A uracil nitroso amine based colorimetric sensor for the detection of Cu²⁺ ions from aqueous environment and its practical applications

A simple uracil nitroso amine based colorimetric chemosensor (UNA-1) has been synthesized and screened for its cation recognition ability. Sensor UNA-1 exhibited a high sensitivity and selectivity towards Cu²⁺ ions in aqueous medium in the presence of a wide range of other competing cations (Ag⁺, Al³⁺, Ba²⁺+, Ca²⁺, Cd²⁺, Co²⁺, Cr³⁺, Cs⁺, Fe²⁺, Fe³⁺, Li⁺, Mg²⁺, Mn²⁺, Na⁺, Ni²⁺, Pb²⁺, Zn²⁺, Hg²⁺ and Sr²⁺). With Cu²⁺, the sensor UNA-1 gave a distinct color change from colorless to dark yellow by forming a complex of 1:1 stoichiometry. Furthermore, sensor UNA-1 was successfully utilized in the preparation of test strips and supported silica for the detection of Cu²⁺ ions from aqueous environment

How Does Health Promotion Work? Evidence from the Dirty Business of Eliminating Dirty Defecation

We investigate the mechanisms underlying health promotion campaigns designed to eliminate open defecation in at-scale randomized field experiments in four countries: India, Indonesia, Mali, and Tanzania. Health promotion works through a number of mechanisms, including: providing information on the return to better behavior, nudging better behavior that one already knows is in her self-interest, and encouraging households to invest in health products that lower the marginal cost of good behavior. We find that health promotion generally worked through both convincing households to invest in in-home sanitation facilities and nudging increased use of those facilities. We also estimate the causal relationship between village open defecation rates and child height using experimentally induced variation in open defecation for identification. Surprisingly we find a fairly linear relationship between village open defecation rates and the height of children less than 5 years old. Fully eliminating open defecation from a village where everyone defecates in the open would increase child height by 0.44 standard deviations. Hence modest to small reductions in open defecation are unlikely to have a detectable effect on child height and explain why many health promotion interventions designed to reduce open defecation fail to improve child height. Our results suggest that stronger interventions that combine intensive health promotional nudges with subsidies for sanitation construction may be needed to reduce open defecation enough to generate meaningful improvements in child health

A Study of Components and Benefits of Organic Waste using Decision Tree: A Classifier in Data Mining

Population in India has been growing at a rapid rate. With this increase, there has also been an increase in the amount of wastes being produced especially in the urban cities. Increase in population has led to increase in waste material. Sources of waste are various, generated from industries, agriculture and domestic, but waste management’s schemes are few and improper. Domestic waste is the one generated in huge amount. There are waste management scheme being used by government and non – government organization to properly dispose and manage waste. Due to increase in habitat in various geographic areas and due to mismanagement of people living in a particular geographic area- people throw waste material anywhere they wish in and around they live. This effect the environment like surface water gets contaminated, soil gets contaminated, pollution increases, leachate occurs,etc. all these creates adverse effect on the human being and ecosystem. This paper gives a brief study of the components organic waste and its benefits on human begins and ecosystem by using decision tree classifier of datamining

Studies on Synthesis of Aldimines: Part-III. Synthesis, Spectral Characterization and Bioactivity of Salicylaldimines

Compounds containing >C=N- (azomethine) were prepared from Salicylaldehyde with Aniline derivatives by conventional chemical synthesis method. The products are tested in process and the completion of reaction product formation was ascertained by TLC. The final products were characterized by physical viz. m.p., analytical viz. TLC, Instrumental viz. UV-Vis and FTIR spectral techniques. Results showed that all the marked activity coefficients(biopotential) for the studied compounds are less than the standard drug, Ketoconazole

Novel AI-driven Malaria Prediction for Optimizing Public Health Management

Malaria is an unmoving real common well-being apprehension in Asian nations like the Republic of India, where the state characterizes approximately 55% of the session events cutting-edge the infirmaries. They are usually distinguished by the absence of appropriate therapeutic care provision and the often late and error-prone diagnosis of the condition. In particular, commonly used devices such as the Rapid Diagnosis Test (RDT) are not completely dependable. They are primarily notable for their failure to provide adequate medical treatment and their tendency to diagnose the disease late and incorrectly. For example, widely used devices like the RDT are not consistent. To improve public health management actions, this work offers a unique augmented tree with penguin search optimization (AT+PSO) methodology for malaria forecasting. The suggested method combines the PSO algorithm with the augmented tree model, also known as random forest (RF). In the preprocessing stage, raw data samples are subjected to data normalization. Then, we applied the PSO to improve the characteristics of the RF model after successfully predicting malaria with the RF. The Python program is used to implement the suggested technique and analyze performance using a range of measures, including accuracy (0.988), sensitivity (0.987), specificity (0.991), F1-score (0.988), and MCC (0.975). In summary, our suggested approach produced the best results in terms of accuracy as opposed to other current strategies for predicting malaria to improve governance of public health

A prospective observational study of prescription pattern of drugs used in the treatment of osteoarthritis in a tertiary care hospital

