Universal Spam Detection using Transfer Learning of BERT Model

Several machine learning and deep learning algorithms were limited to one dataset of spam emails/texts, which waste valuable resources due to individual models. This research applied efficient classification of ham or spam emails in real-time scenarios. Deep learning transformer models become important by training on text data based on self-attention mechanisms. This manuscript demonstrated a novel universal spam detection model using pre-trained Google's Bidirectional Encoder Representations from Transformers (BERT) base uncased models with multiple spam datasets. Different methods for Enron, Spamassain, Lingspam, and Spamtext message classification datasets, were used to train models individually. The combined model is finetuned with hyperparameters of each model. When each model using its corresponding datasets, an F1-score is at 0.9 in the model architecture. The "universal model" was trained with four datasets and leveraged hyperparameters from each model. An overall accuracy reached 97%, with an F1 score at 0.96 combined across all four datasets

Evaluation of M-Sites Using PDAs

As mobile sites (m-sites) are introduced a very relevant question to ask is “How should these sites be different from the typical websites developed for desktop PCs?” This paper presents an initial, exploratory attempt to address some issues related to m-sites. This evaluation of sites was conducted using wireless PDAs in a WLAN environment. The results indicated that regular sites and m-sites differed significantly in perceived search engine functionality. The evaluated m-sites showed little differences across various industries. A discussion of these results as well as recommendations for managers and academic researchers are provided

Kernel-Segregated Transpose Convolution Operation

Transpose convolution has shown prominence in many deep learning applications. However, transpose convolution layers are computationally intensive due to the increased feature map size due to adding zeros after each element in each row and column. Thus, convolution operation on the expanded input feature map leads to poor utilization of hardware resources. The main reason for unnecessary multiplication operations is zeros at predefined positions in the input feature map. We propose an algorithmic-level optimization technique for the effective transpose convolution implementation to solve these problems. Based on kernel activations, we segregated the original kernel into four sub-kernels. This scheme could reduce memory requirements and unnecessary multiplications. Our proposed method was 3.09(3.02)× faster computation using the Titan X GPU (Intel Dual Core CPU) with a flower dataset from the Kaggle website. Furthermore, the proposed optimization method can be generalized to existing devices without additional hardware requirements. A simple deep learning model containing one transpose convolution layer was used to evaluate the optimization method. It showed 2.2× faster training using the MNIST dataset with an Intel Dual-core CPU than the conventional implementation

Privacy-Preserving Deep Learning Model for Covid-19 Disease Detection

Recent studies demonstrated that X-ray radiography showed higher accuracy than Polymerase Chain Reaction (PCR) testing for COVID-19 detection. Therefore, applying deep learning models to X-rays and radiography images increases the speed and accuracy of determining COVID-19 cases. However, due to Health Insurance Portability and Accountability (HIPAA) compliance, the hospitals were unwilling to share patient data due to privacy concerns. To maintain privacy, we propose using differential private deep learning models to secure the patients' private information. The dataset from the Kaggle website is used to evaluate the designed model for COVID-19 detection. The EfficientNet model version was selected according to its highest test accuracy. The injection of differential privacy constraints into the best-obtained model was made to evaluate performance. The accuracy is noted by varying the trainable layers, privacy loss, and limiting information from each sample. We obtained 84\% accuracy with a privacy loss of 10 during the fine-tuning process

Infection with hepatitis B virus carrying novel pre-S/S gene mutations in female siblings vaccinated at birth: two case reports

<p>Abstract</p> <p>Introduction</p> <p>After the initiation of a mass hepatitis B vaccination program in Taiwan, the prevalence of hepatitis B virus infection has declined progressively. However, about 1 percent of the young generation, who received hepatitis B vaccination at birth, remain carriers. Infection with vaccine-escape hepatitis B virus mutants always occurs shortly after birth. Here, we report two female siblings in whom the infection occurred in their adolescence. This report raises the question of whether a booster for hepatitis B vaccination is needed.</p> <p>Case presentation</p> <p>Two 19 and 14-year-old Taiwanese female siblings were born to a mother infected with hepatitis B virus and received a complete course of hepatitis B vaccination at birth. They remained negative for serum hepatitis B surface antigen and positive for serum anti-hepatitis B surface antibody throughout their childhood. However, both were infected with the hepatitis B virus in their adolescence. Hepatitis B virus DNA was extracted from serum samples from the mother and two siblings. Hepatitis B virus pre-S/S sequence was amplified by polymerase chain reaction followed by nucleotide sequencing. When compared with the sequence obtained from the mother, multiple amino acid substitutions located near or in the major hydrophilic region of the surface antigen were identified in the elder sister. Four of these mutations (sL97S, sL98S, sG102R, and sA159P) were novel. A novel in-frame deletion (14 amino acids deleted, pre-S 127-140) was found in the hepatitis B virus pre-S2 region in the younger sister.</p> <p>Conclusions</p> <p>Despite having received hepatitis B vaccination at birth, hepatitis B virus infection can still occur in adolescence with the emergence of novel mutations in the pre-S/S gene. This is a rare event and, to the best of our knowledge, has not been previously reported.</p

Use Of Chinese Medicine Among Colorectal Cancer Patients: A Nationwide Population-Based Study.

