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Respiratory infections by RNA viruses are one of the major burdens on global health and economy. Viruses like influenza or coronaviruses can be transmitted through respiratory droplets or contamina...

Study was done to look for the future neurodevelopmental outcome of the babies with extremely high serum bilirubin level at 1st week of life. Fifty one term and near term babies were enrolled with features of acute bilirubin encephalopathy (ABE), with bilirubin level more than20mg/dl. They were followed up at 3rd and 6th month to observe their neurodevelopment. Neurological outcome was measured with Denver Development Screening Test (DDST-II) and brainstem evoked response audiometry (BERA). The mean peak total serum bilirubin (TSB) was 25.3±2.35(mg/dl). Abnormal developmental was found in 23.5% babies (12 out of 51) and abnormalities were more in the babies whose TSB was beyond 28mg/dl. Abnormal BERA was found among 13.7% babies. TSB value below 25 mg/dl can be considered as safe cut off value for reversibility of bilirubin induced acute brain damage.

As newer variants of SARS-CoV-2 continue to pose major threats to global human health and economy, identifying novel druggable antiviral targets is the key towards sustenance. Here, we identify an evolutionary conserved “E-L-L” motif present within the HR2 domain of all human and non-human coronavirus spike (S) proteins that play a crucial role in stabilizing the post-fusion six-helix bundle (6-HB) structure and thus, fusion-mediated viral entry. Mutations within this motif reduce the fusogenicity of the S protein without affecting its stability or membrane localization. We found that posaconazole, an FDA-approved drug, binds to this “E-L-L” motif resulting in effective inhibition of SARS-CoV-2 infection in cells. While posaconazole exhibits high efficacy towards blocking S protein-mediated viral entry, mutations within the “E-L-L” motif rendered the protein completely resistant to the drug, establishing its specificity towards this motif. Our data demonstrate that posaconazole restricts early stages of infection through specific inhibition of membrane fusion and viral genome release into the host cell and is equally effective towards all major variants of concerns of SARS-CoV-2 including beta, kappa, delta, and omicron. Together, we show that this conserved essential “E-L-L” motif is an ideal target for the development of prophylactic and therapeutic interventions against SARS-CoV-2.

The canonical theory of star formation in a magnetized environment predicts the formation of hourglass-shaped magnetic fields during the prestellar collapse phase. In protostellar cores, recent observations reveal complex and strongly distorted magnetic fields in the inner regions that are sculpted by rotation and outflows. We conduct resistive, nonideal magnetohydrodynamic simulations of a protostellar core and employ the radiative transfer code POLARIS to produce synthetic polarization segment maps. A comparison of our mock-polarization maps based on the toroidal-dominated magnetic field in the outflow zone with the observed polarization vectors of SiO lines in Orion Source I shows a reasonable agreement when the magnetic axis is tilted at an angle θ = 15° with respect to the plane of the sky and if the SiO lines have a net polarization parallel to the local magnetic field. Although the observed polarization is from SiO lines and our synthetic maps are due to polarized dust emission, a comparison is useful and allows us to resolve the ambiguity of whether the line polarization is parallel or perpendicular to the local magnetic field direction.

Modelling the magnetic field in prestellar cores can serve as a useful tool for studying the initial conditions of star formation. The analytic hourglass model of Ewertowski and Basu (2013) provides a means to fit observed polarimetry measurements and extract useful information. The original model does not specify any radial distribution of the electric current density. Here, we perform a survey of possible centrally-peaked radial distributions of the current density, and numerically derive the full hourglass patterns. Since the vertical distribution is also specified in the original model, we can study the effect of different ratios of vertical to radial scale length on the overall hourglass pattern. Different values of this ratio may correspond to different formation scenarios for prestellar cores. We demonstrate the flexibility of our model and how it can be applied to a variety of magnetic field patterns., Comment: 14 pages, 6 figures

The objective of the study is to compare the fracture resistance of endodontic treated tooth restored with GIC, amalgam, and composite cements.Forty teeth were divided into 4 groups of 10 teeth each. Group I teeth were restored with silver amalgam. Group II teeth were restored with GIC. Group III teeth were restored with composite and Group IV teeth were control in which no alteration was performed. Testing machine applied force on teeth to detect fracture resistance.The mean fracture resistance was maximum in Group IV (1050.2 N) followed by Group III (956.2 N), Group I (836.4 N), and Group II (766.4 N). The difference was statistically significant (Composite resin possesses highest fractures resistance as compared to GIC and silver amalgam.

