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Abstract With the growing interest in utilizing Mg and austenitic stainless steel (ASS) in the automotive sector, joining them together in three-sheet configuration is inevitable. However, achieving this task presents considerable challenges due to the large differences in their physical, metallurgical and mechanical properties. To overcome these challenges, the feasibility of using weld-bonding to join Mg alloy/ASS/ASS was investigated. The nugget formation, interface characteristics, microstructure and mechanical properties of the joints were investigated. The results show that the connection between the Mg alloy and upper ASS was achieved through the combined effect of the cured adhesive and weld-brazing in the weld zone. On the other hand, a metallurgical bond was formed at the ASS/ASS interface. The Mg nugget microstructure exhibited fine columar grains composed predominantly of primary α-Mg grains along with a eutectic mixture of α-Mg and β-Mg17Al12. The nugget formed at the ASS/ASS interface consisted largely of columnar grains of austenite, with some equiaxed dendritic grains formed at the centerline of the joint. The weld-bonded joints exhibited an average peak load and energy absorption of about 8.5 kN and 17 J, respectively (the conventional RSW joints failed with minimal or no load application). The failure mode of the joints changed with increasing welding current from interfacial failure via the Mg nugget/upper ASS interface to partial interfacial failure (part of the Mg nugget was pulled out of the Mg sheet). Both failure modes were accompanied by cohesive failure in the adhesive zone.

Background: Somatic cell nuclear transfer (SCNT) is a prominent technology that can preserve superior genetic traits of animals and expand the population in a short time. Hematological characters and endocrine profiles are important elements that demonstrate the stability of the physiological state of cloned animals. To date, several studies regarding cloned camels with superior genes have been conducted. However, detailed hemato-physiological assessments to prove that cloned camels are physiologically normal are limited. In this study, We evaluated the hemato-physiological characteristics of cloned male and female dromedary camels (Camelus dromedaries). Methods: Therefore, we analyzed variations in hematological characteristics and endocrine profiles between cloned and non-cloned age-matched male and female dromedary camels (Camelus dromedaries). Two groups each of male and female cloned and non-cloned camels were monitored to investigate the differences in hemato-physiological characteristics. Results: All the animals were evaluated by performing complete blood count (CBC), serum chemistry, and endocrinological tests. We found no significant difference between the cloned and non-cloned camels. Furthermore, the blood chemistry and endocrine profiles in male and female camels before maturity were similar. Conclusions: These results suggest that cloned and non-cloned camels have similar hematological characteristics and endocrine parameters.

Background and aimsReduced bone mineral density (BMD) and microarchitectural deterioration contribute to increased fracture risk. Although the effects of anti-fracture medications (AFMs) on BMD are well-documented, their impact on bone material properties (BMPs) remains poorly characterized. Accordingly, we conducted a systematic review and meta-analysis to evaluate the effects of AFMs on BMPs. Based on data availability, we further categorized AFMs into anti-resorptives, bisphosphonates alone, and strontium ranelate subgroups to perform additional analyses of BMPs in osteoporotic patients.MethodsWe did a comprehensive search of three databases, namely, PubMed, Web of Science, and Google Scholar, using various permutation combinations, and used Comprehensive Meta-Analysis software to analyze the extracted data.ResultsThe 15 eligible studies (randomized and non-randomized) compared the following: (1) 301 AFM-treated patients with 225 on placebo; (2) 191 patients treated with anti-resorptives with 131 on placebo; (3) 86 bisphosphonate-treated patients with 66 on placebo; and (4) 84 strontium ranelate-treated patients with 70 on placebo. Pooled analysis showed that AFMs significantly decreased cortical bone crystallinity [standardized difference in means (SDM) −1.394] and collagen maturity [SDM −0.855], and collagen maturity in cancellous bone [SDM −0.631]. Additionally, anti-resorptives (bisphosphonates and denosumab) significantly increased crystallinity [SDM 0.387], mineral–matrix ratio [SDM 0.771], microhardness [SDM 0.858], and contact hardness [SDM 0.952] of cortical bone. Anti-resorptives increased mineral–matrix ratio [SDM 0.543] and microhardness [SDM 0.864] and decreased collagen maturity [SDM −0.539] in cancellous bone. Restricted analysis of only bisphosphonate-treated studies showed a significant decrease in collagen maturity [SDM −0.650] in cancellous bone and an increase in true hardness [SDM 1.277] in cortical bone. In strontium ranelate-treated patients, there was no difference in BMPs compared to placebo.ConclusionCollectively, our study suggests that AFMs improve bone quality, which explains their anti-fracture ability that is not fully accounted for by increased BMD in osteoporosis patients.

Thin-film coatings offer a scalable optical platform, as compared to nanopatterned films, for various applications including structural coloring, photovoltaics, and sensing. Recently, Fano resonant optical coatings (FROCs) have gained attention. FROCs consist of coupled thin film nanocavities composed of a broadband and a narrowband optical absorber. The optical properties of FROCs can be dynamically adjusted using chalcogenide phase change materials (PCM). Switching the structural states of PCM layers in the cavity between amorphous and crystalline states, the Fano resonance supported by FROC can be modulated in terms of resonance wavelength, intensity, and bandwidth. This review discusses the scientific and technological facets of both passive and active FROCs for applications in structural coloring and spectrum-splitting filters. We explore electrically tunable FROCs for dynamic color generation and optical steganography. Furthermore, we discuss the utilization of passive and active FROCs as spectrum-splitting filters to mitigate the drop in photovoltaic efficiency of solar cells due to heating and for hybrid thermal-electric power generation.

Diabetes mellitus type 3 refers to diabetes secondary to an existing disease or condition of the exocrine pancreas and is an uncommon cause of diabetes occurring due to pancreatogenic pathology. It accounts for 15–20% of diabetic patients in Indian and Southeast Asian continents. This is case report of a rare case of type 3 diabetes mellitus (T3DM) presenting with diabetic ketoacidosis (DKA). The patient was admitted for DKA along with complaint of hyperglycemia, blood glucose of 405 mg/dl with HbA1c level of 13.7%. Computed tomography evidence revealed chronic calcific pancreatitis with intraductal calculi and dilated pancreatic duct.

