Loss Model Research Articles

PARAMETER ESTIMATION OF LOGNORMAL AND PARETO TYPE I DISTRIBUTIONS USING FREQUENTIST AND BAYESIAN INFERENCES

Extreme events are events that rarely occur but they cause substantial losses. Insurance companies need to take extreme events into account in risk management because extreme events can have a negative impact on the company's financial health. As a result, insurance companies need an appropriate loss model that matches the empirical data from these extreme events. A distribution that is heavy-tailed and skewed to the right is a good distribution for modeling the magnitude of losses from extreme events. In this paper, two distributions with heavy tails and skew to the right will be used to model the magnitude of losses from extreme events, namely the lognormal distribution and the Pareto distribution type I. The parameters of these distributions are estimated using two inferences, namely the frequentist and Bayesian inferences. In the frequentist inference, two methods are applied, namely the moment method and maximum likelihood. On Bayesian inference, two prior distributions are used, namely uniform and Jeffrey. Test model suitability is carried out by visually comparing the model distribution function with the empirical distribution function, as well as by comparing the Root Mean Square Error (RMSE) value. The visualization results of the distribution function and RMSE values ​​show that in general, the Bayesian inference is better at estimating parameters than the frequentist inference. In the frequentist inference, the maximum likelihood method can provide better estimated values ​​than the moment method. In the Bayesian inference, the two prior distributions show a relatively similar fit to the data and tend to be better than the frequentist inference.

Development of a predictive model for loss of functional and cognitive abilities in long-term care home residents: a protocol

IntroductionLong-term care (LTC) residents require extensive assistance with daily activities due to physical and cognitive impairments. Medical treatment for LTC residents, when not aligned with residents’ wishes, can cause discomfort...

Modeling GATA2 deficiency in mice: the R396Q mutation disrupts normal hematopoiesis.

GATA2 deficiency is an autosomal dominant germline disorder of immune dysfunction and bone marrow failure with a high propensity for leukemic transformation. While sequencing studies have identified several secondary mutations thought to contribute to malignancy, the mechanisms of disease progression have been difficult to identify due to a lack of disease-specific experimental models. Here, we describe a murine model of one of the most common GATA2 mutations associated with leukemic progression in GATA2 deficiency, Gata2R396Q/+. While mutant mice exhibit mild defects in peripheral blood, they display significant hematopoietic abnormalities in the bone marrow, including a reduction in hematopoietic stem cell (HSC) function and intrinsic biases toward specific stem cell subsets that differ from previous models of GATA2 loss. Supporting this observation, single-cell RNA sequencing of hematopoietic progenitors revealed a loss of stemness, myeloid-bias, and indications of accelerated aging. Importantly, we show that Gata2R396Q/+ exerts effects early in hematopoietic development, as mutant mice generate fewer HSCs in the aorta gonad mesonephros, and fetal liver HSCs have reduced function. This reduced and altered pool of HSCs could be potential contributors to leukemic transformation in patients, and our model provides a useful tool to study the mechanisms of malignant transformation in GATA2 deficiency.

Ameliorating macrophage pyroptosis via ANXA1/NLRP3/Caspase-1/GSDMD pathway：Ac2-26/OGP-loaded intelligent hydrogel enhances bone healing in diabetic periodontitis.

Craniofacial bone defect healing in periodontitis patients with diabetes background has long been difficult due to increased blood glucose levels which cause overproduction of reactive oxygen species (ROS) and a low pH environment. These conditions negatively affect the function of macrophages, worsen inflammation and oxidative stress, and ultimately, hinder osteoblasts' bone repair potential. In this study, we for the first time found that ANXA1 expression in macrophages was reduced in a diabetic periodontitis environment, with the activation of the NLRP3/Caspase-1/GSDMD signaling pathway, and, eventually, increased macrophage pyroptosis. Next, we have developed a new GPPG intelligent hydrogel system which was ROS and pH responsive, and loaded with Ac2-26, an ANXA1 bioactive peptide, and osteogenic peptide OGP as well. We found that Ac2-26/OGP/GPPG can effectively reduce ROS, mitigates macrophage pyroptosis via the ANXA1/NLRP3/Caspase-1/GSDMD pathway and enhanced osteogenic differentiation. The effect of Ac2-26/OGP/GPPG in regulation of pyroptosis and bone defect repair was also further validated by animal experiments on periodontitis-induced tooth loss model in diabetic rats. To conclude, our study unveils the effect of ANXA1 on macrophage pyroptosis in periodontitis patients with diabetes, based on which we introduced a promising innovative hydrogel system for improvement of bone defects repair in diabetic periodontitis patients via targeting macrophage pyroptosis and enhancing osteogenic potential.

