A convenient practical model for accurately estimating the total entropy (ΣSi) of atmospheric gases based on physical action is proposed. This realistic approach is fully consistent with statistical mechanics, but reinterprets its partition functions as measures of translational, rotational and vibrational action or quantum states, to estimate the entropy. With all kinds of molecular action expressed as logarithmic functions, the total heat required for warming a chemical system from 0o K (ΣSiT) to a given temperature and pressure can be computed, yielding results identical with published experimental third law values of entropy. All thermodynamic properties of gases including entropy, enthalpy, Gibbs energy and Helmholtz energy are directly estimated using simple algorithms based on simple molecular and physical properties, without resource to tables of standard values; both free energies are measures of quantum field states and of minimal statistical degeneracy, decreasing with temperature and declining density. We propose that this more realistic approach has heuristic value for thermodynamic computation of atmospheric profiles, based on steady state heat flows equilibrating with gravity. Potentially, this application of an action principle can provide better understanding of emergent properties of many natural or evolving complex systems, including modelling of predictions for global warming.

The foreign trade sustainable development index system of Shenzhen City, including the three subsystems of environment, economy, and society, was constructed based on the theory of emergy analysis.The sustainable development of foreign trade in Shenzhen City from 2009 to 2016 was evaluated, and a detailed analysis of changes in the emergy of light and heavy industries was performed. The results showed that the scale of economy has been expanding, and the total volume of imports and exports has turned from a rise to a decline in 2013. The status of sustainable development is not optimistic. The transaction volume of energy is reduced, and the quality of people's living environment is declining. The sustainable development of Shenzhen City is not perfect, but it is in a phase of gradual optimization. Moreover, the proportion of heavy industry in import and export trade is significantly higher than that of light industry, which has caused the outflow of energy to a certain extent. Therefore, to improve the level of foreign trade sustainable development, we must improve the efficiency of resource utilization, increase the import of energy products, strengthen the ability to cope with external interference and adjust the foreign trade industrial structure.

Due to advancement in hacking/reverse engineering tools, threat against transfer of sensitive data or highly classified information is always at risk of being intercepted by an attacker. Covert communication outwit this malicious breach of privacy act better than cryptography as it camouflage secret information inside another innocent looking information, while cryptography shows scrambled information that might arouse attention of an attacker. However, the challenges in Steganography are the modification of carrier that causes some abnormalities, which is detectable and often the methods are not optimize. This paper presents an approach in Covert communication Chanel, which utilizes mathematical concept of combination to optimize time of transmission using sets of multiple transmitter’s, and receiver’s addresses where each abstractly represents a set of bits or characters combination without modifying the address. To minimize the number of physical address to be use, a combinatorial and permutation concept of virtual address generation from physical address is introduce. The paper in addition presents some technique like relationship and their application in both re-enforcing resistivity against Steganalysis and generating combinations. Furthermore, a concept of dynamical clockwise and anti-clockwise rotation of combination over addresses after every transmission is introduce to further improve on resistivity against Steganalysis. A simple test was performed for demonstrating relay address, combination and permutation concepts. Based on test results and analysis, the method is effective as expected and it is quite easy to use as it can be implemented in different platform without much difficulties.

In recent years, biomedical research has faced increased scrutiny over issues related to reproducibility and quality in scientific findings(1-3). In response to this scrutiny, funding institutions and journals have implemented top-down policies for grant and manuscript review. While a positive step forward, the long-term merit of these policies is questionable given their emphasis on completing a check-list of items instead of a fundamental re-assessment of how scientific investigation is conducted. Moreover, the top-down style of management used to institute these policies can be argued as being ineffective in engaging the scientific workforce to act upon these issues. To meet current and future biomedical needs, new investigative methods that emphasize collective-thinking, teamwork, shared knowledge and cultivate change from the bottom-up are warranted. Here, a perspective on a new approach to biomedical investigation within the individual laboratory that emphasizes collaboration and quality is discussed.

Disputes on authorships or the order of authors on publications are among the most common conflicts in science, particularly where multi-author papers have become the norm. Here, I propose an adaptable and generalizable method to rationalize and democratize decisions about authorships, which can be applied in diverse scientific areas. In the process, the authors of a manuscript collect, discuss, score, and weight their contributions to the final manuscript. The decision process is assisted by a simple spreadsheet-based “authorship matrix”, which helps to break down the complexity of different contributions and their importance. The matrix generates a score s describing the percentage of the author’s total contributions and can be used to determine authorship and their order. The transparency and simplicity score s can reduce conflicts and thus increase productivity in collaborations.

We explore the use of inverse multiquadratic (IMQ) functions as basis functions when solving the vibrational Schrödinger equation with the rectangular collocation method. The quality of the vibrational spectrum of formaldehyde (in six dimensions) is compared to that obtained using Gaussian basis functions when using different numbers of width-optimized IMQ functions. The effects of the ratio of the number of collocation points to the number of basis functions and of the choice of the IMQ exponent are studied. We show that the IMQ basis can be used with parameters where the IMQ function is not integrable. We find that the quality of the spectrum with IMQ basis functions is somewhat lower that that with a Gaussian basis when the basis size is large and for a range of IMQ exponents. The IMQ functions are, however, advantageous when a small number of functions is used or with a small number of collocation points e.g. when using square collocation.

The Colebrook equation ζ is implicitly given in respect to the unknown flow friction factor λ ; λ=ζ(Re,ε*,λ) which cannot be expressed explicitly in exact way without simplifications and use of approximate calculus. Common approach to solve it is through the Newton-Raphson iterative procedure or through the fixed-point iterative procedure. Both requires in some case even eight iterations. On the other hand numerous more powerful iterative methods such as three-or two-point methods, etc. are available. The purpose is to choose optimal iterative method in order to solve the implicit Colebrook equation for flow friction accurately using the least possible number of iterations. The methods are thoroughly tested and those which require the least possible number of iterations to reach the accurate solution are identified. The most powerful three-point methods require in worst case only two iterations to reach final solution. The recommended representatives are Sharma-Guha-Gupta, Sharma-Sharma, Sharma-Arora, Džunić-Petković-Petković; Bi-Ren-Wu, Chun-Neta based on Kung-Traub, Neta, and Jain method based on Steffensen scheme. The recommended iterative methods can reach the final accurate solution with the least possible number of iterations. The approach is hybrid between iterative procedure and one-step explicit approximations and can be used in engineering design for initial rough, but also for final fine calculations.

In this work, numerical simulations for the absorption and scattering efficiencies of spheroid core–shell nanoparticles (CSNs) were conducted and studied using the discrete-dipole approximation method. The characteristics of surface plasmon resonances (SPR) depend upon shell thickness, the compositions of the core and shell materials, and the aspect ratio of the constructed CSNs. We used different core@shell compositions, specifically Au@SiO₂, Ag@SiO₂, Au@TiO₂, Ag@TiO₂, Au@Ag, and Ag@Au, for extinction spectra analysis. We also investigated coupled resonance mode wavelengths by adjusting the composition’s layer thickness and aspect ratio. In this study, we show that the extinction efficiency of the Ag@TiO₂ core–shell nanoparticles (CSNPs) was higher than that of the others, and we examined the impact of TiO₂ shell thickness and Ag core radius on SPR peak positions. From the extinction spectra we found that the Ag@TiO₂ nanoparticle had better refractive index sensitivity and figure of merit when the aspect ratio was set to 0.3. All of the experimental results proved that the tunability of these plasmonic resonances was highly dependent on the material used, the layer thickness, and the aspect ratio of the core@shell CSNPs.

The interaction between different regions normally is reflected by the form of the stream. For example, the interaction of the flow of people and flow of information between different regions can reflect the structure of cities’ network, and also can reflect how the cities function and connect to each other. Since big data has become increasingly popular, it is much easier to acquire flow data for various types of individuals. Currently, it is a hot research topic to apply the regional interaction model, which is based on the summary level of individual flow data mining. So far, previous research on spatial interaction methods focused on point-to-point and area-to-area interaction patterns. However, there are a few scholars who study the hotspot interaction pattern between two regional groups with some predefined neighborhood relationship by starting with two regions. In this paper, a method for identifying a similar hotspot interaction pattern between two regional groups has been proposed, and the Geo-Information-Tupu methods are applied to visualize the interaction patterns. For an example of an empirical analysis, we discuss China’s air traffic flow data, so this method can be used to find and analyze any hotspot interaction patterns between regional groups with adjoining relationships across China. Our research results indicate that this method is efficient in identifying hotspot interaction flow patterns between regional groups. Moreover, it can be applied to any analysis of flow space that is used to excavate regional group hotspot interaction patterns.

The Sine-Gordon expansion method is implemented to construct exact solutions some conformable time fractional equations in Regularized Long Wave(RLW)-class. Compatible wave transform reduces the governing equation to classical ordinary differential equation. The homogeneous balance procedure gives the order of the predicted polynomial-type solution that is inspired from well-known Sine-Gordon equation. The substitution of this solution follows the previous step. Equating the coefficients of the powers of predicted solution leads a system of algebraic equations. The solution of resultant system for coefficients gives the necessary relations among the parameters and the coefficients to be able construct the solutions. Some solutions are simulated for some particular choices of parameters.

There is no simple method to measure glomerular filtration rate (GFR) in swine, an established model to study renal disease. We developed a protocol to measure GFR in conscious swine with the plasma clearance of iohexol. We used two groups: testing and validation, of 8 animals each. Ten milliliters of iohexol (6.47 g) were injected by the marginal auricular vein and blood samples (3 ml) were collected from the orbital sinus at different points after injection. GFR was determined considering two models: two-compartments (CL2: all samples) and one-compartment (CL1: the last six samples). In the testing group, CL1 overestimated CL2 by ~30%: CL2=245±93 and CL1=308±123 ml/mn. This error was corrected by a first order polynomial quadratic equation to CL1, which was considered the simplified method: SM=-47.909+(1.176xCL1)–(0.00063968xCL1²). SM showed narrow limits of agreement with CL2, and a concordance correlation of 0.97 and a total deviation index of 14.73%. Similar results were obtained for the validation group. This protocol is reliable, reproducible, can be performed in conscious animals, uses a single dose of the marker, and requires a reduced number of samples avoiding urine collection. Finally, it portends a significant improvement in animal-welfare conditions and handling necessities in experimental trials.

This paper deals with a generic methodology to evaluate the magnetic parameters of contactless power transfer systems. Neumann's integral has been used to create a matrix method that can model the magnetics of single coils (circle, square, rectangle). The principle of superposition has been utilised to extend the theory to multi-coil geometries such as double circular, double rectangle and double rectangle quadrature assuming linearity of magnetics. Numerical and experimental validation has been performed to validate the analytical models developed. A rigorous application of the analysis has been carried out to study misalignment and hence the efficacy of various geometries to misalignment tolerance. Comparison of single-coil and multi-coil shapes considering coupling variation with misalignment, power transferred and maximum efficiency is carried out.

The development of low-cost, open-source Remotely Operated Vehicle (ROV) systems has provided almost unrestricted access for researchers looking to monitor the marine environment in ever greater resolution. Sampling microbial communities from the marine environment, however, still usually relies on Niskin-bottle sampling (ROV or CTD based), a method which introduces an inaccuracy and variability that is incompatible with metatranscriptomic analysis. Here, we describe a versatile, easily-replicated platform which achieves in situ mRNA preservation, via the addition of RNAlater to filtered microbial cells, to enhance ROV or CTD functionality.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

Different materials prepared by appropriate synthesis methods and applying different post syn-thesis processes could be used as hole transport layer in perovskite solar cells. In the present work annealing was employed to enhance physical properties of copper oxide (CuO) thin films fabricated via spin coating technique and the effects of annealing on their optical, morphological, electrical and structural properties were investigated. The XRD findings revealed the polycrystalline structure with large crystallite size. Optical spectra showed larger transmission beyond the visible region, reduced absorption, and a decrease in bandgap energy from 1.93 eV to 1.81 eV. The Ag phonon modes at 299.22 and 304 cm-1 shown by the Raman shift confirmed the development of the CuO pure phase. FTIR spectra showed the Cu-O stretching band at 759, 764 and 446 cm−1. SEM revealed the agglomeration of nano crystallites with large grains on the surface. The carrier type conductivity of annealed CuO thin films was determined via two-point hot probe technique. Low resistivity values were determined via four-point probe method. These findings indicate that CuO thin films may be successfully used as a companion with an n-type layer in p-n junction solar cells, and a hole transport layer in perovskite solar cells.

Invasive species are one of the five main causes of biodiversity loss, along with habitat destruction, overexploitation, pollution, and climate change. Represent one of the first barriers to overcome in ecological conservation programs, since are difficult to control and eradicate. Due to the lack of records of invasive exotic species in Panama, this research is necessary to identify and register the documented groups of invasive species of the Chordates and Arthropod groups in Panama. This exhaustive search of invasive species was carried out in different bibliographic databases, electronic portals and scientific journals which addressed the topic at a global level. The results indicate that approximately 133 invasive exotic species of the Arthropoda and Chordata Phylum have been reported in Panama. Of the 133 species, 49 species belong to the Arthropoda Phylum and 84 species belong to the Chordate Phylum. The Panamanian economic activity could promote the introduction of alien species in this country. The study provides the first list of invasive exotic chordate and arthropod species reported for the Republic of Panama.

