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BACKGROUND The impact of the coronavirus disease (COVID-19) pandemic on mental health of the population is important for informing public health policy and decision-making. However, there is limited information on trends in mental health-related healthcare service utilization during the pandemic. OBJECTIVE This study aimed to describe patterns of mental health-related healthcare service utilisation and psychotropic drug dispensations in British Columbia, Canada, during the COVID-19 pandemic compared to a pre-pandemic period. We explored trajectories of use across multiple data sources to determine whether the patterns were similar or different in acute and outpatient settings, and how these patterns differed by age, sex and type of condition. METHODS We conducted a population-based study using administrative health data to capture outpatient physician visits, emergency department visits, hospital admissions, and psychotropic drug dispensations. We examined time trends of mental health-related healthcare utilisation and psychotropic drug dispensations between January 2019 and December 2021. We calculated age-standardised rates and rate ratios to compare healthcare service utilisation before and during the COVID-19 pandemic and stratified by year, sex, age and condition. RESULTS Results: In April 2020, compared to the same period in 2019, we observed a 26% and 16% decrease in acute care visits for mental health-related emergency department visits and hospital admissions, respectively. By late 2020, with the exception of emergency department visits, healthcare service utilisation recovered to pre-pandemic (2019) levels. In 2021, overall mental health-related healthcare service utilisation increased to above pre-pandemic levels, with an increase in the monthly average rate of 22% for outpatient physician visits only and not in other datasets. However, notable and statistically significant increases in healthcare utilisation were observed across all data sources among 10-14 year olds (45% in outpatient physician visits, 31% in emergency department visits, 55% in hospital admissions, and 36% in psychotropic drug dispensations), and 15-19 year olds (51% in outpatient physician visits, 19% in emergency department visits, 13% in hospital admissions, and 39% in psychotropic drug dispensations). Increases were more prominent among females than males, but there was some variation for specific mental health-related conditions. CONCLUSIONS The increase in mental health-related healthcare utilisation and psychotropic drug dispensations in 2020 and 2021 likely reflects important societal consequences of both the pandemic itself and the associated measures. Recovery efforts in British Columbia should take these findings into consideration, especially among most affected sub-populations, such as adolescents. CLINICALTRIAL Not applicable.

The focus of this review is on the phytochromes Agp1 and Agp2 of Agrobacterium fabrum. These are involved in regulation of conjugation, gene transfer into plants, and other effects. Since crystal structures of both phytochromes are known, the phytochrome system of A. fabrum provides a tool for following the entire signal transduction cascade starting from light induced conformational changes to protein interaction and the triggering of DNA transfer processes.

In this work, a predictive maintenance system is discussed as a modern solution for reducing downtimes in complex systems such as airplanes’ jet engines. The developed predictive maintenance system is based on prognostic and predictive algorithms which will be constructed by using machine learning techniques. Bayesian theorem is specially studied and employed for this purpose in this paper. The design and implementation of a Naive Bayesian classifier will be presented to demonstrate and challenge the practicality of the method. A turbofan jet engine health check system was chosen as a complex and live industrial testbed example. We also demonstrate that the system in question has a high entropy and despite this, the Bayesian approach is sufficient enough to eliminate the critical errors as well as maintain a satisfactory overall accuracy.

Dementia and stroke have been considered two major causes of disability in the UK. The field of rehabilitation robotics emerged since early 90’s as a tool to assist therapists with assessing stroke and dementia patients and providing the necessary therapy. The present article aims to offer a review of how current hard robotic devices utilized in upper and lower limb rehabilitation, and how successful they were in increasing the efficiency of the recovery process. Their bottlenecks and short comes are discussed and soft robotics are presented as alternative techniques to resolve them. Novel pneumatic Muscle Actuators (pMA) capable of bending in contrary to traditional pMA are studied here. In particular, we investigate and propose a novel exoskeleton soft robotic arm, which made of several novel pMA for elbow joint rehabilitation. For this purpose, analysis, design, integration and characterization of the proposed arm are presented and geometrical and numerical models are obtained. This study shows that how our proposed exoskeleton soft robotic arm with a lower cost can increase the efficiency of rehabilitation recovery process.

