Miracle-dz/UniFAR-FTUs huggingface dataset:
Intraday management of bank reserves: the effects of caps and fees on daylight overdrafts

The Federal Reserve System imposes caps and charges fees on the negative intraday balances in banks' reserve accounts. i.e., on daylight overdrafts. Our empirical results suggest that caps alone did little to reduce daylight overdrafts in the aggregate. By contrast, the 1994 imposition of fees reduced the average daily maximum overdraft on the Fedwire system by about $93 billion and the average aggregate overdraft at any time during the day by about $43 billion. We also found statistical evidence that higher beginning-of-day reserve balances, lower aggregate dollar values of securities-related transfers over Fedwire, and lower shares of banks' assets funded with federal funds and repurchase agreements reduced daylight overdrafts. Copyright 1996 by Ohio State University Press.
Carbon Standards Examined A Comparison of Atthe-Source and Beyond-the-Source Power Plant Carbon Standards

The proposed replacement rule for the US Clean Power Plan, named the Affordable Clean Energy Rule, employs a narrow “at-the-source” approach that targets heat rate improvements at individual coal plants. The emissions rebound and state-level implications of this type of policy are not well understood. We analyze the potential effects of a similar at-the-source policy scenario on national and state emissions of carbon dioxide (CO2), sulfur dioxide (SO2) and nitrogen oxides (NOX) in 2030 using 2014 results from the Integrated Planning Model (IPM). Compared to a no-policy scenario, we find that an at-the-source scenario that provides an average fleet wide heat rate improvement of 4 percent for coal-fired power plants could result in only a modest decrease (-2.6 percent) in national power sector CO2 emissions, with potential increases in CO2 emissions in eight states totaling three million additional tons of CO2 emissions per year in those states. We decompose the CO2 emissions changes and find evidence of a rebound effect, in which coal plants that become more efficient operate more often. The scenario also results in a modest estimated increase (2.7 percent) in national SO2 emissions and a minor estimated reduction (-2.3 percent) in national NOX emissions, with increases in one or both pollutants in 12 states. Estimated emissions in 2030 are substantially higher under an at-the-source scenario for CO2 (63 percent), SO2 (88 percent), and NOX (56 percent) compared to a more flexible “beyond-the-source” scenario that resembles the Clean Power Plan. Our analysis suggests that a strong possibility of emissions rebound exists for at-the-source power plant standards, leading to increased CO2 and co-pollutant emissions at multiple scales that would degrade air quality and cause adverse health effects. The results reinforce the importance of analyzing both changes in power plant utilization as well as CO2 and co-pollutant emissions at the plant, state, regional and national scale when proposing to weaken emission standards.
Monocular 3D Pose and Shape Estimation of Multiple People in Natural Scenes: The Importance of Multiple Scene Constraints

Human sensing has greatly benefited from recent advances in deep learning, parametric human modeling, and large scale 2d and 3d datasets. However, existing 3d models make strong assumptions about the scene, considering either a single person per image, full views of the person, a simple background or many cameras. In this paper, we leverage state-of-the-art deep multi-task neural networks and parametric human and scene modeling, towards a fully automatic monocular visual sensing system for multiple interacting people, which (i) infers the 2d and 3d pose and shape of multiple people from a single image, relying on detailed semantic representations at both model and image level, to guide a combined optimization with feedforward and feedback components, (ii) automatically integrates scene constraints including ground plane support and simultaneous volume occupancy by multiple people, and (iii) extends the single image model to video by optimally solving the temporal person assignment problem and imposing coherent temporal pose and motion reconstructions while preserving image alignment fidelity. We perform experiments on both single and multi-person datasets, and systematically evaluate each component of the model, showing improved performance and extensive multiple human sensing capability. We also apply our method to images with multiple people, severe occlusions and diverse backgrounds captured in challenging natural scenes, and obtain results of good perceptual quality.
Large discrepancy between observed and simulated precipitation trends in the ascending and descending branches of the tropical circulation

Observed and model simulated changes in precipitation are examined using vertical motion at 500 hPa to define ascending and descending branches of the tropical circulation. Vertical motion fields from reanalyses were employed to subsample the observed precipitation data. An emerging signal of rising precipitation trends in the ascending regions and decreasing trends in the descending regimes are detected in the observational datasets. These trends are substantially larger in magnitude than present‐day model simulations and projections into the 21st century. The discrepancy cannot be explained by changes in the reanalysis fields used to subsample the observations but instead must relate to errors in the satellite data or in the model parametrizations. This has important implications for future predictions of climate change, the reliability of the observing system and the monitoring of the global water cycle.
A conceptual model for lignosulfonate treated soils

