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A checklist of termites (Blattodea: Isoptera) of southern India with their distribution is presented in this paper. In total, 132 species from five families are listed, of which Termitidae Latreille, 1802 is the dominant family comprising 101 species from 27 genera and four subfamilies. The recent additions of species to the regional termite diversity are Krishnacapritermes dineshan Amina & Rajmohana, 2020, K. manikandan Amina & Rajmohana, 2020, and Pseudocapritermes kunjepu Mathew, 2020. Out of 132 species recorded from southern India, 60 species and five genera are endemic to the region, and the subfamily Termitinae Latreille, 1802 accounts for maximum endemism.

Termites, being serious pests of sugarcane, have been posing threat to its cultivation in Indo-Gangetic plains of North-West zone of India. Monthly observations round the year revealed a highest per cent incidence of termites in the month of August to the tune of 25.45% followed by 22.73, 21.82, 18.18 and 15.45% in the months of July, September, October and June, respectively. The incidence was lower in winter months, i.e. January, February and March with 4.55, 5.45 and 7.27%, respectively. It is evident from the weather data that monsoon season with high relative humidity and moderate temperature was favourable for the build-up of the population of termites, while winter season was unfavourable. Study on relative abundance of different species of termites in sugarcane revealed that termite species, Odontotermes obesus, occupied the maximum percentage of occurrence to the tune of 28.57% followed by that was 21.42, 14.28, 14.28, 14.28 and 7.14% of Microtermes obesi, O. horni, O. vaishno, O. bellahunisensis and Odontotermes sp., respectively. Of the total species recorded during the course of study, three species, viz. Odontotermes horni (Wasmann), O. vaishno Bose and O. bellahunisensis Holmgren and Holmgren, were recorded for the first time to infest sugarcane in India. An illustrated key was developed for easy and quick identification of termite species collected from sugarcane. The study holds promise for strategic planning for the management of termites in sugarcane agro-ecosystem.

Funding: Deutsche Forschungsgemeinschaft (DFG) through the SFB 1143 and the Wurzburg-Dresden Cluster of Excellence on Complexity and Topology in Quantum Matter–ct.qmat (EXC 2147, Project No. 390858490), as well as the support of the HLD at HZDR, a member of the European Magnetic Field Laboratory (EMFL). We gratefully acknowledge support from the European Research Council (through the QUESTDO project, 714193), the Leverhulme Trust, and the Royal Society. We thank the Elettra synchrotron for access to the APE-HE beamline under proposal number 20195300. The research leading to this result has been supported by the project CALIPSOplus under Grant Agreement 730872 from the EU Framework Programme for Research and Innovation HORIZON 2020. Part of this work has been performed in the framework of the Nanoscience Foundry and Fine Analysis (NFFA-MUR Italy Progetti Internazionali) project (www.trieste.NFFA.eu).

In this view, organic fluids can help to extract heat from low temperature reservoir and to produce vapour. Organic fluids were used in Rankine cycle to see the power output of the plant using Cycle tempo software which is used for simulating the Rankine cycle and necessary parameter inputs with Isobutane, R11, R12, R123 and R245fa working fluids. The minimum net electric power is obtained from R12 with the value of 5.46 kW and 8.21 kW of maximum power is obtained from organic Rankine cycle using Isobutane as working fluid.

In present day, the unrelenting increase in air and noise pollution has become a perpetual nuisance and likewise an alarming problem. In this periodical, we are providing a system to gauge and monitor the environmental parameters and alarm when the air quality and noise levels breaches safe levels. The system uses the necessary sensors to detect the gases present in the atmosphere as well as the noise levels in a particular region and transmits them to the microcontroller NodeMCU. Now cloud platform Blynk which is connected to Node MCU with Wi-Fi credentials acquires the data and processes it by comparing with the values that are perceived as safe levels. This cloud based monitoring app Blynk further provides an alert system when each of the air quality and noise pollution variables crosses the permissible level. It notifies the user by sending an email or message to an android device or even a buzzer can be activated as an alarm. This data is transmitted continuously, and stored for further interpretation. This cloud based pollution monitoring system is most affordable, reliable and cost efficient and could be enhanced for upcoming challenges.

