Investigating the variation of particle distribution and surface texture of top surfaces based on build position in laser powder bed fusion

Quality analysis of additively manufactured (AM) surfaces is complex, yet critical for determining the functionality of parts and technology improvement. To accurately assess the quality of AM parts, it is necessary to consider the industrial application of the technology. This study investigates the variation of accumulated particles on AM top surfaces as a function of build position. It also seeks to study the surface texture variation as a function of build position, focusing on a spatial bandwidth region larger than that of traditional AM surface features, such as weld tracks, to investigate surface tension effects. Ti-6Al-4V cubes were built in a three-by-three array in a single build with fixed processing parameters. Coherence scanning interferometry was used to capture the primary data of the as-built top surfaces of cubes. The ISO 25178-2 methodology was used to extract the S-L surfaces, using the filtration methods defined in ISO 16610-21. The number of particles, coverage, and density were obtained by averaging over five repeated measurements in five different areas on the top surfaces. Particle distribution and surface texture analysis showed a trend from one location to another across the build, which is discussed according to the process variations

The 2022 symposium on dementia and brain aging in low‐ and middle‐income countries: Highlights on research, diagnosis, care, and impact

Two of every three persons living with dementia reside in low‐ and middle‐income countries (LMICs). The projected increase in global dementia rates is expected to affect LMICs disproportionately. However, the majority of global dementia care costs occur in high‐income countries (HICs), with dementia research predominantly focusing on HICs. This imbalance necessitates LMIC‐focused research to ensure that characterization of dementia accurately reflects the involvement and specificities of diverse populations. Development of effective preventive, diagnostic, and therapeutic approaches for dementia in LMICs requires targeted, personalized, and harmonized efforts. Our article represents timely discussions at the 2022 Symposium on Dementia and Brain Aging in LMICs that identified the foremost opportunities to advance dementia research, differential diagnosis, use of neuropsychometric tools, awareness, and treatment options. We highlight key topics discussed at the meeting and provide future recommendations to foster a more equitable landscape for dementia prevention, diagnosis, care, policy, and management in LMICs. Highlights: Two‐thirds of persons with dementia live in LMICs, yet research and costs are skewed toward HICs. LMICs expect dementia prevalence to more than double, accompanied by socioeconomic disparities. The 2022 Symposium on Dementia in LMICs addressed advances in research, diagnosis, prevention, and policy. The Nairobi Declaration urges global action to enhance dementia outcomes in LMICs

Constructing selection hyper-heuristics for open vehicle routing with time delay neural networks using multiple experts

Hyper-heuristics are general purpose search methods for solving computationally difficult problems. A selection hyper-heuristic is composed of two key components: a heuristic selection method and move acceptance criterion. Under an iterative single-point search framework, a solution is modified by selecting and applying a predefined low-level heuristic, with a decision then taken to accept or reject the resulting solution. Designing a selection hyper-heuristic is an extremely challenging task. In this study, we investigate computer-aided design of a selection hyper-heuristic for the open vehicle routing problem. A time delay neural network is used as an offline apprenticeship learning method. Our approach first observes the search behaviour of multiple expert human-designed selection hyper-heuristics on a selected sample of training instances, before automatically generating a selection hyper-heuristic capable of solving unseen instances effectively. The proposed approach is tested on open vehicle routing problem instances of different sizes to examine the performance and generality of the selection hyper-heuristics generated. Improved performance is demonstrated over a set of well-known benchmarks from the literature when compared to using the existing expert systems directly

The Cool Farm Biodiversity metric: an evidence-based online tool to report and improve management of biodiversity at farm scale

Halting biodiversity loss and achieving food security are both aims of the United Nations 2030 Agenda for Sustainable Development, but there is complex interplay between them. Agriculture drives biodiversity loss, but biodiversity provides benefits to agriculture. There is substantial potential to develop ‘win-win’ solutions for biodiversity and people within productive farmland, by boosting wildlife that can be supported, whilst maintaining yield and other services. To achieve this, farmers need to be able to assess the impacts of their management on biodiversity at farm scale. While suitable tools exist to drive improvement in biodiversity management, none incorporates evidence on the effectiveness of specific management practices. In this study we present the Cool Farm Biodiversity metric, which generates a farm-scale action-based biodiversity management assessment, scored using expert judgements and expert assessment of experimental evidence. The metric is designed to be biome-specific, so it responds to conservation aims, ecosystem processes and farming systems in particular biomes. To demonstrate that the metric is responsive to changes in farm management, we present an example of use on a large arable farm from the temperate forest biome

