Design, Development and Evaluation of Portable Washer for Lotus Rhizomes

629-633The aim of the present study was to design, develop and evaluate a low cost portable washer for Lotus Rhizomes. Different performance parameters and colour values were studied to check the performance of the developed prototype in comparison to the manual washing. The capacity and efficiency of the machine was much higher than the existing manual method of washing. The colour coordinates (L* a* b*) revealed that washing through developed washer makes lotus rhizomes more clean and bright as compared to the  manual washing. Different sanitizers were also tested for shelf life enhancement of lotus rhizomes. Out of all tested sanitizers, the citric acid was found best with regard to shelf life enhancement and cleanliness of lotus rhizomes. The economic analysis reveals that the developed lotus rhizome washer can be beneficial for the people who are directly or indirectly involved in lotus rhizome trade

Clinical effects of Streptococcus salivarius K12 in hospitalized COVID-19 patients: results of a preliminary study

Anatomical and physiological considerations indicate that the oral cavity is a primary source of the lung microbiota community, and recent studies have shown that the microbiota in the lungs contributes to immunological homeostasis, potentially altering the organ’s susceptibility to viral infection, including SARS-CoV-2. It has been proposed that, in the case of viral infection, lung Gram-negative bacteria could promote the cytokine cascade with a better performance than a microbiota mainly constituted by Gram-positive bacteria. Recent observations also suggest that Prevotella-rich oral microbiotas would dominate the oral cavity of SARS-CoV-2-infected patients. In comparison, Streptococcus-rich microbiotas would dominate the oral cavity of healthy people. To verify if the modulation of the oral microbiota could have an impact on the current coronavirus disease, we administered for 14 days a well-recognized and oral-colonizing probiotic (S. salivarius K12) to hospitalized COVID-19 patients. The preliminary results of our randomized and controlled trial seem to prove the potential role of this oral strain in improving the course of the main markers of pathology, as well as its ability to apparently reduce the death rate from COVID-19. Although in a preliminary and only circumstantial way, our results seem to confirm the hypothesis of a direct involvement of the oral microbiota in the construction of a lung microbiota whose taxonomic structure could modulate the inflammatory processes generated at the pulmonary and systemic level by a viral infection

Internet of Things (IoT) Based Indoor Air Quality Sensing and Predictive Analytic—A COVID-19 Perspective

Indoor air quality typically encompasses the ambient conditions inside buildings and public facilities that may affect both the mental and respiratory health of an individual. Until the COVID-19 outbreak, indoor air quality monitoring was not a focus area for public facilities such as shopping complexes, hospitals, banks, restaurants, educational institutes, and so forth. However, the rapid spread of this virus and its consequent detrimental impacts have brought indoor air quality into the spotlight. In contrast to outdoor air, indoor air is recycled constantly causing it to trap and build up pollutants, which may facilitate the transmission of virus. There are several monitoring solutions which are available commercially, a typical system monitors the air quality using gas and particle sensors. These sensor readings are compared against well known thresholds, subsequently generating alarms when thresholds are violated. However, these systems do not predict the quality of air for future instances, which holds paramount importance for taking timely preemptive actions, especially for COVID-19 actual and potential patients as well as people suffering from acute pulmonary disorders and other health problems. In this regard, we have proposed an indoor air quality monitoring and prediction solution based on the latest Internet of Things (IoT) sensors and machine learning capabilities, providing a platform to measure numerous indoor contaminants. For this purpose, an IoT node consisting of several sensors for 8 pollutants including NH3, CO, NO2, CH4, CO2, PM 2.5 along with the ambient temperature & air humidity is developed. For proof of concept and research purposes, the IoT node is deployed inside a research lab to acquire indoor air data. The proposed system has the capability of reporting the air conditions in real-time to a web portal and mobile app through GSM/WiFi technology and generates alerts after detecting anomalies in the air quality. In order to classify the indoor air quality, several machine learning algorithms have been applied to the recorded data, where the Neural Network (NN) model outperformed all others with an accuracy of 99.1%. For predicting the concentration of each air pollutant and thereafter predicting the overall quality of an indoor environment, Long and Short Term Memory (LSTM) model is applied. This model has shown promising results for predicting the air pollutants’ concentration as well as the overall air quality with an accuracy of 99.37%, precision of 99%, recall of 98%, and F1-score of 99%. The proposed solution offers several advantages including remote monitoring, ease of scalability, real-time status of ambient conditions, and portable hardware, and so forth

A Multi-modal Approach for Crop Health Mapping using low altitude Remote Sensing, Internet of Things (IoT) and Machine Learning

The agriculture sector holds paramount importance in Pakistan due to the intrinsic agrarian nature of the economy. Pakistan has its GDP based on agriculture, however it relies on manual monitoring of crops, which is a labour intensive and ineffective method. In contrast to this, several cutting edge technology-based solutions are being employed in the developed countries to enhance the crop yield with the optimal use of resources. To this end, we have proposed an integrated approach for monitoring crop health using IoT, machine learning and drone technology. The integration of these sensing modalities generate heterogeneous data which not only varies in nature (i.e. observed parameter) but also has different temporal fidelity. The spatial resolution of these methods is also different, hence, the optimal integration of these sensing modalities and their implementation in practice are addressed in the proposed system. In our proposed solution, the IoT sensors provide the real-time status of environmental parameters impacting the crop, and the drone platform provide the multispectral data used for generating Vegetation Indices (VIs) such as Normalized Difference vegetation Index (NDVI) for analyzing the crop health. The NDVI provides information about the crop based on the chlorophyll content, which offers limited information regarding the crop health. In order to obtain a rich and detailed knowledge about crop health, the variable length time series data of IoT sensors and multispectral images were converted to a fixed-sized representation to generate crop health maps. A number of machine and deep learning algorithms were applied on the collected data wherein deep neural network with two hidden layers was found to be the most optimal model among all the selected models, providing an accuracy of (98.4%). Further, the health maps were validated through ground surveys and by agriculture experts due to the absence of reference data. The proposed research is basically an indigenous, technology based agriculture solution capable of providing important insights into the crop health by extracting complementary features from multi-modal data set, and minimizing the crop ground survey effort, particularly useful when the agriculture land is large in size

