Predicting healthcare costs for chronic diseases is challenging for actuaries, as these costs depend not only on traditional risk factors but also on patients’ self-perception and treatment behaviors. To address this complexity and the unobserved heterogeneity in cost data, we propose a dual-structured learning statistical framework that integrates covariate clustering into finite mixture of generalized linear models, effectively handling high-dimensional, sparse, and highly correlated covariates while capturing their effects on specific subgroups. Specifically, this framework is realized by imposing a penalty on the prior similarities among covariates, and we further propose an expectation-maximization-alternating direction method of multipliers (EM-ADMM) algorithm to address the complex optimization problem by combining EM with the ADMM. This paper validates the stability and effectiveness of the framework through simulation and empirical studies. The results show that our framework can leverage shared information among high-dimensional covariates to enhance fitting and prediction accuracy, while covariate clustering can also uncover the covariates’ network relationships, providing valuable insights into diabetic patients’ self-perception data.

In laser systems requiring a flat-top distribution of beam intensity, beam smoothing is a critical technology for enhancing laser energy deposition onto the focal spot. The continuous phase modulator (CPM) is a key component in beam smoothing, as it introduces high-frequency continuous phase modulation across the laser beam profile. However, the presence of the CPM makes it challenging to measure and correct the wavefront aberration of the input laser beam effectively, leading to unwanted beam intensity distribution and bringing difficulty to the design of the CPM. To address this issue, we propose a deep learning enabled robust wavefront sensing (DLWS) method to achieve effective wavefront measurement and active aberration correction, thereby facilitating active beam smoothing using the CPM. The experimental results show that the average wavefront reconstruction error of the DLWS method is 0.04 μm in the root mean square, while the Shack–Hartmann wavefront sensor reconstruction error is 0.17 μm.

A multifunctional optical diagnostic system, which includes an interferometer, a refractometer and a multi-frame shadowgraph, has been developed at the Shenguang-II upgrade laser facility to characterize underdense plasmas in experiments of the double-cone ignition scheme of inertial confinement fusion. The system employs a 266 nm laser as the probe to minimize the refraction effect and allows for flexible switching among three modes of the interferometer, refractometer and multi-frame shadowgraph. The multifunctional module comprises a pair of beam splitters that attenuate the laser, shield stray light and configure the multi-frame and interferometric modules. By adjusting the distance and angle between the beam splitters, the system can be easily adjusted and switched between the modes. Diagnostic results demonstrate that the interferometer can reconstruct electron density below 1019 cm–3, while the refractometer can diagnose density approximately up to 1020 cm–3. The multi-frame shadowgraph is used to qualitatively characterize the temporal evolution of plasmas in the cases in which the interferometer and refractometer become ineffective.

This paper studies a novel Brownian functional defined as the supremum of a weighted average of the running Brownian range and its running reversal from extrema on the unit interval. We derive the Laplace transform for the squared reciprocal of this functional, which leads to explicit moment expressions that are new to the literature. We show that the proposed Brownian functional can be used to estimate the spot volatility of financial returns based on high-frequency price observations.

We report on an experimental study in which Lagrangian tracking is applied to millions of microscopic particles floating on the free surface of turbulent water. We leverage a large jet-stirred zero-mean-flow apparatus, where the Reynolds number is sufficiently high for an inertial range to emerge while the surface deformation remains minimal. Two-point statistics reveal specific features of the flow, deviating from the classic description derived for incompressible turbulence. The magnitude of the relative velocity is strongly intermittent, especially at small separations, leading to anomalous scaling of the second-order structure functions in the dissipative range. This is driven by the divergent component of the flow, leading to fast approaching/separation rates of nearby particles. The Lagrangian relative velocity shows strong persistence of the initial state, such that the ballistic pair separation extends to the inertial range of time delays. Based on these observations, we propose a classification of particle pairs based on their initial separation rate. When this is much smaller than the relative velocity prescribed by inertial scaling (which is the case for the majority of the observed particle pairs), the relative velocity transitions to a diffusive growth and the Richardson–Obukhov super-diffusive dispersion is recovered.

Path planning for the unmanned aerial vehicle (UAV) is to assist in finding the proper path, serving as a critical role in the intelligence of a UAV. In this paper, a path planning for UAV in three-dimensional environment (3D) based on enhanced gravitational search algorithm (EGSA) is put forward, taking the path length, yaw angle, pitch angle, and flight altitude as considerations of the path. Considering EGSA is easy to fall into local optimum and convergence insufficiency, two factors that are the memory of current optimal and random disturbance with chaotic levy flight are adopted during the update of particle velocity, improving the balance between exploration and exploitation for EGSA through different time-varying characteristics. With the identical cost function, EGSA is compared with seven peer algorithms, such as moth flame optimization algorithm, gravitational search algorithm, and five variants of gravitational search algorithm. The experimental results demonstrate that EGSA is superior to the seven comparison algorithms on CEC 2020 benchmark functions and the path planning method based on EGSA is more valuable than the other seven methods in diverse environments.

