Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk-Neutral Skewness: Return Predictability and Its Sources

Using data on individual stock options, we show that the currently observed option-implied ex ante skewness is positively related to future stock returns. This contrasts with the existing evidence that uses historical stock or option data to estimate skewness and finds a negative skewness-return relation. We proxy for the ex ante skewness by using the model-free implied skewness (MFIS) and show that high MFIS stocks outperform low MFIS stocks by 45 basis points per month after correcting for systematic exposure. We find that the positive MFIS-return relation stems from the ability of the current MFIS to identify the deviation of a firm’s value from its fundamental value, and the most overvalued stocks have the most negative ex ante skewness. We further find that the speed of the value correction process depends on the arbitrage risk faced by arbitrageurs trying to exploit the observed inefficiencies. Our results have implications for the segmentation of equity and options markets as well as for limits of arbitrage in equity markets.
Cumulative Disparities in the Dynamics of Working Poverty for Later Career U.S. Workers (2002–2012)

Many more Americans experience working poverty than unemployed poverty, a situation that was only exacerbated by the Great Recession. The consequences of working poverty for later career workers, who should be at their highest earning ages, are particularly dire. The authors expect that later career workers are especially vulnerable in terms of the risk and duration of working poverty and that those who have accumulated disadvantages over their life courses, in terms of the intersecting dimensions of race/ethnicity, gender, early-life disadvantage, and educational attainment, will suffer disproportionately. The authors use incidence-based Markov-chain multistate models to analyze the U.S. Health and Retirement Study, which is representative of the U.S. population aged 50 years and older. The results reveal that Black women and men, Latinx, those who experienced more early-life disadvantages, and people with lower education have higher risk and longer durations in working poverty over the period from 2002 to 2012. The findings also suggest that when confronted with economic hardship (the Great Recession) later career workers who originate in lower socioeconomic statuses, especially Blacks and Latinx, are in more precarious economic positions. Important from a policy perspective, educational attainment only partially mediates the association between race/ethnicity and working poverty; disparities persist.
Introducing the improved Forest Canopy density (FCD) model for frequent assessment of Hyrcanian forest

Mapping of forest extent is a prerequisite to acquire quantitative and qualitative information about forests and to formulate management and conservation strategies. forest canopy density (FCD) model is one of the useful RS methods for forest mapping using satellite images. One of the most serious challenges in FCD model is the weakness in the calculation of canopy density in low density forests as well as plain forests. Due to the existence of chlorophyll in croplands, shrubs, pastures, etc., FCD model has difficulty to determinate the forests areas from the other mentioned land cover. Hence, this paper is focused on improving the performance of FCD model to overcome this limitation. This improvement yield by adding a new forest color composite index (FCCI) and removing non-forest vegetation using the average kernel and DEM regard to standard forest definition. In this study, in order to implement and evaluate the performance of the improved model, time series of Landsat images acquired from USGS Landsat standard level-2 products archive. In this study, Landsat time series images acquired from USGS Landsat standard level-2 products were used to estimate forest canopy density in Hyrcanian forests of northern Iran. The results indicated the higher accuracy of the proposed model. Moreover, overall accuracy and kappa index of the model were 10% and 24% superior to initial model, respectively. As a second objective, in order to implement and evaluate the performance of the improved model, canopy changes of the Hyrcanian forests were also examined. In general, the results of this study showed that the total area of Hyrcanian forest increased from 154,272 hectares from 1987 to 2009. Mazandaran, Gilan and Golestan provinces contributed 75,070, 47,615 and 31,567 hectares respectively. In addition, the results showed that the area of Hyrcanian forests decreased by 17,631 hectares between 2009 and 2017.
Processo de domesticação do parasitoide nativo de moscas-das-frutas Doryctobracon areolatus (Szépligeti) em laboratório

