The paper is intended to through light on opticalbiosensors used for various sensing purposes. It provides fundamentals of a sensor and its parameters. It explains the basic phenomena behind optical biosensors qualitatively. It also includes recent advancements in the field of optical biosensors giving emphasis on the plasmon enhanced electric field phenomenon. It creates interest to carry out research in the field of Biosensors.

As the E-commerce industry is Booming every year, online shopping has become a norm while purchasing anything. Hence, the significance of the security of our purchased commodity has also grown. Tracking parcel gives us better visibility about where our parcel is and when we can expect to receive it. This is especially helpful in the case of sensitive or expensive deliveries. Therefore, the development of a courier tracking system using the Global Positioning System (GPS) and Global System for Mobile Communications (GSM)/ General Packet Radio Service (GPRS) modem is undertaken to enable users to locate their vehicles with ease and in a convenient manner. A courier tracking system is an electronic device attached to a vehicle to enable the buyer and the seller to track the courier's location. This paper proposed to design a courier tracking system that works using GPS and GSM/GPRS technology, which would be the cheapest source of tracking. The system will provide users with the capability to track their product remotely through the mobile network and internet. The Tracking system uses a TTGO T-CALL with inbuilt GSM/GPRS SIM800l module, GPS module, to track the courier and send the latitude and longitude of the location using the network. This system is an embedded one. An embedded system is a microprocessor-based computer hardware system with software that is designed to perform a dedicated function. The software used is Blynk Application which is used to control Arduino, raspberry, ESP32 module and gives the accurate position available using the widget provided. The developed courier tracking system demonstrates the feasibility of near real-time tracking of vehicles.

The present manuscript deals with the synthesis of some novel mixed ligand complexes of Cadmium and their characterization on the basis of melting point, elemental and spectral analysis. The newly synthesized complexes were also tested for their antibacterial, antifungal and antitumor activity in-vitro and their results of screening clearly indicating them as potent biomedicinal agents. Introduction There is an enormous potential for the application of metals in medicines and the selection of metal ions offer the possibility for the discovery of metallodrugs with novel mechanism of action[1]. The importance of metal based drugs lies in the fact that they are essential components for various physico-chemical processes occurring in living system[2-6]. The spectrum of the chemotherapeutic values of organotin compounds has been expanded as they have found their place among a class of potential biologically active compounds exhibiting antimicrobial activity against different kinds of microbial strains along with antiinflammatory, cardiovascular, trypanosomal, anti-herpes and anti-tubercular activity[7-11]. Coordination chemistry forms the backbone for the major part of the current researches in chemistry[12-15]. This can be seen from large number of books, review articles and international conferences which are held every year. The importance of coordination compounds and their role in numerous systems of chemical and biological significance can easily be recognized when one realizes that chlorophyll, which is vital to photosynthesis in plants, is- a complex of magnesium and that hemoglobin, which carries oxygen to animal cells is an iron complex[16-19]. Coordinated metal ions incorporated in the structure of enzymes are responsible for their action. The transition metal ions, Zn, Co, Pe, etc. are known to persist in biological systems by coordination with numerous enzymes containing the heme, and related structures such as catalases, peroxidases and cytochromes. The iron containing proteins, ferritin, transferrin and hemosiderin are known to predominate in biological systems[20-22]. Zinc complex as sine insulin and Beryllium salt or complex, as lymphocyte activator are- known for their- importance.

Dengue is another infection caused by mosquitoes. It is a very common infection mainly in tropical and subtropical regions. In India, it is affected in all regions urban and rural. Dengue hemorrhagic fever is a very serious condition that has serious complications that leads to hospitalization and also death in some people especially in children. Second-time infection is dangerous but, one type of virus provides lifelong immunity. But the vaccine is available from 2015 for the age group between 9 to 45 who has previously dengue fever. According to the data by National Vector Borne Disease Control program, there is a drastic decrease in the death rate in India due to dengue fever. Carica papaya is a tropical plant, the leaves extract has medicinal and nutritional benefits and has a significant effect in Dengue fever patients in increasing platelet count. India has a strong culture of using herbs, and plantbased products in the treatment of various diseases. In the present study, thirty patients who are affected with dengue fever and platelets below 40,000 cmm, who are admitted to the different hospitals of Mumbai are selected. As per the doctor’s advice, they have consumed 30ml of Carica papaya leaf extract, evaluation study is done to find the efficacy of Carica papaya leaf extract in increment of platelets. In all the patients it is observed there is a significant increase in the platelet count from baseline to day 6. It is evident that the leaf extract has the efficacy to increase platelet count and will aid in controlling complications and hospital stay.

Excess Volume for three binary mixtures viz. ethanol + [empy][EtSO4], water +[empy][EtSO4] and 1-propanol +[empy][EtSO4] and ternary mixtures of ethanol + water +[empy][EtSO4] at different mole fractions at temperature 298.15K

In the current work, the CAD model of solar panel (photovoltaic) has been developed by using design modeller. The model has been simulated using ANSYS software on fluent solver in workbench in order to observe various parameters affecting the thermal performance of solar panel (photovoltaic). Five types of configurations of solar panel (photovoltaic) with water flow gap i.e. flow gap of 10mm, 20mm, 30mm, 40mm and 50mm have been used. The simulation of the optimized model gives lower value of temperature distribution with respect to different mass flow rate at constant solar radiation. It is also observed from present analysis that solar panel (photovoltaic) with 10mm and 20mm of water flow gap exhibits lower temperature with thermal energy gain with enhancement of 65 to 70 percent of total efficiency, the regression analysis is also performed for developed optimized models for determination of optimum developed optimized model and it was observed that 10mm of water flow gap have effective results as compared to other configurations.

