Ideal Size Research Articles

Design, performance, and techno‐economic analysis of a rooftop grid‐tied PV system for a remotely located building

AbstractThe utilization of fossil fuel leads to excessive CO2 emissions that have negative impacts on the environment. The continued trend of this practice may result in an increase in the occurrence of storms, cyclones, starvation, and floods, as well as a rise in atmospheric temperature. Therefore, the focus should be on renewable energy sources, as they emit less CO2. This study presents the design and modeling of a 135‐kW solar PV grid‐connected power generation system for a university's remotely located building. The system is designed to function optimally in an area with an average solar radiation of 585.8 W/m2. The technical, financial, and annual performance of the system is demonstrated, which includes fixed‐mounted racking with 26° fixed‐tilt angle structures and monofacial PV panels. The design is validated and simulated using the PVsyst for designing a PV On‐Grid design and SketchUp for shadow analysis tools to determine the system's ideal size, technical requirements, and electrical power output. Moreover, two different inverters (Company A and Company B inverters) were used to compare and analyse the system's performance with the same PV panel. This project's results may impact the university's choice to install a solar PV system to minimize power consumption.

Additive Manufacturing of 17-4PH Alloy: Tailoring the Printing Orientation for Enhanced Aerospace Application Performance

Additive manufacturing (AM) is one of the fastest-growing markets of our time. During its journey in the past 30 years, its key to success has been that it can easily produce extremely complex shapes and is not limited by tooling problems when a change in geometry is desired. This flexibility leads to possible solutions for creating lightweight structural elements while keeping the mechanical properties at a stable reserve factor value. In the aerospace industry, several kinds of structural elements for fuselage and wing parts are made from different kinds of steel alloys, such as 17-4PH stainless steel, which are usually milled from a block material made using conventional processing (CP) methods. However, these approaches are limited when a relatively small element must withstand greater forces that can occur during flight. AM can bridge this problem with a new perspective, mainly using thin walls and complex shapes while maintaining the ideal sizes. The downside of the elements made using AM is that the quality of the final product is highly dependent on the build/printing orientation, an issue extensively studied and addressed by researchers in the field. During flight, some components may experience forces that predominantly act in a single direction. With this in mind, we created samples with the desired orientation to maximize material properties in a specific direction. The goal of this study was to demonstrate that an additively manufactured part, produced using laser powder bed fusion (LPBF), with a desired build orientation has exceptional properties compared to parts produced via conventional methods. To assess the impact of the build orientation on the LPBF parts’ properties, one-dimensional tensile and dynamic fracture toughness tests were deployed.

Size of sampling units aproppriate for management level forest inventory in Eastern Amazon, Brazil

This study aimed to indicate the ideal sample size for continuous forest inventories in the tropical forest in Amapá. Data were obtained from a monitoring inventory started in 2010 and completed in 2016, in five permanent sampling units of 100m x 100m with an inclusion level of DBH ≥ 10cm. Randomly allocated sample subunits with five different dimensions ranging from 400 m2 to 1600 m2 were simulated within these units. The measurement times of each sampling unit, from the first to the last three, were timed. Dimensions were analyzed for their accuracy and relative efficiency. Given the above and depending on the purpose of the inventory, the standard sampling unit of 1 ha (100 m x 100 m) is recommended for the inventory variables. The 20 m x 20 m (400 m2) square sampling unit was the most suitable for monitoring growth variables (annual increment in diameter, basal area, and volume), indicating that these sampling units for continuous inventories can become an essential alternative for use in monitoring inventory in the region.