Chestnut is an interesting productive alternative for farmers in Southern Chile. However, cli-matic variability with the occurrence of late spring and early summer frost have cause damages on young trees. Glycine‒betaine (GB) spraying on shoots of sensitive chestnut induce an increase in tolerance during subsequent chilling stress. Experiment was performed on three years-old trees (cultivar Cittá di Castello) conducted in a leader training system and sprayed with com-mercial GB (120 g hL‒1). In summer trees treated with GB showed a better recovery after the frost (‒2.34°C) occurrence for 3.5 h compared to the control. Whereas trees obtained a 28% greater growth of central axis than untreated control (January). The trunk diameter measured in January showed the highest value under GB (27.2mm) compared with the control (25.7 mm). The GB ap-plication increased by 50 and 47% highest fresh and dry weight respectively in leaves. Under GB trees reached a 28% higher net photosynthesis (AN) compared to the AN in control (11.93 µmol CO2 m‒2 s‒1). Moreover, achieved higher stomatal conductance and transpiration rate was 44 and 31% with GB compared to control trees respectively. Antioxidant performance was differentially affected by GB activating non-enzymatic mechanisms and caused a reduced lipid peroxidation. Glycine‒Betaine has become as an interesting agronomic tool that aimed to increase tolerance to environmental stresses such as low temperatures that cause damage to herbaceous shoots and leaves in young chestnut trees.

Following traumatic brain injury (TBI), secondary brain damage due to chronic inflammation is the most predominant cause of the delayed onset of mood and memory disorders. Currently no therapeutic approach is available to effectively mitigate secondary brain injury after TBI. One reason is the blood-brain barrier (BBB), which prevents passage of most therapeutic agents into the brain. Peptides have been among the leading candidates for CNS therapy due to their low immunogenicity and toxicity, bioavailability, and ease of modification. In this study, we demonstrated that non-invasive intranasal administration of KAFAK, a cell penetrating anti-inflammatory peptide, traversed the BBB in a murine model of diffuse, moderate TBI. Notably, KAFAK treatment reduced the production of pro-inflammatory cytokines that contribute to secondary injury. Furthermore, behavioral tests showed improved or restored neurological, memory, and locomotor performance in KAFAK-treated mice. This study demonstrates KAFAK's ability to cross the blood-brain barrier, to lower pro-inflammatory cytokine levels in vivo, and to restore function after a moderate TBI.

Fowlpox virus (FPV) has been used as a vector for many years. To date, surprisingly, very little data exist on the persistence of fowlpox vaccines in chicken tissues, or what kind of immune cells respond to the vaccination at the site of inoculation. Although both humoral and cellular mediated immunity (CMI) play a part in overall immunity against FPV, little is known regarding the cell-mediated immune responses to FPV infection. The main aim of this paper was to measure persistence of the recombinant fowlpox vaccine in the skin tissues following vaccination. The results showed that the recombinant FPVs do not persist for long, and are cleared by 6 days post-vaccination (dpv). The response of immune cells (macrophages, B cells, CD4+ and CD8+ T cells) that infiltrating the site of vaccination was estimated.

Food systems will need to undergo considerable transformation. To be better prepared for and resilient to uncertainty and disturbances in the future, resource users and managers need to further develop knowledge about the food and farming system, with its dominating feedback structures and complexities, and to test robust and integrated system-based solutions. This paper investigates how participatory system dynamics modeling can be adapted to groups at the community level with low or no formal educational background. The paper also analyzes the refinement of workshop participants’ mental models as a consequence of a participatory system dynamics intervention. For this purpose, we ran two workshops with small-scale farmers in Zambia. Analysis of workshop data and post-workshop interviews shows that participatory system dynamics is well adaptable to support an audience-specific learning-by-doing approach. The use of pictures, objects and water glasses in combination with the basic aspects of causal loop diagramming makes for a well-balanced toolbox. Participants acquire understanding that is also relevant beyond systems thinking in that is offers a range of practical insights such as a critical evaluation of common food security strategies.

Background: COVID-19 is a disease of the elderly as 95% of deaths related to COVID-19 occur in people over 60 years of age. Despite the urgent need for a preventive treatment there are currently no serious leads, other than the vaccination. Objective: To find a preventive treatment of COVID-19 in elderly patients. Design: Retrospective case-control study. Setting: Robertsau Geriatric Hospital of the University Hospitals of Strasbourg, France. Patients: 179 elderly patients who had been in contact with the SARS-CoV-2, of whom 89 had tested RT-PCR-positive (COVID-pos) for the virus and 90 had tested RT-PCR-negative (COVID-neg). Measurements: Treatments within 15 days prior to RT-PCR (including antihypertensive drugs, antipsychotics, antibiotics, nonsteroidal anti-inflammatory drugs, proton pump inhibitors (PPIs), paracetamol, anticoagulant, oral antidiabetics (OADs), corticosteroids, immunosuppressants), comorbidities, symptoms, laboratory values, and clinical outcome were all collected using the electronic patient record. Results: COVID-pos patients more frequently had a history of diabetes (P=.016) and alcoholism (P=.023), a lower leukocyte count (P=.014) and a higher mortality rate– 29.2% versus 14.4% – (P=.014) when compared to COVID-neg patients. Patients on PPIs were 2.3 times less likely (odds ratio [OR] = 0.4381, 95% confidence interval [CI] [0.2331, 0.8175], P=.0053) to develop COVID-19 infection, compared to those not on PPIs. No other treatment decreased or increased this risk. COVID-19 patients on antipsychotics (P=.0013) and OADs (P=.0166) were less likely to die. Limitations: retrospective study. Conclusion: PPIs treatment lowered the risk of development of COVID-19 infection, and antipsychotics and OADs decreased the risk of mortality in geriatric patients. If further studies confirm this finding, PPIs could be used preventatively in the elderly in this pandemic context. Moreover, OADS and antipsychotics should be tested in clinical trials.

Aspalathin, a C-glucosyl dihydrochalcone, has previously been shown to protect cardiomyocytes against hyperglycemia-induced shifts in substrate preference and subsequent apoptosis. However, the precise gene regulatory network remains to be elucidated. To unravel the mechanism and provide insight into this supposition, the direct effect of aspalathin in an isolated cell-based system, without the influence of any variables, was tested using an H9c2 cardiomyocytes model. Cardiomyocytes were exposed to high glucose (33 mM) for 48 hours before post-treatment with or without aspalathin. Thereafter, RNA was extracted and RT2 PCR Profiler Arrays were used to profile the expression of 336 genes. Results showed that, 57 genes were differentially regulated in the high glucose or high glucose and aspalathin treated groups. STRING analysis revealed lipid metabolism and molecular transport as the biological processes altered after high glucose treatment, followed by inflammation and apoptosis. Aspalathin was able to modulate key regulators associated with lipid metabolism (Adipoq, Apob, Cd36, Cpt1, Pparγ, Srebf1/2, Scd1 and Vldlr), insulin resistance (Igf1, Akt1, Pde3 and Map2k1), inflammation (Il3, Il6, Jak2, Lepr, Socs3, and Tnf13) and apoptosis (Bcl2 and Chuk). Collectively, our results propose that aspalathin could reverse metabolic abnormalities by activating Adipoq while modulating the expression of Pparγ and Srebf1/2, decreasing inflammation via Il6/Jak2 pathway, which together with an observed increased expression of Bcl2 prevents myocardium apoptosis.

We present multi-sensor measurements from satellites, unmanned aerial vehicle, marine radar, thermal profilers and repeated conductivity-temperature-depth casts made in the Kara Gates strait connecting the Barents and the Kara Seas during spring tide in August 2021. Analysis of the field data during an 18-hour period from four stations evidence that a complex sill in the Kara Gates is the site of regular production of intense large-amplitude nonlinear internal waves. Satellite data show a presence of a relatively warm northeastward surface current from the Barents Sea toward the Kara Sea attaining 0.8-0.9 m/s. Triangle-shaped measurements of three thermal profilers revealed pronounced vertical thermocline oscillations up to 40 m associated with propagation of short-period nonlinear internal waves of depression generated by stratified flow passing a system of shallow sills in the strait. The most intense waves were recorded during the ebb tide slackening and reversal when the background flow was predominantly supercritical. Observed internal waves had wavelength of ~100 m and travelled northeastward with phase speeds of 0.8-0.9 m/s. The total internal wave energy per unit crest length for the largest waves was estimated to be equal to 1.0-1.8 MJ/m.

Methyl Salicylate (MS), the principal constituent of Wintergreen oil (WO) was obtained from acetyl salicylic acid (ASA) by sequential transesterification-esterification reaction promoted by NbCl5for the first time. The reagents were added simultaneously, and the reaction process involved the transesterification and esterification reactions, which were accompanied by thin layer chromatography and gas chromatography. The conversion rate via GC was 100%, and the MS yield was 94%. A cytotoxicity of 50% and 64% for cultured S. aureus and metastatic melanoma cells, respectively, was observed for a concentration of 0.6 mg/mL, whereas no cytotoxicity for non-tumor cells was observed for this concentration, and it is considered to be the optimum concentration.

Staphylococcus aureus mastitis remains a major challenge for dairy farming. Here, 24 mice were immunized and divided into four groups: G1: control; G2: Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF) DNA vaccine; G3: F0F1 ATP synthase subunit α (SAS), succinyl-diaminopimelate (SDD), and cysteinyl-tRNA synthetase (CTS) recombinant proteins; and G4: SAS+SDD+CTS plus GM-CSF DNA vaccine. The lymphocyte subpopulations and the intracellular interleukin-17A (IL-17A) and interferon-γ production in the draining lymph node cells were immunophenotyped by flow cytometry. The immunophenotyping and lymphocyte proliferation was determined in spleen cells cultured with and without S. aureus stimulus. Immunization with S. aureus recombinant proteins generated memory cells in draining lymph nodes. Immunization with the three recombinant proteins plus GM-CSF DNA led to an increase in the percentage of IL-17A+ cells among overall CD44+ (memory), T CD4+, CD4+ T CD44+ CD27-, γδ TCR, γδ TCR+ CD44+ CD27+ and TCRVγ4+ cells. Vaccination with S. aureus recombinant proteins associated with GM-CSF DNA vaccine downregulates TH2 immunity. Immunization with the three recombinant proteins plus the GM-CSF DNA led to a proliferation of overall memory T, CD4+ and CD4+ TEM cells upon S. aureus stimulus. This approach fostered type 3 immunity, suggesting the development of a protective immune response against S. aureus.

This research presents an ensemble model developed to enhance the safety of bedridden patients in healthcare settings. The model utilizes a unique dataset capturing six typical movements performed by patients laying in bed, such as rolling over, falling off the bed, etc. The aim is to automate the classification of these movements, thereby enabling real-time monitoring of patients without the constant presence of hospital personnel in the room, a common practice in current healthcare settings. The dataset is preprocessed and balanced using the Synthetic Minority Over-sampling Technique, and then split into training and test sets for model training and evaluation. Three different models are explored: a Decision Tree Regressor, a Gradient Boosting Regressor, and a Bagging Regressor. The Bagging Regressor is an ensemble model that utilizes the Decision Tree Regressor as its base regressor. Each model’s performance is evaluated using accuracy, R2 score, and Mean Squared Error on both the training and test sets. The ensemble model demonstrates promising results, indicating the potential of machine learning to improve patient safety in healthcare settings. The study also employs K-Fold cross-validation and learning curves to validate the robustness of the ensemble model. This research contributes to the growing body of knowledge on the application of machine learning in healthcare and opens up new avenues for improving patient safety through real-time monitoring and classification of patient movements.

The study assesses the direct effects of climate change by 2060, including extreme events, on the productivity of regional crop farming and livestock in Greece, and the broader socio-economic effects on the agri-food and other sectors. Different approaches (i.e., agronomic models, statistical regression models, equations linking thermal stress to livestock output) were combined to estimate the effects on productivity from changes in the average values of climatic parameters, and subsequently the direct economic effects from this long-term climate change. Recorded damages from extreme events together with climatic thresholds per event and crop were combined to estimate the direct economic effects of these extremes. The broader socio-economic effects were then estimated through input-output analysis. Under average levels of future extreme events, the total direct economic losses for the Greek agriculture due to climate change will be significant, from €437 million/ year to €1 billion/ year. These losses approximately double when indirect effects on other sectors using agricultural products as inputs (e.g., food and beverage, hotels, restaurants) are considered, and escalate further under a tenfold impact of extreme events. Losses in the GDP and employment are moderate at the national level, but significant in regions where the contribution of agriculture is high.

