PRESEE: An MDL/MML Algorithm to Time-Series Stream Segmenting

Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmentingmainly focused on the issue of ameliorating precision instead of payingmuch attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream

Preparation and characterization of squid pen chitooligosaccharide-epigallocatechin gallate conjugates and their antioxidant and antimicrobial activities

Chitooligosaccharide (COS) and epigallocatechin-3-gallate (EGCG) at various concentrations were used for the preparation of COS–EGCG conjugates. The highest total phenolic content (TPC), representing the amount of EGCG conjugated, was obtained for 1 wt% COS together with EGCG at 0.5 wt% (C1-E0.5- conjugate) or 1.0 wt% (C1-E1.0-conjugate) (66.83 and 69.22 mg EGCG per g sample, respectively) (p < 0.05). The 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) and 2,20 -azino-bis(3-ethylbenzothiazoline-6- sulfonic acid) (ABTS) radical scavenging activities (DRSA and ARSA, respectively) and ferric reducing antioxidant power (FRAP) of all the samples showed similar trends with TPC. The C1-E0.5-conjugate had higher DRSA, ARSA, FRAP and oxygen radical absorbance capacity (ORAC) values than COS (p < 0.05). Similarly, the antimicrobial activity of COS increased when conjugated with EGCG (p < 0.05). FTIR, 1 HNMR and 13C-NMR analyses confirmed the successful grafting of EGCG with COS. Therefore, 1 wt% COS and 0.5 wt% EGCG were used for the production of a conjugate with augmented antioxidant activity, which could be used to retard lipid oxidation of fatty foods

Normal-Mode-Analysis-Guided Investigation of Crucial Intersubunit Contacts in the cAMP-Dependent Gating in HCN Channels

Abstract Protein structures define a complex network of atomic interactions in three dimensions. Direct visualization of the structure and analysis of the interaction potential energy are not straightforward approaches to pinpoint the atomic contacts that are crucial for protein function. We used the tetrameric hyperpolarization-activated cAMP-regulated (HCN) channel as a model system to study the intersubunit contacts in cAMP-dependent gating. To obtain a systematic survey of the contacts between each pair of residues, we used normal-mode analysis, a computational approach for studying protein dynamics, and constructed the covariance matrix for C-α atoms. The significant contacts revealed by covariance analysis were further investigated by means of mutagenesis and functional assays. Among the mutant channels that show phenotypes different from those of the wild-type, we focused on two mutant channels that express opposite changes in cAMP-dependent gating. Subsequent biochemical assays on isolated C-terminal fragments, including the cAMP binding domain, revealed only minimal effects on cAMP binding, suggesting the necessity of interpreting the cAMP-dependent allosteric regulation at the whole-channel level. For this purpose, we applied the patch-clamp fluorometry technique and observed correlated changes in the dynamic, state-dependent cAMP binding in the mutant channels. This study not only provides further understanding of the intersubunit contacts in allosteric coupling in the HCN channel, it also illustrates an effective strategy for delineating important atomic contacts within a structure

Are We Ready to Embrace Generative AI for Software Q&A?

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow is that the answers generated by ChatGPT are of low quality. To verify this, we conduct a comparative evaluation of human-written and ChatGPT-generated answers. Our methodology employs both automatic comparison and a manual study. Our results suggest that human-written and ChatGPT-generated answers are semantically similar, however, human-written answers outperform ChatGPT-generated ones consistently across multiple aspects, specifically by 10% on the overall score. We release the data, analysis scripts, and detailed results at https://anonymous.4open.science/r/GAI4SQA-FD5C.Comment: Accepted by the New Ideas and Emerging Results (NIER) track at The IEEE/ACM Automated Software Engineering (ASE) Conferenc

Genome-Wide Association and Mechanistic Studies Indicate That Immune Response Contributes to Alzheimer’s Disease Development

Alzheimer’s disease (AD) is the most common cause of dementia. Although genome-wide association study (GWAS) have reported hundreds of single-nucleotide polymorphisms (SNPs) and genes linked to AD, the mechanisms about how these SNPs modulate the development of AD remain largely unknown. In this study, we performed GWAS for three traits in cerebrospinal fluid (CSF) and one clinical trait in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Our analysis identified five most significant AD related SNPs (FDR &lt; 0.05) within or proximal to APOE, APOC1, and TOMM40. One of the SNPs was co-inherited with APOE allele 4, which is the most important genetic risk factor for AD. Three of the five SNPs were located in promoter or enhancer regions, and transcription factor (TF) binding affinity calculations showed dramatic changes (| Log2FC| &gt; 2) of three TFs (PLAG1, RREB1, and ZBTB33) for two motifs containing SNPs rs2075650 and rs157580. In addition, our GWAS showed that both rs2075650 and rs157580 were significantly associated with the poliovirus receptor-related 2 (PVRL2) gene (FDR &lt; 0.25), which is involved in spreading of herpes simplex virus (HSV). The altered regulation of PVRL2 may increase the susceptibility AD patients to HSV and other virus infections of the brain. Our work suggests that AD is a type of immune disorder driven by viral or microbial infections of the brain during aging