Developing sustainable strategies by LID optimization in response to annual climate change impacts

Designing urban runoff drainage systems is prominent in effectively managing floods due to increasing impermeable regions worldwide. However, although urban runoff drainage systems are configured mainly based on rainfall analysis, climate change influences their hydrological properties substantially. This research introduces an innovative methodology to analyze climate variations on optimal low impact developments (LIDs) of urban drainage systems in historical periods based on annual impacts (AIs) in projection periods considering uncertainties assessments. First, Storm Water Management Model (SWMM) is employed for simulating the process of rainfall-runoff considering quality and quantity analyses. This simulation model is coupled with a non-dominated genetic algorithm- II (NSGA-II) optimization algorithm to minimize the cost of LIDs, flood volume, and pollutant load. Then, future runoff and daily rainfall are projected on a yearly basis, including maximum, minimum, and median rainfall, to identify how climate change affects catchment properties. These projections and an ensemble model are obtained based on the Long Ashton Research Station Weather Generator (LARS-WG), which considers uncertainties. After that, the projected daily precipitation is fragmented into hourly segments utilizing the change factor approach (CFA). Finally, the ideal optimum type, size, and placement of the chosen LIDs are determined using the presented simulation-optimization (SO) model. To prove the effectiveness and appropriateness of the presented framework, it is implemented in a real-world study area in Darabad catchment, Tehran, Iran. Results indicate that the developed optimal LIDs are well-designed and sufficient in both the historical and projection periods. The findings also depict that with the current LIDs established for the historical period, the flooding volume and summation of total suspended solid (TSS) and total Nitrogen (TN) removals are decreased by 55.96% and 60.2% compared to when LIDs are not adopted. In addition, employing the developed LIDs based on an ensemble model results in the runoff volume and pollutants removal decline of up to 31.39% and 46.9%, respectively.

P-669 The effect of ovarian follicle size on oocyte fate and embryology outcome

Abstract Study question Does ovarian follicle size influence ultimate oocyte fate and embryology outcome? Summary answer Per punctured follicle, higher oocyte yield, MII oocytes, 2PN fertilisation, and utilisable blastocyst is observed as follicle increases in size up to threshold of 15.5mm What is known already It is well known that oocyte maturity and probability of successful fertilisation is correlated to the size of follicles where oocyte originated from. However the true cutoff and ideal size at oocyte retrieval remains elusive. Furthermore, there is no conclusive evidence that embryological outcome in terms of blastocyst morphology and utilisation differs in the mid to large ovarian follicular sizes. Study design, size, duration Prospective observational study undertaken in a tertiary fertility referral centre over 10 months. 50 participants recruited and underwent conventional controlled ovarian stimulation as per unit protocol. A total of 288 follicular punctures performed in the study period. Participants/materials, setting, methods 50 oocyte retrieval (OR) procedures were performed. The size of ovarian follicles was individually measured using transvaginal ultrasound. 288 follicular punctures were performed and up to 3 oocytes per patient were collected for the study to be individually cultured to allow for tracking of oocyte and embryo outcomes. Follicular fluid and spent culture media were collected separately for subsequent metabolomics analysis. Follicular sizes were divided into 6 groups ( < =9.5, 10-12.5, 13-15.5, 16-19.5, 20-23.5, > =24). Main results and the role of chance Oocyte fate included 113 mature oocytes, 83 bipronuclear (2PN) oocytes, 7 cleavage stage embryos, and 39 good quality blastocysts suitable for utilisation in fresh or frozen transfer cycles. When compared to overall average per punctured follicle, there is an association of higher oocyte yield, proportion of MII oocytes, 2PN fertilisation, and utilisable blastocyst as follicle size increases. The threshold for a change in fate appears to be when follicle size increases beyond 15.5mm where optimal follicle size may reach plateau. Proportion of good-quality blastocysts appears to be associated with size of follicles at rates as follow- 0% (less than 10mm), 11.1% (10-12.5mm), 13.2% (13-15.5mm), 15.9% (16-19.5mm), 14.5% (20-23.5mm), and 20% (above 24mm). 23 embryos have been utilised to date, yielding a 50% positive pregnancy rate. Of these utilised embryos resulting in a positive pregnancy test, 81.8% of embryos originated from follicles above 15.5mm. Metabolomics analysis for follicular fluid and spent culture media is ongoing. Limitations, reasons for caution The observational nature of the study along with a small sample size are limitations that did not allow clinical significance to be observed. Wider implications of the findings Oocyte retrieved from follicles less than 10mm is futile. There appears to be a plateau in optimal follicle size where no real detriment is demonstrated. This is an important findings to guide stimulation, especially in cases of asynchronous growth where sacrifice in larger follicles is commonly assumed. Trial registration number Not applicable