Because of their high stability, innocuous behaviour, outstanding electric properties and multi-functionality, lead-free double perovskites have emerged as a promising alternative to lead-based perovskites. We present here the structural, microstructural, dielectric and electrical properties of a newly synthesized double perovskite Nd2FeTiO6 (NFTO). The Rietveld refinement of its X-ray diffraction pattern revealed a monoclinic structure with space group P121/c1. The oxide exhibits a temperature-independent dielectric constant and di-electric loss at low temperatures (below 200 °C) making the compound a suitable candidate for fabricating thermally stable capacitors. The AC conductivity was investigated using the Jonscher’s universal power law, and it was inferred that the conduction process is caused by the Correlated BarrierHopping (CBH) mechanism. Furthermore, frequency dependent AC conductivity also revealed the NTCR nature of the NFTO compound.

Abstract Small non-coding RNAs (sncRNAs), being the top regulators of gene expression, have been thoroughly studied in various biological systems, including the testis. Research over the last decade has generated significant evidence in support of the crucial roles of sncRNAs in male reproduction, particularly in the maintenance of primordial germ cells, meiosis, spermiogenesis, sperm fertility, and early post-fertilization development. The most commonly studied small RNAs in spermatogenesis are microRNAs (miRNAs), PIWI-interacting RNA (piRNA), small interfering RNA (siRNA), and transfer RNA-derived small RNAs (ts-RNAs). Small non-coding RNAs are crucial in regulating the dynamic, spatial, and temporal gene expression profiles in developing germ cells. A number of small RNAs, particularly miRNAs and tsRNAs, are loaded on spermatozoa during their epididymal maturation. With regard to their roles in fertility, miRNAs have been studied most often, followed by piRNAs and tsRNAs. Dysregulation of more than 100 miRNAs has been shown to correlate with infertility. piRNA and tsRNA dysregulations in infertility have been studied in only 3–5 studies. Sperm-borne small RNAs hold great potential to act as biomarkers of sperm quality and fertility. In this article, we review the role of small RNAs in spermatogenesis, their association with infertility, and their potential as biomarkers of sperm quality and fertility.

Priya Porwal,1 Nimisha Shah,1 Ajay Singh Rao,1 Ihit Jain,2 Alexander Maniangat Luke,3,4 Krishna Prasad Shetty,3,4 Rodolfo Reda,5 Luca Testarelli,5 Ajinkya M Pawar6 1Department of Conservative Dentistry and Endodontics, K M Shah Dental College and Hospital, Sumandeep Vidyapeeth, Vadodara, Gujarat, India; 2Department of Dental Sciences, GBH American Hospital, Udaipur, Rajasthan, India; 3Department of Clinical Sciences, College of Dentistry, Ajman University, Ajman, United Arab Emirates; 4Centre of Medical and Bio-Allied Health Sciences Research (CMBAHSR), Ajman University, Ajman, United Arab Emirates; 5Section of Endodontics, Department of Oral and Maxillo-Facial Sciences, Sapienza University of Rome, Rome, Italy; 6Department of Conservative Dentistry and Endodontics, Nair Hospital Dental College, Mumbai, Maharashtra, IndiaCorrespondence: Luca Testarelli, Section of Endodontics, Department of Oral and Maxillo-Facial Sciences, Sapienza University of Rome, Rome, Italy, Email luca.testarelli@uniroma1.it Alexander Maniangat Luke, Department of Clinical Sciences, College of Dentistry, Ajman University, Ajman, United Arab Emirates, Email a.luke@ajman.ac.aePurpose: Evaluate the efficacy of transdermal patches containing ketoprofen and diclofenac sodium compared to oral diclofenac tablets in reducing post-endodontic pain after single-visit root canal therapy for teeth with symptomatic irreversible pulpitis.Methods: A total of 78 eligible participants with symptomatic irreversible pulpitis and preoperative VAS scores of 4 or above were enrolled after obtaining ethical approval (SVIEC/ON/DENT/SRP/22064) and CTRI registration (CTRI/2022/07/044231). Exclusion criteria included pregnancy, lactation, fractured/cracked teeth, developmental anomalies, tooth pathology, or ongoing analgesic/NSAID use. After root canal treatment, participants were randomized into three groups using computer randomization. Groups A and B received transdermal patches with Ketoprofen and diclofenac sodium, respectively, applied to the right forearm for 24 hours, with an additional patch on the left forearm for the next day. Group C received four diclofenac sodium oral tablets, twice daily for two days. VAS scales were used to assess pain at 4, 8, 24, and 48 hours post-treatment. The VAS scores collected were tabulated and statistically analyzed using SPSS version 21 with (P < 0.05). Shapiro Wilk test and the Related Samples Friedman’s Two-Way Analysis of Variance by Ranks were used for statistical evaluation.Results: Statistically significant reductions in mean postoperative pain scores were observed across all groups at all time points compared to preoperative scores. Notably, the Ketoprofen patch group exhibited superior performance compared to the diclofenac transdermal patch and oral diclofenac tablet groups at 48 hours, with statistical significance (p=0.047).Conclusion: The present evidence substantiates the efficacy of transdermal patches containing diclofenac and ketoprofen in managing postoperative pain arising from symptomatic irreversible pulpitis in single-rooted teeth. By avoiding the use of oral NSAIDs, these patches provide effective pain relief while minimizing the risk of adverse effects, presenting a favorable option for patients.Keywords: diclofenac transdermal patch, ketoprofen transdermal patch, oral analgesics, topical NSAIDs

Ecotourism is a form of tourism involving responsible travel to natural areas, conserving the environment, and improving the well-being of the local people. Its purpose may be to educate the traveler, to provide funds for ecological censervation, to directly benifit the economic development, and political empowerment of local communities. Ecotourism has come up as an important conservation strategy in the tropical areas where diversity of species and habitats are threatened because of the traditional forms of development. This study deals with a non-linear mathematical model with a novel idea for sustainable development of biomass with ecotourism which is imperative in the present scenario. Stability and bifurcation analysis of the model is done and it is observed from our study that the system predicts unstability and exhibits bifurcation if ecotourism goes beyond a threshold value.

