Miracle-dz/UniFAR-FTUs huggingface dataset:
The Importance of Economic Variables on London Real Estate Market: A Random Forest Approach

This paper follows the recent literature on real estate price prediction and proposes to take advantage of machine learning techniques to better explain which variables are more important in describing the real estate market evolution. We apply the random forest algorithm on London real estate data and analyze the local variables that influence the interaction between housing demand, supply and price. The variables choice is based on an urban point of view, where the main force driving the market is the interaction between local factors like population growth, net migration, new buildings and net supply.
Behavior and Fate of Metribuzin in Eight Ontario Soils

The adsorption, desorption, and mobility of metribuzin [4-amino-6-tert-butyl-3-(methylthio)-as-triazine-5(4H)one] in eight Ontario soils were investigated. The distribution coefficients varied from 0.56 for the least adsorptive Fox sandy loam soil to 31.67 for the most highly adsorptive Leamington muck soil. Most of the adsorbed metribuzin was desorbed from the mineral soils after six aqueous extractions, however substantial amounts of the herbicide remained adsorbed on the muck soils after 10 aqueous extractions. The herbicide was relatively mobile in mineral soils but was immobile in the muck soils. Mobility was inversely correlated with the amount of soil organic matter. Bioassay studies indicated that phytotoxicity of metribuzin also decreased with increasing organic matter content of the soil. Persistence of metribuzin was dependent on microbial degradation. In a field study with Guelph loam, the half-life of metribuzin was approximately 3 months.
Thermal and Flow Characteristics in a Concentric Annular Heat Pipe Heat Sink

A concentric annular heat pipe heat sink (AHPHS) was proposed and fabricated to investigate its thermal behavior. The present AHPHS consists of two concentric pipes of different diameters, which create vacuumed annular vapor space. The main advantage of the AHPHS as a heat sink is that it can largely increase the heat transfer area for cooling compared to conventional heat pipes. In the current AHPHS, condensation takes place along the whole annular space from the certain heating area as the evaporator section. Therefore, the whole inner space of the AHPHS except the heating area can be considered the condenser. In the present study, AHPHSs of different diameters were fabricated and studied experimentally. Basic studies were carried out with a 50 mm-long stainless steel AHPHS with diameter ratios of 1.1 and 1.3 and the same inner tube diameter of 76 mm. Several experimental parameters such as volume fractions of 10–70%, different air flow velocity, flow configurations, and 10–50 W heat inputs were investigated to find their effects on the thermal performance of an AHPHS. Experimental results show that a 10% filling ratio was found to be the optimum charged amount in terms of temperature profile with a low heater surface temperature and water as the working fluid. For the methanol, a 40% filling ratio shows better temperature behavior. Internal working behavior shows not only circular motion but also 3-D flow characteristics moving in axial and circular directions simultaneously.
Decoding semantic predictions from EEG prior to word onset

ABSTRACT The outstanding speed of language comprehension necessitates a highly efficient implementation of cognitive-linguistic processes. The domain-general theory of Predictive Coding suggests that our brain solves this problem by continuously forming linguistic predictions about expected upcoming input. The neurophysiological implementation of these predictive linguistic processes, however, is not yet understood. Here, we use EEG (human participants, both sexes) to investigate the existence and nature of online-generated, category-level semantic representations during sentence processing. We conducted two experiments in which some nouns – embedded in a predictive spoken sentence context – were unexpectedly delayed by 1 second. Target nouns were either abstract/concrete (Experiment 1) or animate/inanimate (Experiment 2). We hypothesized that if neural prediction error signals following (temporary) omissions carry specific information about the stimulus, the semantic category of the upcoming target word is encoded in brain activity prior to its presentation. Using time-generalized multivariate pattern analysis, we demonstrate significant decoding of word category from silent periods directly preceding the target word, in both experiments. This provides direct evidence for predictive coding during sentence processing, i.e., that information about a word can be encoded in brain activity before it is perceived. While the same semantic contrast could also be decoded from EEG activity elicited by isolated words (Experiment 1), the identified neural patterns did not generalize to pre-stimulus delay period activity in sentences. Our results not only indicate that the brain processes language predictively, but also demonstrate the nature and sentence-specificity of category-level semantic predictions preactivated during sentence comprehension. STATEMENT OF SIGNIFICANCE The speed of language comprehension necessitates a highly efficient implementation of cognitive-linguistic processes. Predictive processing has been suggested as a solution to this problem, but the underlying neural mechanisms and linguistic content of such predictions are only poorly understood. Inspired by Predictive Coding theory, we investigate whether the meaning of expected, but not-yet heard words can be decoded from brain activity. Using EEG, we can predict if a word is, e.g., abstract (as opposed to concrete), or animate (vs. inanimate), from brain signals preceding the word itself. This strengthens predictive coding theory as a likely candidate for the principled neural mechanisms underlying online processing of language and indicates that predictive processing applies to highly abstract categories like semantics.
Multilayer information spillover networks: measuring interconnectedness of financial institutions

