Search

Abstract Aims Intra‐aortic balloon pump (IABP) devices are commonly used in patients with heart failure related cardiogenic shock (HF‐CS), including those with out‐of‐proportion right ventricular (RV) dysfunction. Pulmonary artery pulsatility index (PAPi) is a haemodynamic surrogate for RV performance. We aimed to assess short‐term haemodynamic changes in patients with HF‐CS following IABP support stratified by baseline PAPi. Methods and results This is a single‐centre study of 67 consecutive patients with HF‐CS who underwent IABP placement between 2020 and 2022. The primary aim was haemodynamic changes of specific variables on pulmonary artery catheter monitoring over 72 h following IABP placement. Secondary aims were clinically significant changes in diuretic regimens, changes in inotropes or vasopressors at 72 h following IABP, along with clinical outcomes. Prior to IABP placement, 57% of the total cohort (median age 59 years [48, 69], 31% female) had Society of Cardiovascular Angiography and Interventions Stage C HF‐CS. Thirty‐eight (56%) patients had a PAPi

An Intrusion Detection System (IDS) is a valuable tool for network security since it can identify attacks, intrusions, and other types of illegal access. Excessive and irrelevant data slows down the classification process and eventually weakens the system's capacity to make informed decisions when IDS is monitoring a huge volume of network traffic. Innovative approaches are utilized to create large amounts of data and a lot of network traffic in order to test its effectiveness. A vital step in machine learning is feature selection. By determining which features are most essential for describing the dataset and its initial attributes, feature selection seeks to improve intrusion prediction performance while simultaneously delving deeper into the stored data. Making a feature selection is similar to fixing an optimization problem without a clear definition when users don't know where to begin. Finding the fewest characteristics required to describe the dataset, the original features, and to conduct classification is the primary purpose of feature selection, which also aims to improve prediction performance and acquire a deeper understanding of the stored data. As a result, researchers have been focusing on feature-selection issues recently, especially in light of the massive growth in available databases. Metaheuristic algorithms using a learning model have been the subject of studies to optimize feature selection difficulties. This research uses Enhanced Gorilla Troops Optimizer (EGTO), for enhancing the feature selection process and then performing classification. This research presents a Interrelated Dynamic Biased Feature Selection Model using Enhanced Gorilla Troops Optimizer (IDBFS-EGTO) for generation of feature vector set for intrusion detection. Despite its apparent success in handling a wide range of practical problems, it risks getting mired in local optima and premature convergence when faced with more difficult optimization challenges that is overcome with EGTO. The EGTO approach, which uses a collection of operators to strike a more steady equilibrium between exploitation and exploration. The proposed model generates relevant feature subset for machine learning model for accurate detection and classification of intrusions in the network. The proposed model achieved 98.4 % accuracy in intrusion detection and 98.6 % accuracy in EGTO optimization classification. The proposed model is improved by 3.8 % in feature weight allocation accuracy and 1.2 % in detection accuracy levels. The proposed model is compared with the traditional models and the results represent that the proposed model performance is high.

Brain Tumor holds a significant holds in human health, classified into three primary types: glioma, meningioma, and pituitary tumors. Early detection and accurate classification are vital for effective diagnosis and lowering healthcare costs. In PBvit we presents a novel brain tumor detection framework, the Patch Base Vision Transformer (PBVit). PBVit adopts a patch-based approach where input tumor images are divided into fixed-size patches, with each patch treated as a token. These image patches are linearly projected into lower-dimensional token embeddings, and positional encodings are added to help the model understand spatial relationships within the image. PBVit enhances the detection of intricate patterns and anomalies in brain scans, improving diagnostic accuracy. We trained PBVit using the Figshare brain tumor dataset and observed notable performance improvements compared to traditional CNN-based models. The PBVit reached an accuracy of 95.8%, a precision of 95.3%, a recall of 93.2%, and an F1-score of 92%, indicating its robustness in identifying brain tumors. The promising results demonstrate that PBVit can play a important role in facilitating early-stage diagnosis, reducing unnecessary biopsies, and ultimately enhancing patient care, while also showcasing the potential of transformer-based architectures in medical imaging.

Abstract Natural and anthropogenic causes have led to soil degradation, salinisation of inland areas, and groundwater. The degraded soils are unsuitable for primary agriculture, but can be utilised for saline aquaculture. ICAR-CIFE has initiated a selective breeding program for faster growth in common carp cultured at low salinity (6–8 ppt). The present study demonstrates the dynamic nature of physico-chemical parameters of Inland Saline Ground Water (ISGW) and the growth potential of selectively bred F1 generation of common carp using ISGW. About 1560 common carp fingerlings were stocked in two ponds, each representing a unique size class (> 100 g and

Abstract Background There is limited literature in paediatric rheumatology describing holistic lived experiences of medical treatment from perspectives of children and young people (CYP) and their parents or carers (PC). This is important as it could have implications for adherence. This study aimed to explore treatment experiences of CYP and PC in a paediatric rheumatology service. Methods Participants were recruited at a day-case unit for intravenous infusions at a tertiary paediatric rheumatology centre. Joint qualitative semi-structured interviews with CYP and PC were used to collect data. Data were transcribed, quality checked and thematically analysed using NVivo 12.4 to identify findings. Results Thirty-two participants (15 CYP between the ages of 6 and 16 years, 17 PC) took part in interviews lasting 41 min and 43 s, on average. Participants described experiences using infliximab, followed by tocilizumab and abatacept. Participants experienced a wave, oscillating between positive and negative trajectories. Experiences of medical treatments were described as temporary, eventually changing and leading to treatment changes or cessation. Behaviours were influenced through somatic factors (pain, function), social factors (advice from health professionals, encouragement from friends, family and teachers, practicality of using treatment in relation to school, work and finance) and cognitive factors (fear of needles, fear of specific medications, beliefs about necessity). Conclusions Collectively, findings demonstrate experiences of medical treatment reflect the nature of many paediatric rheumatology conditions, oscillating between periods of positive and negative trajectories. Somatic, social and cognitive experiences can be positive, when treatment is considered ‘successful’. Negative somatic, social or cognitive experiences led to behaviours such as treatment non-adherence. A limitation of the study is interviews were conducted jointly with CYP and PC, which may have influenced what participants were willing to say in front of one another however this does mean findings relate to both CYP and PC and so could be suitable targets for interventions to improve adherence.

Abstract This study introduces an innovative approach to automatically analyzing 1H nuclear magnetic resonance (NMR) data, integrating a quantum mechanical spectral analysis (QMSA) to enhance efficiency over manual data analysis in NMR. This proposed digital platform features a standardized quantitative NMR (qNMR) procedure, digital Reference Spectra within a spectral library, and a visualized interactive interface for streamlined, automated NMR data analysis. This digital platform significantly reduces the need for manual intervention and shows promise in using spectral fitting to compare the calculated spectrum derived from a digital Reference Spectrum with an experimental spectrum. The digital platform excels in processing data of both single chemical and mixture, delivering accurate results, and positioning it as an essential tool for automatic 1H qNMR analyses. Case studies highlight the digital platform’s effectiveness, demonstrating its wide-ranging applicability. This shows that the proposed digital platform, based on a qNMR-based QMSA approach, offers reliable qualitative and quantitative analyses and paves the way for integrating digital reference standards into future compendial tests. Graphical Abstract

Abstract Special histologic subtypes of breast cancer (BC) exhibit unique phenotypes and molecular profiles with diagnostic and therapeutic implications, often differing in behavior and clinical trajectory from common BC forms. Novel methodologies, such as artificial intelligence may improve classification. Genetic predisposition plays roles in a subset of cases. Uncommon BC presentations like male, inflammatory and pregnancy-related BC pose challenges. Emerging therapeutic strategies targeting genetic alterations or immune microenvironment are being explored.