People shop in Supermarkets to examine the quality of a product physically before purchasing them. But when it comes to locating their desired products where they can’t rely on staffs, pushing the loaded carts around the market and standing in queues for billing, especially for elderly customers and the disabled, it must be quite an unpleasant shopping experience and time consuming. To overcome these issues, in this paper we provide a novel solution for a better and smart shopping experience by designing an Autonomous Supermarket Robot. It can guide the customers through the repository of various products to the desired one and can be switched over to an Autonomous trolley to carry the purchased products. After the purchase, a load cell and a camera are used to predict the purchased product through Deep learning using Convolution neural networks and finally the customers can pay through their bank account. These technologies work on a common framework and provide a promising potential for robot assistance in supermarkets.

Background Poor adherence to tuberculosis (TB) treatment is associated with disease recurrence and death. Little research has been conducted in India to understand TB medication nonadherence. Methods We enrolled adult drug-susceptible TB patients, approximately half of whom were people with human immunodeficiency virus (PWH), in Chennai, Vellore, and Mumbai. We conducted a single unannounced home visit to administer a survey assessing reasons for nonadherence and collect a urine sample that was tested for isoniazid content. We described patient-reported reasons for nonadherence and identified factors associated with nonadherence (ie, negative urine test) using multivariable logistic regression. We also assessed the association between nonadherence and treatment outcomes. Results Of 650 participants in the cohort, 77 (11.8%) had a negative urine test. Nonadherence was independently associated with daily wage labor (adjusted odds ratio [aOR], 2.7; confidence interval [CI], 1.1–6.5; P = .03), the late continuation treatment phase (aOR, 2.0; CI, 1.1–3.9; P = .03), smear-positive pulmonary disease (aOR, 2.1; CI, 1.1–3.9; P = .03), alcohol use (aOR, 2.5; CI, 1.2–5.2; P = .01), and spending ≥30 minutes collecting medication refills (aOR, 6.6; CI, 1.5–29.5; P = .01). People with HIV reported greater barriers to collecting medications than non-PWH. Among 167 patients reporting missing doses, reported reasons included traveling from home, forgetting, feeling depressed, and running out of pills. The odds of unfavorable treatment outcomes were 4.0 (CI, 2.1–7.6) times higher among patients with nonadherence (P < .0001). Conclusion Addressing structural and psychosocial barriers will be critical to improve TB treatment adherence in India. Urine isoniazid testing may help identify nonadherent patients to facilitate early intervention during treatment., We evaluated adherence to tuberculosis medications in 650 Indian patients by conducting urine isoniazid tests collected during unannounced home visits. Structural barriers to collecting medication refills and psychosocial barriers emerged as the most important factors contributing to medication nonadherence.

This paper deals with image processing and feature extraction. Feature extraction plays a vital role in the field of image processing. There exist different image pre-processing approaches for feature extraction such as binarization, thresholding, resizing, normalisation so on...Then after these techniques are applied to obtain high clarity images. In Feature extraction object recognition and stereo matching are at the base of many computer vision problems. The descriptor generator module is changed for increasing the performance of algorithm. SIFT algorithm consist of two modules such as key point detection module and descriptor generation module. When compared to recent solution, the descriptor generation module speed is fifteen times faster and the time for feature extraction is also reduced.

In the banking sector, every banking infrastructure contains an enormous dataset for customers’ credit card approval which requires customer profiling. The customer profiling means collection of data related to what customers need. It depends on customers’ basic information like field of work, address proof, credit score, salary details, etc. This process mainly concentrates on predicting approval of credit cards to customers using machine learning. Machine Learning is the scientific study of algorithms and statistical models that computers use to perform specific tasks without any external instructions or interference. In the current trend this process is possible using many algorithms like “K-Mean, Improved K-Mean and Fuzzy C-Means”. This helps banks to have an high profitability to satisfy their customers. However, the currently prevailing system shows an accuracy percentage of about 98.08%. The proposed system aims at improvising the accuracy ratio while using only few algorithms.