Understanding the impact of numerical solvers on inference for differential equation models

Most ordinary differential equation (ODE) models used to describe biological or physical systems must be solved approximately using numerical methods. Perniciously, even those solvers that seem sufficiently accurate for the forward problem, i.e. for obtaining an accurate simulation, might not be sufficiently accurate for the inverse problem, i.e. for inferring the model parameters from data. We show that for both fixed step and adaptive step ODE solvers, solving the forward problem with insufficient accuracy can distort likelihood surfaces, which might become jagged, causing inference algorithms to get stuck in local ‘phantom’ optima. We demonstrate that biases in inference arising from numerical approximation of ODEs are potentially most severe in systems involving low noise and rapid nonlinear dynamics. We reanalyse an ODE change point model previously fit to the COVID-19 outbreak in Germany and show the effect of the step size on simulation and inference results. We then fit a more complicated rainfall run-off model to hydrological data and illustrate the importance of tuning solver tolerances to avoid distorted likelihood surfaces. Our results indicate that, when performing inference for ODE model parameters, adaptive step size solver tolerances must be set cautiously and likelihood surfaces should be inspected for characteristic signs of numerical issues

Perceptions, definitions, and therapeutic interventions for occasional constipation: a ROME working group consensus document

Background & Aims: Functional constipation is the most common of the disorders of gut-brain interaction, affecting approximately 12% of the world population. Although classically considered a chronic condition, many individuals experience shorter yet repetitive bouts of constipation representing a different clinical entity. There has been increased interest in this latter disorder, which has recently been classified as occasional constipation. This Rome Foundation working group document reflects the consensus of an international team of specialists who summarized currently available research to provide a working definition of and treatment algorithm for occasional constipation. The recommendations herein are based on current evidence, accounting for gaps in the literature as well as international variance in definitions and health seeking behaviors for constipation. Methods: The committee members reviewed the scientific literature, focusing specifically on occasional constipation, with the understanding that as a new entity, a paucity of data would be available. We used Rome IV research and clinical definitions to establish the framework for our definition of occasional constipation. Where possible, treatment recommendations were determined on the basis of the earliest extractable data from functional constipation studies, focusing on positive results within the first 2 weeks of treatment. We used the Delphi method to create consensus with 100% agreement between the authors. Results: An evidence-based review of the literature resulted in the definition of occasional constipation as follows: “individuals who experience the presence of at least 1 functional constipation symptom, in the absence of alarm signs or symptoms, occurring at irregular and infrequent intervals, which is bothersome enough to induce a patient to seek medical management.” Medical management whether seeking medical care or self-treatment was left to the individual's discretion, and we did not include time anchors because these thresholds require further investigation. Polyethylene glycol and stimulant laxatives are recommended as first-line interventions, whereas magnesium-containing compounds are suggested in individuals failing to respond to these therapies. There are insufficient data to make recommendations for using fiber or stool softeners. Prescription laxatives should be reserved for individuals with chronic constipation. Conclusions: Occasional constipation is a unique clinical entity characterized by infrequent but recurrent symptoms. Data are limited because consensus definitions have been lacking. Establishing a standardized definition and therapeutic recommendations provides a framework for future studies focusing on epidemiologic and symptoms-based outcomes. Further studies are needed to confirm and refine these recommendations

Uniform cooling for concentrator photovoltaic cell by micro-encapsulated phase change material slurry in double-layered minichannels

