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The multiband, multifunctional chiral metasurface with asymmetric transmission exhibits significant potential for diverse applications in modern communication systems, ranging from enhanced signal modulation and polarization control to advanced beam steering and compact antenna design. This research presents a versatile and advanced chiral metasurface operating at multiple bands with diverse functionalities, including asymmetric transmission. The proposed metasurface effectively transforms an incoming Linearly Polarized (LP) wave into a Circularly Polarized (CP) wave. Additionally, it functions as a 90° polarization rotator for the incident LP wave. The design starts with an element of a 2 × 2 supercell comprising a Square Split Ring Resonator (SSRR) and an I-shaped resonator. The right diagonal elements of a supercell undergo scaling down, giving rise to a rotational asymmetry. Chirality is introduced into the design, and cross polarization conversion is enhanced by rotating all four elements by 90° relative to each other. On the back side of the substrate, each element undergoes a 90° rotation compared to its counterpart on the front side, realizing the asymmetric transmission feature. The incorporation of multiband and multifunctional features within a single supercell equips the subject chiral metasurface to be utilized in various engineering applications.

Abstract Prospective use of perovskite hydride materials in H storage a crucial element of clean energy systems has drawn a lot of attention. The structural, electrical, mechanical, thermodynamic, and H storage qualities of Na2CaCdH6 hydride alloys were examined in this work using DFT. According to the structural properties, Na2CaCdH6 has space group 225 (Fm3m), and optimized lattice parameters and volume of Na2CaCdH6 are 3.3485 Å and 593.764 Å3. The measured gravimetric H storage capacity of Na2CaCdH6 hydrides is 2.956 wt%. The hydrides under research are semiconductors, as indicated by the computed electronic characteristics. Elastic constants, Pugh’s ratio, modulus, Poisson’s ratio, anisotropic, and microhardness of Na2CaCdH6 are calculated under mechanical properties. The hydrides are dynamically stable, as indicated by the phonon dispersion curves, but mechanically stable according to the Born criterion for elastic constant (Cij). The Cauchy’s pressure (C″ = 7.836) revealed the ductile behavior. The electronic and mechanical characteristics imply that Na2CaCdH6 hydride can conduct electricity and is also mechanically stable. Our findings shed light on the possibilities of Na2CaCdH6 perovskite hydride material for H storage utilization.

Abstract Background Tomato (Solanum lycopersicum L.) production is severely threatened by bacterial wilt, caused by the phytopathogenic bacterium Ralstonia solanacearum. Recently, nano-enabled strategies have shown tremendous potential in crop disease management. Objectives This study investigates the efficacy of biogenic nanoformulations (BNFs), comprising biogenic silica nanoparticles (SiNPs) and melatonin (MT), in controlling bacterial wilt in tomato. Methods SiNPs were synthesized using Zizania latifolia leaves extract. Further, MT containing BNFs were synthesized through the one-pot approach. Nanomaterials were characterized using standard characterization techniques. Greenhouse disease assays were conducted to assess the impact of SiNPs and BNFs on tomato plant immunity and resistance to bacterial wilt. Results The SiNPs and BNFs exhibited a spherical morphology, with particle sizes ranging from 13.02 nm to 22.33 nm for the SiNPs and 17.63 nm to 21.79 nm for the BNFs, indicating a relatively uniform size distribution and consistent shape across both materials. Greenhouse experiments revealed that soil application of BNFs outperformed SiNPs, significantly enhancing plant immunity and reducing bacterial wilt incidence by 78.29% in tomato plants by maintaining oxidative stress homeostasis via increasing the activities of antioxidant enzymes such as superoxide dismutase (31.81%), peroxidase (32.9%), catalase (32.65%), and ascorbate peroxidase (47.37%) compared to untreated infected plants. Additionally, BNFs induced disease resistance by enhancing the production of salicylic acid and activating defense-related genes (e.g., SlPAL1, SlICS1, SlNPR1, SlEDS, SlPD4, and SlSARD1) involved in phytohormones signaling in infected tomato plants. High-throughput 16 S rRNA sequencing revealed that BNFs promoted growth of beneficial rhizosphere bacteria (Gemmatimonadaceae, Ramlibacter, Microscillaceae, Anaerolineaceae, Chloroplast and Phormidium) in both healthy and diseased plants, while suppressing R. solanacearum abundance in infected plants. Conclusion Overall, these findings suggest that BNFs offer a more promising and sustainable approach for managing bacterial wilt disease in tomato plants. Graphical Abstract

