Search

Background: Chronic myeloid leukemia (CML) results from chromosomal translocation t(9;22) leading to the formation of the BCR-ABL fusion oncogene. CML has three stages: the chronic phase (CP), the accelerated phase (AP), and the blast crisis (BC). Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of CML. TKIs work well in CP-CML, and these patients have a survival rate similar to the normal population, but TKIs are less effective in advanced-phase CML. Even with current advances in treatment, BC-CML patients have an average overall survival of less than a year. Early recognition of CML patients at risk of disease progression can help in timely interventions with appropriate TKIs or other therapeutic modalities. Although some markers of disease progression like BCR-ABL kinase domain, ASXL1, and GATA2 mutations are available, no universal and exclusively specific molecular biomarkers exist to early diagnose CML patients at risk of CML progression for timely therapeutic interventions to delay or minimize blast crisis transformation in CML. A recent study found that all BC-CML patients harbored the FANCD2 (c.2022-5C>T) mutation. Therefore, the current study was designed to detect this FANCD2 mutant in AP-CML (early progression phase) and to clinically validate its potential as a novel molecular biomarker of early CML progression from CP to AP. Methods: Our study comprised 123 CP-CML (control group) and 60 AP-CML patients (experimental group) from 2 oncology centers, from January 2020 to July 2023. Mean hemoglobin level, WBC count, platelet count, treatment type, hepatomegaly, splenomegaly, and survival status of AP-CML patients were significantly different from those of CP-CML patients. However, as these clinical parameters cannot help in the early detection of patients at risk of CML progression, there was a need for a clinically validated biomarker of AP-CML. DNA was extracted from the patients’ blood samples, and the FANCD2 gene was sequenced using an Illumina NextSeq500 next-generation sequencer (NGS). Results: The NGS analysis revealed a unique splice-site mutation in the FANCD2 gene (c.2022-5C>T). This mutation was detected in the majority (98.3%) of AP-CML patients but in none of the CP-CML patients or healthy control sequences from genomic databases. The mutation was confirmed by Sanger sequencing. FANCD2 is a member of the Fanconi anemia pathway genes involved in DNA repair and genomic stability, and aberrations of this gene are associated with many cancers. Conclusions: In conclusion, our study shows that the somatic FANCD2 (c.2022-5C>T) mutation is a new molecular biomarker for early CML progression. We recommend further clinical validation of this biomarker in prospective clinical trials.

The pseudocontinuum models of reactions in packed beds are complicated, and an assessment of the reliability of the predictability of their numerical solution is difficult. The predictability reliability depends on validity and verifiability, whereas the numerical solutions of models of reactions in packed beds cannot be validated or verified. Scientific acceptability cannot commence by metaphysics alone, and the truth of the speculative justifications of the results of the numerical models without robust empirical confirmation is a matter of chance occurrence. Adherence to the principles of noncontradiction and mathematical consistency seems to be the minimal criterion if a pseudocontinuum model is to demonstrate a degree of reliability in prediction, simulation, and design. This article is an exposition of the verifiability, validity, and confirmability characteristics of multiphase multidimensional models of reactions in packed beds. It addresses the difficulties of validation and the complexities of construction of models of reactions in packed beds by modeling kinetic data directly to show that often the claims of validity, verifiability, or confirmability of the results of multidimensional or even one-dimensional models of chemical reactions in packed beds, in spite of robust statistical tools, should be viewed with some degree of skepticism.

Commercial construction projects (CCPs) in New Zealand contribute more to the economy than other project types. However, many face cost and time increases due to inadequate planning. Procurement pathways that involve contractors during design development provide more time to plan, collaboratively. Nevertheless, most projects are procured through traditional tender where contractors are only involved after detailed design. Through two-stage early contractor involvement (2S-ECI), contractors can provide design buildability advice for complex projects, contribute value management, carry out exploratory works, and order materials. The role of subcontractors in 2S-ECI can be significant. Six semi-structured interviews were conducted with clients, consultants, main contractors, and a subcontractor involved in large complex commercial construction projects. The findings build on the emerging body of knowledge about 2S-ECI by providing insight into subcontractor early involvement. Project complexity and market conditions were the main reasons for early subcontractor involvement. Common challenges include a lack of information sharing among the parties, non-competitive selection, and a lack of standard contract documentation. Opportunities for improvement include clarifying client expectations, educating stakeholders, and providing more equitable compensation for pre-construction services. Key drivers for subcontractor involvement include project complexity, market conditions, ordering long-lead-time systems, and performance specifications. Specialist early sub-trades include electrical, mechanical, structural steel, and façades. Subcontractors should typically be engaged as early as possible, often concurrently via main contractors to share performance risk. Pre-construction services provided by subcontractors include planning and sequencing; design buildability analysis; risk mitigation; value management; budget advice; systems procurement; design solutions; and document control systems. Advantages include obtaining specialist project knowledge and improving completion certainty. Producing a pre-construction services agreement (PCSA) for subcontractors may address challenges, as has been carried out for main contractors, but there is still a gap in the contractual framework for 2S-ECI for subcontractors.

Given that some suspected perpetrators were wrongly convicted, a defective bitemark analysis is comparable to dentists’ most crucial clinical decisions regarding assessment. Bias affects human bitemark analysis beyond the limitation of the evidence itself. The aim of this study was to explore the potential for different types of bias in bitemark analysis and the methods involved in that analysis by conducting a scoping review. Results showed that the 14 articles that explore the topic of bias in bitemark analysis were published from 2006-2022. Publications were from the USA mainly (n = 7), followed by the UK (n = 3), Australia (n = 2), New Zealand, (n = 1) and the Netherlands (n = 1). Of these publications, 36% addressed contextual bias, while 57% acknowledged cognitive bias. According to the findings, preventive measures consist of limiting the availability of unrelated data during research, employing several comparison samples for a more impartial assessment, and repeating the analysis while being blind to past findings. Nevertheless, the physical limitations of the evidence such as distortions are still strongly present.

Modular construction (MC) is a promising concept with the potential to revolutionize the construction industry (CI). The sustainability aspects of MC, among its other encouraging facets, have garnered escalated interest and acclaim among the research community, especially in the context of climate change (CC) mitigation efforts. Despite numerous scholarly studies contributing to the understanding of MC, a holistic review of the prevailing literature that systematically documents the impact of utilizing MC on CC mitigation remains scarce. The study conducts a systematic literature review (SLR) of the pertinent literature retrieved from the Scopus repository to explore the relationship between MC and CC mitigation. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, the SLR was conducted on 31 shortlisted articles published between 2010 and 2023. The findings of the study reveal that MC can mitigate the climate crisis by reducing GHG emissions, curtailing resource intensiveness by enabling a circular economy (CE), fomenting energy efficiency, and fostering resourceful land use and management in the CI. A conceptual framework based on the findings of the previous literature is proposed in this study, which outlines several strategies for CC mitigation that can be implemented by the adoption of MC in the CI. The current study is a humble effort to review various offerings of MC to help mitigate CC in the era of striving for global sustainability. For industry practitioners and policymakers, this study highlights the viability of leveraging MC for CC mitigation, aiming to inspire better decision making for sustainable development in the CI. Similarly, for researchers, it presents MC as a potential tool for CC mitigation that can be further explored in terms of its associated factors, and focused frameworks can be developed.

