Efficacy of spectacle lenses specifically designed for myopia control: systematic review and meta-analysis.

Purpose: To investigate the efficacy of spectacle lenses designed to control myopia progression in individuals under 18 years old, focusing on changes in spherical equivalent refraction (SER), axial length (AL) and relative peripheral refraction (RPR).

Methods: A systematic review was conducted according to Prisma guidelines. Databases searched included PubMed, Embase, and Scopus, covering studies from the last six years without language restrictions.

Factorial Analysis and Thermal Kinetics of Chemical Recycling of Poly(ethylene terephthalate) Aided by Neoteric Imidazolium-Based Ionic Liquids.

Poly(ethylene terephthalate) (PET) waste accumulation poses significant environmental challenges due to its persistent nature and current management limitations. This study explores the effectiveness of imidazolium-based neoteric solvents [Emim][OAc] and [Bmim][OAc] as catalytic co-solvents in the glycolysis of PET with ethylene glycol (EG). Reaction thermal kinetics showed that both ionic liquids (ILs) significantly enhanced the depolymerization rate of PET compared to traditional methods.

Ultrasound-Assisted Extrusion Compounding of Nano Clay/Polypropylene Nano Compounds.

The incorporation of nanoparticles can significantly enhance the properties of polymers. However, the industrial production of nanocomposites presents a technological challenge in achieving the proper dispersion of nanoparticles within the polymer matrix. In this work, a novel device is presented that can be seamlessly integrated with standard twin-screw extruders, enabling the application of ultrasonic vibration to molten polymeric material.

Time-frequency co-movements between commodities and global economic policy uncertainty across different crises.

Commodity futures constitute an attractive asset class for portfolio managers. Propelled by their low correlation with other assets, commodities begin gaining popularity among investors, as they allow to capture diversification benefits. This comprehensive study examines the time and frequency spillovers between the Economic Policy Uncertainty [1] and a broad set of commodities encompassing ferrous, non-ferrous, and precious metals, food, and energy commodities over a period from December 1997 to April 2022, which includes various political, economic and health crises.

Promoter Effect of Pt on Zr Catalysts to Increase the Conversion of Furfural to γ-Valerolactone Using Batch and Continuous Flow Reactors: Influence of the Way of the Incorporation of the Pt Sites.

The valorization of biomass and its transformation into fuels are highly interesting due to the abundance of biomass and its almost neutral carbon emissions. In this article, we show the production of γ-valerolactone (GVL), a valuable product, from furfural (FF), a compound that can be easily obtained from biomass. This FF to GVL transformation involves a catalytic cascade reaction with two hydrogenation steps.

Anodizing Tungsten Foil with Ionic Liquids for Enhanced Photoelectrochemical Applications.

This research examines the influence of adding a commercial ionic liquid to the electrolyte during the electrochemical anodization of tungsten for the fabrication of WO nanostructures for photoelectrochemical applications. An aqueous electrolyte composed of 1.5 M methanesulfonic acid and 5% / [BMIM][BF] or [EMIM][BF] was used.

Injection Molding Plastic Solar Cells.

While organic photovoltaics are accessing specific application sectors taking advantage of their unique properties, it is important to identify as many differentiators as possible to expand the market penetration and consolidation of this technology. In this work, for the first time, the large-scale fabrication of organic photovoltaic modules embedded into structural plastic parts through industrial injection molding is demonstrated. Thermoplastic polyurethane is chosen as the injected material to show that this additional processing step can yield flexible, lightweight photovoltaic modules with enhanced device robustness and virtually unchanged performance.

Effects of vacancies on the thermal conductivity of Si nanowires.

Point defects can be used to tailor the properties of semiconductors, but can also have undesired effects on electronic and thermal transport, particularly in ultrascaled nanostructures, such as nanowires. Here we use all-atom molecular dynamics to study the effect that different concentrations and spatial distributions of vacancies have on the thermal conductivity of Si nanowires, overcoming the limitations of previous studies. Although vacancies are not as effective as the nanovoids found in porous Si, they can still reduce the thermal conductivity in ultrathin Si nanowires by more than a factor of two, when found in concentrations smaller than 1%.

Influence of free ammonia extraction in methane production from human urine.