Background: Employee mental health has a significant impact on productivity at work. People who work in healthcare environments are known to be at an increased risk of developing mental health issues. Objective: To assess the psychological distress in housekeeping and sanitation workers of IHBAS hospital Methodology: A cross-sectional study was conducted on the housekeeping and sanitation workers of the IHBAS hospital, a tertiary care Neuropsychiatry hospital and Institute. The socio-demographic data of the workers was collected. Kessler Psychological Distress scale (K10) and the Depression Anxiety Stress Scale -21 (DASS-21) were used to assess psychological distress, depression, anxiety, and stress among workers. The data was entered and analysed in SPSS 21. Results: A total of 598 workers were screened, of which 50.7% were males and 49.3% were females .63.5% of the workers were in the age group of 31 to 50 years,24.4% were between 18-30 years of age and 12% were more than 50 years of age. The output of K10 scale for psychological distress showed that only 0.2% were likely to have a mild disorder. The analysis of DASS-21 yielded on depression subscale that 0.5% had mild depression, and 0.2% each had moderate and extremely severe depression. On the anxiety subscale, 0.5% had moderate anxiety, 0.2% each had mild and extremely severe anxiety and stress subscale yielded that 0.5% had mild stress, and 0.2% had moderate stress Conclusion: Even though the percentage of workers with mental health problems was very low based on screening with K10 and DASSS-21, it is still worthwhile to screen for and appropriately address mental health issues among hospital employees as part of the occupational health program

In this research, we have introduced compartments for asymptomatic and symptomatic individuals, along with reduced susceptibility, as key factors defining our investigation. The study is carried out in diverse scenarios, considering them as crucial for the essential generation number of the model, set at 3.18(r0>1{r}_{0}\gt 1). The persistent reproduction differential method was used to explore the impact of continuous adrenocorticotropic hormone (ACTH) administration on the global gene expression in primary cultures of both fetal and adult adrenal cells. The study also investigates ACTH’s genetic effects on both adult and fetal human adrenal cells. The conclusion of this study is demonstrated through relevant and correct medical applications.

The Covid-19 epidemic has caused substantial obstacles to the supply network globally. Hence there is urgency and necessity to build a model for cash flow in the chain of demand and supply system. This research suggests an inventory model to assist retailers in determining the optimal ordering quantity and replenishment cycle to reduce the total cost in different payment cases. The current study looks toward a partial advance and delays in the payment system considering time-sensitive demand, shortage, and partial backlogging for instantaneous deteriorating items. During the financial crisis, the partial advance and delay-in-payment strategy is planned to keep orders flowing from retailers to suppliers and customers to retailers. The impact of advanced and delayed payments on the total cost of a retailer is examined. To exemplify the model’s application, numerical examples are used. A sensitivity study of critical parameters has been done to identify more sensitive parameters which reveal the clear depiction of present problems.

Background/Aim: Dementia has become a public health problem due to its association with biological risk factors; obesity, diabetes, hypertension and hypercholesterolaemia. Most of these risk factors, appear to be associated with dementia as well as with risk of coronary artery diseases (CADs) and stroke. This study aimed to find out the association of biological risk factors with cognitive impairment and dementia. Methods: Cross-sectional survey in a hospital was performed. After written informed consent and approval from hospital ethic committee, all subjects (n = 2002) above 25 years of age (1016 males and 986 females) were randomly selected and recruited from urban population of Moradabad, North India. Clinical data and risk factors were recorded with the help of case record form and validated questionnaires. Assessment of cognitive decline and dementia was made by Singh's memory function rating scale and biological risk factors by physical examination, sphygmomanometer and electrocardiography. The association of biological risk factors with dementia was calculated by multivariate logistic regression analysis after adjustment of age and sex. Results: Obesity, diabetes, hypertension, CAD and hypercholesterolemia were highly prevalent independent risk factors among patients with dementia. Multivariate logistic regression analysis showed that regardless of age and body mass index, diabetes mellitus and CAD were highly significant (p < 0.001) risk factors of dementia. Hypertension and family history of dementia were weakly but significantly(p < 0.05) associated with dementia. Conclusion: It is possible that increased frequency of obesity, diabetes, hypertension and CAD may increase the risk of dementia in an ageing population. Prevention and control of these biological risk factors may cause decline in the risk of dementia.

High-quality Indo-Mediterranean foods are characterised with unrefined, unprocessed foods, whole grains such as dry millets and beans and porridge. Vegetables such as leaves and gourds, nuts and fruits such as apples, grapes, papaya, guava, etc are major components of this diet. It seems that healthy vegetable oils such as olive, mustard, rape seed oil and protein sources that are beneficial; beans, pulses, cottage cheese are crucial in this diet. Among animal sources, white meats; such as sea foods should also be part of this diet. Vegetables and spices with medicinal properties; gourds, turmeric, fenugreek, coriander and cumin may also be called high quality nutraceutical foods, respectively. There is a need to find out traditional foods from all other countries which may be protective and healthy. There is evidence that calories have tremendous role in weight gain and weight loss. It seems that emphasis on food quality is crucial for prevention of oxidative stress and inflammation in the adipocytes, which predispose obesity and risk of cardiovascular diseases (CVDs) and diabetes. There are gaps in knowledge about the qualities of traditional foods, which prompt authors to present this communication.

Abstract Background COVID-19 infection has been linked with erectile dysfunction, which has also raised apprehensions about the impact of COVID-19 vaccination on male sexual functions. The purpose of this study was to investigate the impact of COVID-19 vaccination on male sexual functions, such as erectile function, orgasmic function, sexual desire, intercourse satisfaction, and overall satisfaction. Methods We used International Index of Erectile Function (IIEF) questionnaire for data collection. Mixed methods were adopted for this study, which consisted of Google online form distribution and the distribution of hard copies of the form to those who were not internet friendly. All data were entered in a spreadsheet and scores were assigned to each response according to the standard scores given in the IIEF questionnaire. Fifteen questions, one corresponding to each question in the IIEF questionnaire, were included to assess the impact of COVID-19 vaccination on each sexual function. Results In the first part of analysis, we calculated sexual function scores and men reporting low sexual function scores (~ 15%) were excluded, providing us with 465 individuals for further analysis. Regarding the impact of COVID-19 vaccination on male sexual functions, 71% individuals reported no impact, 3% reported a decline, 2.7% reported an improvement, and 23.3% could not assess the impact. We also performed analysis on the basis of age-groups of the participants and the duration after vaccination, finding that there was no impact irrespective of the age of subjects or the length of period after vaccination. Conclusions COVID-19 vaccination does not affect male sexual functions, including erectile function, orgasmic function, sexual desire, intercourse satisfaction, and overall sexual satisfaction.