Systolic blood pressure (SBP) is significantly associated with body composition in children and adolescents. However, which one of the components of body composition is the dominant contributor to SBP in children and adolescents remains unclear. We, therefore, aimed to determine the dominant contributor to SBP among components of body composition in a large cohort of American children and adolescents derived from the National Health and Nutrition Examination Survey with cross-sectional analysis. In total, 13 618 children and adolescents (median age 13 years; 6107 girls) with available data on whole-body dual-emission X-ray absorptiometry measurements were included. Multiple linear regression showed that SBP was associated with higher total fat-free mass in boys (β = 0·49, P < 0·001) and girls (β = 0·47, P < 0·001) and with higher total fat mass only in boys (β = 0·12, P < 0·001) after adjustment for covariates. When taking fat distribution into consideration, SBP was associated with higher trunk fat mass (boys: β = 0·28, P < 0·001; girls: β = 0·15, P < 0·001) but negatively associated with leg fat mass (Boys: β = −0·14, P < 0·001; Girls: β = −0·11, P < 0·001), in both boys and girls. Dominance analysis showed that total fat-free mass was the dominant contributor to SBP (boys: 49 %; girls: 55·3 %), followed by trunk fat mass (boys: 32·1 %; girls: 26·9 %); leg fat mass contributed the least to SBP in boys (18·9 %) and girls (17·8 %). Our findings indicated that total fat-free mass was not only associated with SBP but also the most dominant contributor to SBP variation in American children and adolescents.

The impact of hepatitis B virus (HBV) infection on clinical outcomes of coronavirus disease 2019 (COVID-19) remains unclear. The aim of this study is to explore this impact. For this systematic review and meta-analysis, we searched PubMed, Web of Science, Embase, Cochrane library, China National Knowledge Infrastructure (CKNI), China Science and Technology Journal Database (VIP), and Wan Fang database for articles between 1 January 2020 and 1 February 2023. We used the Newcastle–Ottawa Quality Assessment to evaluate the study’s quality. A random-effects meta-analysis was performed utilising the rates of severe/critical illness and death in COVID-19 patients with and without HBV infection. Eighteen studies with a total of 40,502 participants met the inclusion criteria. The meta-analysis showed that compared to those without HBV infection, COVID-19 patients with HBV were at increased risk of mortality (OR = 1.65, I2 = 58%, and 95% CI 1.08–2.53) and severity (OR = 1.90, I2 = 44%, and 95% CI 1.62–2.24). The region and gender may influence the outcomes of COVID-19 patients with HBV infection, but it requires more global data to confirm. In conclusion, HBV infection is significantly linked to an increased risk of severity and mortality in COVID-19.

Few studies examined the association of energy, macronutrients and food consumption at dinner v. breakfast with hypercholesterolaemia. A total of 27 911 participants from the National Health and Nutrition Examination Survey (2003–2016) were included in the cross-sectional study. Energy, macronutrients and food consumption at breakfast, dinner and the difference at dinner v. breakfast (Δratio) were calculated. Multiple logistic regression models and substitution effects of foods at dinner with breakfast were also performed. After adjustment for potential covariates, compared with the lowest quintile, participants in the highest quintile of Δratio in terms of energy had a higher risk of prevalent hypercholesterolaemia (ORΔratio of energy 1·16, 95 % CI (1·01, 1·33)) mainly due to Δratio of low-quality carbohydrates and plant protein (ORΔratio of low-quality carbohydrates 1·19; 95 % CI (1·05, 1·35)); ORΔratio of plant protein 1·13; 95 % CI (1·01, 1·28)). ΔAdded sugars and Δnuts were associated with hypercholesterolaemia (ORΔadded sugars 1·01; 95 % CI (1·00, 1·02)); ORΔnuts 1·08; 95 % CI (1·01, 1·16)). Furthermore, the substitution of added sugars, nuts and processed meat at dinner with breakfast could reduce the OR of hypercholesterolaemia. This study indicated that among US adults, overconsumption of energy, macronutrients including low-quality carbohydrates and plant protein at dinner than breakfast was significantly associated with a higher risk of prevalent hypercholesterolaemia. The replacing of added sugar, nuts and processed meat at dinner with breakfast reduced the risk of prevalent hypercholesterolaemia. This study emphasised the importance of meal timing in the prevention of hypercholesterolaemia.

