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Conserving energy of sensor nodes and ensuring balanced workloads among them are fundamental concerns in Wireless Sensor Network (WSN) design. Clustering strategies offer a promising avenue to minimize node energy consumption, thereby prolonging network lifespan. Nevertheless, numerous multi-hop routing protocols using clustering technique face the challenge of nodes nearer to the Base Station (BS) depleting their energy faster due to forwarding data from the entire network leading to premature node failure and network partitioning known as ‘hotspot problem’. The paper introduces an Energy-Efficient Mega-Cluster-Based Routing (EEMCR) protocol specially designed for expansive coverage area. The primary principle behind designing this protocol is to eliminate the hotspot problem and restrict the transmission range of nodes to the threshold distance defined by the radio energy model, thereby enhancing the overall network lifespan. The protocol adopts a centralized approach employing fixed clustering wherein the BS partitions the network into square-shaped clusters. The cluster size is determined by the threshold transmission range of the sensor radio energy model, guaranteeing that all network communication stays within this threshold distance. Four such clusters form a mega-cluster with a Mega-Cluster-Head (MCH) elected among the four Cluster Heads (CHs). The MCH role is evenly distributed among nodes of all four clusters in subsequent rounds for uniform distribution of its overhead. Implementing data aggregation at two levels (CH level as well as MCH level) leads to reduced data traffic and energy consumption throughout the network. Moreover, data collection by two data mules based on odd–even round number ensures balanced data traffic and energy distribution across the network. Analysis indicates that the proposed protocol effectively mitigates the hot-spot problem and reduces data transmission overhead of sensor nodes. In simulation, the proposed protocol on an average improves network life by 34.5%, 23.5%, 14.5% and 5.5% as compared to existing protocols FCEEC, DBSCAN, LPGCR and FBECS respectively for deployment of nodes between 600 to 1200. Also, approximately 46%, 32%, 21% and 14% of lesser sensor nodes are dead for proposed protocol in respective rounds as compared to existing protocols FCEEC, DBSCAN, LPGCR and FBECS respectively. Comparative evaluations demonstrate improved network lifetime when compared to equivalent recent routing protocols.

This study investigates seasonal variations and influencing factors on the Deep Chlorophyll Maximum (DCM) in the Subtropical Front (STF) and Polar Front (PF) regions of the Indian Sector within the Southern Ocean, utilizing Bio-Argo floats data. Our analysis reveals distinct seasonal and regional patterns in salinity, temperature, and DCM dynamics. The STF region, characterized by warmer, saltier waters and a shallower Mixed Layer Depth (MLD), facilitates stronger stratification and nutrient retention, resulting in an enhanced DCM of 1.55 mg/m 3 . In contrast, the PF’s colder, fresher waters exhibit deeper MLDs and reduced stratification, leading to lower mean DCM concentrations of 0.88 mg/m 3 . The depth of the DCM increased along this gradient, deepening from a median of 42 m at the STF to 78 m at the PF. We identify a robust correlation between DCM, Photosynthetically Active Radiation (PAR), and MLD, highlighting how environmental conditions profoundly influence DCM and its depth in these critical oceanic zones. This study shows that the DCM is present year-round in the STF, while it exhibits seasonal variability in the PF.

This context is about enhancing the freshwater production of a single slope solar desalination still (SSSDS) using water film cooling over the glass cover and using hybrid natural fibre composite (HNFC) insulation. In contrast to the conventional insulations, we proposed the HNFC insulation; this composite was made of natural fibre Pharsalus vulgaris (6 %) and nano-silica (1 %) with unsaturated polyester resin. In this study, conventional SSSDS and proposed SSSDS with enhanced evaporation and condensation have been designed. The same was built with native materials. A conventional and proposed type SSSDS was subjected to the same experimental condition. The experimental result showed that using water film cooling over glass cover and HNFC insulation at 0.5 cm depth caused a 35% increase in the amount of distilled water when compared with the conventional type SSSDS with polystyrene—Styrofoam (thermocol) insulation. Water film cooling over glass cover and HNFC insulation at 1 cm depth caused a 21% increase in the amount of distilled water when compared with the conventional type SSSDS with thermocol insulation. The conventional type solar desalination still with thermocol insulation at 0.5 and 1 cm depth yields are 1.665 and 1.171 l/m 2 /day, respectively, and the proposed solar desalination still with water film cooling over glass cover and HNFC insulation at 0.5 and 1 cm depth yields are 2.253 and 1.420 l/m 2 /day, respectively.

The Southern Ocean (SO) plays a critical role in global ocean productivity and carbon cycling. Bio-Argo floats deployed in the Indian sector of the Southern Ocean provides new insights into the biogeochemical processes. Here we report significantly higher dissolved oxygen(DO) (~ 310 μmol/kg) in summer of 2014–2015 for one float (F1) and winter of 2014 in other float (F2) at sub-surface layer in the subantarctic region of the SO. The summer DO peak in F1 was 10% higher than those during the summer of succeeding year, while the winter DO peak in F2 was 20% higher than those during the winter of succeeding year. Temperature and dynamic height structure show that cyclonic eddies play an important role in the observed increase in the dissolved oxygen: the high DO is a manifestation of the co-occurrence of a cold core eddy which transported the cold oxygen rich water from deep to the surface during winter, while, during summer, the high chlorophyll below the mixed layer depth (MLD) also contributed to the elevated DO. Low apparent oxygen utilisation suggests that the observed high oxygen concentration was due to high production rates over the consumption.

Purpose Among the several therapeutic agents available for the management of diabetes mellitus, sulfonylureas such as gliclazide have several advantages. The hypoglycemic effect and bioavailability of gliclazide loaded in Isabgol husk mucilage microparticles were assessed. The hypoglycemic effect of drug-loaded microparticles was compared with that of pure gliclazide. Methods Gliclazide was incorporated into Isabgol husk mucilage microparticles using an emulsification-crosslinking technique. Gliclazide characterization was performed using a chromatographic method. Results Gliclazide loading in the microparticles was up to 91.23 ± 0.981% w/w. The pharmacokinetic parameters for pure gliclazide (control) were different from those of gliclazide loaded in microparticles (test). After oral administration, the AUC 0–24 h of gliclazide in blood samples of the control and test groups was 10.840 ± 0.018 and 17.608 ± 0.035 μg/(mL h), respectively. In 24 h after oral administration, the percentage reduction from the baseline glucose level in diabetic rabbits was 36.66 ± 4.509% and 98.11 ± 1.018% for the test and control groups, respectively. Conclusion The prolonged hypoglycemic effect and increased bioavailability of gliclazide loaded in Isabgol husk microparticles compared with those of pure drug indicate the applicability of the microparticulate formulation as a novel anti-diabetic drug delivery system.

Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo . To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data.