We propose multilayer information spillover networks to measure the interconnectedness of financial institutions by comprehensively considering mean spillover layer, volatility spillover layer and extreme risk spillover layer based on the Granger causality tests in mean, volatility and risk. Using daily returns of 24 Chinese publicly listed financial institutions during 2008–2018, we construct static and dynamic multilayer information spillover networks and analyze different layers' similarity, uniqueness and overlap. Some unique features, which could not be detected in a particular single-layer, are found in multilayer networks. Dynamic topological features of multilayer networks show that significant changes in degrees or unique edges on extreme risk and volatility spillover layers generally occur in the period before a financial stress, e.g. the beginning of the European sovereign debt crisis and ‘the 2015–2016 Chinese stock market turbulence,’ which can provide early warning signals of the financial stress. The systemically important financial institutions change over time, but banks generally have a high interconnectedness.
Convolutional Neural Network based Intelligent Network Intrusion Detection System

Today cyberspace is developing tremendously, and the Intrusion Detection System (IDS) plays a key role in information security. The IDS, which operates at the network and host levels, should be able to identify various malicious attacks. The job of network-based IDSs is to distinguish between normal and malicious traffic data and trigger an alert in the event of an attack. In addition to traditional signature-based and anomaly-based approaches, many researchers have used various deep learning (DL) techniques to detect intruders, as DL models are capable of automatically extracting salient features from the input data packets. The application of the Convolutional Neural Network (CNN), which is often used to solve research problems in the visual and visual fields, is not much explored for IDS. In this research work the proposed model for intrusion detection is based on feature selection and reduction using CNN and classification using random forest. As compared to some existing work the proposed algorithm proves its efficiency in terms of high accuracy and high detection rate.
Indoor optical wireless access networks—recent progress [Invited]

Optical wireless access networks have seen rapid progress. With beam-steering capability, optical wireless communications can deliver very high capacity, support user mobility with indoor localization supported directly at the optical layer, be resilient against the blocking of beams by exploiting spatial diversity at the optical layer, and guarantee low-latency links with modified protocols and network architectures. This paper presents a review of recent progress in achieving functions of communication, localization, resiliency, and dynamic networking using optical-layer techniques.
Ends justify the means! Attitude toward ambush marketing

PurposeThis study explores why consumers view ambush marketing as an ethical marketing approach.Design/methodology/approachA qualitative study was devised to investigate what ambush marketing means to those consumers who find it ethical or are not annoyed by it. Data were collected via focus groups.FindingsThree main themes emerged from the data analyses. The most dominant theme was Machiavellianism. Favorable evaluations of ambush marketing lean on a Machiavellistic understanding. The second was the Robin Hood effect, which is observed when the ambusher is a smaller or local brand. In the third theme, ambush attacks are considered as charismatic or enjoyable action, in what is termed dark charisma.Practical implicationsFindings of the current study suggest considerable implications both for businesses that deal with sponsorship and for organizing committees.Originality/valueThe extant literature on consumers' attitudes toward ambush marketing mostly focuses on ethical issues and/or the effectiveness of ambush marketing (i.e. harm to official sponsors), using qualitative techniques. However, the literature is devoid of studies exploring consumers' perception on ambush marketing, and more specifically, explanations of what is ethical and unethical from consumers' point of view. To best of the author's knowledge, it is the first study that seeks an explanation about consumers' positive evaluation of ambush marketing.
The Longitudinal Profile of a Prograding River and Its Response to Sea Level Rise

River longitudinal profile, a key morphological characteristic of the river channel, is subject to river mouth progradation. Given the increasing influence of human activities and climate change on this critical downstream control, understanding its effects on the evolution of the longitudinal profile is imperative. A general theoretical framework is proposed to quantify the relevant effects, which is tested by numerical experiment and compared with field, numerical and laboratory data from the literature. The results suggest the existence of a critical ratio of accommodation space to sediment supply of approximately 0.5, above which the typical concave upward profile tends to form. Further analyses show that sea level rise tends to increase the concavity of the longitudinal profile of a river with a relatively low equilibrium bed slope and progradation rate.
Influence of Loss of Function of the Fatty Acid Desaturase 7 Gene on Photosynthetic Activity and Foliar Redox Status

