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Accurate time-series classification (TSC) remains a fundamental challenge in deep learning due to the complexity and variability of temporal patterns. While recurrent neural networks (RNNs) such as LSTM and GRU have shown promise in modeling sequential dependencies, they often suffer from limitations like vanishing gradients and high computational cost when handling long sequences. To overcome these issues, convolutional neural networks (CNNs), particularly the Inception architecture, have emerged as powerful alternatives due to their ability to capture multiscale local patterns efficiently. In this study, we propose InceptionResNet, a hybrid deep learning framework that integrates the residual learning mechanism of ResNet into the InceptionTime architecture. By replacing the fully convolutional network (FCN) shortcut module in InceptionFCN with ResNet-50, the model gains deeper representational capacity and improved gradient flow during training. We conduct extensive experiments on the UCR-85 benchmark dataset, comparing our model against state-of-the-art approaches, including InceptionTime, InceptionFCN, ResNet, FCN, and MLP. The results show that InceptionResNet achieves superior accuracy on 49 of 85 datasets, demonstrating its robustness and effectiveness in handling diverse and complex time series data. This work highlights the potential of integrating multiscale feature extraction and deep residual learning to advance the performance of TSC models in practical applications.

Blockchain designed for Mobile Ad hoc Networks (MANETs) and mesh networks is an emerging research topic that has to cope with the network partition problem. However, existing consensus algorithms used in blockchain have been designed to work in a fully connected network with reliable communication. As this assumption does not hold anymore in mobile wireless networks, we describe in this paper the problem of network partitions and their impact on blockchain. Then, we propose a new consensus algorithm called Consensus for Mesh (C4M) which is inspired by RAFT as a solution to this problem. The C4M consensus algorithm is integrated with Blockgraph, a blockchain solution for MANET and mesh networks. We implemented our solution in NS-3 to analyze its performances through simulations. The simulation results gave the first characterization of our algorithm, its performance, and its limits, especially in case of topology changes.

Cancer stem cells (CSCs) represent a subset of cells within tumours that exhibit self-renewal properties and the capacity to seed tumours. CSCs are typically refractory to conventional treatments and have been associated to metastasis and relapse. Salinomycin operates as a selective agent against CSCs through mechanisms that remain elusive. Here, we provide evidence that a synthetic derivative of salinomycin, which we named ironomycin (AM5), exhibits a more potent and selective activity against breast CSCs in vitro and in vivo , by accumulating and sequestering iron in lysosomes. In response to the ensuing cytoplasmic depletion of iron, cells triggered the degradation of ferritin in lysosomes, leading to further iron loading in this organelle. Iron-mediated production of reactive oxygen species promoted lysosomal membrane permeabilization, activating a cell death pathway consistent with ferroptosis. These findings reveal the prevalence of iron homeostasis in breast CSCs, pointing towards iron and iron-mediated processes as potential targets against these cells. Cancer stem cells are typically refractory to conventional treatments. Now, an unprecedented mechanism has been discovered by which salinomycin and derivatives can sequester iron in lysosomes leading to cytoplasmic iron depletion and the subsequent production of reactive oxygen species that are lethal to the cell. This discovery of the importance of iron in cancer stem cell maintenance provides an opportunity for developing new therapeutics.

Bike sharing systems are booming globally as a green and flexible transportationmode, but the flexibility also brings difficulties in keeping the bike stations balanced with enough bikes and docks. Understanding the spatio-temporal bike trip patterns in a bike sharing system, such as the popular trip origins and destinations during rush hours, is important for researchers to design models for bike scheduling and station management. However, due to privacy and operational concerns, bike trip data are usually not publicly available in many cities. Instead, the station feeds about real-time bike and dock number in stations are usually public, which we refer to as bike sharing system open data. In this paper, we propose an approach to infer the spatio-temporal bike trip patterns from the public station feeds. Since the number of possible trips (i.e., origin-destination station pairs) is much larger than the number of stations, we define the trip inference as an ill-posed inverse problem. To solve this problem, we identify the sparsity and locality properties of bike trip patterns, and propose a sparse and weighted regularization model to impose both properties in the solution. We evaluate our method using real-world data fromWashington, D.C. and New York City. Results show that our method can effectively infer the spatio-temporal bike trip patterns and outperform the baselines in both cities.

Anthracyclines such as doxorubicin are used extensively in the treatment of cancers. Anthraquinone-related angucyclines also exhibit antiproliferative properties and have been proposed to operate via similar mechanisms, including direct genome targeting. Here, we report the chemical synthesis of marmycin A and the study of its cellular activity. The aromatic core was constructed by means of a one-pot multistep reaction comprising a regioselective Diels–Alder cycloaddition, and the complex sugar backbone was introduced through a copper-catalysed Ullmann cross-coupling, followed by a challenging Friedel–Crafts cyclization. Remarkably, fluorescence microscopy revealed that marmycin A does not target the nucleus but instead accumulates in lysosomes, thereby promoting cell death independently of genome targeting. Furthermore, a synthetic dimer of marmycin A and the lysosome-targeting agent artesunate exhibited a synergistic activity against the invasive MDA-MB-231 cancer cell line. These findings shed light on the elusive pathways through which anthraquinone derivatives act in cells, pointing towards unanticipated biological and therapeutic applications. Marmycin A is an anthraquinone natural product with antiproliferative properties. Now the chemical synthesis of marmycin A—through a Diels–Alder cycloaddition, an Ullmann aromatic amination and a Friedel–Crafts cyclization—has enabled a study of its biological activity. Fluorescence microscopy reveals that marmycin A accumulates in lysosomes and promotes cell death independently of genome targeting.

