Nonlinear functional regression by functional deep neural network with kernel embedding

With the rapid development of deep learning in various fields of science and technology, such as speech recognition, image classification, and natural language processing, recently it is also widely applied in the functional data analysis (FDA) with some empirical success. However, due to the infinite dimensional input, we need a powerful dimension reduction method for functional learning tasks, especially for the nonlinear functional regression. In this paper, based on the idea of smooth kernel integral transformation, we propose a functional deep neural network with an efficient and fully data-dependent dimension reduction method. The architecture of our functional net consists of a kernel embedding step: an integral transformation with a data-dependent smooth kernel; a projection step: a dimension reduction by projection with eigenfunction basis based on the embedding kernel; and finally an expressive deep ReLU neural network for the prediction. The utilization of smooth kernel embedding enables our functional net to be discretization invariant, efficient, and robust to noisy observations, capable of utilizing information in both input functions and responses data, and have a low requirement on the number of discrete points for an unimpaired generalization performance. We conduct theoretical analysis including approximation error and generalization error analysis, and numerical simulations to verify these advantages of our functional net

Utjecaj transformirajućeg čimbenika rasta beta 1 dokazanog u autolognom presatku omentuma na cijeljenje kritičnoga koštanoga defekta žbične kosti kunića.

Fracture healing is a complex physiological process. Multiple factors regulate this cascade of molecular reactions, affecting different sites in the osteoblast lineage, through various processes such as: migration, proliferation, chemotaxis, differentiation, inhibition, and extracellular protein synthesis. The omentum is a serous membrane made up of a lattice of blood vessels and fat. Basically, it is a highly vasculated organ with a rich source of angiogenic factors that promote the growth of blood vessels into whatever tissue it is placed close to. Recent studies have revealed that the omentum, apart from being a great source of various growth factors, also contains omnipotent stem cells that can differentiate into a variety of cell types. The study was carried out on 16 adult male New Zealand rabbits in the same condition. A large segmental defect was created in the radius of each animal in groups A and B. In group B the defect was filled with a piece omental fat tissue. The animals were euthanized 56 days after the operation and the bones removed for histomorphometric analysis. Histomorphometric analysis was performed. The osteoblast interface (Ob.S/BS) proved to be the statistically significant parameter (P = 0.005). An osteoblast interface was found in the treated group in contrast to the control. The surface of trabecula covered with the osteiod and osteoblast interface showed a high degree of positive linear correlation, in both the control and the treated group. Our study shows that the statistically significant osteoblast interface leads to the conclusion that omental fat tissue has a certain influence on bone turnover, especially on the formation of the newly-created bone.Cijeljenje loma kosti složeni je fiziološki proces. Više faktora regulira ovu kaskadu molekularnih reakcija utječući na osteoblaste kroz razne procese kao što su migracija, proliferacija, kemotaksija, diferencijacija, inhibicija i ekstracelularna sinteza proteina. Omentum je serozna membrana koju čini mreža krvnih žila i masnog tkiva. To je izrazito vaskulariziran organ koji je ujedno bogat izvor angiogenih faktora koji potiču rast krvnih žila u bilo kojem tkivu na koje ga se položi. Nedavna istraživanja su otkrila, da omentum osim što je obilan izvor različitih faktora rasta, također sadrži omnipotentne matične stanice koje se mogu diferencirati u razne tipove stanica. Istraživanje je obavljeno na 16 odraslih mužjaka novozelandskog kunića istog statusa. Na radijusu svake životinje, podijeljene u skupine A i B, učinjen je veliki segmentalni defekt. U skupini B defekt je bio ispunjen komadićem (isječkom) masnog tkiva omentuma. Životinje su bile eutanazirane 56. dana nakon operativnog zahvata, a kosti su zatim izuzete za potrebe histomorfometrijske analize. Učinjena je histomorfometrijska analiza. Sloj osteoblasta (Ob.S/BS) pokazao se kao statistički značajan pokazatelj (P = 0,005). Sloj osteoblasta ustanovljen je u pokusnoj skupini u usporedbi s kontrolnom skupinom. Površina trabekula pokrivena osteoidima i slojem osteoblasta pokazala je visok stupanj pozitivne linearne korelacije i u kontrolnoj i pokusnoj skupini. Naše istraživanje pokazuje da sloj osteoblasta statistički značajno povećan, te se može zaključiti da masno tkivo omentuma ima stanoviti utjecaj na obnavljanje kostiju, naročito na formiranje novostvorene kosti

Temperature fluctuation and acute myocardial infarction in Beijing: an extended analysis of temperature ranges and differences