There are various natural havocs where human lives and belongings are always susceptible to certain life threats. Here, fire outbreak is taken intoconsideration in respect of home which can be major havoc in terms of human loss and belongings. To prevent and avoid such fire outbreak, we need to cover certain fire parameters like temperature, flame, and smoke, as these parameters help to create an alert whenever there is an outbreak of fire. This paper aims at designing and implementing a low-cost system for real-time monitoring of fire alert system using an IoT platform. The proposed system deals in controlling various conditions for fire outbreak through sensors implemented and the final data collected after analysis are then sent to the webserver and can be accessed over the internet to find out the outcome. This paper projects on Sensor-Based Smart Home (SBSH) fire Monitoring techniques which measure various parameters, i.e., smoke, flame, and temperature of a fire in the home. The Controller Arduino UNO and NodeMCU are used to process the values collected from various sensors. Finally, the sensor data can be viewed graphically using ThingSpeak API. The main purpose of the paper is to achieve a smart home monitoring system with high frequency, real values, and low power.

Ocean melting has thinned Antarctica’s ice shelves at an increasing rate over the past two decades, leading to loss of grounded ice. The Ross Ice Shelf is currently close to steady state but geological records indicate that it can disintegrate rapidly, which would accelerate grounded ice loss from catchments equivalent to 11.6 m of global sea level rise. Here, we use data from the ROSETTA-Ice airborne survey and ocean simulations to identify the principal threats to Ross Ice Shelf stability. We locate the tectonic boundary between East and West Antarctica from magnetic anomalies and use gravity data to generate a new high-resolution map of sub-ice-shelf bathymetry. The tectonic imprint on the bathymetry constrains sub-ice-shelf ocean circulation, protecting the ice shelf grounding line from moderate changes in global ocean heat content. In contrast, local, seasonal production of warm upper-ocean water near the ice front drives rapid ice shelf melting east of Ross Island, where thinning would lead to faster grounded ice loss from both the East and West Antarctic ice sheets. We confirm high modelled melt rates in this region using ROSETTA-Ice radar data. Our findings highlight the significance of both the tectonic framework and local ocean–atmosphere exchange processes near the ice front in determining the future of the Antarctic Ice Sheet. The boundary between West and East Antarctica is a tectonic feature that bisects the Ross Ice Shelf. This boundary constrains ocean circulation under the ice, which affects ice stability, according to airborne survey data and ocean simulations.

Mobile ad hoc networks does not have fixed infrastructure and nodes are dynamically formed different network topologies. These nodes are establishing communication through wireless links. The energy is a vital parameter for this network, as battery life decides the overall working of the network. Failure of one node not only affects itself but also the performance of the entire network. Since all the nodes are battery power therefore energy depletion is one of the major issues to the lifetime of the network. In this paper we propose a back up node for area coverage of the Ad hoc network that enhanced the proper use of energy by reducing the communication with the help of triangulation technique. Therefore, the use of battery power will be minimized which results in increasing the lifetime and better connectivity of the network.

