Time-Sensitive Collaborative Filtering Algorithm with Feature Stability

In the recommendation system, the collaborative filtering algorithm is widely used. However, there are lots of problems which need to be solved in recommendation field, such as low precision, the long tail of items. In this paper, we design an algorithm called FSTS for solving the low precision and the long tail. We adopt stability variables and time-sensitive factors to solve the problem of user's interest drift, and improve the accuracy of prediction. Experiments show that, compared with Item-CF, the precision, the recall, the coverage and the popularity have been significantly improved by FSTS algorithm. At the same time, it can mine long tail items and alleviate the phenomenon of the long tail

Does Full Waveform Inversion Benefit from Big Data?

This paper investigates the impact of big data on deep learning models for full waveform inversion (FWI). While it is well known that big data can boost the performance of deep learning models in many tasks, its effectiveness has not been validated for FWI. To address this gap, we present an empirical study that investigates how deep learning models in FWI behave when trained on OpenFWI, a collection of large-scale, multi-structural datasets published recently. Particularly, we train and evaluate the FWI models on a combination of 10 2D subsets in OpenFWI that contain 470K data pairs in total. Our experiments demonstrate that larger datasets lead to better performance and generalization of deep learning models for FWI. We further demonstrate that model capacity needs to scale in accordance with data size for optimal improvement

Differential Expression of MicroRNA-19b Promotes Proliferation of Cancer Stem Cells by Regulating the TSC1/mTOR Signaling Pathway in Multiple Myeloma

Background/Aims: MiR-19b has been reported to be involved in several malignancies, but its role in multiple myeloma (MM) is still unknown. The objective of this study was to explore the biological mechanism of miR-19b in the progression of MM. Methods: First, we performed real-time polymerase chain reaction (PCR) and Western blot to study the expression of miR-19b, tuberous sclerosis 1 (TSC1), and caspase-3 in different groups. MTT assay was performed to explore the effect of miR-19b on survival and apoptosis of cancer stem cells (CSCs). Computation analysis and luciferase assay were utilized to confirm the interaction between miR-19b and TSC1. Results: A total of 38 participants comprising 20 subjects with MM and 18 healthy subjects as normal controls were enrolled in our study. Real-time PCR showed dramatic upregulation of miR-19b, but TSC1 was evidently suppressed in the MM group. MiR-19b overexpression substantially promoted clonogenicity and cell viability, and further inhibited apoptosis of CSCs in vitro. Furthermore, miR-19b overexpression downregulated the expression of caspase-3, which induced apoptosis. Using in silico analysis, we identified that TSC1 might be a direct downstream target of miR-19b, and this was further confirmed by luciferase assay showing that miR-19b apparently reduced the luciferase activity of wild-type TSC1 3´-UTR, but not that of mutant TSC1 3´-UTR. There was also evident decrease in TSC1 mRNA and protein in CSCs following introduction of miR-19b. Interestingly, reintroduction of TSC1 abolished the miR-19b-induced proliferation promotion and apoptosis inhibition in CSCs. Conclusion: These findings collectively suggest that miR-19b promotes cell survival and suppresses apoptosis of MM CSCs via targeting TSC1 directly, indicating that miR-19b may serve as a potential and novel therapeutic target of MM based on miRNA expression

EFWI\mathbf{\mathbb{E}^{FWI}}: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties

Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO$_2$ sequestration and energy exploration (e.g., hydrogen and geothermal). Elastic full waveform inversion (FWI) is widely applied for characterizing reservoir properties. In this paper, we introduce $\mathbf{\mathbb{E}^{FWI}}$, a comprehensive benchmark dataset that is specifically designed for elastic FWI. $\mathbf{\mathbb{E}^{FWI}}$ encompasses 8 distinct datasets that cover diverse subsurface geologic structures (flat, curve, faults, etc). The benchmark results produced by three different deep learning methods are provided. In contrast to our previously presented dataset (pressure recordings) for acoustic FWI (referred to as OpenFWI), the seismic dataset in $\mathbf{\mathbb{E}^{FWI}}$ has both vertical and horizontal components. Moreover, the velocity maps in $\mathbf{\mathbb{E}^{FWI}}$ incorporate both P- and S-wave velocities. While the multicomponent data and the added S-wave velocity make the data more realistic, more challenges are introduced regarding the convergence and computational cost of the inversion. We conduct comprehensive numerical experiments to explore the relationship between P-wave and S-wave velocities in seismic data. The relation between P- and S-wave velocities provides crucial insights into the subsurface properties such as lithology, porosity, fluid content, etc. We anticipate that $\mathbf{\mathbb{E}^{FWI}}$ will facilitate future research on multiparameter inversions and stimulate endeavors in several critical research topics of carbon-zero and new energy exploration. All datasets, codes and relevant information can be accessed through our website at https://efwi-lanl.github.io/Comment: 20 pages, 11 figure

