PIYAS-Proceeding to Intelligent Service Oriented Memory Allocation for Flash Based Data Centric Sensor Devices in Wireless Sensor Networks

Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks

Targeting of MKRNI for identifying cancer treatment agents

The molecular chaperone Hsp90 binds specifically to hTERT and is required for assembly of active telomerase activity. We show that disruption of Hsp90 function gy geldanamycin efficient ubiquitination and proteasome-mediated degradation of hTERT

A Novel Text Mining Approach for Mental Health Prediction Using Bi-LSTM and BERT Model

With the current advancement in the Internet, there has been a growing demand for building intelligent and smart systems that can efficiently address the detection of health-related problems on social media, such as the detection of depression and anxiety. These types of systems, which are mainly dependent on machine learning techniques, must be able to deal with obtaining the semantic and syntactic meaning of texts posted by users on social media. The data generated by users on social media contains unstructured and unpredictable content. Several systems based on machine learning and social media platforms have recently been introduced to identify health-related problems. However, the text representation and deep learning techniques employed provide only limited information and knowledge about the different texts posted by users. This is owing to a lack of long-term dependencies between each word in the entire text and a lack of proper exploitation of recent deep learning schemes. In this paper, we propose a novel framework to efficiently and effectively identify depression and anxiety-related posts while maintaining the contextual and semantic meaning of the words used in the whole corpus when applying bidirectional encoder representations from transformers (BERT). In addition, we propose a knowledge distillation technique, which is a recent technique for transferring knowledge from a large pretrained model (BERT) to a smaller model to boost performance and accuracy. We also devised our own data collection framework from Reddit and Twitter, which are the most common social media sites. Finally, we employed word2vec and BERT with Bi-LSTM to effectively analyze and detect depression and anxiety signs from social media posts. Our system surpasses other state-of-the-art methods and achieves an accuracy of 98% using the knowledge distillation technique

Clinical Comparison of the Auditory Steady-State Response with the Click Auditory Brainstem Response in Infants

ObjectivesOur goal was to determine the effectiveness of using the auditory steady state response (ASSR) as a measure of hearing thresholds in infants who are suspected of having significant hearing loss, as compared with using the click-auditory brainstem response (C-ABR).MethodsWe retrospectively analyzed the audiologic profiles of 76 infants (46 boys and 30 girls, a total of 151 ears) who ranged in age from 1 to 12 months (average age: 5.7 months). The auditory evaluations in 76 infants who were suspected of having hearing loss were done via the C-ABR and ASSR. In addition, for reference, the mean ASSR thresholds were compared to those of 39 ears of infants and 39 ears of adults with normal hearing at 0.5, 1, 2, and 4 kHz.ResultsThe highest correlation between the C-ABR and ASSR thresholds was observed at an average of 2-4 kHz (r=0.94). On comparison between the hearing of infants and adults at 0.5, 1, 2, and 4 kHz, the mean ASSR threshold in infants was 12, 7, 8, and 7 dB higher, respectively, than that in adults.ConclusionASSR testing may provide additional audiometric information for accurately predicting the hearing sensitivity, and this is essential for the management of infants with severe to profound hearing loss

Artificial Intelligence-Based Speech Analysis System for Medical Support

Purpose Prior research has indicated that stroke can influence the symptoms and presentation of neurogenic bladder, with various patterns emerging, including abnormal facial and linguistic characteristics. Language patterns, in particular, can be easily recognized. In this paper, we propose a platform that accurately analyzes the voices of stroke patients with neurogenic bladder, enabling early detection and prevention of the condition. Methods In this study, we developed an artificial intelligence-based speech analysis diagnostic system to assess the risk of stroke associated with neurogenic bladder disease in elderly individuals. The proposed method involves recording the voice of a stroke patient while they speak a specific sentence, analyzing it to extract unique feature data, and then offering a voice alarm service through a mobile application. The system processes and classifies abnormalities, and issues alarm events based on analyzed voice data. Results In order to assess the performance of the software, we first obtained the validation accuracy and training accuracy from the training data. Subsequently, we applied the analysis model by inputting both abnormal and normal data and tested the outcomes. The analysis model was evaluated by processing 30 abnormal data points and 30 normal data points in real time. The results demonstrated a high test accuracy of 98.7% for normal data and 99.6% for abnormal data. Conclusions Patients with neurogenic bladder due to stroke experience long-term consequences, such as physical and cognitive impairments, even when they receive prompt medical attention and treatment. As chronic diseases become increasingly prevalent in our aging society, it is essential to investigate digital treatments for conditions like stroke that lead to significant sequelae. This artificial intelligence-based healthcare convergence medical device aims to provide patients with timely and safe medical care through mobile services, ultimately reducing national social costs