Lignin, the earth’s second-most abundant biopolymer after cellulose, has long been relegated to low-value byproducts in the pulp and paper industry. However, recent advancements in valorization are transforming lignin into a sustainable and versatile feedstock for producing high-value biofuels, bioplastics, and specialty chemicals. This review explores the conversion of lignin’s complex structure, composed of syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H) units, into value-added products. We critically assess various biochemical and analytical techniques employed for comprehensive lignin characterization. Additionally, we explore strategies for lignin upgrading and functionalization to enhance its suitability for advanced biomaterials. The review emphasizes key areas of lignin valorization, including catalytic depolymerization methods, along with the associated challenges and advancements. We discuss its potential as a feedstock for diverse products such as biofuels, bioplastics, carbon fibers, adhesives, and phenolic compounds. Furthermore, the review briefly explores lignin’s inherent properties as a UV protectant and antioxidant, alongside its potential for incorporation into polymer blends and composites. By presenting recent advancements and case studies from the literature, this review highlights the significant economic and environmental benefits of lignin valorization, including waste reduction, lower greenhouse gas emissions, and decreased reliance on non-renewable resources. Finally, we address future perspectives and challenges associated with achieving large-scale, techno-economically feasible, and environmentally sustainable lignin valorization.

In 2022, 23 piped water samples from Liaquatabad town were examined study for pH, TDS, turbidity, chloride, hardness, nitrate, and sulphate. Majority of these indicators, with the exception of TDS, hardness, and sulphate, complied with the standards given by WHO and NSDWQ. Ca > Mg > Pb > Fe > Ni > Cr > As were metals that were found in that order. E. coli was found in about 74% of the samples while MPN Technique's microbial assessment, which found that more than 70% of the samples were contaminated with faecal matter. Despite having adequate physico-chemical properties in 95.6% samples, the Water Quality Index (WQI) showed that they were unsafe for drinking due to metal contamination. The samples' microbiological quality was good in just 26% of them. Untreated sewage discharge, cross-contamination and presence of faeces were all blamed for the pollution in the samples and responsible for serious health dangers.

Abstract Hereditary spastic paraplegias are a diverse group of degenerative disorders that are clinically categorized as isolated; with involvement of lower limb spasticity, or symptomatic, where spastic paraplegia is complicated by further neurological features. We sought to identify the underlying genetic causes of these disorders in the participating patients. Three consanguineous families with multiple affected members were identified by visiting special schools in the Punjab Province. DNA was extracted from blood samples of the participants. Exome sequencing was performed for selected patients from the three families, and the data were filtered to identify rare homozygous variants. ExomeDepth was used for the delineation of the copy number variants. All patients had varying degrees of intellectual disabilities, poor speech development, spasticity, a wide-based gait or an inability to walk and hypertonia. In family RDHR07, a homozygous deletion involving multiple exons and introns of SPG11 (NC000015.9:g.44894055_449028del) was found and correlated with the phenotype of the patients who had spasticity and other complex movement disorders, but not those who exhibited ataxic or indeterminate symptoms as well. In families ANMD03 and RDFA06, a nonsense variant, c.985C > T;(p.Arg329Ter) in DDHD2 and a frameshift insertion‒deletion variant of AP4B1, c.965-967delACTinsC;p.(Tyr322SerfsTer14), were identified which were homozygous in the patients while the obligate carriers in the respective pedigrees were heterozygous. All variants were ultra-rare with none, or very few carriers identified in the public databases. The three loss of function variants are likely to cause nonsense-mediated decay of the respective transcripts. Our research adds to the genetic variability associated with the SPG11 and AP4B1 variants and emphasizes the genetic heterogeneity of hereditary spastic paraplegia.

Abstract Introduction Metallic and elastomeric ligatures are widely used in orthodontics to secure the archwire within the bracket slots, but elastomeric ligatures have traditionally been associated with increased microbial colonization, which could adversely affect periodontal health. Aim This systematic review compares the periodontal effects of elastomeric and steel ligatures used for orthodontic fixed appliances. Methods Unrestricted literature search of 7 databases (MEDLINE, Scopus, Web of Science, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Virtual Health Library) up to July 2023 were performed for randomized / non-randomized clinical studies on humans comparing the two ligation methods during fixed-appliance therapy. After duplicate study selection, data extraction, and risk-of-bias assessment with the Risk of Bias (RoB) 2 or the Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) tool, random-effects meta-analyses of Mean Differences (MD) or Standardized Mean Differences (SMD) and their 95% confidence intervals (CIs) were carried out, followed by assessment of certainty of existing evidence with the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach. Results A total of 11 studies (3 randomized / 8 non-randomized) with 354 patients (mean age 14.7 years and 42% male) were included. No statistically significant differences were seen for plaque index (5 studies; SMD = 0.48; 95% CI = -0.03 to 1.00; P = 0.07), gingival index (2 studies; MD = 0.01; 95% CI = -0.14 to 0.16; P = 0.89), probing pocket depth (2 studies; MD = 0; 95% CI = -0.17 to 0.16; P = 0.97), or Streptococcus mutans counts (4 studies; SMD = 0.40; 95% CI=-0.41 to 1.20; P = 0.21). Elastomeric ligatures were associated with moderately increased total bacterial load (3 studies; SMD = 0.43; 95% CI = 0.10 to 0.76; P = 0.03). Confidence in these estimates was low in all instances due to the inclusion of non-randomized studies with high risk of bias. Conclusions Existing low quality evidence indicates that ligature method does not seem to influence the periodontal health during fixed treatment, even if elastomeric ligatures are associated with a moderate increase of bacterial load. Registration PROSPERO (CRD42023444383)