The purpose of this work is to predict the mechanical properties of single- to few-layered borophene (η-LB)/epoxy composites using molecular dynamics modelling. An epoxy matrix was used to hold borophene in layers, and a borophene sheet was homogeneously incorporated into the epoxy matrix to generate borophene/epoxy nanocomposites. In this work, the mechanical properties of borophene/epoxy nanocomposites have been analysed in further detail. In addition to the mechanical properties of the nanocomposites, the impacts of borophene on the density distribution of epoxy polymers in the nanocomposites led to the observation that the local density is relatively high near the borophene–β12 interface and gradually declines to the bulk value as one advances away from the interface. The mechanical properties of the borophene-layered nanocomposites were superior to those of their substitutes, with the former having a higher Young’s modulus and a lower thermal expansion coefficient. This is due to the fact that borophene layer loading may result in a significant quantity of high-density polymer being present in the nanocomposites, which enhances the overall properties of the nanocomposites. In addition, the interaction between the three to four layers of loaded borophene layer provides the greatest reinforcement among the two nanocomposites systems. Finite element analysis analyses on the preferred results of the β12 LB were in excellent agreement with those of the experimental simulation data, demonstrating that this computational technique may be used to reliably predict the characteristics of borophene/epoxy composites in the future.

The photovoltaic sector needs a high-throughput slicing method that produces minimal waste to meet rising demand. Wire electric discharge machining (WEDM) has emerged as an alternative slicing method in recent research efforts. Polycrystalline silicon is sliced using the WEDM process with a zinc-coated electrode of Ø0.25 mm in diameter. Experiments were planned and conducted according to Box Behnken’s design of experiments. As inputs, seven different process parameters were used: pulse on time (PONT), pulse off time (POFFT), peak current (PC), spark gap voltage (SGV), wire feed (WF), wire tension (WT), and water pressure (WP). Response parameters measured were cutting speed (CS), surface roughness (SR), and kerf width (KW). Various process parameters have also been analyzed with ANOVA methods for predictive modeling. Based on experimental data, this study determines the appropriate optimal solutions via desirability functions. During the WEDM process, the PONT, POFFT, PC, and SGV significantly influence the discharge energy on the sliced surface. As a result of this study, CS of 0.78 mm2/min, SR of 2.87 μm, and KW of 0.70 mm were observed at the optimal settings of PONT of 119 μs, POFFT of 42 μs, PC of 38A, SGV of 36V, WF of 3 mm/min, WT of 2 kg and WP of 6 kg/cm2. Surface morphology was determined using scanning electron microscope and Energy dispersive X-ray to investigate the surface characteristics.

The aluminum (Al) alloy AA7075 is widely used in various industries due to its high strength-to-weight ratio, which is comparable and replaceable to steel in many applications. However, it has poor resistance to wear and corrosion compared to other Al alloys. The conventional pressure die coating with Cr and cadmium has led to premature failure while the load is applied. It is indeed to develop a novel coating method to improve the mechanical, wear, and corrosion properties of AA7075 Al alloy. In the present investigation, the binary and ternary metals such as zinc–nickel (Zn–Ni), zinc–cobalt (Zn–Co), and nickel–chromium–cobalt (Ni–Cr–Co) are electroplated on the substrate material (AA7075). In order to ensure optimal coating adhesion, the surface of the substrate material was pre-treated with laser surface treatment (LST). The mechanical and corrosion studies have been carried out on the uncoated and coated materials. It is observed from the findings that the ternary coating has higher wear resistance than the binary-coated material. The ternary coating has 64% higher resistance in the non-heat-treated status and 67% higher resistance in the heat-treated condition compared to the uncoated specimens. The tensile strength (MPa) of Ni–Cr–Co on AA7075 pressure die casting (PDC) is higher than the other deposits (582.24 of Ni–Cr–Co > 566.07 of Zn–Co > 560.05 of Zn–Ni > 553.64 of uncoated condition). The presence of a crystalline structure with the high alignment of Co and Ni atoms could significantly improve the corrosion resistance of Ni–Cr–Co coatings on AA 7075 PDC substrates when compared to binary coatings. The scanning electron microscopy (SEM) images, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy findings on the coated materials have been corroborated with the analyses on mechanical and corrosion properties. The XRD analysis of the Zn–Ni binary coating has reported that the diffraction peaks of γ-NiZn3 (831), γ -Ni2Zn11 (330), and 631 with 2θ values 38, 43, and 73° are confirming the presence of Zn–Ni binary deposit on AA7075 PDC substrate. The XRD pattern of Zn–Co-coated material has revealed that the presence of three strong peaks such as Zn (110), Co (111), and CoZn (211) and two feeble peaks such as ε-CoZn3 (220) and ε-CoZn3 (301) are clearly visible. The XRD pattern of Ni–Cr–Co ternary coating has exhibited that the Ni–Cr–Co ternary deposit is a solid solution with a body-centered cubic structure due to the formation peaks at lattice plane such as (110), (220), and (210) with a crystal lattice constant of 2.88 A°. The SEM image for both the binary- and ternary-coated materials has exhibited that the deposited surface has displayed many shallow pits due to hitting by progressive particles. The SEM image has illustrated the presence of Zn–Ni atoms with smaller globular structure. The surface morphology of binary Zn–Co coating on the PDC AA7075 substrate has unveiled the evenly distributed dot-like structure and submerged Co particles in the galaxy of Zn atoms. To understand the effectiveness of bonding by laser texturing, cross-section SEM has been carried out which furthermore revealed the effective adhesion of Ni–Cr–Co on AA7075 PDC; this could also be the reason for the enhancement of microhardness, wear, and corrosion resistance of the said coating.