Understanding electrochemical reactions at the surface of electrodes requires the accurate calculation of key parameters—the transfer coefficient (α), diffusion coefficient (D0), and heterogeneous electron transfer rate constant (k0). The choice of method to calculate these parameters requires careful consideration based on the nature of the electrochemical reaction. In this study, we conducted the cyclic voltammetry of paracetamol to calculate the values of these parameters using different methods and present a comparative analysis. Our results demonstrate that the Ep − Ep/2 equation for α and the modified Randles–Ševčík equation for D0 is particularly effective for the calculations of these two parameters. The Kochi and Gileadi methods are reliable alternatives for the calculation of k0. Nicholson and Shain’s method using the equation k0 = Ψ(πnD0Fν/RT)1/2 gives the overestimated values of k0. However, the value of k0 calculated using the plot of ν−1/2 versus Ψ (from the Nicholson and Shain equation, where ν is scan rate) agrees well with the values calculated from the Kochi and Gilaedi methods. This study not only identifies optimal methodologies for quasi-reversible reactions but also contributes to a deeper understanding of electrochemical reactions involving complex electron transfer and coupled chemical reactions, which can be broadly applicable in various electrochemical studies.

In this paper, we study the Camassa–Holm type equation, which has applications in mathematical physics and engineering. Its applications extend across disciplines, contributing to our understanding of complex systems and helping to develop innovative solutions in diverse areas of research. Our main aim is to construct closed-form solutions of the equation using a powerful technique, namely the Lie group analysis method. Firstly, we derive the Lie point symmetries of the equation. Thereafter, the equation is reduced to non-linear ordinary differential equations using symmetry reductions. Furthermore, the solutions of the equation are derived using the extended Jacobi elliptic function technique, the simplest equation method, and the power series method. In conclusion, we construct conservation laws for the equation using Noether’s theorem and the multiplier approach, which plays a crucial role in understanding the behavior of non-linear equations, especially in physics and engineering, and these laws are derived from fundamental principles such as the conservation of mass, energy, momentum, and angular momentum.

Students’ behavioral and emotional engagement in the classroom environment may reflect the students’ learning experience and subsequent educational outcomes. The existing research has overlooked the measurement of behavioral and emotional engagement in an offline classroom environment with more students, and it has not measured the student engagement level in an objective sense. This work aims to address the limitations of the existing research and presents an effective approach to measure students’ behavioral and emotional engagement and the student engagement level in an offline classroom environment during a lecture. More precisely, video data of 100 students during lectures in different offline classes were recorded and pre-processed to extract frames with individual students. For classification, convolutional-neural-network- and transfer-learning-based models including ResNet50, VGG16, and Inception V3 were trained, validated, and tested. First, behavioral engagement was computed using salient features, for which the self-trained CNN classifier outperformed with a 97%, 91%, and 83% training, validation, and testing accuracy, respectively. Subsequently, the emotional engagement of the behaviorally engaged students was computed, for which the ResNet50 model surpassed the others with a 95%, 90%, and 82% training, validation, and testing accuracy, respectively. Finally, a novel student engagement level metric is proposed that incorporates behavioral and emotional engagement. The proposed approach may provide support for improving students’ learning in an offline classroom environment and devising effective pedagogical policies.

This article highlights the oscillatory properties of second-order Emden–Fowler delay differential equations featuring sublinear neutral terms and multiple delays, encompassing both canonical and noncanonical cases. Through the proofs of several theorems, we investigate criteria for the oscillation of all solutions to the equations under study. By employing the Riccati technique in various ways, we derive results that expand the scope of previous research and enhance the cognitive understanding of this mathematical domain. Additionally, we provide three illustrative examples to demonstrate the validity and applicability of our findings.

This present article examines the frequency control of a dual-area interconnected hybrid power system that integrates conventional as well as non-conventional sources with additional support from electric vehicles. The complicated, non-linear behavior of the system adds to the grid’s already high level of complexity. To navigate this complex environment, it becomes essential to develop a resilient controller. In this respect, a robust secondary controller is developed to handle the problem. The controller is developed while taking into account the intricate design of the contemporary power system. An extensive comparison between well-established controllers is presented to verify the efficacy of the proposed controller. An AI-based optimization technique, namely, COVID-19, is employed to obtain optimal values for different parameters of the controller. This work also investigates the effect of the FACTS device as a static synchronous series compensator (SSSC) on the dynamics of the system. Moreover, it also investigates the role of electric vehicles (EVs) and an SSSC on system stability. Further, the developed system is subjected to significant load variations and intermittent solar and wind disturbances to check the response of the optimal controller under dynamic conditions. The results demonstrate that the proposed controller reactions successfully handle system disturbances, highlighting the strength of the proposed controller design. Lastly, a case study on an IEEE-39 bus system is carried out to check the optimality of the proposed secondary controller.

Background: Liraglutide, a long-acting glucagon-like peptide-1 receptor agonist (GLP1RA), is a well-established anti-diabetic drug, has also been approved for the treatment of obesity at a dose of 3 mg. There are a limited number of studies in the literature that have looked at changes in metabolite levels before and after liraglutide treatment in patients with obesity. To this end, in the present study we aimed to explore the changes in the plasma metabolomic profile, using liquid chromatography-high resolution mass spectrometry (LC-HRMS) in patients with obesity. Methods: A single-center prospective study was undertaken to evaluate the effectiveness of 3 mg liraglutide therapy in twenty-three patients (M/F: 8/15) with obesity, mean BMI 40.81 ± 5.04 kg/m2, and mean age of 36 ± 10.9 years, in two groups: at baseline (pre-treatment) and after 12 weeks of treatment (post-treatment). An untargeted metabolomic profiling was conducted in plasma from the pre-treatment and post-treatment groups using LC-HRMS, along with bioinformatics analysis using ingenuity pathway analysis (IPA). Results: The metabolomics analysis revealed a significant (FDR p-value ≤ 0.05, FC 1.5) dysregulation of 161 endogenous metabolites (97 upregulated and 64 downregulated) with distinct separation between the two groups. Among the significantly dysregulated metabolites, the majority of them were identified as belonging to the class of oxidized lipids (oxylipins) that includes arachidonic acid and its derivatives, phosphorglycerophosphates, N-acylated amino acids, steroid hormones, and bile acids. The biomarker analysis conducted using MetaboAnalyst showed PGP (a21:0/PG/F1alpha), an oxidized lipid, as the first metabolite among the list of the top 15 biomarkers, followed by cysteine and estrone. The IPA analysis showed that the dysregulated metabolites impacted the pathway related to cell signaling, free radical scavenging, and molecular transport, and were focused around the dysregulation of NF-κB, ERK, MAPK, PKc, VEGF, insulin, and pro-inflammatory cytokine signaling pathways. Conclusions: The findings suggest that liraglutide treatment reduces inflammation and modulates lipid metabolism and oxidative stress. Our study contributes to a better understanding of the drug’s multifaceted impact on overall metabolism in patients with obesity.