Ambipolar diffusion likely plays a pivotal role in the formation and evolution of dense cores in weakly-ionized molecular clouds. Linear analyses show that the evolutionary times and fragmentation scales are significantly greater than the hydrodynamic (Jeans) values even for clouds with mildly supercritical mass-to-flux ratio. We utilize values of fragmentation scales and growth times that correspond to typical ionization fractions within a molecular cloud, and apply to the context of the observed estimated lifetime of prestellar cores as well as the observed number of such embedded cores forming in a parent clump. By varying a single parameter, the mass-to-flux ratio, over the range of observationally measured densities, we fit the range of estimated prestellar core lifetimes ($\sim 0.1$ to a few Myr) identified with Herschel as well as the number of embedded cores formed in a parent clump measured in Perseus with the Submillimeter Array (SMA). Our model suggests that the prestellar cores are formed with a transcritical mass-to-flux ratio and higher densities correspond to somewhat higher mass-to-flux ratio but the normalized mass-to-flux ratio $\mu$ remains in the range $1 \lesssim \mu \lesssim 2$. Our best-fit model exhibits $B \propto n^{0.43}$ for prestellar cores, due to partial flux-freezing as a consequence of ambipolar diffusion., Comment: Accepted For Publication in Astronomy & Astrophysics Letters, 9 pages, 5 figures

We perform a linear analysis of the stability of isothermal, rotating, magnetic, self-gravitating sheets that are weakly ionized. The magnetic field and rotation axis are perpendicular to the sheet. We include a self-consistent treatment of thermal pressure, gravitational, rotational, and magnetic (pressure and tension) forces together with two nonideal magnetohydrodynamic (MHD) effects (Ohmic dissipation and ambipolar diffusion) that are treated together for their influence on the properties of gravitational instability for a rotating sheet-like cloud or disk. Our results show that there is always a preferred length scale and associated minimum timescale for gravitational instability. We investigate their dependence on important dimensionless free parameters of the problem: the initial normalized mass-to-flux ratio $\mu_0$, the rotational Toomre parameter $Q$, the dimensionless Ohmic diffusivity $\tilde{\eta}_{\rm OD,0}$, and the dimensionless neutral-ion collision time $\tilde{\tau}_{\rm{ni,0}}$ that is a measure of the ambipolar diffusivity. One consequence of $\tilde{\eta}_{\rm OD,0}$ is that there is a maximum preferred lengthscale of instability that occurs in the transcritical ($\mu_0 \gtrsim 1$) regime, qualitatively similar to the effect of $\tilde{\tau}_{\rm{ni,0}}$, but with quantitative differences. The addition of rotation leads to a generalized Toomre criterion (that includes a magnetic dependence) and modified lengthscales and timescales for collapse. When nonideal MHD effects are also included, the Toomre criterion reverts back to the hydrodynamic value. We apply our results to protostellar disk properties in the early embedded phase and find that the preferred scale of instability can significantly exceed the thermal (Jeans) scale and the peak preferred fragmentation mass is likely to be $\sim 10- 90 \ M_{\rm Jup}$., Comment: 30 pages, 17 figures. Accepted for publication by ApJ

Internet of things (IoT) is an integrated system where in physical devices share and exchange data and information in an wireless mode over Internet. IoT-based fire alert system using supervised machine learning approach is a way that can be used as a preventive measure in home and industrial areas to notify the fire at the earliest to the corresponding units for quick action. Here, in the fire alert system as discussed in this chapter, it is being built using Arduino UNO which has an interface of temperature sensor, a smoke sensor, and flame. The temperature sensor and the smoke sensor as designed here sense the heat and smoke whenever generated from burning of fire. The output set of data as generated from these integrated sensors are then tested and checked through machine learning algorithms to broadcast and predict the potentiality of its desired outcome. To amalgamate the predicted output, support vector machine (SVM) and Naive Bayes algorithm have been applied. The chapter also reveals that the final outcome of the proposed approach will minimize error rates, thus making the system more reliable and accurate.

The process of controlling various operating equipment, machinery, etc., automatically can be termed as automation. This is an efficient method to use in every field to reduce manpower, energy usage, and also for improving the quality, accuracy, precision, and efficiency of any system. The home automation system helps in automating various aspects of life. The invention of advanced technologies and computing methodology helps in automating various activities in the home, often termed as a smart home. Through this automated process, the user can easily closely monitor various activities at home. The computing technologies like the Internet of Things, evolutionary algorithm, data science, and machine learning (ML) algorithms help to analyze, predict, and smartly monitor the home activities. The integration of ML and artificial intelligence (AI) is increasing day by day in managing a smart home. Home automation can help in managing energy consumption, intruder detection, fire detection, gas leakage, and any abnormal activities in and surrounding the home. For example, our home kitchens can be upgraded with the integration of AI and ML to improve the functioning of pantries, fridges, stoves, cooking, and energy efficiency. Smart fridges, cooking technology, and stoves are already emerging in the home automation industry. In this chapter, we have discussed various projects, uses, and applications of AI and ML techniques in various domains.