A Review on the Empirical Core Loss Models for Symmetric Flux Waveforms

A Review on the Empirical Core Loss Models for Symmetric Flux Waveforms

Machine Learning Based Throughput Enhancement in Fifth Generation Networks

The 5G Enhanced Mobile Broadband (eMBB) category offers faster data rates, network capacity, and user experiences than prior generations. This research aims to boost the 5G uplink User Equipment (UE) user data transfer rate. We use Python to build frameworks and analyze data. A 250-m-radius center-excited Picocell Base Station (PBS) is investigated to support 15 clients. Cell-range Poisson distribution determines user position. All UEs send Channel State Information (CSI) to the PBS, which evaluates signal transmission channel conditions. The study uses Rayleigh, Rician, free space path, and longdistance route loss models. This inquiry produces a channel state dataset and then it is formulated dataset is dynamic. For servicespecific requirements, UEs use K-means clustering. Clustering concatenates bandwidth, enhancing system efficiency and UE sum rate. Observations from simulation findings. UEs are grouped by channel gain, achievable data rate, and minimum servicerequired data rate. Users in cluster 3 achieve the highest cumulative rate of 9.09 Mbps after clustering with an average of 7.16 Mbps. Bandwidth concatenation increased system capacity, meeting each UEs service needs. After evaluating different clustering models performance criteria, K-means remains the best algorithm for the framework. The methodology was carefully designed to satisfy study goals. This research will investigate beamforming and dynamic clustering to improve user fairness and performance.

Research on Natural Disaster Risk Based on Garch Volatility and Monte Carlo Algorithm

The purpose of this paper is to study the optimal decision problem of different agents. Firstly, the expression of the profit process of the insurance company is established, and then the loss caused by the natural disaster is fitted into the insurance formula using the double cross-verified natural disaster model. The first is the prediction model of random disaster loss based on Garch volatility test. The other is ridge regression, which combines the possible relevant factors and then makes the forecast. The two results were cross-verified by Garch volatility test again, and then risk assessment and scheme decision were made based on Monte Carlo algorithm and time value theory, and 50,000 simulations were carried out. By estimating the probability of frequency, the probability of bankruptcy under different premiums is obtained. This paper makes an empirical study of New Mexico and Henan in China. For the United States, the paper concludes that an average unit price of $34-35 per policy is appropriate. For Henan Province, this paper focuses on the implementation of natural disaster insurance, and carries out model simulation. The result shows that the premium price of 15% bankruptcy rate is 8 ~ 10 yuan, which is lower than the current policy price, proving that the policy has advantages.

Comparative analysis of the hemostatic effect of systemic recombinant Factor VIIa and exogenous fibrin monomer in an experimental model of heparinization and posttraumatic blood loss

This article presents the results of a study of the systemic hemostatic action of recombinant Factor VIIa in a rabbit model of heparin-induced coagulopathy and posttraumatic bleeding, compared to the administration of exogenous fibrin monomer. The coagulopathy was induced by a single intravenous injection of unfractionated heparin at a dose of 150 IU/kg 15 minutes before injury. Recombinant Factor VIIa (270 μg/kg) or fibrin monomer (0.25 mg/kg) was used as systemic hemostatic agents. One hour after administrating the agents, a standardized liver injury was inflicted, followed by an assessment of blood loss characteristics. Using rotational thromboelastometry and coagulation tests, animal venous blood was analyzed for coagulation time, alpha angle, clot formation time, maximum clot firmness, clot density at 10 minutes, activated partial thromboplastin time, prothrombin time, thrombin time, and fibrinogen concentration. Pharmacologically induced coagulopathy resulted in shifts to a hypocoagulable profile, associated with severe blood loss (1.9 times, p = 0.028) and high animal mortality (26.1%, p = 0.022) compared to the control group. Preventive administration of fibrin monomer or recombinant Factor VIIa reduced posttraumatic blood loss (by 5.4 times, p 0.001, and by 2.1 times, p = 0.009, respectively), resulting in a decrease in mortality rates. However, the administration of these agents did not correct the hypocoagulable profile as observed in thromboelastometry and coagulation tests. These data demonstrate the hemostatic effect of both agents, with a more pronounced effect after fibrin monomer administration, and suggest potential use of low doses of fibrin monomer in trauma-related hemorrhage. The mechanism of action of fibrin monomer requires further investigation. Therefore, fibrin monomer, a fibrinogen derivative obtained from blood plasma, could be a valuable candidate for managing wound bleeding in addition to recommended systemic hemostatics.