Conduction of vasodilator signals plays an important role in the coordination of blood flow distribution. It is thought that endothelium-dependent vasodilation’s are conducted by electrotonic spread through gap junctions of the endothelial cell hyperpolarization generated at the stimulation site. However, nitric oxide (NO) was found to reduce the propagation of vasodilator responses, suggesting the participation of this signaling molecule in the mechanism of conduction. Mouse cremasteric arterioles were stimulated through micro-application of ACh or the NO donor, S-nitroso-N-acetylpenicillamine (SNAP) and the responses were evaluated at the stimulation site (local) and at sites located 500, 1000 and 2000 µm upstream from the vessel segment stimulated with ACh. The response to ACh spread along the entire vessel showing a slight decay and, in contrast, the dilation evoked by SNAP was restricted to the stimulation site, independently of the magnitude of the response. Blockade of NO production with 100 µM NG-nitro-L-arginine methyl ester (L-NAME) or 100 µM NG-nitro-L-arginine (L-NA) reduced the resting diameter by 10-12% (n=4), but the combination of two NO blockers enhanced the basal vasoconstrictor tone by ~38% (n=5) and inhibited the local (~45%) and conducted (~20-35%) responses to ACh. Interestingly, the conduction of ACh-induced vasodilation increased along the vessel length in the presence of L-NAME and L-NA. In addition, endothelial cell hyperpolarization blockade exclusively at the stimulation site through microsuperfusion of tetraethylammonium inhibited the local vasodilation, but not the conduction of the response. These results indicate that ACh activates a NO-sensitive regenerative vasodilator mechanism that is coupled to the activation of NO production and endothelium-dependent hyperpolarization along the vessel length.

Chelating gels may assist initially in root canal preparations to help establish a glide path. While irrigation surveys have investigated liquid chelators, and gels to a minor extent, no endodontic survey has focused on EDTA gels, and why clinicians use them. All 395 members of the Australian Society of Endodontology (ASE) were emailed an 11-question survey concerning chelation gel usage via Qualtrics. Paper copies were also distributed at ASE events. Descriptive statistics was performed for practitioner and chelating gel data. Cross-tabulations of practitioner type with case percentage usage of gels were analyzed with the chi square test (adjusted P value <0.0083). The overall response rate was 181/395 (46%). For 174 eligible responses, those who never/rarely used a gel was: endodontic residents 12/14 (86%), endodontists 53/71 (75%), general dentists 39/86 (45%), and other members 0% (0/3). Most gel users said that gels helped establish a glide path. Those who never/rarely used chelating gels commented that they held no benefits over liquid EDTA. Endodontists were less likely to use a chelation gel than general dentists (P <0.0083). Older members had higher gel usage than younger members (P <0.0083), indicating a possible trend to diminished gel usage over time amongst ASE members.

This article focuses on generating an alternative in order to identify traffic officers during driving. This research employed the latest You Only Look Once (YOLO) model, using a six-phase methodology: data collection, data preparation involving resizing and labeling, implementation of various filters to avoid overfitting, model training, prediction evaluation, and result interpretation. The YOLO model was applied across three iterations using a dataset of 1862 images. To enhance training efficiency and detection speed, the graphics processing unit (GPU) acceleration was utilized, further enhancing the experimental process. The results of this study revealed that the YOLOv8x variant produced the most promising results. This proposed model attained a remarkable F1 score of 0.95, bolstered by a confidence score of 0.631, with the potential for an increase to 0.80 in confidence without significantly compromising the F1-score. These findings are poised to make a substantial contribution to the broader research landscape, particularly in advancing the effectiveness of detection models for traffic officers.

The study of the human microbiome has been a hot topic during the last decades and more recently the skin microbiome has aroused great interest as well. So that, scientists have turned their attention to the role of the skin microbiome in skin health, and its relationship with different disorders as atopic dermatitis, psoriasis, acne, and rosacea, among others. Numerous studies and investigations have been performed to study the role of pre and probiotics as nutraceuticals in the treatment of skin diseases, with growing evidence along the last ten years. This review gathers information on the use of “nutribiotics” in skin care health, focus on the main dermatological diseases and other skin conditions. Clinical studies show that nutribiotics could be a new tool to improve skin health and pre, pro, syn, post and para-probiotics seem to be beneficial on several skin disorders, as well as repairing the skin barrier, or promoting wound healing. In conclusion, skin microbiome has emerged as a new field with high potential to develop disruptive solutions to manage skin health and disease. Future advances in this field may facilitate the treatment of skin dysbiosis being nutribiotics a suitable method for skin care.

A novel compressible real gas 1D finite volume thermofluid network modelling methodology is proposed that can be applied in the analysis of supercritical CO₂ (sCO2) power cycles. It is applied to simulate centrifugal compressor performance via a mean line approach that directly solves the mass, energy, and momentum balance equations for the discretized flow channels within the machine along with the associated loss models, component characteristics, and applicable compressible real gas equation of state. This can be integrated seamlessly with the rest of the power cycle components like pipes, valves, heat exchangers, etc., thereby eliminating the need for static performance maps and the associated difficulties to ensure similarity over the whole range of operation. This direct simulation of the internal flows also makes it possible to do integrated cycle design optimization that includes the geometry of the compressors, and to simulate fast transients for dynamic analysis. The methodology was applied to simulate well-documented air and sCO2 centrifugal compressors and compared the generated results with that of conventional thermofluid network incompressible and compressible ideal gas approaches. The results indicate that the proposed compressible real gas approach can capture the stagnation pressure changes and isentropic efficiencies with good accuracy for both cases over the whole range of mass flow rates and shaft rotational speeds. In contrast, the conventional thermofluid network incompressible and compressible ideal gas approaches are only applicable in selected regions of the fluid property regime and suffer from discretization errors and inappropriate treatment of the relationship between stagnation and static pressures. Furthermore, comparative analyses between the newly proposed approach and the traditional mechanical energy balance method are performed, showing that the latter approach needs to be discretized more finely through the compression process to correctly capture the polytropic compression path shape, whereas the former more accurately captures the stagnation pressure changes through the analyzed compressors with only a single increment per compressor component.

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

Two beneficial characteristics of aircraft generators are having armature windings and PM excitation sources placed on the stator side (maintenance and thermal management) and having a clear-cut rotor without permanent magnets or excitation windings (vulnerable at high speeds due to associated centripetal mechanical stresses). Within this framework, a doubly-salient permanent magnet (DSPM) generator was conceived by optimizing the stator size and rotor structure to minimize the torque ripple and maximize the RMS voltage value per turn of each generator phase. A Multi-Objective Design Strategy based on a 2D finite element analysis was used, being set to have characteristics closest to optimal for a Boeing 767 turbine, that is, the necessary electromotive force for a required power of 90 kW at 3000 rpm, feeding a simplified Boeing 767 electrical power distribution system. The results show that the machine could not deliver the required power at 3000 rpm since the 2D finite elements analysis demonstrates that the 2D model gives optimistic results when compared with the 3D FEM model. However, with a 3D finite element analysis of the machine feeding the aircraft load, it was seen that the machine’s efficiency is 92%, suggesting this machine can be a plausible solution.

A Friedmann-Lemaitre-Robertson-Walker space-time model with all curvatures k=0,±1 is explored in f(R,T) gravity. The solutions are obtained via the parametrization of the scale factor that leads to a model transiting from a decelerated universe to an accelerating one. The physical features of the model are discussed and analysed.

Onion skin waste (OSW), the primary non-edible byproduct from onion processing, offers a renewable source of bioactive compounds. This study aims to valorize OSW through subcritical water extraction (SWE), aligning with circular economy and biorefinery principles. SWE was carried out at 145 °C, 50 bar and 50 min in a discontinuous reactor, producing a phenolic-rich extract (32 ± 3 mg/g), dominated by protocatechuic acid (20 ± 3 mg/g), quercetin-4´-O-glucoside (7.5 ± 0.2 mg/g), and quercetin (3.2 ± 0.6 mg/g). Additionally, it contains sugars (207 ± 20 mg sucrose-Eq/g), proteins (22.8 ± 1.6 mg BSA-Eq/g) and free amino acids (20.4 ± 1.2 mg arginine-Eq/g). Its phenolic richness determines its scavenging activity against ●NO and O2●- radicals, and its α-glucosidase and aldose-reductase inhibition without affecting α-amylase. Notably, the extract demonstrates significant α-glucosidase inhibition (IC50 = 76 ± 4 µg/mL), surpassing acarbose (IC50 = 129.5 ± 1.0 µg/mL), in both pure enzyme and cell culture tests without showing cytotoxicity on AGS, HepG2 and Caco-2 human cell lines. The extract’s bioactivity and nutritional content make it suitable for developing antioxidant and antidiabetic nutraceutical/food components, highlighting the SWE potential for OSW valorization without using organic solvents.

We present results of the detected voltage distribution of a quantum random number generator based on the photonic integration of semiconductor laser, delay interferometer and photodetector. We find that the integrated system behaves as expected for random number generation from gain-switched laser sources. The biggest advantage is that only electrical connections are needed to operate the system without the need for tricky and expensive optical alignment to external circuitry. We supply results showing that random bit stream created from the random numbers passes the NISTS statistical test suite tests; thus demonstrating the feasibility to generate random number via quantum means at gigabit/s rates from a single photonic integrated circuit. The results are backed by numerical simulations.

The development of potent antiviral agents is of utmost importance to combat the global burden of viral infections. Traditional antiviral drug development involves targeting specific viral proteins, which may lead to the emergence of resistant strains. To explore alternative strategies, we investigated the antiviral potential of antimicrobial peptidomimetic compounds. In this study, we evaluated the antiviral potential of short anthranilamide-based peptidomimetic compounds 1-17 against two viruses: Murine Hepatitis Virus 1 (MHV-1-single stranded RNA virus) which is a surrogate of human coronaviruses and Herpes Simplex Virus 1 (HSV-1-double stranded DNA virus). The half-maximal inhibitory concentration (IC50) values of these compounds were determined in vitro to assess their potency as antiviral agents. Compounds 11 and 14 displayed the most potent inhibitory effect with IC50 values of 2.38μM, and 6.3μM against MHV-1 while compounds 9 and 14 showed IC50 values of 14.8μM and 13μM, against HSV-1. Multiple antiviral assessments and microscopic images obtained through transmission electron microscopy (TEM) collectively demonstrated that these compounds exert a direct influence on the viral envelope. Based on this outcome, it can be concluded that peptidomimetic compounds could offer a new approach for the development of potent antiviral agents.

Background: Understanding the factors that influence the market entry, exit, and stability of community pharmacies (i.e., market dynamics) is important for stakeholders ranging from patients to health policymakers and small business owners to large corporate institutions. The purpose of this article is to provide an update to a 15-year ecological comparison for the market dynamics of Minnesota community pharmacies from 2002 to 2017 [1]. Objectives: The first objective was to update the 15-year study [1] by describing the market dynamics of community pharmacies for each county in the state of Minnesota every five years over a 20-year period (i.e., 2002-2022). The second objective was to update the 15-year study by describing the number and proportion of community pharmacies for each county in the state of Minnesota every five years over a 20-year period (i.e., 2002-2022) by (1) ‘Business Organization Structure’ and (2) ‘Pharmacy Type.’ The third and fourth objectives were new for the 2022 study. In response to evolutionary trends in the pharmacy market, objective three described the number of Minnesota licensed pharmacies located in-state and out-of-state between 2002 and 2022. Objective four described the primary type of service provided by licensed pharmacies categorized as out-of-state in 2002 and in 2022. Methods: Data were obtained from the Minnesota Board of Pharmacy, US Census Bureau, and Minnesota State Demographic Center for 2002, 2007, 2012, 2017, and 2022. Descriptive statistics were used to tabulate and summarize the findings and test associations between study variables. Results: Over the 20-year study period, the total number of community pharmacies in Minnesota remained steady. Findings for 2022 were similar to those for 2017 regarding the effects of population density and metropolitan designation on the market dynamics of community pharmacies and regarding the organizational structures and types of pharmacies. The findings revealed significant growth in the number of proportion of pharmacies licensed in Minnesota that were located out-of-state. In 2002, there were 283 of these pharmacies (19% of the total). By 2022, this grew to 960 (46% of the total). Over that 20-year period, the number of mail order and medical supply service pharmacies rose from 196 to 413. The number of specialty pharmacy distributors rose from 37 to 230 and the number of compounding pharmacies rose from 33 to 202. Discussion: The findings confirmed the shift over the past 20 years from traditional retail convenience models to healthcare access models based on population health metrics. National scalability was another detected shift in order to have profitable margins for some services and was feasible due to advances in technologies. Conclusion: The findings showed that community pharmacy distribution in Minnesota’s 87 counties shifted between 2002 and 2022 from traditional retail convenience models to healthcare access models based on population health metrics and to nationally scalable models based on economic pressures. This signals the need for not only new approaches for tracking community pharmacy market dynamics but also adjustments by community pharmacies to remain relevant in a new environment of patient care services.