The Internet of Things (IoT) has become the new area of research and development for variety of applications in industrial and domestic areas. The model proposed in the paper consists of a built-in Wifi module Node MCU, an open source IoT platform, Arduino UNO controller, and programming languages along with sensor devices and network. The proposed model translates, verifies data and communicates to the server based on working principles and framework. It also develops IPv6 network environment which is capable of receiving and responding to different formats of data received from the sensors given in different formats and assess their relevance and accuracy with the help of appropriate coding and forward them to the server in a graphical format. It is assumed that the system will be used for highly emergency situation to make decisions regarding response to the fire in adverse state. The experimental results show the effectiveness and reliability of our proposed system and are illustrated with the graph where data are inserted into the ThingSpeak.com server.

Geocasting is a subset of conventional multicasting problem. Geocasting means to deliver a message or data to a specific geographical area. Routing refers to the activities necessary to route a message in its travel from source to the destination node. The routing of a message is very important and relatively difficult problems in the context of Ad-hoc Networks because nodes are moving very fast, network load or traffic patterns, and topology of the network is dynamical changes with time. In this chapter, different geocast routing mechanisms used in both Mobile Ad-hoc Networks and Vehicular Ad-hoc Networks. The authors have shown a strong and in-depth analysis of the strengths and weaknesses of each protocol. For delivering geocast message, both the source and destination nodes use location information. The nodes determine their locations by using the Global Positioning System (GPS). They have presented a comprehensive comparative analysis of existing geocast routing protocols and proposed future direction in designing a new routing protocol addressing the problem.

Mobile ad hoc networks (MANETs) provide communication of mobile nodes in an infrastructure-less environment. Factors like the mobility of nodes, dynamic topology of the nodes, path breakages, limited availability of resources, etc., affect QoS. This chapter carries important mobility models that are used for simulation. We have considered different mobility models, namely Random Way Point, Gauss Markov, Random Walk-2D, Random Direction-2D, and Constant Velocity. The parameters used for the experiment are PDR, delay, and throughput to check the impact of QoS in MANET using NS-3. It is noted that the Gauss Markov furnished better result concerning PDR and delay, whereas Constant velocity and Random Way Point model performs better for throughput among other mobility models. Researchers will be benefitted from this chapter. It will make them learn which mobility model gives better QoS support in MANET.

Background: Polycystic ovary syndrome (PCOS) is a prevalent hormonal disorder connected to ovulatory infertility and recent research indicates that different diets alter the risk of developing PCOS. Insulin resistance (IR) is one of the key pathologies which classifies PCOS. Understanding the etiology leading to IR in PCOS patients and the disorders associated with IR can allow for a therapeutic measure to be put in place to counteract the etiology and even reduce the risk of developing the disorder. Objective: The objective of this review is to identify the key factors that lead to IR so that diet and other lifestyle aspects can be used to counteract PCOS Symptoms.Design: A total of 679 studies were taken into consideration for this review, however, I performed a literature review of 75 primary papers. Data and findings from these studies were used to gain a better understanding of the dietary etiology of IR in PCOS, and this information can be used to describe a specific diet to counteract its etiology.Results: Many symptoms and disorders in the biological pathway of PCOS is associated with IR. Clinical studies have established that an increase in carbohydrates, low-density lipoproteins, and triglycerides is associated with IR in PCOS patients. Similar studies have found that a decrease in dietary proteins (especially branched chain amino acid intake), lactate, phosphatidylcholine, high-density lipoproteins, and long-chain fatty acids are also associated with PCOS patients. The drug metformin has also been associated with ameliorating many of the negative impacts imposed by IR in PCOS patients. Addressing these factors and changing diet and lifestyle (such as increased exercise) can help reduce the IR-related effects in PCOS patients.