Research on Performance Prediction of Air Quality Assurance Systems for Gas Turbines Based on Novel Test Method

The quality of air intake significantly impacts the overall performance of gas turbines. A new high-precision testing method for the air intake quality assurance system of gas turbines has been proposed, and the influence of typical intake conditions on the system was studied through this testing method. The research results indicate a positive correlation between filtration efficiency and particle size. Atmospheric temperature, particle concentration, filter differential pressure, and atmospheric humidity all affect filtration efficiency, with their influence decreasing in that order. Additionally, this paper presents a performance prediction model based on the LSTM neural network. The calculation results show that the errors of the filter pressure loss and filtration efficiency model test set are both less than 3%, reflecting the characteristics of pressure loss and efficiency well. The research results have significant engineering application value and provide experimental basis for establishing technical standards and high-precision detection systems for air quality assurance in gas turbines.

Model-based compensation and uncertainty analysis of support bearing losses in a chain drive dynamometer

Abstract Efficiency testing of chain drives has received renewed attention in recent years from sectors including elite cycling, e-mobility and automotive engineering. This is because of a desire to maximise performance, reduce energy consumption and minimise wear rate at a component level. In particular, chain and lubricant manufacturers have developed test rigs that replicate transmission drives in order to measure the efficiency and wear behaviour of the chain and sprocket. This paper explores the impact that compensating parasitic losses from test rigs has on the measurement uncertainty. The analytical process of propagating measurement uncertainty for a dynamometer rig is presented, based on the use of modelled bearing friction losses in the rig and quoted datasheet values for the measurement transducers. Two commonly used bearing models are used to illustrate the process. It is found that the measurement uncertainty is dominated by the transducer uncertainties, particularly speed measurement and repeated experimental results corroborate this trend. However, experimental experience also suggests that the uncertainty derived using GUM Method B is conservative compared to the actual system. The research reported also highlights the importance of validating models of parasitic losses for measurement hardware.

In Silico Modeling of Food Digestion, Nutrient Bioavailability and Loss to Colon Linked to Microbiome Dysbiosis

In Silico Modeling of Food Digestion, Nutrient Bioavailability and Loss to Colon Linked to Microbiome Dysbiosis

Causal Effect of Smoking and Cessation on Tooth Loss.

To estimate the causal effects of smoking and cessation on tooth loss using instrumental variable (IV) analysis. Data from the Behavioural Risk Factor Surveillance System (BRFSS), conducted from 1995 to 2006, 2008, 2010, and 2012 in 50 U.S. states and Washington DC, were merged with cigarette pack prices and smoking ban data from the CDC 'Tax Burden on Tobacco' and 'State Tobacco Activities Tracking and Evaluation' (STATE) System. Prices and bans served as IVs for ever smoking and cessation in a control function IV model for self-reported edentulism and loss of 6+ teeth. IV models were adjusted for age, sex, race/ethnicity, educational attainment, type 2 diabetes, state unemployment rates, state health expenditures, and state fixed effects. Ever smoking cigarettes increased the risk of edentulism by 2.6% (95% CI: 2.3%-2.8%) and the risk of loss of 6+ teeth by 10.7% (95% CI: 10.0%-11.3%). Smoking cessation reduced risks of edentulism and loss of 6+ teeth by 7.6% (95% CI: -7.8% to -742%) and 13.5% (95% CI: -13.7% to 13.3%), respectively. This study provides robust evidence that smoking increases tooth loss risk, while cessation significantly reduces it, emphasizing the oral health benefits of tobacco control policies.

