Miracle-dz/UniFAR-FTUs huggingface dataset:
From InGaN pyramids to micro-LEDs characterized by cathodoluminescence

We present a study of the optical properties of various steps in the process of fabricating micro light-emitting diodes (μ-LEDs) based on quantum wells embedded in micron-sized InGaN platelets. In this study, we focus on structures for red emission, but the technology is equally suitable for the less technologically challenging blue and green emitting μ-LEDs. The starting point is growth of an InGaN pyramid with a sub-micron sized hexagonal base. The pyramid is flattened to create a flat top c-facet for the subsequent InGaN quantum well growth. We compare two approaches, reshaping of the pyramid by high-temperature annealing; and by chemical mechanical polishing. Their merits are discussed. The flattened platelets are used as templates to grow low-strain single quantum wells in both heterostructures and full LEDs including n- and p-barriers on either side of the quantum well. The structures are investigated in terms of homogeneity in peak energy position and intensity using hyperspectral cathodoluminescence imaging. We observe that the main contribution to inhomogeneity is the growth of the initial pyramid, that exhibits regular, facet driven variations in the In incorporation.
An Algorithm for Detecting the Integrity of Outer Frame Protection Net on Construction Site Based on Improved SSD

In recent years, the continuous development of the basic construction industry has promoted the progress of urban social economy, and the safety issues in construction have attracted more and more attention. The integrity of the external protection net is of great significance to the safety of the construction personnel. Most of the traditional methods of detecting damage to the protection net have problems such as poor real-time performance and low detection accuracy. In this paper, we present a novel approach based on SSD for solving the problem of the integrity detection of the external frame protection net in the construction site. The improved network merges adjacent feature layers to enrich the semantics of shallow feature maps, thereby improving the detection accuracy of the network, and simultaneously introduces a shallower feature layer and a more advanced receptive field module to improve the detection ability of small targets. The experimental results show that compared with the SSD algorithm, the improved algorithm has higher detection accuracy in the detection task of the external protective net on the construction site, and can meet the real-time detection requirements.
Public space as water infrastructure strategy in achieving runoff flood resilience on a neighborhood scale

Jakarta is a delta city that stands on an alluvial deposits land with 13 rivers from various parts of the city flowing through the town. It makes Jakarta vulnerable to natural disasters related to water elements, one of which is runoff flooding caused by insufficient river water capacity to accommodate an additional water volume. With the extra unaccommodated water volume, water overflows and cannot be reabsorbed by the land surface to stagnate into areas prone to flooding and disrupt people’s activities. Jakarta needs an area resilience against runoff flood disasters, which can be achieved by building infrastructure that is constructed holistically against the city’s water elements to accommodate temporary storage of falling rainwater. We used case studies to analyze Jakarta’s existing park and its potential. We also analyzed Benthemplein Water Square, Rotterdam, Netherlands, to see how the city can build neighborhood resilience. We conclude that public space as the solution for Jakarta’s runoff floods is possible as long as its site context is considered during the design phase. Rotterdam shows that even though the green area is not the dominant part, the built environment can help discharge the rainwater to the nearby river as long as it has a good infrastructure design that can accommodate rainwater storage.
Research on Population Spatialization Method Based on AWA-ESPCN

The spatialization of population is the process of rasterizing demographic data, which is of great significance for government decision-making and promoting the coordinated and sustainable development of social economy, resources and environment. In the continuous research of multiple linear regression, spatial interpolation, the use of multi-source heterogeneous data, random forest and other methods, a batch of highly representative global and national-scale population spatial databases have been born. Therefore, through the super-resolution of deep learning the method is more valuable for population low-scale sampling research and end-to-end mapping to achieve high-precision downscaling and enhance the robustness and generalization of the training model. This paper is based on the population statistics of the counties in Chongqing municipality in 2010, through the area-weighted rasterization coupled sub-pixel convolutional neural network (ESPCN) to learn the global and local features of the population to achieve 500m resolution population spatialization, and compare it with the other 2 compare plan. The results show that the training model using this method has the lowest mean square error, the smallest residual interval, and the best picture effect.
Understanding cotton cultivation dynamics in Aksu Oases (NW China) by reconstructing change trajectories using multi-temporal Landsat and Sentinel-2 data

Abstract Understanding spatiotemporal dynamics of cotton cultivation patterns is an essential input to cotton farming management, production prediction and policy formulations. Thus, this study demonstrates cotton cultivation dynamics by constructing their change trajectories using multi-temporal Landsat and Sentinel-2 images. Then we reclassified the trajectories into four change trends, namely permanent cotton-field, cotton-field gain, cotton-field loss and unstable changes type. The results showed that increased cotton-cultivated areas were greater than the decreased areas. Cotton fields’ expansion gradually appeared in the outer parts of the permanent cotton fields, especially towards the northern mountain front alluvial-plain. Production decline caused by cotton cultivation loss was 3.09 × 108 kg. The observed cotton cultivation dynamics were associated to farmers’ options driven by crop price fluctuations, agricultural policies and natural conditions. The production loss was associated to cotton field loss and fields that underwent unstable changes. Management strategies should thus focus intercepting the loss and the unstable change trajectories.
Extraction of optimal fatigue‐driving steering indicators considering individual differences

