Weight Balance Research Articles

Parallel Force Feedback Device Design With Constant Jacobian Matrix and Net Weight Fully Balanced

Abstract Force feedback devices offer realistic and intuitive feedback to operators, and achieving higher accuracy and transparency has been a prominent research focus in this field. However, errors in real-time force or position calculations are inevitable, which can have adverse effects on the accuracy of the equipment. This article presents the design of a parallel mechanism that incorporates a constant force and velocity mapping relationship based on the type synthesis of the constant Jacobian matrix. Specifically, the mechanism maintains a fixed direction of force applied to the operating platform by the drive pair, which is mounted on the fixed platform in each limb, irrespective of position changes. This unique feature enables the mechanism to achieve a complete net weight balance. The implementation method is detailed in this article, which involves adding appropriate counterweights to achieve a balance between the weight of the connecting rod and the overall gravity of the operating platform. Furthermore, the optimization of structural parameters helps to improve the performance of the developed prototype. The proposed design scheme not only addresses the fundamental reduction of errors caused by real-time force and position mapping solving but also enhances operational transparency. Finally, simulation and experimental tests are conducted to validate the proposed theory.

Automation of conceptual design and modification of aircraft type unmanned aerial vehicles using multidisciplinary optimization and evolutionary algorithms. Part 1: Methods and models

This paper proposes a method for selecting rational parameters for large-size aircraft-type unmanned aerial vehicles at the initial design stages using an optimization algorithm of differential evolution and numerical mathematical modeling of aerodynamic problems. The method assumes implementation of weight and aerodynamic balance in the main flight modes, it can consider aircraft-type unmanned aerial vehicles with one or two lifting surfaces, applies parallel calculations, and automatically generates a three-dimensional geometric model of the aircraft appearance based on the optimization results. A method for accelerating by more than three times the process of solving the problem of optimizing aircraft takeoff weight parameters by introducing the target function into the set of design variables is proposed and demonstrated. The results of assessing the reliability of the mathematical models used for aerodynamics and the correct calculation of the target function are presented, taking into account various constraints. A comprehensive check of the operability and effectiveness of the method were considered by solving demonstration problems by optimizing more than ten main design parameters of the appearance of two existing heavy-class unmanned aerial vehicles with known characteristics from open sources. Examples of using the optimization results to modify prototypes are provided.

Measurement-Noise Filtering for Automatic Discovery of Flow Splitting Ratios in ISP Networks

Network telemetry and analytics is essential for providing highly dependable services in modern computer networks. In particular, network flow analytics for ISP networks allows operators to inspect and reason about traffic patterns in their networks in order to react to anomalies. High performance network analytics systems are designed with scalability in mind, and can consequently only observe partial information about the network traffic. Still, they need to provide a holistic view of the traffic, including the distribution of different traffic flows on each link. It is impractical to monitor such fine-grained telemetry, and in large, heterogeneous networks it is often too complex and error-prone, if not impossible, to access and maintain all technical specifications and router-specific configurations needed to determine e.g. the load balancing weights used when traffic is split onto multiple paths. The ratios by which flows are split on the possible paths must be derived indirectly from the measured flow demands and link utilizations. Motivated by a case study provided by a major European ISP, we suggest an efficient method to estimate the flow splitting ratios. Our approach, based on quadratic linear programming, is scalable and achieves robustness to the measurement noise found in a typical network analytics deployment by filtering out certain constraints in the linear program. Finally, we implement an automated tool for estimating the flow splitting ratios and document its applicability on real data from the ISP.

