Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There Information Content in Information Acquisition?

In this study, we examine whether investors' actions to acquire accounting information are predictive of future firm performance because these actions partially reveal investors' private expectations of this performance. Using a database of EDGAR downloads, we find some evidence that information acquisition of accounting reports by EDGAR users is, on average, predictive of future firm performance. We then determine the identity of the EDGAR user and examine whether different users' private expectations will be relatively more predictive of subsequent performance. We find that the information acquisition activities of more sophisticated institutional users (e.g., hedge funds, investment banks) are more strongly associated with future performance than are those of less sophisticated retail users. Finally, we find that information acquisition by sophisticated institutions is a leading indicator of their equity holdings. In summary, this study provides evidence of predictive information embedded in sophisticated investors' actions to acquire accounting information.
Are Risk Regulators Rational? Evidence from Hazardous Waste Cleanup Decisions

Using original data on the cleanup of 130 hazardous waste sites, we examine the degree Superfund decisions are driven by efficiency concerns, biases in risk perceptions, and political factors. Target risk levels chosen by regulators are largely a function of political variables and risk perception biases. Regulators exhibit biases consistent with anchoring and the availability heuristic, and do not distinguish between current risks to actual residents and potential risks to hypothetically exposed populations. Quantile regressions indicate that political factors affect decisions on the cost per case of cancer averted, especially for the most inefficient cleanup efforts.
Reactivated Spatial Context Guides Episodic Recall

The medial temporal lobe (MTL) is known as the locus of spatial coding and episodic memory, but the interaction between these cognitive domains as well as the extent to which they rely on common neurophysiological mechanisms is poorly understood. The medial temporal lobe (MTL) is known as the locus of spatial coding and episodic memory, but the interaction between these cognitive domains as well as the extent to which they rely on common neurophysiological mechanisms is poorly understood. Here, we use intracranial electroencephalography and a hybrid spatial-episodic memory task (29 subjects, 15 female) to determine how spatial information is dynamically reactivated in subregions of the human MTL and how this reactivation guides recall of episodic information. Our results implicate theta oscillations across the MTL as a common neurophysiological substrate for spatial coding in navigation and episodic recall. We further show that our index of retrieved spatial context is high in the hippocampus (HC) in an early time window preceding recall. Closer to recall, it decreases in the HC and increases in the parahippocampal gyrus. Finally, we demonstrate that hippocampal theta phase modulates parahippocampal gamma amplitude during retrieval of spatial context, suggesting a role for cross-frequency coupling in coding and transmitting retrieved spatial information. SIGNIFICANCE STATEMENT By recording from the human medial temporal lobe (MTL) while subjects recall items experienced in a virtual environment, we establish a direct relation between the strength of theta activity during memory search and the extent to which memories are organized by their spatial locations. We thereby pinpoint a role for theta oscillations in accessing the “cognitive map” during episodic retrieval and further highlight the dynamic interplay of hippocampus and extrahippocampal MTL in representing retrieved spatial context. Our results provide an important step toward a unified theory of MTL function encompassing its role in spatial navigation and episodic memory.
$29 for 70 Items or 70 Items for $29? How Presentation Order Affects Package Perceptions

When consumers consider a package (multi-item) price, which presentation order is more appealing, price first ($29 for 70 items) or item quantity first (70 items for $29)? Will this depend on package size (larger [70 items] vs. smaller [7 items]) or unit price calculation difficulty (higher [$29 for 70 items] vs. lower [$20 for 50 items])? Why? Three studies demonstrate how presentation order affects package evaluations and choice under different levels of package size and unit price calculation difficulty. The first piece of information becomes salient and affects evaluations when packages are larger and unit price calculations are difficult (i.e., price-item [item-price] makes price [items] salient, negatively [positively] affecting evaluations). These effects do not persist with smaller packages or easier unit price calculations. Our findings contribute to several literatures (e.g., numerosity, computational difficulty) but primarily to the order effects literature and have implications for measurement and practice (e.g., pricing).
Sequential Bayesian Design for Accelerated Life Tests

ABSTRACT Most of the recently developed methods on optimum planning for accelerated life tests (ALT) involve “guessing” values of parameters to be estimated, and substituting such guesses in the proposed solution to obtain the final testing plan. In reality, such guesses may be very different from true values of the parameters, leading to inefficient test plans. To address this problem, we propose a sequential Bayesian strategy for planning of ALTs and a Bayesian estimation procedure for updating the parameter estimates sequentially. The proposed approach is motivated by ALT for polymer composite materials, but are generally applicable to a wide range of testing scenarios. Through the proposed sequential Bayesian design, one can efficiently collect data and then make predictions for the field performance. We use extensive simulations to evaluate the properties of the proposed sequential test planning strategy. We compare the proposed method to various traditional non-sequential optimum designs. Our results show that the proposed strategy is more robust and efficient, as compared to existing non-sequential optimum designs. Supplementary materials for this article are available online.
CLASSIFICATION USING NETWORK-IN-NETWORK BASED CONVOLUTIONAL NEURAL NETWORK