Using a simple model for internal heat evolution and mass-internal heat relations found for rocky exo planetary objects in the inner solar system we have inferred the phases of volcanism at earth ( EA) or host star ages (SA) in 52 potentially habitable rocky exo planets. We have also calculated the internal tidal heat contributions and magnetic moments of these exo planets. Based on these results we have inferred the probability of existence of life favouring geophysical conditions in the above exo planets at EA and SA. In M star associated exo planets, occurrences of super flares and long night periods may pose problems for the development of advanced life

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

Evidence that early life exposure to acetaminophen causes neurodevelopmental injury in susceptible children has mounted for more than a decade. Evidence is diverse, including extensive work with laboratory animals, otherwise unexplained associations, factors associated with the metabolism of acetaminophen, and some limited studies in humans. Although evidence has reached an overwhelming level and has been reviewed in detail recently, some controversy remains. In this narrative review, some of those controversies are evaluated. First, the associations through time between acetaminophen use and the prevalence of neurodevelopmental disorders are considered. A systematic review reveals that the use of acetaminophen in the pediatric population was never tracked carefully, but historical events that affected use of the drug were documented and are sufficient to establish apparent correlations with changes in the prevalence of neurodevelopmental disorders. Second, problems with exclusive reliance on results from meta-analyses of large datasets and from studies involving small time frames of drug exposure are reviewed. Third, the potential bias in a study designed to separate the role of vaccines and acetaminophen in the induction of autism spectrum disorder (Autism 2008;12:293-307) is carefully evaluated. Finally, evidence demonstrating why some children are susceptible to acetaminophen-induced neurodevelopmental injury is examined. It is concluded that, at least among the factors considered, there is no valid rationale for controversy regarding the conclusion that early life exposure to acetaminophen causes neurodevelopmental injury in susceptible babies and small children.

Background: In Arizona Helicobacter pylori prevalence of infection among Navajo adults is about 62% and gastric cancer incidence rate is 3-4 times higher than that of the non-Hispanic White population. Aim: The aim of this study was to estimate the prevalence of specific H. pylori virulence factors (cagA and vacA) among Navajo patients undergoing and their association with gastric disease. Methods: Virulence genes, cagA and vacA, in H. pylori were investigated in gastric biopsies from 96 Navajo patients over age 18 who were undergoing esophagogastroduodenoscopy. Biopsies from the antrum and fundus were used for molecular characterization to determine cagA type and number of EPIYA motifs and presence of alleles in the signal (s) and medium (m) regions of the vacA gene. Results: H. pylori infection was found in 22.9% of the biopsy samples. The cagA gene amplified in 57.6% of samples and showed a predominant “Western cagA” type, with the EPIYA-ABC motif (45.4%), most prevalent. The vacA allele s1bm1 was the most prevalent (54.5%). Conclusions: H. pylori genotypes were predominantly cagA Western-type and ABC EPIYA motifs. The vacA s1bm1 genotype was the most prevalent and seemed to be associated with gastritis. American Indian/Alaska Native populations are at higher risk for gastric cancer. It is important to identify genotypes of H. pylori and virulence factors involved in the high prevalence of H. pylori and associated disease among the Navajo population.

Distance learning has assumed a relevant role in the Educational scenario. The use of Virtual Learning Environments contributes to obtain a substantial amount of educational data. In this sense, the analyzed data generate knowledge used by institutions to assist managers and professors in strategic planning and teaching. The discovery of students’ behaviors enables a wide variety of intelligent services for assisting in the learning process. This article presents a literature review in order to identify the intelligent services applied in distance learning. The research covers the period from January 2010 to May 2021. The initial search found 1,316 articles, among which 51 were selected for further studies. Considering the selected articles, 33% (17/51) focus on learning systems, 35% (18/51) propose recommendation systems, 26% (13/51) approach predictive systems or models, and 6% (3/51) use assessment tools. This review allowed to observe that the principal services offered are recommendation systems and learning systems. In these services, the analysis of student profiles stands out to identify patterns of behavior, detect low performance and identify probabilities of dropouts from courses.

Gastric emptying rate (GER) may impact diabetes and obesity in humans and could provide a method to reduce canine weight gain. Starch, the most common source of carbohydrates (CHOs) in pet food, is classified as rapidly or slowly digestible, or resistant to digestion. This study investigated starch source effects in commercial extruded dog foods on the GER of 11 healthy adult Siberian Huskies (5.63±0.72 years; mean±SEM). Test diets were classified as traditional, grain-free, whole-grain, and vegan. Dogs received each diet once, a glucose control twice, and acetaminophen (Ac) as a marker for GER in a randomized, partially-replicated, 6x6 Latin square design. Pre- and post-prandial blood samples were collected at 16 timepoints from -15 to 480 minutes. Serum Ac concentrations were assessed via standard spectrophotometric assays and fitted with a mathematical model to estimate parameters of GER. Data was analyzed using a repeated measures ANOVA, followed by a Tukey-Kramer post-hoc test when significant (p<0.05). More total emptying (p= 0.0430) occurred at faster rate (p=0.0668) in dogs fed the grain-free diet, which contained the lowest total starch (34.03 ± 0.23%) and highest resistant starch (0.52 ± 0.007%). This research may benefit future diet formulations to reduce the prevalence of canine weight gain.

(1) Background: Stimulating oropharyngeal transient receptor potential (TRP) channels inhibits muscle cramping by triggering a supraspinal reflex to reduce α-motor neuron hyperexcitability. This study investigated whether longer stimulation of TRP channels via mouth rinsing with PJ is more effective than drinking PJ at inhibiting an electrically induced muscle cramp (EIMC); (2) Methods: Tibial nerve in 11 cramp-prone adults were percutaneously stimulated to elicit an EIMC of flexor hallucis brevis in three trials 1-week apart. At cramp onset participants received mouth rinsing and expelling PJ (25 mL), ingesting PJ (1 mL∙kg-1 body-mass [BM]), or ingesting water (1 mL∙kg-1 BM). Cramp onset and offset by electromyography and severity of discomfort was recorded using a visual analogue scale (VAS); (3) Results: Median time to cramp cessation as a percentage of water was 82.8% ± 14.634 and 68.6% ± 47.782 for PJ ingestion and mouth rinse respectively. These results had large variability and no statistically significant difference was observed. There were also no differences in perceived cramp discomfort between conditions, despite hazard ratios for time to VAS = 0 higher than water for PJ ingestion (22%) and mouth rinse (35%) (p = 0.66 and 0.51 respectively); (4) Conclusions: Data suggest no difference in cramp duration and perceived discomfort between PJ and water.

Poly lactic acid (PLA) has made inroads for commercial market segment with lot many unique characteristics such as tenacity, low flame rate, moisture regain percentage, loss of ignition percentage, heat of combustion, UV resistance, Elastic recovery and higher melting point allowed it to be the fastest moving material in today's commercial market. An attempt has been made to test the feasibility and biocompatibility aspect of PLA with cement mix. The basic strength and physical test results were carried out and published in an article, to the continuation of the work, micro-structural study was conducted to evaluate the elemental characteristics. Thermo gravimetric analysis revealed that PLA either in granular form or filament will hold good for the inclusion into construction applications, provided degradation aspects are to be looked out for improvisation. From DSC it was found that PLA in filament form is the best inclusion material for construction application, however the tenacity of fibers has to checked, as currently available filaments in market does not have high tenacity value. From EDX reports, 30% inclusion of PLA as replacement for fine aggregate has constituent members as Calcium carbonate(CaCO3), Silica(SiO2) and Wollastonite (CaK) resulted in best composition among the rest. FESEM images revealed that, proper gradation in size, rough surface of PLA granular form or filament form will definitely enhance the mechanical/physical or even chemical behavior of PLA.

This paper aims in studying the effect of vermicompost on soil and growth of the plant Sesamum indicum L. by measuring the its various growth and yield components. For this purpose, a mixture of textile mill sludge, cow dung and saw dust have been mixed in different ratios to produce vermicompost by using the earthworm Perionyx excavates and was compared with inorganic (NPK) and organic fertilizer (FYM). The results of soil quality revealed that the porosity, water holding capacity (WHC), cation exchange capacity (CEC) and occurrence of macronutrients were significantly increased and the particle density were decreased in treatment with 100% vermicompost (VC) followed by soil treated with 50% VC + 50% NPK, on contrary, reduction in porosity, WHC, CEC were noted in NPK treated plots. The effect of vermicompost on plant growth components (root, shoot, leaf area index, branch, DMP) and yield components (pod number, weight, length, seed weight, number of seed, seed yield) were significantly higher in the plots treated with 50% VC + 50% NPK followed by 100% vermicompost than the plots treated only with FYM and NPK. The significant growth upon using vermicompost was accounted by its nutrients composition over other fertilizers.

The impact of riparian wetlands on the cycling, retention and export of nutrients from land to water varies according to local environmental conditions and is poorly resolved in catchment management approaches. To determine the role a specific wetland might play in a catchment mitigation strategy, an alternative approach is needed to the high frequency and spatially detailed monitoring programme that would otherwise be needed. Here, we present a new approach using a combination of novel and well-established geochemical, geophysical and isotope ratio approaches. This was developed and tested against a 2-year high-resolution sampling programme in a lowland permeable wetland in the Lambourn catchment, UK. The monitoring programme identified multiple pathways and water sources feeding into the wetland, generating large spatial and temporal variations in nutrient cycling, retention and export behaviours within the wetland. This complexity of contributing source areas and biogeochemical functions within the wetland were effectively identified using the new toolkit approach. We propose that this technique could be used to determine the likely net source/sink function of riparian wetlands prior to their incorporation into any catchment management plan, with relatively low resource implications when compared to a full high frequency nutrient speciation and isotope geochemistry-based monitoring approach.

The sublimation enthalpies of four highly energetic materials (HEMs): triacetone triperoxide (TATP), 2,4-dinitrotoluene (DNT), 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitrohexahydro-s-triazine (RDX) deposited on stainless steel (SS) substrates were determined by optical fibre coupled-grazing angle probe (GAP) FTIR spectroscopy and thermogravimetric analysis (TGA) for bulk crystaline HEMs samples. The desorption energy of RDX on SS was also studied using grazing angle FTIR microscopy. Metastable phases of 2,4-DNT and TNT were observed when deposited on SS, and their sublimation enthalpies values were obtained by GAP measurements and compared with those for the crystalline phases. The sublimation enthalpies for the alpha phase RDX was also determined by TGA measurements. A layer of crystalline beta phase RDX was observed on SS, and it's sublimation enthalpies was determinate by GAP. PLS calibration curves for the surface concentrations of RDX on SS were generated using GAP to determinate the surface concentration with time at different temperatures.

Background: The assessment of the incidence and characteristic of acute and chronic post-operative endophthalmitis (POE) after cataract surgery in Poland during 2010 - 2015. Patients and methods: All hospitalizations of patients, in the National Database of Hospitalizations, who underwent cataract surgery alone or in combined procedures in Poland between January 2010 and December 2015, with a billing code of endophthalmitis, were selected. Acute endophthalmitis was identified if symptoms occurred within 1 - 42 days from the cataract surgery and chronic endophthalmitis if symptoms occurred ≥ 43 days after cataract surgery, respectively. Results: In total, 1331 cases of POE after 1,218,777 cataract extractions were identified. The overall incidence of POE decreased from 0.125% in 2010 to 0.066% in 2015. In multiple logistic regression analyses, increasing age was significantly associated with acute POE, while type II diabetes mellitus, extracapsular cataract extraction and one-day surgery were significantly associated with chronic POE. The combined cataract surgery and male sex were significant risk factors for both acute and chronic POE. A total of 62.51% of all eyes affected by POE received antibiotic treatment and 37.49% had vitrectomy treatment. Conclusions: During the study period, the total incidence of post-operative endophthalmitis after cataract surgery decreased significantly.

Purpose. Moraxella is an ocular bacterial pathogen isolated in cases of keratitis, conjunctivitis, and endophthalmitis. Gram-negative brick-shaped diplobacilli from ocular specimens, and slow growth in culture, are early indications of Moraxella ocular infection; however, identifying Moraxella to species can be complex and inconsistent. Methods. In this study, bacteria consistent with Moraxella were identified to species using: 1) DNA sequencing coupled with vancomycin susceptibility, 2) MALDI-TOF Mass Spectrometry, and 3) Biolog ID System. Study samples consisted of 9 ATCC Moraxella controls, 82 isolates from keratitis, 21 isolates from conjunctivitis, and 4 isolates from endophthalmitis. Results. The ATCC controls were correctly identified. For keratitis, 66 (80.5%) were identified as M. nonliquefaciens, 7 (9.0%) as M. lacunata, 5 (6%) as M. osloensis, 2 (2.5%) as Acinetobacter lwoffi, 1 (1.0%) as M. bovis/nonliquefaciens, and 1 (1.0%) as M. osloensis/nonliquefaciens. For conjunctivitis, 9 (43.0%) were identified as M. osloensis, 6 (29.0%) as M. nonliquefaciens, 3 (14.3%) as Roseomonas, 2 (9.5%) as Acinetobacter (parvus, junii), and 1 (4.5%) as M. catarrhalis/M. nonliquefaciens. From endophthalmitis, 3 of 4 of the isolates were M. nonliquefaciens. Overall, M. nonliquefaciens and M. osloensis were identified in 70% (75 of 107) and 13% (14 of 107) of cases, respectively, totaling 83% (89 of 107). Conclusions. M. nonliquefaciens and M. osloensis are important bacterial pathogens of the eye as determined by DNA sequencing, MALDI-TOF MS, and Biolog. Although Moraxella catarrhalis is a clinical pathogen, other species of Moraxella appear to have a prominent role in eye infections.

