On Block Cholesky Decomposition for Sparse Inverse Covariance Estimation

The modified Cholesky decomposition is popular for inverse covariance estimation, but often needs pre-specification on the full information of variable ordering. In this work, we propose a block Cholesky decomposition (BCD) for estimating inverse covariance matrix under the partial information of variable ordering, in the sense that the variables can be divided into several groups with available ordering among groups, but variables within each group have no orderings. The proposed BCD model provides a unified framework for several existing methods including the modified Cholesky decomposition and the Graphical lasso. By utilizing the partial information on variable ordering, the proposed BCD model guarantees the positive definiteness of the estimated matrix with statistically meaningful interpretation. Theoretical results are established under regularity conditions. Simulation and case studies are conducted to evaluate the proposed BCD model

Faster Algorithms for Bounded Knapsack and Bounded Subset Sum Via Fine-Grained Proximity Results

We investigate pseudopolynomial-time algorithms for Bounded Knapsack and Bounded Subset Sum. Recent years have seen a growing interest in settling their fine-grained complexity with respect to various parameters. For Bounded Knapsack, the number of items $n$ and the maximum item weight $w_{\max}$ are two of the most natural parameters that have been studied extensively in the literature. The previous best running time in terms of $n$ and $w_{\max}$ is $O(n + w^3_{\max})$ [Polak, Rohwedder, Wegrzycki '21]. There is a conditional lower bound of $O((n + w_{\max})^{2-o(1)})$ based on $(\min,+)$-convolution hypothesis [Cygan, Mucha, Wegrzycki, Wlodarczyk '17]. We narrow the gap significantly by proposing a $\tilde{O}(n + w^{12/5}_{\max})$-time algorithm. Note that in the regime where $w_{\max} \approx n$, our algorithm runs in $\tilde{O}(n^{12/5})$ time, while all the previous algorithms require $\Omega(n^3)$ time in the worst case. For Bounded Subset Sum, we give two algorithms running in $\tilde{O}(nw_{\max})$ and $\tilde{O}(n + w^{3/2}_{\max})$ time, respectively. These results match the currently best running time for 0-1 Subset Sum. Prior to our work, the best running times (in terms of $n$ and $w_{\max}$) for Bounded Subset Sum is $\tilde{O}(n + w^{5/3}_{\max})$ [Polak, Rohwedder, Wegrzycki '21] and $\tilde{O}(n + \mu_{\max}^{1/2}w_{\max}^{3/2})$ [implied by Bringmann '19 and Bringmann, Wellnitz '21], where $\mu_{\max}$ refers to the maximum multiplicity of item weights

A Nearly Quadratic-Time FPTAS for Knapsack

We investigate polynomial-time approximation schemes for the classic 0-1 knapsack problem. The previous algorithm by Deng, Jin, and Mao (SODA'23) has approximation factor 1 + \eps with running time \widetilde{O}(n + \frac{1}{\eps^{2.2}}). There is a lower Bound of (n + \frac{1}{\eps})^{2-o(1)} conditioned on the hypothesis that $(\min, +)$ has no truly subquadratic algorithm. We close the gap by proposing an approximation scheme that runs in \widetilde{O}(n + \frac{1}{\eps^2}) time

Downregulation of Brassica napus MYB69 (BnMYB69) increases biomass growth and disease susceptibility via remodeling phytohormone, chlorophyll, shikimate and lignin levels

MYB transcription factors are major actors regulating plant development and adaptability. Brassica napus is a staple oil crop and is hampered by lodging and diseases. Here, four B. napus MYB69 (BnMYB69s) genes were cloned and functionally characterized. They were dominantly expressed in stems during lignification. BnMYB69 RNA interference (BnMYB69i) plants showed considerable changes in morphology, anatomy, metabolism and gene expression. Stem diameter, leaves, roots and total biomass were distinctly larger, but plant height was significantly reduced. Contents of lignin, cellulose and protopectin in stems were significantly reduced, accompanied with decrease in bending resistance and Sclerotinia sclerotiorum resistance. Anatomical detection observed perturbation in vascular and fiber differentiation in stems, but promotion in parenchyma growth, accompanied with changes in cell size and cell number. In shoots, contents of IAA, shikimates and proanthocyanidin were reduced, while contents of ABA, BL and leaf chlorophyll were increased. qRT-PCR revealed changes in multiple pathways of primary and secondary metabolisms. IAA treatment could recover many phenotypes and metabolisms of BnMYB69i plants. However, roots showed trends opposite to shoots in most cases, and BnMYB69i phenotypes were light-sensitive. Conclusively, BnMYB69s might be light-regulated positive regulators of shikimates-related metabolisms, and exert profound influences on various internal and external plant traits