Patients with cirrhosis experience worse health-related quality of life (HRQoL), and attempts are warranted further exploration of modifiable factors to improve HRQoL. Data on the impact of malnutrition risk on HRQoL among cirrhosis are limited; thus, we aimed to strengthen understanding by clarifying the relationship between nutritional status and low HRQoL in patients with decompensated cirrhosis. Consecutive inpatients with cirrhosis attending our department within a tertiary hospital were studied. Generic health profiles and malnutrition risk were evaluated by the EuroQol-5D (EQ-5D) and Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) score, respectively. Multiple linear regression analysis was used to determine association of malnutrition risk with low HRQoL. In this cohort of 364 patients with median age of 64 years and 49·5 % male, 55·5 % of the study population reported impairment pertinent to HRQoL in at least one dimension in terms of the EQ-5D. Moreover, malnutrition risk (RFH-NPT score: β coefficient = −0·114, P = 0·038) was proved to be independently associated with poor HRQoL in multiple analysis, after adjustment for significant variables like age, BMI and markers of decompensation. Notably, we found that health dimensions representing physical function (i.e. mobility, self-care and usual activities) are substantially affected, while malnourished patients reported less frequencies of complaints in other domain such as anxiety/depression. In conclusion, the risk of malnutrition assessed by the RFH-NPT score is independently associated with low HRQoL. It is operational to improve HRQoL by identifying patients at high malnutrition risk and providing timely nutrition treatment.

The mitochondrial genome provides important information for phylogenetic analysis and an understanding of evolutionary origin. In this study, the mitochondrial genomes of Ilisha elongata and Setipinna tenuifilis were sequenced, which are typical circular vertebrate mitochondrial genomes composed of 16,770 and 16,805 bp, respectively. The mitogenomes of I. elongata and S. tenuifilis include 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA), two ribosomal RNA (rRNA) genes and one control region (CR). Both two species' genome compositions were highly A + T biased and exhibited positive AT-skews and negative GC-skews. The genetic distance and Ka/Ks ratio analyses indicated that 13 PCGs were affected by purifying selection and the selection pressures were different from certain deep-sea fishes, which were most likely due to the difference in their living environment. Results of phylogenetic analysis support close relationships among Chirocentridae, Denticipitidae, Clupeidae, Engraulidae and Pristigasteridae based on the nucleotide and amino acid sequences of 13 PCGs. Within Clupeoidei, I. elongata and S. tenuifilis were most closely related to the family Pristigasteridae and Engraulidae, respectively. These results will help to better understand the evolutionary position of Clupeiformes and provide a reference for further phylogenetic research on Clupeiformes species.

Fibronectin type III domain-containing protein 5 (FNDC5) is a transmembrane protein and the precursor of irisin, which serves as a systemic exerkine/myokine with multiple origins. Since its discovery in 2012, this hormone-like polypeptide has rapidly evolved to a component significantly involved in a gamut of metabolic dysregulations and various liver diseases. After a decade of extensive investigation on FNDC5/irisin, we are still surrounded by lots of open questions regarding its diagnostic and therapeutic values. In this review, we first concentrated on the structure–function relationship of FNDC5/irisin. Next, we comprehensively summarised the current knowledge and research findings regarding pathogenic roles/therapeutic applications of FNDC5/irisin in the context of non-alcoholic fatty liver disease, fibrosis, liver injury due to multiple detrimental insults, hepatic malignancy and intrahepatic cholestasis of pregnancy. Moreover, the prominent molecules involved in the underlying mechanisms and signalling pathways were highlighted. As a result, emerging evidence reveals FNDC5/irisin may act as a proxy for diagnosing liver disease pathology, a sensitive biomarker for assessing damage severity, a predisposing factor for surveilling illness progression and a treatment option with protective/preventive impact, all of which are highly dependent on disease grading and contextually pathological features.

Several Drosophila species (Diptera: Drosophilidae) have become serious economic pests of berry and soft-skinned stone fruits around the world. Prominent examples are Drosophila suzukii (Matsumura), D. melanogaster (Meigen), D. hydei (Sturtevant), and D. immigrans (Sturtevant). Information on the biology and ecology of Drosophila is important for a better understanding of these important fruit pests and, ultimately, for fruit protection. In this study, the gut bacteriomes of these four Drosophila species were surveyed and the differences among bacterial communities were characterised. The 16S rRNA genes of gut microbes were sequenced by Illumina MiSeq technology (Illumina, San Diego, California, United States of America), followed by α-diversity and β-diversity analyses. The results show that bacteria of the family Enterobacteriaceae (Kluyvera and Providencia; phylum Proteobacteria) dominated all four Drosophila species. Specific dominant gut bacterial communities were found in each Drosophila species. The dominant families in D. melanogaster and D. suzukii were Enterobacteriaceae, Comamonadaceae, and Acetobacteraceae. In the intestine of D. hydei, Enterobacteriaceae had a proportion of 56.99%, followed by Acetobacteraceae, Spiroplasmataceae, and Bacillales Incertae Sedis XII. In D. immigrans, besides Enterobacteriaceae, Alcaligenaceae, Flavobacteriaceae, Xanthomonadaceae, Comamonadaceae, and Sphingobacteriaceae also had high relative abundance. These data expand current knowledge about the putative function related to gut microbes – for example, the metabolism of carbohydrates, amino acids, inorganic ions, lipids, and secondary metabolites. This knowledge provides a basis for further metatranscriptomic and metaproteomic investigations.