This study investigates the impact of rookie independent directors (RIDs) on agency costs. Utilizing a sample of Chinese listed firms, we employ panel ordinary least square estimations. Our findings reveal that increased RIDs is positively associated with agency costs, suggesting that rookie independent directors may exacerbate agency conflicts within Chinese firms. Also, qualified financial institutional investors and gender diversity within the board composition mitigate the positive effect of RIDs on agency costs. Overall, our study contributes to understanding corporate governance dynamics in Chinese listed firms by shedding light on the nuanced relationship between rookie independent directors and agency costs.

The rice blast disease, caused by the fungus Magnaporthe oryzae, is a significant agricultural problem that adversely impacts rice production and food security. Understanding the precise molecular pathways involved in the interaction between the pathogen and its host is crucial for developing effective disease management strategies. This study examines the crucial function of the nucleolin MoNsr1 in regulating M. oryzae physiological functions. ΔMoNsr1 deletion mutants showed reduced fungal growth, asexual sporulation, and pathogenicity compared to the wild-type. Mutants exhibited impaired conidial germination and appressoria formation, reducing infection progression. Additionally, ΔMoNsr1 deletion mutant had less turgor pressure, confirming that MoNsr1 is essential for cell wall biogenesis and resistant to external stresses. Furthermore, ΔMoNsr1 deletion mutant showed enhanced sensitivity to oxidative stress, reactive oxygen species, and cold tolerance. Our results offer a thorough understanding of the function of MoNsr1 in the virulence and stress-resilient capability in M. oryzae. These findings provide insights into the novel targets and contribute to the emergence of innovative approaches for managing rice blast disease.

Abstract Metal–organic frameworks (MOFs) have emerged as promising materials for triboelectric nanogenerators (TENGs), but the effects of ligand choice on triboelectric charge remain underexplored. Hence, this paper demonstrates the effect of single, binary, and ternary ligands on TENG performance of cobalt/cerium‐based (Co─Ce) bimetallic MOFs utilizing 2‐methylimidazole (2Melm), terephthalic acid (BDC), and benzene tricarboxylic acid (BTC) as ligands. The detailed structural characterization revealed that varying ligand chemistries led to distinct MOF features affecting TENG performance. Single ligand bimetallic MOFs (designated as CoCe‐2MeIm, CoCe‐BDC, CoCe‐BTC) has lower performance than binary ligand (designated as CoCe‐2MeIm‐BDC, CoCe‐2MeIm‐BTC, CoCe‐BDC‐BTC) and ternary ligand MOFs (designated as CoCe‐2MeIm‐BDC‐BTC). Among all, the binary ligand MOF, CoCe‐2MeIm‐BTC, shows the best results (598 V, 26.7 µA) due to the combined effect of imidazole ring and (─COO─) groups. This is attributed to lone pairs on nitrogen atoms and a delocalized π‐electron system in imidazole system in this material. CoCe‐BTC has the lowest results (31 V, 3.2 µA) due to the bulkier nature of the electron‐withdrawing (─COO─) groups and their impact on the π‐electron system of the benzene ring. This study showcases the potential of ligand chemistry manipulation to control triboelectric charge and thereby enhance MOF‐based TENG performance.

This study explores the impact of green finance and technological innovation on oil production and expulsion by comparing the Expulsinator with traditional pyrolysis methods. The Expulsinator introduces a novel approach to simulating compound production and expulsion in natural settings, utilizing hydrous decomposition in an open pass-on mode and lithostatic compression on an intact starting point disc with an undamaged mineral framework and chemical kerogen network. In contrast, traditional decomposition methods, while valuable for assessing production dynamics, are less suitable for studying primary emigration and expulsion due to sampling damage, improper pressure settings, closed-mode burning, or waterless pyrolysis. This study aims to assess the efficacy of energy production and expulsion emulation by the Expulsinator, driven by green finance initiatives, and compare it with traditional decomposition methods. Production and evacuation behaviors were evaluated using Rock Evaluation pyrolysis, HyPy, and covered small container pyrolysis (CSVP). The Expulsinator exhibited higher asphalt discharge than CSVP, attributed to increased bitumen cross-linking during traditional pyrolysis, which favors pyrobitumen formation. Variations in alkane quantities and structures were observed due to ejection impacts and production dynamics, especially delayed ejection from chromatography. Expulsinator hydrous CSVP ratios remained at 65 %, while TOC ratios exceeded 81 %. Lower gas production was observed compared to CSVP, with higher Expulsinator TOC conversion explained by the rapid removal of produced products in the open setup to prevent reformation. The Expulsinator provides valuable data on oil and gas production suitable for computational modeling tasks, highlighting the role of green finance and technological innovation in advancing sustainable energy solutions.

