Reptiles, especially turtles, are becoming increasingly popular as pets. The haematological evaluation of turtles is an irreplaceable diagnostic tool in veterinary practice. However, the morphologic distinctiveness of turtle blood limits the use of electronic cell-counting devices, making time-consuming, manual counting techniques and evaluation of blood smears necessary. Many samples are dispatched to a laboratory over long distances, where a delay of 24 h or more may occur. At weekends, this interval may exceed 48 h. The objective of the present study was to determine the effect of storage duration at refrigerator temperature (4 °C) on the counts of red blood cells (RBC) and white blood cells (WBC), and on the mean corpuscular volume (MCV) and packed cell volume (PCV) in blood samples from healthy adult red-eared sliders. Blood samples were collected by venipuncture from the occipital venous sinus from six apparently healthy adult red-eared sliders, aged 2 to 4 years. Blood samples were analysed immediately after sampling to obtain the baseline value (BV) of the red blood cell count, white blood cell count and packed cell volume percentage. Blood was stored at 4 °C and the haematological analyses were performed after 24h, 48h and 72h. The results showed the same level of stability for RBC and WBC count, and MCV values during 72 hours of storage at 4 °C and for PCV during 48 hours. Handling of blood samples, and duration of storage of the blood samples can significantly influence the results/values of haematological tests. Consequently, the obtained values of the determined haematological parameters of improperly stored or handled blood samples can give a misleading interpretation of the results on the animal’s health status.

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.

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.

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.

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.

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.

BACKGROUND Stroke volume response during stress is a major determinant of functional status in heart failure and can be measured by two-dimensional (2-D) volumetric stress echocardiography (SE). The present study hypothesis is that SE may identify mechanisms underlying the change in stroke volume by measuring preload reserve through end-diastolic volume (EDV) and left ventricular contractile reserve (LVCR) with systolic blood pressure and end-systolic volume (ESV). METHODS We enrolled 4,735 patients (age 63.6 ± 11.3 yrs, 2800 male) referred to SE for known or suspected coronary artery disease (CAD) and/or heart failure (HF) in 21 SE laboratories in 8 countries. In addition to regional wall motion abnormalities (RWMA), force was measured at rest and peak stress as the ratio of systolic blood pressure by cuff sphygmomanometer/ESV by 2D with Simpson's or linear method. Abnormal values of LVCR (peak/rest) based on force were ≤1.10 for dipyridamole (n=1,992 patients) and adenosine (n=18); ≤2.0 for exercise (n=2,087) or dobutamine (n=638). RESULTS Force-based LVCR was obtained in all 4,735 pts. Lack of stroke volume increase during stress was due to either abnormal LVCR and/or blunted preload reserve, and 57 % of patients with abnormal LVCR nevertheless showed increase in stroke volume. CONCLUSIONS Volumetric SE is highly feasible with all stresses, and more frequently impaired in presence of ischemic RWMA, absence of viability and reduced coronary flow velocity reserve. It identifies an altered stroke volume response due to reduced preload and/or contractile reserve.

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.

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.

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.

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.