PurposeFew studies examined the relationship between temperature fluctuation metrics and acute myocardial infarction (AMI) hospitalizations within a single cohort. We aimed to expand knowledge on two basic measures: temperature range and difference.MethodsWe conducted a time-series analysis on the correlations between temperature range (TR), daily mean temperature differences (DTDmean), and daily mean-maximum/minimum temperature differences (TDmax/min) and AMI hospitalizations, using data between 2013 and 2016 in Beijing, China. The effects of TRn and DTDmeann over n-day intervals were compared, respectively. Subgroup analysis by age and sex was performed.ResultsA total of 81,029 AMI hospitalizations were included. TR1, TDmax, and TDmin were associated with AMI in J-shaped patterns. DTDmean1 was related to AMI in a U-shaped pattern. These correlations weakened for TR and DTDmean with longer exposure intervals. Extremely low (1st percentile) and high (5°C) DTDmean1 generated cumulative relative risk (CRR) of 2.73 (95% CI: 1.56–4.79) and 2.15 (95% CI: 1.54–3.01). Extremely high TR1, TDmax, and TDmin (99th percentile) correlated with CRR of 2.00 (95% CI: 1.73–2.85), 1.71 (95% CI: 1.40–2.09), and 2.73 (95% CI: 2.04–3.66), respectively. Those aged 20–64 had higher risks with large TR1, TDmax, and TDmin, while older individuals were more affected by negative DTDmean1. DTDmean1 was associated with a higher AMI risk in females.ConclusionTemperature fluctuations were linked to increased AMI hospitalizations, with low-temperature extremes having a more pronounced effect. Females and the older adult were more susceptible to daily mean temperature variations, while younger individuals were more affected by larger temperature ranges

The complete reference genome for grapevine (Vitis vinifera L.) genetics and breeding

Grapevine is one of the most economically important crops worldwide. However, the previous versions of the grapevine reference genome consisted of thousands of fragments with missing centromeres and telomeres, which limited the accessibility of the repetitive sequences, the centromeric and telomeric regions, and the inheritance of important agronomic traits in these regions. Here, we assembled a telomere-to-telomere (T2T) gap-free reference genome for the pinot noir cultivar (PN40024) using the PacBio HiFi long reads. The T2T reference genome (PN_T2T) was 69 Mb longer with 9026 more genes identified than the 12X.v2 version (Canaguier et al., 2017). We annotated 67% repetitive sequences, 19 centromeres and 36 telomeres, and incorporated gene annotations of previous versions into the PN_T2T. We detected a total of 377 gene clusters, which showed associations with complex traits, such as aroma and disease resistance. Even though the PN40024 sample had been selfed for nine generations, we still found nine genomic hotspots of heterozygous sites associated with biological processes, such as the oxidation-reduction process and protein phosphorylation. The fully annotated complete reference genome, therefore, provides important resources for grapevine genetics and breeding.This work was supported by the National Natural Science Fund for Excellent Young Scientists Fund Program (Overseas) to Yongfeng Zhou, the National Key Research and Development Program of China(grant2019YFA0906200), the Agricultural Science and Technology Innovation Program (CAAS-ZDRW202101), the Shenzhen Science and Technology Program (grant KQTD2016113010482651), the BMBF funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI). We thank Bianca Frommer, Marie Lahaye, David Navarro-Payá, Marcela K. Tello-Ruiz and Kapeel Chougule for their help in analyzing the RNA-Seq data and in running the gene annotation pipeline. This study is also based upon work from COST Action CA17111 INTEGRAPE and form COST Innovators Grant IG17111 GRAPEDIA, supported by COST (European Cooperation in Science and Technology).ViticultureT2Tgap-fregene clustercentromeretelomerePublishe

Graph Neural Network for Senior High Student’s Grade Prediction

Senior high school education (SHSE) forms a connecting link between the preceding junior high school education and the following college education. Through SHSE, a student not only completes k-12 education, but also lays a foundation for subsequent higher education. The grade of the student in SHSE plays a critical role in college application and admission. Therefore, utilizing the grade of the student as an indicator is a reasonable method to instruct and ensure the effect of SHSE. However, due to the complexity and nonlinearity of the grade prediction problem, it is hard to predict the grade accurately. In this paper, a novel grade prediction model aiming to handle the complexity and nonlinearity is proposed to accurately predict the grade of the senior high student. To deal with the complexity, a graph structure is employed to represent the students’ grades in all subjects. To handle the nonlinearity, the multi-layer perceptron (MLP) is used to learn (or fit) the inner relation of the subject grades. The proposed grade prediction model based on graph neural network is tested on the dataset of Ningbo Xiaoshi High School. The results show that the proposed method performs well in the prediction of senior high school student grades