Browse Articles

Photophoretic flight of perforated structures in near-space conditions

The role of loneliness, work meaning and organizational support in compassion satisfaction among primary care professionals during the pandemic

Bending the curve of land degradation to achieve global environmental goals

Feature selection for specific prediction targets at the user level in a district heating network

Abstract With the challenge of district heating network transition as part of the global objective of clean energy, machine learning provides a methodological approach for understanding the relationships between various influencing factors and demand-side properties of district heating networks, which is decisive for reducing losses, enhancing sustainability, and guaranteeing residential comfort. This work focuses on accelerating the application of modern machine learning methods to modeling district heating networks by generating knowledge on feature engineering and selection for newly suggested prediction targets, namely volume flow, supply, and return temperatures, directly at the building level. A systematic workflow for data acquisition, feature engineering, and selecting the most relevant predictors is presented. For this, statistical and machine learning methods are applied to engineer respective features and establish specific interdependencies, including meteorological conditions, human behavioral patterns, and operational parameters, based on a model region in northern Germany. The qualitative results indicate that the highest impact is for temporal predictors and operational features derived from the infeed facility’s data, i.e., approximately 15 to 20% of the total predictor relevance. In comparison to studies targeting the heat load and suggesting outside air temperature as the most relevant predictor, it was found that for the herein proposed prediction targets, this feature is of secondary relevance (roughly 6–10%). The findings of this study provide a feature engineering and selection strategy, as well as relevant knowledge gain, which is a prerequisite for efficient modeling of district heating networks based on machine learning in the future.

Analysis of the size effect in the nanoscratching process of single crystalline and polycrystalline materials

A forewarning model for the reverse supply chain of urban End-of-Life power batteries based on a mix method of BWM and RBFNN

Role of ethanol to water ratio in hydrogen production by ethanol steam reforming in atmospheric pressure 915 MHz microwave plasma

Thermophotoinduced electron emission from conductive composite based on polytetrafluoroethylene with carbon nanotubes

Abstract This work explores the potential of conductive polymer–carbon nanocomposites, specifically polytetrafluoroethylene with multi-walled carbon nanotubes (PTFE–CNTs), as efficient electron emitters for emission electronics, low-temperature thermionic energy conversion (TEC), sensors, elements of information storage devices, and materials with targeted control of electromagnetic waves’ absorption/reflection. Our main scientific contribution is the demonstration of electron emission from investigated composite PTFE + 10 wt% CNTs at significantly reduced operating temperatures (near 200 °C), much lower than those for pure CNTs and conventional materials for emission electronics and energy. The research combines experimental studies of electron emission under concentrated solar and pulsed laser radiation, structural characterization of samples by electron microscopy, and positron spectroscopy. The last method and contact potential difference method are used to investigate the electronic properties, including charge transfer between composite components, and the work function of the material. Results indicate that electrons can be emitted from both the surface and subsurface (through the polymer layer) of CNTs. The emission current can be enhanced by the Schottky effect due to the electrical fields of adsorbed cations. Additionally, a novel method for tuning the composite’s work function due to irradiation by low-energy electrons is proposed. It opens pathways for targeted control not only of emission performance but other electronic properties of polymer–carbon nanocomposites, including absorption and reflection of electromagnetic waves in a wide frequency range.

Unveiling the therapeutic potential of octreotide in treating morphine dependence

Open vocabulary detection for concealed object detection in AMMW image

PPP2R1A mutations portend improved survival after cancer immunotherapy

A novel approach in diagnosing knee osteoarthritis for content based image retrieval in big data analytics and medical images

Impact of catastrophic flood might have been exacerbated by river-management programme

Visualisation and quantification of the effects of surgical humidification on intestinal perfusion and viability in a porcine model

Atomic Off-Centering Driven Phonon-Glass Electron-Crystal-like Thermoelectric Transport in Entropy-Stabilized Quinary Telluride

Early evidence for capacity standardisation in Western Europe. The vessels from Mailhac (Aude, France) 9th-7th centuries BC

This paper presents an original study of the metrological characteristics of a series of vessels discovered in the necropolis of Le Moulin (Mailhac, southern France) and dated to the Late Bronze Age and the beginning of the Early Iron Age. A metrological study of the capacities of these artefacts is presented, based on a protocol of 3D modelling from 2D drawings to calculate the internal volumes of the vessels, and a series of mathematical and statistical analyses. The results make it possible to identify one of the earliest evidence for metrological practices based on capacity in Western Europe.