In order to increase the economic feasibility, sustainability, and efficiency of energy production, this research proposes an improved optimization framework for hybrid wind-solar energy systems that use an augmented Genetic Algorithm (GA). Wind turbine size and photovoltaic (PV) panel orientation were optimized using historical data on wind and solar resources, system load profiles, and component specifications. There was an 18% increase in energy production, a 14% improvement in wind turbine efficiency, and a 16% increase in solar panel output because to the GA's outstanding performance. An 18% reduction in the payback time and a 12% reduction in the Levelized Cost of Energy (LCOE) were achieved. Results from the evaluation of the project's social and environmental consequences showed that community acceptability increased by 9 percentage points and land-use efficiency by 12 percentage points. A sensitivity study verified that the system could withstand several economic and environmental scenarios. The results demonstrate the promise of GA-based optimization in improving the efficiency of renewable energy hybrid systems.

This study compares satellite-based observations of PM2.5 and Total Carbon (TC) concentrations derived from NASA’s MERRA-2 reanalysis dataset for the Ghaziabad region with ground-based observations at two sites (Site A and Site B) from June 2018 to May 2019. Results reveal consistent underestimation by MERRA-2, with daily mean biases of -85.34 (Site A) and -111.31 (Site B) for PM2.5, and -54.77 (Site A) to -59.08 (Site B) for TC, alongside monthly mean biases of -81.30 to -103.74 for PM2.5 and -54.77 to -59.08 for TC. The absolute error indicates a 49.01% to 53.85% underestimation for both PM2.5 and TC. Daily FAC2 values show around 39% agreement for PM2.5, reducing to 0.27 (Site A) and 0.3 (Site B) monthly, indicating reduced agreement over time. For TC, daily FAC2 is notably low at 0.04 (Site A) and 0.06 (Site B), with no monthly agreement within a factor of 2 of ground-level data. Strong correlations (R²=0.68-0.84 for PM2.5; R²=0.94-0.96 for TC) between biases and ground-level data are observed, indicating proportional relationships. However, discrepancies increase with higher PM2.5 mass concentration, highlighting MERRA-2’s limitations during elevated pollution periods. Significant monthly variations are observed in GLC-PM2.5 concentrations at Site A (F= 61.42, p= 1.68×10-11) and Site B (F=25.15, p=2.96×10-06), and For GLC-TC concentrations at Site A (F=103.85, p=4.10×10-16) and Site B (F=55.70, p=7.54×10-11). Both GLC and MERRA-2 PM2.5 and TC concentrations follow a consistent monthly pattern, with higher levels during post-monsoon and winter seasons and lower levels during monsoon and pre-monsoon periods. This study underscores MERRA-2’s limitations in estimating PM2.5 and TC concentrations compared to ground-based observations and emphasises the necessity for further refinement and validation of the MERRA-2 model to enhance accuracy across different spatial and temporal scales.

Nanocomposite membranes are being considered as potential options for sustainable water desalination. These membranes offer advantages such as enhanced water permeability, improved salt rejection efficiency, and increased resistance to fouling. This study explores the utilization of environmentally friendly materials in the production of nanocomposite membranes, with the aim of improving both sustainability and performance. The synthesis of key findings is achieved through a systematic literature review and data analysis. Nanocomposite membranes, which include green materials such as biopolymers and natural nanoparticles, exhibit improved water permeability. This is evidenced by water permeability values ranging from 90 to 110 L/m^2·h·bar. Moreover, membranes that utilize environmentally friendly materials have shown a remarkable enhancement in salt rejection efficiency, achieving rates as high as 96% to 100%. The resistance to fouling is also improved, as the membranes exhibit resistance values ranging from 6 to 10 kPa. The advancements can be credited to the favorable characteristics of green materials, such as their biocompatibility, biodegradability, and minimal impact on the environment. The results highlight the promise of green nanocomposite membranes in the field of sustainable water desalination, in line with the increasing focus on environmental accountability in technological advancements. Further research should prioritize the improvement of membrane compositions, fabrication methods, and performance metrics to enhance the sustainability and efficiency of nanocomposite membranes for water desalination applications. This will help address global water challenges in a responsible and environmentally friendly manner.

Heavy quarks (charm and beauty) are valuable probes for investigating the properties of the quark–gluon plasma (QGP) formed in ultra-relativistic heavy-ion collisions, as they are mainly produced through hard-scattering processes prior to the formation of the QGP, and their number is conserved during the subsequent QGP evolution. Measurements of the nuclear modification factor RAA of charm and beauty hadrons allow us to characterise the in-medium energy loss of heavy quarks while traversing the QGP. Information on their diffusion and degree of participation in the collective motion of the medium can be obtained by measuring the elliptic-flow coefficient v2 of heavy-flavour particles. Complementary insights into heavy-quark fragmentation and energy redistribution can be obtained by measuring angular correlations involving heavy-flavour particles. In this contribution, the recently published results on the non-prompt v2 coefficient of D0 mesons are presented, comparing them with those of other particle species in Pb–Pb collisions at √SNN = 5.02 TeV. Additionally, we report the recent findings on the RAA of prompt D mesons and Λc+ baryons in Pb–Pb collisions at the same energy. Furthermore, we discuss the new Pb–Pb results on angular correlations between heavy-flavour decay electrons and charged particles in the same collision system.

This review article delves into the advancements in the realm of nanogrids and their potential in addressing energy challenges, particularly in regions with limited access to centralized power grids. The paper reviews the work in the areas of nanogrids as solutions for regions like sub-Saharan Africa, where a significant population lacks access to main grid electricity. The integration of multiple nanogrids within a community, coupled with an investor energy bank, is explored as a means to alleviate the economic burden of energy storage and to harness the full potential of solar energy. The article also examines the challenges faced by centralized power grids and the shift towards distributed generation (DG) as a remedy. The concept of nanogrids is further elaborated, discussing their control topologies, techniques, and the potential of interconnecting multiple nanogrids to form a microgrid. Lastly, the co-design of solar generationbased nano-grids and water treatment in remote areas is studied, emphasizing the importance of providing essential drinking water and electricity to underdeveloped regions. The integration of solar-powered electricity with water treatment processes offers a unique solution to address both electricity and water needs in such areas.