Predicting post-operative vault and optimal implantable collamer lens size using machine learning based on various ophthalmic device combinations

BackgroundImplantable Collamer Lens (ICL) surgery has been proven to be a safe, effective, and predictable method for correcting myopia and myopic astigmatism. However, predicting the vault and ideal ICL size remains technically challenging. Despite the growing use of artificial intelligence (AI) in ophthalmology, no AI studies have provided available choices of different instruments and combinations for further vault and size predictions. This study aimed to fill this gap and predict post-operative vault and appropriate ICL size utilizing the comparison of numerous AI algorithms, stacking ensemble learning, and data from various ophthalmic devices and combinations.ResultsThis retrospective and cross-sectional study included 1941 eyes of 1941 patients from Zhongshan Ophthalmic Center. For both vault prediction and ICL size selection, the combination containing Pentacam, Sirius, and UBM demonstrated the best results in test sets [R2 = 0.499 (95% CI 0.470–0.528), mean absolute error = 130.655 (95% CI 128.949–132.111), accuracy = 0.895 (95% CI 0.883–0.907), AUC = 0.928 (95% CI 0.916–0.941)]. Sulcus-to-sulcus (STS), a parameter from UBM, ranked among the top five significant contributors to both post-operative vault and optimal ICL size prediction, consistently outperforming white-to-white (WTW). Moreover, dual-device combinations or single-device parameters could also effectively predict vault and ideal ICL size, and excellent ICL selection prediction was achievable using only UBM parameters.ConclusionsStrategies based on multiple machine learning algorithms for different ophthalmic devices and combinations are applicable for vault predicting and ICL sizing, potentially improving the safety of the ICL implantation. Moreover, our findings emphasize the crucial role of UBM in the perioperative period of ICL surgery, as it provides key STS measurements that outperformed WTW measurements in predicting post-operative vault and optimal ICL size, highlighting its potential to enhance ICL implantation safety and accuracy.

Collective Dynamics, Diversification and Optimal Portfolio Construction for Cryptocurrencies.

Since its conception, the cryptocurrency market has been frequently described as an immature market, characterized by significant swings in volatility and occasionally described as lacking rhyme or reason. There has been great speculation as to what role it plays in a diversified portfolio. For instance, is cryptocurrency exposure an inflationary hedge or a speculative investment that follows broad market sentiment with amplified beta? We have recently explored similar questions with a clear focus on the equity market. There, our research revealed several noteworthy dynamics such as an increase in the market's collective strength and uniformity during crises, greater diversification benefits across equity sectors (rather than within them), and the existence of a "best value" portfolio of equities. In essence, we can now contrast any potential signatures of maturity we identify in the cryptocurrency market and contrast these with the substantially larger, older and better-established equity market. This paper aims to investigate whether the cryptocurrency market has recently exhibited similar mathematical properties as the equity market. Instead of relying on traditional portfolio theory, which is grounded in the financial dynamics of equity securities, we adjust our experimental focus to capture the presumed behavioral purchasing patterns of retail cryptocurrency investors. Our focus is on collective dynamics and portfolio diversification in the cryptocurrency market, and examining whether previously established results in the equity market hold in the cryptocurrency market and to what extent. The results reveal nuanced signatures of maturity related to the equity market, including the fact that correlations collectively spike around exchange collapses, and identify an ideal portfolio size and spread across different groups of cryptocurrencies.

