Miracle-dz/UniFAR-FTUs huggingface dataset:
Criteria for a transparent assessment of carbon footprints in the food supply chain

Our daily consumption patterns have a major influence on climate change. Several European initiatives use CO2-labels for products to provide guidance for climate friendly consumption decisions. Different methodological details affect the total amount of greenhouse gas emissions (CO2-e) being labeled. A standardized method is needed to generate comparable results. The objective of this study conducted at the Institute for Marketing and Innovation of the University of Natural Resources and Life Sciences, Vienna, was to identify the key methodological criteria for transparent assessment of the carbon footprint of food products. Expert interviews and content analyses were the methodological approach applied. Current carbon footprint standardization processes have to meet the challenge of meeting both scientific accuracy and practicability in order to enable comprehensive implementation in management practice.
Salvando las dificultades del uso de la encuesta en la investigación contable de gestión: Una aplicación empírica

RESUMEN El método de la encuesta ha perdido relevancia en la investigación contable de gestión en los últimos años, criticándose que los datos que recoge contienen demasiados errores de medidas que hacen que el método sea poco fiable y de una validez muy baja [Young, 1996]. Este trabajo va más allá de las recomendaciones generales de cómo llevar a cabo una encuesta, enfatizando la importancia de un buen diseño de la misma para recoger datos de calidad y salvar las diferentes dificultades asociadas a este método. Se describe a través de un estudio empírico el desarrollo del cuestionario y la evaluación psicométrica de las variables, aspectos que suelen estar desatendidos en las investigaciones contables de gestión. El alto índice de respuestas útiles conseguido en el trabajo que se presenta como caso empírico es un aliciente para seguir confiando en el método de la encuesta en futuras investigaciones contables de gestión.
Artificial Intelligence and Behavioral Economics: A Bibliographic Analysis of Research Field

Behavioral economics and artificial intelligence (AI) have been two rapidly growing fields of research over the past few years. While behavioral economics aims to combine concepts from psychology, sociology, and neuroscience with classical economic thoughts to understand human decision-making processes in the complex economic environment, AI on the other hand, focuses on creating intelligent machines that can mimic human cognitive abilities such as learning, problem-solving, decision-making, and language understanding. The intersection of these two fields has led to thrilling research theories and practical applications. This study provides a bibliometric analysis of the literature on AI and behavioral economics to gain insight into research trends in this field. We conducted this bibliometric analysis using the Web of Science database on articles published between 2012 and 2022 that were related to AI and behavioral economics. VOSviewer and Bibliometrix R package were utilized to identify influential authors, journals, institutions, and countries in the field. Network analysis was also performed to identify the main research themes and their interrelationships. The analysis revealed that the number of publications on AI and behavioral economics has been increasing steadily over the past decade. We found that most studies focused on customer and consumer behavior, including topics such as decision-making under uncertainty, neuroeconomics, and behavioral game theory, combined mainly with machine learning and deep learning techniques. We also identified several emerging themes, including the use of AI in nudging and prospect theory in behavioral finance, as well as undeveloped themes such as AI-driven behavioral macroeconomics. The findings suggests that there is a need for more interdisciplinary collaboration between researchers in behavioral economics and AI. We also suggest that future research on AI and behavioral economics further consider the ethical implications of using AI and behavioral insights in decision-making. This study can serve as a valuable resource for researchers interested in AI and behavioral economics.
Generating and Solving Champion-Level Romanian Crosswords Puzzles

The Romanian Crosswords Competition Problem is a challenging, NP-hard constraint optimization problem where state-of-the-art Artificial Intelligence has been lagging behind top human performance. The task is to construct a high-score grid with words from a thematic list, that changes every year, and from a regular list. Each thematic word in the solution gives a number of score points equal to its length. A recent approach to the problem generated grids with scores in the range of top human performance for the first time. However, such scores were obtained for only three years. We present new results with experiments on a larger scale, including an increase from three to eleven years. We produce grids with scores in the top-12 human range in six out of eleven years and discuss steps towards outperforming top humans.
The Application of Grey Clustering Method for Evaluating the Subsiding Water Quality from Cropland in the Irrigation Area of the Yellow River