Research on faults diagnosis of dynamic balance in scroll compressor based on CWT-MViTV2

Abstract The dynamic balancing of rotor systems is a critical factor affecting the vibration of scroll compressors. Traditionally, the detection and correction of rotor dynamic balancing systems have relied on time-domain and frequency-domain analysis of vibration signals, as well as validation using rotor dynamic balancing test platforms. This paper proposes a novel fault diagnosis method for the dynamic balancing of scroll compressor rotor systems. This method acquires the time-domain vibration signals of the scroll compressor through online detection experiments. These signals are then transformed into time-frequency maps using continuous wavelet transform(CWT). By integrating the MViTV2 neural network, this approach enables effective identification of dynamic balancing fault types without requiring disassembly or shutdown of the machine. The fault types, corresponding to the offset of the balancing weight’s centroid, will provide direct data support for subsequent validation work. This study compares various neural network models combined with time-frequency maps and demonstrates that the proposed model achieves the highest accuracy of 99.749% compared to other models, and the method's generalizability is validated in the public dataset. Furthermore, the proposed model maintains a high accuracy of 94.872% in high-noise environments. After improvement, the accuracy of the model has been increased to 95.641%, the training time and the diagnosis time has been reduced to 0.240 iter/s and 0.0277s.

Acetyl-11-keto-beta-boswellic Acid (AKBA) Ameliorates Histopathological and Oxidative Stress Brain Disorders in the Experimental Model of Cuprizone-induced Demyelination

Background: Multiple sclerosis is an inflammatory autoimmune disease that destroys the myelin sheath (demyelination) and neurons of the central nervous system (CNS), with several factors contributing to its development. Objectives: This study investigated the impact of administering acetyl 11-keto-beta boswellic acid (AKBA) in an animal model of cuprizone-induced demyelination. Methods: Thirty-two C57BL/6 female mice (WT; 20 - 25 g, 8 - 10 weeks old) were randomly divided into four groups: (1) Control (CO), (2) Cuprizone-treated (CPZ, 0.3%), (3) AKBA + CPZ (50 mg/kg, pre-treatment), and (4) CPZ + AKBA (50 mg/kg, post-treatment). At the end of the study, the weight and movement balance of the animals were assessed using the rotarod test. After sampling the brain, the extent of the demyelination area in the corpus callosum was measured with Luxol Fast Blue staining, the number of oligodendrocyte cells was determined by immunohistochemistry, and the levels of malondialdehyde (MDA) and total antioxidant capacity (TAC) as oxidative stress factors in the brain tissue were measured. Results: The use of acetyl-11-keto-beta boswellic acid in the cuprizone-induced demyelination model prevented weight loss, increased animal resistance in the rotarod test, and reduced the demyelination rate in the corpus callosum. Additionally, AKBA elevated the number of oligodendrocytes and total antioxidant capacity levels while reducing malondialdehyde levels in brain tissue. Pretreatment with AKBA exhibited a more significant effect. Conclusions: This study showed that acetyl-11-keto-beta boswellic acid, an important active substance of the frankincense plant, likely protects the nervous system and neurons in the cuprizone-induced demyelination model by preventing the decrease in the number of oligodendrocytes, reducing oxidative stress, and preventing the destruction of myelin.

Identification of an ionic mechanism for ERα-mediated rapid excitation in neurons.

The major female ovarian hormone, 17β-estradiol (E2), can alter neuronal excitability within milliseconds to regulate a variety of physiological processes. Estrogen receptor-α (ERα), classically known as a nuclear receptor, exists as a membrane-bound receptor to mediate this rapid action of E2, but the ionic mechanisms remain unclear. Here, we show that a membrane channel protein, chloride intracellular channel protein-1 (Clic1), can physically interact with ERα with a preference to the membrane-bound ERα. Clic1-mediated currents can be enhanced by E2 and reduced by its depletion. In addition, Clic1 currents are required to mediate the E2-induced rapid excitations in multiple brain ERα populations. Further, genetic disruption of Clic1 in hypothalamic ERα neurons blunts the regulations of E2 on female body weight balance. In conclusion, we identified the Clic1 chloride channel as a key mediator for E2-induced rapid neuronal excitation, which may have a broad impact on multiple neurobiological processes regulated by E2.