Experimental Evaluation of MIMO Channel Capacity for Wireless Communication Channels

This research evaluates the channel capacity (CC) of 5th Generation Multiple Input Multiple Output (MIMO) antennas for propagation channels used in wireless communication. In the presence of several frequency sources for the information and communication channels, the effect on the CC of one-port and multi-port antennas is observed using the Path Loss Model (PLM), which is significantly impacted due to the number of antennas used and their characteristics. The CC is also estimated using a different approach, Kronecker's Model (KM). The channel matrix using both models is estimated by maintaining 5 cm and 25 cm spacing between the transmitting and receiving antennas. At 2.4 GHz for a 1-port antenna-based channel, the CC calculated using PLM is 5.5 bps/Hz for both spacing, whereas the CC calculated using KM is 3.65 bps/Hz and 3.12 bps/Hz for 5 cm and 25 cm spacing, respectively. The CC in the PLM is found between 35 to 140 bps/Hz at a frequency of 3.5 GHz, whereas it is reported between 12 to 38 bps/Hz using the KM at the same frequency, irrespective of distances. The maximum CC calculated using PLM is 5 bps/Hz for a 1-port antenna-based channel, 34 bps/Hz for 2-port MIMO antenna-based channels, 80 bps/Hz for 4-port MIMO antenna-based channels, and 157 bps/Hz for 8-port MIMO antenna based channels in the frequency band from 3.45 GHz to 3.7 GHz. Thus, it is experimentally confirmed that the capacity enriched by approximately 4 times on increasing the number of antenna ports from 2 to 8 and operating frequency.

Optimal configuration of shared energy storage for industrial users considering lifetime and charge-discharge strategy coupling

With the development of renewable energy, energy storage has become one of the key technologies to solve the uncertainty of power generation and the disorder of power consumption and shared energy storage has become the focus of attention for its cost-effective characteristics. However, it is always difficult to quantify the coupling relationship between charge and discharge strategy and life expectancy in energy storage configuration. Based on this, this paper proposes an industrial user-side shared energy storage optimal configuration model, which takes into account the coupling characteristics of life and charge and discharge strategy. Firstly, the life loss model of lithium iron phosphate battery is constructed by using the rain-flow counting method. In order to further optimize the user-side shared energy storage configuration in the multi-user scenario, a two-layer model of energy storage configuration is built, and the Big M method and the Karush-Kuhn-Tucker (KKT) conditions are used to equivalently transform the constraints. Based on the predicted life of energy storage and the dichotomy method, the optimal energy storage configuration results are obtained. Comparing the energy cost of users under the three scenarios of no storage configuration, storage configuration according to fixed storage life, and storage configuration according to the model proposed in this paper, the results show that the proposed method can help accurately describe the energy storage model, increase the utilization rate of the power station, and improve the electricity economy of users.

Inhibition of the cGAS‑STING Pathway Reduces Cisplatin-Induced Inner Ear Hair Cell Damage.

Although cisplatin is a widely used chemotherapeutic agent, it is severely toxic and causes irreversible hearing loss, restricting its application in clinical settings. This study aimed to determine the molecular mechanism underlying cisplatin-induced ototoxicity. Here, we established in vitro and in vivo ototoxicity models of cisplatin-induced hair cell loss, and our results showed that reducing STING levels decreased inflammatory factor expression and hair cell death. In addition, we found that cisplatin-induced mitochondrial dysfunction was accompanied by cytosolic DNA, which may act as a critical linker between the cyclic GMP-AMP synthesis-stimulator of interferon genes (cGAS-STING) pathway and the pathogenesis of cisplatin-induced hearing loss. H-151, a specific inhibitor of STING, reduced hair cell damage and ameliorated the hearing loss caused by cisplatin in vivo. This study underscores the role of cGAS-STING in cisplatin ototoxicity and presents H-151 as a promising therapeutic for hearing loss.

