Miracle-dz/UniFAR-FTUs huggingface dataset:
Using photographs and metadata to estimate house prices in South Korea

PurposeMost prior attempts at real estate valuation have focused on the use of metadata such as size and property age, neglecting the fact that the building workmanship in the construction of a house is also a key factor for the estimation of house prices. Building workmanship, such as exterior walls and floor tiling correspond to the visual attributes of a house, and it is difficult to capture and evaluate such attributes efficiently through classical models like regression analysis. Deep learning approach is taken in the valuation process to utilize this visual information.Design/methodology/approachThe authors propose a two-input neural network comprising a multilayer perceptron and a convolutional neural network that can utilize both metadata and the visual information from images of the front view of the house.FindingsThe authors applied the two-input neural network to Guri City in Gyeonggi Province, South Korea, as a case study and found that the accuracy of house price estimations can be improved by employing image information along with metadata.Originality/valueFew studies considered the impact of the building workmanship in the valuation process. The authors revealed that it is useful to use both photographs and metadata for enhancing the accuracy of house price estimation.
Terahertz pulse emission from photoexcited bulk crystals of transition metal dichalcogenides

Multilayer MoS2, MoSe2, and WSe2 crystals were excited with femtosecond optical pulses of various wavelengths. The emitted terahertz (THz) radiation pulses were found to be the most intense at photon energies coinciding with the direct energy gap at the K points of the Brillouin zone of corresponding materials. It was shown that the transition metal dichalcogenides of different dopant type emit THz pulses of opposite polarity, suggesting that the surface field plays a role in THz emission. Nevertheless, the optical pump–THz probe experiments contradicted THz emission observations, demonstrating a decrease in photoconductivity at higher energy quanta. The proposed THz pulse generation mechanism, therefore, assumes the accumulation of excitonic electric dipoles during optical pulse absorption and a fast build-up of the internal electric field inside the samples. This assumption was supported by double optical pulse investigations.
Characterisation of African biomass burning plumes and impacts on the atmospheric composition over the south-west Indian Ocean

Abstract. We present an investigation of biomass burning (BB) plumes originating from Africa and Madagascar based on measurements of a suite of volatile organic compounds (VOCs), carbon monoxide (CO), ozone (O3) and nitrogen dioxide (NO2) obtained during the dry season of 2018 and 2019 at the high-altitude Maïdo observatory (21.1∘ S, 55.4∘ E, 2160 ma.s.l.), located on the remote island of La Réunion in the south-west Indian Ocean (SWIO). Biomass burning plume episodes were identified from increased acetonitrile (CH3CN) mixing ratios. Enhancement ratios (EnRs) – relative to CO – were calculated from in situ measurements for CH3CN, acetone (CH3COCH3), formic acid (HCOOH), acetic acid (CH3COOH), benzene (C6H6), methanol (CH3OH) and O3. We compared the EnRs to emission ratios (ERs) – relative to CO – reported in the literature in order to estimate loss or production of these compounds during transport. For CH3CN and CH3COOH, the calculated EnRs are similar to the ERs. For C6H6 and CH3OH, the EnR is lower than the ER, indicating a net sink of these compounds which was found to be in line with the expected atmospheric lifetime. For CH3COCH3 and HCOOH, the calculated EnRs are larger than the ERs. The discrepancy reaches an order of magnitude for HCOOH (18–34 pptv ppbv−1 compared to 1.8–4.5 pptv ppbv−1). This points to significant secondary production of HCOOH during transport. The Copernicus Atmospheric Monitoring Service (CAMS) global model simulations reproduce the temporal variation of CO mixing ratios well at the observatory but underestimate O3 and NO2 mixing ratios in the plumes by on average 16 ppbv and 60 pptv respectively. This discrepancy between modelled and measured O3 mixing ratios was attributed to (i) large uncertainties in VOC and NOx (NO+NO2) emissions due to BB in CAMS and (ii) misrepresentation of NOx recycling in the model during transport. Finally, transport of pyrogenically emitted CO is calculated with FLEXPART in order to (i) determine the mean plume age during the intrusions at the observatory and (ii) estimate the impact of BB on the pristine marine boundary layer (MBL). By multiplying the excess CO in the MBL with inferred EnRs at the observatory, we calculated the expected impact of BB on CH3CN, CH3COCH3, CH3OH and C6H6 concentrations in the MBL. These excesses constitute increases of ∼20 %–150 % compared to background measurements in the SWIO MBL reported in the literature.
Ethical dilemmas: balancing choice and risk with a duty of care in extending personalisation into the care home