Greek, Roman, and Byzantine Weights from the Ephesus Museum

This article, part of the Corpus Ponderum Antiquorum et Islamicorum (= CPAI ) project, introduces 302 balance weights from the collection of the Ephesus Museum, located in Selçuk (Efes), İzmir. The majority of the weights are made of lead, with a smaller number made of bronze. Among these, 115 weights follow the Greek system, while 187 belong to the Roman system, of which some are classified as Byzantine weights. The find spots of these weights are primarily in and around Selçuk and nearby archaeological sites, providing important data for their provenance or attribution. Although some weights bear ethnics, most only feature unit marks; however, their find spots enable accurate attribution. The Roman system weights, especially the librae, range from the theoretical 12 unciae to as much as 25 unciae, indicating adjustments over time due to inflation and devaluation. Among the Byzantine weights, the glass ones, dating from the 5th to 7th centuries AD, are also notable for the monograms they bear. Additionally, a weight made from a coin dates to the 10th-11th centuries AD.

Expression of Intelectin-1, also known as Omentin-1, is related to clinical phenotypes such as overweight, obesity, insulin resistance, and changes after bariatric surgery.

Intelectin-1 (ITLN1; also Omentin-1, OMNT1) is secreted by adipose tissue (AT) and plays an important role in glucose metabolism regulation, with links to obesity-associated diseases. ITLN1 activity so far has rarely been investigated using RNA-sequencing and in larger cohorts. We evaluated ITLN1 expression among three clinical cohorts of the Leipzig Obesity BioBank-a cross-sectional cohort comprising of 1480 people, a cohort of people with metabolically healthy or unhealthy obesity (31 insulin-sensitive, 42 insulin-resistant individuals with obesity), and a longitudinal two-step bariatric surgery cohort (n = 65). We hypothesized that AT ITLN1 expression is associated with serum omentin-1, clinical parameters associated with obesity, and with weight loss after bariatric surgery. We also investigated the correlation of AT ITLN1 expression with genes related to inflammatory response, lipid metabolism, obesity, and regulation of energy balance. Likewise, we inspected gene group expression and metabolic pathways associated with ITLN1 expression using gene set enrichment and gene correlation analysis. We show that ITLN1 expression differs in VAT and SAT, and should therefore be analyzed separately. Furthermore, ITLN1 expression increases with VAT tissue mass, but is negatively affected by AT tissue dysfunction among individuals with unhealthy obesity, corroborated by interplay with genes related to tissue inflammation. Gene set enrichment and gene correlation analysis of ITLN1 expression suggest that AT ITLN1 expression is related to local inflammatory processes in AT, but also in processes such as regulation of appetite, energy balance, and maintenance of body weight.

BM-FL: A Balanced Weight Strategy for Multi-Stage Federated Learning Against Multi-Client Data Skewing

BM-FL: A Balanced Weight Strategy for Multi-Stage Federated Learning Against Multi-Client Data Skewing

Influence of strut angle and radius on the energy absorption and failure mechanisms in 3-strut, 4-strut and 6-strut lattice structures

Abstract 3D-printed truss structures have remarkable potential in the aerospace and weight-critical technologies fields. However, design parameters need to be carefully considered. A low overhang angle or diameter can result in discrepancies. This research presents an approach by examining the effect of strut overhang angle and radius on the mechanical properties of 3-, 4- and 6-strut lattice structures under compressive loading. 1.6- and 2.4-mm diameter struts were designed with 45°, 50°, 55° and 60° overhang angle strut lattices. Experiments were simulated and compared with test results for each parameter. Even if joint regions have little effect on specimens’ density, it has a remarkable effect on mechanical properties of the specimen. To simulate this, many studies were investigated to simulate joint regions. The study’s goal is to deepen the understanding of how design variations in strut lattice structures influence their energy-absorbing characteristic and mechanical behavior, using a combination of static tests and finite element analysis for validation. This insight is crucial for optimizing lattice design to balance weight, strength, and energy-absorbing capacity effectively. The experimental test result and numerical result showed rather good agreement. It is observed that joint regions, overhang angle, and diameters were the main parameters affecting specimens’ mechanical behavior.