This article from the American Society for Gastrointestinal Endoscopy (ASGE) provides a full description of the methodology used to inform the final guidance outlined in the accompanying summary and recommendations article for strategies to manage endoscopically placed gastrostomy tubes. This article was developed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework and specifically addresses the utility of PEG versus interventional radiology–guided gastrostomy (IR-G), the need for withholding antiplatelet and anticoagulant medications, appropriate timing to initiate tube feedings, and appropriate selection of the gastrostomy technique in patients with malignant dysphagia. In patients needing enteral access, the ASGE suggests PEG as the preferred technique for initial gastrostomy over IR-G. The ASGE recommends that tube feeding can be safely started within 4 hours of the gastrostomy without the need for an intentional delay. The ASGE suggests that a PEG can be performed without the need to withhold antiplatelet medications. In patients on anticoagulants who need to undergo PEG placement, the ASGE suggests that the periprocedural management of anticoagulants should be based on a multidisciplinary discussion with the patient regarding the risk of bleeding versus cardiovascular adverse events. In patients with malignant dysphagia, either transoral “Pull” PEG or transcutaneous “Direct” PEG can be performed for initial enteral access.

One of the most detrimental and severe presentations of Systemic Lupus Erythematosus (SLE) is Lupus Nephritis (LN), which is a type of glomerulonephritis. Type-IV Lupus Nephritis, or diffuse Lupus Nephritis, is a severe illness characterised by diffuse proliferative lesions. In this setting, the prognosis worsens if cellular crescent is present. It is divided into two types: diffuse segmental and the other being diffuse global. Wire-loop lesions could also be observed. There have been reports of Collapsing Glomerulopathy (CG) in SLE patients with Focal Segmental Glomerulosclerosis (FSGS). The collapsing variety of FSGS (cFSGS) is defined histopathologically by segmental or global glomerular capillary condensation and obliteration, the appearance of hyperplastic and hypertrophic podocytes, and substantial tubulointerstitial damage. Numerous aetiologies have been proposed, including viral infections such as Human Immunodeficiency Virus (HIV), Cytomegalovirus (CMV), Epstein-Barr virus, and Parvovirus B19, as well as medications and acute ischaemia. Patients infected with Coronavirus Disease-2019 (COVID-19) have an increased risk of acute renal injury as there is a systemic inflammatory cascade due to an acute infection, causing impairment of basic cellular activities in podocytes. Hereby, the authors present a case report of a 17-year-old female who experienced cardiac tamponade and seizures due to Posterior Reversible Encephalopathy Syndrome (PRES). Further investigation and kidney biopsy revealed she had lupus nephritis Stage-IV Diffuse Proliferative Glomerulonephritis (DPGN) but with the collapsing variety, which is a rare finding. Additionally, the patient tested positive for COVID-19, which may have contributed to the development of the collapsing type of DPGN.

Abstract Background Polygalacturonase inhibiting proteins (PGIPs) play a pivotal role in plant defense against plant pathogens by inhibiting polygalacturonase (PG), an enzyme produced by pathogens to degrade plant cell wall pectin. PGIPs, also known as leucine-rich repeat pathogenesis-related (PR) proteins, activate the host’s defense response upon interaction with PG, thereby reinforcing the host defense against plant pathogens attacks. In Egyptian or extra-long staple cotton (Gossypium barbadense), the interaction between PGIP and PG is one of the crucial steps in the defense mechanism against major pathogens such as Xanthomonas citri pv. malvacearum and Alternaria macrospora, which are responsible for bacterial leaf blight and leaf spot diseases, respectively. Results To unravel the molecular mechanisms underlying these PR proteins, we conducted a comprehensive study involving molecular modeling, protein-protein docking, site-specific double mutation (E169G and F242K), and molecular dynamics simulations. Both wild-type and mutated cotton PGIPs were examined in the interaction with the PG enzyme of a bacterial and fungal pathogen. Our findings revealed that changes in conformations of double-mutated residues in the active site of PGIP lead to the inhibition of PG binding. The molecular dynamics simulation studies provide insights into the dynamic behaviour and stability of the PGIP-PG complexes, shedding light on the intricate details of the inhibitory and exhibitory mechanism against the major fungal and bacterial pathogens of G. barbadense, respectively. Conclusions The findings of this study not only enhance our understanding of the molecular interactions between PGs of Xanthomonas citri pv. malvacearum and Alternaria macrospora and PGIP of G. barbadense but also present a potential strategy for developing the disease-resistant cotton varieties. By variations in the binding affinities of PGs through specific mutations in PGIP, this research offers promising avenues for the development of enhanced resistance to cotton plants against bacterial leaf blight and leaf spot diseases.

Abstract This research aimed to characterize the mitochondrial genome of the Ghoongroo (GH) pig, a notable breed in India, along with its crossbred varieties, to elucidate their matrilineal components, evolutionary history, and implications for conservation. Seven pigs (5 GH, 2 crossbred, namely Rani and Asha) were sequenced for complete mitochondrial genome, while 24 pigs (11 GH, 6 Rani, and 7 Asha) were sequenced for the complete D-loop of the mitochondrial genome. The genome size of these pigs was determined to be 16,690 bp. Analysis of the mitochondrial sequences and phylogenetics uncovered two distinct matrilineal components within the GH population, a phenomenon also observed in its crossbred counterparts, Rani and Asha. Phylogenetic analysis demonstrated a clear clustering of GH sequences into two clades, indicating the presence of two independent maternal lineages. The phylogenetic study using complete mitogenome also indicated that GH pigs were originated locally from Indian wild boar independently from Asian and European pig population. Haplotype analysis from complete D-loop sequences revealed 10 different haplotypes, with some sequences shared among GH, Rani, and Asha, while others differed due to varying matrilineal origins. The haplotype analysis using complete mitogenome sequences revealed 16 different haplotypes with some shared sequences among GH. Furthermore, examination of tRNA genes and nucleotide composition of different genes namely rRNAs, COX1, COX2, ATP6, ND4, ND5, ND6, Cytb offered insights into genetic diversity within these pigs. The findings suggest that geographical isolation and historical events likely contributed to the emergence of distinct maternal lineages within the GH breed. This study underscores the significance of mitochondrial DNA analysis in uncovering hidden genetic diversity within seemingly uniform populations. The molecular insights gained into the genetic makeup of GH pigs could aid in designing effective breeding programs for conservation efforts and highlight its significance in understanding the broader context of pig domestication in India.