Ubiquitin ligase MKRN1 modulates telomere length homeostasis through a proteolysis of hTERT

Telomere homeostasis is regulated by telomerase and a collection of associatedproteins. Telomerase is, in turn, regulated by post-translational modifications of the rate-limiting catalytic subunit hTERT. Here we show that disruption of Hsp90 by geldanamycin promotes efficient ubiquitination and proteasome-mediated degradation of hTERT. Furthermore, we have used the yeast two-hybrid method to identify a novel RING finger gene (MKRN1) encoding an E3 ligase that mediates ubiquitination of hTERT. Overexpression of MKRN1 in telomerase-positive cells promotes the degradation of hTERT and decreases telomerase activity and subsequently telomere length. Our data suggest that MKRN1 plays an important role in modulating telomere length homeostasis through a dynamic balance involving hTERT protein stability

Plasma modification of poly(2-heptadecyl-4-vinylthieno[3,4-d]thiazole) low bandgap polymer and its application in solar cells

For the first time, we here propose a green methodology to modify a low bandgap polymer for highly efficient solar cells using atmospheric pressure plasma jet or soft plasma operating on different feeding gases (air, Ar and N-2). The physical properties of the modified polymer were investigated using conductivity measurements, UV-visible spectroscopy, photoluminescence spectroscopy, X-ray photoelectron spectroscopy, cyclic voltammograms, atomic force microscopy, cathodoluminescence and confocal Raman spectroscopy. Further, we examined the variation of the work function of the polymer before and after plasma treatment using a gamma-focused ion beam. Additionally, photovoltaic cells based on the plasma-modified polymer having ITO/PEDOT:PSS/PHVTT (with or without plasma modification): PC71BM/LiF/Al configuration were fabricated and then characterized. We found that the power conversion efficiency (PCE) of the plasma-modified polymer increased dramatically as compared to the control polymer (without plasma treatment). PCE of the control polymer was found to be 4.11%, while after air, Ar and N-2 gas plasma treatment the polymer showed PCEs of 4.85%, 4.87% and 5.14% respectively. Thus, plasma treatment not only alters the surface properties, but also modifies the bulk properties (changes in HOMO and LUMO bandgap level). Hence, this work provides new dimensions to explore more about plasma and polymer chemistry

Post Herpetic Neuropathy of Sinuvertebral Nerve: A Case Report

Varicella-Zoster virus is a neurotropic virus of the herpes virus family that primarily affects sensory nerves. Herpes zoster causing sinuvertebral neuropathy has not been mentioned in the literature. A 55 years old man presented with low back pain, both buttocks, posterior thigh and leg pain over last 3 months. A straight leg raising test was positive on both sides. A left great toe dorsiflexion was decreased to 4/5. The VAS score at admission for back and leg pain was 7/10. The patient MRI was showing disc degeneration at L5-S1 level. We performed endoscopic interlaminar annuloplasty using radiofrequency ablation to denervate the sinuvertebral nerve attached to the annulus under epidural anesthesia. Patient symptoms completely relieved at the postoperative period and continued upto recent follow up of 6 months. The classical presentation of the patient after herpes zoster infection as back pain with referred leg pain, disc degeneration on MRI, intraoperative evidence of chronic neuropathy and almost complete improvement in patient symptoms after radiofrequency ablation makes it a first reported case of sinuvertebral neuropathy following herpes zoster infection

Primary Malignant Teratoma with a Primitive Neuroectodermal Tumor Component in Thyroid Gland : A Case Report

Teratomas comprise the most common extragonadal germ cell tumors in childhood. Most teratomas involving the thyroid are benign and occur in children. However, the adult cases reported are mostly malignant and commonly arise in the thyroid. We report a case of a 31-yr-old female with a huge neck mass. Pathologic examination revealed it to be malignant teratoma composed of primitive neuroepithelial tissue with primitive neural tubes and loose myxoid to fibrous immature mesenchymal stroma. The patient underwent extensive evaluation of the thyroid gland with computed tomography (CT) scan and positron emission tomography (PET) scan, which revealed no evidence of metastatic disease. She underwent total thyroidectomy with bilateral modified radical neck dissection, intensive chemotherapy and radiotherapy. At 22-months of follow-up, the patient has remained euthyroid and showed no evidence of recurrence. This is the first case, to our knowledge, of malignant thyroid teratoma with a exuberant primitive neuroectodermal tumor component in Korea