On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms

Stochastic gradient descent (SGD) algorithm is the method of choice in many machine learning tasks thanks to its scalability and efficiency in dealing with large-scale problems. In this paper, we focus on the shuffling version of SGD which matches the mainstream practical heuristics. We show the convergence to a global solution of shuffling SGD for a class of non-convex functions under over-parameterized settings. Our analysis employs more relaxed non-convex assumptions than previous literature. Nevertheless, we maintain the desired computational complexity as shuffling SGD has achieved in the general convex setting.Comment: The 37th Conference on Neural Information Processing Systems (NeurIPS 2023

How swelling debts give rise to a new type of politics in Vietnam

Vietnam has seen fast-rising debts, both domestic and external, in recent years. This paperreviews the literature on credit market in Vietnam, providing an up-to-date take on the domesticlending and borrowing landscape. The study highlights the strong demand for credit in both therural and urban areas, the ubiquity of informal lenders, the recent popularity of consumer financecompanies, as well as the government’s attempts to rein in its swelling public debt. Given thehigh level of borrowing, which is fueled by consumerism and geopolitics, it is inevitable that theamount of debt will soon be higher than the saving of the borrowers. Unlike the conventional wisdom that creditors have more bargaining power over the borrowers, we suggest that—albeitlacking a quantitative estimation—when the debts pile up so high that the borrowers could not repay, the power dynamics may reverse. In this new politics of debt, the lenders fear to lose the money's worth and continue to lend and feed the insolvent debtors. The result is a toxic lending/borrowing market and profound lessons, from which the developing world could learn

Synthesis and NMR-Characterization of Three Quinamide-Based Disaccharide Mimetics with Unusual Cyclohexane twist-Conformation

The synthesis of amide-linked disaccharide mimetics has been explored starting with carbohydrate-based amines and a protected quinic acid lactone. Benzyl-2-amino-4,6-Obenzylidene-2-deoxy-α/β-D-glucopyranose (12) and D-glucamine (14) were successfully coupled to give the corresponding quinamides (13 and 15), while the quinoylation of Oacetylated L-fucopyranosyl methylamine (7) failed. The latter was prepared from per-O-acetylL-fucopyranose via the improved multigram scale synthesis of the corresponding per-O-acetylL-fucopyranosyl cyanide (3). Compound 3 was subsequently hydrogenated to yield a mixture of compound 7 and the per-O-acetylated bis-(fucopyranosylmethyl) amine (5). The vicinal coupling constants in the NMR spectra of all quinamide products revealed considerable flexibility of the cyclohexane ring in solution and substantial contributions by twist-chair conformations

Co-doping red-emitting Sr2Si5N8:Eu2+ into yellow-emitting phosphor-packaging for enhancing the optical properties of the 8500 K remote-phosphor packaging wleds

In the last decades, WLEDs attract more and more consideration in both academic and industrial purposes because of its advantages such as fast response time, environment friendliness, small size, long lifetime, and high efficiency. In this research, by doping the red-emitting Sr2Si5N8:Eu2+ phosphor particles into yellow-emitting YAG:Ce phosphor-packaging, a new recommendation for enhancing the optical properties (color uniformity, color rendering index, and lumen output) of the 8500 K remote-phosphor packaging WLEDs is presented, investigated, and demonstrated. By using Mat Lab and Light Tools software based on Mie Theory, the obtained results show that the optical properties of the 8500 K remote-phosphor packaging WLEDs significantly depended on Sr2Si5N8:Eu2+ concentration. The results have provided a potential practical recommendation for manufacturing remote-phosphor W-LEDs.Web of Science1341034102