Background: Treatment of Osteoarthritis aims at reducing pain and improving mobility. NSAIDS are commonly prescribed for symptomatic relief despite well documented adverse effects. Paracetamol with its better safety profile is recommended as the initial analgesic of choice. Osteoarthritis has significant socio-economic impact on the patients and not many studies are available to reflect upon the prescription pattern of drugs in Osteoarthritis. Hence, this study was chosen to generate important feedback to the clinician. The objectives of the study were to study the prescribing pattern of drugs used in the treatment of Osteoarthritis in Tertiary care hospital.Methods: Prescription for 300 osteoarthritis patients collected cross-sectional for 6 months from orthopedic out-patient department were analyzed.Results: 60% of females were affected. Average age of study was 56.46+/- 7.4 years. Knee joint (87.33%) was most commonly affected joint. Average number of drugs prescribed was 2.62 +/- 0.76. Out of 786 drugs prescribed 45.8% were NSAIDs. Paracetamol was underutilized.Conclusions: Paracetamol was underutilized while other NSAIDs were over prescribed

Building Early Warning Systems for Public Health Concerns Using AI-assisted Electrical Modelling for Epidemic Pattern Recognition

A rapid recognition and handling of new threats to public health is crucial for reducing large-scale epidemic outbreaks as well as related consequences. However, this study is relevant because it could enhance the surveillance capabilities that can be used to respond swiftly and effectively to major outbreaks. While there are numerous challenges facing the use of artificial intelligence (AI) in epidemiological research, such technology has a lot of promise. Some of these include integration of complex data sources, validating data, managing computational requirements, and identifying and addressing privacy and security concerns No one doubts that Surveillance Predictive Modeling System-Based Healthcare Framework (SPMS-HF) will overcome these setbacks. SPMS-HF works by using potent AI algorithms to analyze electrical data and hence predict outbreak conditions. This allows for more accurate predictions and early warnings of potential public health risks. There could be different uses for SPMS-HF including real-time disease surveillance, resource efficiency, and public health. Implementation of this program enables healthcare givers alongside police officers to boost community health outcomes while improving their counter-response attitudes. To illustrate the applicability of SPMS-HF simulation analysis was carried out on historical epidemiological data. The results suggest that the model can identify possible health hazards as well as predict future outbreaks with accuracy These findings illustrate how e-images with AI can produce credible warning systems for public health

Cybersecurity and Compliance in Healthcare: A Study on Key Management and Other Regulatory Requirements

Typically, WSNs are implemented in several applications with various topologies. Nodes use wireless mode of communication, and unattended areas are typically selected for WSN deployment. Attack risk is higher in WSNs. Furthermore, the WSN nodes have severe resource constraints. It is quite difficult to provide security in such a setting. Numerous protocols for key management chores and encryption strategies for maintaining security in the WSN environment have been documented in literature. The criticality of the data being transferred over the network determines how complex the assault will be. Applications that monitor agriculture, for example, are safe from attacks. However, applications related to the military and healthcare could attract attackers who are far more skilled. Applications that involve process control and habitat monitoring attract attackers with medium to low skill levels. There isn\u27t a single protocol available right now that could be flexible enough to meet the different requirements of the apps, which typically have variable security requirements. For these different applications, there are differences in the key management task, which is strongly related to the security requirements. As a result, the precise kind and complexity of the key management technique must be chosen and built in accordance with the necessary level of security, the capabilities of the hardware devices available, and the network topology that is used

Studies on Synthesis of Aldimines: Part-I. Synthesis, Characterization and Biological Activity of Aldimines from Benzaldehyde with variedly substituted anilines

A conventional condensation reaction of an aromatic aldehyde, Benzaldehyde with seven different aromatic amines viz. Aniline, 2-Choro-aniline, 3-Choro-aniline, 4-Choro-aniline, 2-Nitro-aniline, 3-Nitro-aniline and 4-Nitro-aniline and reacted efficiently to synthesize a series of Aldmines, I to VII, in moderate to high yield and high purity. The reaction was monitored and the products were analyzed by employing the TLC technique. All the products obtained were characterized by their colour, physical constant, TLC, elemental analysis and spectral (UV-Vis and FTIR) method. The synthesized Aldimines were subjected to in vitro biological activity

Studies on Synthesis of Aldimines: Part-I. Synthesis, Characterization and Biological Activity of Aldimines from Benzaldehyde with variedly substituted anilines

A conventional condensation reaction of an aromatic aldehyde, Benzaldehyde with seven different aromatic amines viz. Aniline, 2-Choro-aniline, 3-Choro-aniline, 4-Choro-aniline, 2-Nitro-aniline, 3-Nitro-aniline and 4-Nitro-aniline and reacted efficiently to synthesize a series of Aldmines, I to VII, in moderate to high yield and high purity. The reaction was monitored and the products were analyzed by employing the TLC technique. All the products obtained were characterized by their colour, physical constant, TLC, elemental analysis and spectral (UV-Vis and FTIR) method. The synthesized Aldimines were subjected to in vitro biological activity