Convolutional Neural Networks Exploiting Attributes of Biological Neurons

In this era of artificial intelligence, deep neural networks like Convolutional Neural Networks (CNNs) have emerged as front-runners, often surpassing human capabilities. These deep networks are often perceived as the panacea for all challenges. Unfortunately, a common downside of these networks is their ''black-box'' character, which does not necessarily mirror the operation of biological neural systems. Some even have millions/billions of learnable (tunable) parameters, and their training demands extensive data and time. Here, we integrate the principles of biological neurons in certain layer(s) of CNNs. Specifically, we explore the use of neuro-science-inspired computational models of the Lateral Geniculate Nucleus (LGN) and simple cells of the primary visual cortex. By leveraging such models, we aim to extract image features to use as input to CNNs, hoping to enhance training efficiency and achieve better accuracy. We aspire to enable shallow networks with a Push-Pull Combination of Receptive Fields (PP-CORF) model of simple cells as the foundation layer of CNNs to enhance their learning process and performance. To achieve this, we propose a two-tower CNN, one shallow tower and the other as ResNet 18. Rather than extracting the features blindly, it seeks to mimic how the brain perceives and extracts features. The proposed system exhibits a noticeable improvement in the performance (on an average of $5\%-10\%$) on CIFAR-10, CIFAR-100, and ImageNet-100 datasets compared to ResNet-18. We also check the efficiency of only the Push-Pull tower of the network.Comment: 20 pages, 6 figure

RETROSPECTIVE MULTICENTRIC STUDY ON THE POST-SURGERY SYMPTOMATIC AND OBJECTIVE IMPROVEMENT OF BENIGN PROSTATIC HYPERPLASIA PATIENTS

Objectives: To evaluate patients of benign prostatic hyperplasia (BPH) preoperatively and identify those who would benefit from surgery, to evaluate outcome of surgery for BPH with respect to symptomatic and objective improvement of patients, and to compare the results of different surgeries for BPH being done different hospitals at Bhopal, which included transurethral resection of the prostate (TURP), transurethral incision of prostate (TUIP)/bladder neck incision (BNI), and Freyer’s prostatectomy? Methods: The present study was carried out at different hospitals of Bhopal. Patients presenting to the surgery outpatient department with symptoms of obstruction, namely, weak urinary stream, frequency hesitancy, intermittency, urgency, nocturia, etc., were included in the study. Some of the subjects included were patients presenting during emergency timings with complaints of retention of urine or occasionally other symptoms. The American Urological Association (AUA) Symptom Index questionnaire was administered to all such patients. They were also evaluated by ultrasound examination and patients having BPH on ultrasound (USG) were further evaluated by uroflowmetry. Results: Prostatic weight correlated well with the maximum urinary flow rates with an inverse relationship. Both maximum and average urinary flow rates (Q max and Qav) were improved by all the three surgeries However, TURP and Freyer’s prostatectomy showed greater improvement as compared to TUIP/BNI. Combination of AUA scoring, USG, and uroflowmetry helped us document improvement in our BPH patients and compared it favorably with other studies. Conclusion: Uroflowmetry was a simple assessment tool easy to learn and use. It was also inexpensive and formed a useful extension to clinical examination providing objective evidence of obstruction. It also helped to indirectly quantity the severity of obstruction. Symptom severity did not correlate with prostate size. Small prostates caused symptoms in the severe range also while even large prostates sometimes caused little symptoms. Prostatic weight correlated well with the maximum urinary flow rates with an inverse relationship

A COMPARATIVE STUDY OF PREVALENCE OF ANEMIA AND ITS RISK FACTORS AMONG SCHOOL-GOING ADOLESCENT GIRLS IN THE FIELD PRACTICE AREAS OF MEDICAL COLLEGE IN GAUTAM BUDDHA NAGAR DISTRICT