Extracting effective steering indicators is critical for fatigue-identiﬁcation based on steering behaviour. However, considering individual differences, the best calculation parameters of the individual driver’s steering indicators are different. The indicator’s performance decreases by using uniﬁed parameters rather than the individual driver’s best parameters. The authors propose a model extracting individual driver’s optimal fatigue steering indicators calculated by the individual driver’s best parameters. Individual driver’s naturalistic driving data are analysed by the model. First, indicators in sober and fatigue state are examined by the Wilcoxon test, and |Z| represents the indicator’s fatigue-identiﬁcation performance. And the function reﬂecting correspondences between calculation parameters and indicator’s fatigue-identiﬁcation performance is constructed. Then the function is optimized using particle swarm optimization to obtain individual driver’s best calculation parameters maximizing | Z |. Finally, effective indicators calculated by the individual driver’s best parameters constitute the individual driver’s optimal fatigue indicator set. Indicators calculated by the individual driver’s best parameters and uniﬁed parameters are used to establish the individual fatigue-identiﬁcation model. The average identiﬁcation accuracy of models using individual driver’s best parameters and uniﬁed parameters is 87.4% and 79.1%, which indicates using individual driver’s optimal fatigue indicators can improve identiﬁcation accuracy. This study can provide references for individualized fatigue-driving identiﬁcation
Weather-Related Construction Delays in a Changing Climate: A Systematic State-of-the-Art Review

Adverse weather delays forty-five percent of construction projects worldwide, costing project owners and contractors billions of dollars in additional expenses and lost revenue each year. Additionally, changes in climate are expected to increase the frequency and intensity of weather conditions that cause these construction delays. Researchers have investigated the effect of weather on several aspects of construction. Still, no previous study comprehensively (1) identifies and quantifies the risks weather imposes on construction projects, (2) categorizes modeling and simulation approaches developed, and (3) summarizes mitigation strategies and adaptation techniques to provide best management practices for the construction industry. This paper accomplishes these goals through a systematic state-of-the-art review of 3207 articles published between 1972 and October 2020. This review identified extreme temperatures, precipitation, and high winds as the most impactful weather conditions on construction. Despite the prevalence of climate-focused delay studies, existing research fails to account for future climate in the modeling and identification of delay mitigation strategies. Accordingly, planners and project managers can use this research to identify weather-vulnerable activities, account for changing climate in projects, and build administrative or organizational capacity to assist in mitigating weather delays in construction. The cumulative contribution of this review will enable sustainable construction scheduling that is robust to a changing climate.
Physicochemical Properties of Rice Flour Suspension Treated by Ultrahigh Hydrostatic Pressure

This study investigated the physicochemical properties of rice flour suspensions under ultrahigh hydrostatic pressure (UHP) treatment. Rice flour suspensions were subjected to 200, 400, and 600 MPa of pressure for 10 min, and heat treatment was used as a control. Proximate characteristics of different rice cultivar were analyzed to amylose, damage starch content, and particle size. Changes in physicochemical properties of rice flour suspensions according to UHP treatment were analyzed to microscopic structure, iodine reaction, α-amylase hydrolysis rate, and resistant starch content. Microscopic structural analyses showed that the structures of the rice flours were altered under both heat and 600 MPa treatment conditions. Water absorption rates were highest under heat treatment (467.53–554.85%), followed by 600 MPa treatment (269.55–334.57%). Iodine reaction values increased with increasing applied pressure. α-Amylase hydrolysis rates and resistant starch contents were highest under heat treatment and increased with increasing applied pressure. Based on these results, 600 MPa treatment of rice flour suspensions was shown to be comparable to heat treatment; as a result, the development of the new rice processing method with different physicochemical properties is expected from rice cultivars treated under UHP processing methods.
Effects of Increased Extracellular Potassium Concentration Induced by Ischemia on the Vulnerability of Ventricular Arrhythmias and the Regularity of Related Ventricular Tachycardia