This study evaluates the preparation of novel ternary functional adsorbents based on polyaniline, zinc oxide nanoparticles, and moringa oleifera gum to produce zinc oxide/Moringa oleifera gum-grafted L-methionine-functionalized polyaniline bionanocomposites (ZM-g-Pani) and employed to sequestrate divalent metal ions (Cd2+, Hg2+ and Pb2+) from wastewater samples. The morphological and structural properties of ZM-g-Pani were exploited using FT-IR, FE-SEM/EDS, TEM, and XRD. FT-IR and FE-SEM studies show that the as prepared nanocomposite has an abundant number of reactive groups and a porous structure, thus demonstrating outstanding divalent metal cation removal. FT-IR study confirms that the attachment of L-methionine to polyaniline is facilitated by the C-S linkage. Both TEM and FE-SEM techniques confirmed the clustered granules of ZnO over the surface of polyaniline, which ultimately provided more surface area to adsorb metal ions. The study demonstrated that Cd2+, Hg2+ and Pb2+ ions could undergo physical sorption and chemisorption simultaneously during the adsorption process. The maximum adsorption capacity was 840.33, 497.51, and 497.51 mg/g for Cd2+, Hg2+, and Pb2+, respectively. The impact of co-existing ions, including NO3−, PO43−, SO42−, Cl−, Na+, Cu2+, and Al3+, showed that there were no notable alterations in the adsorption of the selected metal ions with ZM-g-Pani. ZM-g-Pani showed eight successive regeneration cycles for Cd2+, Hg2+, and Pb2+ with more than 85% removal efficiency.

In the local building industry of Pakistan, pre-engineered steel building manufacturers mainly employ their own self-developed software and Excel sheets. These systems are based on empirical formulas mentioned in the AISI manual. Under this scenario, a need was found to validate AISI flow charts using commercial software like CUFSM 5.04 and ABAQUS R2019x. This study presents a validation of the CUFSM software and the American Iron and Steel Institute (AISI) Direct Strength Method (DSM) results of channel section flexural members using the non-linear finite element method employing ABAQUS. In this study, eight standard cold-formed channel-section (C-section) steel members were modeled and analyzed using ABAQUS to simulate realistic behavior under four-point loading conditions. The non-linear finite element models incorporated material and geometric non-linearities to capture the actual response of the steel elements. The results obtained from ABAQUS were compared with those predicted by the CUFSM and DSM, focusing on critical parameters such as nominal strength, buckling modes, and deformation patterns. During this study, it was observed that out of the selected sections, the AISI charts predict conservative and even unsafe flexural capacities in some of the cases concerning other methods, with a maximum difference of 14.03%. The differences obtained using DSM and ABAQUS when compared with the results of the AISI charts varies on both the plus and minus sides. This study will not only affect the industry in terms of innovative designs for efficient structures but also the community in regards to low-budget construction.

Recent advances in high-temperature superconductors (HTS) have made them extremely attractive for low-temperature, high-magnetic-field-power applications such as in fusion technology, where the advantages over traditional low-temperature superconductors (LTS) allow for the design of fusion reactors operating in different and more convenient regimes. However, the performance enhancement exhibited by novel conductors poses several challenges for the measurement of their superconducting properties. The high critical currents coupled with the relatively low thermal stability of the conductors and their mechanical fragility render this task a challenge, as the angular anisotropies complicate the experimental setup. In this work, we describe the development of our novel high-current measurement facility, focusing on the solutions introduced regarding critical aspects such as the superconducting leads and the sample holder design. We show how simple but effectively designed solutions can be adopted to combat the complexity of the measurement. The results reported in this work guide the development of a measurement system able to withstand high critical currents (I > 1500 A) at high magnetic fields (µ0H > 12 T) by evaluating the angular response of 4 mm wide short samples (L ~ 7.5 cm) in a robust and reproducible manner.

The current study explored the differential interaction between ethylene (ET) and abscisic acid (ABA) in relation to salt stress in mustard (Brassica juncea L.) plants. Significant reductions in seed germination, growth, and photosynthesis were observed with 100 mmol NaCl. Among the cultivars tested, the Pusa Vijay cultivar was noted as ET-sensitive. Pusa Vijay responded maximally to an application of 2.0 mmol ethephon (Eth; 2-chloethyl phosphonic acid-ethylene source), and exhibited the greatest growth, photosynthesis, activity of 1-aminocyclopropane carboxylic acid (ACC) synthase (ACS), and ET evolution. Notably, Eth (2.0 mmol) more significantly improved the seed germination percentage, germination and vigor index, amylase activity, and reduced H2O2 content under salt stress, while ABA (25 µmol) had negative effects. Moreover, the individual application of Eth and ABA on Pusa Vijay under both optimal and salt-stressed conditions increased the growth and photosynthetic attributes, nitrogen (N) and sulfur (S) assimilation, and antioxidant defense machinery. The addition of aminoethoxyvinylglycine (0.01 µmol AVG, ET biosynthesis inhibitor) to ABA + NaCl-treated plants further added to the effects of ABA on parameters related to seed germination and resulted in less effectiveness of growth and photosynthesis. In contrast, the effects of Eth were seen with the addition of fluoridone (25 µmol Flu, ABA biosynthesis inhibitor) to Eth + NaCl. Thus, it can be suggested that ET is crucial for alleviating salt-induced inhibition in seed germination, growth, and photosynthesis, while ABA collaborated with ET to offer protection by regulating nutrient assimilation and enhancing antioxidant metabolism. These findings provide insight into the complex regulatory processes involved in ET–ABA interaction, enhancing our understanding of plant growth and development and the mitigation of salt stress in mustard. It opens pathways for developing hormonal-based strategies to improve crop productivity and resilience, ultimately benefiting agricultural practices amidst a challenging environment.

Recent advancements in amorphous materials have opened new avenues for exploring unusual magnetic phenomena at the sub-nanometer scale. We investigate the phenomenon of low-temperature “magnetic hardening” in heterogeneous amorphous Fe–Ni–B–Nb thin films, revealing a complex interplay between microstructure and magnetism. Magnetization hysteresis measurements at cryogenic temperatures show a significant increase in coercivity (HC) below 25 K, challenging the conventional Random Anisotropy Model (RAM) in predicting magnetic responses at cryogenic temperatures. Heterogeneous films demonstrate a distinct behavior in field-cooled and zero-field-cooled temperature-dependent magnetizations at low temperatures, characterized by strong irreversibility. This suggests spin-glass-like features at low temperatures, which are attributed to exchange frustration in disordered interfacial regions. These regions hinder direct exchange coupling between magnetic entities, leading to magnetic hardening. This study enhances the understanding of how microstructural intricacies impact magnetic dynamics in heterogeneous amorphous thin films at cryogenic temperatures.

This article examines the oscillatory characteristics of a fourth-order Emden–Fowler differential equation, specifically when it includes a sublinear neutral term. Our methodology centers on establishing multiple theorems that introduce innovative conditions to guarantee that there are no positive solutions to the examined equation. Due to the symmetry between non-oscillatory solutions, we obtain oscillation conditions by excluding only positive solutions. We employ the Riccati technique in various ways to achieve this objective. The criteria presented in this study complement and generalize many findings published in the literature. We support the efficiency of our findings by applying them to an example.