Screening biomarkers for Sjogren’s Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells

BackgroundSjögren’s syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis.MethodsWe downloaded three datasets of SS patients’ and healthy pepole’s whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers’ diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied.ResultsWe obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2.ConclusionIn this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients

Effect of storage time on the silage quality and microbial community of mixed maize and faba bean in the Qinghai-Tibet Plateau

Tibetan Plateau is facing serious shortage of forage in winter and spring season due to its special geographical location. Utilization of forages is useful to alleviate the forage shortage in winter and spring season. Consequently, the current study was aimed to evaluate the influence of storage time on the silage quality and microbial community of the maize (Zea mays L.) and faba bean (Vicia faba L.) mixed silage at Qinghai-Tibet Plateau. Maize and faba bean were ensiled with a fresh weight ratio of 7:3, followed by 30, 60, 90, and 120 days of ensiling. The results showed the pH value of mixed silage was below 4.2 at all fermentation days. The LA (lactic acid) content slightly fluctuated with the extension of fermentation time, with 33.76 g/kg DM at 90 days of ensiling. The AA (acetic acid) and NH3-N/TN (ammonium nitrogen/total nitrogen) contents increased with the extension of fermentation time and no significantly different between 90 and 120 days. The CP (crude protein) and WSC (water soluble carbohydrate) contents of mixed silage decreased significantly (P < 0.05) with ensiling time, but the WSC content remained stable at 90 days. The Proteobacteria was the predominant phyla in fresh maize and faba bean, and Pseudomonas and Sphingomonas were the predominant genera. After ensiling, Lactobacillus was the prevalent genus at all ensiling days. The relative abundance of Lactococcus increased rapidly at 90 days of ensiling until 120 days of fermentation. Overall, the storage time significant influenced the silage fermentation quality, nutrient content, and microbial environment, and it remained stable for 90 days of ensiling at Qinghai-Tibet Plateau. Therefore, the recommended storage time of forage is 90 days in Qinghai-Tibet Plateau and other cool areas

A Fast Specular Highlight Removal Method for Smooth Liquor Bottle Surface Combined with U2-Net and LaMa Model

Highlight removal is a critical and challenging problem. In view of the complex highlight phenomenon on the surface of smooth liquor bottles in natural scenes, the traditional highlight removal algorithms cannot semantically disambiguate between all-white or near-white materials and highlights, and the recent highlight removal algorithms based on deep learning lack flexibility in network architecture, have network training difficulties and have insufficient object applicability. As a result, they cannot accurately locate and remove highlights in the face of some small sample highlight datasets with strong pertinence, which reduces the performance of some tasks. Therefore, this paper proposes a fast highlight removal method combining U2-Net and LaMa. The method consists of two stages. In the first stage, the U2-Net network is used to detect the specular reflection component in the liquor bottle input image and generate the mask map for the highlight area in batches. In the second stage, the liquor bottle input image and the mask map generated by the U2-Net are input to the LaMa network, and the surface highlights of the smooth liquor bottle are removed by relying on the powerful image inpainting performance of LaMa. Experiments on our self-made liquor bottle surface highlight dataset showed that this method outperformed other advanced methods in highlight detection and removal

Vertical Variation in Leaf Traits and Crown Structure Promote the Coexistence of Forest Tree Species

Vertical stratification in trees may respond to selective pressures to enhance light interception and utilization; therefore, the vertical functional variation in leaf traits may indicate niche partitioning within forests. In this study, vertical variations in leaf and crown structure traits of seven common tree species were analysed with respect to differences between species in different height groups, within the same height range, in the same species across tree height, and different parts of the individual tree crown to reveal coexistence mechanisms in subtropical forest tree species. There were multiple levels of trait variation in the vertical dimension, validating the existence of vertical niche differentiation in subtropical forest species. The functional trait differences arose among different height groups, among species co-occurring within the same height range, in the same species across tree height, and among different parts of the individual tree crown. Variation in comparative advantages, which was characterised by those traits between species across different height ranges, was also one of the manifestations of niche differentiation in the vertical dimension. Moreover, contrasting results between lower height ranges and higher ranges in the relationship between species’ differences in functional traits and species’ difference of abundance were found, further confirming that there was obvious vertical niche separation in the community. This study emphasised the importance of vertical variation in species’ performances in elucidating the mechanisms of tree species coexistence in subtropical forests