Bamboo has been widely utilized as a load bearing material in building construction since ancient times by taking advantage of its excellent mechanical performances under loading as well as its low density and rapid growth. Applications of bamboo to engineering, architecture, and infrastructure require an in-depth understanding of the relationship between its morphology and mechanics, including how this regularly spaced segmental structure adapts to taking the applied loads. However, previous research on buckling behavior of structural bamboo considered it as a homogenous tube without multiscale structural features, and no reasonable explanation for the regular segment length was proposed. Here, we have implemented representative volume elements within the framework of finite element analysis to study the mechanical response of a bamboo culm under axial compressive load and systematically investigated how the bamboo's hierarchical structural features (e.g., gradient fiber distribution, periodic nodes, and others) contribute to its compression capacity. We find that column buckling is a critical failure mode that leads to the collapse of the entire structure, which can be disastrous. We observe that the gradient fiber distribution pattern along the radial direction significantly contributes to its strength. We find that the occurrence of fiber deviation at the node region reduces the strength of bamboo. Nevertheless, our results show that structural features such as external ridge and internal diaphragm play the role of reinforcement while the effect is more significant for bamboo than other plants with similar node appearance. Our work provides structural insights into the outstanding mechanics of bamboo. Such information could provide a guide for engineers to predict the material mechanics according to its structure, design bamboo-inspired composite materials, and construct high-performance architectures with bamboo accordingly.

Tracking a liquid or food bolus in videofluoroscopic images during X-ray based diagnostic swallowing examinations is a dominant clinical approach to assess human swallowing function during oral, pharyngeal and esophageal stages of swallowing. This tracking represents a highly challenging problem for clinicians as swallowing is a rapid action. Therefore, we developed a computer-aided method to automate bolus detection and tracking in order to alleviate issues associated with human factors. Specifically, we applied a stateof-the-art deep learning model called Mask-RCNN to detect and segment the bolus in videofluoroscopic image sequences. We trained the algorithm with 450 swallow videos and evaluated with an independent dataset of 50 videos. The algorithm was able to detect and segment the bolus with a mean average precision of 0.49 and an intersection of union of 0.71. The proposed method indicated robust detection results that can help to improve the speed and accuracy of a clinical decisionmaking process.

OBJECTIVE Sensing the effects of alcohol consumption in real time could offer numerous opportunities to reduce related harms. This study sought to explore accuracy of gait-related features measured by smartphone accelerometer sensors on detecting alcohol intoxication (breath alcohol concentration [BrAC] > .08%). METHOD In a controlled laboratory study, participants (N = 17; 12 male) were asked to walk 10 steps in a straight line, turn, and walk 10 steps back before drinking and each hour, for up to 7 hours after drinking a weight-based dose of alcohol to reach a BrAC of .20%. Smartphones were placed on the lumbar region and 3-axis accelerometer data was recorded at a rate of 100 Hz. Accelerometer data were segmented into task segments (i.e., walk forward, walk backward). Features were generated for each overlapping 1-second windows, and the data set was split into training and testing data sets. Logistic regression models were used to estimate accuracy for classifying BrAC ≤ .08% from BrAC > .08% for each subject. RESULTS Across participants, BrAC > .08% was predicted with a mean accuracy of 92.5% using logistic regression, an improvement from a naive model accuracy of 88.2% (mean sensitivity = .89; specificity = .92; positive predictive value = .77; and negative predictive value = .97). The two most informative accelerometer features were mean signal amplitude and variance of the signal in the x-axis (i.e., gait sway). CONCLUSIONS We found preliminary evidence supporting use of gait-related features measured by smartphone accelerometer sensors to detect alcohol intoxication. Future research should determine whether these findings replicate in situ.

Crossbar arrays are a popular solution when implementing systems that have array-like architecture. With the recent developments in the field of neuromorphic engineering, crossbars are now routinely used to implement artificial neural networks or, more generally, to perform vector–matrix multiplication in hardware. However, the interconnect resistance present in all crossbars can lead to significant deviations from the intended behaviour of these structures. In this work, we present badcrossbar—an open-source tool for computing currents and voltages in such non-ideal passive crossbar arrays. Additionally, the package allows to easily visualise currents and voltages (or other numerical variables) in the branches and on the nodes of these structures.