This article explores the Ricci tensor of slant submanifolds within locally metallic product space forms equipped with a semi-symmetric metric connection (SSMC). Our investigation includes the derivation of the Chen–Ricci inequality and an in-depth analysis of its equality case. More precisely, if the mean curvature vector at a point vanishes, then the equality case of this inequality is achieved by a unit tangent vector at the point if and only if the vector belongs to the normal space. Finally, we have shown that when a point is a totally geodesic point or is totally umbilical with n=2, the equality case of this inequality holds true for all unit tangent vectors at the point, and conversely.

Land use and land cover changes (LULCCs) are vital indicators for assessing the dynamic relationship between humans and nature, particularly in diverse and evolving landscapes. This study employs remote sensing (RS) data and machine learning algorithms (MLAs) to investigate LULCC dynamics within the Indus River Delta region of Sindh, Pakistan. The focus is on tracking the trajectories of land use changes within mangrove forests and associated ecosystem services over twenty years. Our findings reveal a modest improvement in mangrove forest cover in specific areas, with an increase from 0.28% to 0.4%, alongside a slight expansion of wetland areas from 2.95% to 3.19%. However, significant increases in cropland, increasing from 22.76% to 28.14%, and built-up areas, increasing from 0.71% to 1.66%, pose risks such as altered sedimentation and runoff patterns as well as habitat degradation. Additionally, decreases in barren land from 57.10% to 52.7% and a reduction in rangeland from 16.16% to 13.92% indicate intensified land use conversion and logging activities. This study highlights the vulnerability of mangrove ecosystems in the Indus Delta to agricultural expansion, urbanization, resource exploitation, and land mismanagement. Recommendations include harmonizing developmental ambitions with ecological conservation, prioritizing integrated coastal area management, reinforcing mangrove protection measures, and implementing sustainable land use planning practices. These actions are essential for ensuring the long-term sustainability of the region’s ecosystems and human communities.

This paper presents a novel robust output feedback control that simultaneously performs both stabilization and trajectory tracking for a class of underactuated nonholonomic systems despite model uncertainties, external disturbance, and the absence of velocity measurement. To solve this challenging problem, a generalized normal form has been successfully created by employing an input–output feedback linearization approach and a change in coordinates (diffeomorphism). This research mainly focuses on the stabilization problem of nonholonomic systems that can be transformed to a normal form and pose several challenges, including (i) a nontriangular normal form, (ii) the internal dynamics of the system are non-affine in control, and (iii) the zero dynamics of the system are not in minimum phase. The proposed scheme utilizes combined backstepping and sliding mode control (SMC) techniques. Furthermore, the full-order high gain observer (HGO) has been developed to estimate the derivative of output functions and internal dynamics. Then, full-order HGO and the backstepping SMC have been integrated to synthesize a robust output feedback controller. A differential-drive type (2,0) the wheeled mobile robot has been considered as an example to support the theoretical results. The simulation results demonstrate that the backstepping SMC exhibits robustness against bounded uncertainties.

Decarbonization is gaining priority from the macro to the micro level. However, achieving this is a critical challenge, as industries are still immature. This study explores the practices used to calculate and reduce embodied carbon (EC) in New Zealand (NZ) commercial construction projects. In the Paris Agreement, NZ pledged to reduce its net GHG emissions to 50 percent below the gross 2005 levels by 2030. The built environment generates approximately 40% of global greenhouse gas (GHG) emissions, with 11% being generated by manufacturing materials. EC represents carbon dioxide (CO2) emitted into the atmosphere throughout the extraction, fabrication, transportation, and assembly of building materials. A survey questionnaire was distributed to stakeholders in commercial construction via the New Zealand Institute of Quantity Surveyors (NZIQS) open forum. Twenty-seven valid responses were analyzed. The survey tested and expanded on the interview findings. Calculating and reducing EC are not mandatory in NZ. Most industry professionals had yet to experience EC calculation in projects. Clients most commonly drive EC reduction in public projects with calculations that are often conducted during the concept or detailed design stages. The challenges in measuring and lowering EC include a lack of client willingness to fund EC calculation, lack of knowledge and experience, lack of previous cost data, lack of EC materials, and lack of fit-for-purpose EC calculation tools. These findings may inform NZ government policy initiatives supporting EC reduction to meet their 2050 target.

Perovskite solar cells (PSCs) have rapidly become a hot area of research in the photovoltaic field due to their (e.g., 26.2%), ease of fabrication, and low cost. Over the last decade the electron transport layer (ETL) has been one of the most critical elements in achieving high-performing solar cells, necessitating a higher electron mobility and superior charge extraction ability. Consequently, there is a significant demand for an improved ETL that is not only cost-effective but also exhibits high charge extraction and mobility, particularly in the context of planar solar cell architecture. Tin Oxide (SnO2) has emerged as one of the most promising high-performance inorganic ETLs suitable for PSCs. In this work, we synthesize solution-processed SnO2. The spin-coated SnO2 thin films undergo annealing at relatively low temperatures ranging from 130 °C to 180 °C and various characterization tools are employed for the evaluation of thin films.

The Water Editorial Office retracts the article “Exploring Groundwater Quality Assessment: A Geostatistical and Integrated Water Quality Indices Perspective” [...]

Subarachnoid hemorrhage (SAH) remains a major cause of cerebrovascular morbidity, eliciting severe headaches and vasospasms that have been shown to inversely correlate with vasodilator calcitonin gene-related peptide (CGRP) levels. Although dura mater trigeminal afferents are an important source of intracranial CGRP, little is known about the effects of SAH on these neurons in preclinical models. The present study evaluated changes in CGRP levels and expression in trigeminal primary afferents innervating the dura mater 72 h after experimentally induced SAH in adult rats. SAH, eliciting marked damage revealed by neurological examination, significantly reduced the density of CGRP-immunoreactive nerve fibers both in the dura mater and the trigeminal caudal nucleus in the medulla but did not affect the total dural nerve fiber density. SAH attenuated ex vivo dural CGRP release by ~40% and in the trigeminal ganglion, reduced both CGRP mRNA levels and the number of highly CGRP-immunoreactive cell bodies. In summary, we provide novel complementary evidence that SAH negatively affects the integrity of the CGRP-expressing rat trigeminal neurons. Reduced CGRP levels suggest likely impaired meningeal neurovascular functions contributing to SAH complications. Further studies are to be performed to reveal the importance of impaired CGRP synthesis and its consequences in central sensory processing.

Animal models have been essential for advancing research of fetal alcohol spectrum disorder (FASD) in humans, but few animal species effectively replicate the behavioural and clinical signs of FASD. The honey bee (Apis mellifera) is a previously unexplored research model for FASD that offers the distinct benefit of highly social behaviour. In this study, we chronically exposed honey bee larvae to incremental concentrations of 0, 3, 6, and 10% ethanol in the larval diet using an in vitro rearing protocol and measured developmental time and survival to adult eclosion, as well as body weight and motor activity of newly emerged adult bees. Larvae reared on 6 and 10% dietary ethanol demonstrated significant, dose-responsive delays to pupation and decreased survival and adult body weight. All ethanol-reared adults showed significantly decreased motor activity. These results suggest that honey bees may be a suitable social animal model for future FASD research.