Fatty Acid Desaturase7 (FAD7) is a chloroplast-localized enzyme that converts 16 and 18 carbon dienoic fatty acids to trienoic fatty acids. The suppressor of prosystemin-mediated response2 (spr2) mutant in tomato (Solanum lycopersicum) and the fad7-1 mutant in Arabidopsis (Arabidopsis thaliana) result in the loss of function of FAD7, which alter the fatty acid profiles of chloroplast membranes and enhance resistance against aphids. This research contributes toward the long-term goal of identifying factors that determine aphid resistance in FAD7 mutants. Previous data suggested constitutive differences between spr2 and WT including increased expression of genes associated with photosynthesis and differences in redox status in chloroplasts suggested by lipid profiles. The objective of this study was to validate these previous data. This study reports that the spr2 mutant enhances photosynthetic efficiency constitutively compared to wild-type (WT) plants. While no constitutive differences in intermediates and products of photosynthesis were detected, the spr2 mutants showed increased growth, suggesting increased photosynthesis may be translated in to growth. Moreover, glutamate levels were constitutively higher in spr2 compared to WT and could be important in defense signaling for aphid resistance. Also, the spr2 mutants were able to maintain the enhanced photosynthesis under potato aphid (Macrosiphum lycopersicum) pressure. One-day after aphid infestation, aphids triggered a short-term increase in the energy directed towards photosynthesis. The enhanced photosynthesis could also be channeling energy towards defense compound production for the resistance mechanism or could be the plant adapting to adverse environmental stress, indicative of tolerance. Furthermore, to study the redox status in chloroplasts, Arabidopsis fad7-1 lines containing roGFP2 transgene were developed as a useful tool. Preliminary results indicated the fad7-1 mutant is as or more reduced than WT (Col-0), but further studies are needed to confirm this. The redox status depends on the relative balance between reactive oxygen species (ROS) and antioxidants. The plants could potentially have more ROS due to enhanced photosynthesis, but they could also have more antioxidants. Further work is necessary to detect individual ROS species. This study aids in identifying potential links between primary metabolism and plant defenses against insects.
Ongerealiseerde resultaten op transacties met deelnemingen: niet elimineren maar verwerken als minderheidsbelang

Verslaggevingsstelsels schrijven voor dat ongerealiseerde resultaten op transacties met deelnemingen moeten worden geëlimineerd. Dit artikel bespreekt de methodes in drie verslaggevingsstelsels (Titel 9, IFRS en US GAAP) voor de eliminatie van ongerealiseerde resultaten, en de bezwaren die daarbij kunnen worden onderkend. De thans voorgeschreven methodes geven de economische realiteit van dergelijke transacties slechts gefragmenteerd weer. Dit artikel stelt een alternatieve methode voor die tegemoetkomt aan de geïdentificeerde bezwaren, en de economische realiteit beter weergeeft, door ongerealiseerde resultaten niet te elimineren, maar te beschouwen als minderheidsbelang, en mutaties te verwerken via de bestemming van het resultaat.
Estimating uncertainty in deep learning for reporting confidence to clinicians in medical image segmentation and diseases
 detection

Deep learning (DL), which involves powerful black box predictors, has achieved a remarkable performance in medical image analysis, such as segmentation and classification for diagnosis. However, in spite of these successes, these methods focus exclusively on improving the accuracy of point predictions without assessing the quality of their outputs. Knowing how much confidence there is in a prediction is essential for gaining clinicians' trust in the technology. In this article, we propose an uncertainty estimation framework, called MC‐DropWeights, to approximate Bayesian inference in DL by imposing a Bernoulli distribution on the incoming or outgoing weights of the model, including neurones. We demonstrate that by decomposing predictive probabilities into two main types of uncertainty, aleatoric and epistemic, using the Bayesian Residual U‐Net (BRUNet) in image segmentation. Approximation methods in Bayesian DL suffer from the “mode collapse” phenomenon in variational inference. To address this problem, we propose a model which Ensembles of Monte‐Carlo DropWeights by varying the DropWeights rate. In segmentation, we introduce a predictive uncertainty estimator, which takes the mean of the standard deviations of the class probabilities associated with every class. However, in classification, we need an alternative approach since the predictive probabilities from a forward pass through the model does not capture uncertainty. The entropy of the predictive distribution is a measure of uncertainty, but its exponential depends on sample size. The plug‐in estimate in mutual information is subject to sampling bias. We propose Jackknife resampling, to correct for sample bias, which improves estimating uncertainty quality in image classification. We demonstrate that our deep ensemble MC‐DropWeights method, using the bias‐corrected estimator produces an equally good or better result in both quantified uncertainty estimation and quality of uncertainty estimates than approximate Bayesian neural networks in practice.
Variations of Stable Isotopic Composition in Atmospheric Water Vapor and their Controlling Factors—A 6‐Year Continuous Sampling Study in Nanjing, Eastern China