Binuclear Metal-Based Covalent Organic Framework Mimicking Metallohydrolases for Direct Photoreforming of PET Plastic

Drone-based application of whale tags: A “tap-and-go” approach for scientific animal-borne investigations

Deploying animal-borne suction-based tag devices on whales has been one of the primary tools used by researchers over the past several decades to gather high-resolution scientific information, such as bioacoustics, heart rate, dive depth, and body orientation. However, the process of successfully applying animal-borne tags is logistically challenging and requires substantial operator skill. Current methods apply tags by approaching the whale in a boat and adhering the tag via a long extension pole. In this study, we explore an alternative approach to apply animal-borne suction-based tag devices using First Person View (FPV) racing drones. These drones have been specifically adapted to withstand exposure to seawater, allowing them to operate effectively in marine environments. The drones are equipped with a custom interface, allowing to release the tag when it is applied on the whale’s back. In this study, we present the development of the delivery drone as well as tag deployment techniques. The proposed method was demonstrated on sperm whales (Physeter macrocephalus) off Dominica, resulting in fast deployment time (one minute and fifteen seconds on average) and a relatively high deployment success rate (over 55 %). In addition, the presented deployment process offers a less invasive technique for tagging, as boats are not needed for close approaches. These methods also serve as a framework to enable future development of more automated solutions to apply the tag on exact anatomical targets with controlled initial adhesion pressure and without manual operation.

Associations between neighborhood social capital, oral health risk factors, and tooth decay among Medicaid-enrolled adolescents: A hypothesis-generating preliminary study

Neighborhood-based social capital – defined as resources within neighborhood social networks – is a potential contributor to adolescent oral health, but mechanisms that link the two are not well elucidated. We evaluated the potential mediating role of neighborhood, household, and individual oral health risk factors in the neighborhood social capital-tooth decay relationship. We collected cross-sectional data from 331 Medicaid-enrolled adolescents (ages 12–18 years) and one of their caregivers from 73 census tracts (neighborhoods) in three counties in Oregon, U.S.A in 2015 and 2016. Medicaid is a public insurance program in the U.S. providing no-cost dental insurance to low-income children. We measured four neighborhood social capital constructs: social support, social leverage, informal social control, and neighborhood organization participation. Oral health risk factors included worrying about food money, poor access to vegetables and fruits, inconsistent family and oral health routines, and adolescent stress. The outcome was number of untreated decayed tooth surfaces. Causal mediation analyses with mixed effect models were used to examine associations. Neighborhoods with higher social support had a lower prevalence of worrying about food money (prevalence ratio [PR] 0.74;95% CI: 0.56, 0.96;p = .02) as did neighborhoods with higher informal social control (PR 0.75;95% CI:0.58, 0.97;p = .03). All oral health risk factors were strongly associated with untreated decayed tooth surfaces. No form of neighborhood social capital was significantly associated with tooth decay. Natural indirect effects of neighborhood social support and informal social control operating through worrying about food money were not statistically significant. Future longitudinal studies that include robust measures of neighborhood social capital and adequate sample sizes are needed to enable neighborhood-based interventions that promote adolescent oral health.

The impact of free trade port construction on regional import and export: Evidence from Hainan

The construction of the Hainan Free Trade Port (HFTP) represents one of the most advanced regional development models explored by China. This study clarifies the concept of the free trade port and analyzes it from a trade perspective. Our empirical results show that the construction of the free trade port has significantly increased trade volumes, enhanced the diversification of products, and reduced the volatility of exports. A marked short-term surge in export volumes was observed immediately after the policy’s implementation. Moreover, the effects of the free trade port’s construction on trade are heterogeneous when viewed through the lens of product categorization.