Faberbowman1103

Deep network in network (DNIN) model is an efficient instance and an important extension of the convolutional neural network (CNN) consisting of alternating convolutional layers and pooling layers. In this model, a multilayer perceptron (MLP), a nonlinear function, is exploited to replace the linear filter for convolution. Increasing the depth of DNIN can also help improve classification accuracy while its formation becomes more difficult, learning time gets slower, and accuracy becomes saturated and then degrades. This paper presents a new deep residual network in network (DrNIN) model that represents a deeper model of DNIN. This model represents an interesting architecture for on-chip implementations on FPGAs. In fact, it can be applied to a variety of image recognition applications. This model has a homogeneous and multilength architecture with the hyperparameter "L" ("L" defines the model length). In this paper, we will apply the residual learning framework to DNIN and we will explicitly reformulate convolutional layers as residual learning functions to solve the vanishing gradient problem and facilitate and speed up the learning process. We will provide a comprehensive study showing that DrNIN models can gain accuracy from a significantly increased depth. On the CIFAR-10 dataset, we evaluate the proposed models with a depth of up to L = 5 DrMLPconv layers, 1.66x deeper than DNIN. The experimental results demonstrate the efficiency of the proposed method and its role in providing the model with a greater capacity to represent features and thus leading to better recognition performance.In the research of motor imagery brain-computer interface (MI-BCI), traditional electroencephalogram (EEG) signal recognition algorithms appear to be inefficient in extracting EEG signal features and improving classification accuracy. In this paper, we discuss a solution to this problem based on a novel step-by-step method of feature extraction and pattern classification for multiclass MI-EEG signals. First, the training data from all subjects is merged and enlarged through autoencoder to meet the need for massive amounts of data while reducing the bad effect on signal recognition because of randomness, instability, and individual variability of EEG data. Second, an end-to-end sharing structure with attention-based time-incremental shallow convolution neural network is proposed. Shallow convolution neural network (SCNN) and bidirectional long short-term memory (BiLSTM) network are used to extract frequency-spatial domain features and time-series features of EEG signals, respectively. Then, the attention model is introduced into the feature fusion layer to dynamically weight these extracted temporal-frequency-spatial domain features, which greatly contributes to the reduction of feature redundancy and the improvement of classification accuracy. At last, validation tests using BCI Competition IV 2a data sets show that classification accuracy and kappa coefficient have reached 82.7 ± 5.57% and 0.78 ± 0.074, which can strongly prove its advantages in improving classification accuracy and reducing individual difference among different subjects from the same network.To investigate the influences of heterogeneity and waning immunity on measles transmission, we formulate a network model with periodic transmission rate, and theoretically examine the threshold dynamics. We numerically find that the waning of immunity can lead to an increase in the basic reproduction number R 0 and the density of infected individuals. Moreover, there exists a critical level for average degree above which R 0 increases quicker in the scale-free network than in the random network. To design the effective control strategies for the subpopulations with different activities, we examine the optimal control problem of the heterogeneous model. Numerical studies suggest us no matter what the network is, we should implement control measures as soon as possible once the outbreak takes off, and particularly, the subpopulation with high connectivity should require high intensity of interventions. However, with delayed initiation of controls, relatively strong control measures should be given to groups with medium degrees. Furthermore, the allocation of costs (or resources) should coincide with their contact patterns.Iliopsoas abscess (IPA) is uncommon condition in children, diagnosis might be delayed because of nonspecific signs and symptoms. Only few patients have classical clinical triad at presentation in the form of fever, back pain, and inguinal pain at hip flexion. The diagnosis most likely to be reached in the first time by the use of abdominal computed tomography (CT) scan. We present a Saudi child with nonspecific signs and symptoms of fever, flank pain, and limping who was diagnosed as IPA by abdominal ultrasound and CT scan. The case was managed with intravenous antibiotics along with transcutaneous abscess drainage.Multivalvular destruction may be a clinical manifestation of infective endocarditis (IE), which is a devastating infection of the heart either alone or superimposed with congenital subaortic membrane as in this case report. Here, we report a case of multivavular destruction with severe vegetation presented as a manifestation of infective endocarditis (IE) in a neglected case of 18-year-old male with previous rheumatic heart disease. Transesophageal echocardiography is an important imaging modality for diagnosis of superimposed aortic and heart lesions. Early necessary investigation and correct diagnosis is mandatory to prevent bad complications.Heparin-induced thrombocytopenia (HIT) is an immune-mediated condition causing thrombocytopenia and paradoxical thrombosis after exposure to heparin or low-molecular-weight heparin. It has been rarely reported by Fondaparinux, an artificial pentasaccharide similar to heparin. This manuscript presents a case of HIT associated with fondaparinux use.Due to their chemical properties, accidental or suicidal ingestion of batteries into the digestive system can cause fatal complications; Treatment should not be delayed and close monitoring is required. A 26-year-old male patient is treated by the psychiatry department with diagnoses of antisocial personality disorder and depressive adjustment disorder. He consulted with the complaint of ingesting cylindrical AA battery for suicidal purpose. In our case, the cylindrical AA battery in the duodenum was removed from the rectum at the end of the third day without any complications. However, the continuous movement of the cylindrical AA battery with lactulose treatment in the gastrointestinal tract and the support of this movement with abdominal radiographs can reduce the risk of fatal complications. When planning the battery treatment in the gastrointestinal tract, the location of the battery and whether it is mobile should be determined. While obstruction of oesophagus by batteries requires emergency surgical treatment, batteries that remained fixed in the stomach for longer than 48 hours need to be treated with surgical or endoscopic methods.The coronavirus disease 2019 (COVID-19) pandemic may further promote the development of Industry 4.0 leading to the fifth industrial revolution (Society 5.0). Industry 4.0 technology such as Big Data (BD) and Artificial Intelligence (AI) may lead to a personalized system of healthcare in Pakistan. The final bridge between humans and machines is Society 5.0, also known as the super-smart society that employs AI in healthcare manufacturing and logistics. In this communication, we review various Industry 4.0 and Society 5.0 technologies including robotics and AI being inspected to control the rate of transmission of COVID-19 globally. We demonstrate the applicability of advanced information technologies including AI, BD, and Information of Technology (IoT) to healthcare. Lastly, we discuss the evolution of Industry 4.0 to Society 5.0 given the impact of the COVID-19 pandemic in accordance with the technological strategies being considered and employed.The COVID-19 pandemic has highlighted the important role of telemedicine as a tool for safe healthcare delivery across the world. While its use was more common in the developed world, the developing world has also adopted this strategy. It is important to develop a clear process and contextual guidance for effective use of this strategy for better patient-doctor interaction and its role in teaching/learning of trainees.In order to investigate the current status of skin cancer research output in Pakistan, International (PubMed) and national (PakMediNet) scientific databases were searched using variety of keywords to retrieve relevant publications. A strict inclusion criterion was applied to select skin cancer publications for final analyses. Data were recorded by two authors and consistent data were entered into SPSS and Microsoft Excel and analyzed for annual growth rate and frequencies. Of 116 articles that were finally included in the study, 74 were original articles, 24 were case-reports, 10 were review articles, three were editorials, two were research communications and one each of case-series, correspondence and response to letter to the editor. The first article on skin cancer from Pakistan was published in 1976 whereas the last article included in our study was published in December 2018. Excluding Karachi, most of the cities have no contribution in the field of skin cancer. Since 1976 to date, the average number of publications per year has been low, with only 2.7 publications per year. Skin cancer research is alarmingly scarce in Pakistan. This calls for immediate attention by all concerned to contribute and devise appropriate measures towards skin cancer research in Pakistan.

