Rethinking Attention Mechanism in Time Series Classification

Attention-based models have been widely used in many areas, such as computer vision and natural language processing. However, relevant applications in time series classification (TSC) have not been explored deeply yet, causing a significant number of TSC algorithms still suffer from general problems of attention mechanism, like quadratic complexity. In this paper, we promote the efficiency and performance of the attention mechanism by proposing our flexible multi-head linear attention (FMLA), which enhances locality awareness by layer-wise interactions with deformable convolutional blocks and online knowledge distillation. What's more, we propose a simple but effective mask mechanism that helps reduce the noise influence in time series and decrease the redundancy of the proposed FMLA by masking some positions of each given series proportionally. To stabilize this mechanism, samples are forwarded through the model with random mask layers several times and their outputs are aggregated to teach the same model with regular mask layers. We conduct extensive experiments on 85 UCR2018 datasets to compare our algorithm with 11 well-known ones and the results show that our algorithm has comparable performance in terms of top-1 accuracy. We also compare our model with three Transformer-based models with respect to the floating-point operations per second and number of parameters and find that our algorithm achieves significantly better efficiency with lower complexity

DTCM: Deep Transformer Capsule Mutual Distillation for Multivariate Time Series Classification

This paper proposes a dual-network-based feature extractor, perceptive capsule network (PCapN), for multivariate time series classification (MTSC), including a local feature network (LFN) and a global relation network (GRN). The LFN has two heads (i.e., Head_A and Head_B), each containing two squash CNN blocks and one dynamic routing block to extract the local features from the data and mine the connections among them. The GRN consists of two capsule-based transformer blocks and one dynamic routing block to capture the global patterns of each variable and correlate the useful information of multiple variables. Unfortunately, it is difficult to directly deploy PCapN on mobile devices due to its strict requirement for computing resources. So, this paper designs a lightweight capsule network (LCapN) to mimic the cumbersome PCapN. To promote knowledge transfer from PCapN to LCapN, this paper proposes a deep transformer capsule mutual (DTCM) distillation method. It is targeted and offline, using one- and two-way operations to supervise the knowledge distillation process for the dual-network-based student and teacher models. Experimental results show that the proposed PCapN and DTCM achieve excellent performance on UEA2018 datasets regarding top-1 accuracy

Constructing hyperchaotic attractors of conditional symmetry

By applying the symmetry property of nonlinear function for obtaining new polarity balance, hyperchaotic systems of conditional symmetry are constructed, and coexisting hyperchaotic attractors of conditional symmetry originated from 1-D and 2-D offset boosting are captured accordingly. More interestingly, a symmetric hyperchaotic system is proven to host conditional symmetry, and consequently output coexisting symmetric pair of attractors and their duplication of conditional symmetry. Consequently, two independent processes of attractor merging are observed, which have not been previously reported. Furthermore, the property of offset boosting is discussed for the newly constructed hyperchaotic systems. Circuit implementation based on the develop kit of STM32 is developed, it demonstrates those coexisting attractors are in good agreement with the theoretical analysis and numerical simulations

De novo transcriptome assembly and quantification reveal differentially expressed genes between soft-seed and hard-seed pomegranate (Punica granatum L.).