Objectives: (1) The study was to determine the prevalence of iron deficiency anemia among adolescent girls in the field practice areas of a medical college of GautamBuddha Nagar district and (2) to assess the risk factors associated with iron deficiency anemia among adolescent girls in the field practice areas of a medical college of GautamBuddha Nagar district. Methods: A school-based cross-sectional study was conducted to assess the prevalence of anemia among adolescent girls of the field practice areas of the medical college of Gautam Buddha Nagar District. The sample size came out to be 236. One school each from RHTC and UHTC was selected randomly, and all adolescent girls were enrolled in the study. Results: The present study was conducted on 684 adolescent females (251 from RHTC and 433 from UHTC) in our study period of 3 months. The prevalence of anemia in the whole population was 42%, 54.5% among rural and 35.5% of adolescents in urban area were found to be anemic at the time of the study. The factors that were found to be significantly associated with adolescent anemia were age of onset of menarche, history of albendazole intake, residing in joint family, and lower socioeconomic status. Conclusion: The prevalence was high among girls who were above 16 years of age and girls who belonged to lower socio-economic groups and belonging to rural area. There is a need for a regular supply of iron and folic acid tablets and for improving medication adherence regarding consuming these tablets among adolescent girls and also about the dietary advice

Breaking Yield Ceiling in Wheat: Progress and Future Prospects

Wheat is one of the most important staple crops that contribute considerably to global food and nutritional security. The future projections of the demand for wheat show significant enhancement owing to the population growth and probable changes in diets. Further, historical yield trends show a reduction in the relative rate of gain for grain yield over time. To maintain future food security, there is a strong need to find ways to further increase the yield potential of wheat. Grain yield is a quantitative trait that is highly influenced by the environment. It is determined by various interlinked yield component traits. Molecular breeding approaches have already proven useful in improving the grain yield of wheat and recent advances in high-throughput genotyping platforms now have remodelled molecular breeding to genomics-assisted breeding. Hence, here in this chapter, we have discussed various advancements in understanding the genetics of grain yield, its major components, and summarised the various powerful strategies, such as gene cloning, mining superior alleles, transgenic technologies, advanced genome editing techniques, genomic selection, genome-wide association studies-assisted genomic selection, haplotype-based breeding (HBB), which may be/being used for grain yield improvement in wheat and as the new breeding strategies they could also be utilised to break the yield ceiling in wheat

Investigation of DNA damage response and apoptotic gene methylation pattern in sporadic breast tumors using high throughput quantitative DNA methylation analysis technology

<p>Abstract</p> <p>Background-</p> <p>Sporadic breast cancer like many other cancers is proposed to be a manifestation of abnormal genetic and epigenetic changes. For the past decade our laboratory has identified genes involved in DNA damage response (DDR), apoptosis and immunesurvelliance pathways to influence sporadic breast cancer risk in north Indian population. Further to enhance our knowledge at the epigenetic level, we performed DNA methylation study involving 17 gene promoter regions belonging to DNA damage response (DDR) and death receptor apoptotic pathway in 162 paired normal and cancerous breast tissues from 81 sporadic breast cancer patients, using a high throughput quantitative DNA methylation analysis technology.</p> <p>Results-</p> <p>The study identified five genes with statistically significant difference between normal and tumor tissues. Hypermethylation of <it>DR5 </it>(P = 0.001)<it>, DCR1 </it>(P = 0.00001)<it>, DCR2 </it>(P = 0.0000000005) and <it>BRCA2 </it>(P = 0.007) and hypomethylation of <it>DR4 </it>(P = 0.011) in sporadic breast tumor tissues suggested a weak/aberrant activation of the DDR/apoptotic pathway in breast tumorigenesis. Negative correlation was observed between methylation status and transcript expression levels for <it>TRAIL</it>, <it>DR4</it>, <it>CASP8</it>, <it>ATM</it>, <it>CHEK2</it>, <it>BRCA1 </it>and <it>BRCA2 </it>CpG sites. Categorization of the gene methylation with respect to the clinicopathological parameters showed an increase in aberrant methylation pattern in advanced tumors. These uncharacteristic methylation patterns corresponded with decreased death receptor apoptosis (P = 0.047) and DNA damage repair potential (P = 0.004) in advanced tumors. The observation of BRCA2 -26 G/A 5'UTR polymorphism concomitant with the presence of methylation in the promoter region was novel and emerged as a strong candidate for susceptibility to sporadic breast tumors.</p> <p>Conclusion-</p> <p>Our study indicates that methylation of DDR-apoptotic gene promoters in sporadic breast cancer is not a random phenomenon. Progressive epigenetic alterations in advancing tumors result in aberrant DDR-apoptotic pathway thereby promoting tumor development. We propose, since pathological epigenetic changes of the DDR-apoptotic genes are reversible modifications, these could further be targeted for therapeutic interventions.</p