Based on the pollution problems of the subsiding water from cropland in the irrigation area of the upper reaches Yellow River,the grey clustering method was used to evaluate the water quality of two monitoring sections in Lingwu experimental area of Ningxia province.The results indicated that: the concentration of nitrogen and phosphorus went beyond the standards seriously,meanwhile the subsiding water quality from cropland in the irrigation area were affected by the following factors,such as,breeding pollution,irrigation and overfertilization.So it is the very imperative for us to realize that we must control the pollution from the source,reducing the application of the fertilization,developing the organic fertilizer and bio-fertilizer,readjusting and optimizing the industrial structure,developing the green agriculture and the ecological agriculture etc,so as to alleviate the pollution of the subsiding water from cropland in the irrigation area of the Yellow River.
The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Long Version) Die den Einsatz des bei nicht-hepatischen Anwendungen: Update 2017 (Langversion)

The updated version of the EFSUMB guidelines on the application of non-hepatic contrast-enhanced ultrasound (CEUS) deals with the use of microbubble ultrasound contrast outside the liver in the many established and emerging applications. Die aktualisierte Version der EFSUMB-Leitlinien für die Anwen-dung von nicht-hepatischem kontrastverstärktem Ultraschall (CEUS) befasst mit der Verwendung von Mikrobläschen Ultraschall-Kontrastmitteln außerhalb der in zahl-reichen etablierten und neu entstehenden Einsatzbereichen.
Dealing With Jamming Attacks in Uplink Pairwise NOMA Using Outage Analysis, Smart Relaying, and Redundant Transmissions

This study focuses on optimizing the performance of an uplink pairwise Non-Orthogonal Multiple Access (NOMA) scenario with and without the support of a relayer, while subject to jamming attacks. We consider two different relaying protocols, one where the sources and the destination are within range of each other and one where they are not. The relay node can be mobile, e.g., a mobile base station, an unmanned aerial vehicle (UAV) or a stationary node that is chosen as a result of a relay selection procedure. We also benchmark with a NOMA retransmission protocol and an Orthogonal Multiple Access (OMA) scheme without a relayer. We analyze, adjust and compare the four protocols for different settings using outage analysis, which is an efficient tool for establishing communication reliability for both individual nodes and the overall wireless network. Closed-form expressions of outage probabilities can be adopted by deep reinforcement learning (RL) algorithms to optimize wireless networks online. Accordingly, we first derive closed-form expressions for the individual outage probability (IOP) of each source node link and the relayer link using both pairwise NOMA and OMA. Next, we analyze the IOP for one packet (IOPP) for each source node considering all possible links between the source node to the destination, taking both phases into account for the considered protocols when operating in Nakagami- $m$ fading channels. The overall outage probability for all packets (OOPP) is defined as the maximum IOPP obtained among the source nodes. This metric is useful to optimize the whole wireless network, e.g., to ensure fairness among the source nodes. Then, we propose a method using deep RL where the OOPP is used as a reward function in order to adapt to the dynamic environment associated with jamming attacks. Finally, we discuss valuable guidelines for enhancing the communication reliability of the legitimate system.
Adaptive Method to Increase Vehicle Detection System Robustness on Blurred and Noisy Aerial Images

In this paper, the problem of neural-based detection of vehicles on blurred and noisy images of remote sensing is considered. The aim of this study is to improve the performance of object detection in aerial images exposed to distortions of various nature. This aim is achieved using the proposed technique, which includes optimal training images augmentation and an adaptive input data preprocessing reducing the impact of high-frequency noise. The simulation results, carried out on the publicly available DOTA aerial images dataset, show that the application of optimal robust training and the use of the proposed adaptive system simultaneously allow to obtain a more robust neural-based vehicle detection system for various tasks of remote sensing.
The Effect of a Familiar and Unfamiliar Lecturer on Attention Level and Assimilation of Information in a Video Lecture: Preliminary Experimental Data

The development of modern pedagogical science cannot be imagined today without the use of modern technologies and arrangement of interdisciplinary relationships. An example of such interaction is neuropedagogy which can be considered as a scientific field that combines pedagogy, cognitive sciences and neuroscience, to be used to investigate the interrelation between the physiological processes in the brain and learning. The paper presents the results of a research carried out to investigate the effect of a familiar and unfamiliar lecturer on attention level and information assimilation through a video lecture using the electroencephalogram. The “attention” scale was assessed on the basis of the analysis of beta and theta rhythms ‘ activity. During the pilot experiment, the testees watched two video lectures. One of them was presented by a familiar trusted lecturer whose lectures the learners had already listened to. The second video lecture was delivered by an unfamiliar lecturer whom the learners had never heard before. According to the preliminary study results, both videos showed exactly the same mean value attention of 81.1 %. However, the video lectures assimilation rates differed. The efficiency in case of the familiar lecturer was 72%, and 60% in case of the unfamiliar lecturer. The obtained data require further study and confirmation, extension of the sample and testing of different video topics for more objective assessment. The lecturer's role needs clarification and can help to improve the perception of information.
TECHNOLOGICAL INNOVATION: WINNERS AND LOSERS