Generative models offer design diversity but tend to be computationally expensive, while non-generative models are computationally cost-effective but produce less diverse and often invalid designs. However, the limitations of non-generative models can be overcome with the introduction of augmented shape signature vectors (SSVs) to represent both geometric and physical information. This recent advancement has inspired a systematic comparison of the effectiveness and efficiency of generative and non-generative models in constructing design spaces for novel and efficient design exploration and shape optimization, which is demonstrated in this work. These models are showcased in airfoil/hydrofoil design, and a comparison of the resulting design spaces is conducted in this work. A conventional generative adversarial network (GAN) and a state-of-the-art generative model, the performance-augmented diverse generative adversarial network (PaDGAN), are juxtaposed with a linear non-generative model based on the coupling of the Karhunen–Loève Expansion and a physics-informed shape signature vector (SSV-KLE). The comparison demonstrates that, with an appropriate shape encoding and a physics-augmented design space, non-generative models have the potential to cost-effectively generate high-performing valid designs with enhanced coverage of the design space. In this work, both approaches were applied to two large foil profile datasets comprising real-world and artificial designs generated through either a profile-generating parametric model or a deep-learning approach. These datasets were further enriched with integral properties of their members’ shapes, as well as physics-informed parameters. The obtained results illustrate that the design spaces constructed by the non-generative model outperform the generative model in terms of design validity, generating robust latent spaces with no or significantly fewer invalid designs when compared to generative models. The performance and diversity of the generated designs were compared to provide further insights about the quality of the resulting spaces. These findings can aid the engineering design community in making informed decisions when constructing design spaces for shape optimization, as it has been demonstrated that, under certain conditions, computationally inexpensive approaches can closely match or even outperform state-of-the art generative models.

Exosomes are extracellular vesicles of endosomal origin, ranging from 30 to 150 nm in diameter, that mediate intercellular transfer of various biomolecules, such as proteins, lipids, nucleic acids, and metabolites. They modulate the functions of recipient cells and participate in diverse physiological and pathological processes, such as immune responses, cell–cell communication, carcinogenesis, and viral infection. Stem cells (SCs) are pluripotent or multipotent cells that can differentiate into various cell types. SCs can also secrete exosomes, which exhibit remarkable therapeutic potential for various diseases, especially in the field of regenerative medicine. For example, exosomes derived from mesenchymal stem cells (MSCs) contain proteins, lipids, and miRNAs that can ameliorate endocrine disorders, such as diabetes and cancer. Exosomes from SCs (sc-exos) may offer similar advantages as SCs, but with reduced risks and challenges. Sc-exos have lower tumorigenicity, immunogenicity, and infectivity. They can also deliver drugs more efficiently and penetrate deeper into tissues. In this review, we provide an overview of the recent advances in sc-exos and their therapeutic applications in various diseases, such as diabetes and cancer. We also elucidate how the biological effects of sc-exos depend on their molecular composition. We also address the current challenges and future directions of using sc-exos.

(1) Background: Microsporidiosis (nosemosis) is an intestinal disorder of adult honey bees caused by the microsporidian pathogens Vairimorpha apis and Vairimorpha ceranae. In Canada, fumagillin is an approved antibiotic used to treat this disease. However, the recommended dosage is based on efficacy studies for V. apis, the native pathogen in European honey bees. Since the detection of V. ceranae in Apis mellifera, V. ceranae became more prevalent in managed European honey bees and seems to have replaced V. apis due to yet unknown reasons. (2) Methods: This colony study investigated the efficacy of fumagillin administered in the fall to colonies infected with both V. apis and V. ceranae and its effects on the Vairimorpha species’ prevalence overwinter. Spore loads in control and fumagillin-treated colonies were analysed by microscopy; Vairimorpha species prevalence was determined molecularly and infection and treatment effects on colony productivity were assessed. (3) Results: Fall fumagillin treatment was associated with a temporary reduction in spore load, but there was no difference in spore loads between treated and control colonies the following spring. Interestingly, fumagillin-treated colonies had a significantly greater prevalence of V. ceranae relative to V. apis the following spring, suggesting fumagillin is less effective in controlling V. ceranae.

To generate an orthophoto mosaic from a collection of aerial images, the original images are first orthorectified individually using a Digital Surface Model (DSM). Then, they are stitched together along some determined seamlines to form the orthophoto mosaic. Determining appropriate seamlines is a critical process, as it affects the visual and geometric quality of the results. The stitching process can usually be done in frame-to-frame or multi-frame modes. Although the latter is more efficient, both still involve a lot of pre-processing, such as creating individual orthophotos, image registration, and overlap extraction. This paper presents a novel coarse-to-fine approach that directly determines the seamline network without such pre-processing. Our method has been specifically applied for UAV photogrammetry projects where, due to the large number of images and the corresponding overlaps, the orthophoto mosaic generation can be very challenging and time-consuming. We established the seamlines simultaneously for all the images through a two-step process. First, a DSM was generated, and a low-resolution grid was overlayed. Then, for each grid point, an optimal image was selected. Then, the grid cells are grouped into polygons based on their corresponding optimal image. Boundaries of these polygons established our seamline network. Thereafter, to generate the orthophoto mosaic, we overlayed a higher/full resolution grid on the top of the DSM, the optimal image of each point of which was quickly identified via our low-resolution polygons. In this approach, not only seamlines were automatically generated, but also were the need for the creation, registration, and overlap extraction of individual orthophotos. Our method was systematically compared with a conventional frame-to-frame (CF) technique from different aspects, including the number of double-mapped areas, discontinuities across the seamlines network, and the amount of processing time. The outcomes revealed a 46% decrease in orthophoto generation time and a notable reduction in the number of double-mapped areas, sawtooth effects, and object discontinuities within the constructed orthophoto mosaic.

Background: Understanding post-stroke fatigue (PSF) and its associated factors is crucial for effective therapy and rehabilitation. This study aimed to assess the mediating role of the excessive daytime sleepiness-related functional status (SFS) on the relationship between sleep and the severity of fatigue in subacute stroke survivors. Methods: Subacute stroke survivors (n = 50; male = 38; female = 12), completed a cross-sectional study involving the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the insomnia severity index (ISI), the functional outcome of the sleep questionnaire (FOSQ), and the fatigue severity scale (FSS). Results: The SFS mediated the association between the severity of fatigue and sleep problems. The PSQI and FOSQ (b = −0.37, p < 0.001), and the FOSQ and FSS were correlated (b = −0.18, p < 0.05), with a significant indirect effect of the PSQI on the FSS. The ISI correlated with the FOSQ (b = −0.20, p < 0.001), with significant direct (b = 0.15, p < 0.001), as well as indirect, effects of the ISI on the FSS. The ESS correlated with the FOSQ (b = −0.23, p < 0.001), with a significant indirect effect of the ESS on the FSS. Conclusions: In subacute stroke survivors, fatigue and sleep are linked. Increased understanding of sleep-PSF may help in exploring new targets for supplement therapy.