The WSNs network is comprises of various sensors and work towards accomplishment of a certain goal. In WSNs, nodes are working with limited battery power. In this paper, we have analyzed the effect of faulty vs non-faulty nodes in the performance of the network. In our experiment certain number of node are randomly faulted for a particular duration during simulation. Analysis of performance at different layers is evaluated based on various QoS parameters like throughput, PDR and average end-to-end delay. The performance of AODV routing protocol is computed in the network layer. Other OoS parameters is computed at the Application layer. The simulation study shows that in presence of faulty sensor nodes significantly affect network performance. The throughput is degraded by 8.6 % approximate in presence of faulty node when node number is 50. The average end to end average increased by 19%. The packet delivery ratio is degraded different values for different node density; this observed that average 6% less PDR is in case of faulty node.

The fading models play a very vital role in the performance of routing protocols in Wireless Sensor Networks. The fading can significantly influence network performance. In this paper, we have used Rayleigh, Fast Rayleigh and Ricean fading models for evaluating their effect in wireless sensor networks. We have used AODV routing protocol for routing data packets from source to destination. We have computed various QoS parameters such as throughput, PDR, average end-to-end delay, jitters. The simulation results show that, throughput and PDR is highest in fast Rayleigh model. The average delay and jitters is minimum in fast Rayleigh model. Overall, the network performance is better when fast Rayleigh fading model is deployed.

Respiratory infections by RNA viruses are one of the major burdens upon global health and economy. Viruses like influenza or coronaviruses can be transmitted through respiratory droplets or contaminated surfaces. An effective antiviral coating can decrease the viability of the virus particles in the outside environment significantly, hence reducing their transmission rate. In this work, we have screened a series of nanoparticles and their composites for antiviral activity using Nano Luciferase based highly sensitive influenza A reporter virus. Using this screening system, we have identified copper-graphene (Cu-Gr) nanocomposite shows strong antiviral activity. Extensive material and biological characterization of the nanocomposite suggested a unique metal oxide embedded graphene sheet architecture that can inactivate the virion particles only within 30 minutes of pre-incubation and subsequently interferes with the entry of these virion particles into the host cell. This ultimately results in reduced viral gene expression, replication and production of progeny virus particles, slowing down the overall pace of progression of infection. Using PVA as a capping agent, we have been able to generate a Cu-Gr nanocomposite based highly transparent coating that retains its original antiviral activity in the solid form.

Dissimilar flows can be compared by exploiting the fact that all flux densities divided by their conjugate volume densities form velocity fields, which have been described as generalized winds. These winds are an extension of the classical notion of wind in fluids which puts these distinct processes on a common footing, leading to thermodynamical implications. This paper extends this notion from fluids to radiative transfer in the context of a classical two-stream atmosphere, leading to such velocities for radiative energy and entropy. These are shown in this paper to exhibit properties for radiation previously only thought of in terms of fluids, such as the matching of velocity fields where entropy production stops.

In the wireless sensor networks, energy consumption is a very crucial issue because they work through the limited battery power of individual nodes. Here, we have analyzed various energy models on the performance. Different routing protocols are used on various node densities. In WSN, if nodes battery limit once exhausted the ongoing message exchanges for any kind of work get completely discontinued. A sensor node in WSN uses battery power when they are sending, receiving, and listening ongoing communication in transmitting, receiving, idle, and sleep mode. The total energy is consumed for different activities, like routing protocols message exchanges, MAC layer operations as well as other network layers. Any kind of message exchanges required a certain amount of power. Therefore, battery life is a major concern in the network. The maximum power consumption is observed when nodes receive and transmit packets from one node to another. So, proper utilization of battery of individual nodes is always desirable in this network. The individual node battery level determines the overall network performance and lifetime. In this paper, we have used various energy models. The AODV and DSR routing protocols are used for evaluating their performance in terms of energy consumption. Our simulation results show that AODV routing protocol used less battery power as compared to DSR in all energy models.