Anomaly detection relies on individuals’ behavior profiling and works by detecting any deviation from the norm. When used for online banking fraud detection, however, it mainly suffers from three disadvantages. The historical behavior data are often too limited to profile his/her behavior pattern. Due to the heterogeneous nature of transaction data, there lacks a uniform treatment of different kinds of attribute values, which becomes a potential barrier for model development and further usage. The transaction data are highly skewed, and it becomes a challenge to utilize the label information effectively. The three disadvantages result in both poor generalization and high false positive rate of anomaly detection, and we propose a ranking metric embedding based multi-contextual behavior profiling (ReMEMBeR) model to battle them effectively. With the idea of collaborative filtering, for an individual, information from other similar individuals can be used to establish his/her behavior profile. The proposed model can, thus, integrate the multicontextual behavior patterns and allow transactions to be examined under the different contexts. Extensive experiments on a real-world online banking transaction dataset demonstrate that our model not only outperforms benchmarks on all metrics but also can be combined with them to achieve even better performance.

Stress is a feeling of emotional or physical tension. It can cause from both physical and emotional reason like chronical disease, depression, negative thoughts, self-doubt, anger etc. It is both positive and negative. Positive stress helps in avoiding danger or deadline but when it lasts for longer period, it may harm your health and mind. To prevent last long stress, it is necessary to detect them in the early stages which is only possible if detects on time. In this paper, a comprehensive review has been presented which focused on stress detecting and monitoring using wearable sensors, Electroencephalography (EEG), Electrocardiogram (ECG) and photo plethysmography. The stressors techniques, results, advantages, limitations and issue for each study are highlighted and expected to provide a path for future research studies and multimodal stress detection based on deep learning technique has been proposed at last.

COVID-19 is global pandemic which has changed the audience in India on the way of consume media. There is an increasingly growing number of consumers adapting to OTT Platform. While global players like Netflix and Amazon prime have steadily grown their market share in India, Indian streaming services like Hot star and JIO Cinema has gained a stronger foothold. This paper explores the role played by the pandemic in evolving OTT media consumption trends; a qualitative Analyses of increase in OTT adoption; impact of OTT on children, adults and elder lies, and future of streaming service in India through an analytical research. Other than primary data content from news articles, industry research reports, International journals for accumulation of key trends were also analyses.

A graph G with p vertices and q edges is said to be vertex odd mean graph if there is an injective function f: V(G)→ { 1, 3, 5……., 2q-1}such that each edge uv is labeled as ƒ(u)+ƒ(v) if f(u) 2 +f(v) is even and 𝒇(𝒖)+𝒇(𝒗)+𝟏 𝟐 if f(u) +f(v) is odd, then the resulting edges are distinct. The findings of this paper are, double triangular snake (D (𝑘𝐶n) + 2𝑛𝑃2), Jelly fish J(m, n), 𝑃n ° 𝐻1, and an alternate triangular snake A(𝑇n ) are vertex odd mean graphs.

This paper analyzed a system of computer with component-wise redundancy with independent failures of software and hardware. There are two units-one primarily operative and other reserved as hardware cold standby. After determined operation time, by conducting precautionary conservation of hardware unit, there are two possibilities that is operative unit undergoes for software up gradation with some probability while other possibility for hardware unit after independent failures. A single server is available instantly to provide the services like repairs of hardware, software components and preventive maintenance. The system is in good state after repair. The different failures of system follow exponential distribution whereas others are arbitrary. Regenerative Point Graphical Technique (RPGT) with semi-Markov process is used for finding the consistency and other strictures of the system speedily and easily. The derived expressions like mean time to system failure (MTSF), availability of the system, different busyness of system and the number of visits of the server are shown graphically.

Vascular structures of the retina hold crucial information for the detection and diagnosis of ocular illnesses, such as glaucoma, diabetic retinopathy, and age-related macular degeneration. Fluorescein angiography, scanning laser ophthalmoscopes, and fundus photography are often employed techniques in the diagnosis of these illnesses (FA). Generally, retinal vascular segmentation is carried out either manually or interactively, which makes it time demanding and prone to human errors. In this study, we suggest ELEMENT, a new multi-modal framework for vessel segmentation (vEs- seL sEgmentation using Machine lEarning and coNnecTivity). This framework uses machine learning and region growth to classify images based on pixels rather than regions. The suggested features capture comprehensive evidence based on vessel connection and grey level attributes. At the classification step, the latter information is smoothly transmitted via the pixels. ELEMENT decreases inconsistencies and increases throughput during segmentation. In three main groups of tests, we evaluate and contrast the effectiveness of the proposed technique versus cutting-edge vascular segmentation algorithms for each of the ocular modalities.