This paper reviews innovative methodologies in the realm of renewable energy harvesting and storage from ambient sources. One focal area is the untapped potential of water wave energy, a globally distributed renewable energy source. Current technologies, primarily reliant on electromagnetic generators, face challenges, especially in irregular environments and at low frequencies. However, the advent of the triboelectric nanogenerator (TENG) offers a promising solution, especially for low-frequency water wave motions. TENG technology not only presents a new avenue for large-scale blue energy harvesting but also signifies a shift towards the era of the Internet of Things, where energy is derived from various sources including human motion and vibrations. Another domain delves into the history and evolution of energy harvesting, tracing back to traditional methods like water wheels and windmills. The modern era witnesses a resurgence in interest due to advancements in lowpower electronics, wireless standards, and miniaturization. Lastly, wearable biosensors, poised to redefine personalized healthcare and telemedicine, necessitate innovative power solutions. Wearable energy harvesters, capable of converting ambient energy sources into electricity, are emerging as pivotal components in self-powered wearable sensors, paving the way for real-time health monitoring and human-machine interfaces.

This paper offers a comprehensive review of the advancements in the realm of renewable energy, specifically focusing on solid oxide fuel cells and electrolysers for green hydrogen production. The review delves into the significance of wind energy as a pivotal renewable energy source and underscores the importance of precise forecasting for efficient energy management and distribution. The integration of machine learning-based approaches, such as Support Vector Regression and Random Forest Regression, has shown promising results in enhancing the accuracy of wind energy production forecasts. Furthermore, the paper explores the broader landscape of renewable energy generation forecasting, emphasizing the rising prominence of machine learning and deep learning techniques. As the penetration of renewable energy sources into the electricity grid intensifies, the need for accurate forecasting becomes paramount. Traditional methods, while valuable, have encountered limitations, paving the way for advanced algorithms capable of deciphering intricate data relationships. The review also touches upon the inherent challenges and prospective research avenues in the domain, including addressing uncertainties in renewable energy generation, ensuring data availability, and enhancing model interpretability. The overarching goal remains the seamless integration of renewable sources into the grid, propelling us towards a greener future.

This paper reviews the work in the areas of machine learning applications for energy management in smart buildings, 5G technology’s role in smart energy management, and the use of machine learning algorithms in microgrid energy management systems. The first area focuses on the adaptability of building-integrated energy systems to unpredictable changes through AI-initiated learning processes and digital twins. The second area explores the impact of 5G technology on smart buildings, particularly in Singapore, emphasizing its role in facilitating high-class services and efficient functionalities. The third area delves into the application of various machine learning algorithms, such as supervised and unsupervised learning, in managing and monitoring microgrids. These broad areas collectively offer a comprehensive understanding of how machine learning can revolutionize energy management systems in smart buildings, making them more efficient, adaptable, and sustainable.

The integration of renewable energy and the optimization of energy use are crucial components of sustainable energy transitions aimed at mitigating climate change. Modern technology, notably the Internet of Things (IoT), offers a myriad of applications within the energy sector, spanning energy supply, transmission and distribution, and demand. IoT holds the potential to enhance energy efficiency, boost the share of renewable energy sources, and reduce the environmental impact of energy consumption. This review article synthesizes existing literature on IoT applications in Hydelenergy systems, with a particular focus on smart grids. Furthermore, it delves into the enabling technologies of IoT, including cloud computing and data analysis platforms. Challenges in deploying IoT in the energy sector, such as privacy and security concerns, are also addressed, with proposed solutions like blockchain technology. This review serves as a comprehensive resource for energy policymakers, economists, and managers, providing insights into IoT’s role in optimizing policymakers, economists, and managers, providing insights into IoT’s role in optimizing energy systems.

This study examines the relative effectiveness of Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Linear Programming (LP) in optimizing hybrid energy microgrids. Drawing upon empirical data derived from the study, the research explores many facets, including economic efficacy, environmental viability, and microgrid robustness. The use of GA showcases a significant 10% decrease in overall system expenses, highlighting its efficacy in augmenting economic feasibility. PSO diligently tracks, attaining an 8% decrease, while SA and LP make significant contributions but provide somewhat lesser cost reductions at 7% and 6%, correspondingly. Within the domain of renewable energy integration, GA and PSO have emerged as frontrunners, with remarkable advancements of 12% and 10%, respectively. SA and LP provide commendable contributions, demonstrating their effectiveness in optimizing the usage of renewable energy sources inside the microgrid, as seen by their respective increases of 8% and 7%. The environmental factor, as quantified by the decrease of carbon emissions, highlights the commendable efficacy of GA and PSO, resulting in significant reductions of 15% and 12% respectively. SA and LP provide praiseworthy environmental efforts, achieving reductions of 10% and 8% respectively. The resilience index highlights the strength of GA and PSO in assessing the resilience of the microgrid, with GA showing an increase of 0.05 and PSO showing an increase of 0.04. SA and LP make a significant contribution, with increments of 0.03 and 0.02, underscoring the potential of evolutionary and swarm-based methodologies to bolster the microgrid’s resilience against disturbances. Scenario analysis effectively brings unpredictability into the operational environment of the microgrid, continually showcasing the remarkable flexibility of GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) over a wide range of situations. SA and LP demonstrate consistent efficacy but with somewhat reduced flexibility. Statistical evaluations provide compelling evidence confirming the exceptional efficacy of GA and PSO in improving microgrid metrics. Ultimately, this research provides valuable perspectives on the intricate trade-offs between various optimization techniques, empowering decision-makers to choose strategies that align with specific microgrid objectives. Moreover, it contributes to the wider discussion on resilient, sustainable, and economically feasible energy infrastructures.

This research examines the way to a carbon-neutral future by looking at the integration of renewable vitality sources and vitality capacity advances in feasible energy arrangements. Through a multidisciplinary approach, enveloping information collection, numerical modelling, and scenario investigations, the study investigates the flow of transitioning vitality frameworks. The optimization of energy capacity capacities is educated by scientific models, uncovering that as renewable infiltration increments (20%, 40%, and 60%), optimal capacity capacities rise correspondingly (300 MWh, 700 MWh, and 1200 MWh). Situation investigations illustrate that higher renewable entrance and appropriately measured energy capacity capacities lead to significant diminishments in CO2 outflows (25%, 45%, and 65%) while keeping up positive financial reasonability. Sensitivity investigations confirm the vigour of the models, showing the versatility to varieties in key parameters such as renewable asset accessibility, energy capacity productivity, and capital costs. A comparative investigation against related work underscores the competitiveness and uniqueness of the proposed approach, emphasizing the noteworthiness of numerical modelling in optimizing energy frameworks. This research contributes profitable insights for policymakers, industry partners, and analysts committed to exploring the complexities of accomplishing a carbon-neutral future. The discoveries displayed here, together with those from different studies crossing worldwide vitality exchange, green hydrogen production, and urban arranging, collectively contribute to the broader discourse on economic energy move.