Diversity and Activity of Microbial Extracellular Peptidases in Soil

Soil nitrogen exists largely as organic matter, including plant liter, dead animal matter, and microbial necromass. About 90% of soil organic nitrogen is proteinaceous material that is too large for plants and microorganisms to assimilate directly. Protein depolymerization therefore plays a critical role in mobilizing this organic source of nitrogen, producing lower molecular weight molecules that are bioavailable for both microorganisms and plants. The decomposition of proteins in soils serves as the rate-limiting step of the nitrogen cycle. The ability of microorganisms to access and break down proteinaceous material depends largely on their production of extracellular peptidases, but it involves a trade-off with the energetic cost of producing and secreting these enzymes into the environment, including the risk that other microorganisms can compete with the peptidase-producing organisms for the products released through depolymerization. Consequently, in order to optimize this energy investment, there might be a tight connection between soil environmental conditions and microbial proteolytic activity. Despite its ecological importance, there is a lack of understanding about the diversity of these extracellular peptidases and their activity as an important factor influencing the protein degradability in soils. In this dissertation, I first assessed the genetic potential for microorganisms to produce extracellular enzymes, and second, I developed and applied a novel approach to measure the activities of different classes of peptidases in soil. In my first two chapters, I evaluated the abundance and diversity of microbial extracellular peptidases, their evolutionary conservation, and distribution as a function of environmental habitat and lifestyle. Chapter 2 focuses on the secreted peptidases of prokaryotes (Archaea, Bacteria); chapter 3 focuses on Fungi, the dominant soil eukaryote. In both chapters, I analyzed secreted peptidases across microbial lineages using their genomic information and corresponding annotated protein sequences assembled from several databases, including MEROPS, Silva, JGI Genome Portal, and MycoCosm. Peptidase gene sequences of 147 archaeal, 2,191 bacterial and 612 fungal genomes were screened for secretion signals, resulting in 55,072 prokaryotic and 31,668 eukaryotic genes coding for secreted peptidases. I found that Archaea, Bacteria, and Fungi possess unique complements of secreted peptidases and there are differences in the number of secreted peptidases per genome, indicating potential differential abilities for organic nitrogen acquisition. The majority of secreted peptidase families not only follow the phylogenetic evolutionary distribution, but also segregate based on the microbial lifestyles and microbial habitats. This suggests that microorganisms optimize their secreted peptidases to match their surrounding environments. In Chapter 4, I incorporated the use of selective inhibitors to block the activity of different classes of peptidases. I designed a protocol with these peptidase inhibitors to use directly in natural soils. I validated and optimized this protocol with pure enzymes and peptidase-supplemented soils. This research revealed that the profile of extracellular peptidase activities belonging to different catalytic types varies among soils and correlates with both soil chemical and microbial properties. This is in line with our assumption that soil microorganisms respond to their environmental conditions by investing in peptidases that can optimize their activity. Collectively, this work provides a comprehensive and foundational understanding about the contribution of different catalytic types of microbial extracellular peptidases to organic nitrogen turnover in soils

An End-to-End Time Series Model for Simultaneous Imputation and Forecast

Time series forecasting using historical data has been an interesting and challenging topic, especially when the data is corrupted by missing values. In many industrial problem, it is important to learn the inference function between the auxiliary observations and target variables as it provides additional knowledge when the data is not fully observed. We develop an end-to-end time series model that aims to learn the such inference relation and make a multiple-step ahead forecast. Our framework trains jointly two neural networks, one to learn the feature-wise correlations and the other for the modeling of temporal behaviors. Our model is capable of simultaneously imputing the missing entries and making a multiple-step ahead prediction. The experiments show good overall performance of our framework over existing methods in both imputation and forecasting tasks

A comprehensive evaluation of polygenic score and genotype imputation performances of human SNP arrays in diverse populations

publishedVersio

Application of DNA Barcoding to Authentic Panax Vietnamensis

Panax L. genus consists of 11 species and sub- species. It distribute in North America and in eastern Asia (mostly northeast China, Korea, Bhutan, eastern Siberia), typically in cooler climates. In Vietnam, up to now, currently five species of the genus Panax and one sub-species have been identified including Panax bipinnatifidus Seem., P. stipuleanatus Feng Tsai et, P. vietnamensis Ha et Grushv., P. pseudoginseng Wall., P. ginseng Meyer. and Panax vietnamensis var. fuscidiscus. Panax vietnamensis is endemic species in Vietnam that only distribute around Ngoc Linh mountain with the altitude from 1500m to 2400m, in limited geograpgical coordinates from 14055’ to 15007’ north latitude and from 107051’ to 108005’ east longitude. This species is unique Panax species that distributes to 150 north latitude and it is considered as the most valuable medicinal plants in Vietnam. But Panax vietnamensis and Panax vietnamensis var. fuscidiscus share many similar characteristics and make people often confused. In this research, we used of DNA barcoding to authentic Panax vietnamensis. We sequenced 4 chloroplast DNA regions includes MatK, rbcL, rpoB and 1 nuclear DNA regions ITS for comparison and choose the best one for identification of the Panax species. Our result showed that ITS-rDNA is the best marker for authentic Panax species. MatK is good for identify at species level but rpoB good for identify at subspecies level. The sequence of MatK, rbcL, rpoB, rpoC, ITS of Panax vietnamensis and Panax vietnamensis var. fuscidiscus were submitted to Genebank with accessory number as KJ 418201, KJ 418206, KT 154685, KT 194325, KT154583, KT 194326, KJ 418194, KJ 418193 respectively

Effect of Dzyaloshinskii–Moriya interaction on Heisenberg antiferromagnetic spin chain in a longitudinal magnetic field

Using functional integral method for the Heisenberg antiferromagnetic spin chain with the added Dzyaloshinskii-Moriya Interaction in the presence of the longitudinal magnetic field, we find out expression for free energy of the spin chain via spin fluctuations, from which quantities characterize the antiferromagnetic order and phase transition such as staggered and total magnetizations derived. From that, we deduce the significant effect of the Dzyaloshinskii-Moriya interaction on the reduction of the antiferromagnetic order and show that the total magnetization can be deviated from the initial one under the influence of canting of the spins due to a combination of the Dzyaloshinskii-Moriya interaction and the magnetic field. Besides, the remarkable role of the transverse spin fluctuations due to the above factors on the antiferromagnetic behaviours of the spin chain is also indicated. &nbsp