Explore the vast range of titles available.

The increasing need for high-performance computing, preservation, and networking capabilities to support corporate and scientific applications is driving a rapid expansion in the use of cloud computing server farms. Virtual machine (VM) consolidation plays a crucial role in this context, involving the direct migration of VMs from underutilized physical servers to optimize power consumption efficiency, operational costs, and reduce CO2 emissions. A pivotal step in VM consolidation is the detection of host overload, which aims to predict potential server over-subscription with VMs. This paper introduces an Optimized Support Vector Regression model for overloaded detection. To enhance the Support Vector Regression (SVR) performance, optimal selection of SVR parameters is achieved using the Enhanced Tasmanian Devil Optimization algorithm. Following overload detection, VM migration occurs, but this process raises concerns about system integrity and data confidentiality. To address these concerns, data is encrypted using the Cyclic Shift Transposition Algorithm before migration. The proposed approach’s performance is evaluated across various metrics such as energy consumption, ESV, Migration, and SLA X0.001, and its effectiveness is compared with different existing methods.

The utilization of cloud computing server farms is developing quickly, and the interest in high-performance computing (HPC), stockpiling, and systems administration assets for business and logical applications is expanding. Virtual machine (VM) coordination includes the immediate migration of VMs running on fewer physical servers, accordingly permitting more workers to be killed or running in low force mode to improve power utilization proficiency, working expense, and CO2 emanations. A significant advance in VM reconciliation is the location of the host over-burden, which endeavors to anticipate whether the physics server will over-subscribe with VMs. For overloaded detection, in this paper optimized support vector regression (OSVR) model is proposed. Here, to enhance the performance of support vector regression (SVR), the parameters of SVR are optimally selected by using the Oppositional Beetle Swarm Optimization (OBSO) algorithm. After the overloaded detection, the virtual machines are migrated. However, during migration, the system integrity and confidentiality of data may be affected. To avoid the problem, before migration, the data are encrypted using Cyclic Shift Transposition Algorithm (CSTA). The performance of the proposed approach is analyzed in terms of different measures and effectiveness compared with different methods. The results shows that our proposed approach attained the minimum migration and energy consumption.

IntroductionRecent evidence has questioned the advantage of local anesthetic (LA) combinations. This study tested the hypothesis that mixing rapid-onset (lidocaine) and long-duration (bupivacaine) LA would provide faster onset of complete conduction blockade (CCB) compared with bupivacaine alone and longer duration of analgesia compared with lidocaine alone during low-volume (20 mL) ultrasound-guided (USG) supraclavicular brachial plexus block (SCBPB).MethodsSixty-three patients receiving USG-SCBPB were randomly allocated into: group L: 20 mL 2% lidocaine with epinephrine 1:200 000; group B: 20 mL 0.5% bupivacaine; group LB: 20 mL of equi-volume mixture of both drugs. Sensory and motor blockade was recorded on a three point sensory and motor assessment scale at 10 min intervals for up to 40 min and the total composite score (TCS) at each time point was determined. The duration of analgesia was also noted.ResultsThe mean time to CCB of group LB (16±7 min) was comparable (p>0.05) with group L (14±6 min) and group B (21±8 min) in patients who were attained CCB. However, the proportion of patients attaining complete conduction block (TCS=16/16) was significantly lower (p=0.0001) in group B (48%) when compared with group L (95%) and group LB (95%) at the end of 40 min. The median (IQR) duration of postoperative analgesia was longest in group B; 12.2 (12–14.5) hours, followed by group LB 8.3 (7–11) hours and 4 (2.7–4.5) hours in group L.ConclusionAt 20 mL LA volume, equal mixture of lidocaine and bupivacaine provided significantly faster onset of CCB compared with bupivacaine alone and longer duration of postoperative analgesia compared with lidocaine alone but shorter than bupivacaine alone during low-volume USG-SCBPB.Trial registration numberCTRI/2020/11/029359.