An Intelligent Wildfire Detection Approach through Cameras Based on Deep Learning

Fire is one of the most serious disasters in the wild environment such as mountains and jungles, which not only causes huge property damage, but also may lead to the destruction of natural ecosystems and a series of other environmental problems. Considering the superiority and rapid development of computer vision, we present a novel intelligent wildfire detection method through video cameras for preventing wildfire hazards from becoming out of control. The model is improved based on YOLOV5S architectures. At first, we realize its lightweight design by incorporating the MobilenetV3 structure. Moreover, the improvement of detection accuracy is achieved by further improving its backbone, neck, and head layers. The experiments on a dataset containing a large number of wild flame and wild smoke images have demonstrated that the novel model is suitable for wildfire detection with excellent detection accuracy while meeting the requirements of real-time detection. Its wild deployment will help detect fire at the very early stage, effectively prevent the spread of wildfires, and therefore significantly contribute to loss prevention

Diatom response to heavy metal pollution and nutrient enrichment in an urban lake: evidence from paleolimnology

Diatoms and geochemical stratigraphy were studied in sediment core samples collected from a heavily polluted urban lake (SE China) in order to track the history of eutrophication and heavy metal contamination. The sediment profile covered ca. 60 years (from ca. 1951 to 2011) based on 137Cs and Spheroidal carbonaceous particles (SCP) dating, and encompassed a period of rapid industrial development in this region. Diatoms experienced two visible shifts, including the replacement of benthic and epiphytic taxa by planktonic species (e.g., Cyclotella meneghiniana Kützing) in 1972, and the dominance of Cyclotella atomus Hustedt and Nitzschia palea (Kützing) W. Smith after 1999. Metals (i.e., Cd, Pb and Zn), total phosphorus, total nitrogen and total organic carbon all increased in the past 60 years. Redundancy analysis was used to correlate diatom with chemical change and explained 50.3–60% of total variation in diatom data for three periods (from 1951 to 1999, between 1951 and 2011 and from 1972 to 2011). The combined effects of nutrients and metals were the predominant factor, capturing 29.6–42.8% of the total variance. Nutrients alone accounted for little more variance than did metals alone for the first flora shift about 1972. The further shift after 1999 was more influenced by the sole effect of metals than that of nutrients. Increases in species (e.g., N. Palea) able to tolerate both nutrient-related and metal-related stressors were related to persistent nutrient and metal inputs. In addition, climate warming might exacerbate eutrophication and metal contamination in this lake.Diatoms and geochemical proxies were analyzed in recent sediments from an urban lake. Chronology was estimated based on 137Cs and Spheroidal carbonaceous particles dating. Diatom succession over the past 60 years correlated with nutrient enrichment and heavy metal inputs

Quorum Quenching Mediated Bacteria Interruption as a Probable Strategy for Drinking Water Treatment against Bacterial Pollution

Pseudomonas aeruginosa in water lines may cause bacteria pollution indrinking fountains that could affect the quality of potable water, thus posing a risk to public health. A clean and efficient strategy is required for drinking water treatment for food safety. In this study, an AiiA-homologous lactonase was cloned from a deep-sea probiotics Bacillus velezensis (DH82 strain), and was heterologously expressed so that the capacity of the enzyme on the N-acyl-L-homoserine lactone (AHL)-degrading, effect of bacterial proliferation, biofilm formation and toxic factors release, and membrane pollution from P. aeruginosa could each be investigated to analyze the effect of the enzyme on water treatment. The enzyme effectively degraded the signal molecules of P. aeruginosa (C6-HSL and C12-HSL), inhibited early proliferation and biofilm formation, significantly reduced toxic products (pyocyanin and rhamnolipid), and inhibited bacterial fouling on the filter membrane, which prevented the secondary contamination of P. aeruginosa in drinking water. The findings demonstrated that the quorum quenching enzyme from probiotics could prevent bacteria pollution and improve potable water quality, and that the enzyme treatment could be used as a probable strategy for drinking water treatment