Analysis of Stress and Pillar Strength in Underground Coal Mines

Underground coal mining is located in Tanah Kuning, Batu Tanjung Village, Talawi District, Sawahlunto City. Some constraints arose in a CV. BMK is the existence of several mining fronts on mining blocks that have started to become critical and fail. It can be seen from the condition of the supports in some places that they have started to crook and break. In addition, in several locations, many rocks were found hanging (wedges) on the roof of the openings that could be seen between the rows of supports. This indicates a significant change in strain around the coal pits and pillars. The research was carried out by testing in situ stresses using Flat-jack, observing the condition of the rock mass, and testing the physical and mechanical properties of the rock. The purpose of this study was to find out the magnitude of the strength and stress on the pillarbased on the theory of tributary area loading, to provide safe and economical pillar geometry recommendations, and to discover the causes of rock mass movements. Based on the results of the analysis using the Tributary Area theory, the Safety factor Pillar 1 obtained was categorized as unsafe based on the reference value of the safety factor. The most ideal pillar size recommendation based on previous geotechnical studies was 9 m x 9 m with a maximum recovery of 38% and a safety factor of 1.7. Based on the results of the calculation of strength and loading on the pillars, the value of Pillar 1 strength is 6.0 MPa, Pillar 2 strength was 9.57 MPa, and Pillar 3 was 10.9 MPa with the value of Pillar load for Pillar 1 = 5.1 MPa, Pillar 2 = 4.47 MPa and Pillar 3 = 5.58 Mpa.

Comparative study of different formulae for prediction of best fit endotracheal tube size in children

BackgroundVarious formulae have been used to predict appropriate endotracheal tube (ETT) size in children, but there is no consensus regarding the best predictor. Recent use of ultrasonography (USG) to predict the ETT size may not always be feasible leaving the physical parameters as most useful and practical option. The present study was planned to compare age-, height- and weight-based formulae for ETT size prediction in children.ResultsThe accuracy in predicting ETT size was found to be 88.67%, 73.33% and 32.67% for height-based formula (HBF), age-based formula (ABF) and weight-based formula (WBF), respectively. Pearson correlation coefficient was best for HBF (0.968 with 95% CI of 0.937–0.999), followed by ABF (0.942 with 95% CI of 0.887–0.996) and WBF (0.874 with 95% CI of 0.794–0.953). HBF was found to be best suited for children 1–3 years, ≤ 90 cm and weight < 15 kg with accuracy of > 98%, while WBF was unsatisfactory across all age, height and weight groups.ConclusionsHBF is the best predictor of ETT size across all age groups with marginal superiority over ABF, especially in age group < 3 years. WBF was least effective in predicting ideal ETT size. It is recommended that HBF should be preferred over ABF and WBF for selection of ETT size in paediatric patients. This practice assumes greater importance especially in emergency situations where exact age and weight cannot be ascertained while height is easily obtainable.

Pine-to-Bioenergy: Potential of pine sap as adhesive and pine flower biomass waste in the production of biobriquettes

Pine-flower biomass waste is abundant, but its utilization is still lacking. This research converts pine-flower waste into biobriquettes by using pine resin adhesive. This study aims to identify the effect of pine resin adhesive concentration and the effect of grain size on the quality of the resulting biobriquettes. The production of biobriquettes begins by processing pine flower waste into biochar using the pyrolysis method at 400 °C. Biochar from pinecones was ground and sieved into sizes (250, 500, and 750 µm). Then proximate analysis (moisture content, ash content, volatile matter, fixed carbon), and heating value were performed. Making biobriquettes using pine resin adhesive with different concentrations (5, 10, and 15%) of the total mixture According to the results, the ideal grain size was 750 m, the adhesive concentration was 15%, and the moisture content, ash content, volatile matter content, fixed carbon content, and heating value were all respectively 2.23%, 4.51%, 30.23%, 70.04%, and 23.34 MJ/kg, and the longest flame was also determined to be 0.0250 g/sec. All of them comply with universally accepted biobriquette standards (Indonesian National Standard 01–6235–2000), Japanese, English, and ISO 17225. Biobriquettes have potential applications in bioenergy products. Investigation of the economic feasibility of biobriquette production seen from Profit on Sales is 26.43%, Rate on Investment is 34.00%, Pay Out Time is 2.47 years, and Break Event Point is 49.22%.

Body dissatisfaction, ideals, and identity in the development of disordered eating among adolescent ballet dancers.