Minimally invasive colorectal cancer surgery: an observational study of medicare advantage and fee-for-service beneficiaries

BackgroundEnrollment of Medicare beneficiaries in medicare advantage (MA) plans has been steadily increasing. Prior research has shown differences in healthcare access and outcomes based on Medicare enrollment status. This study sought to compare utilization of minimally invasive colorectal cancer (CRC) surgery and postoperative outcomes between MA and Fee-for-Service (FFS) beneficiaries.MethodsA retrospective cohort study of beneficiaries ≥ 65.5 years of age enrolled in FFS and MA plans was performed of patients undergoing a CRC resection from 2016 to 2019. The primary outcome was operative approach, defined as minimally invasive (laparoscopic) or open. Secondary outcomes included robotic assistance, hospital length-of-stay, mortality, discharge disposition, and hospital readmission. Using balancing weights, we performed a tapered analysis to examine outcomes with adjustment for potential confounders.ResultsMA beneficiaries were less likely to have lymph node (12.9 vs 14.4%, p < 0.001) or distant metastases (15.5% vs 17.0%, p < 0.001), and less likely to receive chemotherapy (6.2% vs 6.7%, p < 0.001), compared to FFS beneficiaries. MA beneficiaries had a higher risk-adjusted likelihood of undergoing laparoscopic CRC resection (OR 1.12 (1.10–1.15), p < 0.001), and similar rates of robotic assistance (OR 1.00 (0.97–1.03), p = 0.912), compared to FFS beneficiaries. There were no differences in risk-adjusted length-of-stay (β coefficient 0.03 (− 0.05–0.10), p = 0.461) or mortality at 30-60-and 90-days (OR 0.99 (0.95–1.04), p = 0.787; OR 1.00 (0.96–1.04), p = 0.815; OR 0.98 (0.95–1.02), p = 0.380). MA beneficiaries had a lower likelihood of non-routine disposition (OR 0.77 (0.75–0.78), p < 0.001) and readmission at 30-60-and 90-days (OR 0.76 (0.73–0.80), p < 0.001; OR 0.78 (0.75–0.81), p < 0.001; OR 0.79 (0.76–0.81), p < 0.001).ConclusionsMA beneficiaries had less advanced disease at the time of CRC resection and a greater likelihood of undergoing a laparoscopic procedure. MA enrollment is associated with improved health outcomes for elderly beneficiaries undergoing operative treatment for CRC.

Utilizing neural networks and genetic algorithms in AI-assisted CFD for optimizing PCM-based thermal energy storage units with extended surfaces

Phase Change Materials (PCMs) offer significant benefits for applications such as electronic cooling and Thermal Energy Storage (TES) due to their high energy storage capacity and stability. However, their limited thermal conductivity restricts widespread utilization. To address this limitation, the use of fins has become a common technique to enhance heat transfer. Optimizing fin lengths and locations is challenging, as they affect natural convection. This study aims to develop a model using a feed-forward back-propagation network, trained on simulation data, for designing a TES unit. A design matrix, incorporating factors such as fin lengths and heights, is obtained through response surface methodology. Single- and multi-objective Genetic Algorithms (GAs) are employed to seek optimal solutions, considering Complete Melting Time (CMT) and total fin length. The results demonstrate the excellent performance of the network model, with an error of less than 2.98%. The single-objective GA yields a minimum CMT. In a finless enclosure, the CMT is 338.5% higher compared to the single-objective configuration. The multi-objective GA, using Euclidean distance specified from the Pareto front to balance weight and material costs, results in a CMT that is 192% higher compared to the single-objective optimization but with a total fin length that is 286% shorter. While these improvements are significant, it is important to note that fins can increase material and manufacturing costs, as well as the overall unit weight. This artificial intelligence-computational fluid dynamics method not only predicts TES unit performance but also reduces computational costs in designing an optimal TES unit.

Analyzing Runs of Homozygosity Reveals Patterns of Selection in German Brown Cattle.