Abstract This study endeavors to tackle the energy requirements of the building sector by employing passive design strategies. However, there exists a dearth of comprehension regarding the energy efficiency performance of foamed alkali-activated materials. To bridge this research gap, the study proposes a solution in the form of a thermally proficient wall material crafted from ceramic tile dust (CTD), class C fly ash (FA), and Ground Granulated Blast-Furnace Slag (GGBS), all of which are industrial by-products. The foamed ternary alkali-activated (FTAA) blocks, developed as a result of this research, exhibited commendable performance in terms of mechanical strength of 18.6 MPa, lower density of 1200 kg/m3, porosity of 15.95%, lower specific heat capacity (SHC) of 831 J/(Kg·K), and thermal conductivity (TC) of 0.38 W/(m·K). The thermal efficiency of FTAA blocks curtails the transfer of heat from the external environment to the interior, thereby engendering a more agreeable indoor milieu for occupants. A simulation study utilizing the eQuest tool was executed to evaluate the thermal attributes of the developed blocks and their consequential impact on energy requirements. The findings revealed that in comparison to clay bricks, employing FTAA blocks could yield potential annual energy savings of approximately 4%. Furthermore, notable cost savings of about 4.94% during peak summer months and 5.51% annually were observed. The significance of utilizing these ternary blocks, derived from industrial waste, resides in their affirmative contribution to environmental preservation, augmented indoor thermal comfort, and diminished energy consumption for end users. Consequently, this research makes a meaningful stride towards diminishing operational energy in buildings, harmonizing with sustainability objectives.

Abstract Proper modeling of PV cells/modules through parameter identification based on the real current-voltage (I-V) data is important for the efficiency of PV systems. Most related works have concentrated on the classical single-diode model (SDM) and double-diode model (DDM) and their parameter extraction by various metaheuristic algorithms. In order to render more accurate and representative modeling, this paper adds a small resistance in series with the diodes in SDM and DDM. The new models are named reconfigured SDM (Reconfig-SDM) and reconfigured DDM (Reconfig-DDM), and they have not been studied so far as we know. A squirrel search algorithm (SSA) is employed to globally find the parameters of the new models. The performance achieved is experimentally tested on both a commercial RTC France solar cell and a CS6P-220P polycrystalline PV module located at Düzce University in Türkiye. A vivid comparison of experimental findings, observation, and analysis clearly demonstrates that the proposed Reconfig-SDM and Reconfig-DDM tuned by the SSA have better capacity and effectiveness for modeling PV devices than some cutting-edge approaches. Specifically, compared with the best-performing approach in the literature, Reconfig-SDM and Reconfig-DDM could reduce the error rate up to 0.37% and 2.58% for the solar cell, and 3.21% and 29.0% for the solar module.

This study examines the application of Laser Directed Energy Deposition (L-DED) to reduce the use of bronze in the manufacturing of worm gears. Addressing the gap in research regarding the L-DED of bronze on steel substrates, the study refines process parameters to improve deposition quality significantly. The approach involves depositing single bronze tracks using various combinations of process parameters, followed by the analysis of cross-sections to evaluate porosity and track cross-section geometry. Building on the optimized parameters identified during single-track experiments, we achieve multi-layer depositions of 3 mm thickness. These layers are then transformed into cylindrical specimens that are subjected to rigorous wear testing in a pin-on-disc setup against a 42CrMo4V counterpart under dry sliding conditions, aimed at investigating debonding and friction characteristics. Additionally, disc-shaped specimens created with the optimized parameters are evaluated under lubricated conditions via a disc-on-disc test, accurately replicating motor gear loading scenarios. Comprehensive assessments of porosity, microstructure, and microhardness are conducted on these specimens. Finally, our findings reveal the potential of DED bronze as a groundbreaking alternative to traditional wrought bronze in gear applications, highlighting its promise for reducing bronze usage in worm gears with an enhanced wear performance.

In this paper, we determine the fuzzy similarity measure between the ranking of states with respect to best the states for work for women and work in general. We break the states into regions and determine the same fuzzy similarity measures for each region. We find that the fuzzy similarity measures range from high to very high. We develop new fuzzy similaritymeasures to be used in rankings.

Abstract Tor putitora is an endangered cyprinid fish constrained to cold water and is also considered an indicator of a healthy aquatic ecosystem. The present study aimed to examine the haplotypic diversity, genetic variation and population structure of T. putitora isolates using COI and Cyt b gene sequences submitted in GenBank. Bioinformatic analysis was carried out using 106 COI and 183 Cyt b gene sequences as well as 2 reference genome sequences. Analysis of COI and Cyt b gene reveals 18 and 85 haplotypes respectively. Mutation was observed at 44 different sites in COI and 173 in Cyt b gene sequences. Haplotype 4 and haplotype 37 were considered ancestral in COI and Cyt b respectively. Analysis of COI gene reveals moderate haplotype diversity (0.630) and low Nucleotide diversity (0.00662) whereas Cyt b has higher haplotype diversity (0.804) and low Nucleotide diversity (0.00582). Moreover, the neutrality test such as Tajima’s D, and Fu’s Fs showed negative values in both gene sequences, suggesting population expansion attributed to habitat destruction. So, comprehending the genetic variability within and among the T. putitora population is crucial for conserving and managing this species. Integration of genetic diversity into conservation planning can enhance the effectiveness of breeding programs and habitat restoration efforts.

Purpose: Non-obstructive azoospermia (NOA) is a common, but complex problem, with multiple therapeutic options and a lack of clear guidelines. Hence, there is considerable controversy and marked variation in the management of NOA. This survey evaluates contemporary global practices related to medical and surgical management for patients with NOA. Materials and Methods: A 56-question online survey covering various aspects of the evaluation and management of NOA was sent to specialists around the globe. This paper analyzes the results of the second half of the survey dealing with the management of NOA. Results have been compared to current guidelines, and expert recommendations have been provided using a Delphi process. Results: Participants from 49 countries submitted 336 valid responses. Hormonal therapy for 3 to 6 months was suggested before surgical sperm retrieval (SSR) by 29.6% and 23.6% of participants for normogonadotropic hypogonadism and hypergonadotropic hypogonadism respectively. The SSR rate was reported as 50.0% by 26.0% to 50.0% of participants. Interestingly, 46.0% reported successful SSR in

The metaverse has profoundly altered the conventional online landscape and has attracted significant interest from researchers and industry professionals. As the metaverse changes quickly, it needs strong and safe cryptographic solutions to make sure that transactions are fair and safe in its highly connected world. This paper presents a novel blockchain-assisted fair exchange signature protocol leveraging quantum key distribution (QKD) to ensure security against both classical and quantum adversaries. The suggested protocol combines blockchain technology with quantum key distribution to create an exchange framework that can’t be changed, is clear, and can’t be tampered with. It also uses quantum mechanics to create keys that are always safe. By incorporating a fair exchange mechanism, the protocol guarantees that either both parties fulfill their obligations or neither party benefits, addressing trust issues in decentralized metaverse transactions. Furthermore, we provide a detailed analysis of the protocol’s security, efficiency, and scalability, highlighting its resistance to quantum attacks and its suitability for real-time applications in the metaverse. Simulation results demonstrate that the protocol significantly enhances exchange fairness, minimizes latency, and ensures robust authentication, making it a promising candidate for securing transactions in next-generation digital ecosystems. Web 3.0 technologies provide a resolution by facilitating a decentralized metaverse ecology. The suggested protocol utilizes quantum fundamentals to facilitate safe communication, while the incorporation of quantum cryptography with Web 3.0 improves the efficiency, security, and authenticity of metaverse environments. We test the proposed quantum signature scheme both theoretically and practically using QuantumSim simulations, demonstrating strong signature performance in comparison to other schemes. The results indicate a computational cost of $0.815 ms$ , and communication costs of 1312 bits, demonstrating the protocol’s resilience and performance by conducting a thorough safety and efficiency analysis and demonstrating compliance with essential security features, including unforgeability, undeniability, verifiability, and traceability.