Early indication of some diseases such as Parkinson and Multiple Sclerosis often manifests with walking difficulties. Gait analysis provides vital information for assessing the walking patterns during the locomotion, especially when the outcomes are quantitative measures. This paper explores methods that can respond to the changes in the gait features during the swing stage using Kinect Camera, a low cost, marker-free, and portable device offered by Microsoft. Kinect has been exploited for tracking the skeletal positional data of body joints to assess and evaluate the gait performance. Linear kinematic gait features are extracted to discriminate between walking speeds by using five supervised modulation based machine-learning classifiers as follow: Decision Trees (DT), linear/nonlinear Support Vector Machines (SVMs), subspace discriminant and k-Nearest Neighbour (k-NN). The role of modulation techniques such as Frequency Modulation (FM) for increasing the efficiency of classifiers have been explored. The experimental results show that all five classifiers can successfully distinguish gait futures signal associated with walking patterns with high accuracy (average expected value of 86.19% with maximum of 92.9%). This validates the capability of the presented methodology in detecting key “indicators” of health events.\ud Keywords: Gait Analysis, Kinematic Gait Features, Amplitude and Frequency Modulations, Baseband Signal, Passband Mapping, Machine-Learning, Classification Technique

Human gait analysis can provide vital information especially with optical sensor to track and asses the changes in gait pattern. In this paper, the Kinect v2 based system is used for classifying a several walk speeds and Convolutional Encoder (CE) technique is validated. Positional skeletal data is collected from the lower body's joints and Amplitude Modulation (AM) is used to modify gait signal for extracting the gait features namely baseband frequency and modulation index. The obtained results show that 97.8% of the considered parameters are appropriate for classifying between three kinds of walk speeds.

We have investigated the growth and the optical properties of vertically-ordered Ge/Si self-assembled quantum dots. The quantum dots are grown by ultrahigh-vacuum chemical vapor deposition. We first investigate the morphological evolution of the islands following the overgrowth by a thin silicon film. A shape transition (domes to pyramids) is observed along with a significant flattening of the islands and a modification of the density. The vertical alignment of the islands is then investigated. We show that the vertical correlation can be monitored by the decrease of the critical thickness from layer to layer. The three different regimes governing the correlation between the islands are analyzed in terms of the shape transition of the islands. The density of states in the Ge/Si quantum dots is finally investigated. A strong dependence of the photoluminescence of the dots is observed as a function of the excitation power density. This dependence is interpreted in terms of state filling and recombination from the confined excited hole states in the dots. The photoluminescence data are correlated to the density of states as calculated by solving the three-dimensional (3-D) Schrodinger equation in these islands with a lateral size of the order of 100 nm.

We have investigated near-infrared p-i-n photodetectors with Ge/Si self-assembled quantum dots. The self-assembled quantum dots were grown by chemical vapor deposition on Si(001). A vertical stacking of 20 layers of quantum dots was inserted into a near-infrared waveguide obtained with a Si0.98Ge0.02 alloy. The samples were processed into ridge waveguides. The photoresponse of the device covers the near-infrared spectral range up to 1.5 μm. At room temperature, a responsivity of 210 mA/W is measured at 1.3 μm and 3 mA/W at 1.5 μm. The photocurrent is compared to the photoluminescence and to the absorption of the quantum dots measured in the waveguide geometry. At room temperature, the onset of the absorption is around 1.9 μm (0.65 eV). The photocurrent is blueshifted as compared to the absorption.

A model is proposed for the respiratory adaptation to falling oxygen concentration during growth of the microaerophilic bacterium Campylobacter mucosalis. During the early stages of growth, the oxidation of formate is a two-stage branched process involving the production of H2O2 followed by its peroxidatic removal. In later stages of growth, at lower oxygen concentrations, the predominant electron flow is linear to a membrane-bound cytochrome-c oxidase which reduces O2 directly to H2O. Several components of this model have been investigated. H2O2 was produced during formate oxidation and accumulated when electron transfer to the cytochrome-c peroxidase was inhibited. A cytochrome c-553, of the Class 1 type, was purified and shown to be the specific electron donor to both the peroxidase and the membrane-bound oxidase. The levels of this cytochrome c and of the peroxidase were higher in cells harvested early in growth. In later stages of growth, the activity of the membrane-bound oxidase increased. Proton pumping across the membrane was detected with either H2O2 or oxygen as terminal electron acceptor. The novel energy-conserving role of H2O2 in this catalase-negative bacterium is discussed in relation to its microaerophilic nature.