A Pb-free FASnI3 perovskite solar cell improved by using Cu2O/ZnO as two-dimensional-based hole/electron transport nanolayers has been proposed and studied by using a SCAPS-1D solar simulator. To calibrate our study, at first, an FTO/ZnO/MAPbI3/Cu2O/Au multilayer device was simulated, and the numerical results (including a conversion efficiency of 6.06%, an open circuit potential of 0.76 V, a fill factor parameter of 64.91%, and a short circuit electric current density of 12.26 mA/cm2) were compared with the experimental results in the literature. Then, the conversion efficiency of the proposed FASnI3-based solar cell was found to improve to 7.83%. The depth profile energy levels, charge carrier concentrations, recombination rate of electron/hole pair, and the FASnI3 thickness-dependent solar cell efficiency were studied and compared with the results obtained for the MAPbI3-containing device (as a benchmark). Interestingly, the FASnI3 material required to obtain an optimized solar cell is one-half of the material required for an optimized MAPbI3-based device, with a thickness of 200 nm. These results indicate that developing more environmentally friendly perovskite solar cells is possible if suitable electron/hole transport layers are selected along with the upcoming Pb-free perovskite absorber layers.

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography–high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace.

Prefabricated construction is expanding and taking over traditional construction with more intervention of prefabricated building elements. Despite prefabricated construction reducing health and safety risks compared to conventional construction, there is still a risk that needs to be addressed. This article aims to investigate prefabricated construction safety through accident analysis. The accident data was retrieved through governmental resources and covered accident claims, safety costs, vulnerable occupations, and injuries (including type, cause, prior activity, and site of injury). Prefabricated construction safety is then simplistic and predictively modelled. The most common trend has been reported with graphical representation and relevant discussion. Furthermore, the trends are forecasted by using the ARIMA model (p, d, q) based on key performance parameters. The conclusion has been driven by the current status of prefabricated construction safety. This study is a pioneer in modelling prefabricated construction safety to enhance understanding of accidents and forecasting through optimization.

This paper delves into the asymptotic and oscillatory behavior of all classes of solutions of fourth-order nonlinear neutral delay differential equations in the noncanonical form with damping terms. This research aims to improve the relationships between the solutions of these equations and their corresponding functions and derivatives. By refining these relationships, we unveil new insights into the asymptotic properties governing these solutions. These insights lead to the establishment of improved conditions that ensure the nonexistence of any positive solutions to the studied equation, thus obtaining improved oscillation criteria. In light of the broader context, our findings extend and build upon the existing literature in the field of neutral differential equations. To emphasize the importance of the results and their applicability, this paper concludes with some examples.

In maritime logistics, accurately predicting the Estimated Time of Arrival (ETA) of vessels is pivotal for optimizing port operations and the global supply chain. This study proposes a machine learning method for predicting ETA, drawing on historical Automatic Identification System (AIS) data spanning 2018 to 2020. The proposed framework includes a preprocessing module for extracting, transforming, and applying feature engineering to raw AIS data, alongside a modeling module that employs an XGBoost model to accurately estimate vessel travel times. The framework’s efficacy was validated using AIS data from the Port of Houston, and the results indicate that the model can estimate travel times with a Mean Absolute Percentage Error (MAPE) of just 5%. Moreover, the model retains consistent accuracy in a simplified form, pointing towards the potential for reduced complexity and increased generalizability in maritime ETA predictions.

Light-emitting diode (LED) technology is a form of artificial lighting that offers precise control over spectral composition, creating specific conditions for plant growth and development. However, the influence of various LED wavelengths on the regeneration characteristics in African violet (AV) has not been extensively explored. This study aims to investigate the changes in the regeneration traits of AV when exposed to different LED light colors within controlled conditions. In this study, AV leaf cuttings were prepared and subjected to white, red, blue, and red + blue light colors for a period of three months in a growth chamber. Afterward, they were transferred to the laboratory for further analysis. The results indicated that the AVs treated with red + blue colors exhibited the most significant improvement in several morpho-physiological traits of both the roots and shoots. The highest total biomass (2.96 g), shoot fresh weight (1.76 g), root dry weight (0.14 g), root volume (3.10 cm3), and shoot length (1.60 cm) were observed in this treatment group. Furthermore, the highest levels of photosynthetic pigments, such as chlorophyll a, chlorophyll b, and carotenoids (0.14, 0.12, and 3.80 mg g−1 f.w., respectively), were predominantly observed in the red + blue treatment group. In conclusion, this study introduces a novel methodology for optimizing lighting conditions to enhance the regeneration of African violets, shedding light on the potential for improving AV regeneration practices.

This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to dynamically process AIS data by cleaning, compressing, and enhancing it with additional attributes such as online traffic volume, origin/destination, vessel trips, trip direction, and vessel routing. This processed data, enriched with valuable details, serves as an alternative to raw AIS data stored in a centralized database. For user interactions, a user interface is designed to query the database and provide real-time information on a map-based interface. To deal with false or missing AIS records, two methods, dead reckoning and machine learning techniques, are employed to anticipate the trajectory of the vessel in the next time steps. To evaluate each method, several metrics are used, including R squared, mean absolute error, mean offset, and mean offset from the centerline. The functionality of the proposed system is showcased through a case study conducted in the Gulf Intracoastal Waterway (GIWW). Three years of AIS data are collected and processed as a simulated API to transmit AIS records every five minutes. According to our results, the Seq2Seq model exhibits strong performance (0.99 R squared and an average offset of ~1400 ft). However, the second scenario, dead reckoning, proves comparable to the Seq2Seq model as it involves recalculating vessel headings by comparing each data point with the previous one.

Diabetes mellitus (DM) is characterized by an absolute decline in insulin secretion and peripheral resistance and is the most prevalent metabolic and endocrine disorder. However, the pathogenesis of DM also includes adipocyte insulin resistance, increased glucagon secretion, increased renal glomerular glucose absorption, and neurotransmitter dysfunction. Although there is a wide spectrum of therapeutics available for glycemic control, owing to the identification of various pathogenic determinants of DM, management of DM remains challenging and complex. Current therapeutic interventions against DM focus mostly on glycemic control without considering the other pathological determinants that eventually lead to treatment failure and the progression of DM. Furthermore, long-term use of these conventionally available anti-diabetic drugs leads to various side effects, henceforth development of novel drugs against DM remains an unending search strategy for researchers. Various studies conducted in various parts of the world have proposed that these novel therapeutic interventions target multiple and alternate pathogenic hotspots involved in DM. The current review article discusses novel therapeutic options that hold particular promise to support their safety and discuss the side effects resulting from their use so that these novel candidate drugs can be effectively fabricated into potential drugs for the treatment of DM.

Groundwater plays a major role in addressing the worldwide problem of water scarcity and food security. With a growing population and increasing urbanization, there is a rising demand for groundwater to meet agricultural and domestic water needs. A variety of advanced approaches are necessary to sustain groundwater management. This study investigated the age and origin of groundwater, as well as its relationship with anthropogenic and climatic factors. Stable isotopes were used, namely oxygen-18 (18O) and deuterium (2H) for the estimation of groundwater origin and radioactive isotopes of Tritium (3H) for the estimation of its age. The investigation of stable isotopes revealed that the aquifer is predominantly influenced by river water, with a minor contribution from rainwater. Furthermore, the analysis of radioactive isotopes revealed that the groundwater age ranges from 5 to 50 years old in most areas. Older groundwater is predominantly found in urban areas, while younger groundwater is present in agricultural and woodland regions. However, the presence of “old” water in the upper groundwater layers in urban areas is attributed to over-abstraction and limited natural recharge. The primary climatic factor that governs the age and origin of groundwater is rainfall upstream of the study area, which directly contributes to the river flows. The rainfall is high in the east but, due to urbanization, recharge is decreased. Consequently, old and river recharge groundwater is found in this area. These observations underscore the unsustainable and alarming use of groundwater in urban areas.