We analyze the effect of innovation on asset prices in a tractable, general equilibrium framework with heterogeneous households and firms. Innovation has a heterogenous impact on households and firms. Technological improvements embodied in new capital benefit workers, while displacing existing firms and their shareholders. This displacement process is uneven: newer generations of shareholders benefit at the expense of existing cohorts; and firms well positioned to take advantage of these opportunities benefit at the expense of firms unable to do so. Under standard preference parameters, the risk premium associated with innovation is negative. Our model delivers several stylized facts about asset returns, consumption and labor income. We derive and test new predictions of our framework using a direct measure of innovation. The model's predictions are supported by the data.
License Plate Recognition on Low-Cost Devices

This paper presents a comprehensive approach to vehicle license plate recognition running on low-cost devices. Leveraging convolutional neural networks, we evaluate models like YOLOv7-tiny and YuNet for license plate detection, favoring YuNet's $1080\times 1080$ resolution for the accuracy-computation trade-off. For license plate character recognition, we proposed a YOLOv4-tiny derivation model, achieving good accuracy and fast computation. The proposed approaches were validated on a test set from real traffic using Raspberry Pi 4 as the target computational device.
Approach , avoidance , and their conflict : the problem of anchoring

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THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS

This paper describes heat transfer measurements on the external surface of a Natural Laminar Flow (NLF) nacelle. The measurement technique employed temperature sensitive liquid crystals and platinum resistance thermometers (PRTs) to measure the surface temperature over an electrically heated pad. This gave an immediate visual indication of the transition location. The heat transfer distribution along the length of the pad has been determined and is compared with a simple theoretical model. Results are presented for the cruise condition of Mach 0.56 at an altitude of 6400m. NOMENCLATURE h heat transfer coefficient, Wm 2K' k thermal conductivity of modelled heater pad, WmK ' 1 distance from pad centre line to pad edge, m q heat flux, Wm 2 q0 constant heat flux component, Wm 2 Re Reynolds number based on nacelle chord T temperature, K t thickness of modelled heater pad, m y distance from pad centre line, m Greek (3 ✓(h,o/tk), m'
Experimental exploration of the stratigraphy of fjords fed by glaciofluvial systems

Abstract Whereas most Late Quaternary sedimentary systems experienced only sea-level rise, fjords record unique sequences because rapid uplift after the unloading of the Last Glacial Maximum (LGM) ice sheets outpaced global eustatic sea-level rise. This study aims to disentangle how rapid initial uplift and high variability of eustatic sea-level change affects fjord sedimentary records. Two numerical models are coupled, ICE-5G and SedFlux, and show that timing and duration of deglaciation and total uplift strongly affect fjord stratigraphy. The ICE-5G model predicts a number of distinct time intervals during which many fjords deglaciate, independent of latitude and short-term climate. Deglaciation of the entire fjord system takes significantly longer (c. 6 ka) for fjords that deglaciate early (17–15 ka BP) than for fjords deglaciating after 9 ka BP (c. 1 ka). Exponential uplift curves totalled c. 220–280 m, and have half-lives of 1–1.4 ka. High uplift rates consistently cause rapid progradation of the rivermouth over tens of kilometres. Thick packages of glaciomarine, and glaciofluvial sediments emerged above sea level and are subsequently incised. Sensitivity tests predict high frequency of submarine mass movements. Fjords that deglaciated early additionally show deposition to be strongly dominated by rapid sea-level rise; signs of drowning are pronounced and subsequent thick fine-grained sequences aggrade. We conclude that recently deglaciated fjords record solely deposition under falling sea-level and thus provide the best modern analogues of forced-regressive systems.
Mechanisms of Seismically Induced Settlement of Buildings with Shallow Foundations on Liquefiable Soil

Seismically induced settlement of buildings with shallow foundations on liquefiable soils has resulted in significant damage in recent earthquakes. Engineers still largely estimate seismic building settlement using procedures developed to calculate postliquefaction reconsolidation settlement in the free-field. A series of centrifuge experiments involving buildings situated atop a layered soil deposit have been performed to identify the mechanisms involved in liquefaction-induced building settlement. Previous studies of this problem have identified important factors including shaking intensity, the liquefiable soil's relative density and thickness, and the building's weight and width. Centrifuge test results indicate that building settlement is not proportional to the thickness of the liquefiable layer and that most of this settlement occurs during earthquake strong shaking. Building-induced shear deformations combined with localized volumetric strains during partially drained cyclic loading are the dominant mechanisms. The development of high excess pore pressures, localized drainage in response to the high transient hydraulic gradients, and earthquake-induced ratcheting of the buildings into the softened soil are important effects that should be captured in design procedures that estimate liquefaction-induced building settlement.
High performance organisation : a quantitative inquiry at a specific metropolitan municipality in the Gauteng province

