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A new side to side movement dipstick along with reverse transcribing recombinase polymerase amplification pertaining to fast and also aesthetic diagnosis in the BVDV and BPIV3.
As research in smart homes and activity recognition is increasing, it is of ever increasing importance to have benchmarks systems and data upon which researchers can compare methods. While synthetic data can be useful for certain method developments, real data sets that are open and shared are equally as important. This paper presents the E-care@home system, its installation in a real home setting, and a series of data sets that were collected using the E-care@home system. Our first contribution, the E-care@home system, is a collection of software modules for data collection, labeling, and various reasoning tasks such as activity recognition, person counting, and configuration planning. It supports a heterogeneous set of sensors that can be extended easily and connects collected sensor data to higher-level Artificial Intelligence (AI) reasoning modules. Our second contribution is a series of open data sets which can be used to recognize activities of daily living. NSC-2260804 In addition to these data sets, we describe the technical infrastructure that we have developed to collect the data and the physical environment. Each data set is annotated with ground-truth information, making it relevant for researchers interested in benchmarking different algorithms for activity recognition.Adhesive capsulitis (AC) is a glenohumeral (GH) joint condition, characterized by decreased GH joint range of motion (ROM) and compensatory ROM in the elbow and scapulothoracic (ST) joint. To evaluate AC progression in clinical settings, objective movement analysis by available systems would be valuable. This study aimed to assess within-session and intra- and inter-operator reliability/agreement of such a motion capture system. The MVN-Awinda® system from Xsens Technologies (Enschede, The Netherlands) was used to assess ST, GH, and elbow ROM during four tasks (GH external rotation, combing hair, grasping a seatbelt, placing a cup on a shelf) in 10 AC patients (mean age = 54 (± 6), 7 females), on two test occasions (accompanied by different operators on second occasion). Standard error of measurements (SEMs) were below 1.5° for ST pro-retraction and 4.6° for GH in-external rotation during GH external rotation; below 6.6° for ST tilt, 6.4° for GH flexion-extension, 7.1° for elbow flexion-extension during combing hair; below 4.4° for GH ab-adduction, 13° for GH in-external rotation, 6.8° for elbow flexion-extension during grasping the seatbelt; below 11° for all ST and GH joint rotations during placing a cup on a shelf. Therefore, to evaluate AC progression, inertial sensors systems can be applied during the execution of functional tasks.Rigidity is one of the cardinal symptoms of Parkinson´s disease (PD). Present in up 89% of cases, it is typically assessed with clinical scales. However, these instruments show limitations due to their subjectivity and poor intra- and inter-rater reliability. To compile all of the objective quantitative methods used to assess rigidity in PD and to study their validity and reliability, a systematic review was conducted using the Web of Science, PubMed, and Scopus databases. Studies from January 1975 to June 2019 were included, all of which were written in English. The Strengthening the Reporting of observational studies in Epidemiology Statement (STROBE) checklist for observational studies was used to assess the methodological rigor of the included studies. Thirty-six studies were included. Rigidity was quantitatively assessed in three ways, using servomotors, inertial sensors, and biomechanical and neurophysiological study of muscles. All methods showed good validity and reliability, good correlation with clinical scales, and were useful for detecting rigidity and studying its evolution. People with PD exhibit higher values in terms of objective muscle stiffness than healthy controls. Rigidity depends on the angular velocity and articular amplitude of the mobilization applied. There are objective, valid, and reliable methods that can be used to quantitatively assess rigidity in people with PD.To effectively find the direction of non-circular signals received by a uniform linear array (ULA) in the presence of non-negligible perturbations between array elements, i.e., mutual coupling, in colored noise, a direction of arrival (DOA) estimation approach in the context of high order statistics is proposed in this correspondence. Exploiting the non-circularity hidden behind a certain class of wireless communication signals to build up an augmented cumulant matrix, and carrying out a reformulation of the distorted steering vector to extract the angular information from the unknown mutual coupling, by exploiting the characteristic of mutual coupling, i.e., a limited operating range and an inverse relation of coupling effects to interspace, we develop a MUSIC-like estimator based on the rank-reduction (RARE) technique to directly determine directions of incident signals without mutual coupling compensation. Besides, we provide a solution to the problem of coherency between signals and mutual coupling between sensors co-existing, by selecting a middle sub-array to mitigate the undesirable effects and exploiting the rotation-invariant property to blindly separate the coherent signals into different groups to enhance the degrees of freedom. Compared with the existing robust DOA methods to the unknown mutual coupling under the framework of fourth-order cumulants (FOC), our work takes advantage of the larger virtual array and is able to resolve more signals due to greater degrees of freedom. Additionally, as the effective aperture is virtually extended, the developed estimator can achieve better performance under scenarios with high degree of mutual coupling between two sensors. Simulation results demonstrate the validity and efficiency of the proposed method.This paper