Research on E-commerce Online to Offline Behavior Mechanism in Agricultural Products

Currently, online and offline channel integration as a successful business model is used in many industries, this paper aims at providing an insight into the factors affecting online channel (online shop) and offline channels (entity shop) in the agricultural product industry. Drawn from the extant literature, a consumer online and offline behavior model including trust, system quality, information quality , environment quality and service quality, online and offline satisfaction ,customer loyalty were provides. Data were obtained from 228 customers in china during 2014. Based on the data obtained, SPSS19.0 software is used to analyze reliability test and validity, descriptive statistics, correlation analysis, and AMOS17.0 were employed to calculate the path coefficient, and tests the proposed model. Data analysis shows that: The model describes the relationship among the online satisfaction, offline satisfaction and customer loyalty, and establishes a multi-relationship model that includes trust, system quality, information quality, environment quality and service quality. The factors impacting online satisfaction include trust, system quality and information quality; the factors impacting offline satisfaction include environment satisfaction and service quality. Meanwhile, we highlight the role of trust in online satisfaction, and prove that both online satisfaction and offline satisfaction have interaction on customer loyalty. Keywords

Soundscape and social relationships in urban public spaces

‘Soundscape’ is defined as the acoustic environment as perceived or experienced and/ or understood in context by a person or people. In the context of urban public spaces, activities can be varied among different social relationship groups which might influence their requirements for soundscape. Four studies were carried out in urban public squares of Suzhou, China, and Sheffield and London, UK to explore the mechanism between soundscape and social relationships. Behavioural observations (study 1) and interviews with Grounded Theory (study 2) were used to explore types of relationship in relation to their patterns of use and the public’s perceptual structure of soundscape in urban public spaces. A questionnaire (study 3) then investigated how companion factors, compared with other demographic factors, influence soundscape evaluation. Finally, study 4 used survey and observations to explore how social willingness levels of various social relationship types might be enhanced through soundscape design. Three types of social relationship were categorized and ranked by relationship intensities: Intimate Pair, Intimate Group and Social Group. People with closer relationships participate multiple activities at once and involve more social interactions. Grounded Theory generated four elements of soundscape, which form a three- level process: sound classifications- sound appraisals (sound features and psychological reactions)- and judgment (sound preferences). Companion factors were suggested to influence soundscape evaluations comparing to other demographic factors: closer groups tended to evaluate socially interactive sounds more positively. Human sounds and event sounds, as two kinds of socially interactive sounds, were both found to stimulate social willingness while event sounds negatively affect soundscape suitability. A balance between suitability and stimulation should be achieved to enhance sociability, especially for closer groups. Results from this study give guidance for future urban public soundscape research addressing sound preferences of various relationship types. This study included a limited choice of urban public spaces and cities, and social relationships were limited to relationship intensities. Future research should consider methods such as face recognition and deep learning to more-efficiently recognize relationship types and sociability of urban public spaces

A phenol-based compartmental ligand as a potential chemosensor for zinc(ii) cations

An "end-off"-type compartmental Lewis base, 2,6-bis(2-hydroxybenzyl-2-hydroxyethylamino)methyl-4-methylphenol (L), was synthesized as a potential chemosensor for Zn2+ ions. L coordinates two Zn2+ cations in methanol-water solution, forming a dinuclear complex whose formulation was confirmed by ESI-MS spectroscopy and Job's plot. The fluorescence of L is remarkably enhanced by Zn2+ as compared with K+, Ca2+, Mg2+, Cu2+, Pb2+, Mn2+, Fe3+, Fe2+, Co2+, Cd2+ and Ni2+ ions. The fluorescence enhancement is attributed to the complexation of Zn2+ with L, which interrupts the photoinduced electron transfer process and rigidifies the molecular skeleton of L. The fluorescence of L is greatly dependent on the acidity and polarity of the solvents. This compound may be used as a probe to sense Zn2+ ion in polar protic solvents after proper modification