Background: Middle ear surgeries are performed under either local or general anaesthesia. Many advantages have been reported with the local anaesthetic techniques. Objectives: To compare the effectiveness of clonidine with lignocaine and lignocaine alone infiltration for middle ear surgeries with respect to duration of analgesia, pain score & surgeon’s satisfaction. Methodology: 66 adult patients undergoing elective middle ear surgeries were divided into two groups, study group A (n=33) and control group B (n=33). 15ml of local anaesthesia infiltrated at posterior auricular area and between tragus and helix using 2% lignocaine with 1 in 200000 dilution of adrenaline with 30mcg of clonidine hydrochloride for study group A and 15ml of 2% lignocaine with 1 in 200000 dilution of adrenaline with 0.2ml normal saline given for control group B by the surgeon, after confirming successful blockade, procedure started. Patients were asked to rate intraoperative pain using visual analogue scale consisting of scoring from 1 to 10. Surgeon satisfaction scores were assessed using Likert scale consisting of scoring from 1 to 7. Results: Demographic data were comparable in both the groups. Duration of analgesia was significantly higher in group A compared to group B. The surgeon satisfaction was better in group A than Group B. SBP and DBP found significantly higher in group B compared to group A. Conclusion: Duration of analgesia and surgeon satisfaction were better in clonidine as adjuvant compared with lignocaine with adrenaline alone infiltration, with well-maintained haemodynamic.

Abstract The road network in the Himalayan terrain is vital for India's socio-economic development and national security, yet the complexities of topography, geological structures, diverse lithology, and neotectonics make planning and maintaining these routes a challenging task. Population growth and expanding road construction have caused slope destabilization, mass wasting, and movement across the Himalayan terrain. Field-based slope stability assessments are essential for slope mass characterization and slope stabilization, helping planners predict and select suitable construction strategies for roads and other infrastructure. This study presents a comprehensive slope stability and displacement analysis of the Kuther landslide, situated along the Jawali to Kuther road in the Dehar Watershed, Kangra District, Himachal Pradesh. An integrated approach was used, combining surface displacement monitoring with the COSI-Corr technique and slope stability assessments through methods such as rock mass rating, kinematic analysis, slope mass rating, and continuous slope mass rating. Findings indicate that the slope is highly susceptible to planar failure, with some instances of wedge failure. The rock mass ranges from class III to IV, indicating conditions from partially stable to stable, while displacement analysis reveals the slope is creeping at an average rate of 4 mm/year. This study highlights the critical need for comprehensive slope stability and displacement analyses to ensure the safety of vulnerable areas and their communities.

Abstract 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.

Abstract Herbicide paraquat dichloride, a potent redox agent found its way to natural water bodies and influences their health; however, its impact on the reproductive health of fish is potentially less studied and requires clear investigation. This study was conducted to elucidate its effect on the gonadal health of female fish, Channa punctatus over 60 days. The 96-h LC50 of test herbicide was calculated as 0.24 mL/L for the fish under examination, subsequently, three sub-lethal concentrations were taken in addition to control for the study. The experimental methodology included assessment of oxidative stress markers, hormone levels, expression of interrelated genes, and histological analysis to ascertain the damage to the ovary. At each exposure period, a significant (p

Abstract Background Immunothrombosis is the process by which the coagulation cascade interacts with the innate immune system to control infection. However, the formation of clots within the brain vasculature can be detrimental to the host. Recent work has demonstrated that Toxoplasma gondii infects and lyses central nervous system (CNS) endothelial cells that form the blood-brain barrier (BBB). However, little is known about the effect of T. gondii infection on the BBB and the functional consequences of infection on cerebral blood flow (CBF) during the different stages of infection. Main body We demonstrate that brain endothelial cells upregulate the adhesion molecules ICAM-1 and VCAM-1 and become morphologically more tortuous during acute T. gondii infection of mice. Longitudinal two-photon imaging of cerebral blood vessels during infection in mice revealed vascular occlusion in the brain, prompting an analysis of the coagulation cascade. We detected platelet-fibrin clots within the cerebral vasculature during acute infection. Analysis of CBF using longitudinal laser-speckle imaging during T. gondii infection demonstrated that CBF decreased during acute infection, recovered during stable chronic infection, and decreased again during reactivation of the infection induced by IFN-γ depletion. Finally, we demonstrate that treatment of mice with a low-molecular-weight heparin, an anticoagulant, during infection partially rescued CBF in T. gondii-infected mice without affecting parasite burden. Conclusions Our data provide insight into the host-pathogen interactions of a CNS parasite within the brain vasculature and suggest that thrombosis and changes in cerebral hemodynamics may be an unappreciated aspect of infection with T. gondii.

Abstract Current fetal alcohol spectrum disorders (FASD) studies primarily focus on alcohol’s actions on the fetal brain although respiratory infections are a leading cause of morbidity/mortality in newborns. The limited studies examining the pulmonary adaptations in FASD demonstrate decreased surfactant protein A and alveolar macrophage phagocytosis, impaired differentiation, and increased risk of Group B streptococcal pneumonia with no study examining sexual dimorphism in adaptations. We hypothesized that developmental alcohol exposure in pregnancy will lead to sexually dimorphic fetal lung morphological and immune adaptations. Pregnant rats were orogastrically treated once daily with alcohol (4.5 g/kg, gestational day [GD] 4 to 10, peak BAC, 216 mg/dl; 6.0 g/kg, GD 11 to 20, peak BAC, 289 mg/dl) or 50% maltose dextrin (isocalorically matched pair-fed controls) to control for calories derived from ethanol. Male and female fetal lung RNA from a total of 20 dams were assessed using the TapeStation (Agilent) and Qubit RNA broad-range assay. Samples with RNA Integrity Numbers (RINs) > 8 were prepared using the NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB), xGen Broad-range RNA Library Prep (IDT), and xGen Normalase UDI Primer Plate 2 (IDT). Final libraries were checked for quality and quantity by Qubit hsDNA and LabChip. The samples were sequenced on the Illumina NovaSeq S4 Paired-end 150 bp. Fetal lung tissue were analyzed for histopathological assessments. Mean fetal weight, crown-rump length and placental efficiency of the alcohol-administered rats were significantly lower (P 2 (P

Surfactants get discharged indiscriminately in wastewater which increased several fold during COVID-19, raising environmental concerns. In this study, two locally available plant species Canna indica and Acorus calamus were compared for the sodium dodecyl sulfate (SDS, − a chemical surfactant) removal in vertical flow constructed wetlands (VFCWs) augmented with biochar. The dose-response relationship was studied for 144 days in four phases by varying the SDS concentration at 10, 25, 50, and 100 ppm in wastewater. The mean SDS removal efficiencies varied from 85 % - 98 % during the different phases. The results suggested that planted artificial wetlands acted more stable than unplanted ones, although the removal efficiencies of the planted and unplanted were found similar (97.9 % - 98.4 %) in phase 4. Further, GC–MS analysis confirmed C2 products formed during SDS degradation indicating mineralization of SDS. The bioconcentration factor (BCF) and translocation factor (TF) studies revealed no accumulation of SDS in the roots of both plants as BCF (root) 1 in the case of both plants, among which translocation of SDS in C. indica with biochar amendment (TF = 17.8) was found to be highest. TF values indicated that biochar may have supported the uptake and translocation of SDS in C. indica whereas biochar has not supported the pollutant transfer in A. calamus. In terms of plant health, C. indica showed better growth and higher biomass increase than the A. calamus. The results implicate that C. indica with biochar-amended CW systems has great potential and can be recommended for efficient removal and uptake of SDS.