Abstract The article reports the perspectives of senior care staff as part of a study exploring personalisation in care homes. Behind the conceptual sword and shield of ‘choice and control’ associated with personalisation in the United Kingdom (UK) lie irreconcilable flaws, thrown into sharp relief in this context. Personalisation, which originated in community-based social services, has recently been extended into UK care homes. This service development has been stimulated by a desire to promote a humane response to caring for an ageing population, whilst containing costs. Seemingly promoting a relational approach, personalisation also entails consumerist underpinnings, with consequent tensions resulting in weakened policy mechanisms. Discussing findings pertaining to ‘food and eating’, the article illustrates the complex interplay between supporting resident capabilities with poor staff ratios; when choice is not really choice at all; balancing choice, risk and the duty of care; and responding to diverse perspectives about what matters. This complexity reflects the highly skilled nature of care work as promoted by care ethicists. The tensions permeated care home life and found parallels in the wider system of care. Honesty about the limitations of choice and control is essential to achieve ethical care in care homes. The care home constitutes fertile ground for exposing and exploring the shortcomings of the ‘logic of choice’ and for advancing a more relational, inclusive and sustainable conceptualisation of personalisation.
Channel Mismatch Speaker Verification Based on Deep Learning and PLDA

At present, speaker recognition technology is developing continuously, but in real world, existing speaker recognition algorithms are generally disturbed by channel factors. With the increase of current data volume, neural network has also become a key technology for speaker recognition. This paper introduction a speaker recognition method based on supervised training and a channel compensation algorithm. The experimental results show that this method combined with channel compensation algorithm can remove the influence of channel noise and has a good speaker recognition effect. The experimental results show that the combination of x-vector and PLDA channel compensation algorithm can obtain better recognition rate and ensure the robustness of the algorithm.
A clustering method for graphical handwriting components and statistical writership analysis

Handwritten documents can be characterized by their content or by the shape of the written characters. We focus on the problem of comparing a person's handwriting to a document of unknown provenance using the shape of the writing, as is done in forensic applications. To do so, we first propose a method for processing scanned handwritten documents to decompose the writing into small graphical structures, often corresponding to letters. We then introduce a measure of distance between two such structures that is inspired by the graph edit distance, and a measure of center for a collection of the graphs. These measurements are the basis for an outlier tolerant K‐means algorithm to cluster the graphs based on structural attributes, thus creating a template for sorting new documents. Finally, we present a Bayesian hierarchical model to capture the propensity of a writer for producing graphs that are assigned to certain clusters. We illustrate the methods using documents from the Computer Vision Lab dataset. We show results of the identification task under the cluster assignments and compare to the same modeling, but with a less flexible grouping method that is not tolerant of incidental strokes or outliers.
Evaluation of Cyber Deception Using Deep Learning Algorithms

A machine learning-based approach is proposed and actualized to measure cyber deceptive defenses with negligible human inclusion. This dodges obstructions related to deceptive examination on humans, amplifying robotized assessment's adequacy before human subject’s research must be attempted. Utilizing ongoing advances in profound learning, the methodology synthesizes realistic, interactive, and adaptive traffic for utilization by target web services. A contextual analysis applies how to assess an interruption identification framework furnished with application layer embedded deceptive reactions to attacks. Results exhibit that blending adaptive web traffic bound with hesitant attacks controlled by outfit learning, online adaptive metric learning, and novel class discovery to recreate able enemies comprises a forceful and challenging test of cyber deceptive defenses.
Forest Transformation Urgency for Topsoil Diversity Optimization During Environmental Change