Background: Traditional Chinese medicine (CM) appears to be used worldwide, especially by cancer patients. The aim of the present study was to explore CM uses and CM non-users by patients with colorectal cancer (CRC).Materials and methods: A retrospective study was conducted using registration and claims data sets for 2007 from the National Health Insurance Research Database. Patients with colorectal cancer were identified from the Registry for Catastrophic illness Patients. Binary logistic regression was used to estimate odds ratios as the measure of association with the use of CM.Results: A total of 61,211 CRC patients diagnosed in 2007 were analysis. Most CM users preferred to visit private clinics (46.9%) with 306,599 visits. In contrast, the majority of CM non-users preferred to visit private hospitals (42.2%) with 538,769 visits. Among all 176,707 cancer-specific CM visit, there were 66.6% visits to CM outpatient department (OPD) of private hospitals, while in 477,612 non-cancer-specific CM visits, 62.0% was for private clinics. The proportion of expenses for diagnostic fees for CM user in CM visits was much less than that for WM visits and CM non-users (US$4.6 vs. 29.3 vs. 33.5). The average cost for CM user in CM was less than that for WM visits and CM non-users (US$6.3 vs. 25.9 vs. 30.3). Female patients, younger age, and patients not living in the northern region, with higher EC or more comorbidities were more likely to receive CM treatment.Conclusion: The prevalence and costs of insurance-covered CM among CRC patients were low. Further longer longitudinal study is needed to follow up this trend.Key words: Chinese Medicine, Digestive System Neoplasms, Health Insuranc

Progenitor-like cells derived from mouse kidney protect against renal fibrosis in a remnant kidney model via decreased endothelial mesenchymal transition

Showing A quantification of GFP-positive cells in the lung after intravenous injection of MKPCs in five-sixths nephrectomized mice (y axis shows the number of cells, while the x axis (FL1-H) shows the fluorescence intensity; M1 is the area of GFP-positive cells) and B immunohistochemistry of the lung after intravenous injection of MKPCs into a mouse that underwent five-sixths nephrectomy. Few GFP positive cells were found in the lung at the first day but there were no GFP-positive cells at week 14. (TIFF 2253 kb

Adherence to the screening program for HBV infection in pregnant women delivering in Greece

BACKGROUND: Hepatitis B infection (HBV) is a major Public Health Problem. Perinatal transmission can be prevented with the identification of HBsAg(+) women and administration of immunoprophylaxis to their newborns. A national prevention programme for HBV with universal screening of pregnant women and vaccination of infants is in effect since 1998 in Greece. METHODS: To evaluate adherence to the national guidelines, all women delivering in Greece between 17–30/03/03 were included in the study. Trained health professionals completed a questionnaire on demographic data, prenatal or perinatal screening for HBsAg and the implementation of appropriate immunoprophylaxis. RESULTS: During the study period 3,760 women delivered. Prenatal screening for HBsAg was documented in 91.3%. Greek women were more likely to have had prenatal testing. HBsAg prevalence was 2.89% (95%CI 2.3–3.4%). Higher prevalence of HBV-infection was noted in immigrant women, especially those born in Albania (9.8%). Other risk factors associated with maternal HBsAg (+) included young maternal age and absence of prenatal testing. No prenatal or perinatal HBsAg testing was performed in 3.2% women. Delivering in public hospital and illiteracy were identifiable risk factors for never being tested. All newborns of identified HBsAg (+) mothers received appropriate immunoprophylaxis. CONCLUSION: The prevalence of HBsAg in Greek pregnant women is low and comparable to other European countries. However, immigrant women composing almost 20% of our childbearing population, have significant higher prevalence rates. There are still women who never get tested. Universal vaccination against HBV at birth and reinforcement of perinatal testing of all women not prenatally tested should be discussed with Public Health Authorities

Is it better to treat chronic hepatitis B as early as possible?—Con

Ideally, treatment of chronic hepatitis B in its early stage prior to irreversible liver damage should be most effective in preventing adverse clinical outcome. However, currently available treatments have low efficacy in achieving sustained response among patients in the early phase of chronic hepatitis B infection when the immune response to hepatitis B virus is weak. This review will provide evidence why a ‘wait and monitor’ approach is appropriate for chronic hepatitis B patients who are in the immune tolerant phase.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73513/1/j.1440-1746.2004.03660.x.pd

Frequency Shift of Carbon-Nanotube-Based Mass Sensor Using Nonlocal Elasticity Theory

The frequency equation of carbon-nanotube-based cantilever sensor with an attached mass is derived analytically using nonlocal elasticity theory. According to the equation, the relationship between the frequency shift of the sensor and the attached mass can be obtained. When the nonlocal effect is not taken into account, the variation of frequency shift with the attached mass on the sensor is compared with the previous study. According to this study, the result shows that the frequency shift of the sensor increases with increasing the attached mass. When the attached mass is small compared with that of the sensor, the nonlocal effect is obvious and increasing nonlocal parameter decreases the frequency shift of the sensor. In addition, when the location of the attached mass is closer to the free end, the frequency shift is more significant and that makes the sensor reveal more sensitive. When the attached mass is small, a high sensitivity is obtained