The concentrator photovoltaic (CPV) systems often suffer high heat flux, leading to cell temperatures rising, which will affect its performance and reduce the service life. Double-layered minichannel heat sink (DL-MCHS) is an efficient cooling technology, which could effectively lower down the top temperature of CPV cell. Micro-encapsulated phase change material slurry (MPCS) is a novel type of latent heat functional fluid and has a good application prospect in the field of cooling. Therefore, MPCS flowing in the DL-MCHS, as the thermal management device was investigated for the cooling of CPV cell. Three configurations of minichannels, including staggered arrangement, parallel arrangement and dual unequal arrangement were compared and optimized. On the basis of optimization, the flow and heat transfer performance of MPCS with different concentrations in double-layered straight and wavy minichannels had been numerically studied. The results indicated that the lowest top temperature of dual unequal DL-MCHS obtained by counter arrangement could be reduced by 0.56 °C compared with the parallel arrangement at Re = 152. Both the ΔP and h were significantly influenced by concentrations. When Re reached 262, ΔP of 5 wt% MPCS in wave minichannel with 5 mm wavelength was 44 % larger than that of pure water in straight minichannel, which would consume more pumping power. However, the heat dissipation performance was improved significantly and Nusselt number in double-layered wavy minchannels also increased with the wavelength decreasing. Therefore, Performance Evaluation Criteria (PEC) was proposed to evaluate the overall performance, which was also greatly influenced by particle concentration and channel wavelength. After optimization, the highest PEC of MPCS in the wavy minichannel was achieved to 1.60. Because of the wavy minichannel with concave-convex structure, the obstacle of total thermal resistance became smaller for the wavelength decreasing. These findings of MPCS in minichannel can provide a good theoretical basis and engineering application in the cooling technology of CPV

Mechanistic insight into the role of AUXIN RESISTANCE4 in trafficking of AUXIN1 and LIKE AUX1-2

AUXIN RESISTANCE4 (AXR4) regulates the trafficking of auxin influx carrier AUXIN1 (AUX1), a plasma-membrane protein that predominantly localizes to the endoplasmic reticulum (ER) in the absence of AXR4. In Arabidopsis (Arabidopsis thaliana), AUX1 is a member of a small multigene family comprising 4 highly conserved genes—AUX1, LIKE-AUX1 (LAX1), LAX2, and LAX3. We report here that LAX2 also requires AXR4 for correct localization to the plasma membrane. AXR4 is a plant-specific protein and contains a weakly conserved α/β hydrolase fold domain that is found in several classes of lipid hydrolases and transferases. We have previously proposed that AXR4 may either act as (i) a post-translational modifying enzyme through its α/β hydrolase fold domain or (ii) an ER accessory protein, which is a special class of ER protein that regulates targeting of their cognate partner proteins. Here, we show that AXR4 is unlikely to act as a post-translational modifying enzyme as mutations in several highly conserved amino acids in the α/β hydrolase fold domain can be tolerated and active site residues are missing. We also show that AUX1 and AXR4 physically interact with each other and that AXR4 reduces aggregation of AUX1 in a dose-dependent fashion. Our results suggest that AXR4 acts as an ER accessory protein. A better understanding of AXR4-mediated trafficking of auxin transporters in crop plants will be crucial for improving root traits (designer roots) for better acquisition of water and nutrients for sustainable and resilient agriculture

High Step-Up Dual-Switch X-Source DC-DC Converters Integrating Various Capacitor-Winding-Diode Voltage-Double Technology

In this article, a new class of high step-up dual-switch X-source dc–dc converters integrating various capacitor-winding-diode voltage-double technology is presented, which are parallel-winding dual-switch X-source dc–dc converters, series-winding dual-switch X-source dc–dc converters, and flipped parallel-winding dual-switch X-source dc–dc converters. According to different winding homonymous end connections, voltage gains and turn ratios of proposed converters have two relations: inversely proportional relations and positive proportional relations. Also, all proposed topologies can produce the higher voltage gain, and own the lower voltage stresses. Operation principles, math derivations, and performance advantages of the proposed converters are analyzed in detail. Finally, the experimental prototype is built to demonstrate the operational feasibility of the proposed converter

Macroprudential policies and Brexit: A welfare analysis

Brexit will have implications on financial stability and the implementation of macroprudential policies. The United Kingdom (UK) will no longer be subject to the jurisdiction of the European Systemic Risk Board. This paper studies the welfare implications of this change of regime. By means of a dynamic stochastic general equilibrium model, I compare the pre-Brexit scenario with the new one, in which the UK sets macroprudential policy independently. I find that, after Brexit, the UK is better off by setting its own macroprudential policy without taking into account Europe's welfare as a whole