Study of Photoluminescence Behaviour of Porous Silicon Samples Prepared at 20 mA Current Density

The paper presents a study on a series of porous silicon films of various thicknesses, prepared at 20 mA current density using a photoluminescence fitting model to determine the average crystallite size of sphe-rical shaped interconnected silicon quantum dots. Discrepancy in photoluminescence behavior of the samples is well explained with this model. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3097

Developing a Universal Identification Model: Integrating AI and IoT Tools with DNAFIDs to Recognize COVID-19 Patients

DNA fingerprinting identification systems based on artificial intelligence infuse almost every facet of life. Its impact on various aspects of human health can be seen today. It has also found its importance in the identification of global COVID-19 infections, whether suspected or proven, in patients. Because of the IoT and the application of sophisticated filtering techniques to big data, it’s conceivable. The technology of DNA profiling, which creates detailed profiles of individual characteristics, is a necessity. This can be incredibly helpful in the acquisition process in certain circumstances when paired with other data. Many candidates’ medical and physiological factors are included in the Human Clinical Profile (HCP), as are social profile-related services. The government spends significant tax dollars vetting the physical and medical characteristics of various candidates for clinical care and purposes related to public health response. We propose a technique that may help analyze the physical traits of candidates preemptively and conduct forensic investigation for human identification, which may help reduce the cost of check-ups and other medical processes. This technique combines DNA profiling with artificial intelligence tools to pre-screen candidates for COVID-19 patients who require physical and remote monitoring. Further experiments done in a targeted manner are justification for the hypothesis

Comparative Analysis of P&O and INC MPPT Algorithms for PV System under Variable Irradiance

Applications of Photovoltaic (PV) panels are increasing day by day in worldwide. Electricity generation through PV panels is one of the best example for utilization of renewable energy sources i.e., solar energy. Hence, operating PV panels at their best utilization is must to make system cost effective. Due to nonlinear characteristics of a PV system, identifying a locations corresponding to operating condition at maximum power delivery is required to make system more efficient. In order to achieve the best utilization of PV panels, a maximum power point tracking (MPPT) technique should be implemented. Hence, a MPPT method plays an important role in PV based power generation systems. However, an efficient algorithm is must to operate PV system at its MPPT level. In this paper a comparative performance analysis of two famous MPPT algorithms is presented in this paper. The Perturb and observed (P&O) and Incremental Conductance (IC) methods are developed in this paper for comparing their responses under variable irradiances. MATLAB/Simulink based results are presented in this paper under various operating conditions

A Parametric Study on the Bixin Oil Suspensions Produced Using Annatto Seeds (Bixia Orella) and Its Potential Application in Coloring Margarine Products

Bixin obtained from Annatto seeds (Bixinella orella), has been used by the food industry as a source for natural color for a long time due to its low toxicity and high colorific value. Given its potential applications in dairy and meat industry to obtain a desired reddish - orange hue, a method was sought, which would quickly extract the desired pigment from the seed coat at low cost and allow for its direct application in the desired product. The bixin mass was extracted using demineralized water (D.M.W), sunflower oil or methanol and was then re-suspended in sunflower oil to a bixin strength of 10%. A study of the extraction process, viscosity and color hue (L*a*b value) of the 10% formulated product in margarine at low doses of 0.1% was carried out. Data indicated that methanol extraction provided the desirable reddish hue in margarine and yielded a product with lowest viscosity