In radiotherapy, accurate deposition of energy to the targeted volume is vital to ensure effective treatment. Gel dosimeters are attractive detection systems, as tissue substitutes with potential to yield three-dimensional dose distributions. Radio-fluorogenesis is creation fluorescent chemical products in response to energy deposition from high-energy radiation. This report shares studies of a radio-fluorogenic gel dosimetry system, gelatin with coumarin-3-carboxlyic acid (C3CA), for the quantification of imparted energy. Aqueous solutions exposed to ionizing radiation result in the production of hydroxyl free radicals through water radiolysis. Interactions between hydroxyl free radicals and coumarin-3-carboxylic acid produce a fluorescent product. 7-hydroxy-coumarin-3-carboxylic acid has a blue (445 nm) emission, following UV to near UV (365–405 nm) excitation. Effects of C3CA concentration and pH buffers were investigated for this system. The response of the system was explored with respect to strength, type, and exposure rate of high-energy radiation. Results show a linear dose response relationship with a dose-rate dependency and no energy or type dependencies. This report supports the utility of gelatin-C3CA for phantom studies of radio-fluorogenic processes.

In vitro studies show that diclofenac inhibits enzymatic steroid glucuronidation. This study was designed to investigate the influence of diclofenac on the excretion of stanozolol and 3'-hydroxystanozolol via analyses in hair, blood and urine in vivo in a rat study. Brown Norway rats were administered with stanozolol (weeks 1-3) and diclofenac (weeks 1-6). Weekly assessment of steroid levels in hair was complemented with spot urine and serum tests. Levels of both stanozolol and 3'-hydroxystanozolol steadily increased in hair during stanozolol treatment and decreased post-treatment, but remained readily detectable for 6 weeks. In contrast, compared to control rats, diclofenac significantly reduced urinary excretion of 3’-hydroxystanozolol which was undetectable in most samples. This is the first report of diclofenac altering steroid metabolism in vivo, detrimentally affecting detection in urine, but not in hair which holds considerable advantages over urinalysis for anti-doping tests.

For the first time, few-layer graphene (FLG) nanosheets were synthesized by the method of self-propagating high-temperature synthesis (SHS) from biopolymers (starch and lignin). We suggested that biopolymers (lignin, tree bark) and polysaccharides, in particular starch, could be an acceptable source of native cycles for the SHS process. The carbonization of biopolymers under the conditions of the SHS process was chosen as the basic method of synthesis. Chemical reactions, under the conditions of the SHS process, proceed according to a specific mechanism of nonsothermal branched-chain processes, which are characterized by the joint action of two fundamentally different process-accelerating factors - avalanche reproduction of active intermediate particles and self-heating. The method of obtaining FLG nanosheets included the thermal destruction of hydrocarbons in a mixture with an oxidizing agent. We used biopolymers as hydrocarbons and ammonium nitrate as an oxidizing agent. Thermal destruction was carried out in the mode of SHS, heating the mixture in a vessel at a speed of 20–30 oC/min to 150-200 oC and keeping at this temperature for 15–20 min with the discharge of excess gases into atmosphere. A combination of spectrometric research methods, supplemented by electron microscopy data, has shown that the particles of the carbonated product powder in their morphometric and physical parameters correspond to FLG nanosheets. An X-ray diffraction analysis of the indicated FLG nanosheets was carried out, which showed the absence of formations with a graphite crystal structure in the final material. The surface morphology was also studied and the features of the IR absorption of FLG nanosheets were analyzed. It is shown that the developed SHS method makes it possible to obtain FLG nanosheets with linear dimensions of tens of microns and a thickness of not more than 1-5 graphene layers (several graphene layers).

Progress in laser-driven proton acceleration requires increasing the proton maximum energy and laser-to-proton conversion efficiency, while reducing the divergence of the proton beam. However, achieving all these qualities simultaneously has proven challenging experimentally, the increase in beam energy often coming at the cost of beam quality. Numerical simulations suggest that coupling multi-PW laser pulses with ultrathin foils could offer a route for such simultaneous improvement. Yet experimental investigations have been limited by the scarcity of such lasers and the need for very stringent temporal contrast conditions to prevent premature target expansion before the pulse maximum. Here, combining the newly commissioned Apollon laser facility that delivers high-power ultrashort (∼24fs) pulses, with a double plasma mirror scheme to enhance its temporal contrast, we demonstrate the generation of up to 35 MeV protons with only 5 J of laser energy. This approach also achieves improved laser-to-proton energy conversion efficiency, reduced beam divergence, and optimized spatial beam profile. Therefore, despite the laser energy losses induced by the plasma mirror, the proton beams produced by this method are enhanced on all accounts compared to those obtained under standard conditions. Particle-in-cell simulations reveal that this improvement results from the intensified electrostatic field caused by a more compact hot-electron distribution.

Numerical simulations of the sub-critical flow past a circular cylinder at the Reynolds number, Re=130,000 are performed using two numerical platforms, commercial, Ansys Fluent and open source, OpenFoam (finite volume method and large eddy simulation based on a differential equation for the sub-grid kinetic energy). An overview of the available experimental data and similar large eddy simulation studies is presented. A detailed analysis of all accumulated data demonstrates satisfactory agreement between them with a dispersion of the order of 10% (for the main integral flow parameters). A detailed comparison of the results obtained by single- and double-precision numerical methods using Ansys Fluent did not reveal any noticeable discrepancies for the integral and local flow parameters, as well as spectral characteristics. It is shown that the behavior of the dynamic system of the fluid dynamic equations computed with single precision is stable by Lyapunov and does not lead to any loss of accuracy. The reconstructed attractors of the dynamic systems in the phase space are limited by an ellipsoid.

Aluminium alloys are used for fabrication of fuel clad of research grade nuclear reactors as well as of several types of core components of high flux research reactors. In order to carry out design and safety analysis of these components, their mechanical and fracture properties are required by the designer. In this work, experiments have been conducted on tensile specimens machined from an aluminium alloy block to evaluate the material stress-strain curve. For evaluation of fracture properties, experiments have been conducted on disc shaped compact tension specimens in order to determine the fracture toughness of aluminium alloy. From crystal plasticity based finite element analysis and experimental data, a material damage parameter for prediction of crack initiation has been evaluated. The variation of the parameter for various values of initial a/W ratios of the disc-shaped CT specimens have been studied. It was observed that the damage parameter is independent of crack geometry and hence, it qualifies as transferable material property which can be used to predict crack initiation in a component of this material subjected to different kinds of loading conditions. In addition, the JR curves of the disc-shaped CT specimens have also been evaluated from experiments. The material damage parameter has also been used to study the crack initiation in single crystal fracture specimens with two different orientations. It was observed that the [111] orientation is more susceptible to crack initiation and propagation compared to the [100] orientation as the damage parameter is high in the ligament of the specimen ahead of the crack-tip for the same level of load. The results of the experiments and the material damage parameter shall be helpful for integrity analysis of fuel clad of research reactors as well as components of high flux research reactors.

The objective of this paper is to investigate the debonding behavior of the interface between continuously and discontinuously fiber reinforced thermoplastics using the climbing drum peel test. The study emphasizes the importance of considering different climatic boundary conditions due to the properties of thermoplastics. Specimens with varying moisture contents are prepared and tested. It is observed that an increase in moisture content initially results in a higher fracture surface energy being required to separate the two materials, but a further increase results in a decrease of the required energy. The study presents an explanatory model of increasing plasticization of the polymer due to increased polymer chain mobility, which results in more deformation energy being required to propagate the crack. The experiment is also modeled numerically for the first time with cohesive surfaces, which successfully reproduces the force-displacement curve in the experiment.

This study examines the performance of the Indian Monsoon Data Assimilation and Analy-sis (IMDAA) in predicting five extremely severe cyclonic storms (ESCS) over the Bay of Bengal. The Advanced Research version of the WRF (ARW) model is utilized for this analysis over the last two decades. The initial and lateral boundary conditions are derived from the IMDAA datasets with a horizontal resolution of 0.12° × 0.12°. Five ESCSs from the past two decades are considered: Sidr 2007, Phailin 2013, Hudhud 2014, Fani 2019, and Amphan 2020. The model is integrated up to 96 hours using double nested domains of 12 km and 4 km. Model performance is evaluated using the 4 km results, compared with available observational datasets, including the best-fit data from the India Meteorological Department (IMD), The Tropical Rainfall Measuring Mission (TRMM) satellite, and Doppler Weather Radar (DWR). The results indicate that IMDAA provides accurate forecasts for ESCSs Fani, Hudhud, and Sidr in terms of track, intensity, and mean sea level pressure, aligning well with IMD observational datasets. However, Sidr's track deviates more from the observations. The calculated mean absolute maximum sustained wind speed errors range from 8.4 m/s to 10.6 m/s from day-1 to day-4, while mean track errors range from 114 km to 496 km during the same period. Statistical analysis, including bias, mean error, and standard deviation, underscores the significance of ESCS prediction. The discussion also covers rainfall prediction, maximum reflectivity, and the associated structure of the storms.

Cities are especially vulnerable to heavy rainfall events and the associated flooding. Urban drainage systems are not dimensioned to handle extreme heavy rainfall events, there is a need to enhance the resilience of those systems. Nature-based solutions (NBS) have the potential to retrofit existing urban drainage systems by providing, among other benefits, storage volume. This study presents an approach for including NBS with different degrees of implementation in a 1D/2D model and investigates their potential for flood mitigation in a study area in Berlin. The analyzed NBS are infiltration systems (e.g. infiltration swales) dimensioned to return periods of T = 5 and 100 years, various green roofs and tree locations (e.g. tree trenches). The NBS are represented by SWMM LID elements. The results show that overall the mitigation effect of NBS declines with increasing rainfall intensities. However, infiltration systems dimensioned to T = 100 years achieve almost three times the flood reduction compared to systems dimensioned to T = 5 years, even during extreme heavy rainfall events (100 mm), resulting in a reduced total flood volume of 15.1% to 25.8%. Overall, green roofs (excluding extensive green roofs) provide the greatest flood reduction (33.5%), while tree locations have the least effect.

The methanation of CO2 is of great interest in power-to-gas systems and contributes to the mitigation of climate change through carbon dioxide capture and the subsequent production of high value-added products. This study investigated CO2 methanation with three Ni catalysts supported on Al2O3 and ZrO2, which were simulated using a mathematical model of a packed bed reactor designed based on their chemical kinetics reported in the literature. The simulated reactive system was fed with syngas obtained from residual coffee pulp, obtained after solvent phytochemical extraction process, under several gasification conditions. The results reflect a high incidence of catalyst support, preparation method, and syngas composition on CO2 conversion and CH4 selectivity. For all the syngas compositions, Ni/ZrO2 catalysts show the best values for CO2 conversion and CH4 selectivity for Ni/Al2O3 catalyst.

Relative contribution of different repair pathways to the radiation-induced DNA damage responses remains a challenging issue of studying the radiation injury endpoints. Comparative manifestation of homologous recombination (HR) after application of different radiation doses greatly determines an overall effectiveness of recovery in dividing cell after irradiation, since HR is an error-free mechanism intended for repair of DNA double strand breaks (DSB) during S/G2 phases of cell cycle. In this article, we present an experimentally observed evidence of dose-dependent shift in relative contribution of HR in human fibroblasts after X-ray exposure at doses 20-1000 mGy, which is also supported by quantitative modeling of DNA DSB repair. Our findings indicate that the radiation dose increase leads to dose-dependent decrease in relative contribution of HR into the entire repair process.

Small molecule modulators of neurotensin receptor 1 (NTSR1), a class A G protein-coupled receptor (GPCR), has been emerging as promising therapeutics for psychiatric disorders and cancer. Interestingly, a chemical group substitution of NTSR1 modulators can launch different downstream regulation, highlighting the significance of deciphering the internal fine-tuning mechanism. Here, we conducted synergistic application of Gaussian accelerated molecular dynamics simulation, conventional molecular dynamics simulation, and Markov state models (MSM) to investigate the underpinning mechanism of ‘driver chemical groups’ of modulators triggering inverse signaling. The result indicated that the flexibility of leucine moiety in NTSR1 agonists contributes to the inward displacement of TM7 through a loosely coupled allosteric pathway, while the rigidity of adamantane moiety in NTSR1 antagonists leads to unfavorable downward transduction of agonistic signaling. Furthermore, we found that R3226.54, Y3196.51, F3537.42, R1483.32, S3567.45 and S3577.46 may play a key role in inducing the activation of NTSR1. Together, our findings not only highlight the ingenious signal transduction within class A GPCRs, but also lay a foundation for the development of targeted drugs harboring different regulatory function of NTSR1.

