Duelundpoole2679

Our experimental results on the modified MPIIGaze dataset demonstrate that the proposed approach achieves an average performance improvement of 4.53%-8.9% under low and dark light conditions, which is a promising step toward further research.Atopic dermatitis (AD) is a complex, often lifelong allergic disease with severe pruritus affecting around 10% of both humans and dogs. To investigate the role of mast cells (MCs) and MC-specific proteases on the immunopathogenesis of AD, a vitamin D3-analog (MC903) was used to induce clinical AD-like symptoms in c-kit-dependent MC-deficient Wsh-/- and the MC protease-deficient mMCP-4-/-, mMCP-6-/-, and CPA3-/- mouse strains. MC903-treatment on the ear lobe increased clinical scores and ear-thickening, along with increased MC and granulocyte infiltration and activity, as well as increased levels of interleukin 33 (IL-33) locally and thymic stromal lymphopoietin (TSLP) both locally and systemically. The MC-deficient Wsh-/- mice showed significantly increased clinical score and ear thickening albeit having lower ear tissue levels of IL-33 and TSLP as well as lower serum levels of TSLP as compared to the WT mice. In contrast, although having significantly increased IL-33 ear tissue levels the chymase-deficient mMCP-4-/- mice showed similar clinical score, ear thickening, and TSLP levels in ear tissue and serum as the WT mice, whereas mMCP-6 and CPA3 -deficient mice showed a slightly reduced ear thickening and granulocyte infiltration. Our results suggest that MCs promote and control the level of MC903-induced AD-like inflammation.Axle-box bearings are one of the most critical mechanical components of the high-speed train. Vibration signals collected from axle-box bearings are usually nonlinear and nonstationary, caused by the complicated operating conditions. Due to the high reliability and real-time requirement of axle-box bearing fault diagnosis for high-speed trains, the accuracy and efficiency of the bearing fault diagnosis method based on deep learning needs to be enhanced. To identify the axle-box bearing fault accurately and quickly, a novel approach is proposed in this paper using a simplified shallow information fusion-convolutional neural network (SSIF-CNN). Firstly, the time domain and frequency domain features were extracted from the training samples and testing samples before been inputted into the SSIF-CNN model. Secondly, the feature maps obtained from each hidden layer were transformed into a corresponding feature sequence by the global convolution operation. EHT1864 Finally, those feature sequences obtained from different layers were concatenated into one-dimensional as the fully connected layer to achieve the fault identification task. The experimental results showed that the SSIF-CNN effectively compressed the training time and improved the fault diagnosis accuracy compared with a general CNN.The composition of the extracellular matrix (ECM) plays a pivotal role in tumour initiation, metastasis and therapy resistance. Until now, the ECM composition of salivary gland carcinomas (SGC) has not been studied. We quantitatively analysed the mRNA of 28 ECM-related genes of 34 adenoid cystic (AdCy; n = 11), mucoepidermoid (MuEp; n = 14) and salivary duct carcinomas (SaDu; n = 9). An incremental overexpression of six collagens (including COL11A1) and four glycoproteins from MuEp and SaDu suggested a common ECM alteration. Conversely, AdCy and MuEp displayed a distinct overexpression of COL27A1 and LAMB3, respectively. Nonhierarchical clustering and principal component analysis revealed a more specific pattern for AdCy with low expression of the common gene signature. In situ studies at the RNA and protein level confirmed these results and indicated that, in contrast to MuEp and SaDu, ECM production in AdCy results from tumour cells and not from cancer-associated fibroblasts (CAFs). Our findings reveal different modes of ECM production leading to common and distinct RNA signatures in SGC. Of note, an overexpression of COL27A1, as in AdCy, has not been linked to any other neoplasm so far. Here, we contribute to the dissection of the ECM composition in SGC and identified a panel of deferentially expressed genes, which could be putative targets for SGC therapy and overcoming therapeutic resistance.The ecology of large, wide-ranging carnivores appears to make them vulnerable to conservation challenges in the wild and welfare challenges in captivity. This poses an ethical dilemma for the zoo community and supports the case that there is a need to reconsider prevailing management paradigms for these species in captivity. Whilst the welfare challenges wide ranging carnivores face have been attributed to reduced ranging opportunities associated with the decreased size of captive habitats, attempts to augment wild carnivore welfare in captivity typically focus on behaviours linked to hunting. Thus far, this has yet to result in the systematic elimination of signs of compromised welfare amongst captive carnivores. Here an assessment is carried out to identify the likely welfare priorities for Amur tigers, which, as one of the widest ranging terrestrial carnivores, serves as an excellent exemplar for species experiencing extreme compression of their ranging opportunities in captivity. These priorities are then used to consider novel strategies to address the welfare challenges associated with existing management paradigms, and in particular, attempt to overcome the issue of restricted space. The insights generated here have wider implications for other species experiencing substantive habitat compression in captivity. It is proposed here that the impact of habitat compression on captive carnivore welfare may not be a consequence of the reduction in habitat size per se, but rather the reduction in cognitive opportunities that likely covary with size, and that this should inform strategies to augment welfare.The benefits of automatic identification technologies in healthcare have been largely recognized. Nevertheless, unlocking their potential to support the most knowledge-intensive medical tasks requires to go beyond mere item identification. link2 This paper presents an innovative Decision Support System (DSS), based on a semantic enhancement of Near Field Communication (NFC) standard. Annotated descriptions of medications and patient's case history are stored in NFC transponders and used to help caregivers providing the right therapy. The proposed framework includes a lightweight reasoning engine to infer possible incompatibilities in treatment, suggesting substitute therapies. A working prototype is presented in a rheumatology case study and preliminary performance tests are reported. The approach is independent from back-end infrastructures. The proposed DSS framework is validated in a limited but realistic case study, and performance evaluation of the prototype supports its practical feasibility. Automated reasoning on knowledge fragments extracted via NFC enables effective decision support not only in hospital centers, but also in pervasive IoT-based healthcare contexts such as first aid, ambulance transport, rehabilitation facilities and home care.