Cell-to-cell communication is a fundamental process in every multicellular organism. In addition to membrane-bound and released factors, the sharing of cytosolic components represents a new, poorly explored signaling route. An extraordinary example of this communication channel is the direct transport of mitochondria between cells. In this review, we discuss how intercellular mitochondrial transfer can be used by cancer cells to sustain their high metabolic requirements and promote drug resistance and describe relevant molecular players in the context of current and future cancer therapy.

Abstract Just recently, the literature has established the existence of a dark side with regard to customer orientation (CO) in terms of sales performance. However, no clear position is presented about the possible dark side of CO when it comes to B2B relational outcomes, preventing managers from knowing when to accentuate/suppress CO activities. The aim of this study is to examine the relational consequences of suppliers' CO seen through the customers' lenses, and to investigate the moderating role of perceived emotional value in a professional service relationship context. A conceptual model anchored in value and relationship marketing theories is tested on a sample of 226 professional service firms' business customers, using the PROCESS routine. The study finds that perceived CO is related to satisfaction with the relationship and with relationship performance in an inverted U-shaped form, while satisfaction is positively related to relationship performance. We show that, although preferring to receive CO from their supplier, customers might want a relationship that is not as intense/comprehensive as the one that the supplier aims to achieve. The study unfolds emotional value as a moderating mechanism that can prevent the diminishing effect of CO activities.

The predictive factors of violence between married couples or adolescents are well-known. However, less is known about the factors relating to intimate violence among college students. This study examined sociodemographic variables (age, duration of relationship, and relationship satisfaction), impulsivity, and empathy as predictors of dating violence, using data from 474 female college students from the University of Mostar, Bosnia and Herzegovina. The sample completed online the Conflict Tactics Scale 2 Short Form, the Interpersonal Reactivity Index, and the Short Impulsive Behavior Scale. The results indicated a higher prevalence of victimization than perpetration for psychological aggression. The obtained data showed that younger women and those in longer relationships, as well as those unsatisfied with their relationship, are more prone to experience psychological victimization or perpetration. Relationship satisfaction was also shown to be a predictor of physical perpetration causing injury. Impulsivity facets were found to have a differential weight in explaining dating violence. Empathy was shown to be a significant predictor of dating victimization, specifically “perspective taking” for psychological victimization and empathic concern for sexual victimization. These results suggest the need to develop specific interventions and prevention programs focused on relationship satisfaction, impulsivity, and empathy.

The network edge presses an urgent need for efficient network management and orchestration (MANO), in order to efficiently cope with the wide heterogeneity in services and resources, while providing a low-latency for the hosted services. Based on ETSI standardization, the MEC platform can be managed and orchestrated by NFV MANO components. In this demo, we show how to measure the impact of the Virtualized Infrastructure Manager (VIM), which is a component of the NFV MANO, on the performance of the MANO system. In our testbed-based experimentation, we evaluated the performance in terms of time needed for a MANO system to instantiate/terminate a network service on top of the MEC platform. Open Source MANO (OSM) and Open Baton are used as MANO entities, while for the VIM environments we investigated the impact of OpenStack and Amazon Web Services (AWS) on the above-mentioned OSM, and the impact of OpenStack and Docker on Open Baton.

By providing storage and computational resources at the network edge, which enables hosting applications closer to the mobile users, Multi-Access Edge Computing (MEC) uses the mobile backhaul, and the network core more efficiently, thereby reducing the overall latency. Fostering the synergy between 5G and MEC brings ultra-reliable low-latency in data transmission, and paves the way towards numerous latency-sensitive automotive use cases, with the ultimate goal of enabling autonomous driving. Despite the benefits of significant latency reduction, bringing MEC platforms into 5G-based vehicular networks imposes severe challenges towards poorly scalable network management, as MEC platforms usually represent a highly heterogeneous environment. Therefore, there is a strong need to perform network management and orchestration in an automated way, which, being supported by Software Defined Networking (SDN) and Network Function Virtualization (NFV), will further decrease the latency. With recent advances in SDN, along with NFV, which aim to facilitate management automation for tackling delay issues in vehicular communications, we study the closed-loop life-cycle management of network services, and map such cycle to the Management and Orchestration (MANO) systems, such as ETSI NFV MANO. In this paper, we provide a comprehensive overview of existing MANO solutions, studying their most important features to enable network service and resource orchestration in MEC-enhanced vehicular networks. Finally, using a real testbed setup, we conduct and present an extensive performance analysis of Open Baton and Open Source MANO that are, due to their lightweight resource footprint, and compliance to ETSI standards, suitable solutions for resource and service management and orchestration within the network edge.