This paper delves into the investigation of quasi-linear neutral differential equations in the third-order canonical case. In this study, we refine the relationship between the solution and its corresponding function, leading to improved preliminary results. These enhanced results play a crucial role in excluding the existence of positive solutions to the investigated equation. By building upon the improved preliminary results, we introduce novel criteria that shed light on the nature of these solutions. These criteria help to distinguish whether the solutions exhibit oscillatory behavior or tend toward zero. Moreover, we present oscillation criteria for all solutions. To demonstrate the relevance of our results, we present an illustrative example. This example validates the theoretical framework we have developed and offers practical insights into the behavior of solutions for quasi-linear third-order neutral differential equations.

Background: The use of natural products in skin care has been valued for their tremendous therapeutic benefits since ancient times. The current study was aimed at exploring the Leptadenia pyrotechnica plant extract and development of a stable emulgel loaded with the same extract to assess its cosmeceutical potentials. Methodology: A stable emulgel loaded with methanolic plant extract along with its control gel was prepared by homogenization. The antioxidant potential of extracts prepared in different solvents (methanol MLP, ethanol ELP, n-hexane nLP, ethyl acetate EALP, and petroleum ether PLP) was determined by DPPH scavenging activity. The presence of phytochemicals was confirmed by total phenolic and flavonoid content analysis (TPC/TFC). HPLC was used for quantification of bioactive components. FTIR analysis was performed for confirmation of functional groups. SPF was calculated via spectroscopic analysis for extract, control gel, and extract loaded emulgel. Stability studies included physical evaluation, pH, conductivity, spreadability, and rheological testing of both control and test emulgels at different temperatures, i.e., 8 °C ± 1, 25 °C ± 1, 40 °C ± 1, 40 °C ± 1 with RH of 75% for a period of 90 days. Results: DPPH radical scavenging activity showed the highest antioxidant activity of 85.5% ± 2.78 for MLP. TPC and TFC were also found to be highest for the methanolic fraction, i.e., 190.98 ± 0.40 mgGAE/g and 128.28 ± 2.64 mgQE/g, respectively. The SPF of methanolic extract, placebo gel, and LPEG was 13.43 ± 0.46, 2.37 ± 0.33, and 7.28 ± 0.56, respectively. HPLC assay confirmed the presence of catechin, vanillic acid, caffeic acid, and sinapinic acid. Rheological analysis showed that formulation has pseudo-plastic flow behavior. Other stability tests also revealed that prepared emulgel is a stable one. Conclusion: A stable emulgel loaded with Leptadenia pyrotechnica plant extract was successfully prepared and characterized for its cosmetic effects.

Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR–SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR–SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR–SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively.

In the present study, the effect of annealing treatment on the room-temperature mechanical performance of AZ61, AZ61-0.5CaO and AZ61-1CaO was thoroughly investigated. The as-rolled samples were annealed at 400 °C for 1 h followed by furnace cooling. Microstructural characterization was carried out using optical microscopy (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and electron back-scattered diffraction (EBSD). Moreover, room-temperature uniaxial tensile tests were carried out on the non-annealed and annealed samples along the rolling direction at the strain rate of 10−3 s−1. Microstructural analysis showed the presence of profuse {101¯2} twinning in non-annealed samples and the twinning fraction was increased by the addition of CaO content. SEM showed the formation of precipitates in the AZ61-CaO alloys and TEM confirmed the precipitates to be (Mg, Al)2Ca. The room-temperature tensile tests showed that the mechanical properties of AZ61 were slightly reduced by the addition of CaO, which was attributed to the higher local stress concentration due to the twin–twin interactions. Furthermore, the annealing treatment led to significant enhancement in the YS and UTS of AZ61-1CaO, which is related to the precipitation hardening induced by the intermetallic precipitates.

This research work focuses on a Near-Infra-Red (NIR) finger-images-based multimodal biometric system based on Finger Texture and Finger Vein biometrics. The individual results of the biometric characteristics are fused using a fuzzy system, and the final identification result is achieved. Experiments are performed for three different databases, i.e., the Near-Infra-Red Hand Images (NIRHI), Hong Kong Polytechnic University (HKPU) and University of Twente Finger Vein Pattern (UTFVP) databases. First, the Finger Texture biometric employs an efficient texture feature extracting algorithm, i.e., Linear Binary Pattern. Then, the classification is performed using Support Vector Machine, a proven machine learning classification algorithm. Second, the transfer learning of pre-trained convolutional neural networks (CNNs) is performed for the Finger Vein biometric, employing two approaches. The three selected CNNs are AlexNet, VGG16 and VGG19. In Approach 1, before feeding the images for the training of the CNN, the necessary preprocessing of NIR images is performed. In Approach 2, before the pre-processing step, image intensity optimization is also employed to regularize the image intensity. NIRHI outperforms HKPU and UTFVP for both of the modalities of focus, in a unimodal setup as well as in a multimodal one. The proposed multimodal biometric system demonstrates a better overall identification accuracy of 99.62% in comparison with 99.51% and 99.50% reported in the recent state-of-the-art systems.

The El Nino Southern Oscillation (ENSO) phenomenon is devastating as it negatively impacts global climatic conditions, which can cause extreme events, including floods and droughts, which are harmful to the region’s economy. Pakistan is also considered one of the climate change hotspot regions in the world. Therefore, the present study investigates the effect of the ENSO on extreme precipitation events across the Upper Indus Basin. We examined the connections between 11 extreme precipitation indices (EPIs) and two ENSO indicators, the Southern Oscillation Index (SOI) and the Oceanic Niño Index (ONI). This analysis covers both annual and seasonal scales and spans the period from 1971 to 2019. Statistical tests (i.e., Mann–Kendall (MK) and Innovative Trend Analysis (ITA)) were used to observe the variations in the EPIs. The results revealed that the number of Consecutive Dry Days (CDDs) is increasing more than Consecutive Wet Days (CWDs); overall, the EPIs exhibited increasing trends, except for the Rx1 (max. 1-day precipitation) and Rx5 (max. 5-day precipitation) indices. The ENSO indicator ONI is a temperature-related ENSO index. The results further showed that the CDD value has a significant positive correlation with the SOI for most of the UIB (Upper Indus Basin) region, whereas for the CWD value, high elevated stations gave a positive relationship. A significant negative relationship was observed for the lower portion of the UIB. The Rx1 and Rx5 indices were observed to have a negative relationship with the SOI, indicating that El Nino causes heavy rainfall. The R95p (very wet days) and R99p (extreme wet days) indices were observed to have significant negative trends in most of the UIB. In contrast, high elevated stations depicted a significant positive relationship that indicates they are affected by La Nina conditions. The PRCPTOT index exhibited a negative relationship with the SOI, revealing that the El Nino phase causes wet conditions in the UIB. The ONI gave a significant positive relationship for the UIB region, reinforcing the idea that both indices exhibit more precipitation during El Nino. The above observations imply that while policies are being developed to cope with climate change impacts, the effects of the ENSO should also be considered.