Dark structures in sunspot light bridges

We present unprecedented high-resolution TiO images and Fe I 1565 nm spectropolarimetric data of two light bridges taken by the 1.6-m Goode Solar Telescope at Big Bear Solar Observatory. In the first light bridge (LB1), we find striking knot-like dark structures within the central dark lane. Many dark knots show migration away from the penumbra along the light bridge. The sizes, intensity depressions and apparent speeds of their proper motion along the light bridges of 33 dark knots identified from the TiO images are mainly in the ranges of 80$\sim$200~km, 30\%$\sim$50\%, and 0.3$\sim$1.2~km~s$^{-1}$, respectively. In the second light bridge (LB2), a faint central dark lane and striking transverse intergranular lanes were observed. These intergranular lanes have sizes and intensity depressions comparable to those of the dark knots in LB1, and also migrate away from the penumbra at similar speeds. Our observations reveal that LB2 is made up of a chain of evolving convection cells, as indicated by patches of blue shift surrounded by narrow lanes of red shift. The central dark lane generally corresponds to blueshifts, supporting the previous suggestion of central dark lanes being the top parts of convection upflows. In contrast, the intergranular lanes are associated with redshifts and located at two sides of each convection cell. The magnetic fields are stronger in intergranular lanes than in the central dark lane. These results suggest that these intergranular lanes are manifestations of convergent convective downflows in the light bridge. We also provide evidence that the dark knots observed in LB1 may have a similar origin.Comment: 6 figure

Impact Response Comparison Between Parametric Human Models and Postmortem Human Subjects with a Wide Range of Obesity Levels

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138906/1/oby21947_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138906/2/oby21947.pd

Efficient Neural Neighborhood Search for Pickup and Delivery Problems

We present an efficient Neural Neighborhood Search (N2S) approach for pickup and delivery problems (PDPs). In specific, we design a powerful Synthesis Attention that allows the vanilla self-attention to synthesize various types of features regarding a route solution. We also exploit two customized decoders that automatically learn to perform removal and reinsertion of a pickup-delivery node pair to tackle the precedence constraint. Additionally, a diversity enhancement scheme is leveraged to further ameliorate the performance. Our N2S is generic, and extensive experiments on two canonical PDP variants show that it can produce state-of-the-art results among existing neural methods. Moreover, it even outstrips the well-known LKH3 solver on the more constrained PDP variant. Our implementation for N2S is available online.Comment: Accepted at IJCAI 2022 (short oral

Therapeutic Mechanisms of Berberine to Improve the Intestinal Barrier Function via Modulating Gut Microbiota, TLR4/NF-κ B/MTORC Pathway and Autophagy in Cats

BackgroundInflammatory bowel disease (IBD), a disease that seriously harms human and animal health, has attracted many researchers’ attention because of its complexity and difficulty in treatment. Most research has involved rats and dogs, and very little was cats. We should know that gut microbiota varies significantly from animal to animal. Traditional Chinese Medicine and its monomer component have many advantages compared with antibiotics used in pet clinics. Numerous studies have shown berberine (berberine hydrochloride) therapeutic value for IBD. However, the specific mechanism remains to consider.ResultsWe assessed gut pathology and analyzed fecal bacterial composition using Histological staining and 16S rRNA sequence. Dioctyl sodium sulfosuccinate (DSS) administration destroyed intestinal mucosal structure and changed the diversity of intestinal flora relative to control. RT-PCR and western blot confirmed specific molecular mechanisms that trigger acute inflammation and intestinal mucosal barrier function disruption after DSS treatment. And autophagy inhibition is typical pathogenesis of IBD. Interestingly, berberine ameliorates inflammation during the development of the intestinal by modulating the toll-like receptors 4 (TLR4)/nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway and activating autophagy. Berberine significantly reduces tumor necrosis factor α (TNF-α), interleukin (IL)-6, and IL-1β expression in cats’ serum. Enhancing the antioxidant effect of IBD cats is one of the protective mechanisms of berberine. We demonstrated that berberine repairs intestinal barrier function by activating the mammalian target of rapamycin (mTOR) complex (MTORC), which inhibits autophagy.ConclusionBerberine can restore intestinal microbiota homeostasis and regulate the TLR4/NF-κB pathway, thereby controlling inflammatory responses. We propose a novel mechanism of berberine therapy for IBD, namely, berberine therapy can simultaneously activate MTORC and autophagy to restore intestinal mucosal barrier function in cats, which should be further studied to shed light on berberine to IBD

Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training

An activation function is an element-wise mathematical function and plays a crucial role in deep neural networks (DNN). Many novel and sophisticated activation functions have been proposed to improve the DNN accuracy but also consume massive memory in the training process with back-propagation. In this study, we propose the nested forward automatic differentiation (Forward-AD), specifically for the element-wise activation function for memory-efficient DNN training. We deploy nested Forward-AD in two widely-used deep learning frameworks, TensorFlow and PyTorch, which support the static and dynamic computation graph, respectively. Our evaluation shows that nested Forward-AD reduces the memory footprint by up to 1.97x than the baseline model and outperforms the recomputation by 20% under the same memory reduction ratio.Comment: 8 pages, ICCD 202

Sequencing and Analysis of MicroRNAs in Bovine Milk Exosomes

In this study, density-gradient centrifugation was used to extract bovine milk exosomes, and the small non-coding RNA (sRNA) in the exosomes were sequenced by Illumina sequencing technology to explore the expression profile of bovine milk microRNAs (miRNAs). Through quality control of the original sequence, a total of 3 899 629 pure sRNA sequences were obtained, and their length was concentrated at 28 nt. By comparison with the database, 61 known miRNAs and 346 novel miRNAs were identified. The results of gene ontology enrichment analysis showed that miRNAs from bovine milk exosomes played a critical role in various biological processes such as cell process, single organism process and metabolic process. It mainly consisted of cells and organelles and was mainly involved in molecular functions such as binding, catalytic activity and transporter activity. The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that the known miRNAs and the new miRNA target genes were significantly enriched in pertussis (ko05133), chemokine signal pathway (ko04062), endocytosis (ko04144), lysosome (ko04142) and other pathways, and bovine milk exosome miRNAs played an important role in specific signaling pathways

Differential co-expression analysis reveals early stage transcriptomic decoupling in Alzheimer’s disease

Background: Alzheimer's disease (AD) is one of the leading causes of death in the US and there is no validated drugs to stop, slow or prevent AD. Despite tremendous effort on biomarker discovery, existing findings are mostly individual biomarkers and provide limited insights into the transcriptomic decoupling underlying AD. We propose to explore the gene co-expression patterns in multiple AD stages, including cognitively normal (CN), early mild cognitive impairment (EMCI), late MCI and AD. Methods: We modified traiditonal joint graphical lasso to model our asusmption that the co-expression networks in consecutive disease stages are largely similar with critical differences. In addition, we performed subsequent network comparison analysis for identification of stage specific transcriptomic decoupling. We focused our analysis on top AD-enriched pathways. Results: We observed that 419 edges in CN, 420 edges in EMCI, 381 edges in LMCI and 250 edges in AD were frequently estimated with non zero weights. With modified JGL, the weight of all estimated edges in CN, EMCI and LMCI are zero. In AD group, 299 edges were occasionally estimated to be nonzero and the average correlation between genes was 0.0023. For co-expression change during AD progression, there are 66 pairs of genes that demonstrated a continuously decreasing or increasing co-expression from CN to EMCI, LMCI and AD.The network level clustering coefficient remains stable from CN to LMCI and then decreases significantly when progressing to AD. When evaluating edge level differences, we identified eight gene modules with continuously decreasing or increasing co-expression patterns during AD progression. Five of them shows significant changes from CN to EMCI and thus have the potential to serve system biomarkers for early screening of AD. Conclusion: We employed a modified joint graphical lasso for estimation of co-expression networks for multiple stages of AD. Comparing with graphical lasso, our modified joint graphical lasso model accounts for the similarity in consecutive disease stages. Our results on real data set revealed five gene clusters with obvious co-expression pattern change from CN to EMCI, which could be used as potential system-level biomarkers for early screening of AD