SCOPE: Scalable Composite Optimization for Learning on Spark

Many machine learning models, such as logistic regression~(LR) and support vector machine~(SVM), can be formulated as composite optimization problems. Recently, many distributed stochastic optimization~(DSO) methods have been proposed to solve the large-scale composite optimization problems, which have shown better performance than traditional batch methods. However, most of these DSO methods are not scalable enough. In this paper, we propose a novel DSO method, called \underline{s}calable \underline{c}omposite \underline{op}timization for l\underline{e}arning~({SCOPE}), and implement it on the fault-tolerant distributed platform \mbox{Spark}. SCOPE is both computation-efficient and communication-efficient. Theoretical analysis shows that SCOPE is convergent with linear convergence rate when the objective function is convex. Furthermore, empirical results on real datasets show that SCOPE can outperform other state-of-the-art distributed learning methods on Spark, including both batch learning methods and DSO methods

An investigation of the mathematical elements of the Dai culture south-west Yunnan province, China

Dai ethnic mathematical culture is an important part of Dai ethnic culture. Mathematical elements show in their daily life. Through a research project of the Yunnan Dehong Dai people in southwest China, We collected the first-hand information, tried to do a small investigative study, and collected mathematics teaching resources that is useful to primary and secondary schools students on mathematics learning  in this minority areas. Keyword: Dai ethnic; Mathematical culture; Primary and secondary schools; Teaching resources

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

The recent GPT-4 has demonstrated extraordinary multi-modal abilities, such as directly generating websites from handwritten text and identifying humorous elements within images. These features are rarely observed in previous vision-language models. We believe the primary reason for GPT-4's advanced multi-modal generation capabilities lies in the utilization of a more advanced large language model (LLM). To examine this phenomenon, we present MiniGPT-4, which aligns a frozen visual encoder with a frozen LLM, Vicuna, using just one projection layer. Our findings reveal that MiniGPT-4 possesses many capabilities similar to those exhibited by GPT-4 like detailed image description generation and website creation from hand-written drafts. Furthermore, we also observe other emerging capabilities in MiniGPT-4, including writing stories and poems inspired by given images, providing solutions to problems shown in images, teaching users how to cook based on food photos, etc. In our experiment, we found that only performing the pretraining on raw image-text pairs could produce unnatural language outputs that lack coherency including repetition and fragmented sentences. To address this problem, we curate a high-quality, well-aligned dataset in the second stage to finetune our model using a conversational template. This step proved crucial for augmenting the model's generation reliability and overall usability. Notably, our model is highly computationally efficient, as we only train a projection layer utilizing approximately 5 million aligned image-text pairs. Our code, pre-trained model, and collected dataset are available at https://minigpt-4.github.io/.Comment: Project Website: https://minigpt-4.github.io/; Code, Pretrained Model, and Dataset: https://github.com/Vision-CAIR/MiniGPT-4; Deyao Zhu and Jun Chen contributed equally to this wor

Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is the main clinical cause of death and cardiovascular disease and thus has high rates of morbidity and mortality. The increase in cardiovascular disease with aging is partly the result of vascular endothelial cell senescence and associated vascular dysfunction. This study was performed to identify potential key cellular senescence-related genes (SRGs) as biomarkers for the diagnosis of AMI using bioinformatics.MethodsUsing the CellAge database, we identified cellular SRGs. GSE66360 and GSE48060 for AMI patients and healthy controls and GSE19322 for mice were downloaded from the Gene Expression Omnibus (GEO) database. The GSE66360 dataset was divided into a training set and a validation set. The GSE48060 dataset was used as another validation set. The GSE19322 dataset was used to explore the evolution of the screened diagnostic markers in the dynamic process of AMI. Differentially expressed genes (DEGs) of AMI were identified from the GSE66360 training set. Differentially expressed senescence-related genes (DESRGs) selected from SRGs and DEGs were analyzed using Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed.ResultsA total of 520 DEGs were screened from the GSE66360 training set, and 279 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 14 DESRGs, including 4 senescence suppressor genes and 10 senescence inducible genes. The top 10 hub genes, including FOS, MMP9, CEBPB, CDKN1A, CXCL1, ETS2, BCL6, SGK1, ZFP36, and IGFBP3, were screened. Furthermore, three diagnostic genes were identified: MMP9, ETS2, and BCL6. The ROC analysis showed that the respective area under the curves (AUCs) of MMP9, ETS2, and BCL6 were 0.786, 0.848, and 0.852 in the GSE66360 validation set and 0.708, 0.791, and 0.727 in the GSE48060 dataset. In the GSE19322 dataset, MMP9 (AUC, 0.888) and ETS2 (AUC, 0.929) had very high diagnostic values in the early stage of AMI. Finally, based on these three diagnostic genes, we found that drugs such as acetylcysteine and genistein may be targeted for the treatment of age-related AMI.ConclusionThe results of this study suggest that cellular SRGs might play an important role in AMI. MMP9, ETS2, and BCL6 have potential as specific biomarkers for the early diagnosis of AMI