It is believed that oral infections can increase the risk of systematic diseases, such as atherosclerosis and coronary heart disease, stroke, chronic obstructive pulmonary disease, diabetes, cancer, rheumatoid arthritis, etc. It seems that oral invasive pathogens induce a systemic inflammatory response via mediators released by the cardiovascular system and liver, which increases the risk to the patient of these systematic infections, such as hypertension. On the basis of previous studies of the stomatognathic system, investigating the coexistence of systemic diseases and inflammation in the oral cavity, it can be expected that there is a connection between inflammation of the denture-bearing area in patients using acrylic removable dentures and the presence of systemic diseases, and that patients with inflammation in oral mucosa are more likely to have systemic diseases.

A retrospective study was carried out on a group of patients seeking prosthetic treatment at the Prosthetic Department of the University Dental Clinic (UKS) from March 2012 to February 2013. link3 All data were collected using a UKS electronic database with KS-SOMED. The minimum period of use for removable prostheses was five years.

According to anamnesis, the most common systemic diseases in our study group were hypertension disease. In total, 58% of patients with hypertension disease had no inflammation in the oral cavity.

The occurrence of systemic diseases in edentulous people using removable prosthetic restorations, and the subsequent use of medications for these diseases, may result in a lack of clinical symptoms of concomitant fungal infection of the oral mucosa.

The occurrence of systemic diseases in edentulous people using removable prosthetic restorations, and the subsequent use of medications for these diseases, may result in a lack of clinical symptoms of concomitant fungal infection of the oral mucosa.Recent developments in cloud computing allow data to be securely shared between users. This can be used to improve the quality of life of patients and medical staff in the Internet of Medical Things (IoMT) environment. However, in the IoMT cloud environment, there are various security threats to the patient's medical data. As a result, security features such as encryption of collected data and access control by legitimate users are essential. Many studies have been conducted on access control techniques using ciphertext-policy attribute-based encryption (CP-ABE), a form of attribute-based encryption, among various security technologies and studies are underway to apply them to the medical field. However, several problems persist. First, as the secret key does not identify the user, the user may maliciously distribute the secret key and such users cannot be tracked. Second, Attribute-Based Encryption (ABE) increases the size of the ciphertext depending on the number of attributes specified. This wastes cloud senvironment.This paper describes the design and the performance of simultaneous, multifrequency impedance measurement system for four inductive-loop (IL) sensors which have been developed for vehicle parameters measurement based on vehicle magnetic profile (VMP) analysis. Simultaneous impedance measurement on several excitation frequencies increases the VMP measurement reliability because typical electromagnetic interferences (EMI) are narrowband, and should not simultaneously affect, in the same way, all measurement bands that are spread in the frequency, i.e., it is expected that at least one measurement band is disturbance-free. The system consists of two standard and two slim IL sensors, specially designed and installed, the analogue front-end, and an industrial computer with digital-to-analogue and analogue-to-digital converters accessed via field-programmable gate array (FPGA). The impedance of the IL sensors is obtained by vector measurement of voltages from auto-balancing bridge (ABB) front-end. Complex voltages are demodulated from excitation frequencies with FIR filters designed with the flat-top windows. The system is capable of delivering VMPs in real-time mode, and also storing voltages for off-line postprocessing and analysis. Field distributions and sensitivities of slim and standard IL sensors are also discussed. Field test confirmed assumed increased reliability of VMP measurement for proposed simultaneous multifrequency operational mode.