proposes an efficient and practical implementation of the Maximum Likelihood Ensemble Filter via a Modified Cholesky decomposition (MLEF-MC). link2 The method works as follows via an ensemble of model realizations, a well-conditioned and full-rank square-root approximation of the background error covariance matrix is obtained. This square-root approximation serves as a control space onto which analysis increments can be computed. These are calculated via Line-Search (LS) optimization. link3 We theoretically prove the convergence of the MLEF-MC. Experimental simulations were performed using an Atmospheric General Circulation Model (AT-GCM) and a highly nonlinear observation operator. The results reveal that the proposed method can obtain posterior error estimates within reasonable accuracies in terms of ℓ - 2 error norms. Furthermore, our analysis estimates are similar to those of the MLEF with large ensemble sizes and full observational networks.In this paper we tackle the problem of indoor robot localization by using a vision-based approach. Specifically, we propose a visual odometer able to give back the relative pose of an omnidirectional automatic guided vehicle (AGV) that moves inside an indoor industrial environment. A monocular downward-looking camera having the optical axis nearly perpendicular to the ground floor, is used for collecting floor images. After a preliminary analysis of images aimed at detecting robust point features (keypoints) takes place, specific descriptors associated to the keypoints enable to match the detected points to their consecutive frames. A robust correspondence feature filter based on statistical and geometrical information is devised for rejecting those incorrect matchings, thus delivering better pose estimations. A camera pose compensation is further introduced for ensuring better positioning accuracy. The effectiveness of proposed methodology has been proven through several experiments, in laboratory as well as in an industrial setting. Both quantitative and qualitative evaluations have been made. Outcomes have shown that the method provides a final positioning percentage error of 0.21% on an average distance of 17.2 m. A longer run in an industrial context has provided comparable results (a percentage error of 0.94% after about 80 m). The average relative positioning error is about 3%, which is still in good agreement with current state of the art.To explore Auricularia auricula-judae polysaccharides (AAP) as natural anticoagulants for application in the functional food industry, ultrasound assisted extraction (UAE) was optimized for the extraction of AAP by using a response surface methodology (RSM). The maximum extraction yield of crude AAP (14.74 mg/g) was obtained at the optimized extraction parameters as follows Extraction temperature (74 °C), extraction time (27 min), the ratio of liquid to raw material (103 mL/g), and ultrasound power (198 W). Furthermore, the acidic AAP (aAAP) was precipitated with cetyltrimethylammonium bromide (CTAB) from crude AAP (cAAP). aAAP was further purified using ion exchange chromatography with a DEAE Purose 6 Fast Flow column to obtain aAAP-1. Additionally, according to the HPLC analysis, the aAAP-1 was mainly composed of mannose, glucuronic acid, glucose, galactose, and xylose, with a molar ratio of 80.639.882.25131.13. Moreover, the results of the activated partial thromboplastin time (APTT), prothrombin time (PT), and thrombin time (TT) indicated aAAP-1 had anticoagulant activity, which was a synergic anticoagulant activity by the endogenous and exogenous pathway.Legionella pneumophila is a facultative intracellular pathogen found in aquatic environments as planktonic cells within biofilms and as intracellular parasites of free-living amoebae such as Acanthamoeba castellanii. This pathogen bypasses the elimination mechanism to replicate within amoebae; however, not all amoeba species support the growth of L. pneumophila. Willaertia magna C2c Maky, a non-pathogenic amoeba, was previously demonstrated to possess the ability to eliminate the L. pneumophila strain Paris. Here, we study the intracellular behaviour of three L. pneumophila strains (Paris, Philadelphia, and Lens) within W. magna C2c Maky and compare this strain to A. castellanii and W. magna Z503, which are used as controls. We observe the intracellular growth of strain Lens within W. magna Z503 and A. castellanii at 22 °C and 37 °C. Strain Paris grows within A. castellanii at any temperature, while it only grows at 22 °C within W. magna Z503. Strain Philadelphia proliferates only within A. castellanii at 37 °C. Within W. magna C2c Maky, none of the three legionella strains exhibit intracellular growth. Additionally, the ability of W. magna C2c Maky to decrease the number of internalized L. pneumophila is confirmed. These results support the idea that W. magna C2c Maky possesses unique behaviour in regard to L. pneumophila strains.Biodegradation is one of the most effective and profitable methods for the elimination of toxic polychlorinated biphenyls (PCBs) and total petroleum hydrocarbons (TPH) from the environment. In this study, aerobic degradation of the mentioned pollutants by bacterial strains Mycolicibacterium frederiksbergense IN53, Rhodococcus erythropolis IN129, and Rhodococcus sp. IN306 and mixed culture M1 developed based on those strains at 111 ratio was analyzed. The effectiveness of individual strains and of the mixed culture was assessed based on carried out respirometric tests and chromatographic analyses. The Rhodococcus sp. IN306 turned out most effective in terms of 18 PCB congeners biodegradation (54.4%). The biodegradation index was decreasing with an increasing number of chlorine atoms in a molecule. Instead, the Mycolicobacterium frederiksbergense IN53 was the best TPH degrader (37.2%). In a sterile soil, contaminated with PCBs and TPH, the highest biodegradation effectiveness was obtained using inoculation with mixed culture M1, which allowed to reduce both the PCBs (51.
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