Myocardial ischemia could induce arrhythmias such as ventricular tachycardia and ventricular fibrillation, leading to sudden death and other serious consequences. This manuscript adopted the cardiac modeling and simulation method to study the activity pattern of myocardial ischemia-related ventricular tachycardia and the effect of increased extracellular potassium concentration on arrhythmia vulnerability. A whole ventricular electrophysiological model of endocardial ischemia caused by distal occlusion of left anterior descending coronary artery was established. The simulation results suggested that the relationship between the vulnerability of ventricular arrhythmias and extracellular potassium concentration was bell shaped with a peak in susceptibility at 12 mM. This result was caused by the effect of extracellular potassium concentration on the dispersion of repolarization and the effective refractory period of cardiomyocytes. The extension of the effective refractory period was due to the electrical remodeling of the ventricle. Specifically, it was because of the delayed recovery of the INa current. In addition, the regularity of endocardial/epicardial reentrant pattern during non-transmural ischemia was also analyzed. The endocardium formed micro-reentrant, while the epicardium established macro-reentrant rotating around the ischemic regions provided a new idea for the determination of clinical ablation targets.
Swing reduction for double‐pendulum three‐dimensional overhead cranes using energy‐analysis‐based control method

In practical applications, when the mass of the hook cannot be ignored or the shape of the payload is irregular, the crane often exhibits the dynamic characteristics of double‐pendulum. Due to the complexity of double‐pendulum effect, the design of a controller for an three‐dimensional overhead crane with double‐pendulum effect is more complicated and more challenging. In addition, it is difficult to obtain satisfactory control performance due to the uncertainty of the parameters of the crane system. Moreover, the saturation constraint of the actuator is not considered, which may cause the actuator to saturate and severely degrade the control performance. Aiming at these practical problems, we propose a nonlinear controller based on energy analysis for the three‐dimensional overhead cranes system with double‐pendulum effect, while considering the saturation constraints of the actuator. Meanwhile, the asymptotic stability of the closed‐loop system is not only guaranteed. The comparative simulation and experimental results demonstrate the effectiveness of the proposed controller in trolley positioning and swing angles eliminating.
Tert-butyl alcohol used to fabricate nano-cellulose aerogels via freeze-drying technology

Aerogel, a highly porous material, is attracting increasing attention owing to low thermal conductivity and high specific surface area. Freeze-drying technology has been employed to produce nano-cellulose aerogels; however, the resultant product has low specific surface areas. Here, a modified approach to prepare nano-cellulose aerogels was reported, which involves tert-butyl alcohol as a solvent. Nano-cellulose aerogels were prepared via a spontaneous gelation fashion using calcium chloride solution, followed by tert-butyl alcohol solvent displacement and freeze drying. Addition of calcium chloride (0.25%) accelerated the physical gelation process. The application of tert-butyl alcohol as a solvent contributed to preservation of gel network. The obtained spherical nano-cellulose aerogels had a shrinkage rate of 5.89%. The specific surface area and average pore size was 164. 9666 m2 g−1 and 10.01 nm, respectively. Additionally, nano-cellulose aerogels had a comparable thermal degradation property when compared to microcrystalline cellulose. These biophysical properties make nano-cellulose aerogels as a promising absorption material.
Assessing the Viability of Rainwater Harvesting System for Sustainable Manufacturing in Water Stressed Regions

Water is considered to the life wire of many manufacturing industry. Water is used for processing of materials, cooling of engines, firefighting and also important for sanitation and welfare of workers. As the population of the world increases, the demand for water to meet domestic and industrial needs of man increases. In line with sustainable development, there is need for practices in manufacturing which will help preserve scarce resources for domestic needs. The global trend in industries is sustainable manufacturing which is hinged at increasing operational efficiency and as well reducing cost and wastages. As a result, there is a growing interest on rainwater as an alternative source. In this paper, the rainwater harvesting system was assessed to establish its viability for a small scale pozzolana plant for sustainable manufacturing. The methodology adopted was estimating water consumption in the production plant and potential harvestable rainwater from the roof top. The harvestable rainwater was estimated based on the rainfall data obtained from the Famine Early Warning Systems Network (FEWS NET) and the rooftop (catchment) area was determined by taking dimensions of the rooftop to establish the area while a collection efficiency of 90% was assumed. Design and operational parameters from literature was used to describe the effectiveness of the system for the study area. Results revealed that water demand to run the plant for production and sanitation for staff welfare can be covered substantially using rainwater with a reliability of 99.7% and annual water savings of 1,350,000.00. The investment is viable and will be amortized in only 1.6 years. The rainwater harvesting system will generate economic benefits by reducing the cost of production and consequently the selling price will be reduced for consumers.
Disturbance observer based dead‐beat control of multi‐input systems with unknown disturbances and bounded inputs using discrete‐time higher order sliding mode