Abstract Combined effect of environmental change and management variability leads to reduced soil diversity in homogenous forest stands. On the other hand, forest soil diversity is maintained with rich tree species composition. In this study, focus has been put on deriving urgency to change forest tree species composition in order to increase soil diversity in biogeographic regions with uneven impact of environmental change. The relation of forest tree species and soil diversities was compared between the periods of dominant sulphur deposition (1985–1994) and the period of regional environmental change (2003–2012) in the Czech Republic (Central Europe; 78 866 km2; 115–1602 m n.m.). Forest tree species and soil diversities were assessed using linear regression, discrimination analysis and geographically weighted regression including residue analysis. The effect of spatial differences of acid deposition on soil properties, though, decreased, still dependencies between the diversity of bedrock, soils and forest tree species increased significantly. Only 12.9 % of forests in the territory of the CR have optimum tree species diversity. The total of 65.9 % of forest require highly or moderately urgent transformation. An increase in spatial dependencies between soil and tree species diversities confirms the importance of site differentiation in forest transformation.
Strength and Ductility Improvement through Thermomechanical Treatment of Wire-Feed Electron Beam Additive Manufactured Low Stacking Fault Energy (SFE) Aluminum Bronze

An as-cast macrostructure of electron beam additively manufactured metallic materials was represented by coarse columnar grains whose axes were inclined at 25° with respect to the substrate’s plane. One part of the as-grown samples was annealed to form a coarse grain microstructure while the other part was pre-deformed by forging and then annealed what allowed obtaining recrystallized microstructures with small grains and multiple annealing twin boundaries. This sample showed both high strength and plasticity during the tensile tests. These tensile tests demonstrated also two-stage stress-strain curves as depended on their strain hardening rates. High and low strain hardening rates corresponded to a twinning-dominated deformation at stage II and dislocation-base deformation at stage III. A submicron size strain-induced grain-subgrain microstructure was formed in the vicinity of a necked zone as a result of combined twinning/dislocation grain refining.
Corporate Sustainability Practices in Tourism—Evidence from Tanzania

ABSTRACT The purpose of this study is to explore the corporate sustainability practices undertaken in the tourism sector, drawing on evidence from Tanzania. The study extracted corporate sustainability-related information reported on the websites of tour operators and accommodation firms operating in Tanzania and conducted thematic analysis on the extracted information. The findings revealed that social services, economic prosperity, nature conservation and eco-efficiency are the main corporate sustainability practices. The tour operators generally put great emphasis on social service initiatives, which were operationalized through philanthropic contributions to community projects. Accommodation firms specifically emphasized eco-efficiency, nature conservation and economic prosperity. Although the conception of corporate sustainability of all the tourism firms seems to be the same, their practices were differentiated by differences in their nature of operations and resource capabilities. The findings imply that corporate sustainability practices are socially constructed and provide grounds to inform destination planning, development and management.
Relationship of Serum Concentrations of Calcium, Beta-hydroxybutyrate and Glucose to the Occurrence of Mammary and Uterine Disorders during Early Lactation on Dairy Cattle

This study aimed to relate the serum levels of energy indicators (glucose and beta-hydroxybutyrate) and calcium to the occurrence of uterine and mammary diseases in the transition period of Holstein cows. One hundred and fifteen Holstein cows from a commercial herd were monitored starting one week before calving and during the first 2 weeks after calving. The presence of subclinical mastitis was monitored for 3 weeks postpartum using the California Mastitis Test (CMT) and somatic cell counting. Positive samples of subclinical mastitis were analyzed for bacterial identification. Clinical mastitis was monitored for 6 weeks postpartum, using data that were recorded by the farmer based on some established definitions. The presence of uterine disorders was identified for 3 weeks postpartum by clinical examination. Blood collections were made from all cows for determining calcium, glucose, and β-hydroxy-butyrate (BHB) the week before calving and twice during the postpartum (days 5 and 15 postpartum). A group of 70 healthy cows was used as control. Clinical mastitis was identified in 20% of the cows, subclinical mastitis in 10.4% and clinical metritis in 8.7% of the cows. The bacterial agents with the highest occurrence in subclinical mastitis cases were coagulase-negative Staphylococcus and Streptococcus. No relationships were observed between any of the biochemical metabolite studied and the uterine and mammary diseases in the cows during the studied period
Research on classification of spiral galaxies and stars based on convolutional neural network