Diabetes mellitus is a disease commonly called Diabetes. Diabetes is among the most frequent diseases globally. This disease affects internationally with different ailments and complications in majority of peoples. Diabetes is a chronic disease with the ability to create a global medical care crisis. In compliance with International Diabetes Federation 382 million people are reportedly living with diabetes throughout the entire world. The diabetes disorder can't be cured but it can control, diagnosis and prediction of diabetes is vital to restrain the death rate as a result of its seriousness globally. Many In recent years, machine learning (ML) algorithms have been used in the prediction of diabetes. A clever predictive model utilizing deep modelling is commonly advised with the aid of conditional data collection to forecast the severity and particular risk factor of diabetics. In this article, to resolve this problem we employed the Interpretable Filter based Convolutional Neural Network (IF-CNN) prediction model and Pet Dog-Smell Sensing (PD-SS) algorithm that can automatically predict the diabetes from PIMA Indian diabetes datasets. This may enhance the general strategy of disease prediction in patients database that may solve the issues faced by traditional algorithms employing the Deep Neural Network (DNN) methods. The automated extraction, selection and classification of attributes, disease forecast is the hard task with aggressive performance for your PIMA information which may be implemented with the projected Deep Learning version economically. This may enhance the general plan of disease prediction from patients database that may solve the issues faced by traditional algorithms employing the Interpretable Filter established Deep Learning version prediction model to diagnose and predict the diabetes disease in multi-level databases. The intention of this research is to create a method that could carry out early diabetes predictions for a more reliable patient by including findings of SVM and CNN-LSTM(Long Short-Term Memory) machine learning methods also IF-CNN achieved 96.26% accuracy.

User Image sharing social site maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users inadvertently shared personal information. In light of these incidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. The solution relies on an image classification framework for image categories which may be associated with similar policies and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to user’s social features. Image Sharing takes place both among previously established groups of known people or social circles and also increasingly with people outside the users social circles, for purposes of social discovery-to help them identify new peers and learn about peers interests and social surroundings, Sharing images within online content sharing sites, therefore, may quickly lead to unwanted disclosure. The aggregated information can result in unexpected exposure of one’s social environment and lead to abuse of one’s personal information.

The keyestablishment for secure many-to-many communications is very important nowadays. The problem is inspired by the proliferation of large-scale distributed file systems supporting parallel access to multiple storage devices. In this, a variety of authenticated key exchange protocols that are designed to address the issues. This shows that these protocols are capable of reducing the workload of the metadata server and concurrently supporting forward secrecy and escrow-freeness. All this requires only a small fraction of increased computation overhead at the client. This proposed three authenticated key exchange protocols for parallel network file system (pNFS). The protocols offer three appealing advantages over the existing Kerberos-based protocol. First, the metadata server executing these protocols has much lower workload than that of the Kerberos-based approach. Second, two of these protocols provide forward secrecy: one is partially forward secure (with respect to multiple sessions within a time period), while the other is fully forward secure (with respect to a session). Third, designed a protocol which not only provides forward secrecy, but is also escrow-free.

People are facing several health issues due to the stress and unhealthy food habits. But the greater issue being the ignorance towards these two. On this regard we proposed a new idea that is a smart blood pressure and glucose level monitoring system through sensor monitoring system anybody can measure the blood pressure and glucose level, this sensor was interfaced with IOT through raspberry-pi. At first the data of the person’s average blood pressure and glucose level is stored as a data in cloud, and as per the measurements of daily or monthly basis the data will be compared with the cloud through HTTP and MQTT Protocol. If there any changes found in the data, it will automatically forward the message to the hospitals through that the doctor can suggest the person regarding daily routine food through this we can avoid major health problems.