The wireless sensor networks sensor nodes are operated through battery power; for every particular activity, amount of energy is used. The node lifetime also depends on battery life. The longer the battery life leads to a longer life of the network. So, energy utilization is crucial. In this paper, we have used location-based routing protocol and multipath routing protocol for analyzing the consumption of energy. The principal objective of this work is to analyze the performance of different categories of routing protocols in terms of energy utilization. So that appropriate routing protocol may be adapted for future communication. The total energy is consumed for various activities, like routing protocols message exchanges, MAC layer operations as well as other network layers. Any kind of message exchanges required a certain amount of power. We have analyzed power consumption for individual nodes. The AOMDV and LAR routing protocols are used to evaluate their performance in terms of energy consumption. This is evident from the result that the AOMDV routing protocol utilizes lesser battery power as compared to protocol.

Mobile Ad hoc Networks (MANETs) provides changing network topology due to the mobility of nodes. The complexity of the network increases because of dynamic topology of nodes. In a MANET, nodes communicate with each other without the help of any infrastructure. Therefore, achieving QoS in MANET becomes a little difficult. The movement of mobile nodes is represented through mobility models. These models have great impact on QoS in MANET. We have proposed a mobility model which is a 3D implementation of existing Random Direction (RD) mobility model. We have done a simulation on AODV with QoS metrics throughput, delay and PDR, using NS-3 and performed analysis of the proposed mobility models with other 3D mobility models, namely Random Way Point (RWP) and Gauss Markov (GM). It is concluded that our proposed model gives better throughput, delay and PDR for AODV routing protocol in comparing to RWP and GM mobility models. This paper is for students and researchers who are involved in wireless technology and MANET. It will help them to understand how a mobility model impacts the entire network and how its enhancement improves the QoS in MANET.

Dental implants are the preferred treatment modality in the present edentulous era. Selective serotonin reuptake inhibitors (SSRIs) have detrimental effect on bone density. The present study was conducted to determine the effect of SSRIs on the success rate of dental implants.The present study was conducted on 352 patients of both genders with 680 dental implants. History of depression and SSRI medication was retrieved. Patients were divided into two groups. Group I (110 patients, 230 dental implants) patients were on SSRI, while group II (242 patients, 450 dental implants) patients were non-SSRI. In all patients, the implant failure rate was recorded.In group I, 35 patients were50 years, while 75 were50 years of age. In group II, 60 patients were50 years, while 182 were50 years of age. The difference was significant (p0.05). Group I had 45 males and 65 females, while group II comprised of 105 males and 137 females. Group I showed 25 implant failures and group II had 21 implant failures. Age group50 years showed 12 implant failures while50 years had 13 in group I compared with 10 in patients50 years and 11 in patients with50 years of age; 56% smokers had implant in group I as compared with 60% failure in group II. In group I, 27% diabetic patients had failures as compared with 13.4% in group II. The difference was significant (p0.05). Group I showed maximum failures in terms of loosening of screw (8) followed by fracture of implant (7), peri-implantitis (6), and fracture of screw (4), whereas in group II, 7 cases were of loosening of screw, 6 cases were of fracture of screw, 5 cases of fracture of implant, and 3 cases of peri-implantitis. The difference was nonsignificant (p0.05).Selective serotonin reuptake inhibitors cause increased osteoclastic activity, leading to bone loss and implants placed in patients with history of depression are more prone to failures.Failure rates of dental implants are significantly increased in patients taking SSRIs due to depression. Careful case analysis and history of depression may minimize the failure rates.

