Interferon-γ Level in Patients with Atopic Dermatitis

Atopic Dermatitis is an itchy, inflammatory skin condition with a predilection for the skin flexures. Studies have found the expression of IL-4 and decreased IFN-γ expression was more pronounced in allergen-specific T cells stimulated by various allergens. A comparative descriptive study cover 21 case of AD and 16 control individuals. The mean level of INF-γ was higher among the control than the cases of AD but there was no significant difference between the mean INF-γ level (P = 0.261). There was no significant difference in age between cases and control (P = 0.053). Keywords: Atopic dermatitis, INF- γ, Family history, Children DOI: 10.7176/JHMN/64-01 Publication date:July 31st 201

A Protocol for the Secure Linking of Registries for HPV Surveillance

In order to monitor the effectiveness of HPV vaccination in Canada the linkage of multiple data registries may be required. These registries may not always be managed by the same organization and, furthermore, privacy legislation or practices may restrict any data linkages of records that can actually be done among registries. The objective of this study was to develop a secure protocol for linking data from different registries and to allow on-going monitoring of HPV vaccine effectiveness.A secure linking protocol, using commutative hash functions and secure multi-party computation techniques was developed. This protocol allows for the exact matching of records among registries and the computation of statistics on the linked data while meeting five practical requirements to ensure patient confidentiality and privacy. The statistics considered were: odds ratio and its confidence interval, chi-square test, and relative risk and its confidence interval. Additional statistics on contingency tables, such as other measures of association, can be added using the same principles presented. The computation time performance of this protocol was evaluated.The protocol has acceptable computation time and scales linearly with the size of the data set and the size of the contingency table. The worse case computation time for up to 100,000 patients returned by each query and a 16 cell contingency table is less than 4 hours for basic statistics, and the best case is under 3 hours.A computationally practical protocol for the secure linking of data from multiple registries has been demonstrated in the context of HPV vaccine initiative impact assessment. The basic protocol can be generalized to the surveillance of other conditions, diseases, or vaccination programs

A decentralized data evaluation framework in federated learning

Federated Learning (FL) is a type of distributed deep learning framework in which multiple devices train a local model using local data, and the gradients of the local model are then sent to a central server that aggregates them to create a global model. This type of framework is ideal where data privacy is of utmost importance because the data never leave the local device. However, a major concern in FL is ensuring the data quality of local training data. Since there is no control over the local training data, ensuring that the local model is trained on clean data becomes challenging. A model trained on poor-quality data can have a significant impact on its accuracy. In this paper, we propose a decentralized approach using blockchain to ensure local model data quality. We use miners to validate each local model by checking its accuracy against a secret testing dataset. This is done using a smart contract that the miners invoke during the mining process. The local model is aggregated with the global model only if it passes a preset accuracy threshold. We test our proposed method on two datasets: the Brain Tumor Classification dataset from Kaggle, comprised of 7000 MRI images divided into two classes (Tumor/No Tumor), and the Medical MNIST dataset, which includes 58,954 images classified into six different classes: AbdomenCT, BreastMRI, ChestCT, Chest X-ray, Hand X-ray, and HeadCT. Our results show that our method outperforms the original FL approach in all experiments

Fault Location in Solar Farms

Power delivery interruption and catastrophic failures are some of the potential consequences of undetected faults in photovoltaic (PV) arrays. A voltage protection scheme with the minimum number of sensors which is capable of detecting, classifying, and locating line-to-line (intrastring and cross string), line-to-ground, and open-circuit faults in a utility-scale PV array is proposed in this article. The proposed protection scheme consists of three steps. In the first stage, by a simple and efficient algorithm occurrence of any disturbance in the system is detected using some voltage sensors. At this stage, faulty strings in the PV array are also identified. In the second step, using a new least squares-based method, fault and shading conditions are discriminated from each other. Finally, in the third step, the faults inside the faulty string are located using a new method based on multiclass artificial neural networks. Fault location methods that have been developed so far require a large number of sensors or additional equipment for the exact location of faulty modules inside the fault string, but in the proposed method, only one sensor is used per string for fault localization. The proposed scheme for detection and location of faults is evaluated by simulating a typical system in different conditions

A statistical-based criterion for incipient fault detection in underground power cables established on voltage waveform characteristics

The incipient faults which mainly occur due to the electric arc occurrence in the power cables with insulation defects are hardly detectable by the conventional protective relays, and over time can develop into a permanent fault in the system. Employing Kalman filter, this paper puts forward a method to detect the incipient faults and to discriminate them from other similar incidents in the power system. The proposed method is established on the comparison between the waveform of the measured voltage and fundamental component of the measured voltage, estimated by Kalman filter algorithm in the sending end of the cable during the fault. Employing the difference between the measured and estimated waveforms, the incipient fault detection and discrimination are carried out within two stages. In the first stage, event detection is relegalized by comparing the standard deviation of the obtained error with a certain threshold. The second stage is conducted to find the incipient fault based on the non-attenuating characteristic and quasi-periodic nature of the incipient fault. The feasibility of the proposed method is verified through computer simulation using four different electric arc models and also the acquired experimental data from real incipient faults