The essence of any Foundry is its furnace. The operation of the furnace legally involves the process of melting metal by hand is highly dependent on human performance as well ability. With increasing demand and improved technology, this is a common approach it is quickly replaced by temperature-controlled libraries. Basic the effectiveness of such a control to compare the temperature of the metal with the set melting temperature and send the corresponding output to the heat or heat feature. The type of temperature and the furnace customize the type of controller used. While such a control system exists, other safety and fuel management controls plans are the essentials of a modern day oven. This paper is intended in the construction of such a gas burner control system. Gas exploded Furnace Control System includes an active Burner Management System a large part of the melting process. The Control system is built with emphasis on Flame Feedback method, which was analyzed in detail. The control system is actually a temperature control system which includes sensor inputs including thermocouple and flame rod, and effects such as large gas valve, heat rod and blower fan motor. Thus this system is aimed at proper burner management that facilitates the furnace operation and ensures safety of not only the furnace-burner system but the plant in general.

In this research mission, we motive to construct a protracted-variety (ProlongedRange)-primarily based net of factors (IoT) comfortable localization device and appliance primarily based totally on multisensory synthesiscomputation. The Prolonged range generation is used to layout a community security device and right now deal with the computing device, wherein the purpose is to broaden a community server host that collects and approaches function signals from the multisensingsignal series and evaluation processing module and at once detects region by using community nodes thru the sensors cloud, excessive-degree improvement platform, and the multisensory fusion computing workstations, which send the consequences to the crucial monitoring gadget thru the Wi-Fi gadgets of the Prolonged range network. The relaxed localization computing chip very final outcomes, as advanced on this mission, can be used in the domain names of electricity control, environmental manipulate, facts management, manufacturing unit monitoring, and renewable strength manipulate. The device of this task comprises prolonged range hosts, which get hold of signs from numerous nodes and are linked to multisensory fusion arithmetic device via a Wi-Fi network. To sum up, in this look at, we emphasize the usage of multisensory fusion computing generation to implement a relaxed localization gadget of a wireless sensor network technology (WSN), and we remember the use of the embedded system and prolonged range era to broaden a monitoring machine for manufacturing facility fire manage anti-theft, energy, facts, and protection primarily based on cozy localization. In this study, we pass domain names and integrate associated engineering automation, community safety technology, multisensory synthesis computation design, and the (ProlongedRange) localization method, and the study’sfindings are anticipated to make a contribution to the network protection of the protection organization and studies at theLora IoTlocalization method.

The rapid change in communication and network technology makes the transfer of secret message/information through insecure channel highly vulnerable. Hence the security of information exchanged becomes a critical and imperative issue. Towards this direction, we examine the new encryption/decryption technique with digital signature using the decimal expansion of transcendental number is obtained.

Background Moyamoya vasculopathy, arising secondary to tubercular meningitis (TBM) is unusual. There have also been a few reports of cerebral venous sinus thrombosis (CVST) in TBM. A case of TBM, complicated simultaneously by Moyamoya syndrome and CVST, is being presented here. Case A 1-year-old girl presented with febrile encephalopathy, vomiting, seizures and left hemiparesis. Cerebrospinal fluid analysis was suggestive of TBM. Extensive infarcts were noted in the magnetic resonance imaging, involving right middle cerebral artery (MCA), anterior cerebral artery and the left MCA. Magnetic resonance venogram revealed left transverse venous sinus thrombosis and magnetic resonance angiography showed bilateral moyamoya pattern of arteriopathy. Patient was started on antitubercular therapy and low molecular weight heparin. Conclusions Early vascular involvement affecting both arterial and venous structures has not hitherto been reported in CNS tuberculosis. Early recognition of secondary complications of CNS tuberculosis is crucial to prevent the morbidity and mortality associated with TBM.