Rare study on quantitative relationship between energetic impact of debris flows on the intensity and duration of growth disturbances of tree rings was carried out, partly due to lack of feasible approaches and detailed field evidence. In this study, we firstly determine the age of a recent debris flow derived from historic landslide deposits at Qingyang mountain (QYM) on the northeastern Tibet plateau by dendrogeomorphic technique. We acquired the quantitative data of annual widths of tree rings in history and confirmed the influence of debris flow rather than other factors (e.g. climatic event and inset outbreaking) in disturbing the growth of tree rings in a specific year. Using the approach, we determined the age of the debris flow at QYM occurred in 1982, which was speculated to be triggered by high monthly precipitation of July in 1982. Subsequently, based on the boundaries of historic debris flow identified on remote sensing images before and after 1982 and depth-integrated continuum model, we reconstructed the process of 1982-debris flow and obtained the kinematic energy of debris flow impacting on the sampled trees. Based on the study, we observed that two growth disturbance patterns of tree rings influenced by the reconstructed 1982-debris flow were revealed including growth suppression and asymmetric growth. A raw logarithm relationship between duration (i.e. lasting time for the disturbed tree rings to recover the initial width) and intensity of growth disturbances (i.e. growth suppression ratio of disturbed tree rings) was obtained. We concluded that there is a negative exponential relationship between simulated kinematic energy of debris flow impacting on the disturbed trees and time to recover the initial width of corresponding tree rings.

Abstract: The purpose of this study is to explore, from the perspective of government interven-tion, behavioral logic and game relationship among farmers, service organizations and the gov-ernment in the pest and disease control outsourcing system, as well as the endogenous motiva-tion of each subject. The results indicate that the stronger the willingness of each subject, the faster the stable state of joint pest and disease control among the three parties can be formed; In the case of implementing a single policy tool, the convergence rate of each party that imple-ments the regulatory policy alone is fast but may be unstable, while the rate is slow but more stable when a guidance- or incentive-based policy is solely applied; The effect of policy tool combination is much better than that of a single policy tool applied. The simultaneous imple-mentation of the three types of policy tools can form a policy system with both positive and negative mechanisms, which can maximize complementary and superposition effect.

The use of the commercial simulator Aspen Plus® could bring an amelioration in the accuracy of the predictions of the chemical species composition in the output streams of the anaerobic digestion process, due to availability of a broad library of thermodynamic and phenomena transport properties in this commercial package. In the present investigation, the process simulation model for anaerobic digestion, which was originally developed by Rajendran et al. [1], has been modified by including a stoichiometric-equilibria reactor to calculate the extent of the ionization of the molecules present in the anaerobic digestate. The refined model offers a more accurate prediction of the composition of the biogas because it delves on the chemical equilibrium of the gaseous stream and the anaerobic digestate. Additionally, the refined model allows to assess the possibility of upgrading the gaseous stream to biomethane degree via manufacturing of ammonium bicarbonate. This processing pathway relies on the stabilization of the anaerobic digestate by means of biomass ash-based treatment. First of all, the titration of the manure digestate with the hydrochloric acid showed that a dose of 3.18 mEq/g would be required to attain the targeted pH of zero-point charge, upon addition of the sewage sludge ash in a ratio to the manure digestate of 0.6 ± 0.2 %. Secondly, the profiles of ammonia, carbon dioxide, and methane found in the biogas agree with both the pH of the treated digestate and the processes described in for the simultaneously upgrading the biogas and the production of ammonium bicarbonate. The refined Aspen Plus® model presented in this article needs to be further developed to ensure the standards are attained in all output streams of stabilized anaerobic digestate, biomethane, and isolated added-value chemical fertilizers.

Despite being well established phenomena, solidification principles are experiencing tough challenges in their application to explain microscale transport phenomena in additive manufacturing melt pool. The problem becomes even more complicated when applied to multicomponent bulk metallic glass matrix composites (BMGMC) whose behavior is dubious and still not fully understood. The aim of the present study is to highlight pathways to overcome these challenges. A comprehensive nucleation and growth model based on original KGT theory and Rappaz modification is proposed encompassing actual transient thermophysical BMGMC data to predict evolving microstructure during additive manufacturing. The model is aimed at pictorial representation of in-situ ductile phase dendrite evolution from melt pool during solidification using two-dimensional cellular automaton (CA) methods. It is proposed to be coded in MATLAB® using commercial simulation code ABAQUS® at back end for macroscopic heat transfer model. The results will be compared with experimental values for validation.

In this study, we present more than 8 years of observations of the quasi-16-day wave (Q16DW) in the mesosphere and lower thermosphere (MLT) wind at middle latitudes observed by the Mengcheng (33.4°N, 116.5°E) meteor radar. The long-term variation in amplitudes calculated from the data between April 2014 and December 2022 shows enhanced wave activity during winter and early spring (near equinox) and suppressed wave activity during the summer. The Q16DWs are relatively weak in the meridional wind. During the winter months, the Q16DWs in the zonal component exhibit a burst below 85 km, and their amplitudes reach up to 10 m/s. In the early spring, the Q16DWs strengthen above 90 km with amplitudes in excess of 12 m/s. The phase differences between the zonal and meridional components of the Q16DW are, on average, slightly smaller than 90°, suggesting the existence of orthogonal relationships between them. During strong bursts, the periods of the Q16DW in winter range between 15 and 18 d, whereas in winter, the periods tend to be more diffuse. The wintertime Q16DW is amplified, on average, when the zonal wind shear peaks, suggesting that barotropic instability may be one source of Q16DW. Q16DW amplitudes exhibit considerable interannual variability; however, a relationship between the 11-year solar cycle and the Q16DW is not found.

A long-term forecast study on the electricity demand of Taoussa of Mali is conducted in this paper, with various scenarios of socioeconomic and technological conditions. The analysis tool, which is applied in scenarios simulation, is the Model for Analysis of Energy Demand from the International Atomic Energy Agency. The analysis results are annual electricity demand and peak load forecast for the electrification from the period 2020 to 2035. During the planning period, the analysis results show that the electricity demand will increase to 49.40 MW (332.57 GWh) for the low scenario (LS), 66.46 MW (472.61 GWh) for the reference scenario (RS), and 89.47 MW (635 GWh) for the high scenario (HS). In addition, the total electricity demand increased at an average rate of 8.13% in the LS, 10.31% in the RS and 12.56% in the HS in all sectors. The electricity peak demand is expected to grow at 7.92%, 10.53% and 12.91% corresponding to the three scenarios; in this case, the system peak demand in 2035 will increase to 64.88 MW for the LS, 92.2 MW for the RS and 126.22 MW, the days of peak load are between 17th -23rd in May. The Industry sector will be the biggest electricity consumer of Taoussa area.

Metallic glass matrix composites are unique new materials which have superior mechanical properties as compared to existing conventional materials. Owing to this, they are potential candidates for various future structural applications. However, they suffer from disadvantages of brittleness, poor ductility and little or no toughness and they manifest catastrophic failure on application of force. Their behavior is dubious and require extensive experimentation to draw conclusive results. In present study, which is continuation of previous study by author, an effort has been made to overcome this pitfall by simulation. A quantitative mathematical model based on KGT theory has been developed to describe nucleation and growth of crystalline phase dendrites in glassy matrix during solidification. It yields information about numerical parameters to understand the behavior of each individual element in a phase in multicomponent sluggish slurry and their effect on final microstructural evolution. Model is programmed and simulated in MATLAB®. Its validation is done by comparison with identical curves reported in literature previously for similar alloys. Results indicate that effect of incorporating all heat transfer coefficients at macroscopic level and diffusion coefficients at microscopic level play a vital role in refining the model and bringing it closer to actual experimental observations. Two types of hypoeutectic and eutectic systems namely Zr₆₅Cu₁₅Al₁₀Ni₁₀ and Zr_47.5Cu_45.5Al₅Co₂ respectively were studied. Simulation results were found to be in good agreement with prior simulated and experimental values

Information is the currency of life, but the origin of prebiotic information remains a mystery. We propose transitional pathways from the cosmic building blocks of life to the complex prebiotic organic chemistry that led to the origin of information systems. The prebiotic information system, specifically the genetic code, is segregated, linear, and digital and probably appeared during biogenesis four billion years ago. In the peptide/RNA world, lipid membranes randomly encapsulated amino acids, RNA, and protein molecules, drawn from the prebiotic soup, to initiate a molecular symbiosis inside the protocells. This endosymbiosis led to the hierarchical emergence of several requisite components of the translation machine: tRNAs, aaRS, mRNAs, and ribosomes. When assembled in the right order, the translation machine created biosynthetic polypeptides, a process that transferred information from mRNAs to proteins. This was the beginning of the prebiotic information age. The molecular attraction between tRNA and amino acids led to different stages of the translation machines and the genetic code. tRNA is an ancient molecule that designed and built mRNA for storing the information of its cognate amino acid. Each mRNA strand became the storage device for the genetic information that encoded the amino acid sequences in triplet nucleotides. As information appeared in the digital languages of the codon within mRNA, and the genetic code for protein synthesis evolved, the prebiotic chemistry then became more organized and directional. The origin of the genetic code is enigmatic; herein we propose an evolutionary explanation: the demand for a wide range of specific enzymes in the peptide/RNA world was the main selective pressure for the origin of information-directed protein synthesis. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and the adaptive theory. These three theories are compatible with our coevolution model of the translation machines and the genetic code. We suggest biosynthetic pathways as the origin of the specific translation machines which provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machines: GNC code developed by the pre-tRNA/pre-aaRS /pre-mRNA machine, SNS code by the tRNA/aaRS/mRNA machine, and finally the universal genetic code by the tRNA/aaRS/mRNA/ribosome machine. Our hypothesis provides the logical and incremental steps for the origin of the programmed protein synthesis. In order to understand the prebiotic information system better, we converted letter codons into numerical codons in the Universal Genetic Code Table. We have developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa. This conversion has granted us insight into how the translation might have worked in the peptide/RNA world. There is great potential in the application of numerical codons to bioinformatics such as barcoding, DNA mining, or DNA fingerprinting. We constructed the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. Using AnyLogic software we were able to simulate and visualize the entire evolution of the translation machines and the genetic code. The results indicate that the emergence of the information age from the peptide/RNA world was a watershed event in the origin of life about four billion years ago.

The Late Heavy Bombardment Period (4.1 to 3.8 billion years ago) of heightened impact cratering activity on young Earth is likely the driving force for the origin of life. During the Eoarchean, asteroids such as carbonaceous chondrites delivered the building blocks of life and water to early Earth. Asteroid collisions created innumerable hydrothermal crater lakes in the Eoarchean crust which inadvertently became the perfect cradle for prebiotic chemistry. These hydrothermal crater lakes were filled with cosmic water and the building blocks of life. forming a thick prebiotic soup. The unique combination of exogenous delivery of extraterrestrial building blocks of life, and the endogenous biosynthesis in hydrothermal impact crater lakes very likely gave rise to life. A new symbiotic model for the origin of life within the hydrothermal crater lakes is here proposed. In this scenario, life arose around four billion years ago through five hierarchical stages of increasing molecular complexity: cosmic, geologic, chemical, information, and biological. During the prebiotic synthesis, membranes first appeared in the hydrothermal crater lakes, followed by the simultaneous origin of RNA and protein molecules, creating the RNA/protein world. These proteins were noncoded protein enzymes that facilitated chemical reactions. RNA molecules formed in the hydrothermal crater basin by polymerization of the nucleotides on the montmorillonite mineral substrate. Similarly, the initial synthesis of abiotic protein enzymes was mediated by the condensation of amino acids on pyrite surfaces. The regular wet-dry cycles within the crater lakes assisted further concentration, condensation, and polymerization of the RNAs and proteins. Lipid membranes randomly encapsulated amino acids, RNA, and protein molecules from the prebiotic soup to initiate a molecular symbiosis inside the protocells, this led to the hierarchical emergence of several cell components. As the role of protein enzymes became essential for catalytic process in the RNA/protein world, Darwinian selection from noncoded to coded protein synthesis led to translation systems and the genetic code, heralding the information stage. In this stage, the biochemical pathways suggest the successive emergence of translation machineries such as tRNAs, aaRS, mRNAs, and of ribosomes for protein synthesis. The molecular attraction between tRNA and amino acid led to the emergence of translation machinery and the genetic code. tRNA is an ancient molecule that created mRNA for the purpose of storing amino acid information like a digital strip. Each mRNA strand became the storage device for genetic information that encoded the amino acid sequences in triplet nucleotides. As information became available in the digital languages of the codon within mRNA, biosynthesis became less random and more organized and directional. The original translation machinery was simpler before the emergence of the ribosome than that of today. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and adaptive theory. We believe that these three theories are not mutually exclusive, but are compatible with our coevolution model of translations machines and the genetic code. We suggest biosynthetic pathways as the origin of the translation machine that provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machinery: GNC code with four codons and four amino acids during interactions of pre-tRNA/pre-aaRS /pre-mRNA, SNS code consisting of 16 codons and 10 amino acids appeared during the tRNA/aaRS/mRNA interaction, and finally the universal genetic code evolved with the emergence of the tRNA/aaRS/mRNA/ribosome machine. The universal code consists of 64 codons and 20 amino acids, with a redundancy that minimizes errors in translation. To address the question of the origin of the biological information system in the RNA/protein world, we converted letter codons into numerical codons in the Universal Genetic Code Table. We developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa, gaining insight into how translation might have worked in the RNA/protein world. We simulated the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. We used AnyLogic software to simulate and visualize the evolution of the translation machines and the genetic code. We conclude that the emergence of the information age from the RNA/protein world was a watershed event in the origin of life about four billion years ago.