Campylobacter sputorum subspecies mucosalis, the causative organism of porcine intestinal adenomatosis, will grow microaerophillically in the presence of hydrogen as an electron donor, and under these conditions contains a high complement of c-type cytochromes. The cytochromes c in a crude extract of the organism were examined by redox potentiometry. The redox potentiometric data were consistent with the presence of at least two low midpoint potential and two high midpoint potential cytochromes c. Furthermore the prediction could be made that one of the high midpoint potential cytochromes contains an asymmetric α-peak. A high midpoint potential cytochrome c was isolated and then characterized with respect to its spectrum, midpoint potential, amino acid composition and N-terminal sequence. The pure cytochrome was shown to exhibit a midpoint potential close to that predicted from titration of the crude preparations and to possess a markedly asymmetric α-peak. The cytochrome exhibits similarities to a number of high midpoint potential low spin cytochromes c and has been compared to these. Partial isolation and characterization of three low midpoint potential low spin cytochromes c was possible. These cytochromes (the cytochromes c552) show no similarity to other low potential cytochromes c reported in the literature with respect to spectrum and molecular weights and are apparently unique to the organism. The presence of both low midpoint and high midpoint potential cytochromes c has so far been reported for only a few organisms, including members of the genus Campylobacter. In the light of the redox potentiometric data, the electron transport chain of Campylobacter sputorum subspecies mucosalis has been compared to those of other well studied organisms.

We have investigated the interband and the intraband absorption properties of Ge/Si self-assembled islands. The investigated structure consists of a p–i–n junction containing Ge/Si self-assembled islands embedded in a Si 0.98 Ge 0.02 waveguiding layer. The variation of transmission associated with carrier injection under forward bias is monitored both in the near-infrared and in the mid-infrared spectral ranges. We show that the carrier injection leads to an absorption resonant at 185 meV which is polarized along the growth axis of the islands. This transition corresponds to an intraband optical transition from the island ground states to the two-dimensional wetting layer states. This assignment is supported by a two-dimensional band structure calculation performed in a 14 band k · p formalism. Meanwhile, the carrier injection leads to a bleaching of the interband absorption. We show that this electroabsorption spectroscopy is a useful tool for the study of self-assembled islands that is complementary of standard photoluminescence, electroluminescence or absorption spectroscopies.

The quality of life and cost of care for elderly people varies dramatically between those living independently and those receiving acute or long-term care, which takes place at home, in residential care or in hospital. The common aim of national health service providers is to keep elderly people safe at their own homes for as long as possible to promote independent living, increase their quality of life and reduce hospital costs. Hence, the application of autonomous sensing systems to enhance everyday life of such population will be valuable and has been considered here. \ud Recently, Microsoft Kinect v2 has been used for gait analysis systems, to perform data classification of gait pattern changes based on walking speeds. This system enables the tracking without the need of any markers. Moreover, the Kinect camera is considered a low-cost device, and is quick to install, even in an unprepared environment. However, the primary challenge of such a device is that it provides a low data rate which leads to a decrease in the quality of extracted features, compared to other Motion Capture Systems (MoCap). Furthermore, in the data classification stage, the performance of classification is greatly affected by the boundary between different classes which is called decision boundary. This raises other questions such as: how to weight the features from the class labels, and which kind of similarity metric can be used. \ud To improve the quality of features, the Amplitude Modulation (AM) and Convolutional Encoder (CE) can play a major role in detection and in ranking the gait pattern changes based on walking speed. For this purpose, the collected data is mapped into a higher frequency spectrum using the AM domain. Consequently, the “AM-modified gait signal” is produced to improve the quality of extracted gait features, by increasing the level of the frequency sampling rate. \ud In this research, the main novelty is the combination of Amplitude Modulation (AM) and Convolutional Encoder (CE) techniques in one system (AM/CE) in order to understand and identify the walking speed effects on gait parameters. The former is proposed to extract new gait features without the need to determine the gait cycle phases, while the latter is developed to classify gait data based on walking speeds. Therefore, the performance of the CE technique is improved efficiently in gait data classification by weighting the bit positions in \ud xv \ud \ud Hamming Distance (HD) length, which leads to an increase in the accuracy of measurement of the similarity metric.