An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction

يعد سرطان الرئة من أخطر الأمراض وأكثرها انتشارًا ، حيث يتسبب في العديد من الوفيات كل عام. على الرغم من أن صور التصوير المقطعي المحوسب تستخدم في الغالب في تشخيص السرطان ، إلا أن تقييم عمليات الفحص يعد مهمة معرضة للخطأ وتستغرق وقتًا طويلاً. يمكن للنموذج القائم على التعلم الآلي والذكاء الاصطناعي تحديد أنواع سرطان الرئة وتصنيفها بدقة تامة ، مما يساعد في الكشف المبكر عن سرطان الرئة الذي يمكن أن يزيد من معدل البقاء على قيد الحياة. في هذا البحث ، تُستخدم الشبكة العصبية التلافيفية لتصنيف السرطانة الغدية وسرطان الخلايا الحرشفية وصور المسح المقطعي المحوسب للحالة العادية من مجموعة بيانات صور مسح الصدر بالأشعة المقطعية باستخدام مجموعات مختلفة من الطبقة المخفية والمعلمات في نماذج CNN. تم تدريب النموذج المقترح على 1000 صورة مسح مقطعي للخلايا السرطانية وغير السرطانية للعثور على أفضل مزيج من المعلمات في CNN للتنبؤ بسرطان الرئة بدقة. سجل النظام المقترح أعلى دقة بلغت 92.79٪. بالإضافة إلى ذلك ، تتناول الورقة 192 ملاحظة تمت باستخدام نموذج CNN.Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-cancerous cells to find the best combination of parameters in CNN to predict lung cancer accurately.  The proposed system recorded the highest accuracy of 92.79%. In addition to that, the paper addresses 192 observations made using the CNN model.

Biofertilizer and their importance in sustainable agriculture

There are many small or undeveloped countries whose economy depends on agricultural production. A healthy agriculture production depends on various factors like soil quality, water, fertilizer, skilled labor, and many more. Fertilizer is the most crucial things that influence agricultural production. A fertilizer is a kind of chemical or natural substance that is helpful in crop production. However, to achieve quick agricultural yields we usually used chemical fertilizer which is very responsive to biofertilizer but the chemical fertilizer is not as eco-friendly as biofertilizer. Biofertilizer are natural fertilizes which are living microbial inoculants of bacteria, algae, fungi alone or in combination and they augment the availability of nutrients to the plants. Mycorrhizal fungi preferentially withdraw minerals from organic matter for the plant whereas cyanobacteria are characterized by the property of nitrogen fixation. The role of biofertilizer in agriculture assumes special significance, particularly in the present context of increased cost of chemical fertilizer and their hazardous effects on soil health. Agricultural fertilizers are essential for proper crop growth and yield. Chemical fertilizers have recently been used by farmers to increase yield and speed up the process. Natural biofertilizer, on the other hand, not only have a higher yield but are also safe for humans.  The benefits of biofertilizer include low cost, enhanced nutrient availability, improved soil fertility, protect plants from soil-borne pathogens, sustainable agricultural production, enhanced biotic and abiotic stress tolerance, promote phytohormone production, improve soil health, causing less environmental pollution, and its continued use improves the fertility of soil considerably. &nbsp

Microbial Plastic Degradation: Nature's Solution for Sustainable Waste Management

Plastic pollution has emerged as a global environmental crisis, demanding innovative and sustainable waste management strategies. This review explores the potential of harnessing nature's capabilities, specifically through microbial plastic degradation, as a promising avenue for sustainable waste management. The focus is on the collaborative action of microorganisms, utilizing their enzymatic activities to enhance plastic degradation. This review delves into the intricate mechanisms of microbial interaction with various types of plastics, emphasizing recent advancements in microbial plastic degradation research. Furthermore, it discusses the challenges associated with scaling up microbial degradation processes and envisions the incorporation of these approaches into practical waste management solutions. This exploration of microbial plastic degradation represents a critical step in mitigating the environmental impact of plastic pollution and promoting a more sustainable and eco-friendly waste management paradigm

Unraveling Cellular Heterogeneity: Insights From Single-Cell Omics Technologies

In the era of precision medicine and personalized healthcare, the emergence of single-cell omics technologies has revolutionized our comprehension of cellular biology. This abstract offers an overview of the rapidly expanding field of single-cell omics, which encompasses genomics, transcriptomics, proteomics, and epigenomics, detailing its transformative impact across various scientific disciplines. Single-cell omics techniques have introduced an unprecedented level of cellular resolution, empowering researchers to meticulously dissect intricate cellular heterogeneity and dynamics within tissues and organisms. Through the profiling of individual cells, these methodologies have shed light on novel insights spanning developmental biology, cancer research, immunology, neurobiology, and microbiology. The integration of multi-modal single-cell data holds the promise of providing a comprehensive view of cellular systems. This abstract underscores the potential of single-cell omics in unraveling the complexities inherent in biological systems, propelling advancements in diagnostics, and catalyzing the development of targeted therapeutics as part of the broader pursuit of precision medicine