Introduction: Chemo- and bio-genic metallic nanoparticles (NPs), as a novel nano-enabled strategy, have demonstrated a great potential in crop health management. Objective: The current study aimed to explore the efficacy of advanced nanocomposites (NCs), integrating biogenic (bio) metallic NPs and plant immunity-regulating hormones, in crop disease control. Methods: Iron (Fe) NPs were biosynthesized using cell-free supernatant of a Fe-resistant strains, Bacillus marisflavi ZJ-4. Further, salicylic acid-coated bio-FeNPs (SI) NCs were prepared via co-precipitation method under alkaline conditions. Both bio-FeNPs and SINCs were characterized using basic analytical techniques, including Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction analysis, and scanning/transmission electron microscopy. Results: Bio-FeNPs and SINCs had variable shapes with average sizes of 72.35 nm and 65.87 nm, respectively. Under greenhouse conditions, bio-FeNPs and SINCs improved the agronomic traits of the watermelon plants, and SINCs outperformed bio-FeNPs, providing the maximum growth promotion of 32.5%. Soil-drenching with bio-FeNPs and SINCs suppressed Fusarium oxysporum f. sp. niveum-caused Fusarium wilt in watermelon, and SINCs provided better protection than bio-FeNPs, through inhibiting the fungal invasive growth within host plants. SINCs improved the antioxidative capacity and primed a systemic acquired resistance (SAR) response via activating the salicylic acid signaling pathway genes. These findings indicate that SINCs can reduce the severity of Fusarium wilt in watermelon by modulating antioxidative capacity and potentiating SAR to restrict in planta fungal invasive growth. Conclusion: This study provides new insights into the potential of bio-FeNPs and SINCs as biostimulants and bioprotectants for growth promotion and Fusarium wilt suppression, ensuring sustainable watermelon production.

Dystocia, a challenging condition in obstetrics, can arise from various causes, including fetal monsters with structural abnormalities. This case report presents a unique case of dystocia due to a fetal monster known as Perosomus Elumbis in a beetal breed goat from Pakistan. The 4-years-old pregnant doe presented with prolonged straining and failure to deliver the fetus after 8 hours of labor. Upon examination, the cervix was dilated, and only the forelimbs of the fetus were visible in the birth canal. The subsequent delivery involved the application of manual traction by using a dystocia kit, and the removal of edematous fluid from the legs. The monster fetus exhibited absence of hair growth, along with the absence of thoracic vertebrae. Two other fetuses were present, with one found dead and the other alive. Post-treatment involved fluid therapy, antibiotics, and supportive care for the doe. This case report sheds light on the occurrence of Perosomus Elumbis fetal monsters and their impact on dystocia in goat breeding. Understanding the underlying causes and implementing appropriate management strategies are crucial for successful outcomes in similar cases.

Abstract The study elucidates the potential benefits of incorporating a BiI3 interfacial layer into perovskite solar cells (PSCs). Using MAPbI3 and MAGeI3 as active layers, complemented by the robust TiO2 and Spiro-OMeTAD as the charge-transport-layers, we employed the SCAPS-1D simulation tool for our investigations. Remarkably, the introduction of the BiI3 layer at the perovskite-HTL interface significantly enhanced hole extraction and effectively passivated defects. This approach minimized charge recombination and ion migration towards opposite electrodes, thus elevating device performance relative to conventional configurations. The efficiency witnessed a rise from 19.28 to 20.30% for MAPbI3 and from 11.90 to 15.57% for MAGeI3. Additionally, MAGeI3 based PSCs saw an improved fill-factor from 50.36 to 62.85%, and a better Jsc from 13.22 to 14.2 mA/cm2, signifying reduced recombination and improved charge extraction. The FF for MAPbI3 based PSCs saw a minor decline, while the Voc slightly ascended from 1.24 to 1.25 V and Jsc from 20.01 to 21.6 mA/cm2. A thorough evaluation of layer thickness, doping, and temperature further highlighted the critical role of the BiI3 layer for both perovskite variants. Our examination of bandgap alignments in devices with the BiI3 interfacial layer also offers valuable understanding into the mechanisms fueling the observed improvements.

