-time LSE method is recommended to be applied over the multi-time delay method for data fusion.

Transport Characteristics and Potential Source Areas of PM2.5 in Yangquan City Under Different Pollution Levels

Based on the PM2.5 monitoring data, NCEP data, and the meteorological data of the weather situation analysis at the corresponding time in Yangquan City from 2020 to 2022, using the HYSPLIT4 backward trajectory model, multi-station potential source contribution factor analysis （MS-PSCF） and trajectory density analysis （TDA） were introduced to study the differentiation and classification of PM2.5 transport channels and potential sources in Yangquan City. The results showed that： ① The PM2.5 pollution in Yangquan was mainly concentrated in Yangquan and Pingding, whereas the pollution in Yuxian was relatively light. The proportion of days with different pollution levels and the average and maximum values of PM2.5 concentration in Yangquan and Pingding were significantly higher than those in Yuxian, and the distribution characteristics of PM2.5 were closely related to the local special terrain. ② The amount of PM2.5 pollution and the concentration of PM2.5 in different pollution levels were the highest in light wind weather. The influence of east-west regional transport on PM2.5 pollution times and PM2.5 concentration of Yangquan and Pingding was obvious, and the contribution of east wind was significant. The influence of local pollution sources was the main factor in the moderate pollution weather in Yuxian County. ③ There were four main ground conditions for the generation and maintenance of moderate or above pollution weather： warm low pressure type （22%）, high pressure front （bottom） type （54%）, high pressure back type （14%）, and pressure equalization field （10%）. High pressure front （bottom） type was the main ground situation causing the increase in PM2.5 concentration. There were two types of upper air conditions, namely, flat westerly flow type （78%） and northwest flow type （22%）. The upper westerly flow type was the main upper air condition that caused the increase in PM2.5 concentration. ④ The results of transport channels and potential source areas of PM2.5 with different pollution levels obtained by MS-PSCF and TDA were consistent. The main transport channels of PM2.5 were the northeast, southeast, and northwest channels, whereas the northeast and southeast channels were short-distance transport routes, which were the main routes causing the increase in PM2.5 concentration. The northwest channel was consistent with the northwest dust transport channel, belonging to long-distance transmission. The main potential source areas of PM2.5 pollution were located in the central and western parts of Hebei and the southeast part of Hebei, the northeast part of Henan and its junction with the southwest part of Shandong, and the southeast part of Shanxi.

Prevalence of Clinical malaria and associated symptoms in pregnant women at Hamusit Health Center, Northwest Ethiopia

BackgroundMalaria is the disease caused by intracellular parasites known as Plasmodium species and is mainly transmitted by blood sucking female Anopheles mosquitoes. During pregnancy, malaria results in severe complications to the mother, the fetus and the newborn. Symptoms of malaria, such as fever, malaise, headache, nausea and vomiting, in pregnant women can be mistakenly attributed solely to pregnancy. In Ethiopia, the prevalence of malaria in asymptomatic pregnant women has been well documented. However, studies indicating the prevalence and clinical presentation of malaria in pregnant women are lacking. Therefore, there is little information on the prevalence of malaria and significantly associated signs and symptoms in pregnant women. The aim of this cross-sectional study was to determine the prevalence of malaria and identify clinical signs and symptoms associated with malaria which suggest presence of malaria in pregnant women at Hamusit Health Center, Northwest Ethiopia. MethodsA health facility-based cross-sectional study was conducted on 231 malaria symptomatic pregnant women from April to June 2023. A convenience sampling technique was employed. The socio demographic and clinical data of the study participants was collected through face-to-face interview using questionnaire. Thick and thin blood films were prepared from capillary blood and stained with 10% Giemsa. The stained blood smear was washed with clean water, air dried and examined under a light microscope. The Statistical Package for Social Sciences software version 20 (SPSS 20) was used to analyses data. Logistic regression was used to assess signs and symptoms associated with malaria. An adjusted odds ratio with a 95% confidence interval was calculated, and a P value < 0.05 was considered statistically significant. ResultsThe overall prevalence of malaria among symptomatic pregnant women in the study area was 22.9% (53/231) (95% CI: 17.3-29%). The most prevalent species was P. falciparum, with a frequency of 14.3% (33/231) (95% CI: 10% -18.6%), followed by P. vivax, 5.2% (12/231) (95% CI: (2.6% – 8.2%). The remaining 3.5% (8/231) (95% CI: 1.8% – 6.7%) were mixed infections of P. falciparum & P. vivax. Primigravidae (62.3%) and first trimester pregnancies (52.8%) were more affected. Malaria signs and symptoms mainly, fever [(P=0.002, AOR (95%CI); 5.1(1.84, 14.30)], joint pain [(P=0.001, AOR (95%CI); 7.8(2.24, 27.32)], vomiting [(P=0.007, AOR (95%CI); 2.9(1.34, 6.43)], malaise [(P=0.005, AOR (95%CI); 3.6(1.48, 8.67)] and fatigue [(P=0.0039, AOR (95%CI); 2.1(1.04, 4.37)], were significantly associated with malaria infection in pregnant women. ConclusionsMalaria positivity in pregnant women with fever, joint pain, vomiting, malaise and fatigue is considerably high in the study area. These signs and symptoms in pregnant women are strong indicators of malaria infection.

Mitochondrial Genome Characteristics Reveal Evolution of Acanthopsetta nadeshnyi (Jordan and Starks, 1904) and Phylogenetic Relationships

In the present study, the mitochondrial genomic characteristics of Acanthopsetta nadeshnyi have been reported and have depicted the phylogenetic relationship among Pleuronectidae. Combined with a comparative analysis of 13 PCGs, the TN93 model was used to review the neutral evolution and habitat evolution catalysis of the mitogenome to verify the distancing and purification selectivity of the mitogenome in Pleuronectidae. At the same time, a species differentiation and classification model based on mitogenome analysis data was established. This study is expected to provide a new perspective on the phylogenetic relationship and taxonomic status of A. nadeshnyi and lay a foundation for further exploration of environmental and biological evolutionary mechanisms.

Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater

AbstractPhysics‐informed neural networks (PINNs) are neural networks (NNs) that directly encode model equations, like Partial Differential Equations (PDEs), in the network itself. While most of the PINN algorithms in the literature minimize the local residual of the governing equations, there are energy‐based approaches that take a different path by minimizing the variational energy of the model. It is shown that in the case of the steady thermal equation weakly coupled to magnetic equation, the energy‐based approach displays multiple advantages compared to the standard residual‐based PINN: it is more computationally efficient, it requires a lower order of derivatives to compute, and it involves less hyperparameters. The analyzed benchmark problems are the single‐ and multi‐objective optimal design of an inductor for the controlled heating of a graphite plate. The optimized device is designed by involving a multi‐physics problem: a time‐harmonic magnetic problem and a steady thermal problem. For the former, a deep neural network solving the direct problem is supervisedly trained on Finite Element Analysis (FEA) data. In turn, the solution of the latter relies on a hypernetwork that takes as input the inductor geometry parameters and outputs the model weights of an energy‐based PINN (or ePINN). Eventually, the ePINN predicts the temperature field within the graphite plate.