Human urine has a high chemical oxygen demand (COD) content which makes anaerobic treatments potentially appropriate for the management of yellow waters, allowing for energy recovery. However, its high N content makes this treatment challenging. The present work studied the viability of performing an anaerobic digestion process for COD valorization on a real (not synthetic) urine stream at laboratory scale.

Location attributes explaining the entry of firms in creative industries: evidence from France.

This paper focuses on creative industries and the role played by the existing spatial distribution and agglomeration economies of these activities in relation to their entry decisions. We rely on employment and firm-level data in the creative industries (provided by INSEE) and compare the location of new establishments in the creative and non-creative industries between 2009 and 2013 in French departments (NUTS 3 regions). We use count data models and spatial econometrics to show that location determinants are rather similar in creative and non-creative industries and that specialisation in creative industries positively influences the entry of all other industries.

A Smart Agricultural System Based on PLC and a Cloud Computing Web Application Using LoRa and LoRaWan.

The increasing challenges of agricultural processes and the growing demand for food globally are driving the industrial agriculture sector to adopt the concept of 'smart farming'. Smart farming systems, with their real-time management and high level of automation, can greatly improve productivity, food safety, and efficiency in the agri-food supply chain. This paper presents a customized smart farming system that uses a low-cost, low-power, and wide-range wireless sensor network based on Internet of Things (IoT) and Long Range (LoRa) technologies.

The bioeconomy in spain as a new economic paradigm: the role of key sectors with different approaches.

The bioeconomy includes the sectors that use renewable biological resources to produce value added products, such as food, feed, energy, and bio-based products. Its importance has been demonstrated by its inclusion as a priority in specific and related policies such as the bioeconomy strategy, the Sustainable Development Goals, the European Green Deal, and the Next Generation recovery plan. Spain has not lagged behind and considers the bioeconomy as a priority in its policy strategies to achieve a more sustainable economy.

A Novel Approach of a Low-Cost UWB Microwave Imaging System with High Resolution Based on SAR and a New Fast Reconstruction Algorithm for Early-Stage Breast Cancer Detection.

In this article, a new efficient and robust approach-the high-resolution microwave imaging system-for early breast cancer diagnosis is presented. The core concept of the proposed approach is to employ a combination of a newly proposed delay-and-sum (DAS) algorithm and the specific absorption rate (SAR) parameter to provide high image quality of breast tumors, along with fast image processing. The new algorithm enhances the tumor response by altering the parameter referring to the distance between the antenna and the tumor in the conventional DAS matrices.

Deep learning for fully automatic detection, segmentation, and Gleason grade estimation of prostate cancer in multiparametric magnetic resonance images.

Although the emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), analyzing these images remains still complex even for experts. This paper proposes a fully automatic system based on Deep Learning that performs localization, segmentation and Gleason grade group (GGG) estimation of PCa lesions from prostate mpMRIs. It uses 490 mpMRIs for training/validation and 75 for testing from two different datasets: ProstateX and Valencian Oncology Institute Foundation.

Healthy lifestyle, metabolomics and incident type 2 diabetes in a population-based cohort from Spain.

Background: The contribution of metabolomic factors to the association of healthy lifestyle with type 2 diabetes risk is unknown. We assessed the association of a composite measure of lifestyle with plasma metabolite profiles and incident type 2 diabetes, and whether relevant metabolites can explain the prospective association between healthy lifestyle and incident type 2 diabetes.

Methods: A Healthy Lifestyle Score (HLS) (5-point scale including diet, physical activity, smoking status, alcohol consumption and BMI) was estimated in 1016 Hortega Study participants, who had targeted plasma metabolomic determinations at baseline examination in 2001-2003, and were followed-up to 2015 to ascertain incident type 2 diabetes.

Glycoprotein Profile Measured by a H-Nuclear Magnetic Resonance Based on Approach in Patients with Diabetes: A New Robust Method to Assess Inflammation.