A domesticacao de especies nativas de parasitoides em laboratorio e de grande interesse, pois, como elas ja estao adaptadas aos agroecossistemas brasileiros, sua liberacao pode resultar em aumento de sua populacao em campo. Os objetivos da presente pesquisa foram estabelecer um processo de domesticacao do parasitoide nativo Doryctobracon areolatus (Szepligeti, 1911) em laboratorio e estudar aspectos do comportamento de parasitismo. Para iniciar o processo de domesticacao, realizaramse coletas de frutos em pomares de areas rurais, para a obtencao de especimes de D. areolatus. A partir dos insetos obtidos em campo, foi iniciada a domesticacao do parasitoide em laboratorio. O processo de domesticacao foi descrito, sendo mantida a criacao de D. areolatus por cinco geracoes. Avaliou-se a idade ideal das larvas hospedeiras para permitir a melhor porcentagem de parasitismo e a proporcao de femeas na progenie. A maior proporcao de larvas parasitadas e superparasitadas e o maior indice de parasitismo foram obtidos quando larvas de Anastrepha fraterculus de seis/sete dias de idade foram oferecidas as femeas de D. areolatus. A razao sexual nao foi alterada com a idade da larva hospedeira. Discutiram-se os principais problemas na domesticacao de parasitoides a partir de insetos obtidos em campo sobre outros hospedeiros.
Microwave-Assisted Stille Cross-Coupling Reaction Catalysed by in Situ Formed Palladium Nanoparticles

The Stille coupling of organotin compounds with aryl iodides and aryl bromides catalysed by in situ formed nanoparticles from commercially available palladium dichloride in PEG-400 in the presence of DMAP under microwave irradiation has been developed. For tetraphenylstannane, the reaction was carried out in an atom-efficient way, as 4 equiv. of aryl halides coupled effectively with 1 equiv. of tetraphenylstannane to furnish 4 equiv. of the corresponding functionalised biaryls in high yields. Under the same conditions, PhSnBu3 also reacted with aryl halides to produce biphenyls.
Karakterisasi Fisik Pati Tapioka Modifikasi Gabungan Hidroksipropilasi dengan Fosfat-Ikat Silang

Native tapioca starch has limited application in food industry due to its physicochemical characteristics that are not suitable for processing conditions, such as unstable at high temperature heating, acidic conditions, stirring, and undergoing syneresis. This deficiency can be overcome by applying a dual modification involving hydroxypropylation and cross-linking with phosphates. In this study, modification was carried out by hydroxypropylation using propylene oxide (8, 10, and 12%), followed by cross-linking with a combination of sodium tripolyphosphate (STPP) and sodium phosphate (STMP) with a ratio of 2%: 5%. The modified tapioca starch had water content of 7.82-8.19% with a pH value of 7.04-7.26, and phosphorus resiude of <0.4%. There were no change in starch granules and type of cristallline (A-tyype) of starch modifications. The dual modified starch with the addition of 10% propylene oxide concentration with a mixture of STMP : STTP ratio (2%:5% was selected to have acceptable physicochemical properties. It showed lowered pasting temperature, minimum break down viscosity, increased peak and setback viscosity compared to that of native starch. The modified tapioca starch also showed more heat stable and stirring resistant than that of native tapioca starch.
Light Reflected from Different Plant Canopies Affected Beta vulgaris L. Growth and Development

Studies on crop response to light quality (red (R) to far-red (FR) light ratio) often recommend early weed removal to reduce the effects of shade avoidance responses on crop yield. However, it is unclear whether crops are able to distinguish reflected light quality of kin from that of nonkin. We evaluated the response of sugar beet (Beta vulgaris L.) to reflected FR light from sugar beet, common lambsquarters (Chenopodium album L.), Kentucky bluegrass (Poa pratensis L.), alfalfa (Medicago sativa L.), and bare soil (control) under outdoor conditions in 2016 and 2017. Treatments were completely randomized with 10 replications per treatment. The study methods ensured there was no direct resource competition. The reflected R:FR of plant species ranged from 0.06 (common lambsquarters) to 0.24 (sugar beet) compared to 0.7 for the bare soil. In 2016 and 2017, there were 2 to 4 more leaves in the sugar beet surrounded by soil compared to sugar beet surrounded by neighboring species. There was up to 47, 57, 43, and 23% reduction in sugar beet leaf area, shoot dry weight, root diameter, and root dry weight, respectively, due to reflected R:FR light from neighboring species. Sugar beet did not respond differently to reflected light quality of kin compared to nonkin.
Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 2: Sensitivity analysis and model calibration