In this paper, we present our entry to the challenge of detection and classification of acoustic scenes and events (DCASE). This paper describes the result of our proposed system for automatic audio scene classification task. Our approach is based on the deep learning method that is adopted from computer vision research field. The convolutional neural network is adopted to solve the problem of audio based scene classification, specifically the architecture of network-in-network is utilized to build the classifier. For the feature extraction part, mel frequency spectral coefficients (MFCC) is used as the input vector for the classifier. Differ from the original architecture of network-in-network, in this work we perform 1-D convolution operation instead of performing 2-D convolution. The classifier is trained using every frames from MFCC feature set, and the results for every frames are then thresholded and voted to choose the final scene label of audio data. The proposed work in this paper shows a better performance of the provided baseline system of DCASE challenge for both development and evaluation dataset.
The Effect of Child Abuse on University Student’s Psychological Status A Retrospective study

Child abuse commonly underpins adult depression. Child abuse is classified into four categories; physical, sexual, mental and neglect. This paper will study and discuss the rate of depression caused by child abuse at the time of the abuse, the data collected from the first section of the survey, which consisted of two categorical questions. There are two questions that this research will try to answer; have more females experienced one or multiple types of abuse during their childhood compared to male? And have the ones who have experienced abuse suffered from a degree of depression at the time of the abuse. The depression test that consisted of four questions that determined the participant’s depression percentage The result and tables have been duplicated from the Public Service Pension Plan (PSPP), 21 females and 36 males participated in the survey. In total 57 students answered the questions that were sent through email. 73% of the participants said that they were not abused as a child in any of the forms. 27% of the participants have been abused in one or more of the ways as a child. , further, 71.4% of the abuse were physical followed by mental and neglect (28%. 28%, respectively). Likely there were zero records of sexual abuse. Most of the abuse was happening around age 1-5 years and less likely on age 1-5 and above. Females become more depressed than males. 57.2% of the abused children were suffering from anxiety followed by an interruption in their relationship and low self esteem It can be concluded that more female were abused as a child. We can see that the constant (Male) is 49.29 and the female participants are 26.34 more than the constant. This proves that females become more depressed than men. Therefore, much work will need to Protect the children from harm.
Policing intimate partner violence in Victoria (Australia): Examining police attitudes and the potential of specialisation

The adequacy of police responses to intimate partner violence has long animated scholarly debate, review and legislative change. While there have been significant shifts in community recognition of and concern about intimate partner violence, particularly in the wake of the Victorian Royal Commission into Family Violence, it nonetheless remains a significant form of violence and harm across Australian communities and a key issue for police, as noted in the report and recommendations of the Royal Commission. This article draws on findings from semi-structured interviews (n = 163) with police in Victoria and pursues two key inter-related arguments. The first is that police attitudes towards incidents of intimate partner violence remain overwhelmingly negative. Despite innovations in policy and training, we suggest that this consistent dissatisfaction with intimate partner violence incidents as a policing task indicates a significant barrier, possibly insurmountable, to attempts to reform the policing of intimate partner violence via force-wide initiatives and the mobilisation of general duties for this purpose. Consequently, our second argument is that specialisation via a commitment to dedicated intimate partner violence units – implemented more consistently and comprehensively than Victoria Police has to date – extends the greatest promise for effective policing of intimate partner violence in the future.
Modeling risk of hunting pressure on large mammals in northwestern Argentina