In astronomy, the shape of galaxies can often reflect the course of its evolution, and can further reveal the development law of the universe. With the progress and development of observation technology, image data has grown explosively, and the efficiency of traditional manual astronomical image classification is far from enough. Image classification based on machine learning effectively solves the problem of low efficiency of artificial classification, but in the face of massive data sets, the classification effect of traditional machine learning is often not as good as deep learning. In this paper, relevant concepts based on neural network image classification algorithm are introduced. Then, according to the characteristics of the mainstream CNN (convolutional neural network) model, the design and optimization of the custom RS CNN model are completed. Finally, the custom RS CNN is used to conduct classification experiments on spiral galaxies and stars.
Poaceae Orthologs of Rice OsSGL, DUF1645 Domain-Containing Genes, Positively Regulate Drought Tolerance, Grain Length and Weight in Rice

BackgroundGrain yield is a polygenic trait influenced by environmental and genetic interactions at all growth stages of the cereal plant. However, the molecular mechanisms responsible for coordinating the trade-off or cross-talk between these traits remain elusive.ResultsWe characterized the hitherto unknown function of four STRESS_tolerance and GRAIN_LENGTH (OsSGL) Poaceae ortholog genes, all encoding DUF1645 domain-containing proteins, in simultaneous regulation of grain length, grain weight, and drought stress-tolerance in rice. In normal growth conditions, the four ortholog genes were mainly expressed in the developing roots and panicles of the corresponding species. Over-expressing or heterologous high-level expressing Poaceae OsSGL ortholog genes conferred remarkably increased grain length, weight, and seed setting percentage, as well as significantly improved drought-stress tolerance in transgenic rice. Microscopical analysis also showed that the transgene expression promoted cell division and development. RNA-seq and qRT-PCR analyses revealed 73.8% (18,711) overlapped DEGs in all transgenic plants. Moreover, GO and KEGG analyses of different comparisons revealed that the key DEGs participating in drought stress-response belonged to hormone (especially auxin and cytokinin) pathways, and signaling processes were apparently affected in the young panicles. ConclusionTogether, these results suggest the four OsSGL orthologs perform a conserved function in regulating stress-tolerance and cell growth by acting via a hormone biosynthesis and signaling pathway. It may also induce a strategy for tailor-made crop yield improvement.
Regulatory Effects of Nur77 on Airway Remodeling and ASMC Proliferation in House Dust Mite-Induced Asthma

Airway remodeling played a vital role in the development of asthma, and airway smooth muscle (ASM) mass was its hallmark. However, few strategies targeting ASM remodeling were developed in treating asthma. Nur77 was the transcription factor nuclear receptor involved in the pathogenesis of several lung diseases. Nur77 distribution and expression were determined in an HDM-mediated allergic asthma model. Its effect on airway hyperresponsiveness (AHR), chronic inflammation, and ASM remodeling in asthmatic mice was evaluated using a lentivirus-mediated shRNA. Possible mechanisms were explored by examining Nur77 actions and its underlying pathways in primary human AMC cells (ASMCs). In this study, we reported that Nur77 expression was mainly distributed along ASM and increased in lungs of HDM-challenged mice. Nur77 depletion by lentivirus-mediated shRNA ameliorated AHR, chronic inflammation, goblet cell hyperplasia, and airway remodeling in the asthmatic mouse model. By means of primary human ASMC, we discovered that Nur77 upregulation by HDM stimulation promoted cell proliferation and ROS production, as well as reduced antioxidant gene expression. These alterations might associate with MFN2/MAPK/AKT pathways. These findings broadened our understanding of airway remodeling and ASMC proliferation, which might provide a novel therapeutic target for asthma patients.
Nutzung von Stickern in Messenger-Diensten und ihre Jugendschutzrelevanz