Drawing on conservation resources theory, this study examined the relationships between customer incivility, supervisor incivility, and job performance. The study also investigated the mediating role of psychological distress and the moderating role of mindfulness in the above relationships. The findings, based on a data set collected from frontline employees working at an airport terminal in Vietnam, showed that psychological distress mediated the impacts of both customer incivility and supervisor incivility on extra-role performance but not on in-role performance. Finally, mindfulness mitigated the negative effects of both customer incivility and supervisor incivility on psychological distress. These findings offer a number of implications for theory and practice.

PurposeBased on a duality approach, this study examines the path from utilitarian value via cognitive trust versus hedonic value via affective trust in online shopping well-being. This study also explores the moderating role of extraversion in the relationships between shopping value and trust.Design/methodology/approachA data set collected from 648 online consumers in Vietnam was used to validate the measures employing confirmatory factor analysis (CFA) and to test the hypotheses using structural equation modelling (SEM).FindingsThe results show that online shopping well-being is determined hedonically and affectively rather than in an utilitarian manner and cognitively. Affective trust positively contributes to online shopping well-being, but cognitive trust does not. The dual-process associations between utilitarian shopping value and cognitive trust and between hedonic shopping value and cognitive trust were also confirmed. Finally, extraversion moderates the cognitive and affective associations between shopping values and trust.Originality/valueThis study contributes to the literature on online shopping by applying a dual perspective to confirm the role of hedonic shopping value and affective trust in positively determining online shopping well-being. As a result, this study provides a deeper understanding about if and why online shopping well-being is affect-based, instead of cognition-based.

A reduced graphite oxide nanosheet electrode (RGOnS) was prepared as a sensor for amoxicillin (AMX) detection, an antibiotic commonly used in the livestock farm, by the square-wave adsorptive stripping voltammetry technique. Graphite oxide with nanosheet shape was produced from a graphite electrode by a chronoamperometry process at 5 V and then an electrochemical reduction process was carried out to form RGOnS with restored long-range conjugated networks and better conductivity. The electrodes were characterized by SEM, EDX, and FTIR spectroscopy. The RGOnS electrode prepared at an optimal reduction potential of −1 V for 120 s exhibits a larger electrochemical active surface area, and the obtained oxidation signal of AMX is approximately ten times higher than that of the pristine graphite electrode. The analytical conditions such as the pH of electrolyte and accumulation time were optimized. The calibration curve built under the optimal conditions provided a good linear relationship in the range of AMX concentration from 0.5–80 µM with the correlation coefficient of 0.9992. The limit of detection was calculated as 0.193 µM. Satisfactory results are obtained from the detection of the AMX in different samples using the prepared electrode.

PurposeAdopting the duality approach, this study aims to examine cognitive and affective associations between shopping values, impulse buying tendencies and consumer shopping well-being. In addition, the study also aims to test the moderating role of self-control and compare the proposed relationships across the offline and online shopping contexts.Design/methodology/approachA survey dataset was collected from a sample of 529 offline and online consumers in Vietnam. Structural equation modelling (SEM) was employed to test the proposed relationships among the studied constructs.FindingsThe consequence of impulse buying is positive and affect-based. In addition, the positive associations between shopping values and impulse buying via dual process are validated and moderated by self-control. In addition, the association between cognitive impulse buying and shopping well-being is stronger in the online shopping context, whereas hedonic value has more influence on affective impulse buying in the offline shopping context. All other relationships are not statistically different across the two shopping contexts.Originality/valueThis study introduces an appropriate theoretical framework for studying impulse buying—the duality approach. Second, the research validates the dual process and positive consequence of impulse buying. Third, self-control's moderating role is validated, whereas the studied associations are initially compared across shopping contexts.

PurposeWorkplace incivility (WI) has been extensively studied. However, less is known about how WI spills over into employees' lives. Building on the work-home resources model, the authors develop a conceptual model investigating work-family enrichment (WFE) as the mediator between WI and subjective well-being (SWB) and coping strategies as the moderator of this indirect relationship.Design/methodology/approachSurvey data were gathered from 266 frontline employees (FLEs) working in different banks in Vietnam, using a convenience sampling technique. The partial least squares structural equation modeling (PLS-SEM) technique was employed.FindingsThe results show that coworker incivility (COWI) predicts a lower level of WFE, which in turn is associated with SWB, while supervisor incivility is not. The authors also found that coping strategies moderate the adverse influence of COWI on employees' WFE.Originality/valueAlthough much research has been conducted on the predictors of SWB, little is known about how WI and WFE together impact SWB, and insight into how to buffer the effects of WI are also lacking. This study thus fills a gap in the literature. Implications for theory, practice and future research are discussed.