Pomegranate (Punica granatum L.) belongs to Punicaceae, and is valued for its social, ecological, economic, and aesthetic values, as well as more recently for its health benefits. The 'Tunisia' variety has softer seeds and big arils that are easily swallowed. It is a widely popular fruit; however, the molecular mechanisms of the formation of hard and soft seeds is not yet clear. We conducted a de novo assembly of the seed transcriptome in P. granatum L. and revealed differential gene expression between the soft-seed and hard-seed pomegranate varieties. A total of 35.1 Gb of data were acquired in this study, including 280,881,106 raw reads. Additionally, de novo transcriptome assembly generated 132,287 transcripts and 105,743 representative unigenes; approximately 13,805 unigenes (37.7%) were longer than 1,000 bp. Using bioinformatics annotation libraries, a total of 76,806 unigenes were annotated and, among the high-quality reads, 72.63% had at least one significant match to an existing gene model. Gene expression and differentially expressed genes were analyzed. The seed formation of the two pomegranate cultivars involves lignin biosynthesis and metabolism, including some genes encoding laccase and peroxidase, WRKY, MYB, and NAC transcription factors. In the hard-seed pomegranate, lignin-related genes and cellulose synthesis-related genes were highly expressed; in soft-seed pomegranates, expression of genes related to flavonoids and programmed cell death was slightly higher. We validated selection of the identified genes using qRT-PCR. This is the first transcriptome analysis of P. granatum L. This transcription sequencing greatly enriched the pomegranate molecular database, and the high-quality SSRs generated in this study will aid the gene cloning from pomegranate in the future. It provides important insights into the molecular mechanisms underlying the formation of soft seeds in pomegranate

Supporting information from A simple route to a novel acid-sensitive 20(<i>S</i>)-<i>O</i>-linked camptothecin norcantharidin acid ester derivative

Spectrum for all synthesized compound

Exercise Interventions Improved Sleep Quality through Regulating Intestinal Microbiota Composition

(1) Background: Sleep quality is closely related to the physical and mental health of college students. The objectives of this study were to obtain data on the sleep quality of university students and to investigate the relationship between intestinal flora and the improvement in sleep quality through exercise intervention. (2) Methods: Here, 11 university students with a body mass index (BMI) &le; 18 and Pittsburgh Sleep Quality Index (PSQI) &ge; 7 were selected as experimental subjects, and another 11 healthy people were recruited as control subjects. The experimental group and control group were each intervened with exercise for 8 weeks. We used 16SrDNA sequencing technology to analyze the variations of the intestinal flora and the relation of the variations and sleep quality improvement between the experimental group and the control group before and after the exercise intervention. (3) Results: The differences in gut flora composition between people with sleep disorders and healthy people were statistically significant (p &lt; 0.05). Before and after the exercise intervention, the differences were also statistically significant (p &lt; 0.05) in people with sleep disorders. The sleep-disordered population had a larger proportion compared with the healthy population (p &lt; 0.05). Blautia and Eubacterium hallii were microbe markers in the sleep-disordered population before and after the exercise intervention, while there was no microbe marker found in the healthy population. (4) Conclusions: The increase in Blautia and Eubacterium hallii, and the decrease in Agathobacter are associated with healthy sleep. Gut flora may be related to sleep disorders. Exercise intervention can improve sleep quality while changing the diversity of the gut flora, and exercise intervention targeting the gut flora is a new concept for preventing and treating sleep disorders

The impact of the new acute respiratory distress syndrome (ARDS) criteria on Berlin criteria ARDS patients: a multicenter cohort study

Objective: The European Society of Intensive Care Medicine (ESICM) recently recommended changes to the criteria of acute respiratory distress syndrome (ARDS), patients with high-flow oxygen were included, however, the effect of these changes remains unclear. Our objectives were to evaluate the performance of these new criteria and to compare the outcomes of patients meeting the new ARDS criteria with those meeting the Berlin ARDS criteria. Methods: This was a retrospective cohort. The patients admitted to the intensive care unit (ICU) were diagnosed with ARDS. Patients were classified as meeting Berlin criteria ARDS (n = 4279), high-flow nasal oxygen (HFNO) criteria ARDS (n = 559), or new criteria ARDS (n = 4838). Results: In comparison with HFNO criteria ARDS and new criteria ARDS, patients with Berlin criteria ARDS demonstrated lower blood oxygen levels assessed by PaO2/FiO2, SpO2/FiO2, and ROX (SpO2/FiO2/respiratory rate) (p < 0.001); and higher severity of illness assessed by the Sequential Organ Failure Assessment (SOFA) score, Acute Physiology And Chronic Health Evaluations (APACHE II), Simplified Acute Physiology Score (SAPS II) (p < 0.001), (p < 0.001), and longer ICU and hospital stays (p < 0.001). In comparison with the HFNO criteria, patients meeting Berlin criteria ARDS had higher hospital mortality (10.6% vs. 16.9%; p = 0.0082), 28-day mortality (10.6% vs. 16.5%; p = 0.0079), and 90-day mortality (10.7% vs. 17.1%; p = 0.0083). ARDS patients with HFNO did not have severe ARDS; Berlin criteria ARDS patients with severe ARDS had the highest mortality rate (approximately 33%). PaO2/FiO2, SpO2/FiO2, and ROX negatively correlated with the SOFA and APACHE II scores. The SOFA and APACHE II scores had high specificity and sensitivity for prognosis in patients with new criteria ARDS. Conclusion: The new criteria of ARDS reduced the severity of illness, length of stay in the ICU, length of hospital stays, and overall mortality. SOFA and APACHE II scores remain important in assessing the prognosis of patients with new criteria ARDS. Trial registration: Registration number: ChiCTR2200067084.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Genome-wide association study provided insights into the polled phenotype and polled intersex syndrome (PIS) in goats