Sticker-Paketen zum Download zur Verfügung. Nach Bedarf können weitere (themenspezifische) Pakete online heruntergeladen werden und die Sticker, die man von anderen Nutzer*innen erhalten hat, in der eigenen Stickersammlung gespeichert werden. Zudem besteht die Möglichkeit, Sticker ohne großen Aufwand oder Vorkenntnisse mit Hilfe spezieller Apps selbst zu erstellen, diese anschließend weiterzuverbreiten und anderen Nutzer*innen zur Verfügung zu stellen. Dabei haben die Produzent*innen einen großen Gestaltungsspielraum. Denn nicht nur aus Bildern und Fotos lassen sich Sticker kreieren. Die im Juli 2020 eingeführte Animations-Funktion ermöglicht es auch, kurze Videosequenzen zu verwenden, die im Chat – ähnlich einer GIF-Animation – in Endlosschleife abgespielt werden. Darüber hinaus können Sticker zusätzlich mit Text und dementsprechend mit einer expliziten Botschaft versehen werden, wodurch sie sich optisch an sogenannte Memes anlehnen oder diese nachbilden.
Feature Extraction Method of Radiation Source in Deep Learning Based on Square Integral Bispectrum

The feature extraction method of radiation source based on deep learning is a hotspot of specific emitter identification research. In the selection of the initial radiation source data for feature extraction, there are mainly two kinds of time series IQ data and frequency domain bispectral data. Both the IQ signal and the signal bispectrum contain the information that can characterize the fingerprint of the radiation source, and the deep learning methods mostly use different deep network structures to obtain better classification performance. This paper proposes a feature extraction method of radiation source based on bispectral data, and designs a deep network structure combining convolution and long short memory network, which has a better classification and recognition rate than a single convolution network and a single LSTM network.
REVIEW OF TRANSMUTATION REACTIONS IN SOLIDS

Transmutation reactions in highly loaded hydrides have been reported by a number of research groups. These studies are briefly summarized with emphasis on common systematics and key “signatures”. Transmutations divide into two types: heavy intermediate compound nucleus reactions yielding an array of products with a large spectrum of masses; direct reactions between H/D and the electrode metal or impurity atoms yielding isolated “single” products. Various mechanisms have been proposed to explain the products and the ability to overcome the extremely large Columbic repulsion of the high-Z elements involved. Here we briefly consider a model involving orbital mixing and virtual neutron formation associated with charge accumulation and hydrogen/deuteron flow at highly loaded interfaces.
Evolution of calcium phosphate precipitation in hanging drop vapor diffusion by in situ Raman microspectroscopy

The time-evolution of calcium phosphate precipitation by vapor diffusion has been studied by in situ confocal Raman microspectroscopy. A hanging drop configuration within a device known as “crystallization mushroom” was employed in order to improve the Raman signal coming from growing crystals. This innovative methodology allowed to identify and follow the evolution of the precipitates formed at different areas of the drops containing mixed solutions of Ca(CH3COO)2 and (NH4)2HPO4 due to the diffusion of CO2 and NH3 gases released from NH4HCO3 solutions at different concentrations (30 mM, 100 mM and 2 M). Time-dependent in situ Raman spectra indicated that amorphous calcium phosphate (ACP) was the first precipitate appearing just after mixing the Ca- and PO4-containing solutions. A few minutes later, it transformed to dicalcium phosphate dihydrate (DCPD). The lifetime of DCPD strongly depends on the concentration of the NH4HCO3 solutions and thus on the pH increase rate. The pathway for the phase transformation from ACP to DCPD and then to octacalcium phosphate (OCP) followed a dissolution–reprecipitation mechanism. Additionally, OCP acted as temporal template for the heterogeneous nucleation and crystallization of biomimetic carbonate–apatite nanocrystals (cAp). The characterization by TEM, XRPD and Raman spectroscopy of the freeze-dried powders obtained after seven days confirmed that OCP and cAp were the remaining phases when using 30 mM and 100 mM NH4HCO3 solutions. By contrast, working with the highest NH4HCO3 concentration the system evolved to the precipitation of elongated calcite crystals.