Analytical modelling and analysis of magnet eddy current loss in magnet‐surrounded permanent magnet synchronous machine caused by stator slot effect

Analytical modelling and analysis of magnet eddy current loss in magnet‐surrounded permanent magnet synchronous machine caused by stator slot effect

Stability of the Implant–Alveolar Bone Complex According to the Peri-Implant Bone Loss and Bone Quality: A Finite Element Analysis Study

Peri-implant bone loss and bone quality significantly affect the biomechanical stability and long-term success of dental implants. This study used finite element analysis to evaluate the stress distribution and deformation behavior of implants and alveolar bone according to bone loss (0–5 mm) and bone quality (normal and low). A finite element model was implemented based on a three-dimensional mandibular model. The mechanical properties of each component were assigned, and finite element analysis was performed using a static occlusal load. The results showed that progressive bone loss increased von Mises stresses in the implant fixture and surrounding bone, and low-quality bone showed a significant vulnerability to stress concentration. The 2 mm bone loss model showed the maximum stress in cortical bone, and from 3 mm onwards, the stress decreased due to extensive loss of cortical bone. This may be because extensive bone loss causes the implant to lose interface with cortical bone and contact only with cancellous bone. This study confirmed that bone loss and the vulnerability of bone quality may potentially affect implant failure. Continued research is needed to suggest customized implants based on the structural vulnerability of alveolar bone.

Performance Optimization of 5G–Satellite Integrated Networks for IoT Applications in Smart Cities: A Two-Ray Propagation Model Approach

The convergence of 5G terrestrial networks with satellite systems offers a revolutionary approach to achieving global, seamless connectivity, particularly for Internet of Things (IoT) applications in urban and rural settings. This paper investigates the implications of this 5G–satellite integrated network architecture, specifically through the application of the two-ray propagation model and the free-space path loss (FSPL) model. By simulating signal characteristics over varying distances, altitudes, and environmental parameters, we explore how factors such as transmitter height, satellite altitude, and frequency impact received power, path loss, channel capacity, and outage probability. The key findings indicate that received power decreases significantly with increasing distance, with notable oscillations in the two-ray model due to interference from ground reflections, particularly evident within the first 100 km. For example, at 50 km, a 300 km satellite altitude yields approximately −115 dBm in received power, while at 1000 km altitude, this power drops to around −136 dBm. Higher frequencies (e.g., 32 GHz) exhibit greater path loss than lower frequencies (e.g., 24 GHz), with a 5 dB difference observed at 1000 km, reinforcing the need for frequency considerations in long-range communication design. In terms of channel capacity, increasing bandwidth enhances achievable data rates but declines with distance due to diminishing received power. At 100 km, a 50 MHz bandwidth supports up to 4500 Mbps, while at 3000 km, capacity drops to around 300 Mbps. The outage probability analysis shows that higher signal-to-noise ratio (SNR) thresholds substantially increase the likelihood of communication failures, especially at distances exceeding 2000 km. For instance, at 3000 km, the outage probability for a 15 dB SNR threshold reaches approximately 25%, compared to less than 5% for a 5 dB threshold. These results underscore the critical trade-offs in designing 5G–satellite IoT networks, balancing bandwidth, frequency, SNR thresholds, and satellite altitudes for optimal performance across diverse IoT applications. The analysis provides valuable insights for enhancing connectivity and reliability in 5G–satellite integrated networks, especially in remote and underserved regions.

Orbital Migration Through Atmospheric Mass Loss

Abstract Atmospheric mass loss is thought to have strongly shaped the sample of close-in exoplanets. These atmospheres should be lost isotropically, leading to no net migration on the planetary orbit. However, strong stellar winds can funnel the escaping atmosphere into a tail trailing the planet. We derive a simple kinematic model of the gravitational interaction between the planet and this anisotropic wind, and derive expressions for the expected migration of the planet. Over the expected range of parameters, we find typical migrations of a few tenths to a few percent inward. We argue that this modest migration may be observable for planet pairs near mean motion resonances, which would provide an independent observational constraint on atmospheric mass loss models.

Multi-Objective Optimization Method for Performance Prediction Loss Model of Centrifugal Compressors

Multi-Objective Optimization Method for Performance Prediction Loss Model of Centrifugal Compressors