Abstract Background Breeding polled goats is a welfare-friendly approach for horn removal in comparison to invasive methods. To gain a comprehensive understanding of the genetic basis underlying polledness in goats, we conducted whole-genome sequencing of 106 Xinong Saanen dairy goats, including 33 horned individuals, 70 polled individuals, and 3 polled intersexuality syndrome (PIS) individuals. Methods The present study employed a genome-wide association study (GWAS) and linkage disequilibrium (LD) analysis to precisely map the genetic locus underlying the polled phenotype in goats. Results The analysis conducted in our study revealed a total of 320 genome-wide significant single nucleotide polymorphisms (SNPs) associated with the horned/polled phenotype in goats. These SNPs exhibited two distinct peaks on chromosome 1, spanning from 128,817,052 to 133,005,441 bp and from 150,336,143 to 150,808,639 bp. The present study identified three genome-wide significant SNPs, namely Chr1:129789816, Chr1:129791507, and Chr1:129791577, as potential markers of PIS-affected goats. The results of our LD analysis suggested a potential association between MRPS22 and infertile intersex individuals, as well as a potential association between ERG and the polled trait in goats. Conclusion We have successfully identified three marker SNPs closely linked to PIS, as well as several candidate genes associated with the polled trait in goats. These results may contribute to the development of SNP chips for early prediction of PIS in goats, thereby facilitating breeding programs aimed at producing fertile herds with polled traits

Complementary iTRAQ-based proteomic and RNA sequencing-based transcriptomic analyses reveal a complex network regulating pomegranate (Punica granatum L.) fruit peel colour

Peel colour is an important factor affecting the marketability of pomegranate fruits. Therefore, elucidating the genetic mechanism of fruit peel colour development may be useful for breeding pomegranate cultivars with enhanced fruit peel colours. In this study, we combined an iTRAQ-based proteome-level analysis with an RNA sequencing-based transcriptome-level analysis to detect the proteins and genes related to fruit peel colour development in pomegranate. We analysed the ‘Tunisia’ (red fruit) and ‘White’ (white fruit) pomegranate cultivars at two stages of fruit development. A total of 27 differentially abundant proteins (increased abundance) and 54 differentially expressed genes (16 up-regulated and 38 down-regulated) were identified from our proteomics and transcriptomics data. The identified proteins and genes contribute to pomegranate fruit peel colour by participating in the biosynthesis of anthocyanins, stilbenoids, diarylheptanoids, gingerols, flavonoids, and phenylpropanoids. Several candidate proteins and genes corresponded to enzymes related to general reactions (PAL, 4CL, DFR, LDOX/ANS, CHS, and F3′5′H) and glycosylation (GT1 and UGAT) of compounds and pigments related to the colour of pomegranate fruit peel. Complementary proteome- and transcriptome-level analyses revealed a complex molecular network controlling fruit peel colour. The candidate genes identified in this study may be useful for the marker-based breeding of new pomegranate cultivars