Objective The aims of this study are to compare the multiphasic contrast-enhanced computed tomography (CECT) characteristics of infiltrative hepatocellular carcinoma (HCC) with nodular HCC and to assess the conspicuity of infiltrative HCC on different phases of CECT.

The q-rung orthopair fuzzy set can represent a wide range of uncertainty in information. When combined with a soft set, the resulting notion of a q-rung orthopair fuzzy soft set (OFSSq ) is more effective in dealing with uncertainties as it allows for parameterization. The OFSSq is a parameterized family of q-rung orthopair fuzzy sets and a generalization of the Intuitionistic fuzzy soft set (IFSS), the Pythagorean fuzzy soft set (PFSS) and the Fermatean fuzzy soft set (FFSS). While entropy and similarity measures have been defined for these fuzzy set extensions, defining these measures for OFSSq provides generalized expressions that apply to all these special cases. This article proposes distinct expressions for entropy and similarity measures for OFSSq s. The proposed entropy measure aids in assessing uncertainty within an OFSSq , while the similarity measure identifies the degree of similarity between any two OFSSqs. This article showcases the use of the suggested entropy and similarity measures in decision making, highlighting their effectiveness. Both concepts of entropy and similarity will be applied to decision making problems related to Covid-19 pandemic, especially when some dubious inputs are present, and a quick decision must be made.

Background: Proximal humerus fractures are typically minimally displaced and often result from low-energy trauma, particularly in elderly individuals with osteoporosis. In such cases, conservative or non-surgical treatments are generally effective. However, the optimal treatment approach remains an active research and debate area for fractures with moderate to severe displacement. Aims and Objectives: This study aims to conduct a comprehensive comparative analysis, focusing on evaluating and distinguishing the functional outcomes in elderly patients with complex proximal humerus fractures. Materials and Methods: A prospective, comparative study was conducted involving 60 elderly patients. The primary goal was to assess and compare the functional outcomes of complex proximal humerus fractures treated surgically using plating versus conservative treatment methods. Results: At the 8-week follow-up, patients in the non-surgical group demonstrated significantly lower average values for flexion, abduction, external rotation, and internal rotation than the surgical group. However, by the 6-month mark, no significant differences were observed between the two groups. Conclusion: The locking plate is a preferred implant for comminuted proximal humerus fractures. In this study, outcomes from locked plate fixation were comparable to those of non-operative treatments. Early initiation of physiotherapy and a robust rehabilitation program are crucial for achieving optimal functional recovery.

Internal hernia is the protrusion of a viscus through a normal or abnormal peritoneal or mesenteric aperture within the confines of the peritoneal cavity. They can be congenital or acquired after abdominal surgery. We report a case of a 58-year-old woman who presented with complaints of abdominal pain and nonbilious vomiting for 2 days. She underwent an abdominal hysterectomy 15 years ago. After baseline blood investigations and imaging, a diagnosis of subacute intestinal obstruction was made. As she clinically worsened over 24 h, CT imaging was done, which suggested acute small bowel obstruction secondary to adhesions. Surgery revealed herniation with incarceration of distal ileal loops through a defect in the sigmoid mesocolon. Bowel resection was done, and the defect was closed. The clinical presentation of internal hernias, especially transmesosigmoid hernia, is nonspecific, and they rapidly progress to bowel ischemia. Early intervention and surgical correction are prudent for good clinical outcomes.

Abstract Background Lymphatic Filariasis (LF) is a neglected tropical disease affecting more than 882 million people in 44 countries of the world. A multi-epitope prophylactic/therapeutic vaccination targeting filarial defense proteins would be invaluable to achieve the current LF elimination goal. Method Two groups of proteins, namely Anti-oxidant (AO) and Heat shock proteins (HSPs), have been implicated in the effective survival of the filarial parasites in their hosts. Several B-cell, CTL, and T-helper epitopes were predicted from the three anti-oxidant proteins GST, GPx, and SOD. Likewise, epitopes were also predicted for HSP110, HSP90, and HSP70. Among the predicted epitopes, screening was applied to include only non-allergenic, non-toxic epitopes to construct two MEVs, PVAO and PVHSP. The epitopes for each group of proteins were connected to each other by the inclusion of suitable linkers and an adjuvant. The 3D models for PVAO and PVHSP were predicted, and validated, followed by prediction of physicochemical properties using bioinformatics tools. The binding free energy of PVAO and PVHSP with Toll like Receptors (TLR) TLR1/2, TLR4, TLR5, TLR6, and TLR9 was calculated with HawkDock. The immunogenicity of both the MEVs were assessed by Immune simulation after which codon adaptation and in-silico cloning were carried out. Results Conservation of the selected AOs and HSPs in other parasitic nematode species suggested that both the generated chimera could be helpful in cross-protection too. The 3D models of both MEVs contained more than 97% residues in allowed regions, as predicted by PROCHECK server. High MMGBSA and docking scores were obtained between MEVs and TLR4, TLR1/2, TLR6, and TLR9. Molecular dynamics simulation confirmed the stability of candidate vaccines in dynamic conditions present in the biological systems. The in-silico immune simulation indicated significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ, and IL-2 responses following immunization with PVAO and PVHSP. Conclusion The immunoinformatics approaches used in this study confirmed that, the designed vaccines are capable of eliciting sustained immunity against LF, however, additional in-vivo studies would be required to confirm their efficacy. Furthermore, by employing multi-epitope structures and constructing two different cocktail vaccines for LF, this study can form an important milestone in the development of future LF vaccine/s.

Abstract Diabetic Retinopathy (DR) stands as a significant global cause of vision impairment, underscoring the critical importance of early detection in mitigating its impact. Addressing this challenge head-on, this study introduces an innovative deep learning framework tailored for DR diagnosis. The proposed framework utilizes the EfficientNetB0 architecture to classify diabetic retinopathy severity levels from retinal images. By harnessing advanced techniques in computer vision and machine learning, the proposed model aims to deliver precise and dependable DR diagnoses. Continuous testing and experimentation shows to the efficiency of the architecture, showcasing promising outcomes that could help in the transformation of both diagnosing and treatment of DR. This framework takes help from the EfficientNet Machine Learning algorithms and employing advanced CNN layering techniques. The dataset utilized in this study is titled ’Diagnosis of Diabetic Retinopathy’ and is sourced from Kaggle. It consists of 35,108 retinal images, classified into five categories: No Diabetic Retinopathy (DR), Mild DR, Moderate DR, Severe DR, and Proliferative DR. Through rigorous testing, the framework yields impressive results, boasting an average accuracy of 86.53% and a loss rate of 0.5663. A comparison with alternative approaches underscores the effectiveness of EfficientNet in handling classification tasks for diabetic retinopathy, particularly highlighting its high accuracy and generalizability across DR severity levels. These findings highlight the framework’s potential to significantly advance the field of DR diagnosis, given more advanced datasets and more training resources which leads it to be offering clinicians a powerful tool for early intervention and improved patient outcomes.