Background: The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Methods: Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. A null model was created using frequencies of random SNPs. Results: Polygenic selection signal of educational attainment GWAS hits is high among a handful of SNPs within genomic regions replicated across GWAS publications. A polygenic score comprising 9 SNPs predicts population IQ (r=0.88), outperforming 99% of the polygenic scores obtained from sets of random SNPs (Monte Carlo p= 0.011). Its predictive power remains unaffected after controlling for spatial autocorrelation (Beta= 0.83). The largest polygenic score (161 SNPs) exhibits similar predictive power (Beta=0.8). Random polygenic scores are moderate predictors of population IQ (thanks to spatial autocorrelation), and their predictive power increases logarithmically with the number of SNPs, indicating an exponential reduction in noise. Conclusion: This study provides guidance for using GWAS hits together with random SNPs for testing polygenic selection using Monte Carlo simulations.

Despite nearly a century of research on water related issues, water erosion remains one of the greatest threats to soil health and soil ecosystem services around the world. Yet to date, data on water erosion needed to develop mitigation strategies is scarce, especially in the Sahelian regions. The current study therefore sets out to estimate annual soil losses caused by water erosion and to analyze trends over the period of 1981-2020 in the Mékrou watershed, located in the Middle Niger river sub-basin in West Africa. The revised universal soil loss equation, remote sensing and the Geographic Information System (GIS) were deployed in this study. Several types of data were used, including rainfall, soil conditions, topography and satellite images. The estimated average annual amount of water erosion in the Mékrou watershed is 6.49 t/ha/yr over 1981-2020. The dynamics of the ten-year average are highly variable, with a minimum of 3.45 t/ha/yr between 1981 and 1990, and a maximum of 8.50 t/ha/yr between 1991 and 2000. Even though these average soil losses in the Mékrou basin are below the tolerable threshold of 10 t/ha/yr, mitigation actions are needed for prevention. In addition, the spatial dynamics of water erosion are noticeably heterogeneous. The study reveals that 72.7% of the surface area of the Mékrou watershed is subject to slight water erosion below the threshold, compared with 27.3%, particularly in the mountainous south-western part, which is subject to intense erosion above the threshold.

Aiming at the problem of underactuated unmanned surface vehicles (USVs) performing fixed-point operations in the sea but without dynamic positioning control system. This paper introduces an original approach for positioning control, and the method is named as virtual anchor control method. This method is applicable in slow-varying current environments, and this approach does not need the prior knowledge of current information or vessel motion model parameters, thus offering convenient usability. This method is comprised by four steps. Firstly, a linear concise motion model with unknown disturbances is proposed. Then, the motion planning law is designed by imitating underlying principles of ship anchoring. Next, an adaptive disturbance observer is proposed for estimating uncertainties in the motion model. Last step, based on the observer, a sliding-mode method is used for heading control law designing, and thrust control law is also conducted by applying the Lyapunov method. Finally, numerical simulation experiments with significant disturbances and tidal current variations are conducted, which demonstrate that the proposed method has good control effect and robustness.

The finite volume method (FVM) is a kind of numerical analysis method that can take into account topography and apply local subdivision cells as the finite element method (FEM). The adjoint state method (ASM) can easily calculate the gradient vector of the objective function for the inversion. The author developed a program that applied these methods to 3-D Magnetotelluric (MT) inversion and verified it using test models. As a result, it was confirmed that the program can perform analysis properly and efficiently considering topography and subsurface resistivity heterogeneity.

The thesis proposes a argument that a mass point moving in a horizontal circle on the Earth’s surface can generate a radial centrifugal force of the Earth’s center of mass, thus realizing an unconventional anti-gravity path. Based on the author’s theory of absolute airspace and its reference system, and through the theoretical analysis of the difference in the distribution of gravitational acceleration at different latitudes caused by the rotation of the earth, and the centrifugal force of a mass point moving in a horizontal circle on the earth’s surface is analyzed, the validity of the argument is demonstrated. At the same time, the paper puts forward two possible basic principles, and makes theoretical analysis and demonstration. Conceive of the concrete experimental verification of principle two is proposed. Four technical schemes for anti-gravity ascent are proposed and basic analysis is made. On the premise of not fully considering the practical technical ability, it is theoretically proved that three of them have realistic operability and development potential. In theory, this paper opens up a different way of anti-gravity for human beings, which will bring new ideas and prospects for human beings to get rid of the bondage of gravity.

Cleft lip and palate are the most common congenital craniofacial anomalies. The etiology of this condition is unclear. The overall incidence of cleft lip and palate is 1/700. Prenatal diagnosis of cleft lip by 3D ultrasound is possible in more than 70% of cases, while it is less effective for cleft palate. There are several classifications of cleft lip and palate that were proposed over the years, however, only few have found clinical application, with none of them generally accepted as most effective and understandable. Allori et al. presented classification of a cleft lip and palate which is comprehensive and uniform, and it can precisely define the vast majority of the clefts, thus enabling easier communication between the health workers during their everyday practice. In this paper, we compared the accuracy of preoperative diagnoses compared to intraoperative diagnoses according to Kernahan and Stark classification from 1958, and these diagnoses were converted according to the Allori et al. classification of cleft lip and palate. Classification of cleft lip and palate presented by Allori et al. is clear, easy to understand, and it can be successful tool in studying the epidemiology of clefts.

In the modern days the data is coming from various devices like mobiles, tabs, laptops, computers, IOT devices e.tc and is stored in the electronics form in the systems using the concept of files or data bases. Clustering Technique is used to extract data from these sources. Improving the accuracy of the model is improved using the feature selection or feature engineering or both. The feature engineering is used to add a new feature based on the global mean. Along with that new feature in addition to the feature selection increase the overall accuracy of the model.

In order to achieve the dual carbon goal and simplify the decarbonization process, a CO2 recovery process of the fire-flooding exhaust was designed. The process adopted the two-stage membrane separation method to recover CO2 and obtain high purity CO2 rich flow, and then through the mixed refrigerant liquefaction and rectification column, food grade liquid CO2 was obtained. HYSYS process simulation shows that for the fire-flooding exhaust with a flow rate of 1000 kg/h and a given composition, the process can achieve a CO2 recovery of 69.02%, total product sales S=2086.8 yuan/h, and specific power consumption of 2.818 kW∙h/kg. On this basis, a hybrid simulation platform of HYSYS & Matlab was established. Taking the specific power consumption of the product as the objective function, sequential quadratic programming (SQP) algorithm was adopted to optimize the process, and the optimized specific power consumption was reduced by 18.8%. Finally, by adjusting N2/CO2 components, the adaptability of the optimization condition was analyzed.

In manufacturing chatter is an unwanted phenomenon that can lead to product quality reduction and tool wear. Real time chatter detection is key to preventing these issues and improving overall machining efficiency. In this paper we propose an unsupervised chatter detection method using autoencoders (AE) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm that uses internal signals of Computer Numerical Control (CNC) machines. The proposed method starts by using an AE to extract features from raw internal signals collected from CNC machines. This step reduces the dimensionality of the data and captures the underlying patterns of chatter. Then the extracted features are fed into DBSCAN clustering algorithm which is a density based algorithm that groups similar data points and identifies outliers. We tested the proposed method with real world data collected from various CNC machines. The results show that our unsupervised chatter detection method has high accuracy, precision and recall, can detect chatter and distinguish it from normal machining. Also the method is robust to noise and can adapt to dynamic machining conditions. In summary our work presents an unsupervised chatter detection method using AE and DBSCAN clustering that uses internal signals of CNC machines. This method is a reliable and efficient solution for real time chatter detection so manufacturers can improve product quality, optimize machining process and reduce tool wear during machining.

In this paper we introduce the Adomian decomposition method for a class of first order fuzzy dynamic equations on arbitrary time scales for existence of solutions. The results are provided with suitable numerical examples.

This paper investigates, experimentally and numerically, the buckling behavior of innovative sustainable Low-Cost Bamboo Composite (LCBC) structural columns under compressive loading. The LCBC columns are manufactured from bamboo culms in combination with bio-based resins to form composite structural columns. Different LCBC cross-sectional configurations are investigated in this study including the Russian doll (RD), Big Russian doll (BRD), Hawser (HAW), and Scrimber (SCR). Extra-large, large, medium, and small sizes of bamboo are employed to form the proposed configurations. Two bio-based resins including one bio-epoxy and one furan-based resin, in addition to a soft bio-based filler and a synthetic epoxy resin are applied. The bamboo species used as the cast-in-place giant bamboo for all configurations include Moso, Guadua, and Tali. In addition to experimental testing of the slender LCBC short columns, finite element analysis (FEA) software ABAQUS is applied to model the composite columns and predict their behavior. A buckling analysis using static Riks method is carried out to determine the LBCB’s response to axial compressive loading. A model is calibrated using test results with various imperfections, accounting for the variable behavior of each bamboo specimen, to accurately predict the behavior of LCBC columns with different resin contents. Slender LCBC columns showed maximum stress at buckling up to 60 MPa, highlighting the potential of bio-based resins for structural applications. The study found that the samples with bio-epoxy resin (BE2) exhibited enhanced material stiffness when compared to with synthetic epoxy (EPX) and furan-based resin (PF1), while PF1 specimens demonstrated increased ductility. The BE2 samples showed strain hardening in their stress-strain behavior, and the PF1 samples exhibited a long plateau phase before reaching the maximum load. Among the specimens with Moso bamboo and BE2 resin, those with SCR and HAW configurations achieved the highest compressive strengths.

The current design of irrigation and fertilization systems often depends on a single index, leading to irrational systems due to the lack of a comprehensive multi-index evaluation. The aim of this study is to optimize the irrigation and nitrogen fertilizer application levels of spring maize using the TOPSIS method, in order to achieve a balance between growth characteristics, yield, water use efficiency, and soil nitrogen content. In the typical semi-arid region of Northeast China, through precise control experiments from 2022 to 2023, we adopted a two factor quadratic saturation D-optimal design method to study the effects of different irrigation amounts (145.40, 271.70, 348.20, 436.20 mm) and nitrogen fertilizer application amounts (34.80, 185.90, 277.40, 382.80 kg·hm-2) on spring maize. Results indicate that increasing both irrigation and nitrogen application rates can enhance dry matter accumulation by 15.17% to 32.70%. The impact of irrigation and fertilization on the net photosynthetic rate (Pn) of spring maize was found to be greater for irrigation amount than nitrogen application, particularly at 9:00 am and 13:00 pm, and slightly less so at 11:00 am and 15:00 pm. Concurrently, there was a significant increase in total nitrogen (TN1 by 20.85% for 0-20 cm soil layer, TN2 by 33.33% for 20-40 cm soil layer) and alkali-hydrolyzed nitrogen (AHN1 by 14.65% for 0-20 cm, AHN2 by 28.86% for 20-40 cm). Yields improved by 12.02% to 44.09%, and water use efficiency (WUE) saw an increase ranging from 20.08% to 140.07%. The optimal water and fertilizer management mode for spring maize SBDI (shallow buried drip irrigation) in semi-arid areas was determined through comprehensive analysis using TOPSIS entropy weight method. When the irrigation amount is 436.20 mm and the nitrogen fertilizer application amount is 277.40 kg·hm-2, it can significantly promote the accumulation of dry matter, yield, water use efficiency, photosynthetic characteristics, and soil nitrogen content of spring maize. This study provides a theoretical basis for the practical application of SBDI water fertilizer coupling technology for spring maize.

Spectral photon counting cone-beam CT imaging is challenged by individual pixel response behaviour, which leads to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform post-processing ring artefact correction of sinogram data or scan reconstructions, without taking the pixel response explicitly into account. Here we present a novel post-processing method (DAC-shifting), which explicitly measures the current pixel response using flat field images, and subsequently corrects the projection data. The DAC-shifting method was evaluated with a repeat series of spectral photon counting imaging (Medipix3) of a phantom with different density inserts, and in iodine K-edge imaging. The method was also compared against PMMA based STC. The DAC-shifting method was shown to be effective in correcting individual pixel response, and was robust against detector instability. On the contrary, STC correction showed varying results, which was almost as good as DAC-shifting when data was acquired just after STC calibration, but worse with larger time differences. In K-edge imaging, DAC-shifting provides a sharper attenuation peak, and more uniform CT values, which is expected to benefit iodine concentration quantification.