Connecting smart industrial components to computer networks revolutionizes business operations. However, in the Industrial Internet of Things (IIoT), the sharing of data has bandwidth, computational, and privacy issues. Researchers presented cloud computing and fine-grained access control to overcome these challenges. However, traditional centralized computing systems involve single points of failure. To mitigate these challenges, we have proposed a secure and incentive-based data-sharing framework for IIoT systems using blockchain technology. We leverage blockchain due to its ability to provide secure and tamper-resistant data storage and sharing as participants store their data on a distributed ledger (DL), preventing unauthorized access. A security protocol is designed that utilizes the properties of elliptic curve cryptography (ECC). Moreover, Shapley value is employed to calculate revenue and distribute it fairly. To perform the formal security evaluation, we have conducted extensive simulations using the Automated Validation of Internet Security Protocols and Applications (AVISPA) and Scyther protocol simulation tools, which demonstrated that our protocol is robust against various adversarial attacks. The experimental results show that the proposed incentive distribution framework demonstrated fairness in the distribution of revenue among participants.

Despite advanced health facilities in many developed countries, diabetic patients face multifold health challenges. Type 2 diabetes mellitus (T2DM) go along with conspicuous symptoms due to frequent peaks, hypoglycemia =180 mg/dL two hours postprandial, according to the American Diabetes Association (ADA)). The worse effects of Type 2 diabetes mellitus are precisely associated with the poor lifestyle adopted by patients. In particular, a healthy diet and nutritious food are the key to success for such patients. This study was done to help T2DM patients improve their health by developing a favorable lifestyle under an AI-assisted Continuous glucose monitoring (CGM) digital system. This study aims to reduce the blood glucose level fluctuations of such patients by rectifying their daily diet and maintaining their exertion vs. food consumption records. In this study, a well-precise prediction is obtained by training the ML model on a dataset recorded from CGM sensor devices attached to T2DM patients under observation. As the data obtained from the CGM sensor is time series, to predict blood glucose levels, the time series analysis and forecasting are done with XGBoost, SARIMA, and Prophet. The results of different Models are then compared based on performance metrics. This helped in monitoring various trends, specifically irregular patterns of the patient’s glucose data, collected by the CGM sensor. Later, keeping track of these trends and seasonality, the diet is adjusted accordingly by adding or removing particular food and keeping track of its nutrients with the intervention of a commercially available all-in-one AI solution for food recognition. This created an interactive assistive system, where the predicted results are compared to food contents to bring the blood glucose levels within the normal range for maintaining a healthy lifestyle and to alert about blood glucose fluctuations before the time that are going to occur sooner. This study will help T2DM patients get in managing diabetes and ultimately bring HbA1c within the normal range (

Poly(ADP-ribosyl)ation (PARylation), catalyzed by poly(ADP-ribose) polymerases (PARPs) and hydrolyzed by poly(ADP-ribose) glycohydrolase (PARG), is a kind of post-translational protein modification that is involved in various cellular processes in fungi, plants, and mammals. However, the function of PARPs in plant pathogenic fungi remains unknown. The present study investigated the roles and mechanisms of FonPARP1 in watermelon Fusarium wilt fungus Fusarium oxysporum f. sp. niveum (Fon). Fon has a single PARP FonPARP1 and one PARG FonPARG1. FonPARP1 is an active PARP and contributes to Fon pathogenicity through regulating its invasive growth within watermelon plants, while FonPARG1 is not required for Fon pathogenicity. A serine/threonine protein kinase, FonKin4, was identified as a FonPARP1-interacting partner by LC–MS/MS. FonKin4 is required for vegetative growth, conidiation, macroconidia morphology, abiotic stress response and pathogenicity of Fon. The S_TKc domain is sufficient for both enzyme activity and pathogenicity function of FonKin4 in Fon. FonKin4 phosphorylates FonPARP1 in vitro to enhance its poly(ADP-ribose) polymerase activity; however, FonPARP1 does not PARylate FonKin4. These results establish the FonKin4-FonPARP1 phosphorylation cascade that positively contributes to Fon pathogenicity. The present study highlights the importance of PARP-catalyzed protein PARylation in regulating the pathogenicity of Fon and other plant pathogenic fungi.