Since the dawn of the new democracy in South Africa, the media has been fraught with episodes of dissatisfaction among stakeholders about the service delivery record of municipalities. The aim of this study is, therefore, to explore employees’ experiences and perceptions, particularly at the Tshwane Metropolitan Municipality, regarding the service delivery performance of this municipality. The study was particularly motivated by the apparent lack of a scientifically tested intellectual tool to assist municipalities in improving service provision to residents. A quantitative research design was adopted to ensure uniformity and consistency of the data gathering and analysis processes. To this end, a population of 800 participants was targeted and at least 474 participants responded, thus, registering a response rate of 59%. The main findings of this study was the High Performance Organisational Culture model applicable to local government, whose factors yielded Cronbach Alpha coefficients of between 0.703 and 0.964. The managerial implication of the results of the study is a potential to equip the decision makers in the municipal sector with an empirically tested tool to assist the municipalities to ascend to a high performance status and thus, improve the quality of life of residents. The study is poised to provide a useful framework for policy formulation on high performance in the municipal sector.
A Study of the Hydraulics of Meandering Compound Channel Flows

Two subjects are chosen for discussions; one is the flow characteristics in a meandering compound channel with flat rigid and equilibrium rigid beds, and the other is the resistance of flows in compound channels.Experimental results show that the flow parttern, the profiles of water surface and velocity are strongly affected by energy or momentum transfer between in-bank and over-bank flows.An energy conservation equation is presented in order to evaluate the effects of interaction between the flows in main channel and flood plain to the flow resistence. A method is developed to predict the flow-depths, the mean velocities or the flow-discharges of main channel and flood plain. Its applicability is verified by flume data as well as by sensibility analysis.
Statistical analysis of nutrient data quality (nitrate and phosphate), applied to useful predictor models in the northwestern Mediterranean Sea

A dataset comprising 12 oceanographic cruises (from 1979 to 1983), covering two regions in the Northwestern Mediterranean Sea (Gulf of Lyon and Catalan Sea), was statistically analysed for nitrate and phosphate relationships with silicate, salinity and depth. This analysis provided a preliminary assessment of the data’s quality, as well as a predictor model of these nutrients below the surface layer. Results from the statistical analysis showed no significant difference (P = 0.05), between the regression equations (nitrate-depth and phosphate-salinity) of most cruises in the Gulf of Lyon, indicating that these relationships do not change in this area, particularly in summer and autumn. A significant relationship between nitrate and phosphate with salinity and depth (multiple regression) was observed, suggesting that nitrate and phosphate distribution in the intermediate level are significantly related to the mixture of the water masses and the degradation of organic matter. The phosphate data showed a wide variance and a bias, probably due to procedural problems in the chemical analysis. Below the Intermediate Levantine Water, results from the ANOVA showed no significant variation of the phosphate and nitrate concentrations in the water column. However, a spatial and temporal variation was observed in this level.
Reevaluation of conflicting Eocene tropical temperature estimates: Molluskan oxygen isotope evidence for warm low latitudes

Oxygen isotope data from planktonic foraminifera for the warm Eocene epoch suggest that tropical sea-surface temperatures (SSTs) may have been cooler than at present. Such data have stimulated various explanations involving, e.g., major changes in ocean heat transport. However, the planktonic data disagree with terrestrial climate proxies, which suggest significantly warmer low-latitude temperatures. We examined this discrepancy by analyzing seasonal oxygen isotope variations in shallow-marine mollusks from the Mississippi Embayment. Results indicate that mean annual SSTs decreased from 26–27 °C in the early Eocene to 22–23 °C in the Oligocene, agreeing well with temperatures inferred from terrestrial climate proxies. These cooling trends, with more significant winter cooling (5 °C) than summer cooling (3 °C), are consistent with the predicted consequences of decreasing atmospheric CO 2 concentration through the Paleogene, suggesting that atmospheric CO 2 change was a major controlling factor for Paleogene climate change. That winter SST estimates from the mollusks agree well with the foraminiferal SST estimates suggests that planktonic foraminiferal growth in low latitudes occurred mainly during the cooler winter months throughout the Eocene. We hypothesize that the unusual hydrography of Eocene oceans shifted foraminiferal productivity primarily to winter, biasing foraminiferal SST estimates of mean annual SSTs.