We analyse 400 perturbed-parameter simulations for two configurations of an optimality-based plankton-ecosystem model (OPEM), implemented in the University of Victoria Earth-System Climate Model (UVic-ESCM), using a Latin-Hypercube sampling method for setting up the parameter ensemble. A likelihood-based metric is introduced for model assessment and selection of the model solutions closest to observed distributions of NO3−, PO43−, O2, and surface chlorophyll a concentrations. According to our metric the optimal model solutions comprise low rates of global N2 fixation and denitrification. These two rate estimates turned out to be poorly constrained by the data. For identifying the “best” model solutions we therefore also consider the model’s ability to represent current estimates of water-column denitrification. We employ our ensemble of model solutions in a sensitivity analysis to gain insights into the importance and role of individual model parameters as well as correlations between various biogeochemical processes and tracers, such as POC export and the NO3− inventory. Global O2 varies by a factor of two and NO3− by more than a factor of six among all simulations. Remineralisation rate is the most important parameter for O2, which is also affected by the subsistence N quota of ordinary phytoplankton (QN0,phy) and zooplankton maximum specific ingestion rate. QN0,phy is revealed as a major determinant of the oceanic NO3− pool. This indicates that unraveling the driving forces of variations in phytoplankton physiology and elemental stoichiometry, which are tightly linked via QN0,phy, is a prerequisite for understanding the marine nitrogen inventory.
SENSITIVITY ANALYSIS OF THE SPATIAL AND ALTITUDE DISTRIBUTIONS OF POLLUTANTS USING THE WEATHER RESEARCH AND FORECASTING MODEL WITH CHEMISTRY (WRF/CHEM)

The Weather Research and Forecasting (WRF) model is a new "state-of-the-art" meteorological model which offers the users many different options for physical parameterizations. The recent introduction of a Chemical module (WRF/Chem) allows to perform an "on-line" description of the chemical evolution of trace pollutants by coupling a time-dependent chemical mechanism to the primitive meteorological equations. The advantage of WRF/Chem model over traditional dispersion models (CALPUFF, ISC3, etc.) is that a 3-D+temporal description of the pollutants distribution can be obtained. In this work, the WRF/Chem model has been used to study the dependence of the spatial and temporal distribution of point sources of pollutants with the altitude at which they are emitted. The study considers a detailed 24 hours winter period over a 200 km × 200 km regional domain centered at Buenos Aires, including only the pollutants emissions from typical power-plant stack with variable height. A sensitivity analysis of the model was performed considering different scenarios where the altitude and emission rate of the stack were modified, keeping the total emission constant. The response of WRF/Chem model to the proposed cases was statistically analyzed by computing several types of difference measures, as mean bias error, mean absolute error and index of agreement. Larger sensitivity to emissions schemes was found for the scenarios emitting near surface or at elevated levels. For those emitting at intermediate levels, the height of the time-variant Planetary Boundary Layer (PBL) is a relevant parameter.
Neoliberal Social Work and COVID-19

28 April 2020 was International Workers Memorial Day (IWM). It's an annual event organised by trade unions to commemorate the many thousands of workers who have died unnecessarily and too young as a result of government or employer negligence, through industrial accidents or through avoidable industrial diseases like asbestosis. In 2020, IWM Day was a bit different. For this year we observed a minute's silence for all the frontline workers-health workers, care workers, bus drivers, shop workers and social workers-who have lost their lives due to COVID-19. In Part II of this book, contributors report on the new and imaginative ways that social workers are developing practice to keep in touch with service users during the crisis, to reduce social isolation and protect mental health. There have also been accounts of social workers making links with the new mutual aid organisations that are springing up everywhere. Working under the occupation, the community health workers in Aida and Azza have produced a video and pamphlets detailing ways to minimise the risk of contracting COVID-19. They call their patients daily and arrange for the safe delivery of life-saving diabetes medication. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
Foodborne Transmission of SARS-CoV-2 Is More Evident Than It Has Been Before