Abstract Aims The ICMR INDIAB-17 study revealed a diabetes prevalence of 11.4% in India, emphasizing the need for effective treatment for glycemic control. A Phase IV study was conducted to evaluate the safety and efficacy of a Fixed Dose Combination (FDC) of Remogliflozin, Metformin and Vildagliptin (RMV) in Type 2 Diabetes Mellitus (T2DM) patients uncontrolled on Metformin plus SGLT2 inhibitor or Metformin plus DPP4 inhibitor dual therapy. Methods A total of 215 patients (mean age: 46.4 years; 64% male, 36% female) were enrolled across multiple centers in India. The study population included patients with a baseline HbA1c ≥ 8% at the time of screening. The primary objective was to assess safety based on treatment-emergent adverse events (TEAEs), while the secondary. aim was to evaluate effectiveness in terms of glycemic (HbA1c, fasting plasma glucose, postprandial glucose) and extra-glycemic measures (renal and lipid parameters). Statistical analysis was conducted using paired t-tests and the Wilcoxon signed-rank test for within-group comparisons, and the Bonferroni correction was applied to adjust for multiple comparisons. Effectiveness was evaluated at baseline, week 12, and week 24. Results The study demonstrated statistically significant reductions in mean HbA1c levels from baseline to both week 12 and week 24 (p

Abstract This study demonstrates multithreshold engineering of a solution-processed heterojunction electrochemical transistor using a blend of n-type CdSe tetrapod-shaped nanocrystals (TpNCs) and an n-type polymeric organic semiconductor (OSC). The unique geometry of TpNCs enables a broad concentration range of charge percolation, where charge transfer between TpNC and OSC domains determines multiple threshold voltages. The OSC domain’s threshold voltage shifts from 1 to −1 V as TpNC content increases, while the TpNC domain maintains a threshold above 1.5 V. This allows for stable intermediate states, crucial for multivalued logic operations. Charge percolation and photoluminescence studies show selective charge redistribution, shifting the threshold voltages in the polymer networks. Ternary logic gates, including TNOT, TNAND, and TNOR, based on these heterojunction transistors, were also demonstrated, highlighting the potential of this approach for advanced logic applications.

The application of advanced omics technologies in plant science has generated an enormous dataset of sequences, expression profiles, and phenotypic traits, collectively termed “big data” for their significant volume, diversity, and rapid pace of accumulation. Despite extensive data generation, the process of analyzing and interpreting big data remains complex and challenging. Big data analyses will help identify genes and uncover different mechanisms controlling various agronomic traits in crop plants. The insights gained from big data will assist scientists in developing strategies for crop improvement. Although the big data generated from crop plants opens a world of possibilities, realizing its full potential requires enhancement in computational capacity and advances in machine learning (ML) or deep learning (DL) approaches. The present review discuss the applications of genomics, transcriptomics, proteomics, metabolomics, epigenetics, and phenomics “big data” in crop improvement. Furthermore, we discuss the potential application of artificial intelligence to genomic selection. Additionally, the article outlines the crucial role of big data in precise genetic engineering and understanding plant stress tolerance. Also we highlight the challenges associated with big data storage, analyses, visualization and sharing, and emphasize the need for robust solutions to harness these invaluable resources for crop improvement.

Abstract Pre-harvest sprouting (PHS) in groundnut leads to substantial yield losses and reduced seed quality, resulting in reduced market value of groundnuts. Breeding cultivars with 14–21 days of fresh seed dormancy (FSD) holds promise for precisely mitigating the yield and quality deterioration. In view of this, six multi-locus genome-wide association study (ML-GWAS) models alongside a single-locus GWAS (SL-GWAS) model were employed on a groundnut mini-core collection using multi season phenotyping and 58 K “Axiom_Arachis” array genotyping data. A total of 9 significant SNP-trait associations (STAs) for FSD were detected on A01, A04, A08, A09, B02, B04, B05, B07 and B09 chromosomes using six ML-GWAS models. Additionally, the SL-GWAS model identified 38 STAs across 14 chromosomes of groundnut. A single STA on chromosome B02 (qFSD-B02-1) was consistently identified in both ML-GWAS and SL-GWAS models. Furthermore, candidate gene mining identified nine high confidence genes viz., Cytochrome P450 705 A, Dormancy/auxin associated family protein, WRKY family transcription factor, Protein kinase superfamily protein, serine/threonine protein phosphatase, myb transcription factor, transcriptional regulator STERILE APETALA-like, ethylene-responsive transcription factor 7-like and F-box protein interaction domain protein as prime regulators involved in Abscisic acid/Gibberellic acid signaling pathways regulating dormancy/germination. In addition, three of the allele-specific markers developed from the identified STAs were validated across a diverse panel. These markers hold potential for increasing dormancy in groundnut through marker-assisted selection (MAS). Thus, this research offers insights into genetic and molecular mechanisms underlying groundnut seed dormancy in addition to providing markers and donors for breeding future varieties with 2–3 weeks of FSD.

Abstract Academic institutions face increasing challenges in predicting student enrollment and managing retention. A comprehensive strategy is required to track student progress, predict future course demand, and prevent student churn across various disciplines. Institutions need an effective method to predict student enrollment while addressing potential churn. The existing approaches are often inadequate in handling both numerical and textual data, limiting the ability to provide personalized retention strategies. We propose an innovative framework that combines deep learning with recommender systems for student enrollment prediction and churn prevention. The framework integrates advanced preprocessing techniques for both numeric and textual data. Feature extraction is performed with statistical measures for numeric data, and advanced text techniques like GloVe embeddings, Latent Dirichlet Allocation (LDA) for topic modeling, and SentiWordNet for sentiment analysis. A weighted feature fusion approach combines these features, and the optimal features are selected using the Pythagorean fuzzy AHP with a Hybrid Optimization approach, specifically the Instructional Emperor Pigeon Optimization (IEPO). The DeepEnrollNet model, a hybrid CNN-GRU-Attention QCNN architecture, is used for enrollment prediction, while Deep Q-Networks (DQN) are applied to generate actionable retention recommendations. This comprehensive methodology improves predictive accuracy for student enrolment and provides tailored strategies to enhance retention by addressing both text and numeric data in a unified framework. The DeepEnrollNet has the minimum MSE of 0.218978, MSRE of 0.216445, a NMSE of 0.232453, RMSE of 0.23213, and MAPE of 0.218754.