In the past, the occurrence of macro alga Ulva lactuca on the coastal areas of Jeju Island, Korea, has resulted in the expansion of devastating green tides, thus affecting coastal sustainability, aesthetic appearances, and tourism activities. Taking consideration of the above scenario, substantial economic costs are required for the environmental protection of the island, and it is highly recommended to employ Ulva lactuca in an alternative useful way. Hence, this paper proposes a new strategy to utilize Ulva lactuca as a tribopositive layer in a triboelectric nanogenerator (TENG). Based on the coastal bio-waste Ulva lactuca, the fabricated TENG device generates a maximum output voltage of 875 V, output current of 52 μA, and power density of 272.72 μW/cm2. Furthermore, the device presents excellent cyclic stability with no degradation in the output voltage even after 10000 consecutive cycles at a frequency of 2 Hz. The proposed TENG is further employed to charge the various commercially available capacitors, lightning LEDs, power stopwatches, and scavenge energy from body motions. It is anticipated that the proposed TENG device will pave a new way towards Ulva lactuca management for sustainable energy harvesting and clean coastlines.

Abstract The allure of perovskite solar cells (PSCs), which has captivated the interest of researchers, lies in their versatility to incorporate a wide range of materials within the cell’s structure. The compatibility of these materials plays a vital role in the performance enhancement of the PSC. In this study, multiple perovskite materials including FAPbI3, MAGeI3 and MASnI3 are numerically modelled along with the recently emerged kesterite (CBTS, CMTS, and CZTS) and zinc-based (ZnO and CdZnS) charge transport materials. To fully explore the potential of PSCs and comprehend the interplay among these materials, a total of 18 PSC structures are modeled from different material combinations. The impact of band gap, electron affinity, absorption, band alignment, band offset, electric field, recombination rate, thickness, defects, and work function were analyzed in detail through a systematic approach. The reasons for varying performance of different PSCs are also identified. Based on the simulated results, the most suitable charge transport materials are CdZnS/CMTS for FAPbI3 producing a power conversion efficiency (PCE) of 22.05%, ZnO/CZTS for MAGeI3 with PCE of 17.28% and ZnO/CBTS for MASnI3 with a PCE of 24.17%.

Tissue engineering, a rapidly advancing field in medicine, has made significant strides with the development of artificial tissue substitutes to meet the growing need for organ transplants. Three-dimensional (3D) porous scaffolds are widely utilized in tissue engineering, especially in orthopedic surgery. This study investigated the fluidic properties of diamond and gyroid structures with varying porosity levels (50–80%) using Computational Fluid Dynamics (CFD) analysis. The pressure and velocity distributions were analyzed, and it was observed that the pressure decreased gradually, whereas the velocity increased in the central area of the surface structures. Specifically, the pressure drop ranged from 2.079 to 0.984 Pa for the diamond structure and from 1.669 to 0.943 Pa for the gyroid structure as the porosity increased from 50% to 80%. It was also found that the permeability increased as the porosity level increased, with values ranging from 2.424×10−9 to 5.122×10−9 m2 for the diamond structure and from 2.966×10−9 to 5.344×10−9 m2 for the gyroid structure. The wall shear stress (WSS) was also analyzed, showing a consistent decrease with increased porosity for both types of structures, with WSS values ranging from 9.903×10−2 to 9.840×10−1 Pa for the diamond structure and from 1.150×10−1 to 7.717×10−2 Pa for the gyroid structure. Overall, this study provides insights into the fluidic properties of diamond and gyroid structures, which can be useful in various applications such as tissue engineering.

Recommender systems (RSs) play a pivotal role in mitigating information overload by aiding individuals or groups in discovering relevant and personalized information. An individual’s food preferences may vary when dining with friends compared to dining with family. Most of the existing group RSs generally assume users to be associated with a single group. However, in real-world scenarios, a user can be part of multiple groups due to overlapping/diverse preferences. This raises several challenges for traditional RSs due to the inherent complexity of group memberships, degrading the effectiveness and accuracy of the recommendations. Computing user to group membership degrees is a complex task, and conventional methods often fall short in accurately capturing the varied preferences of individuals. To address these challenges, we propose an integrated two-stage group recommendation (ITGR) framework that considers users’ simultaneous memberships in multiple groups with conflicting preferences. We employ fuzzy C-means clustering along with collaborative filtering to provide a more flexible and precise approach to membership assignment. Group formation is carried out using similarity thresholds followed by deep neural collaborative filtering (DNCF) to generate the top-k items for each group. Experiments are conducted using a large-scale recipes’ dataset, and the results demonstrate that the proposed model outperforms traditional approaches in terms of group satisfaction, normalized discounted cumulative gain (NDCG), precision, recall, and F1-measure.