Little is known about how female adolescent ballet dancers-a group at high-risk for the development of body dissatisfaction and eating disorders-construct body ideals, and how their social identities interact with body ideals to confer risk for disordered eating. Using a novel body figure behavioral task, this study investigated (1) whether degree of body dissatisfaction corresponded to severity of disordered eating thoughts and behaviors, and (2) how ballet identity corresponded with ideal body figure size among adolescent ballet dancers. Participants were 188 female ballet dancers ages 13-18 years who completed self-report measures of study constructs and the behavioral task. Linear regression models indicated that more severe body dissatisfaction was positively associated with increased disordered eating thoughts and behaviors (p < .19), except for muscle building (p = .32). We also found that identifying more strongly as a ballet dancer was correlated with having a smaller ideal body size (p = .017). Findings from this study suggest desire to achieve smaller body sizes is correlated with more severe disordered eating endorsement and stronger ballet identity. Instructors and clinicians may consider assessing the extent to which individuals identify as a ballet dancer as a risk factor for disordered eating and encourage adolescent dancers to build and nurture other identities beyond ballet. Eating disorders are debilitating conditions that can lead to malnutrition, social isolation, and even premature death. Though disordered eating thoughts and behaviors can affect anyone, adolescents in physically demanding and body image-driven activities including ballet dance are particularly vulnerable. Investigating how factors like body dissatisfaction and strength of identity are associated with disordered eating among high-risk groups is crucial for developing effective prevention and intervention methods that minimize harm.

Tilos Island's ideal microgrid size for wind, solar, and batteries

This article describes a power plant that is versatile regarding its modeling and associated with a Multiple Objectives Particle Swarm optimization in order to determine the optimal size of each component of the power plant. The simulation is appropriate for a variety of power sources, storage devices and loads. The method is utilized on a Wind Turbine/ Photovoltaic Device/ Battery System setup located in Tilos, Greece. The optimization is intended to reduce the expense of the system and the energy derived from alternative sources that are not renewable. The results produce a Pareto front that represents the expense of the equipment and the degree of autonomy of the micro-grid. The most effective solution to a specific expense associated with energy importation is demonstrated as an example.

Simultaneous network reconfiguration and capacitor allocations using a novel dingo optimization algorithm

&lt;span&gt;Power loss and voltage magnitude fluctuations are two major issues in distribution networks that have drawn a lot of attention. Numerous strategies have been put forward to provide remedies to lessen the undesirable effects of these issues. Combining two of these approaches and dealing with them simultaneously to get more effective outcomes is essential. Therefore, this study hybridizes the network reconfiguration and capacitor allocation strategies using a novel dingo optimization algorithm (DOA) to solve the optimization problems. The optimization problems for simultaneous network reconfiguration and capacitor allocations were formulated and solved using a novel DOA. To demonstrate its effectiveness, DOA’s results were contrasted with those of the other optimization techniques. The methodology was validated on the IEEE 33-bus network and implemented in the MATLAB program. The results demonstrated that the best network reconfiguration was accomplished with switches 7, 11, 17, 27, and 34 open, and buses 8, 29, and 30 were the best places for capacitors with ideal sizes of 512, 714, and 495 kVAr, respectively. The voltage profile was significantly improved, and the power losses were significantly decreased. When compared to some of the different methods, DOA came out on top.&lt;/span&gt;

An XGBoost approach to detect driver visual distraction based on vehicle dynamics

Objectives Distracted driving such as reading phone messages during driving is risky, as it increases the probability of severe crashes. This study proposes an XGBoost model for visual distraction detection based on vehicle dynamics data from a driving simulation study. Methods A simulated driving experiment involving thirty-six drivers was launched. We obtained the vehicle dynamics parameters required for the model using the time window and fast Fourier transform methods, totaling 26 items. Meanwhile, the effects of varied time window sizes (1–7 s) and amount of input indications on model performance were studied. Results By conducting a comparative analysis, it has been determined that the ideal time window size is 5 s. Additionally, the optimal number of input indicators was found to be 23. The XGBoost model for distinguishing distractions achieved an accuracy rate of 85.68%, a precision rate of 85.83%, a recall rate of 83.85%, an F1 score of 84.82%, and an AUC value of 0.9319, which were higher than SVM and RF. The gain-based feature rank demonstrated that the standard deviation of vehicle sideslip rate and the mean amplitude of the 0–1 Hz spectrum component of the steering wheel angle were more crucial than other features. Conclusions The research results indicate that the steering wheel angle and vehicle sideslip angle may be more conducive to identifying distractions. This XGBoost model could potentially be applied in advanced driving assistant systems (ADAS) to warn driver and reduce cellphone involved distracted driving.