This research explores the transformative part of nanomaterials in progressing urban maintainability through the integration of renewable vitality frameworks. Synthesized quantum dabs, carbon nanotubes, and graphene were characterized and connected over assorted applications, counting solar vitality saddling, wind vitality improvement, vitality capacity, and urban foundation improvement. In solar cells, the integration of quantum specks resulted in an eminent increment in control transformation proficiency (PCE), with an 85% change in short-circuit current thickness (J sc) and a 20% increment in open-circuit voltage (Voc). Wind turbine edges upgraded with carbon nanotubes displayed a momentous 21% rise in control yield and a 40% advancement in soundness, emphasizing the potential of nanomaterials in optimizing wind vitality frameworks. Graphene-based supercapacitors illustrated a multiplied particular capacitance and a 10% increment in cyclic solidness, underscoring the adequacy of nanomaterials in vitality capacity applications. The consolidation of nanocomposite building materials showcased a 44% diminishment in warm conductivity, contributing to made strides cover for maintainable urban foundations. Nanosensors, coordinated into smart frameworks, showed a prevalent 80% increment in affectability and a 50% lessening in reaction time compared to customary sensors.

This research explores the transformative potential of nanomaterial developments in tending to water and soil contamination through economical natural remediation procedures. Three unmistakable nanomaterials, Nanoparticle A, Nanocomposite B, and Nanotube C, were synthesized and efficiently assessed for their adequacy in poison expulsion. In adsorption tests, Nanocomposite B showed remarkable lead expulsion capacity, outperforming Nanoparticle A and Nanotube C with values of 30 mg/g. Catalytic debasement tests illustrated Nanocomposite B’s predominant proficiency in corrupting phenol, accomplishing a noteworthy 68%, outflanking Nanotube C and Nanoparticle A. A comprehensive natural compatibility appraisal uncovered decreased ecotoxicity and cytotoxicity files for Nanocomposite B, situating it as a naturally inviting choice for remediation. Comparative investigations with related works exhibit the importance of fitting nanomaterial properties focused on poison expulsion. The promising results emphasize Nanocomposite B’s potential as a maintainable and multifunctional arrangement for water and soil remediation. This investigation contributes profitable insights to the developing field of nanotechnology-enabled natural administration, emphasizing the requirement for the capable sending of nanomaterials to attain long-term environmental and human well-being benefits.

Sand casting method is used to produce many useful products for many applications. The aim of the study is to manufacture a product with excellent dimensional geometry is achieved in sand casting process at low cost. We would expect manuscripts to show how design and/or manufacturing problems have been solved using computer modeling, simulation and analysis. In this work, the important mechanical properties of hardness and surface roughness are investigated on Aluminum 6063 cast material with and without incorporating the copper tubes as a vent hole in sand casting process. Since copper has high thermal conductivity when compared to other metals, the heat transfer rate will be varying from existing system. The copper tubes have made different diameters of holes on outer surfaces with selective distance of intervals. The specific number of copper tubes with various diameters are designed by CATIA modeling software and analyzed with Taguchi Design of Experiment. Taguchi L9 orthogonal array is used proficiently in the optimal value of hardness and surface roughness. The results are revealed that the maximum hardness value of 104 BHN is attained for 10mm distance of holes made on copper tube with an angle of 90o degree. The minimum surface roughness of 2.11 micron is achieved for 20mm distance of holes made on copper tube with 45o of angle as a vent hole in sand casting process.

Data from a variety of sample cities was evaluated as part of a research looking into the integration of big data analytics into urban planning. The goals were to evaluate the impact of data analytics infrastructure, data volume and processing time, urban development initiatives, and data analytics efficiency. The results showed significant differences in data analytics resources across cities, indicating different levels of investment and preparedness for data-driven decision making. It was clear that cities could handle large amounts of data efficiently thanks to their strong data processing skills. Data analytics have an impact on urban development initiatives, highlighting the revolutionary potential of data-driven urban planning. The outcomes of efficiency tests demonstrated how data analytics procedures are useful for improving urban services and for making well-informed judgments. This study offers important new insights into the mechanics of data-driven urban planning and how it can influence how cities develop in the future.

Stress is the body's response to any changes that might place it under mental, emotional, or physical strain and could either demand attention or prompt action. A stress reaction can be brought on by both internal and external factors. The conditions, demands, issues, and expectations you deal with every day are all regarded as external influences, as are your physical surroundings, your job, your contacts with others, your family, and all other related factors. The ability of your body to respond to and handle external stimuli depends on internal factors. Your ability to handle stress is influenced internally by your food habits, level of general health and fitness, mental health, and the amount of sleep and rest you get. Such demanding conditions could affect how certain stress hormone levels are regulated. Biomarkers such as mGlu2/3, 5-hydroxyindoleacetic acid (5-HIAA), serum alpha-amylase, amygdala reactivity, neuropeptide Y (NPY), heat shock proteins, cortisol, and catecholamines are used to assess the hormone imbalance. Disease prevention, early detection, and therapy are all possible uses for biomarkers. In this review, we looked at a wide range of stress-related biomarkers that might cause different psychiatric illnesses and how those conditions can, over time, alter a person's lifestyle.