Replication Data for: Continuous Authentication using Touch Dynamics and its Application in Personal Health Records

The dataset contains 20 data files for 20 participants with overall 125794 instances of touch dynamics information collected using TouchSense (available at https://play.google.com/store/apps/details?id=org.mun.navid.touchsens). The application is implemented in such a way that it prompts the user to type in 30 random words or numbers. While the user interacts with the keyboard, it captures the touch inputs corresponding to those actions and stores them in a data file. This dataset can be used exclusively for research purposes. Commercial purposes are fully excluded. Attribute information: 1- pressure (numeric), 2- size (numeric), 3- touchmajor (numeric), 4- touchminor (numeric), 5- duration (numeric), 6- flytime (numeric), 7- shake (numeric), 8- orientation (numeric), 9- type (numeric), 10- class (AndroidId, Others) Pressure: indicates the pressure applied by a touch action. Size: indicates the number of pixels affected on the screen by a touch action. Touch Major: reports the major axis of an ellipse that represents the touched area. Touch Minor: reports the minor axis of an ellipse that represents the touched area. Duration: represents the time interval from the moment a finger touches the screen until the finger loses contact with it. Fly Time: shows the time elapsed between finishing typing a character and starting to type the next one. Shake: records the amount of vibration of the smartphone while performing touch actions. Orientation: records whether the touch behavior was recorded while the device was in the landscape orientation or the portrait one. Word or Number: records whether the touch behavior involves typing in a word or a number

Secure surveillance of antimicrobial resistant organism colonization or infection in Ontario long term care homes.

BACKGROUND: There is stigma attached to the identification of residents carrying antimicrobial resistant organisms (ARO) in long term care homes, yet there is a need to collect data about their prevalence for public health surveillance and intervention purposes. OBJECTIVE: We conducted a point prevalence study to assess ARO rates in long term care homes in Ontario using a secure data collection system. METHODS: All long term care homes in the province were asked to provide colonization or infection counts for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), and extended-spectrum beta-lactamase (ESBL) as recorded in their electronic medical records, and the number of current residents. Data was collected online during the October-November 2011 period using a Paillier cryptosystem that allows computation on encrypted data. RESULTS: A provably secure data collection system was implemented. Overall, 82% of the homes in the province responded. MRSA was the most frequent ARO identified at 3 cases per 100 residents, followed by ESBL at 0.83 per 100 residents, and VRE at 0.56 per 100 residents. The microbiological findings and their distribution were consistent with available provincial laboratory data reporting test results for AROs in hospitals. CONCLUSIONS: We describe an ARO point prevalence study which demonstrated the feasibility of collecting data from long term care homes securely across the province and providing strong privacy and confidentiality assurances, while obtaining high response rates

A comprehensive experimental study on the effects of hexagonal boron nitride particle size and loading ratio on thermal and mechanical performance in epoxy composites

Harnessing the potential of hexagonal boron nitride (h-BN) in epoxy composites for tailoring thermal conductivity is a promising avenue in materials science. However, achieving balanced enhancements in both in-plane and through-plane directions remains a challenge that requires innovative solutions. The primary objective of this research is to evaluate how thermal and mechanical characteristics of an epoxy matrix are affected by the size and amount of h-BN particles. To achieve this goal, h-BN particles with varying sizes (micro and nano) are incorporated into the epoxy matrix at different weight ratios spanning from 0.5 wt % to 20 wt % using a pre-dispersion technique. The epoxy composites reinforced with h-BN through a molding process exhibits enhanced mechanical and thermal performance in contrast to the pristine epoxy material. During the flexural test, acoustic emission data is collected to identify the initiation and progression of damage within the specimens under testing conditions. The most notable enhancement in thermal conductivity is observed when incorporating 20 wt% of micron-sized h-BN particles. This leads to a remarkable 107% increase in the in-plane direction and an impressive 112% increase in the through-plane direction. These results can be attributed to the formation of a three-dimensional thermally conductive network by the larger h-BN particles, which extends the path of phonon scattering. Furthermore, there are significant improvements in both flexural modulus and tensile modulus. Epoxy composites containing 10 wt% of micron-sized h-BN experiences an approximate 42% increase, while those with 20 wt% of the same particles displays a substantial 47% rise in these properties. This study effectively addresses the challenges associated with tailoring the thermal properties of epoxy composites, opening up new opportunities for applications in various industries, including electronics, aerospace and thermal management systems