An increasing trend in ancestral and classical inbreeding coefficients as well as inbreeding depression for longevity were found in the German Brown population. In addition, the proportion of US Brown Swiss genes is steadily increasing in German Browns. Therefore, the aim of the present study was to analyze the presence and genomic localization of runs of homozygosity (ROH) in order to evaluate their associations with the proportion of US Brown Swiss genes and survival rates of cows to higher lactations. Genotype data were sampled in 2364 German Browns from 258 herds. The final data set included 49,693 autosomal SNPs. We identified on average 35.996 ± 7.498 ROH per individual with a mean length of 8.323 ± 1.181 Mb. The genomic inbreeding coefficient FROH was 0.122 ± 0.032 and it decreased to 0.074, 0.031 and 0.006, when genomic homozygous segments > 8 Mb (FROH>8), >16 Mb (FROH>16) and >32 Mb (FROH>32) were considered. New inbreeding showed the highest correlation with FROH>32, whereas ancestral inbreeding coefficients had the lowest correlations with FROH>32. The correlation between the classical inbreeding coefficient and FROH was 0.572. We found significantly lower FROH, FROH>4, FROH>8 and FIS for US Brown Swiss proportions <60% compared to >80%. Cows surviving to the 2nd, 4th, 6th, 8th, and 10th lactation had lower genomic inbreeding for FROH and up to FROH>32, which was due to a lower number of ROH and a shorter average length of ROH. The strongest ROH island and consensus ROH shared by 50% of the animals was found on BTA 6 at 85-88 Mb. The genes located in this genomic region were associated with longevity (NPFFR2 and ADAMTS3), udder health and morphology (SLC4A4, NPFFR2, GC and RASSF6), milk production, milk protein percentage, coagulation properties of milk and milking speed (CSN3). On BTA 2, a ROH island was detected only in animals with <60% US Brown Swiss genes. Genes within this region are predominantly important for dual-purpose cattle breeds including Original Browns. For cows reaching more than 9 lactations, an exclusive ROH island was identified on BTA 7 with genes assumed to be associated with longevity. The analysis indicated that genomic homozygous regions important for Original Browns are still present and also ROH containing genes affecting longevity may have been identified. The breeding of German Browns should prevent any further increase in genomic inbreeding and run a breeding program with balanced weights on production, robustness and longevity.

Atmospheric Aircraft Conceptual Design Based on Multidisciplinary Optimization with Differential Evolution Algorithm and Neural Networks

A methodology for selecting rational parameters of atmospheric aircraft during the initial design stages using a differential evolutionary optimization algorithm and numerical mathematical modeling of aerodynamics problems is proposed. The technique involves implementing weight and aerodynamic balance in the main flight modes, considering atmospheric aircraft with one or two lifting surfaces, applying parallel calculations, and auto-generating a three-dimensional geometric model of the aircraft’s appearance based on the optimization results. A method for accelerating the process of optimizing aircraft parameters in terms of takeoff weight by more than three times by introducing an objective function into the set of design variables is proposed and demonstrated. The reliability of mathematical models used in aerodynamics and the accuracy of the objective function calculation considering various constraints are explored. A comprehensive test of the performance and efficiency of the methodology is conducted by solving demonstration problems to optimize more than ten main design parameters for the appearance of two existing heavy-class unmanned aerial vehicles with known characteristics from open sources.

Multi-objective multi-population simplified swarm optimization for container loading optimization with practical constraints

The container loading problem (CLP) holds significant importance in logistics and supply chain management due to its direct influence on transportation costs and times, thereby impacting the competitive advantages of enterprises across industries. Although there are existing studies for CLP, there remains a gap in addressing the optimization of multiple objectives while satisfying practical constraints. Moreover, container loading methods must also meet performance requirements such as high computational speed, explainability, and implementation capability. Although meta-heuristic-based algorithms have shown effective computational capabilities and performance, such algorithms often being trapped in the local optima especially when searching in the vast solution space of the CLP, particularly as the quantity and diversity of cargo sizes and shapes increase. Motivated by realistic needs, this study aims to develop a UNISON-based framework that integrates the merging spaces algorithm, a novel simple but effective hybrid simplified swarm optimization genetic algorithm (SSO-GA), and a multi-populations co-evolution strategy to determine the loading sequence of parcels to maximize space utilization and weight balance while satisfying to practical constraints. Specifically, the merging spaces algorithm merges fragmented small spaces resulting from loaded parcels into larger spaces, thereby facilitating the accommodation of additional parcels. The hybrid SSO-GA splits encoded solutions and updates segment using novel strategies resulting in the rearrangement of a group of parcels and their corresponding layouts for better space utilization. Furthermore, the multi-populations co-evolution strategy enhances the diversity of the search space and stabilizes solution quality by simultaneously exploiting the best solutions and exploring alternative solutions during the solution update process. An empirical study was conducted by using a public benchmark dataset which demonstrated the practical effectiveness of the proposed framework by significantly improving average space utilization while ensuring center balance and satisfying practical constraints. Furthermore, this study can also serve as a digital support system capable of assisting decision-makers in optimizing container loading operations, thereby improving productivity and saving valuable time.