Groundwater is an important source of freshwater. At the same time, anthropogenic activities, in particular, industrialization, urbanization, population growth, and excessive application of fertilizers, are some of the major reasons for groundwater quality deterioration. Therefore, the present study is conducted to evaluate groundwater quality by using integrated water quality indices and a geospatial approach to identify the different water quality zones and propose management strategies for the improvement of groundwater quality. Groundwater quality was evaluated through the physicochemical parameters (pH, chloride (Cl−), fluoride(F−), iron (Fe−2), nitrate (NO3−1), nitrite (NO2), arsenic (As), total hardness, bicarbonate (HCO3−), calcium (Ca+2), magnesium (Mg+2), color, taste, turbidity, total dissolved solids (TDS)) and microbiological parameters including total coliforms, fecal coliforms, and Escherichia coli of samples collected from the water and sanitation agency (WASA) and urban units. Irrigation parameters crucial to the assessment, including (electrical conductivity (EC), residual sodium carbonates (RSC), and sodium adsorption ratio (SAR)), were also collected at more than 1100 sites within the study area of upper and central Punjab. After collecting the data of physicochemical parameters, the analysis of data was initiated to compute the water quality index for groundwater quality, a four-step protocol in which the Analytical Hierarchy Process (AHP) was used to determine the weights of selected parameters by generating a pairwise matrix, on the relative importance of parameters using the Satty scale. The index was then classified into five classes for quality assessment of drinking water (excellent, good, medium, bad, and very bad) and four classes for irrigation water quality assessment (excellent, good, permissible, and unsuitable). After computing the index values for drinking as well as irrigation purposes, the values were interpolated, and various maps were developed to identify the status of groundwater quality in different zones of the study area. Mitigation strategies for water pollution involve source control, such as monitoring industrial discharge points and managing waste properly. Additionally, treating wastewater through primary, secondary, or tertiary stages significantly improves water quality, reducing contaminants like heavy metals, microbiological agents, and chemical ions, safeguarding water resources. The findings highlight significant regional variations in water quality issues, with heavy metal concerns concentrated notably in Lahore and widespread emerging microbiological contamination across all studied divisions. This suggests a systemic problem linked to untreated industrial effluents and poorly managed sewerage systems. The computed indices for the Lahore, Sargodha, and Rawalpindi divisions indicate water quality ranging from marginal to unfit, underscoring the urgency for remediation. Conversely, other divisions fall within a medium class, potentially suitable for drinking purposes. Notably, microbiological contamination at 27% poses a major challenge for water supply agencies, emphasizing the critical need for pre-disposal primary, secondary, and tertiary treatments. These treatments could potentially rehabilitate 9%, 35%, and 41% of the study area, respectively, pointing toward tangible, scalable solutions critical for safeguarding broader water resources and public health. With the current pace of water quality deterioration, access to drinking water is a major problem for the public. The government should prioritize implementing strict monitoring mechanisms for industrial effluent discharge, emphasizing proper waste management to curb groundwater contamination. Establishing comprehensive pre-disposal treatments, especially primary, secondary, and tertiary stages, is imperative to address the prevalent heavy metal and microbiological issues, potentially rehabilitating up to 41% of affected areas. Additionally, creating proactive policies and allocating resources for sustainable groundwater management are crucial steps for ensuring broader water resource security and public health in the face of deteriorating water quality. Therefore, urgent regional action is needed to address escalating anthropogenic threats to groundwater, emphasizing the crucial need for proactive measures to safeguard public health and ensure sustainable water resources.

This research investigates the use of phase change materials (PCMs) in thermal energy storage (TES) unit-based cooling systems to increase the efficiency of air conditioners (ACs) by reducing the air inlet temperature. This study aims to evaluate different configurations of PCM enclosures, and different PCMs (paraffin and salt hydrate), by changing the speed of inlet air to achieve heat reduction of inlet air. The study includes experimental and simulation investigations. Every configuration simulates the hot-season atmospheric conditions of the UAE. A duct containing enclosures of paraffin RT-31 and salt hydrate (calcium chloride hexahydrate) was used for the simulation study using ANSYS/Fluent. A conjugate heat transfer model employing an enthalpy-based formulation is developed to predict the optimized PCM number of series and optimum airflow rate. Four designs of the AC duct were modelled and evaluated that contained one to four series of PCM containers subjected to different levels of supplied air velocities ranging from 1 m/s–4 m/s. The simulation study revealed that employing four series (Design 4) of PCM enclosures at a low air velocity of 1 m/s enhanced the pre-cooling performance and reduced the outlet air temperature to 33 °C, yielding a temperature drop up to 13 °C. The performance of salt hydrate (calcium chloride hexahydrate) was observed to be better than paraffin (RT-31) in terms of the cooling effect. Characterization of paraffin wax (RT-31) and salt hydrate was performed to establish the thermophysical properties. The experimental setup based on a duct with integrated PCM enclosures was studied. The experiment was repeated for three days as the repeatability test incorporating RT-31 as the PCM and a 3 °C maximum temperature drop was observed. The drop in the outlet air temperature of the duct system quantifies the cooling effect. Net heat reduction was around 16%.

In the present work, a concise library of benzothiazole-derived pyrazoline-based thiazole (1–17) was designed and synthesized by employing a multistep reaction strategy. The newly synthesized compounds were screened for their α-glucosidase and urease inhibitory activities. The scaffolds (1–17) were characterized using a combination of several spectroscopic techniques, including FT-IR, 1H-NMR, 13C-NMR, and EI-MS. The majority of the synthesized compounds demonstrated a notable potency against α-glucosidase and urease enzymes. These analogues disclosed varying degrees of α-glucosidase and urease inhibitory activities, with their IC50 values ranging from 2.50 to 17.50 μM (α-glucosidase) and 14.30 to 41.50 (urease). Compounds 6, 7, 14, and 12, with IC50 values of 2.50, 3.20, 3.40, and 3.50 μM as compared to standard acarbose (IC50 = 5.30 µM), while the same compounds showed 14.30, 19.20, 21.80, and 22.30 comparable with thiourea (IC50 = 31.40 μM), respectively, showed excellent inhibitory activity. The structure−activity relationship revealed that the size and electron-donating or electron-withdrawing effects of substituents influenced the enzymatic activities such as α-glucosidase and urease. Compound 6 was a dual potent inhibitor against α-glucosidase and urease due to the presence of -CF3 electron-withdrawing functionality on the phenyl ring. To the best of our knowledge, these synthetic compounds were found to be the most potent dual inhibitors of α-glucosidase and urease with minimum IC50 values. Moreover, in silico studies on most active compounds, i.e., 6, 7, 14, and 12, were also performed to understand the binding interaction of most active compounds with active sites of α-glucosidase and urease enzymes.

Substitution of vapor compression refrigeration systems (VCRS) by using Thermoelectric Peltier offers numerous advantages. The Peltier effect is the inverse of the Seebeck effect: as a current flows between two dissimilar materials, it causes one side to grow hotter, making the other side cooler. This effect was experimentally exploited to simultaneously cool and heat water. In 60 min, 1 L of water was cooled from 40 °C to 16 °C and another liter heated from 25 °C to 45 °C. Power consumption was about 0.0828 kWh with a COP of 1.33, which can be enhanced using improved methods of heat dissipation on the Peltier device.