Abstract Disruptions in cognitive function have been reported in individuals undergoing haemodialysis and those with chronic kidney disease. This pilot study protocol primarily assesses the feasibility and acceptability of using mobile cognitive gaming apps for patient-led cognitive training during haemodialysis sessions. The protocol consists of three phases: (1) reviewing and evaluating available cognitive gaming apps, (2) conducting focus groups/interviews with people with kidney disease to determine app preferences, and (3) undertaking a quasi-experimental randomised controlled trial to compare cognitive outcomes between a patient-led app intervention group and a standard care control group over four months. Primary outcomes will include changes in cognitive test scores [Montreal Cognitive Assessment (MoCA), Modified Mini-Mental State Exam (3MSE), Rapid Objective Working Memory Assessment (ROWMA)], while secondary outcomes will encompass quality of life measures [Patient-Reported Outcomes Measurement (PROM) Kidney Disease Quality of Life Short Form (KDQoL-SF™) v 1.3, Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Instrument, European Quality of Life Five Dimension (EQ-5D)]. If demonstrated to be effective, this novel method of utilising gamified cognitive training applications could potentially mitigate cognitive decline and improve the well-being of people receiving haemodialysis without necessitating significant clinical resources. The findings from this research will guide the development of a larger definitive randomised trial in the future.

Abstract Over the past two decades, cloud computing has experienced exponential growth, becoming a critical resource for organizations and individuals alike. However, this rapid adoption has introduced significant security challenges, particularly in intrusion detection, where traditional systems often struggle with low detection accuracy and high processing times. To address these limitations, this research proposes an optimized Intrusion Detection System (IDS) that leverages Graph Neural Networks and the Leader K-means clustering algorithm. The primary aim of the study is to enhance both the accuracy and efficiency of intrusion detection within cloud environments. Key contributions of this work include the integration of the Leader K-means algorithm for effective data clustering, improving the IDS’s ability to differentiate between normal and malicious activities. Additionally, the study introduces an optimized Grasshopper Optimization algorithm, which enhances the performance of the Optimal Neural Network, further refining detection accuracy. For added data security, the system incorporates Advanced Encryption Standard encryption and steganography, ensuring robust protection of sensitive information. The proposed solution has been implemented on the Java platform with CloudSim support, and the findings demonstrate a significant improvement in both detection accuracy and processing efficiency compared to existing methods. This research presents a comprehensive solution to the ongoing security challenges in cloud computing, offering a valuable contribution to the field.

Abstract Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. The proposed AVOACS method improves clustering by including four critical terms: communication mode decider, distance of sink and nodes, residual energy and intra-cluster distance. Through mimicking the natural scavenging behavior of African vultures, AVOACS continuously balances energy consumption on nodes resulting in an increase in network stability and lifetime. For CH selection, we use AVOACS, which considers the following parameters: communication mode decider, the distance between sink and node, residual energy, and intra-cluster distance. In comparison to the OE2-LB protocol, simulation findings demonstrate that AVOACS enhances stability, network lifetime, and throughput by 21.5%, 31.4%, and 16.9%, respectively. The results show that AVOACS is an effective clustering algorithm for energy-efficient operation in heterogeneous WSN environments as it contributes to a large increase of network lifetime and significant enhancement of performance.

Abstract Sixteen thio/semicarbazide-based benzyloxy derivatives (BT1-BT16) were synthesized and evaluated for their inhibitory activities against monoamine oxidases (MAOs). Most compounds showed better inhibitory activity against MAO-B than against MAO-A. BT1, BT3, and BT5 showed the greatest inhibitory activity with an identical IC50 value of 0.11 µM against MAO-B, followed by BT6 and BT7 (IC50 = 0.12 µM) and BT2 (IC50 = 1.68 µM). The selectivity index of BT5 was the highest (363.64) for MAO-B, whereas that of BT1 was 88.73. BT1 and BT5 were reversible MAO-B inhibitors, based on the results of dialysis experiments. In inhibition kinetics, BT1 and BT5 were competitive MAO-B inhibitors with Ki values of 0.074 ± 0.0020 and 0.072 ± 0.0079 µM, respectively. Additionally, in the in-vitro parallel artificial membrane penetration assay, BT1 and BT5 crossed the blood–brain barrier. Cytotoxicity and possible neuroprotective effects of the lead compounds were assessed using IMR 32 cells. Levels of the antioxidant superoxide dismutase, catalase, and glutathione peroxidase in IMR 32 cells were increased by pretreatment with lead compounds. Five lead molecules (BT1, BT3, BT5, BT6, and BT7) were used for the docking studies. A significant pi–pi interaction with Tyr 326 was observed and molecular dynamics studies were performed for the most promising BT1-MAO-B complex. These results suggested that BT1 and BT5 could be used therapeutically for the treatment of various neurodegenerative diseases.

Abstract We analyse neutral and charged matter distributions in second order Lovelock gravity, also known as Einstein–Gauss–Bonnet gravity, in arbitrary dimensions for a static, spherically symmetric spacetime. We first transform the charged condition of pressure isotropy, an Abel differential equation of the second kind, into canonical form. We then determine a systematic approach to integrate the condition of pressure isotropy by showing that the canonical form is a Chini differential equation. The Chini invariant, which allows the master differential equation to be separable, is identified. This enables us to find three new general solutions, in implicit form, to the condition of pressure isotropy. We also show that previously obtained exact specific solutions arise as special cases in our general class of models. The Chini invariant does not arise in general relativity; it is a distinguishing feature of Einstein–Gauss–Bonnet gravity.

Background: With growing awareness of pomegranate's health benefits, pomegranate products have been consumed more frequently in recent years, and pomegranate peel has emerged as one of the most prevalent wastes in the food industry. Pomegranate Peel concentrate is an indigenous substance with strong antioxidant and antidiabetic actions as a result of its tannins as well as polyphenols content. Methods: In the present study, pomegranate skin extract, both liquid and alcohol-based, was evaluated for polyphenolic and flavonoid content. Alcoholic fruit peel extract was also assessed for 1,4-α-D-glucan glucanohydrolase and α-D-glucoside glucohydrolase enzyme activity. Results: According to findings, pomegranate peel extract showed significant antioxidant content. Phytochemical analysis of ethanol-derived extract of pomegranate peel found a noteworthy amount of ellagitannins and flavonoids such as Punicalin, Punicalgin, Punicic acid, Catechin, Quercetin, Rutin, and Kaempferol. In contrast, punicalgin, ellagic acid, and gallic acid are responsible for antidiabetic activity. The LC-MS characterization of peel extract of pomegranate showed 10 bioactive compounds. The IC50 value for 80% alcoholic extract of pomegranate peel was found to be 5.86 mg/ml of α- amylase and 6.58 mg/ml of α-glucosidase. Conclusion: It was found that the inhibition of 1,4-α-D-glucan glucanohydrolase and α-D-glucoside glucohydrolase enzymes could be an effective mechanism by which it can give anti-diabetic effects.

Abstract The study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. The optimization aims to minimize both mass and compliance simultaneously. MOCS2arc is an advanced version of the traditional Multi-Objective Cuckoo Search (MOCS) algorithm, enhanced through a dual archive strategy that significantly improves solution diversity and optimization performance. To evaluate the effectiveness of MOCS2arc, we conducted extensive comparisons with several established multi-objective optimization algorithms: MOSCA, MODA, MOWHO, MOMFO, MOMPA, NSGA-II, DEMO, and MOCS. Such a comparison has been made with various performance metrics to compare and benchmark the efficacy of the proposed algorithm. These metrics comprehensively assess the algorithms' abilities to generate diverse and optimal solutions. The statistical results demonstrate the superior performance of MOCS2arc, evidenced by enhanced diversity and optimal solutions. Additionally, Friedman's test & Wilcoxon’s test corroborate the finding that MOCS2arc consistently delivers superior optimization results compared to others. The results show that MOCS2arc is a highly effective improved algorithm for multi-objective truss structure optimization, offering significant and promising improvements over existing methods.