The main objective of this paper is to develop a simple and robust secure encryption scheme with digital signature. In this paper a cryptosystem with digital signature using the decimal expansion of an irrational number is obtained. Mathematics Subject Classication: 11T71, 14G50, 68P25, 68R01

A high isolation Diplexer with Pentagonal Open Loop Resonators (P-OLR) is presented in this paper. The Diplexer contains two resonators providing pass bands in the desired frequency, thus attaining significant size reduction. The P-OLR offers several design freedoms, such as the pass band frequency can be adjusted by properly tuning its geometrical parameters and its bandwidth can be controlled through changing the coupling coefficients between the T-shaped feed and the resonator. To verify the designed method a P-OLR diplexer operating at the Wi-Fi bands is successfully designed and fabricated on FR4 epoxy. The maximum insertion loss of two pass bands is 1.5 dB and the isolation between channels at the pass bands higher than 25 dB.

Gastrointestinal stromal tumors (GISTs) are mesenchymal tumors that can arise in any part of gastrointestinal tract. It is commonly seen in the fifth or sixth decade of life with slight male preponderance.Intussusception and subsequent obstruction is a very uncommon presentation of these lesions because of their tendency to grow in an extraluminal fashion. In the literature, very few cases of small bowel intussusceptions from a stromal tumor in adults have been described. We report a rare case of GIST presenting as acute intestinal obstruction due to intussusception in an elderly male.

The main object of this paper is to present a mutual authentication protocol that guarantees security, integrity and authenticity of messages, transferred over a network system. In this paper a symmetric key cryptosystem, that satisfies all the above requirements, is developed using theorems of J.R. Chen, I.M. Vinogradov and Fermat and the decimal expansion of an irrational number.

Scimitar syndrome is a rare congenital anomaly characterized by anomalous pulmonary venous drainage to the inferior vena cava, causing a left-to-right shunt. Six patients with scimitar syndrome were diagnosed in our hospital between 2002 and 2008. There were 4 girls and 2 boys; 4 < 5 kg in weight, 2 < 8 kg in weight. Scimitar syndrome was suspected in 5 cases because of dextroversion, and diagnosed by color Doppler echocardiography in all 6 when a scimitar vein was detected entering the inferior vena cava. Computed tomography confirmed the diagnosis in all patients. Two patients had horseshoe lung, 2 had a unilobar right lung, 1 had a hypoplastic right lung, and 1 had a hypoplastic right lower lobe. Three patients had severe pulmonary arterial hypertension, 2 had moderate pulmonary arterial hypertension, and one had normal pulmonary arterial pressure. All patients had lower respiratory tract infections, volume loss of the right lung, a normal or hyperinflated left lung, dextroversion of the heart, and scimitar arteries from the descending aorta. Pneumonectomy was performed in 3 patients, lobectomy in 1, ligation of anomalous vessels in 1, and 1 died before surgery.

The main reason of Cirrhosis is the formation of thickened cell line with proteins called as FIBROTICS. Fibrosis means formation of excess of tissue as in a reparative or reactive process. Chronic scarring with liver results in damage to the reparative nodules which is severe and non-reversible. If it is allowed to continue, the buildup of scarred tissue can eventually stop the functions of the liver. Perisinusoidal space in the regenerative nodules has stellate cells which are present below the Hepatocytes and above the Sinusoid. Sinusoid carries the blood along with other cells. The stellate cells in the perisinusoidal space contain vitamin A (quiescent) which get activated after injury. These cells secrete TGF-β and produce collagen. In normal state liver carries wound healing process but when comes to constant injury, the collagen with fibrosis makes the stellate cells to enlarge resulting in the compression of the sinusoid. It creates a pressure in the sinusoid which moves the fluid from the sinusoid to peritoneal cavity that causes ASCITES, the one of the symptoms of cirrhosis. Further enlargement will cause congestive splenomegaly. This is the main reason for the diversion of blood to portosystemic shunt. This finally results in hepatorenal failure (liver failure). Our idea is to bring permanent cure and prevention to the liver cirrhosis by using Nano-robots. A Nano-robot is designed by ELECTRIC-BIOSENSOR. Mostly the nanoparticles present in the samples are used. Drugs like aspirin, dicumarol, and arsenicals destroy the vitamin A. The Nanobots carrying these samples detect the vitamin A and subsequently inactivates them. This leads to shrinking of the cells in the liver and cures the liver cirrhosis. It prevents the liver cirrhosis in starting stage itself.