Background:Although highly strict social distancing and viral spread protection guidelines are in force, the reported numbers of COVID-19 cases across the world are still increasing. This indicates that we are still unable to completely understand the transmission routes of SARS-CoV-2. One of the possible routes that can play a significant role is the fecal-oral transmission since SARS-CoV-2 can replicate in the intestines as demonstrated by isolation of infectious virus from fecal samples of COVID-19 cases. Scope and approach:In this review, we compare the characteristics of SARS-CoV-2 with the distinctive characteristics of enteric foodborne viruses. We also discuss and respond to the arguments given in some reports that downplay the importance of foodborne transmission route of SARS-CoV-2. Key findings and conclusions:Enteric viruses such as human noroviruses (HuNoVs) and hepatitis A virus (HAV) are known to transmit through foods such as fresh produce and berries, leading to frequent multistate foodborne disease outbreaks all over the world. SARS-CoV-2 was found to share four distinctive characteristics of foodborne viruses that allow them to transmit through foods. This similarity in characteristics, recent report of detecting SARS-CoV-2 particles from frozen food packages in China, and recent suspected foodborne COVID-19 case in New Zealand, indicate that foodborne transmission of SARS-CoV-2 is more evident than previously thought possible. To support or deny this route of transmission, urgent research needs to be undertaken to answer two primary questions and many secondary ones as described in this review.
ANALISA CLUSTER APLIKASI PADA APP STORE DENGAN MENGGUNAKAN METODE K-MEANS

Bagi para pengguna iphone, salah satu tempat untuk mengunduh ratusan ribu aplikasi android adalah App Store . Aplikasi-aplikasi iOS di bagi menjadi ketegori-ketegori yang unik. Di dalam aplikasi iOS ini terdapat aplikasi-aplikasi yang berbayar dan gratis. Dengan kategori tersebut pengguna bisa dengan mudah mencari aplikasi yang dibutuhkannya. Pada penelitian ini kami menggunakan metode K-Means untuk melihat ciri-ciri dari atribut yang ada. Dataset App Store diambil dari website resmi kaggle. Tujuan dari penelitian ini adalah untuk menganalisa hasil cluster dari K-Means. Hasil dari penelitian adalah adanya sebuah cluster yang memiliki ciri-ciri aplikasi yang ideal, yaitu nilai user rating tinggi, harga yang cukup lumayan dan memiliki ukuran aplikasi yang rendah.
Defining Immersion: Literature Review and Implications for Research on Audiovisual Experiences

The use of the term immersion to describe a multitude of varying experiences in the absence of a definitional consensus has obfuscated and diluted the term. The non-exhaustive literature review presented in this paper indicates that immersion is a psychological concept as opposed to being a property of the system or technology that facilitates an experience. An adaptable definition of immersion is synthesized based on the findings from the literature review: a state of deep mental involvement in which the individual may experience disassociation from the awareness of the physical world due to a shift in their attentional state. This definition is used to contrast and differentiate interchangeably used terms such as presence from immersion and outline the implications for conducting immersion research on audiovisual experiences. A new methodology for quantifying immersion is proposed and avenues for future work are briefly discussed.
Changes of Physicochemical Properties and Antioxidant Activities of Red Wines during Fermentation and Post-fermentation