Abstract Non-Hermitian models describe the physics of ubiquitous open systems with gain and loss. One intriguing aspect of non-Hermitian models is their inherent topology that can produce intriguing boundary phenomena like resilient higher-order topological insulators (HOTIs) and non-Hermitian skin effects (NHSE). Recently, time-multiplexed lattices in synthetic dimensions have emerged as a versatile platform for the investigation of these effects free of geometric restrictions. Despite holding broad applications, studies of these effects have been limited to static cases so far, and full dynamical control over the non-Hermitian effects has remained elusive. Here, we demonstrate the emergence of topological non-Hermitian corner skin modes with remarkable temporal controllability and robustness in a two-dimensional photonic synthetic time lattice. Specifically, we showcase various dynamic control mechanisms for light confinement and flow, including spatial mode tapering, sequential non-Hermiticity on-off switching, dynamical corner skin mode relocation, and light steering. Moreover, we establish the corner skin mode’s robustness in the presence of intensity modulation randomness and quantitatively determine its breakdown regime. Our findings extend non-Hermitian and topological photonic effects into higher synthetic dimensions, offering remarkable flexibility and real-time control possibilities. This opens avenues for topological classification, quantum walk simulations of many-body dynamics, and robust Floquet engineering in synthetic landscapes.

Introduction: There is a scarcity of studies in which both alveolar bone remodeling and root resorption are simultaneously assessed and compared against possible influencing factors such as rate of retraction and change in inclination. The aim of our study was to assess the changes in the alveolar bone thickness and root length of the maxillary anterior teeth after retraction and correlate it to the potential influencing factors, namely rate of retraction and change in inclination. Subjects and Methods: Ten patients requiring upper premolar extraction as part of their treatment were included in the study. Alveolar bone and root length changes were measured using cone beam computed tomography and the rate of retraction and change in inclination were assessed using lateral cephalograms. Two readings: Preretraction and postretraction were taken. Statistical analysis was done using Paired rank t-test and Spearman’s rank correlation tests. Significance level was set at P < 0.05. Results and Conclusions: The labial alveolar bone thickness showed an increase, whereas the palatal and total alveolar bone thickness showed a decrease. Root resorption was observed in all teeth. Alveolar bone changes showed a positive correlation to the rate of retraction and a negative correlation to the change in inclination. The root length change showed a positive correlation to the change in inclination.

Background and Aim: McCoy laryngoscope and video laryngoscopes (VLS) are being increasingly used in practice as they offer advantages over Macintosh laryngoscope in the management of difficult airway. The present study was aimed at comparing McCoy laryngoscope and The Anaesthetist Society Scope (TAScope) VLS regarding ease of intubation using Intubation Difficulty Scale (IDS) score in patients with an anticipated difficult airway. Methods: A total of 80 patients of either sex, belonging to the American Society of Anesthesiologists physical status I and II, undergoing surgery under general anesthesia and having simplified airway risk index score of 4 and above were randomized to two groups, McCoy group (n = 40) and TAScope group (n = 40). The primary objective of the study was to compare ease of intubation using IDS score in both the groups. Secondary objectives included time for intubation (TI), hemodynamic stress response, and incidence of oropharyngeal trauma. Results: Mean IDS score was significantly lower in TAScope group in comparison to McCoy group (0.9 ± 1.35 vs. 3.57 ± 2.46, P < 0.0001). The need for multiple intubation attempts, laryngeal pressure, and excess lifting force was significantly less in TAScope group (P = 0.0493, P = 0.0001 and P = 0.0007, respectively). TI was significantly longer in TAScope group in comparison to McCoy group (45.27 ± 6.06 s vs. 30.95 ± 9.13 s, P < 0.0001). The incidence of oropharyngeal trauma and hemodynamic changes was comparable in both the groups. Conclusion: TAScope is superior to McCoy laryngoscope for intubation in adult patients with anticipated difficult airway as it improves glottic view and facilitates easy intubation.

For patients with end-stage cardiac failure, heart transplantation is still a lifesaving surgery; however, access to this treatment in public institutions faces many obstacles. This review article examines the status of heart transplantation in public institutions, including its difficulties and possible remedies. This review also examines the various obstacles faced by public sector hospitals when performing heart transplant procedures, including financial aspects, infrastructure, legal procedures, trained personnel and transplant teams, and logistical difficulties related to organ procurement and distribution. In conclusion, even though heart transplantation in public hospitals has many difficulties, systematic efforts to remove obstacles and provide creative fixes have the potential to improve the results and accessibility for patients in need of this lifesaving procedure.

Introduction: Papillary thyroid carcinoma (PTC) has an excellent prognosis, but few cases are treatment-resistant. To check the applicability of combined BRAFV600E and MEK-targeted therapy, the current study correlated BRAFV600E with the MAPK pathway activation status in a cohort of PTCs. The prognostic relevance of BRAFV600E and the usability of immunohistochemistry (IHC) for detecting the mutation were also assessed. Methods: Randomly selected 50 PTC and 15 non-PTC cases were re-classified according to the 2022 WHO classification. The BRAF mutation status was compared with the IHC of BRAFV600E, pERK1/2, pMEK1/2, and clinicopathological variables, including response to radioactive iodine and disease-free survival. Results: BRAFV600E mutation was present in 38%. Most (87.8%) cases were immunopositive for pMEK1/2 and 40% for pMEK1/2. Although BRAFV600E mutation did not correlate with the MAPK activation status, it had an adverse impact on tumour sensitivity to radioiodine (P < 0.05). Five of the seven radioiodine-resistant tumours were BRAFV600E-mutated. An Allred cut-off score of 7 had a sensitivity of 100% and a specificity of 84% for detecting the mutation by IHC. All the non-PTC cases were BRAF-wild type, but 20% showed weak immunopositivity for mutated protein and were scored 6. Conclusions: BRAFV600E-mutated PTCs are more likely to be RAI-resistant. MAPK pathway activation status did not vary significantly with BRAF mutation. Immunopositivity for pMEK1/2 in most suggests a scope for MEK1-targeted therapy in recalcitrant PTC cases even in the absence of the BRAF mutation. In addition, IHC is a reliable technique for detecting BRAFV600E mutation but needs validation by correlation with molecular studies.

Context: Numerous pathogens (bacteria, viruses, or fungi) can cause childhood pneumonia. The clinical presentations of viral and bacterial pneumonia can be similar. Though viruses are a more common cause as compared to bacteria, antibiotics remain the first line of treatment for pneumonia. Aims: This study was planned to describe the pulmonary histopathological patterns in cases of pediatric pneumonia (age

The illness known as nonbacterial thrombotic endocarditis (NBTE) is characterized by the deposition of fibrin and thrombi on deteriorated or normal heart valves without microbes. Compared to infective endocarditis, this disease is more frequently observed in chronic inflammatory conditions and is linked to a higher incidence of thromboembolic events. Vegetations on two-dimensional echocardiography and negative blood cultures suggest the disease. It is generally associated with advanced malignancies and very rarely with squamous cell carcinoma (SCC) of the esophagus. Here, we describe the case of a 68-year-old female with SCC of the esophagus who developed NBTE.