Rational design of interlaced Co 9 S 8 /carbon composites from ZIF-67/cellulose nanofibers for enhanced lithium storage

Abstract(#br)Cellulose nanofibers (CNFs) are used to string ZIF-67 particles and interlaced Co 9 S 8 /porous carbon composite (Co 9 S 8 /C-CNFs) is obtained via carbonization and sulphidation of ZIF-67/CNFs composites. The CNFs can effectively limit the growth of ZIF-67 particles and avoid the agglomeration and most importantly, serve as the conductive skeleton to “bridge” carbonized ZIF-67 particles after carbonization. Due to the unique structure and the improved conductivity, Co 9 S 8 /C-CNFs as anode of lithium-ion batteries exhibits enhanced electrochemical properties and the specific capacity is 700 mAh g −1 at current density of 500 mA g −1 after 150 cycles compared to that of 342 mAh g −1 for samples without CNFs incorporation. Such nanoscale design may boost to explore other nanocomposites for energy storage

Automatic 2D-to-3D video conversion technique based on depth-from-motion and color segmentation

Most of the TV manufacturers have released 3DTVs in the summer of 2010 using shutter-glasses technology. 3D video applications are becoming popular in our daily life, especially at home entertainment. Although more and more 3D movies are being made, 3D video contents are still not rich enough to satisfy the future 3D video market. There is a rising demand on new techniques for automatically converting 2D video content to stereoscopic 3D video displays. In this paper, an automatic monoscopic video to stereoscopic 3D video conversion scheme is presented using block-based depth from motion estimation and color segmentation for depth map enhancement. The color based region segmentation provides good region boundary information, which is used to fuse with block-based depth map for eliminating the staircase effect and assigning good depth value in each segmented region. The experimental results show that this scheme can achieve relatively high quality 3D stereoscopic video output. ? 2010 IEEE.EI

‘ZhongPan 101’ and ‘ZhongPan 102’: Two Flat Peach Cultivars From China

Flat peach [Prunus persica (L.) Batsch var. platycarpa] is a variant of ordinary peach with a unique flat shape. It is well known for its shape and delicious fruits (Miao et al. 2022). Although flat peach has a long history of cultivation in China, until the beginning of the 20th century, flat peach was only distributed as a minor variety in the main peach-producing areas of China. In terms of flat peach cultivars, only 46 of the 709 peach cultivars listed in Peach Genetic Resource in China (Wang et al. 2012) are flat peach cultivars, and most of them are flat landraces. Several problems have been noted previously in flat peach cultivars, including poor closure of the blossom end (blossom-end scarring in mild cases and cracking in severe cases), cracked stone in some cultivars (loss of commercial value in severe cases), nonsymmetrical fruit shape, small flesh, and low yield (Wang 2021). Many of the shortcomings of flat peach cultivars are intrinsic problems of the cultivars, which are difficult to improve through cultivation measures. This is the key factor limiting the large-scale promotion of flat peach cultivation in China. For many years, peach breeders in China have been devoted to the genetic improvement of flat peach, and some improved flat peach cultivars have been released, for instance, ‘Pocket Zaoban’ (Jiang et al. 2007) and ‘124 Pantao’ (Ma et al. 2003). However, problems persist in these cultivars, including small fruits, soft flesh, and blossom-end cracks. Only a few flat peach cultivars have good overall performance. In recent years, the Zhengzhou Fruit Research Institute (ZFRI), Chinese Academy of Agricultural Sciences (CAAS), identified genetic sources of flat peach with slow or nonmelting flesh, a well-closed blossom end, and little or no cracking. They were hybridized with high-quality peach and nectarine cultivars or selections. After multiple generations of improvement, breakthroughs were made in early flat peach breeding, and a series of flat peach cultivars with excellent comprehensive traits have been produced. These cultivars are favored by fruit farmers in the main peach-producing areas in China. Hence, the main problems in flat peach cultivation are expected to be solved, which will help expand the cultivation area of flat peach. ‘ZhongPan 101’ and ‘ZhongPan 102’ are two yellow-flesh flat peach cultivars 45 released from the ZFRI, CAAS. These two cultivars produce large, well-shaped, high-quality fruits with a completely closed stylar end and high yield. Three years of evaluation has confirmed that the peach trees of the two cultivars are stable. ‘ZhongPan 101’ and ‘ZhongPan 102’ were well adapted to climate of the middle and lower reaches of the Yellow River; have performed well in Henan, Jiangsu, and Anhui Provinces; and are suggested for trial wherever ‘ZhongYouPan 9’ is grown