This article proposes a new robust dead‐beat controller for multivariable systems using multirate sampled data. Applying a discrete‐time higher order sliding mode control approach, the proposed dead‐beat controller design uses the state‐space nominal model (model without disturbances) of the system and its controllability indices to compute the state feedback matrix. The obtained control annihilates the system state in a minimal number of sampling periods. For example, a heuristic procedure for selecting a sampling time is considered in order to keep maximal amplitudes of control inputs within the allowable limits. Since the dead‐beat control has poor robustness, a new discrete‐time supertwisting disturbance observer is used to suppressed disturbance effects. Stability analysis of the proposed observer has shown that it is suitable for Lipschitz type of disturbances. The sampling period of the disturbance observer is generally smaller than the control sampling period. Properties of the proposed control system are demonstrated in simulation examples.
Identification of monetary shocks through the yield curve: Evidence for Brazil

This paper derives a new measure of monetary shock for Brazil based on the yield curve. First, the Diebold and Li (2006) model is estimated with nominal yields. The changes of the latent variables of this model surrounding monetary policy meetings are used to analyze the effects on the Brazilian economy. Monetary policy decisions associated with steeper yield curves lead to higher future economic activity.
Phenotypic plasticity under rapid global changes: The intrinsic force for future seagrasses survival

Coastal oceans are particularly affected by rapid and extreme environmental changes with dramatic consequences for the entire ecosystem. Seagrasses are key ecosystem engineering or foundation species supporting diverse and productive ecosystems along the coastline that are particularly susceptible to fast environmental changes. In this context, the analysis of phenotypic plasticity could reveal important insights into seagrasses persistence, as it represents an individual property that allows species’ phenotypes to accommodate and react to fast environmental changes and stress. Many studies have provided different definitions of plasticity and related processes (acclimation and adaptation) resulting in a variety of associated terminology. Here, we review different ways to define phenotypic plasticity with particular reference to seagrass responses to single and multiple stressors. We relate plasticity to the shape of reaction norms, resulting from genotype by environment interactions, and examine its role in the presence of environmental shifts. The potential role of genetic and epigenetic changes in underlying seagrasses plasticity in face of environmental changes is also discussed. Different approaches aimed to assess local acclimation and adaptation in seagrasses are explored, explaining strengths and weaknesses based on the main results obtained from the most recent literature. We conclude that the implemented experimental approaches, whether performed with controlled or field experiments, provide new insights to explore the basis of plasticity in seagrasses. However, an improvement of molecular analysis and the application of multi‐factorial experiments are required to better explore genetic and epigenetic adjustments to rapid environmental shifts. These considerations revealed the potential for selecting the best phenotypes to promote assisted evolution with fundamental implications on restoration and preservation efforts.
PROTOCOL: Water, sanitation and hygiene for reducing childhood mortality in low‐ and middle‐income countries

Abstract Respiratory tract infections and diarrhoea are the two biggest killers of children in low income contexts. They are closely related to access to, and use of improved water, sanitation and hygiene (WASH). However, there is no high quality systematic review that quantifies the effect of WASH improvements on childhood mortality. Existing systematic reviews of WASH improvements measure effects on morbidity, under the (often implicit) assumption that morbidity is closely correlated with mortality. This is at least partly because the impact evaluations on which they are based are only designed to detect changes in morbidity with statistical precision, whereas mortality is a relatively rare outcome. The proposed review will address this evidence synthesis gap, using the greater statistical power of meta‐analysis to pool findings across studies.
Analytical and clinical comparison between two different chemiluminescent enzyme immunoassays for the measurement of C-peptide in serum

BACKGROUND: Connecting peptide (C-peptide) is the cleavage product of proinsulin and is released in blood in equimolar amounts to insulin. Compared to the latter, C-peptide has a longer plasma half-life and is less affected by haemolysis, therefore could be a useful marker of insulin production. We aimed to compare the analytical performance of two different chemiluminescent enzyme immunoassays (CLEIA) for the measurement of C-peptide in serum. METHODS: Overall, 106 subjects (median age: 51 [20 – 75]; M/F: 72/34) with available serum samples were included in the study; 14 (13.2%) had a diagnosis of impaired fasting glucose (IFG) and 28 (26.4%) of type 2 diabetes mellitus (T2DM). C-peptide was measured in serum by Elecsys® C-Peptide (Roche, Mannheim, Germany) and by Lumipulse® C-Peptide (Fujirebio, Tokyo, Japan) CLEIAs. RESULTS: Median C-peptide levels measured by Elecsys® and Lumipulse® were comparable in our study cohort (2.6 [0.3 – 13.3] ng/mL vs. 2.54 (0.01 – 10.50) ng/mL, respectively; p = 0.665). No random differences were observed between the two methods; the analytical agreement between both was satisfactory. C-peptide serum values were strongly correlated to insulin concentration (r s = 0.626, p < 0.001, for Elecsys®; r s = 0.719, p < 0.001, for Lumipulse®) and increased in a stepwise manner from patients with normal glucose tolerance to those with IFG and T2DM (p < 0.001). Both CLEIAs showed an area under the curve > 0.7 for the discrimination between patients with and without overt T2DM. CONCLUSIONS