The effect of temperature and additives on the formation and structure of Triton X-114 (TX-114) micelles were studied using cloud point (CP technique), nuclear magnetic resonance (NMR), critical micellar concentration (CMC), micropolarity, and viscosity measurements. The clouding process of 2% (w/v) aqueous TX-114 in the presence of ionic liquids (ILs) was governed by the hydrophobic nature of the alkyl chains; the more hydrophobic the IL is, the more is the effect on the clouding process. ILs with hexyl and octyl group chains showed a drastic increase in cloud points supported by the exact reversal in trend obtained for viscosity measurements. An in-depth thermodynamic analysis of the clouding process helped to determine if it was entropy or enthalpy driven in each case. CMC of TX-114 slightly increased on the addition of ILs, accounting for strong interactions between the two, leading to delay in micellization. The impact of hydrophobicity was further studied using fluorescence spectrophotometry with pyrene as a solvatochromic probe. IL with octyl chain showed an increase in polarity, which could be attributed to the chain's deeper penetration inside the micelle. 1H NMR and Dynamic Light Scattering studies further confirmed the interaction and micellar size prediction, respectively.

Meltwater stored in ponds and crevasses can weaken and fracture ice shelves, triggering their rapid disintegration. This ice-shelf collapse results in an increased flux of ice from adjacent glaciers and ice streams, thereby raising sea level globally. However, surface rivers forming on ice shelves could potentially export stored meltwater and prevent its destructive effects. Here we present evidence for persistent active drainage networks - interconnected streams, ponds and rivers - on the Nansen Ice Shelf in Antarctica that export a large fraction of the ice shelf's meltwater into the ocean. We find that active drainage has exported water off the ice surface through waterfalls and dolines for more than a century. The surface river terminates in a 130-metre-wide waterfall that can export the entire annual surface melt over the course of seven days. During warmer melt seasons, these drainage networks adapt to changing environmental conditions by remaining active for longer and exporting more water. Similar networks are present on the ice shelf in front of Petermann Glacier, Greenland, but other systems, such as on the Larsen C and Amery Ice Shelves, retain surface water at present. The underlying reasons for export versus retention remain unclear. Nonetheless our results suggest that, in a future warming climate, surface rivers could export melt off the large ice shelves surrounding Antarctica - contrary to present Antarctic ice-sheet models, which assume that meltwater is stored on the ice surface where it triggers ice-shelf disintegration. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Energy is a very crucial parameter in Mobile Ad Hoc Networks since mobile nodes are operated with this scarce resource. If nodes battery is drained, then ongoing transmission in the network is disrupted and discontinued. Mobile nodes can communicate with each other directly or multi-hop fashion. A mobile node uses battery power while working in various modes, i.e., transmitting, receiving, idle, and sleep. Routing protocols, MAC layer, and other network layers exchanges various control packets for executing their task. Overall, performance of the network indirectly depends on the battery power. So, wisely utilizing battery of individual nodes may significantly increase the network performance and lifetime. We have studied the energy utilization of individual node in the network. We have used AODV routing protocol for the analysis of individual node energy utilization in different mode of their operation. Finally, we observed that in receiving mode nodes average energy consumption is higher as compared to transmit mode operation.

The growing use of networking in almost every possible field, data transferring or data sharing has become an essential need. All kinds of users directly or indirectly involved in data transfer. But data transferring is susceptible to various risks i.e. hacking of potential data, tempering, etc. Various services based on data sharing or transferring across the network needs security and reliability of the system. Most of the stakeholders may not be fully aware about the fact that their communication is unsecure. Users are relying upon the system they are using and assume that their ongoing communication is secure.Generally, data categorized into text and image messages. There are many works on securing of text message through encryption has been achieved in last decades. But securing images are differs in many ways from that because text. Nowadays, securing image is necessary and quite in demand. In this paper, we have proposed an image encryption algorithm to secure image while being transmitted in two layers.

Ad hoc networks provides communication without the help of any fixed infrastructure. Due to dynamic topology changes, mobility of nodes and lack of central coordination routing in MANET is a challenging task. In MANET, achieving higher QoS is a hard job, various researchers are working to boost the performance. In this paper, we have done rigorous experiments on existing protocols such as AODV, DSDV, DSR, and AOMDV to expose the performance and QoS using NS2. The parameters that have been considered for experimental analysis are the throughput of the network, delay incurred, and packet delivery ratio (PDR).