Long‐term continuous monitoring of water vapor isotopes has great potential to improve our understanding of mechanisms that control stable isotope variations in hydrological processes, which is essential for accurate interpretation of isotopic proxy records. Here we presented a 6‐year daily data set of stable isotopes in atmospheric water vapor (δ18Ov, δDv, and d‐excessv) and precipitation (δ18Op, δDp, and d‐excessp) at Nanjing in Eastern China, an area under the influence of the East Asian Monsoon. Based on isotopic variations, we divided a year into three seasons, that is, summer monsoon season (June–September), spring (March–May), and fall‐winter (October–February). During summer monsoon season, the low δ18Ov values were mainly caused by the upstream convective rainout process during the large‐scale water vapor transport, and the d‐excessv values were the lowest due to the weak kinetic isotopic fractionation over its oceanic moisture source. Spring had the highest δ18Ov values, which was related to less distillation of local moisture under relatively high air temperatures. The relatively high d‐excessv values resulted from the kinetic isotopic fractionation due to drier condition. The fall‐winter season has the lowest δ18Ov values because the local distillation was the strongest with low air temperature. The d‐excessv values were highest during this season because of the strongest kinetic isotopic fractionation during the continental moisture recycling under dry climate condition. Using the isotopic composition of both precipitation and water vapor, we found that the annual mean subcloud raindrop evaporation is ~11% of precipitation. These findings improve our understanding of hydrological cycle on the East Asian Monsoon region and will potentially improve our interpretation of numerous isotopic proxy records from this region.
‘The World for Which we Account’: Systems Thinking in Rob Gray’s Works

ABSTRACT One aspect of Rob Gray’s immense intellectual legacy that deserves particular attention is how he first connected accounting and ecology in a meaningful way, drawing on systems thinking. In celebrating his contribution, I sketch in this piece a few notes linking the founding The Greening of Accountancy. The Profession After Pearce (Gray, 1990) with two papers published in the turn of the century that revolve around the fundamental issues and his critique of triple bottom line reporting.
Feasibility of Wireless Horse Monitoring Using a Kinetic Energy Harvester Model

To detect behavioral anomalies (disease/injuries), 24 h monitoring of horses each day is increasingly important. To this end, recent advances in machine learning have used accelerometer data to improve the efficiency of practice sessions and for early detection of health problems. However, current devices are limited in operational lifetime due to the need to manually replace batteries. To remedy this, we investigated the possibilities to power the wireless radio with a vibrational piezoelectric energy harvester at the leg (or in the hoof) of the horse, allowing perpetual monitoring devices. This paper reports the average power that can be delivered to the node by energy harvesting for four different natural gaits of the horse: stand, walking, trot and canter, based on an existing model for a velocity-damped resonant generator (VDRG). To this end, 33 accelerometer datasets were collected over 4.5 h from six horses during different activities. Based on these measurements, a vibrational energy harvester model was calculated that can provide up to 64.04 μW during the energetic canter gait, taking an energy conversion rate of 60% into account. Most energy is provided during canter in the forward direction of the horse. The downwards direction is less suitable for power harvesting. Additionally, different wireless technologies are considered to realize perpetual wireless data sensing. During horse training sessions, BLE allows continues data transmissions (one packet every 0.04 s during canter), whereas IEEE 802.15. 4 and UWB technologies are better suited for continuous horse monitoring during less energetic states due to their lower sleep current.
The Influence of Mimicry on Wing Shape Evolution in the Butterfly Papilio dardanus (Lepidoptera: Papilionidae)

Abstract Throughout its range in Africa, Papilio dardanus Brown, 1776 (Lepidoptera: Papilionidae) displays femalelimited mimicry of multiple model species, and the absence of hind wing tails is an important component of their mimetic convergence. Nonmimetic P. dardanus females have a narrow, disjunct distribution (Ethiopia, Madagascar, Comoros), and resemble males in color and by possessing hind wing tails. We used elliptical Fourier analysis to investigate whether mimetic P. dardanus female forms converged on the wing shape of their unpalatable models in the tribes Acraeini and Danaini (Lepidoptera: Nymphalidae). Models varied in forewing and hind wing shapes, and separated in shape space according to phylogenetic affinities. Forewing and hind wing shapes of mimics did not closely match those of models. Nonetheless, we found that mimetic P. dardanus female hind wings differed from conspecific males that had their tails photographically removed to allow standardized comparisons. Four nonmimetic Papilio Linnaeus, 1758 (Lepidoptera: Papilionidae) species did not show significant wing shape dimorphism between sexes, supporting the idea that in P. dardanus females, the evolution of mimicry led to changes in hind wing shape beyond the loss of tails.
The first species of Actiniaria, Spongiactis japonica gen.n., sp.n. (Cnidaria: Anthozoa), an obligate symbiont of a glass sponge

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