The urgent need to find mitigating pathways for limiting world CO2 emissions to net zero by 2050 has led to intense research on CO2 sequestration in deep saline reservoirs. This paper reviews key advancements in lab- and simulation-scale research on petrophysical, geochemical, and mineralogical changes during CO2–brine–rock interactions performed in the last 25 years. It delves into CO2 MPD (mineralization, precipitation, and dissolution) and explores alterations in petrophysical properties during core flooding and in static batch reactors. These properties include changes in wettability, CO2 and brine interfacial tension, diffusion, dispersion, CO2 storage capacity, and CO2 leakage in caprock and sedimentary rocks under reservoir conditions. The injection of supercritical CO2 into deep saline aquifers can lead to unforeseen geochemical and mineralogical changes, possibly jeopardizing the CCS (carbon capture and storage) process. There is a general lack of understanding of the reservoir’s interaction with the CO2 phase at the pore/grain scale. This research addresses the gap in predicting the long-term changes of the CO2–brine–rock interaction using various geochemical reactive transport simulators. Péclet and Damköhler numbers can contribute to a better understanding of geochemical interactions and reactive transport processes. Additionally, the dielectric constant requires further investigation, particularly for pre- and post-CO2–brine–rock interactions. For comprehensive modeling of CO2 storage over various timescales, the geochemical modeling software called the Geochemist’s Workbench was found to outperform others. Wettability alteration is another crucial aspect affecting CO2–brine–rock interactions under varying temperature, pressure, and salinity conditions, which is essential for ensuring long-term CO2 storage security and monitoring. Moreover, dual-energy CT scanning can provide deeper insights into geochemical interactions and their complexities.

In recent decades, substantial advancements have been made in photovoltaic technologies, leading to impressive power conversion efficiencies (PCE) exceeding 25% in perovskite solar cells (PSCs). Tin-based perovskite materials, characterized by their low band gap (1.3 eV), exceptional optical absorption and high carrier mobility, have emerged as promising absorber layers in PSCs. Achieving high performance and stability in PSCs critically depends on the careful selection of suitable charge transport layers (CTLs). This research investigates the effects of five copper-based hole transport materials and two carbon-based electron transport materials in combination with methyl ammonium tin iodide (MASnI3) through numerical modelling in SCAPS-1D. The carbon-based CTLs exhibit excellent thermal conductivity and mechanical strength, while the copper-based CTLs demonstrate high electrical conductivity. The study comprehensively analyses the influence of these CTLs on PSC performance, including band alignment, quantum efficiency, thickness, doping concentration, defects and thermal stability. Furthermore, a comparative analysis is conducted on PSC structures employing both p-i-n and n-i-p configurations. The highest-performing PSCs are observed in the inverted structures of CuSCN/MASnI3/C60 and CuAlO2/MASnI3/C60, achieving PCE of 23.48% and 25.18%, respectively. Notably, the planar structures of Cu2O/MASnI3/C60 and CuSbS2/MASnI3/C60 also exhibit substantial PCE, reaching 20.67% and 20.70%, respectively.

OBJECTIVES To determine the frequency and pattern of anterior crossbite with primary and mixed dentition in School Children. METHODOLOGY A descriptive cross-sectional study was conducted at Sharif Medical and Dental College, Lahore. This study included 296 participants having either deciduous or mixed dentition, no history of orthodontic treatment, aged between 3-11 years, both genders and Pakistani nationals. Participants with a history of trauma, cleft lip/palate, or any craniofacial syndrome and systemic disease were excluded. Participant’s age, gender, skeletal class, and anterior crossbite (ACB) were recorded. The Chi-square/Fisher exact test was run to compare ACB and their pattern among gender, age group, and skeletal class. RESULTS There is a relatively high rate of anterior crossbite in this population, which is about 10%. The females were 169(57.09%) and males were 127(42.91%). The mean age was 6.92 ± 1.68 years. Overall, the ACB was present in 31(10.47%). The most common pattern of ACB was single incisor involvement (n=11, 35.48%) followed by two incisors (n=9, 29.03%), and the least was four incisors (n=5, 16.13%). The difference for ACB was statistically significant among skeletal classes (p

Brain tumors (BT) represent a severe and potentially life-threatening cancer. Failing to promptly diagnose these tumors can significantly shorten a person’s life. Therefore, early and accurate detection of brain tumors is essential, allowing for appropriate treatment and improving the chances of a patient’s survival. Due to the different characteristics and data limitations of brain tumors is challenging problems to classify the three different types of brain tumors. A convolutional neural networks (CNNs) learning algorithm integrated with data augmentation techniques was used to improve the model performance. CNNs have been extensively utilized in identifying brain tumors through the analysis of Magnetic Resonance Imaging (MRI) images The primary aim of this research is to propose a novel method that achieves exceptionally high accuracy in classifying the three distinct types of brain tumors. This paper proposed a novel Stack Ensemble Transfer Learning model called “SETL_BMRI”, which can recognize brain tumors in MRI images with elevated accuracy. The SETL_BMRI model incorporates two pre-trained models, AlexNet and VGG19, to improve its ability to generalize. Stacking combined outputs from these models significantly improved the accuracy of brain tumor detection as compared to individual models. The model’s effectiveness is evaluated using a public brain MRI dataset available on Kaggle, containing images of three types of brain tumors (meningioma, glioma, and pituitary). The experimental findings showcase the robustness of the SETL_BMRI model, achieving an overall classification accuracy of 98.70%. Additionally, it delivers an average precision, recall, and F1-score of 98.75%, 98.6%, and 98.75%, respectively. The evaluation metric values of the proposed solution indicate that it effectively contributed to previous research in terms of achieving high detection accuracy.