Ramsar wetlands are one of the least investigated areas for microplastic contamination. Harike wetland is located downstream of the confluence of the Beas and Sutlej rivers. Rivers are nature's drainage systems, which collect waste from everywhere and move ahead. On the same note, the Harike wetland, the largest wetland in North India, is an ideal home for migratory birds and aquatic animals. The water in the canal and the fish living within it have been examined for microplastics. Results revealed that the number of microplastics did not significantly differ between sites 1 and 2, but showed a seasonal variation with higher levels observed in the winter season compared to summer and the rainy season. The most common types of plastics detected in the wetland and canal were HDPE and nylon, which were further analyzed using conformational tests, ATR-FTIR, and GC-MS techniques. Additionally, microplastics measuring less than 5mm in size were recovered from the gut of Cyprinus carpio fish, with a 7% recovery rate from the total number of fish analyzed. Although this percentage may seem low, it cannot be ignored given the potential impact on the aquatic environment. This percentage may be less, but it is not ignorable. Indeed, the amount of poorly managed plastic garbage generated by people living around or illegal outskirts garbage dumping near rivers and tributaries is a potential source of aquatic debris.

Wetlands are consequential habitats with diverse flora and fauna. The overutilization of these habitats led to the implementation of conservational strategies which includes Ramsar convention. Harike wetland is the largest wetland in northern India, declared as a Ramsar site. However, the recent industrialization and anthropogenic activities may result in the ecological degradation of this wetland. The wetland is eminently polluted due to industrial discharges, therefore the present study was undertaken to investigate heavy metal status of Harike wetland. The analysis included bio-essential (chromium, manganese, iron, cobalt, nickel, copper, zinc) and non-essential (arsenic, mercury, cadmium, lead) heavy metals. The concentration of heavy metals in the surface water was determined using inductively Coupled Plasma-Mass Spectrometry and the recovered values were compared to the global and national standards. Among all the heavy metals analysed the mean concentrations of iron (437.983 µg/l), mercury (4.011 µg/l) and lead (156.719 µg/l) were recorded to be alarming. The higher concentration of heavy metals may be directly related to the inlet from river Sutlej, as the water is contaminated by various industrial, domestic and agricultural sources. Therefore, continuous monitoring and adequate measures need to be implemented to improve the water quality of internationally recognized wetland.

Bardet–Biedl syndrome is an autosomal-recessive ciliopathic disorder affecting multiple organ systems. Characteristic features include progressive retinal dystrophy, obesity, polydactyly hypogonadism, mental retardation, and renal disorders. Other manifestations include congenital heart diseases, hepatic fibrosis, ataxia, and diabetes. Approximately 30% of patients with Biedl–Bardet syndrome (BBS) have hepatobiliary disorders such as periportal fibrosis, nonalcoholic fatty liver disease, and cystic dilation of the bile ducts. The association of BBS with choledochal cysts (CDC) is extremely rare. Here, we report a case of a 14-year-old boy with a novel variant of BBS and associated type IV CDC. The patient was managed surgically with CDC excision and Roux-en-Y hepaticojejunostomy.

Abstract Background In contrast with the preceding stages of the germ cells, spermatozoa are unusually rich in small non-coding RNAs in comparison to the coding RNAs. These small RNAs may have had an essential role in the process of spermatogenesis or may have critical roles in the post-fertilization development. Sporadic efforts have identified a few differentially expressed miRNAs in infertile individuals, which do not replicate in other studies. Methods In order to identify miRNAs signatures of infertility or poor sperm quality, we compared miRNA differential expression data across nine datasets, followed by their analysis by real-time PCR in a case–control study. This was followed by the validation of potential biomarkers in yet another set of cases and controls. For this, total RNA was isolated from 161 sperm samples. miRNA expression levels in infertile cases and fertile controls were measured using TaqMan real-time PCR. Meta-analyses of two miRNAs (hsa-miR-9-3p and hsa-miR-122-5p) were performed using Comprehensive Meta‐Analysis Software (version 2). All statistical analyses were performed with the help of GraphPad Prism Software (version 8). Results Literature search identified seven miRNAs (hsa-let-7a-5p, hsa-miR-9-3p, hsa-miR-22-5p, has-miR-30b-5p, hsa-miR-103-3p, hsa-miR-122-5p and hsa-miR-335-5p) showing consistent dysregulation in infertility across a minimum of four studies. In the discovery phase, six miRNAs showed strong association with infertility with four (hsa-miR-9-3p, hsa-miR-30b-5p, hsa-miR-103-3p and hsa-miR-122-5p) showing consistent differential regulation across all sub-groups. Receiver operating characteristic (ROC) curve analysis showed that the area under curve of > 0.75 was achieved by three (hsa-mir-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) miRNAs. In the validation phase, these three miRNAs showed consistent association with infertility (hsa-mir-9-3p, hsa-miR-30b-5p, and hsa-miR-122-5p). Meta-analysis on hsa-miR-122-5p showed its significant quantitative association with infertility [Hedge’s g = -2.428, p = 0.001 (Random effects)]. Conclusions Three miRNAs (hsa-miR-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) have strong linkage with infertility and a high potential as sperm quality biomarkers.

The broad conceptualization of fertility preservation and restoration has become already a major concern in the modern western world since a large number of individuals often face it in the everyday life. Driven by different health conditions and/or social reasons, a variety of patients currently rely on routinely and non-routinely applied assisted reproductive technologies, and mostly on the possibility to cryopreserve gametes and/or gonadal tissues for expanding their reproductive lifespan. This review embraces the data present in human-focused literature regarding the up-to-date methodologies and tools contemporarily applied in IVF laboratories' clinical setting of the oocyte, sperm, and embryo cryopreservation and explores the latest news and issues related to the optimization of methods used in ovarian and testicular tissue cryopreservation.

The present work aims to carry out a feasible study of wire electro-discharge machining (WEDM) during the machining of Inconel 690 superalloy gears. Processing conditions of power-on time, power-off time, current, and spark-gap voltage are varied to evaluate the process performance in terms of material removal rate (MRR), surface roughness (SR), and wire consumption. Parametric optimization has been carried out using combined approach of response surface methodology (RSM) and artificial neural network (ANN). Results revealed that ANN predicted values are 99% in agreement with the experimental results which validates its effectiveness as compared to RSM predicted values. A viability study of noise characteristics of the processed gear is also done using a noise testing setup. Additionally, FE-SEM has been used to analyze the machined surface’s topography. Greater discharge energy brought by a longer pulse length raises the values of MRR, SR, and recast layer thickness (RLT). This study explores the capability of WEDM to produce a more precise and smooth gear profile as compared to other conventional machining methods. Additionally, RLT and microhardness of the machined surface have been critically studied to comprehend the better understanding of the process mechanism.