We present a real-time feasible Nonlinear Model Predictive Control (NMPC) scheme to control a microgrid described by a detailed Differential Algebraic Equation (DAE). Our NMPC formulation allows to consider secondary voltage and frequency control, steady-state equal load sharing, economic goals and all relevant operational constraints in a single optimization problem. The challenge is to control the fast and large dynamical system in real-time. To achieve this goal, we use the recently introduced Advanced Step Real-Time Iteration (AS-RTI) scheme and its efficient implementation in the acados software package. We present an NMPC scheme which delivers feedback in the range of milliseconds. Thereby, the controller responds efficiently to large disturbances and mismatches in the predictions and effectively controls the fast transient dynamics of the microgrid. Our NMPC approach outperforms a state-of-the-art I-controller usually used in microgrid control and shows minor deviation to a fully converged NMPC approach.

Background Immune-related diarrhoea/colitis (ir-D/C) is a common adverse event of immune checkpoint inhibitor (ICI) therapy. Guidelines recommend corticosteroid (CS) treatment; however, the average treatment duration for ir-D/C remains poorly defined. Methods All advanced melanoma patients treated with ICI therapy at the Royal Marsden Hospital between 2011 and 2016 were reviewed to identify ir-D/C cases alongside clinical variables. Results 117 any-grade ir-D/C episodes occurred in 109 (21%) patients out of a total of 519 patients treated (ipilimumab=77 episodes, anti-PD1=17 (nivolumab or pembrolizumab), ipilimumab and nivolumab=23 (ipi+nivo)) (seven patients had ir-D/C more than once on different lines of treatment) and >/=grade 3 ir-D/C occurred most frequently (63/519 patients (12%) vs 29/519 (5%) grade 1, and 25/519 (5%) grade 2). Median onset (days) of all-grade ir-D/C after starting ICI therapy was 41 for ipilimumab (IQR 24 to 59, n=77), 91 for anti-PD1 (IQR 46 to 355, n=17) and 45 for ipi+nivo (IQR 24 to 67, n=23). In 71/117 (61%) patients, ir-D/C episodes were treated with CS (17% grade 2; 79% grade 3/4): 54 being steroid-responsive; 17 being steroid-refractory and received additional anti-tumor necrosis factor (TNF) treatment. Median grade 3 ir-D/C CS duration was similar across treatments, averaging 58 days. Median overall CS duration (days) was longer in the grade 3/4 D/C steroid-refractory group (94 vs 45 days). Infection developed in 11/71 (15%) CS recipients and in 6/17 (35%) anti-TNF recipients. In 65/117 (55%) patients, ir-D/C episodes were investigated with flexible sigmoidoscopy. Of these patients, 38/65 (58%) had macroscopic colitis and 12/65 (18%) had microscopic colitis. The steroid-refractory group had more macroscopic changes, 13/17 (76%), than the steroid-responsive group, 22/41 (54%). Conclusion Rates of grade 3 ir-D/C were higher than reported in clinical trials. The 58-day median duration of CS therapy for grade 3 ir-D/C places a significant number of patients at risk of complications. We demonstrate that microscopic colitis is an important subgroup, advocating biopsies in ir-D/C even with macroscopically normal bowel.

The ongoing pandemic of SARS-CoV-2 calls for rapid and cost-effective methods to accurately identify infected individuals. The vast majority of patient samples is assessed for viral RNA presence by RT-qPCR. Our biomedical research institute, in collaboration between partner hospitals and an accredited clinical diagnostic laboratory, established a diagnostic testing pipeline that has reported on more than 40,000 RT-qPCR results since its commencement at the beginning of April 2020. However, due to ongoing demand and competition for critical resources, alternative testing strategies were sought. In this work, we present a clinically-validated standard operating procedure (SOP) for high-throughput SARS- CoV-2 detection by RT-LAMP in 25 minutes that is robust, reliable, repeatable, sensitive, specific, and inexpensive.