Golf shot performance analysis: the effects of ground slope on weight transfer and shot characteristics

ABSTRACT The aim of this study was to examine the elite golf players’ centre of force (COF) displacements and golf shot performance during golf shots on three different ground inclinations. Twenty elite golf players were asked to hit golf shots on flat surface, 10° uphill and 10° ball above feet using their six irons. COF displacements (TekScan MatScan® force platform) and golf shot performance (TrackMan® golf radar system) were analysed. In this study, golf players’ weight transfer was similar in each shot (p > 0.05), except higher A-P sway during the ball above feet golf shots (p < 0.05). Reduced control of balance during shots from ball above feet resulted in shorter shot length than flat surface, even if the angles of attacks were similar (p < 0.05). In addition, increased COF distance during flat ground and ball above feet golf shots improved clubhead speed and shot length (p < 0.05). These results show that ball above feet slope condition, rather than uphill, alters postural control and golf swing characteristics. In order to improve the performance of these shots, it is recommended to add balance training and weight transfer techniques in A-P direction to the training programmes.

Soil organic matter persistence in hyperhumic colluvial soils caused by palaeofires, root inputs and mineral binding

Understanding the formation of long-term persistent soil organic matter (SOM) is key to optimizing soil management and predicting the response of the terrestrial organic carbon (OC) pool to climate change, yet our knowledge of the soil-type dependent weight of different stabilization pathways (e.g., recalcitrance and mineral binding) is fragmentary. Owing to their stratigraphy, the exceptionally SOM-rich (up to 2 m of mineral soil with >5% OC) colluvial slope deposits of Atlantic Europe (Haplic Umbrisol [colluvic/hyperhumic]) are archives of palaeo-environmental conditions including SOM formation pathways. The objective of this study was to determine how the different drivers of persistent SOM formation influenced the formation of these organic-rich soils. For this purpose, we use Holocene (∼9000 yrs) molecular composition records obtained from pyrolysis-GC–MS (Py-GC–MS) and thermally assisted hydrolysis and methylation (THM-GC–MS). The results emphasize three pathways to stability (i.e., persistence on millennial timescales): 1) palaeofires that generated recalcitrant pyrogenic SOM, 2) release of root-derived aliphatic macromolecules (suberin-like SOM), and 3) formation of microbial necromass. Pathways 1 and 2 are controlled by land use: Pathway 1 was relatively important under intense anthropogenic fire regimes and pyrophytic shrubland expansion; Pathway 2 was stimulated during early forest phases and under pasture conditions, when past societies focused vegetation management on grazing instead of fire; Pathway 3 was controlled by binding with aluminium-dominated mineral phases. However, we found indications that Pathway 2 (suberin input and preservation) relied partially on sorptive preservation as well. Aided by structured equation modeling (SEM), we show that the formation of persistent SOM pools was driven by balanced weights of i) microbial vs. plant-derived SOM and ii) intrinsic chemical properties of SOM (recalcitrance continuum) vs. mineral binding/occlusion, which varied in keeping with interactions between past land use, topography and vegetation. These findings are inconsistent with the prevalent paradigm of persistent SOM formation by sorptive/occlusive preservation of microbial necromass alone.