In GNSS/IMU integrated navigation systems, factors such as satellite occlusion and non-line-of-sight conditions can lead to degradation of satellite positioning results, Subsequently affecting the overall accuracy of the integrated navigation system. To address this issue and ef-fectively utilize historical pseudorange information from satellites, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. These virtual constraints are con-structed using satellite ‘s position from previous time step, the rate of change of pseudoranges, and ephemeris data. This virtual constraint can serve as an alternative solution for individual satellites in case of signal anomalies, ensuring the integrity and continuity of the graph optimi-zation model. Additionally, this paper conducts an analysis of the graph optimization model constructed using these virtual constraints, comparing it with traditional integrated navigation graph optimization model, and analyzes and reconstructs the marginalization process based on these virtual constraints. The experimental results, compared with tightly coupled Kalman fil-tering and the original graph optimization method on a set of real-world data, demonstrate that the introduction of virtual pseudoranges maintains high positioning accuracy. The RMSE error between it and the original graph optimization remains within 5%, affirming the high feasibility of this approach.

In response to the burgeoning global demand for premium agricultural products, particularly within the competitive nut market, this paper introduces an innovative methodology aimed at enhancing the grading process for almonds and their shells. Leveraging state-of-the-art Deep Convolutional Neural Networks (CNNs), specifically the AlmondNet-20 architecture, our study achieves exceptional accuracy exceeding 99%, facilitated by the utilization of a 20-layer CNN model. To bolster robustness in differentiating between almonds and shells, data augmentation techniques are employed, ensuring the reliability and accuracy of our classification system. Our model, meticulously trained over 1000 epochs, demonstrates remarkable performance, boasting an accuracy rate of 99% alongside a minimal loss function of 0.0567. Rigorous evaluation through test datasets further validates the efficacy of our approach, revealing impeccable precision, recall, and F1-score metrics for almond detection. Beyond its technical prowess, this advanced classification system offers tangible benefits to both industry experts and non-specialists alike, ensuring globally reliable almond classification. The application of deep learning algorithms, as showcased in our study, not only enhances grading accuracy but also presents opportunities for product patents, thereby contributing to the economic value of our nation. Through the adoption of cutting-edge technologies such as the AlmondNet-20 model, we pave the way for future advancements in agricultural product classification, ultimately enriching global trade and economic prosperity.

The integration of magnetic observatories of many countries into the Intermagnet network has provided researchers with new opportunities to investigate many geophysical processes. The joint processing of measurement evidence from magnetic observatories located in various geolocations makes it possible to better understand the dynamics of the interaction of solar plasma fluxes with the Earth's magnetosphere. For the correct interpretation of the dynamics of physical processes, the accuracy of the time reference of measurement results is of great importance. The measurement results of local observatories were transformed to a unified ecliptic coordinate system oriented towards the Sun in order to extract small variations in the magnetic field occurring before the magnetic storm commencement. Before transforming the coordinates, a constant component equal to the average daily value of the magnetic field components was removed from the results of minute-by-minute measurements. Owing to the averaging evidence from 84 magnetic observatories of the Intermagnet network, variations in the magnetic field of cosmic origin, preceding the magnetic storm commencement were detected. The correlation analysis of these variations recorded by different observatories revealed the presence of time shifts between the data series of different observatories. Only 62% of the observatories had a relative data shift within the range of ± 1 minute. Before the joint data processing in order to efficient use of data recorded with a time shift a method for correcting time shifts has proposed.

This study presents a novel semi-supervised deep learning method utilizing 3D TOF-MRA images for the detection of brain aneurysms, employing landmark-based techniques that mimic radiologist practices to enhance detection accuracy and efficiency.

In response to the issues of sensor noise and accumulated motion errors that lead to low positioning accuracy and insufficient robustness during large maneuvers or continuous flight of small unmanned aerial vehicles (UAVs) in complex environments, this paper proposes a multi-source and multimodal data fusion method. Initially, it employs a multimodal data fusion of various sensors including GPS (Global Positioning System), IMU (Inertial Measurement Unit), and visual sensors to complement the strengths and weaknesses of each hardware component, thereby eliminating motion errors to enhance accuracy. To mitigate the impact of sudden changes in sensor data, the method introduces a digital twin UAV data source. By utilizing the Extended Kalman Filter algorithm, it fuses data from both the real UAV and its digital twin, and the filtered positional information is fed back into the control system of the real UAV. This enables real-time correction of UAV positional deviations caused by sensor noise and environmental disturbances. The multi-source multimodal fusion Kalman filter method proposed in this paper significantly improves the positioning accuracy of UAVs in complex scenarios and the overall stability of the system. This method holds significant value in maintaining high-precision positioning in variable environments and has important practical implications for enhancing UAV navigation and application efficiency.

The rebound behaviors of rubber balls based on ethylene-propylene-diene monomer (EPDM) / chlorinated butyl rubber (CIIR) blends were investigated systematically. A novel method was proposed to characterize the damping capacity of the EPDM/CIIR blends. The damping capacity can be represented by the rebound height of rubber balls, and lower rebound height corresponds to better damping capacity. A mathematical model expressed by an equation obtained through theoretical derivation has been proposed to predict the rebound height of the rubber balls. The energy dissipation rate (EDR) defined by the ratio of the height loss to the rebound time was proposed to further characterize the damping capacity. The EDR value shows the highest for the pure CIIR and lowest for the pure EPDM, showing a decrease trend with the increase of EPDM content in the rubber blends. By comparison one can obtain that the damping capacity of the EPDM/CIIR blends decreases with the decrease of external excitation, the conclusion of which plays a key role in the formulation design of viscoelastic damping rubber materials.

By repeated unloading and loading of the excavation dynamic and static loads, repeated train dynamic and static loads of multi-factors, the underpass tunnel, cross tunnel engineering influence area rock layer, the existing tunnel structure of the three constitutes a multifaceted structure, multi-factor interaction system. Existing tunnels into the prediction theory model of the new tunnel excavation process of dynamic and static loads, dynamic and static loads of existing tunnels are mostly analyzed individually, the results of synergistic analysis needs to be improved. Based on the theory of the current layer method, the paper comprehensively considers the stiffness of the existing tunnel, the stiffness of the new tunnel, the excavation method load and the existing tunnel load, coupled with Peck's empirical formula, the theoretical model of deformation prediction for excavation of a two-lane highway tunnel under the tunnel through the existing railroad is proposed, and verified and optimized by numerical calculations and monitoring data, which proves the applicability and reliability of the theoretical model in the similar strata and the project promotion.

This paper introduces a new adaptation of the enthalpic lattice Boltzmann method (LBM) tailored to simulate the intricate dynamics of conjugate heat transfer in non-homogeneous media, showcasing considerable potential for enhancing heat exchanger designs. This approach expands upon the conventional enthalpic LBM framework by seamlessly incorporating tailored source terms, enabling precise representation of local and transient variations in the medium’s thermophysical properties. The resulting LBM model comprehensively captures the energy conservation equation, with exceptions made only for flow compressibility and viscous dissipation, thereby significantly augmenting its versatility in analyzing heat exchanger configurations. Verification tests, comprising assessments of both transient and steady-state solutions, unequivocally validate the accuracy of the proposed model, further bolstering its reliability for analyzing heat exchange processes within intricate heat exchanger geometries. To demonstrate its efficacy, simulations of conjugate heat transfer processes involving fluid natural convection within structured cavities were performed, imposing both Dirichlet and Neumann boundary conditions to emulate scenarios encountered in practical heat exchanger operations. The findings yield compelling insights, particularly in the transient regime, revealing the beneficial impact of structured cavities on enhancing heat transfer processes. These insights inform potential design optimizations for heat exchangers. The results emphasize the potential of the modified enthalpic LBM approach to elucidate complex heat transfer phenomena in non-homogeneous media and structured geometries, offering valuable implications for heat exchanger engineering and optimization.

Using UAV-based multispectral images for quickly and accurately monitoring chlorophyll content is critical for field management and yield estimation. However, the lower model accuracy and the poor robustness of the estimation models are still preventing the widespread application of UAV-based multispectral images. We carried out two field trials at various experimental sites to further enhance the precision and applicability of the model used to estimate the chlorophyll content of potato plants. Firstly, the texture features and vegetation indices derived from multispectral images were screened using the Pearson correlation coefficient method, and Normalized difference red edge (NDRE) performed the best over the two growth periods. Secondly, principal component analysis (PCA) was applied to recombine five bands of multispectral images, and third PCA results (PCA3) was selected to combined with NDRE according to the construction principle of NDRE, and the newly constructed parameter was named improved NDRE (INDRE). Finally, INDRE was used to establish a chlorophyll content estimation model of potato plants, and compared with some traditional parameters. The results demonstrated that the INDRE had the maximum accuracy (R2 = 0.7865, RMSE = 2.1378), and corresponding R2 increased by 0.1481 and RMSE decreased by 1.2994 than NDRE. Additionally, the model was validated using independent data from Experiment 2, and INDRE considerably increased estimation accuracy compared to other factors. In conclusions, the INDRE suggested in this study significantly enhances the accuracy and applicability of the chlorophyll content inversion model and can serve as an additional reference for fertilization management.

Tack is one of the most important factors affecting the operability of prepregs, but it is still very difficult to obtain the change of prepreg tack with time at different temperatures. In this paper, a newly designed T-peel device is used to test the tack decay rate of prepregs at different temperatures. The obtained decay rate deviates less than 8.9% from the manufacturer's data. The maximum deviation of the ratio of tack decay speeds calculated by the Arrhenius equation from the experiments is not higher than -9.7%. It is proved that the present method can obtain the decay rate of tack of prepregs at different temperatures. This method is also applicable to the other two types of prepregs. The article proposes the handling life unit, an operational life measurement unit for prepregs, and establishes that the relationship between tack and remaining shelf life reduces prepreg management costs.

Detecting the presence of explosives is important to protect human lives in military conflicts and peacetime. Gas-phase detection of explosives can make use of the change of material properties, which can be sensitive to environmental conditions such as temperature and humidity. This paper describes a remote-controlled automatic shutter method for environmental impact assessment of photoluminescence (PL) sensors under near-open conditions. Utilizing the remote-sensing method, we obtained environmental effects without being exposed to sensing vapor molecules, and explained how PL intensity was influenced by the temperature, humidity, and exposure time. We also developed a theoretical model including the effect of exciton diffusion for PL quenching, which worked well under limited molecular diffusions. Incomplete recovery of PL intensity, or degradation effect, was considered as an additional factor in the model.

The article presents the issues related to load sharing in direct current grid and a novel control method which has advantages over known solutions. Unlikely of many similar sounding papers this article shows attempt of creation fully controllable non-isolated system which allows load sharing between permanent magnet alternator equipped with machine side converter (MSC) and dual active bridge (DAB) tied to batteries or supercapacitor. The power sharing is essential feature of parallel connected direct current generators and all types of voltage sources in this way are contributing power to the system. Such system should have possibility of the rapid voltage build up in the case of sudden electrical load changes. To keep the optimal efficiency of the alternator the rotational speed changes according to proper mapping of driving combustion engine. When rotational speed is too low then sudden electrical load can cause significant voltage drop and time needed for voltage build up will vary according to RPM increase. In such situations the undervoltage system can trip the breaker and finally there may be a blackout. To avoid such problem the DC systems which consist of batteries and supercapacitor were introduced. System components include a self-excited synchronous generator (SESG) operating at variable shaft speed as well as batteries and supercapacitors that provide electricity for sudden electrical load changes on the distribution grid. The core of presented system is in power distribution method which consists of programmed controllers structure allowing precise currents distribution. A novelty in the proposed method is the use of a cascaded system of current and DC voltage regulators which allows power distribution precise control. In contrary to previously presented solutions, the proposed system allows fast and accurate control of currents loading parallel connected DC voltage sources for wide range generator speed changes. In presented solution both converters have been equipped with Schottky diodes preventing flow of equalizing currents between closed transistors in the parallel mode of operation. An experimental test-stand of the described system is presented with its theoretical basis and experimental results.

This experimental study probes the dynamic behaviour of a 3mm ABS sheet during positive mould vacuum-assisted thermoforming. In this process, the sheet undergoes large and fast deformations, caused by the applied vacuum and mechanical stretching by the mould. The objective is to elucidate the complexities of these large, rapid and non-isothermal deformations. The non-isothermal conditions are caused by the radiative heating of the sheet, convective heat loss to the surrounding air and conductive heat transfer from the sheet to the mould. Utilizing stereo Digital Image Correlation (DIC) in tandem with thermal imaging, the present study accurately maps the occurring displacement, strain and strain rate field in relation to real-time temperature variation of the material. The study progresses to observe the ABS material from the moment it contacts the mould until it conforms to a positive 250mm diameter semi-sphere cast aluminium mould. The DIC methods are validated by comparing thickness values derived from DIC’s principal strain directions to ultrasonic thickness gauge readings. This knowledge not only broadens the understanding of the thermo-mechanical behaviour of the material but also aids in optimizing process parameters for improved thickness uniformity in thermoformed products.

To identify the exchange coefficients of a nonlinear polynomial tricompartmental general system of α+β , we follow the procedure; firstly, the recommended solution is to introduce an adequate time t*&gt;0 in a determinable manner. That is, after injecting quantity a into the main compartment, wait a moment for the exchange in the polynomial α+β order nonlinear general system to settle, and then compare this compartment to compartment 2 at t*. Secondly, applying the Taylor formula will linearize the system and identify the exchange coefficients. Finally, we will prove that the linearization method is stable.