The subtropical Yungas and Chaco forests of northwestern Argentina are two of the most biodiverse and threatened biomes in South America. It is unclear how development pressure and increased human presence may be affecting wildlife in this increasingly fragmented and degraded landscape. We initiated a broad-scale analysis of the spatial distribution and magnitude of anthropogenic factors that may influence large mammal mortality due to potential human hunting pressure in a landscape linkage connecting these threatened forests. We conducted a literature review of Neotropical study sites that reported hunting of large mammals by indigenous people or colonists, and used this information to inform development of a risk distribution model. We identified linear distance values that represented the spatial patterns of hunter travel distance (i.e., willingness to travel) when in search of large bodied (>10 kg) prey species. To parameterize our model, we used information on percent forest cover, and values that reflect hunter travel distances as a function of distance from disturbance on the landscape, referencing roads and human settlements. The resultant risk map highlights gradients of risk of human-caused mortality due to hunting of large mammals potentially inhabiting or moving through the study region. We report patterns across the study landscape that show areas of relatively low mortality risk and putative linkages, while in other locations we report clear aggregations of high risk values suggesting areas of conservation concern. Where existing protected areas are close to or overlapping high risk areas, land managers should implement focused anti-poaching campaigns and prevent land clearing activities that could elevate humancaused risk of mortality. Likewise, locations at low risk of human-caused hunting mortality (especially those areas located amid the protected area network) may be robust for conservation, and thus should be considered a management priority. Minimizing new human disturbance, particularly in locations we report as low to moderate risk, should be actively pursued before these locations become targets of future land-use change. If managers seek to sustain the region‘s wildlife populations for future generations, then focused hunting control action and public awareness campaigns combined with forest conservation programs should be a high priority on the management agenda. Special funds are needed to improve managers‘ ability to control poaching throughout this region and help support new wildlife population studies to further focus conservation planning.
Pose-Guided Photorealistic Face Rotation

Face rotation provides an effective and cheap way for data augmentation and representation learning of face recognition. It is a challenging generative learning problem due to the large pose discrepancy between two face images. This work focuses on flexible face rotation of arbitrary head poses, including extreme profile views. We propose a novel Couple-Agent Pose-Guided Generative Adversarial Network (CAPG-GAN) to generate both neutral and profile head pose face images. The head pose information is encoded by facial landmark heatmaps. It not only forms a mask image to guide the generator in learning process but also provides a flexible controllable condition during inference. A couple-agent discriminator is introduced to reinforce on the realism of synthetic arbitrary view faces. Besides the generator and conditional adversarial loss, CAPG-GAN further employs identity preserving loss and total variation regularization to preserve identity information and refine local textures respectively. Quantitative and qualitative experimental results on the Multi-PIE and LFW databases consistently show the superiority of our face rotation method over the state-of-the-art.
Gigantic intrinsic orbital Hall effects in weakly spin-orbit coupled metals

A recent paper [D. Go et al., Phys. Rev. Lett. 121, 086602 (2018)] proposed that the intrinsic orbital Hall effect (OHE) can emerge from momentum-space orbital texture in centrosymmetric materials. In searching for real materials with strong OHE, we investigate the intrinsic OHE in metals with small spin-orbit coupling (SOC) in face-centered cubic and body-centered cubic structures (Li, Al, V, Cr, Mn, Ni, and Cu). We find that orbital Hall conductivities (OHCs) in these materials are gigantic $\ensuremath{\sim}{10}^{3}\ensuremath{-}{10}^{4}\phantom{\rule{4pt}{0ex}}(\ensuremath{\hbar}/e){(\mathrm{\ensuremath{\Omega}}\ifmmode\cdot\else\textperiodcentered\fi{}\mathrm{cm})}^{\ensuremath{-}1}$, which are comparable or larger than spin Hall conductivity (SHC) of Pt. Although SHCs in these materials are smaller than OHCs due to small SOC, we found that SHCs are still sizable and the spin Hall angles may be of the order of 0.1. We discuss implications on recent spin-charge interconversion experiments on materials having small SOC.
Composition of Intestinal Microbiota in Two Lines of Rainbow Trout (Oncorhynchus Mykiss) Divergently Selected for Muscle Fat Content

Background: Recently, studies suggest that gut microbiota contributes to the development of obesity in mammals. In rainbow trout, little is known about the role of intestinal microbiota in host physiology. Objective: The aim of this study was to investigate the link between intestinal microbiota and adiposity, by high-throughput 16S RNA gene based illumina Miseq sequencing in two rainbow trout lines divergently selected for muscle lipid content. Fish from these two lines of rainbow trout are known to have a differing lipid metabolism. Methods: Samples from the two lines (L for lean and F for fat) were collected from Midgut (M) and Hindgut (H) in juvenile fish (18 months) to compare intestinal microbiota diversity. Results: Whatever the lines and intestinal localisation, Proteobacteria, Firmicutes and Actinobacteria are the dominant phyla in the bacterial community of rainbow trout (at least 97%). The results indicate that richness and diversity indexes as well as bacterial composition are comparable between all groups even though 6 specific OTUs were identified in the intestinal microbiota of fish from the fat line and 2 OTUs were specific to the microbiota of fish from the lean line. Our work contributes to a better understanding in microbial diversity in intestinal microbiota of rainbow trout. Conclusion: Altogether, our study indicates that no major modification of the intestinal microbiota is induced by selection for muscle lipid content and associated metabolic changes. Finally, we identified members of core microbiota in rainbow trout.
Stable room-temperature micron-scale crack growth in single-crystalline silicon