Agricultural soil pollution with potentially toxic trace elements (PTEs) has emerged as a significant environmental concern, jeopardizing food safety and human health. Although, conventional remediation approaches have been used for PTEs-contaminated soils treatment; however, these techniques are toxic, expensive, harmful to human health, and can lead to environmental contamination. Nano-enabled agriculture has gained significant attention as a sustainable approach to improve crop production and food security. Silicon nanomaterials (SiNMs) have emerged as a promising alternative for PTEs-contaminated soils remediation. SiNMs have unique characteristics, such as higher chemical reactivity, higher stability, greater surface area to volume ratio and smaller size that make them effective in removing PTEs from the environment. The review discusses the recent advancements and developments in SiNMs for the sustainable remediation of PTEs in agricultural soils. The article covers various synthesis methods, characterization techniques, and the potential mechanisms of SiNMs to alleviate PTEs toxicity in plant-soil systems. Additionally, we highlight the potential benefits and limitations of SiNMs and discusses future directions for research and development. Overall, the use of SiNMs for PTEs remediation offers a sustainable platform for the protection of agricultural soils and the environment.

A sustainable and resilient crop production system is essential to meet the global food demands. Traditional chemical-based farming practices have become ineffective due to increased population pressures and extreme climate variations. Recently, nanobiotechnology is considered to be a promising approach for sustainable crop production by improving the targeted nutrient delivery, pest management efficacy, genome editing efficiency, and smart plant sensor implications. This review provides deeper mechanistic insights into the potential applications of engineered nanomaterials for improved crop stress resilience and productivity. We also have discussed the technology readiness level of nano-based strategies to provide a clear picture of our current perspectives of the field. Current challenges and implications in the way of upscaling nanobiotechnology in the crop production are discussed along with the regulatory requirements to mitigate associated risks and facilitate public acceptability in order to develop research objectives that facilitate a sustainable nano-enabled Agri-tech revolution. Conclusively, this review not only highlights the importance of nano-enabled approaches in improving crop health, but also demonstrated their roles to counter global food security concerns.

Sugarcane is the world’s largest cultivated crop by biomass and is the main source of sugar and biofuel. Sucrose phosphate synthase (SPS) enzymes are directly involved in the synthesis of sucrose. Here, we analyzed and compared one of the important gene families involved in sucrose metabolism in a high and low sucrose sugarcane cultivar. A comprehensive in silico analysis of the SoSPS family displayed their phylogenetic relationship, gene and protein structure, miRNA targets, protein interaction network (PPI), gene ontology and collinearity. This was followed by a spatial expression analysis in two different sugarcane varieties. The phylogenetic reconstruction distributed AtSPS, ZmSPS, OsSPS, SoSPS and SbSPS into three main groups (A, B, C). The regulatory region of SoSPS genes carries ABRE, ARE, G-box, and MYC as the most dominant cis-regulatory elements. The PPI analysis predicted a total of 14 unique proteins interacting with SPS. The predominant expression of SPS in chloroplast clearly indicates that they are the most active in the organelle which is the hub of photosynthesis. Similarly, gene ontology attributed SPS to sucrose phosphate synthase and glucosyl transferase molecular functions, as well as sucrose biosynthetic and disaccharide biological processes. Overall, the expression of SPS in CPF252 (high sucrose variety) was higher in leaf and culm as compared to that of CPF 251 (low sucrose variety). In brief, this study adds to the present literature about sugarcane, sucrose metabolism and role of SPS in sucrose metabolism thereby opening up further avenues of research in crop improvement.

In this paper, a unique structural design methodology for chipless radio-frequency identification (RFID) tags in frequency domain is presented. The tag geometry is developed by loading an open-loop resonator with micro-metallic-cells (MMC). The realization give rise to a checkerboard resonator type with electromagnetic signatures in its radar cross section that are extremely efficient to manipulate. The resonators layout is distributed on either side of a Rogers substrate to double its coding density. The proposed chipless RFID tag has a memory of 8-bits in total. The operating band of the tag is 6.5-10.5 GHz. The tag has a high bit coding density of 10.94 bits/cm2 and spectral efficiency of 2 bits/GHz. The tag has a very compact size of 17.4 × 4.2 mm2. The simple structuring methodology and efficient resonators layout will give RFID system designers the flexibility to apply the proposed tag in a wide range of modern applications.