The Impact of Logistics Services On The E-Shoppers' Satisfaction

In a digital era, E-commerce is fast-growing industry. People never thought to live without E-commerce. A day without E-commerce would be complicated, inconvenience and impossible. There are many components in online shopping market that play important roles in satisfying online shoppers. One of it is logistics services which influence online shoppers satisfaction level. Thus, this study mainly explore how logistics services may influences online shoppers satisfaction level. The specific aim of this paper is to determine the main logistics services elements that influences satisfaction of online shoppers. A total of 178 respondents who have experienced in online shopping were interviewed face-to-face using a structured questionnaire. Pearson correlation and multiple regression were used to analyze the data. The findings from the study revealed that service recovery, delivery service and customer service were the factors positively influencing the satisfaction level of E-commerce shoppers. The results of this study would helpful for online retailers to identify ways for improvement of their services especially from logistics perspective that eventually will enhance shoppers loyalty and enhance satisfaction

MultiRes Attention Deep Learning Approach for Abdominal Fat Compartment Segmentation and Quantification

Global increase in obesity has led to alarming rise in co-morbidities leading to deteriorated quality of life. Obesity phenotyping benefits profiling and management of the condition but warrants accurate quantification of fat compartments. Manual quantification MR scans are time consuming and laborious. Hence, many studies rely on semi/automatic methods for quantification of abdominal fat compartments. We propose a MultiRes-Attention U-Net with hybrid loss function for segmentation of different abdominal fata compartments namely (i) Superficial subcutaneous adipose tissue (SSAT), (ii) Deep subcutaneous adipose tissue (DSAT), and (iii) Visceral adipose tissue (VAT) using abdominal MR scans. MultiRes block, ResAtt-Path, and attention gates can handle shape, scale, and heterogeneity in the data. Dataset involved MR scans from 190 community-dwelling older adults (mainly Chinese, 69.5% females) with mean age—67.85 ± 7.90 years), BMI 23.75 ± 3.65 kg/m2. Twenty-six datasets were manually segmented to generate the ground truth. Data augmentations were performed using MR data acquisition variations. Training and validation were performed on 105 datasets, while testing was conducted on 25 datasets. Median Dice scores were 0.97 for SSAT & DSAT and 0.96 for VAT, and mean Hausdorff distance was <5 mm for all the three fat compartments. Further, MultiRes-Attention U-Net was tested on a new 190 datasets (unseen during training; upper & lower abdomen scans with different resolution), which yielded accurate results. MultiRes-Attention U-Net significantly improved the performance over MultiResUNet, showed excellent generalization and holds promise for body-profiling in large cohort studies

Dependence of BOLD signal fluctuation on arterial blood CO2 and O2: Implication for resting-state functional connectivity

Blood oxygenation level dependent (BOLD) functional MRI signal is known to be modulated by the CO level. Typically only end-tidal CO, rather than the arterial partial pressure of CO (paCO), was measured while the arterial partial pressure of O (paO) level was not controlled due to free breathing, making their contribution not separable. Especially, the influences of paO and paCO on resting-state functional connectivity are not well studied. In this study, we investigated the relationship between paCO and resting as well as stimulus-evoked BOLD signals under hyperoxic and hypercapnic manipulation with tight control of arterial paO. Rats under isoflurane anesthesia were subjected to six inspired gas conditions: 47% O in air (Normal), adding 1%, 2% or 5% CO, carbogen (95% O/5% CO), and 100% O. Somatosensory BOLD activation was significantly increased under 100% O, while reduced with increased paCO levels. However, while resting BOLD connectivity pattern expanded and bilateral correlation increased under 100% O, the correlation coefficient between the left and right somatosensory cortex was generally not dependent on paCO or paO. Interestingly, the correlation in 0.04-0.07Hz range significantly increased with CO levels. Intracortical electrophysiological recordings showed a similar trend as the BOLD but the neurovascular coupling varied. The results suggest that paO and paCO together rather than paCO alone alter the BOLD signal. The response is not purely vascular in nature but has strong neuronal origins. This should be taken into consideration when designing calibrated BOLD experiment and interpreting functional connectivity data especially in aging, under drug, or neurological disorders

Deposition of AlN thin films with cubic crystal structures on silicon substrates at room temperature

Japanese Journal of Applied Physics, Part 2: Letters395 AL423-L425JAPL

Connectomic imaging reveals Huntington-related pathological and pharmaceutical effects in a mouse model

Recent studies suggest that neurodegenerative diseases could affect brain structure and function in disease-specific network patterns; however, how spontaneous activity affects structural covariance network (SC) is not clear. We hypothesized that hyper-excitability in Huntington disease (HD) disrupts the coordinated structural and functional connectivity, and treatment with memantine helps to reduce excitotoxicity and normalize the connectivity. MRI was conducted to measure somatosensory activation, resting-state functional-connectivity (rsFC), SC, amplitude of low frequency fluctuation (ALFF) and ALFF covariance (ALFFC) in the YAC128 mouse model of HD. We found somatosensory activation was unchanged but the subcortical ALFF was increased in HD mice, indicating subcortical but not cortical hyperactivity. The reduced sensorimotor rsFC but spared hippocampal and default mode networks in the HD mice was consistent with the more pronounced impairment in motor function compared with cognitive performance. The disease suppressed SC globally and reduced ALFFC in the basal ganglia network as well as its anti-correlation with the default mode network. By comparing these connectivity measures, we found that the originally coupled rsFC-SC relationship was impaired whereas SC-ALFFC correlation was increased by HD, suggesting disease facilitated covariation of brain volume and activity amplitude but not neural synchrony. The comparison with mono-synaptic axonal projection supports the hypothesis that rsFC, but not SC or ALFFC, is highly dependent on structural connectivity under healthy conditions. Treatment with memantine had a strong effect on normalizing the SC and reducing ALFF while slightly increasing other connectivity measures and restoring the rsFC-SC coupling, which is consistent with its effect on alleviating hyper-excitability and improving the coordinated neural growth. These results indicate that HD affects the cerebral structure–function relationship which could be partially reverted by NMDA antagonism. These connectivity measures provide unique insights into pathological and pharmaceutical effects in brain circuitry, and could be translatable biomarkers for evaluating drug effect and refining its efficacy

The lateral entorhinal cortex is a hub for local and global dysfunction in early Alzheimer's disease states

Functional network activity alterations are one of the earliest hallmarks of Alzheimer’s disease (AD), detected prior to amyloidosis and tauopathy. Better understanding the neuronal underpinnings of such network alterations could offer mechanistic insight into AD progression. Here, we examined a mouse model (3xTgAD mice) recapitulating this early AD stage. We found resting functional connectivity loss within ventral networks, including the entorhinal cortex, aligning with the spatial distribution of tauopathy reported in humans. Unexpectedly, in contrast to decreased connectivity at rest, 3xTgAD mice show enhanced fMRI signal within several projection areas following optogenetic activation of the entorhinal cortex. We corroborate this finding by demonstrating neuronal facilitation within ventral networks and synaptic hyperexcitability in projection targets. 3xTgAD mice, thus, reveal a dichotomic hypo-connected:resting versus hyper-responsive:active phenotype. This strong homotopy between the areas affected supports the translatability of this pathophysiological model to tau-related, early-AD deficits in humans

The lateral entorhinal cortex is a hub for local and global dysfunction in early Alzheimer's disease states

10.1177/0271678X221082016JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM4291616-163

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations