Statistical Inference with Stochastic Gradient Methods under ϕ\phi-mixing Data

Stochastic gradient descent (SGD) is a scalable and memory-efficient optimization algorithm for large datasets and stream data, which has drawn a great deal of attention and popularity. The applications of SGD-based estimators to statistical inference such as interval estimation have also achieved great success. However, most of the related works are based on i.i.d. observations or Markov chains. When the observations come from a mixing time series, how to conduct valid statistical inference remains unexplored. As a matter of fact, the general correlation among observations imposes a challenge on interval estimation. Most existing methods may ignore this correlation and lead to invalid confidence intervals. In this paper, we propose a mini-batch SGD estimator for statistical inference when the data is $\phi$-mixing. The confidence intervals are constructed using an associated mini-batch bootstrap SGD procedure. Using ``independent block'' trick from \cite{yu1994rates}, we show that the proposed estimator is asymptotically normal, and its limiting distribution can be effectively approximated by the bootstrap procedure. The proposed method is memory-efficient and easy to implement in practice. Simulation studies on synthetic data and an application to a real-world dataset confirm our theory

Maize straw application as an interlayer improves organic carbon and total nitrogen concentrations in the soil profile: A four-year experiment in a saline soil

Soil salinization is a critical environmental issue restricting agricultural production. Deep return of straw to the soil as an interlayer (at 40 cm depth) has been a popular practice to alleviate salt stress. However, the legacy effects of straw added as an interlayer at different rates on soil organic carbon (SOC) and total nitrogen (TN) in saline soils still remain inconclusive. Therefore, a four-year (2015–2018) field experiment was conducted with four levels (i.e., 0, 6, 12 and 18 Mg ha–1) of straw returned as an interlayer. Compared with no straw interlayer (CK), straw addition increased SOC concentration by 14–32 and 11–57% in the 20–40 and 40–60 cm soil layers, respectively. The increases in soil TN concentration (8–22 and 6–34% in the 20–40 and 40–60 cm soil layers, respectively) were lower than that for SOC concentration, which led to increased soil C:N ratio in the 20–60 cm soil depth. Increases in SOC and TN concentrations in the 20–60 cm soil layer with straw addition led to a decrease in stratification ratios (0–20 cm:20–60 cm), which promoted uniform distributions of SOC and TN in the soil profile. Increases in SOC and TN concentrations were associated with soil salinity and moisture regulation and improved sunflower yield. Generally, compared with other treatments, the application of 12 Mg ha–1 straw had higher SOC, TN and C:N ratio, and lower soil stratification ratio in the 2015–2017 period. The results highlighted that legacy effects of straw application as an interlayer were maintained for at least four years, and demonstrated that deep soil straw application had a great potential for improving subsoil fertility in salt-affected soils.publishedVersio

Association of methylenetetrahydrofolate reductase C677T polymorphism and serum lipid levels in the Guangxi Bai Ku Yao and Han populations

<p>Abstract</p> <p>Background</p> <p>The association of methylenetetrahydrofolate reductase (MTHFR) gene polymorphism and serum lipid profiles is still controversial in diverse ethnics. Bai Ku Yao is an isolated subgroup of the Yao minority in China. The aim of the present study was to eveluate the association of MTHFR C677T polymorphism and several environmental factors with serum lipid levels in the Guangxi Bai Ku Yao and Han populations.</p> <p>Methods</p> <p>A total of 780 subjects of Bai Ku Yao and 686 participants of Han Chinese were randomly selected from our previous stratified randomized cluster samples. Genotyping of the MTHFR C677T was performed by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and then confirmed by direct sequencing.</p> <p>Results</p> <p>The levels of serum total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein (Apo) AI and ApoB were lower in Bai Ku Yao than in Han (<it>P </it>< 0.05-0.001). The frequency of C and T alleles was 77.4% and 22.6% in Bai Ku Yao, and 60.9% and 39.1% in Han (<it>P </it>< 0.001); respectively. The frequency of CC, CT and TT genotypes was 58.7%, 37.3% and 4.0% in Bai Ku Yao, and 32.6%, 56.4% and 11.0% in Han (<it>P </it>< 0.001); respectively. The levels of TC and LDL-C in both ethnic groups were significant differences among the three genotypes (<it>P </it>< 0.05-0.01). The T allele carriers had higher serum TC and LDL-C levels than the T allele noncarriers. The levels of ApoB in Han were significant differences among the three genotypes (<it>P </it>< 0.05). The T allele carriers had higher serum ApoB levels as compared with the T allele noncarriers. The levels of TC, TG and LDL-C in Bai Ku Yao were correlated with genotypes (<it>P </it>< 0.05-0.001), whereas the levels of LDL-C in Han were associated with genotypes (<it>P </it>< 0.001). Serum lipid parameters were also correlated with sex, age, body mass index, alcohol consumption, cigarette smoking, and blood pressure in the both ethnic groups.</p> <p>Conclusions</p> <p>The differences in serum TC, TG, LDL-C and ApoB levels between the two ethnic groups might partly result from different genotypic and allelic frequencies of the MTHFR C677T or different MTHFR gene-enviromental interactions.</p