In Situ Removable Additive Assisted Organic Solar Cells Achieving Efficiency over 19% and Fill Factor Exceeding 81%

AbstractAdditive engineering can precisely regulate the bulk‐heterojunction active layer morphology with ideal domain size and purity, playing a critical role in development of organic solar cells (OSCs). Herein, two solid additives, 1,4‐dichlorobenzene (DCB) and 1‐chloro‐4‐iodobenzene (CIB), with low melting point (mp.) of ≈52 °C, are investigated comprehensively with comparison to 1,4‐diiodobenzene (DIB, mp. 131 °C). After spin‐coating, DIB residue is found in the as‐cast PM6:BTP‐eC9 based blend film, whereas the DCB and CIB are completely removed during the spin‐coating, showing in situ removable properties that enable convenient processing. In OSCs, the DCB‐ and CIB‐processed active layers afford power‐conversion efficiencies (PCEs) of 18.2% and 18.4%, respectively, all higher than that of 17.8% for DIB. Among the three solid additives, the CIB is most effective in enhancements of absorption coefficients of the donor and acceptor, affording fast and more balanced carrier transports, and suppressing recombination. Of particular note, the CIB can provide some universality as an in situ removable solid additive, based on its elevations of PCEs for several binary and PM6:D18‐Cl:L8‐BO ternary active layers. Impressively, a prominent PCE of 19.1% with a remarkable fill factor of 81.1% is achieved for the CIB‐processed ternary active layer. This work demonstrates the potential of in situ removable solid additive engineering in high‐efficiency OSCs.

Nanoemulsification of soybean oil using ultrasonic microreactor: Process optimization, scale-up and numbering-up in series

Ultrasonically-induced nanoemulsions have been widely investigated for the development of functional food, cosmetics, and pharmaceuticals due to ideal droplet sizes (DS), low polydispersity index (PDI), and superior physical stability. However, a series of frequently-used ultrasonic set-ups mainly suffered from a low ultrasonic energy efficiency caused by the large acoustic impedance and energy consumption, subordinately confronted with a low throughput, complicated fabrication with complex structure and weak ultrasonic cavitation. Herein, we employed a typical ultrasonic microreactor (USMR) that ensured the high-efficient energy input and generated intense cavitation behavior for efficient breakage of droplets and continuous production of unified oil-in-water (O/W) nanoemulsions in a single cycle and without any pre-emulsification treatment. The emulsification was optimized by tuning the formula indexes, technological parameters, and numerical analysis using Response Surface Methodology (RSM), followed by a comparison with the emulsification by a traditional ultrasonic probe. The USMR exhibited superior emulsification efficiency and easy scale-up with remarkable uniformity by series mode. In addition, concurrent and uniform nanoemulsions with high throughput could also be achieved by a larger USMR with high ultrasonic power. Based on RSM analysis, uniform DS and PDI of 96.4 nm and 0.195 were observed under the optimal conditions, respectively, well consistent with the predicted values. Impressively, the optimal nanoemulsions have a uniform spherical morphology and exhibited superior stability, which held well in 45 days at 4℃ and 25℃. The results in the present work may provide a typical paradigm for the preparation of functional nanomaterials based on the novel and efficient emulsification tools.