Mechanical power ratio threshold for ventilator-induced lung injury

RationaleMechanical power (MP) is a summary variable incorporating all causes of ventilator-induced-lung-injury (VILI). We expressed MP as the ratio between observed and normal expected values (MPratio).ObjectiveTo define a threshold value of MPratio leading to the development of VILI.MethodsIn a population of 82 healthy pigs, a threshold of MPratio for VILI, as assessed by histological variables and confirmed by using unsupervised cluster analysis was 4.5. The population was divided into two groups with MPratio above or below the threshold.Measurements and main resultsWe measured physiological variables every six hours. At the end of the experiment, we measured lung weight and wet-to-dry ratio to quantify edema. Histological samples were analyzed for alveolar ruptures, inflammation, alveolar edema, atelectasis. An MPratio threshold of 4.5 was associated with worse injury, lung weight, wet-to-dry ratio and fluid balance (all p < 0.001). After 48 h, in the two MPratio clusters (above or below 4.5), respiratory system elastance, mean pulmonary artery pressure and physiological dead space differed by 32%, 36% and 22%, respectively (all p < 0.001), being worse in the high MPratio group. Also, the changes in driving pressure, lung elastance, pulmonary artery occlusion pressure, central venous pressure differed by 17%, 64%, 8%, 25%, respectively (all p < 0.001).LimitationsThe main limitation of this study is its retrospective design. In addition, the computation for the expected MP in pigs is based on arbitrary criteria. Different values of expected MP may change the absolute value of MP ratio but will not change the concept of the existence of an injury threshold.ConclusionsThe concept of MPratio is a physiological and intuitive way to quantify the risk of ventilator-induced lung injury. Our results suggest that a mechanical power ratio > 4.5 MPratio in healthy lungs subjected to 48 h of mechanical ventilation appears to be a threshold for the development of ventilator-induced lung injury, as indicated by the convergence of histological, physiological, and anatomical alterations. In humans and in lungs that are already injured, this threshold is likely to be different.

The life of the Sun

Understanding the development and evolution of the Sun is critical for understanding the origins of our solar system and the circumstances for life on Earth. We can learn about our suns dynamics, energy output, and magnetic activity by analysing its evolution, and we can even forecast solar events that affect our world. Extensive study has indicated that the Sun is now in its main sequence stage, but research on its future development, such as becoming a red giant or crashing into a white dwarf, is still underway. Solar evolution research also sheds light on the inner workings of other stars and fundamental processes in the cosmos. The Hertzsprung-Russell diagram aids in the classification and understanding of stars by providing essential information about their life cycle and attributes. The pre-main sequence, main sequence, and post-main sequence stages of the Suns origin and development are discussed in this article. It examines the origin of the Sun from interstellar materials as well as the probable impact of core-collapse supernovae. It also delves into the main sequence period, where stars masses and ages play important roles in shaping their properties. The main sequences existence is linked to hydrostatic equilibrium and the balance of energy production and gas weight. The scattering of stars that depart from the main sequence, such as red giants and white dwarfs, is also discussed in the article. Finally, it dives into post-main sequence development, in which the Sun switches from hydrogen fusion to helium fusion, causing the star to expand and cool. Finally, the Suns ultimate phase of development involves the burning of hydrogen and helium, which results in the expulsion of outer layers and the creation of a planetary nebula. The remaining core cools and transforms into a black dwarf, bereft of nuclear and gravitational energy sources.

An explicit finite element discrete crack analysis of open hole tension failure in composites

Developing efficient, robust methods for predicting the progressive failure of carbon fiber composites under tension is essential for optimal design, balancing weight reduction, damage tolerance, and service life. Implicit finite element (FE) methods struggle with the complex interplay of failure mechanisms, leading to a heavy reliance on costly, time-consuming experimental testing. This study introduces a novel explicit algorithm designed for laminate-level mesh models, capable of simulating cohesive cracks without predefined paths. Utilizing an explicit finite element software approach, our method effectively addresses convergence issues associated with the non-linear and unstable nature of composite failures during quasi-static loading. Contrasting with implicit FE method, this mesh-independent approach is both practical and numerically robust. The algorithm’s performance, tested on carbon-fiber reinforced composites with varying ply configurations [452/-452]s, [45n/90n/-45n/0n]s and [45/90/-45/0]ns (n=1/2/4/8), demonstrates improved simulation accuracy and efficiency over implicit FE methods, aligning well with prior experimental and simulation data. This advancement offers a promising solution for accurately simulating and understanding the complex failure behavior of these composites.