A 3½ years old mongrel female cat was brought with the history of inappetence, seizure and lateral recumbency since 4 days and motion sickness since 2 days. Faecal examination confirmed Toxocara cati and Ancylostoma tubaeforme along with un-hatched live Toxocara cati larvae. Treatment has been initiated with Pyrantel pamoate and along with supportive therapy.

Aim and Objectives: The aim of the study is to analyse and utilize regarding the gestational diabetes in the prescription given in the Gynaecology department of a tertiary care Hospital .To get an insight into the current pattern of prescriptions in Gestational Diabetes. Materials and Methods: A Prospective study has been carried out for a period of 6 months(December 2016- April2017) in a Tertiary Care Hospital Tamilnadu Maternity Government Hospital located at Chennai.50 patients were diagnosed with Gestational Diabetes .The case sheets of the patients are thoroughly studied. Results and Discussion: Total of 50 gestational diabetes patients were studied. Among the study population age was ranging from 20-30 years. The number of patients ranging from 20-30 years were 37 (74%), and the number of patients ranging from 30-40 years were 13 (26%).The Route of Administration in GDM are done by two routes. The oral dosage Form (22%) and another is subcutaneous dosage form (88%).The Trimester of GDM are found among Patients. Conclusion: According to the survey GDM mainly occurs in the age ranging from 20-30 years and also they are more commonly affected in the Second Trimester (3-6 months) of Pregnancy. Insulin is found to be more safe than compered to oral Hypoglycaemic drugs because the drugs which contain Molecular Weight less than 500 Da crosses the Placental barrier. Insulin molecular weight is greater than 1000 Da, so it do not cross the placenta. The study found that insulin are potent and safe. So, they are prescribed in extensively in GDM.

Interference coordination and Resource allocation has emerged as one of the most attractive techniques for combating interference in next generation cellular networks, such as the 3GPP UTRAN Long Term Evolution (LTE), which operates with universal frequency reuse in order to exploit the whole frequency bandwidth in each cell. Inter-cell interference caused by simultaneous transmissions scheduled on the same frequency resources by nearby base stations (BSs), particularly limiting the performance of user equipments (UEs) located at the cell-edges. Cooperative communications may improve the reliability of transmissions, but can also be prejudicial if relays are strongly interfered. In this paper we propose resource allocation modes for relays and reduce both interference and energy consumption. Simulation results show how our proposed allocation modes permit to outperform classical modes in terms of cooperation effectiveness, power consumption and perceived Quality of Service.

Single molecular layers of molybdenum disulphide in suspension in water can be collected at a water-organic liquid interface if mixed well with an immiscible organic liquid. Techniques are described for depositing thin (30–350A˚), highly oriented optical quality films of restacked MoS 2 on a variety of substrates. Characterization of the MoS 2 films with X-ray diffraction and optical absorption are described. The same techniques are successfully applied in depositing oriented films of unexfoliated MoS 2 and WS 2 powder.

The I–V characteristics of metal-insulator-semiconductor (MIS) and photoelectrochemical (PEC) solar cells fabricated on passivated and unpassivated p-silicon samples are used to study the effects of atomic hydrogen passivation of dislocations in Si. Upon passivation, both types of cells show a dramatic decrease in the reverse dark current. In general, the open circuit voltage V oc , the fill factor FF, and the short circuit current I sc are also improved. Occasionally, anomalous I–V characteristics were observed in some passivated samples indicating the possibility of acceptor neutralization by atomic hydrogen. This effect may complicate the interpretation of the experimental results, in terms of a dislocation conductivity model. Identifying specific effects of hydrogenation of dangling bonds on the conductivity and the density of recombination centers in dislocations is, thus, hampered.