Advancing Biomedical Frontiers: Unveiling The Potential Of 3d Bioprinting In Organ Regeneration

The advent of 3D bioprinting marks a pivotal moment in biomedical research and healthcare, unlocking a realm of possibilities. This abstract explores the transformative potential of 3D bioprinting technology, its diverse applications in medical domains, and the inherent challenges it faces. 3D bioprinting represents a revolutionary fusion of three-dimensional printing precision with the intricacies of biological materials. This groundbreaking technology revolutionizes the fabrication of intricate, customized structures by layering bioinks containing living cells, biomaterials, and growth factors. These engineered constructs faithfully replicate the complex architecture of native tissues and organs, presenting unprecedented opportunities for progress in regenerative medicine, drug testing, and disease modeling. The versatility of 3D bioprinting extends across various medical fields. In regenerative medicine, the ability to craft tissue grafts and organ substitutes tailored to individual patients has the potential to transform transplantation procedures, overcoming challenges like donor shortages and organ rejection. Additionally, pharmaceutical companies are employing 3D bioprinting to generate functional tissue models for drug testing, reducing reliance on animal testing and speeding up drug development processes. 3D bioprinting represents a transformative technology with the potential to advance healthcare through personalized regenerative solutions, ethical drug testing practices, and an improved understanding of diseases.However, the adoption of 3D bioprinting is not without its challenges. The intricacy of the bioprinting process necessitates a profound understanding of cellular biology, materials science, and engineering. Overcoming hurdles related to ensuring cell viability and functionality within printed structures is paramount, along with the imperative to scale up production for clinical applications. Ethical and regulatory considerations also emerge, particularly in the context of printing human tissues and organs

Low Noise Multiquantum Well DAR IMPATT Diodes Based On SiXGe1-X/Si

A Multiquantum Well (MQW) SixGe1-x/Si DAR (Double Avalanche Region) IMPATT (Impact Avalanche Transit Time) diode as a high power-high efficiency-low noise source at W-band is proposed in this paper. The RF power, conversion efficiency and noise of the device are optimized with respect to number of quantum wells and Ge mole fraction. The proposed device delivers peak power of 2.7 W, conversion efficiency of 7.5% and noise measure of 25 dB when the number of wells in the MQW structure is four and mole fraction of Ge is 0.3. The admittance plots of the device exhibit distinct negative conductance bands for three different (0.1, 0.2 and 0.3) mole fractions of Ge. An upward shift of optimum frequency is observed with increasing Ge mole fraction. The noise measure of the device decreases with increasing mole fraction of Ge and decreasing current

Noise Performance of Heterojunction DDR MITATT Devices Based on at W-Band

Noise performance of different structures of anisotype heterojunction double-drift region (DDR) mixed tunneling and avalanche transit time (MITATT) devices has been studied. The devices are designed for operation at millimeter-wave W-band frequencies. A simulation model has been developed to study the noise spectral density and noise measure of the device. Two different mole fractions and of Ge and corresponding four types of device structure are considered for the simulation. The results show that the -Si heterojunction DDR structure of MITATT device excels all other structures as regards noise spectral density ( sec) and noise measure (33.09 dB) as well as millimeter-wave properties such as DC-to-RF conversion efficiency (20.15%) and CW power output (773.29 mW)

Women's autonomy and utilization of maternal healthcare in India: Evidence from a recent national survey.

ObjectiveThe present study aims to examine the association between women's decision-making autonomy and utilization of maternal healthcare services among the currently married women in India.MethodsA total of 32,698 currently married women aged 15-49 years who had at least one live birth in the past five years preceding the survey and had information regarding autonomy collected by the National Family Health Survey 2015-16 were used for analysis. Bivariate and multivariate logistic regression models were employed for the analyses of this study.ResultsUtilization of maternal healthcare services was higher among the women having a high level of decision-making autonomy compared to those who had a low autonomy in the household. The regression results indicate that women's autonomy was significantly associated with increased odds of maternal healthcare services in India. Women with high autonomy had 37% and 33% greater likelihood of receiving ANC (AOR: 1.37, 95% CI: 1.25-1.50) and PNC care (AOR: 1.33, 95% CI: 1.24-1.42) respectively compared to women having low autonomy. However, no significant association was observed between women's autonomy and institutional delivery in the adjusted analysis.ConclusionThis study recommends the need for comprehensive strategies involving improvement of women's autonomy along with expansion of education, awareness generation regarding the importance of maternity care, and enhancing public health infrastructure to ensure higher utilization of maternal healthcare services that would eventually reduce maternal mortality