Patients with type 2 diabetes mellitus (T2DM) and atherogenic dyslipidemia (AD) are at higher risk of developing cardiovascular diseases (CVDs), so an interest in discovering inflammation biomarkers as indicators of processes related to CVD progression is increasing. This study aims (a) to characterize the plasma glycoprotein profile of a cohort of 504 participants, including patients with and without T2DM and/or AD and controls, and (b) to study the associations between the glycoprotein profile and other lipid and clinical variables in these populations. We characterized the plasma glycoprotein profiles by using H-NMR.

Detection of Invisible Damages in 'Rojo Brillante' Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics.

The main cause of flesh browning in 'Rojo Brillante' persimmon fruit is mechanical damage caused during harvesting and packing. Innovation and research on nondestructive techniques to detect this phenomenon in the packing lines are necessary because this type of alteration is often only seen when the final consumer peels the fruit. In this work, we have studied the application of hyperspectral imaging in the range of 450-1040 nm to detect mechanical damage without any external symptoms.

Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview.

Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFLD starts quietly and can progress until liver damage is irreversible.

Ultrasonic nodal point, a new configuration for ultrasonic moulding technology.

Ultrasonic moulding is a new technology that uses high power ultrasound to melt and mould thermoplastic polymers to produce samples with mini and micro features. The main feature of this technology is the use of ultrasonic energy as the heating source instead of a conventional injection screw. Even if ultrasonic moulding overcomes some of the drawbacks of conventional mini and micro-injection moulding, it still presents two main limitations that are hindering its widespread applicability: the lack of stability of the process and the difficulty to obtain samples with good mechanical properties for some materials.

Laparoscopic sleeve gastrectomy alters H-NMR-measured lipoprotein and glycoprotein profile in patients with severe obesity and nonalcoholic fatty liver disease.

Patients with morbid obesity frequently present non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH) associated with pro-atherogenic alterations. Laparoscopic sleeve gastrectomy (LSG) is an effective treatment for weight reduction, and for the remission of hepatic alterations. Using H-nuclear magnetic resonance (H-NMR), we investigated the effects of LSG on lipoprotein and glycoprotein profile in patients with morbid obesity and liver disease.

Do local characteristics act in a similar way for the first two waves of COVID-19? Analysis at intraurban level in Barcelona.

Background: This paper concerns the spatial determinants of the first two waves of COVID-19 at the neighbourhood level.

Methods: Using data for the first and second waves of COVID-19 at the neighbourhood level in Barcelona, we analyse whether local characteristics acted in the same way during the two waves and identify typologies of areas depending on such determinants. Univariate and bivariate local Moran's I and count data models are used.

Enhanced prediction of hemoglobin concentration in a very large cohort of hemodialysis patients by means of deep recurrent neural networks.

Erythropoiesis Stimulating Agents (ESAs) have become a standard anemia management tool for End Stage Renal Disease (ESRD) patients. However, dose optimization constitutes an extremely challenging task due to huge inter and intra-patient variability in the responses to ESA administration. Current data-based approaches to anemia control focus on learning accurate hemoglobin prediction models, which can be later utilized for testing competing treatment choices and choosing the optimal one.

Plant-wide modelling in wastewater treatment: showcasing experiences using the Biological Nutrient Removal Model.

Plant-wide modelling can be considered an appropriate approach to represent the current complexity in water resource recovery facilities, reproducing all known phenomena in the different process units. Nonetheless, novel processes and new treatment schemes are still being developed and need to be fully incorporated in these models. This work presents a short chronological overview of some of the most relevant plant-wide models for wastewater treatment, as well as the authors' experience in plant-wide modelling using the general model BNRM (Biological Nutrient Removal Model), illustrating the key role of general models (also known as supermodels) in the field of wastewater treatment, both for engineering and research.

Low temperature conversion of levulinic acid into γ-valerolactone using Zn to generate hydrogen from water and nickel catalysts supported on sepiolite.

In the present article, γ-valerolactone has been obtained from levulinic acid with a yield exceeding 25% using very mild conditions without feeding hydrogen (30 °C, atmospheric pressure, water as the hydrogen source). The overall reaction conducted is a two-step process: first, a redox reaction involving the oxidation of metallic Zn to ZnO for hydrogen production through the water splitting reaction and, second, a catalytic reaction involving Ni-supported catalysts for the production of γ-valerolactone from levulinic acid. Ni active sites have been supported on sepiolite, an abundant and cheap material.