The black clam ( Villorita cyprinoides Gray, 1825) is the most commercially important clam in India and the major share of its landing (around 25,000 tonnes/year) comes from Kochi backwaters (KBW), the largest estuarine system on the west coast of India, where approximately 4000 fishermen harvest them year-round. This study based on recent and historical data sets, comprehended how multiple anthropogenic stressors impact the black clam distribution in the KBW. In the first part, a recent data set from an extensive hydrographic and sediment sampling from 22 locations in the central and southern sections of the KBW during the Pre-Monsoon (March), Southwest Monsoon (July), and Northeast Monsoon (December) was introduced to demarcate the most conducive salinity and sediment textural conditions of black clam. Black clam in the KBW prefer midstream and upstream regions with mesohaline to oligohaline conditions and sand-dominant substratum, but their current distribution is shaped by multiple anthropogenic stressors, notably the consequence of the installation of the Thannermukkom Barrage (TB) in 1975 to prevent saltwater intrusion for paddy cultivation. The combination of current and historical data, supplemented with literature, demonstrates that TB generated various stressors on the natural distribution, resulting in a decrease in the abundance of black clam in the KBW. This includes (a) shrinkage and relocation of their most preferred salinity zones (mesohaline) for spawning from the south of TB (Vembanad) to the north of TB, (b) the increased siltation due to stagnancy in the Vembanad caused by TB increased the contribution of finer particles especially clay in the bottom substratum, which is less preferred over sand by black clam and (c) the opening and closing of the TB shutters cause salt shock causing vast mortality of black clam on both sides of TB. Secondary stressors of TB are affected by (a) poor water quality, eutrophication, and massive spread of hyacinth mats, making it difficult for local fishermen to exploit the black clam resource, and (b) overexploitation of the black clam in certain areas due to shrinkage in the total area and relocation of the conducive spawning environment in KBW.

To use batteries as large-scale energy storage systems it is necessary to measure and understand their degradation in-situ and in-operando . As a battery’s degradation is often the result of molecular processes inside the electrolyte, a sensing platform which allows to measure the ions with a high spatial resolution is needed. Primary candidates for such a platform are NV-centers in diamonds. We propose to use a single NV-center to deduce the electric field distribution generated by the ions inside the electrolyte through microwave pulse sequences. We show that the electric field can be reconstructed with great accuracy by using a protocol which includes different variations of the free induction decay to obtain the mean electric field components and a pulse sequence consisting of three polarized π -pulses to measure the electric field’s standard deviation σ E . From a semi-analytical ansatz we find that for a lithium ion battery there is a direct relationship between σ E and the ionic concentration. Our results show that it is therefore possible to use NV-centers as sensors to measure both the electric field distribution and the local ionic concentration inside electrolytes.

This study investigates the effects of hot-pressing temperatures on the dielectric, ferroelectric, and energy storage properties of solvent-casted Poly (vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) films. The hot-pressing process enhances the crystallinity and alignment of polymer chains, directly affecting their electrical properties. The aim is to optimize the performance of PVDF-TrFE films for potential energy storage devices. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) analysis were used to investigate phase formation and the fraction of β-phase. The presence of the β-fraction inside the copolymer is crucial for multifunctional applications. The scanning electron microscopy (SEM) analysis verified the uniform and glossy surface of the P(VDF-TrFE) film. The dielectric, ferroelectric, and piezoelectric properties were found suitable for energy storage and harvesting applications. The remnant polarisation (Pr) and coercive field (Ec) in the ferroelectric hysteresis loop were affected by β-fraction and crystallinity.