Room-temperature fracture along the (111) plane of silicon is probed at the micron-scale using chevron notched cantilever beams that enable stable crack growth before unstable fracture in successful tests. The main experimental observation is that a growing crack can extend and arrest at different stress intensity factor values within the same specimen. The present data thus provide evidence of variations in the effective Si fracture toughness along the path of a growing crack. This effect could be explained by variations in the extent of limited cracktip plasticity along the crack path. The present work also shows that the microscopic chevron notch test is, from an experimental point of view, an inconvenient method to probe the fracture toughness of silicon because it is difficult with silicon to nucleate a crack at the chevron tip at loads low enough to allow for subsequent stable crack growth.
The Brazilian Wine Industry: a case study on geographical proximity and innovation dynamics

his paper aims to analyze the cooperation and learning processes in the local system of vitiviniculture production of Serra Gaucha’s region (Rio Grande do Sul, Brazil), in order to characterize the dynamics of innovation of the firms located there. In methodological terms, a non-probabilistic exploratory study has been conducted. Field research in 20 wineries as well as interviews with related organizations were carried out in order to understand which learning mechanisms support innovative strategies adopted by enterprises. Since learning processes are also the result of local interactions, it was necessary to understand whether these interactions produced cooperative links . The results showed that innovations made by the firms were basically incremental. To do so, they use their intrinsic learning processes as well as external agents. These agents can be located in the region or elsewhere. The geographical proximity becomes more relevant for smaller firms. It was still possible to perceive the existence of cooperation in both vertical and horizontal level. Most frequent actions of vertical cooperation occur especially between firms and their suppliers. When horizontal cooperation occurs between enterprises, it takes place particularly in international trading.
An Electrocardiogram (ECG) Domain Ontology

This paper presents an ontology of the electrocardiogram domain. The ontology purpose is to bring in a theory of the electrocardiogram (ECG). The ECG is the most applied test for mapping the heart activity. Notably with the recent advances in information and communication technologies, new services in Healthcare have been provided, standing out remote reporting and telemonitoring. In this context the ECG has a key usefulness. However, the diversity of biomedical data combined to heterogeneous information systems have been inhibited these advances in Healthcare environments. This initiative then addresses the need for semantic interoperability, in general, and data integration, in particular, in Health Informatics. Besides, it also provides an approach for developing ECG automatic analysis systems.
Document Enhancement Using Visibility Detection

This paper re-visits classical problems in document enhancement. Rather than proposing a new algorithm for a specific problem, we introduce a novel general approach. The key idea is to modify any state-of-the-art algorithm, by providing it with new information (input), improving its own results. Interestingly, this information is based on a solution to a seemingly unrelated problem of visibility detection in R3. We show that a simple representation of an image as a 3D point cloud, gives visibility detection on this cloud a new interpretation. What does it mean for a point to be visible? Although this question has been widely studied within computer vision, it has always been assumed that the point set is a sampling of a real scene. We show that the answer to this question in our context reveals unique and useful information about the image. We demonstrate the benefit of this idea for document binarization and for unshadowing.
Sign Language Recognition using Partial Least Squares and RGB-D Information

Deaf people use systems for communication based on sign language and fingerspelling. Manual spelling or fingerspelling is based on the alphabet, where each letter is represented by an unique movement of the hand. Hand-shapes corresponding to letter of the alphabet can be characterized using appearance and depth images. The fusion of visual and shape cues is a very promising approach. The recent introduction of fast and inexpensive RGB-D sensors, such as Microsoft Kinect, allow to collect appearance and depth images. In this paper, we present a framework that recognizes the American Sign Language (ASL) Fingerspelling using RGB-D images. The proposed framework is based on the bag of features strategy combined with the Partial Least Squares (PLS) technique in order to create models of the letters in the manual alphabet. It also uses the Binary Appearance and Shape Elements (BASE), a fast and low cost descriptor that combines intensity and shape information. We conduct two experiments, the first is based on classification methods. The SVM and PLS classifiers are evaluated. In the second experiment, SIFT and BASE feature descriptors are appraised. SIFT achieves slightly higher accuracy, while BASE runs faster with low memory consumption. This is desirable condition when the objective is to run in real time. In both experiments PLS classifier outperforms the SVM.