Analysis of preoperative and postoperative depression and anxiety in patients with osteochondral lesions of the talus

PurposeThis study aims to investigate the psychological status of patients with Hepple V osteochondral lesions of the talus (OLT) and evaluate the effect of autologous osteoperiosteal transplantation (AOPT) on their psychological well-being.MethodsFifty patients with Hepple V OLT who underwent AOPT at the Comprehensive Foot and Ankle Surgery Ward of Xi’an Honghui Hospital from November 2021 to May 2023 were included in this study. The patients were divided into two groups based on the presence or absence of preoperative symptoms of anxiety/depression. Group A comprised patients with preoperative symptoms, while Group B included patients without such symptoms. Preoperative and final follow-up assessments included the Hospital Anxiety and Depression Scale for evaluating anxiety and depression, the visual analogue scale for pain assessment, and the American Orthopaedic Foot and Ankle Society scores for assessing ankle and hindfoot function.ResultsAmong the 50 Hepple V OLT patients who obtained complete follow-up, twenty-four had preoperative symptoms of anxiety/depression, with an incidence rate of up to 48%. Patients in Groups A and B showed significant improvement in all evaluation indexes after AOPT compared to the preoperative period, but the overall prognosis of Group A was poorer than that of Group B.ConclusionAOPT can effectively improve patients’ pain, functional activities, and psychological status, and there is a significant correlation between patients’ preoperative psychological status and prognosis

Improved Biocompatibility of Novel Biodegradable Scaffold Composed of Poly-L-lactic Acid and Amorphous Calcium Phosphate Nanoparticles in Porcine Coronary Artery

Using poly-L-lactic acid for implantable biodegradable scaffold has potential biocompatibility issue due to its acidic degradation byproducts. We have previously reported that the addition of amorphous calcium phosphate improved poly-L-lactic acid coating biocompatibility. In the present study, poly-L-lactic acid and poly-L-lactic acid/amorphous calcium phosphate scaffolds were implanted in pig coronary arteries for 28 days. At the follow-up angiographic evaluation, no case of stent thrombosis was observed, and the arteries that were stented with the copolymer scaffold had significantly less inflammation and nuclear factor-κB expression and a greater degree of reendothelialization. The serum levels of vascular endothelial growth factor and nitric oxide, as well the expression of endothelial nitric oxide synthase and platelet-endothelial cell adhesion molecule-1, were also significantly higher. In conclusion, the addition of amorphous calcium phosphate to biodegradable poly-L-lactic acid scaffold minimizes the inflammatory response, promotes the growth of endothelial cells, and accelerates the reendothelialization of the stented coronary arteries

Dynamic residual deep learning with photoelectrically regulated neurons for immunological classification

Dynamic deep learning is considered to simulate the nonlinear memory process of the human brain during long-term potentiation and long-term depression. Here, we propose a photoelectrically modulated synaptic transistor based on MXenes that adjusts the nonlinearity and asymmetry by mixing controllable pulses. According to the advantage of residual deep learning, the rule of dynamic learning is thus elaborately developed to improve the accuracy of a highly homologous database (colorimetric enzyme-linked immunosorbent assay [c-ELISA]) from 80.9% to 87.2% and realize the fast convergence. Besides, mixed stimulation also remarkably shortens the iterative update time to 11.6 s as a result of the photoelectric effect accelerating the relaxation of ion migration. Finally, we extend the dynamic learning strategy to long short-term memory (LSTM) and standard datasets (Cifar10 and Cifar100), which well proves the strong robustness of dynamic learning. This work paves the way toward potential synaptic bionic retina for computer-aided detection in immunology