Flooding and other natural disasters threaten human life and property worldwide. They can cause significant damage to infrastructure and disrupt economies. Tamil Nadu coast is severely prone to flooding due to land use and climate changes. This research applies geospatial tools and machine learning to improve flood susceptibility mapping across the Tamil Nadu coast in India, using projections of Land Use and Land Cover (LULC) changes under current and future climate change scenarios. To identify flooded areas, the study utilised Google Earth Engine (GEE), Sentinel-1 data, and 12 geospatial datasets from multiple sources. A random forest algorithm was used for LULC change and flood susceptibility mapping. The LULC data are classified for the years 2000, 2010, and 2020, and from the classified data, the LULC for years 2030, 2040, and 2050 are projected for the study. Four future climate scenarios (SSP 126, 245, 370, and 585) were used for the average annual precipitation from the Coupled Model Intercomparison Project 6 (CMIP6). The results showed that the random forest model performed better in classifying LULC and identifying flood-prone areas. From the results, it has been depicted that the risk of flooding will increase across all scenarios over the period of 2000–2100, with some decadal fluctuations. A significant outcome indicates that the percentage of the area transitioning to moderate and very high flood risk consistently rises across all future projections. This study presents a viable method for flood susceptibility mapping based on different climate change scenarios and yields estimates of flood risk, which can provide valuable insights for managing flood risks.

ABSTRACT Background and Aims: Sciatic nerve block at the popliteal level for lower limb procedures provides unpredictable success rates even with ultrasonographic (USG) guidance. This study aimed to compare USG-guided single-point versus two-point injection techniques. Methods: Sixty patients posted for foot surgeries under USG-guided sciatic nerve block were randomised into Group Single Point, receiving a single injection of 20 mL of 1.5% lignocaine with adrenaline just proximal to the sciatic nerve bifurcation, and Group Double Point, receiving two injections of 10 mL of 1.5% lignocaine with adrenaline, one at the point similar to the first group and a second injection 6 cm above the first point. Sensory blockade onset, time to complete sensory blockade, time to complete motor blockade, length of the nerve exposed and analgesia duration were evaluated. Statistical analysis was performed with Statistical Package for the Social Sciences (SPSS) statistics version 20 software. Results: Double-point injection technique showed a significantly faster time to complete motor blockade [14.46 (9.93) min], increased length of nerve exposed to local anaesthetic [23.23 (7.209) cm] and extended duration of analgesia [420.40 (99.34) min] compared to the single-point injection technique [20.89 (12.62) min, 18.78 (5.95) cm and 344.28 (125.97) min, respectively]. The onset of sensory blockade and the time to complete sensory blockade were comparable between the two groups. Conclusion: USG-guided popliteal sciatic nerve block with a double-point injection technique does not significantly shorten the time to complete the sensory block. However, the time to complete motor nerve block and duration of analgesia are prolonged significantly, which may be clinically beneficial for postoperative analgesia.

Background and Aims: Myofascial pain syndrome (MPS) is a common cause of chronic musculoskeletal pain, characterised by myofascial trigger points (TPs). TP injection is an established technique for management of MPS. In this study, we analysed the efficacy of myofascial TP injection of lignocaine and the influencing biomechanical factors on MPS. Methods: After obtaining ethical committee approval, we included the first 100 adult patients of MPS with failed physical therapy aged above 18 years, and with TPs in the trapezius, infraspinatus, and/or the levator scapulae muscles and Visual analog scale (VAS) >4. TP injection of 2% (2 ml) lignocaine was performed. Visual analogue scale (VAS) scores were recorded immediately and after 1 month. Number of repeat TP injections and use of oral analgesic in one month was noted. Results were analysed with the analysis of variance test. Results: The mean VAS reduced significantly both immediately and 1 month after therapeutic injections (8.57 ± 0.77, 2.67 ± 1.43 and 2.82 ± 1.4, respectively, P < 0.01). Keeping the palm below the head during sleep was the major contributing factor for myofascial TP, followed by slanting the neck to use mobile phones. Repeat TP injection was used in 4% of cases. Conclusion: TP injection of 2 ml of 2% lignocaine along with correction of predisposing biomechanical factors provided significant pain relief for MPS in patients with failed physical therapy without any side effects.