PICK1 regulates the trafficking of ASIC1a and acidotoxicity in a BAR domain lipid binding-dependent manner

<p>Abstract</p> <p>Background</p> <p>Acid-sensing ion channel 1a (ASIC1a) is the major ASIC subunit determining acid-activated currents in brain neurons. Recent studies show that ASIC1a play critical roles in acid-induced cell toxicity. While these studies raise the importance of ASIC1a in diseases, mechanisms for ASIC1a trafficking are not well understood. Interestingly, ASIC1a interacts with PICK1 (protein interacting with C-kinase 1), an intracellular protein that regulates trafficking of several membrane proteins. However, whether PICK1 regulates ASIC1a surface expression remains unknown.</p> <p>Results</p> <p>Here, we show that PICK1 overexpression increases ASIC1a surface level. A BAR domain mutant of PICK1, which impairs its lipid binding capability, blocks this increase. Lipid binding of PICK1 is also required for PICK1-induced clustering of ASIC1a. Consistent with the effect on ASIC1a surface levels, PICK1 increases ASIC1a-mediated acidotoxicity and this effect requires both the PDZ and BAR domains of PICK1.</p> <p>Conclusions</p> <p>Taken together, our results indicate that PICK1 regulates trafficking and function of ASIC1a in a lipid binding-dependent manner.</p

Proximity effect at superconducting Sn-Bi2Se3 interface

We have investigated the conductance spectra of Sn-Bi2Se3 interface junctions down to 250 mK and in different magnetic fields. A number of conductance anomalies were observed below the superconducting transition temperature of Sn, including a small gap different from that of Sn, and a zero-bias conductance peak growing up at lower temperatures. We discussed the possible origins of the smaller gap and the zero-bias conductance peak. These phenomena support that a proximity-effect-induced chiral superconducting phase is formed at the interface between the superconducting Sn and the strong spin-orbit coupling material Bi2Se3.Comment: 7 pages, 8 figure

Isopropyl 3,4-dihy­droxy­benzoate

In the crystal structure of the title compound, C10H12O4, O—H⋯O hydrogen bonds incorporating R 2 2(10) and R 2 2(14) motifs link mol­ecules into chains along [10]. An intra­molecular O—H⋯O hydrogen bond is also observed

Neutron Scattering Measurements of Spatially Anisotropic Magnetic Exchange Interactions in Semiconducting K0.85Fe1.54Se2 (TN=280 K)

We use neutron scattering to study the spin excitations associated with the stripe antiferromagnetic (AFM) order in semiconducting K$_{0.85}$Fe$_{1.54}$Se$_2$ ($T_N$=$280$ K). We show that the spin wave spectra can be accurately described by an effective Heisenberg Hamiltonian with highly anisotropic in-plane couplings at $T$= $5$ K. At high temperature ($T$= $300$ K) above $T_N$, short range magnetic correlation with anisotropic correlation lengths are observed. Our results suggest that, despite the dramatic difference in the Fermi surface topology, the in-plane anisotropic magnetic couplings are a fundamental property of the iron based compounds; this implies that their antiferromagnetism may originate from local strong correlation effects rather than weak coupling Fermi surface nesting.Comment: 5 pages, 4 figure