Evaluation of the uniformity of UVA LED illumination on flat surfaces: Discrete ordinate method, single axis, and surface scanning radiometry

Uniform illumination from UVA LED lamps is a crucial design characteristic for a range of industries including photocatalytic applications. In this work, radiometry and the discrete ordinate method (DOM) are used to determine the ideal target surface size and working distance from a UVA LED lamp for highly uniform illumination. Horizontal incident radiation and full surface incident radiation measurements were conducted using a scanning radiometry technique. It is shown that horizontal incident and full surface incident radiation measurements show good agreement for uniformity measurements over a range of working distances, with maximum uniformity (2.6% and 3.6% standard deviation respectively) over the measured range found at 15 mm working distance. DOM simulation results showed good agreement with radiometry for power and incident radiation measurements, whilst indicating a maximum uniformity at 20 mm working distance. These results demonstrate that DOM simulations can be used as a fast, low cost, and reliable indication of surface uniformity, peak surface irradiance, and power measurements in the design of UV lamps for industrial and academic applications.

Religion or language? How family socialisation shapes the influence of parental origin-country fertility norms on the ideal family size among children of immigrants in France

ABSTRACT How do immigrant parents transmit their origin-country fertility ideals to their children? Drawing on a national sample of immigrants and their children in France (the ‘Trajectories et Origins’ survey), this study argues that the two main aspects of cultural practices in migrant families, religion and language, influence the fertility socialisation of immigrant children in different ways. Religion, often regulating family life and sexuality, directly shapes the ideal family size of immigrant children. Among children of immigrants, those growing up in Muslim families and those in highly religious families desire more children. By contrast, the use of parental origin-country language does not directly affect ideal family size but instead moderates country-of-origin influence. Those who (solely or partly) spoke their parental origin-country language at home during childhood conform more closely to parental origin-country fertility ideals than those who grew up speaking French. These findings highlight that religion and language play different roles in fertility socialisation in migrant families.

Optimizing Lipid Nanoparticles for Delivery in Primates.

Lipid nanoparticles (LNPs) are clinically proven to successfully deliver both small interfering RNA (siRNA) therapeutics and larger mRNA payloads for prophylactic vaccine applications. Non-human primates (NHPs) are generally considered to be the most predictive of human responses. However, for ethical and economic reasons, LNP compositions have historically been optimized in rodents. It has been difficult to translate LNP potency data from rodents to NHPs for intravenously (IV) administered products in particular. This presents a major challenge for preclinical drug development. An attempt to investigate LNP parameters, which have historically been optimized in rodents, is carried out, and seemingly innocuous changes are found to result in large potency differences between species. For example, the ideal particle size for NHPs (50-60nm) is found to be smaller than for rodents (70-80nm). Surface chemistry requirements are also different, with almost double the amount of poly(ethylene glycol) (PEG)-conjugated lipid needed for maximal potency in NHPs. By optimizing these two parameters, approximately eight-fold increase in protein expression from intravenously administered messenger RNA (mRNA)-LNP in NHP is gained. The optimized formulations are well tolerated when administered repeatedly with no loss of potency. This advancement enables the design of optimal LNP products for clinical development.

Bimetallic Biogenic Pt-Ag Nanoparticle and Their Application for Electrochemical Dopamine Sensor

In this study, Silver-Platinum (Pt-Ag) bimetallic nanoparticles were synthesized by the biogenic reduction method using plant extracts. This reduction method offers a highly innovative model for obtaining nanostructures using fewer chemicals. According to this method, a structure with an ideal size of 2.31 nm was obtained according to the Transmission Electron Microscopy (TEM) result. The Pt-Ag bimetallic nanoparticles were characterized using Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffractometry (XRD), and Ultraviolet-Visible (UV-VIS) spectroscopy. For the electrochemical activity of the obtained nanoparticles in the dopamine sensor, electrochemical measurements were made with the Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) methods. According to the results of the CV measurements taken, the limit of detection (LOD) was 0.03 µM and the limit of quantification (LOQ) was 0.11 µM. To investigate the antibacterial properties of the obtained Pt-Ag NPs, their antibacterial effects on Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacteria were investigated. In this study, it was observed that Pt-Ag NPs, which were successfully synthesized by biogenic synthesis using plant extract, exhibited high electrocatalytic performance and good antibacterial properties in the determination of dopamine (DA).