Quercetin as a possible complementary agent for early-stage COVID-19: concluding results of a randomized clinical trial

Background: Quercetin, a natural polyphenol with demonstrated broad-spectrum antiviral, anti-inflammatory, and antioxidant properties, has been proposed as an adjuvant for early-stage coronavirus disease 2019 (COVID-19) infection. Objective: To explore the possible therapeutic effect of quercetin in outpatients with early-stage mild to moderate symptoms of COVID-19. Methods: This was an open-label randomized controlled clinical trial conducted at the department of medicine, King Edward Medical University, Lahore, PK. Patients were randomized to receive either standard of care (SC) plus an oral quercetin supplement (500 mg Quercetin Phytosome®, 1st week, TDS: 2nd week, BDS) (n = 50, quercetin group) or SC alone (n = 50, control group). Results: After one week of treatment, patients in the quercetin group showed a speedy recovery from COVID-19 as compared to the control group, i.e., 34 patients (vs. 12 in the control group) tested negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (p = 0.0004), and 26 patients (vs. 12 in the control group) had their COVID-19-associated acute symptoms resolved (p = 0.0051). Patients in the quercetin group also showed a significant fall in the serum lactate dehydrogenase (LDH) mean values i.e., from 406.56 ± 183.92 to 257.74 ± 110.73 U/L, p = 0.0001. Quercetin was well-tolerated by all the 50 patients, and no side effects were reported. Conclusion: Our results, suggest the possible therapeutic role of quercetin in early-stage COVID-19, including speedy clearance of SARS-CoV-2, early resolution of the acute symptoms and modulation of the host’s hyperinflammatory response. Clinical Trial Registration: clinicaltrials.gov, identifier NCT04861298

Role of proline, K/Na ratio and chlorophyll content in salt tolerance of wheat (Triticum aestivum

Abstract Studies to determine the role of proline, K/Na ratio and chlorophyll contents in salt tolerance of wheat genotypes were conducted in lysimeters using hydroponics technique. Seeds were allowed to germinate under normal condition (1.5 dS m -1 ) and salinity treatment of 12 dS m -1 was imposed after one week of germination. Crop was irrigated at the interval of two weeks or whenever required with 1/4 th Hoagland nutrient solution of respective concentrations. Results clearly indicated that wheat genotypes with higher proline, K/Na ratio and chlorophyll contents had higher grain yield. On the basis of yield reduction, three genotypes viz. Lu-26s, Sarsabz and KTDH were found tolerant. These genotypes also maintained the higher concentration of proline, K/Na ratio and chlorophyll contents under saline conditions

INFLUENCE OF INCREASING FLUORIDE DOSE RATES ON SELECTED LIVER AND KIDNEY ENZYMES PROFILE IN DOMESTIC CHICKEN (Gallus domesticus)

ABSTRACT Fluoride has been considered to cause hepatic and renal tissue damages in animals and humans. The present study investigated the effect of varying concentrations of fluoride on hepatic and renal enzyme profile in domestic chicken (n=80). Chicken were distributed into 4 groups. Group A was kept unexposed while group B, C and D were exposed to 10, 20 and 30 µg/g body weight of NaF respectively on weekly basis for four weeks. Alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine amino-transferase (ALT) and bilirubin were determined as indicators of liver function test (LFT), while uric acid was as a parameter for renal function test (RFT). All LFT and RFT parameters showed high values (P< 0.05) after one, two three and four weeks in all groups. 579.4 ± 1.55, 355.0 ± 2.13, 246.2 ± 2.45 and 0.83 ± 1.46 were the ALP, AST, ALAT and bilirubin values for LFT and uric acid was 6.74 ± 2.92 in D group at the end of four weeks. All these results indicate the probability of severe effect on the physiology of the liver and kidneys in the exposed birds

INFLUENCE OF INCREASING FLUORIDE DOSE RATES ON SELECTED LIVER AND KIDNEY ENZYMES PROFILE IN DOMESTIC CHICKEN (Gallus domesticus)

ABSTRACT Fluoride has been considered to cause hepatic and renal tissue damages in animals and humans. The present study investigated the effect of varying concentrations of fluoride on hepatic and renal enzyme profile in domestic chicken (n=80). Chicken were distributed into 4 groups. Group A was kept unexposed while group B, C and D were exposed to 10, 20 and 30 µg/g body weight of NaF respectively on weekly basis for four weeks. Alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine amino-transferase (ALT) and bilirubin were determined as indicators of liver function test (LFT), while uric acid was as a parameter for renal function test (RFT). All LFT and RFT parameters showed high values (P< 0.05) after one, two three and four weeks in all groups. 579.4 ± 1.55, 355.0 ± 2.13, 246.2 ± 2.45 and 0.83 ± 1.46 were the ALP, AST, ALAT and bilirubin values for LFT and uric acid was 6.74 ± 2.92 in D group at the end of four weeks. All these results indicate the probability of severe effect on the physiology of the liver and kidneys in the exposed birds