The goal of this study was to vinify four varieties of grapes, namely Vitis labrusca L (Gerbong), Vitis labrusca B (Campbell Early), Vitis labrusca (Muscat Bailey A) and Vitis hybrid (Sheridan), and to investigate the changes in the physicochemical properties and antioxidant activity of the red wines during fermentation and post-fermentation. The ethanol content of the four red wines varied only slightly from 11.4%-12.8%, indicating that no significant change occurred during the fermentation and post-fermentation. The total anthocyanin and phenol contents as bioactive compounds were the highest level in the Vitis labrusca B red wine. The antioxidant activity was also the highest of 88.9% after 10 days fermentation in the Vitis labrusca B red wine and showed from only 36.6% to 61.7% in the other red wines, though the range decreased to 33.1 %-64.1 % during post-fermentation for 120 days at 4°C. Our results show that the Vitis labrusca B red wine has the potential to become a functional red wine because of its high antioxidant activity.
RoSmEEry: Robotic Simulated Environment for Evaluation and Benchmarking of Semantic Mapping Algorithms

Human-robot interaction requires a common understanding of the operational environment, which can be provided by a representation that blends geometric and symbolic knowledge: a semantic map. Through a semantic map the robot can interpret user commands by grounding them to its sensory observations. Semantic mapping is the process that builds such a representation. Despite being fundamental to enable cognition and high-level reasoning in robotics, semantic mapping is a challenging task due to generalization to different scenarios and sensory data types. In fact, it is difficult to obtain a rich and accurate semantic map of the environment and of the objects therein. Moreover, to date, there are no frameworks that allow for a comparison of the performance in building semantic maps for a given environment. To tackle these issues we design RoSmEEry, a novel framework based on the Gazebo simulator, where we introduce an accessible and ready-to-use methodology for a systematic evaluation of semantic mapping algorithms. We release our framework, as an open-source package, with multiple simulation environments with the aim to provide a general set-up to quantitatively measure the performances in acquiring semantic knowledge about the environment.
Quantum Uncertainty in Decision Theory

An approach is presented treating decision theory as a probabilistic theory based on quantum techniques. Accurate definitions are given and thorough analysis is accomplished for the quantum probabilities describing the choice between separate alternatives, sequential alternatives characterizing conditional quantum probabilities, and behavioral quantum probabilities taking into account rational-irrational duality of decision making. The comparison between quantum and classical probabilities is explained. The analysis demonstrates that quantum probabilities serve as an essentially more powerful tool of characterizing various decision-making situations including the influence of psychological behavioral effects.
Data-driven Algorithms for signal processing with rational functions

Rational approximation schemes for reconstructing signals from samples with poorly separated spectral content are described. These methods are automatic and adaptive, requiring no tuning or manual parameter selection. Collectively, they form a framework for ﬁtting trigonometric rational models to data that is robust to various forms of corruption, including additive Gaussian noise, perturbed sampling grids, and missing data. Our approach combines a variant of Prony’s method with a modiﬁed version of the AAA algorithm. Using representations in both frequency and time space, a collection of algorithms is described for adaptively computing with trigonometric rationals. This includes procedures for diﬀerentiation, ﬁltering, convolution, and more.
Information Theoretic Key Agreement Protocol based on ECG signals

Wireless body area networks (WBANs) are becoming increasingly popular as they allow individuals to continuously monitor their vitals and physiological parameters remotely from the hospital. With the spread of the SARS-CoV-2 pandemic, the availability of portable pulse-oximeters and wearable heart rate detectors has boomed in the market. At the same time, in 2020 we assisted to an unprecedented increase of healthcare breaches, revealing the extreme vulnerability of the current generation of WBANs. Therefore, the development of new security protocols to ensure data protection, authentication, integrity and privacy within WBANs are highly needed. Here, we targeted a WBAN collecting ECG signals from different sensor nodes on the individual's body, we extracted the inter-pulse interval (i.e., R-R interval) sequence from each of them, and we developed a new information theoretic key agreement protocol that exploits the inherent randomness of ECG to ensure authentication between sensor pairs within the WBAN. After proper pre-processing, we provide an analytical solution that ensures robust authentication; we provide a unique information reconciliation matrix, which gives good performance for all ECG sensor pairs; and we can show that a relationship between information reconciliation and privacy amplification matrices can be found. Finally, we show the trade-off between the level of security, in terms of key generation rate, and the complexity of the error correction scheme implemented in the system.