Hebei Province was affected by two coronavirus disease 2019 (COVID-19) outbreak waves during the period 22 January 2020 through 27 February 2020 (wave 1) and 2 January 2021 through 14 February 2021 (wave 2). To evaluate and compare the epidemiological characteristics, containment delay, cluster events and social activity, as well as non-pharmaceutical interventions of the two COVID-19 outbreak waves, we examined real-time update information on all COVID-19-confirmed cases from a publicly available database. Wave 1 was closely linked with the COVID-19 pandemic in Wuhan, whereas wave 2 was triggered, to a certain extent, by the increasing social activities such as weddings, multi-household gatherings and church events during the slack agricultural period. In wave 2, the epidemic spread undetected in the rural areas, and people living in the rural areas had a higher incidence rate than those living in the urban areas (5.3 vs. 22.0 per 1 000 000). Furthermore, Rt was greater than 1 in the early stage of the two outbreak waves, and decreased substantially after massive non-pharmaceutical interventions were implemented. In China's ‘new-normal’ situation, development of targeted and effective intervention remains key for COVID-19 control in consideration of the potential threat of new coronavirus strains.

ABSTRACT IMPACT: It is our hope that a better understanding of the relationship between genetic variants that influence heart failure precursor traits will not only inform clinical care, but enable better assessment of inherited risk and will identify new biological targets for drug development. OBJECTIVES/GOALS: In this project, using a large-scale human genomic dataset with extensive phenotype data available, we intend to interrogate the known MTSS1 variants that have been associated with heart failure (HF) in previous GWAS studies in order to understand the directionality and mechanisms of their effects. METHODS/STUDY POPULATION: Data was obtained from the UK Biobank, a large prospective cohort of ˜500,000 patients across the United Kingdom with extensive phenotype data, including ˜50,000 patients with cardiac MRI and ˜200,000 with whole exome sequencing. We test for associations between genetic variants at the MTSS1 locus and HF precursor traits using logistic regression or linear regression, adjusting for age, gender, and principal components (PCs) of ancestry. For rare variant analyses we ‘bin’ rare variants (MAF < 0.01) using the software tool BioBin to aggregate low frequency genetic variants into single genetic units. RESULTS/ANTICIPATED RESULTS: Preliminary data have shown that variants in the known MTSS1 enhancer region which reduce MTSS1 expression are associated with smaller, more contractile hearts. We anticipate that common variants known to reduce enhancer activity will attenuate heart failure precursor traits, will be associated with a reduced risk clinical heart failure, and will favorably impact clinical outcomes once HF is established. We also anticipate that rare exonic variants predicted to impair MTSS1 function will attenuate heart failure precursor traits. DISCUSSION/SIGNIFICANCE OF FINDINGS: Through this work, we intend to take advantage of multiple novel approaches to better understand a complex disease process, identify a new potential therapeutic target (namely one that targets cardiac function), and to determine which patient subgroups will benefit from this our therapeutic interventions and why.

The surface topology of biomaterial has a definite effect on the growth behavior of nerve cells for peripheral nerve regeneration. In this study, the silk fibroin (SF) film with different anisotropic microgroove/ridge was constructed by micropatterning technology. The effects of topologies width on the directional growth of dorsal root ganglion (DRG) neurons were evaluated. The results showed that the topological structure of the SF film with higher SF concentration was more clear and complete. The microtopography of the SF film with a concentration of 15% and a groove width of around 30 μm could effectively guide the directional growth of the nerve fibers of DRG. And nerve fibers could obviously form nerve fiber bundles which may have a certain pavement effect on the recovery of nerve function. The study indicated that the SF film with a specific width of the topological structure may have potential applications in the field of directional nerve regeneration.

Intelligent control of friction and adhesion has attracted much attention for use in soft robotics, human-sensor interfaces, and bionics. Here we introduce a shape memory photonic crystal (SMPC) polymer that can be programmed and recovered by solvent to realize switchable surface friction. Micro sliding test show that the friction coefficient on this SMPC in the programmed and recovered state can vary by three times. We also show that the mechanism behind this switchable friction coefficient is the surface roughness related adhesion.