1) To explore the possible impact of the pandemic on the health seeking behavior of the patients, 2) To explore the relation of socio-demographics on the utility of health-care facilities.

This cross-sectional study was conducted by enrolling all patients ≥15 years of age presenting to the Out-Patient-Department of three main public-hospitals after obtaining ethical committee approval. A questionnaire with validated Urdu translation was filled by each participant that included socio-demographic data, pre-Covid and Covid-19 era health seeking behaviors and the impact of the pandemic on the utilization of healthcare facilities. Data was analyzed using SPSS V.19.

A total of 393 patients were enrolled with a male preponderance (72%) and a median age range of 31-45 years. Fifty-eight percent of the study population was unemployed and 47.3% were seeking follow up care. The frequency of ER and multiple (>4 times) OPD visits were significantly decreased in the Covid-19 times whereas, the laboratory and radiology services were largely unaffected. A significant number of patients were not satisfied with the current healthcare facilities that was seen irrespective of the socio-demographic status. Emergency Room and radiology services were largely unaffected whereas, elective procedures and laboratory facilities were reported to be severely affected or delayed in relation to socio-demographic variables.

Healthcare inequalities have widened and depression has shown a sharp rise during this pandemic. Defactinib The over-burdened healthcare facilities at the verge of collapse may miss out on the chronic non-Covid patients which would ultimately lead to increased morbidity and mortality.

Healthcare inequalities have widened and depression has shown a sharp rise during this pandemic. The over-burdened healthcare facilities at the verge of collapse may miss out on the chronic non-Covid patients which would ultimately lead to increased morbidity and mortality.