Pruning random resistive memory for optimizing analogue AI

The rapid advancement of artificial intelligence (AI) has been marked by the large language models exhibiting human-like intelligence. However, these models also present unprecedented challenges to energy consumption and environmental sustainability. One promising solution is to revisit analogue computing, a technique that predates digital computing and exploits emerging analogue electronic devices, such as resistive memory, which features in-memory computing, high scalability, and nonvolatility. However, analogue computing still faces the same challenges as before: programming nonidealities and expensive programming due to the underlying devices physics. Here, we report a universal solution, software-hardware co-design using structural plasticity-inspired edge pruning to optimize the topology of a randomly weighted analogue resistive memory neural network. Software-wise, the topology of a randomly weighted neural network is optimized by pruning connections rather than precisely tuning resistive memory weights. Hardware-wise, we reveal the physical origin of the programming stochasticity using transmission electron microscopy, which is leveraged for large-scale and low-cost implementation of an overparameterized random neural network containing high-performance sub-networks. We implemented the co-design on a 40nm 256K resistive memory macro, observing 17.3% and 19.9% accuracy improvements in image and audio classification on FashionMNIST and Spoken digits datasets, as well as 9.8% (2%) improvement in PR (ROC) in image segmentation on DRIVE datasets, respectively. This is accompanied by 82.1%, 51.2%, and 99.8% improvement in energy efficiency thanks to analogue in-memory computing. By embracing the intrinsic stochasticity and in-memory computing, this work may solve the biggest obstacle of analogue computing systems and thus unleash their immense potential for next-generation AI hardware

Antibody Responses and the Effects of Clinical Drugs in COVID-19 Patients

The coronavirus disease 2019 (COVID-19) emerged around December 2019 and have become a global epidemic disease currently. Specific antibodies against SAS-COV-2 could be detected in COVID-19 patients’ serum or plasma, but the clinical values of these antibodies as well as the effects of clinical drugs on humoral responses have not been fully demonstrated. In this study, 112 plasma samples were collected from 36 patients diagnosed with laboratory-confirmed COVID-19 in the Fifth Affiliated Hospital of Sun Yat-sen University. The IgG and IgM antibodies against receptor binding domain (RBD) and spike protein subunit 1 (S1) of SAS-COV-2 were detected by ELISA. We found that COVID-19 patients generated specific antibodies against SARS-CoV-2 after infection, and the levels of anti-RBD IgG within 2 to 3 weeks from onset were negatively associated with the time of positive-to-negative conversion of SARS-CoV-2 nucleic acid. Patients with severe symptoms had higher levels of anti-RBD IgG in 2 to 3 weeks from onset. The use of chloroquine did not significantly influence the patients’ antibody titer but reduced C-reaction protein (CRP) level. Using anti-viral drugs (lopinavir/ritonavir or arbidol) reduced antibody titer and peripheral lymphocyte count. While glucocorticoid therapy developed lower levels of peripheral lymphocyte count and higher levels of CRP, lactate dehydrogenase (LDH), α-Hydroxybutyrate dehydrogenase(α-HBDH), total bilirubin (TBIL), direct bilirubin (DBIL). From these results, we suggested that the anti-RBD IgG may provide an early protection of host humoral responses against SAS-COV-2 infection within 2 to 3 weeks from onset, and clinical treatment with different drugs displayed distinct roles in humoral and inflammatory responses

Stable Ta2O5 Overlayers on Hematite for Enhanced Photoelectrochemical Water Splitting Efficiencies

Hematite (α‐Fe2O3) is one of the most promising photoanodes for water oxidation, however the efficiencies of current hematite materials remain low. Surface trap states are often reported as one of the factors which limit the activity of hematite photoelectrodes, often leading to undesirable surface pinning and trap‐mediated recombination. The deposition of ultra‐thin Al2O3 overlayers is known to enhance hematite activity through passivation of surface states, however Al2O3 is rapidly degraded at normal hematite operating pH values (pH≈13). This study reports atomic layer deposition (ALD) of Ta2O5 thin films as stable, passivating overlayers on a range of hematite photoelectrodes and demonstrates that enhanced activity correlates with observed changes in trap‐state dynamics