This paper describes an anisotropic elastoplastic based constitutive model for describing the behaviour of lignosulfonate stabilized soils. The proposed model is an extension of the earlier model developed by Dafalias (1987). The theoretical formulations of the current model were based on the frame work of critical state concept. The novel feature of this model is the incorporation of a material constant b, which takes into account of the degree of cementation. It is demonstrated that the model can capture the behaviour of lignosulfonate treated soil.
Comparative assessment of phytochemical composition, antioxidant and anticholinesterase activities of two Basidiomycota Truffle Fungi from Turkey

© 2017 Marmara University Press, All Rights Reserved http://doi.org/10.12991/mpj.2018. 41 Marmara Pharm J 2018;22(1): 59-65 Received: 14.06. 2017 / Accepted: 16.08. 2017 Corresponding Author: Gülsen Tel-Çayan E-mail: gulsentel@mu.edu. tr; gulsentelcayan@gmail.com Phone: +90 252 2111494 ORCID No: https://orcid.org/0000-0002-1916-7391 How to cite this article: Tel-Çayan G, Deveci E, Çayan F, Duru ME. Comparative assessment of phytochemical composition, antioxidant and anticholinesterase activities of two Basidiomycota Truffle Fungi from Turkey. Marmara Pharm J. 2018; 22 (1): 59-65. ABSTRACT: The aim of the present study was to compare phytochemical composition and biological activities of various extracts of two Basidiomycota truffle collected from Turkey. Analysis of phytochemical compositions in terms of phenolic and fatty acid compositions was determined using HPLC-DAD, GC and GC/MS. Fumaric (10.62, 4.12 μg/g) and protocatechuic acids (2.71, 20.50 μg/g) were identified as the major organic and phenolic acids in Chondrogaster pachysporus and Setchelliogaster tenuipes truffles. Linoleic acid (53.03 %) for C. pachysporus and palmitic acid (38.60 %) for S. tenuipes were found to be the most dominant fatty acids. The extracts were also tested for their antioxidant and anticholinesterase activities. As for antioxidant and anticholinesterase activity results, C. pachysporus truffle showed better activity than S. tenuipes. This work presents the first phytochemical study on C. pachysporus and S. tenuipes truffles and sheds light on their potential usage as the natural source in the food, pharmaceutical, and cosmetic industries.
Variability in clear‐sky longwave radiative cooling of the atmosphere

[1] The longwave radiative cooling of the clear-sky atmosphere (QLWc) is a crucial component of the global hydrological cycle and is composed of the clear-sky outgoing longwave radiation to space (OLRc) and the net downward minus upward clear-sky longwave radiation to the surface (SNLc). Estimates of QLWc from reanalyses and observations are presented for the period 1979–2004. Compared to other reanalyses data sets, the European Centre for Medium-range Weather Forecasts 40-year reanalysis (ERA40) produces the largest QLWc over the tropical oceans (217 W m−2), explained by the least negative SNLc. On the basis of comparisons with data derived from satellite measurements, ERA40 provides the most realistic QLWc climatology over the tropical oceans but exhibits a spurious interannual variability for column integrated water vapor (CWV) and SNLc. Interannual monthly anomalies of QLWc are broadly consistent between data sets with large increases during the warm El Nino events. Since relative humidity (RH) errors applying throughout the troposphere result in compensating effects on the cooling to space and to the surface, they exert only a marginal effect on QLWc. An observed increase in CWV with surface temperature of 3 kg m−2 K−1 over the tropical oceans is important in explaining a positive relationship between QLWc and surface temperature, in particular over ascending regimes; over tropical ocean descending regions this relationship ranges from 3.6 to 4.6 ± 0.4 W m−2 K−1 for the data sets considered, consistent with idealized sensitivity tests in which tropospheric warming is applied and RH is held constant and implying an increase in precipitation with warming.
Aberrations in Renal Function Parameters Following Oral Administration of Phyllanthus amarus in Cadmium-Induced Kidney Damage in Adult Wistar Rats

Renal disease has been found to be the ninth leading cause of death. Environmental pollution is a serious cause for concern nowadays and the exposure of humans to heavy metals released into the environment by several sources produces deleterious and lethal effects. Cadmium (Cd) which is a non-essential heavy metal known to possess toxic effects on living things can be found almost anywhere and its toxicity is of concern to industrial workers and all humans due to its use in some industrial products and also in agriculture. The chief organ of toxic impact in the human is the kidney, where the proximal tubule is a major target of Cd deposition. The present study investigated if ethanolic extract of Chanca Piedra (CP) (Phyllantus amarus) has any prophylactic or ameliorative effects against nephrotoxicity induced by cadmium sulphate in adult male Wistar rats. A total of forty-two (42) adult male Wistar rats were used for this study and were divided into seven (7) groups (n=6) as follows: Group A (control), Group B (40mg/kg BW), Group C (100mg/kg BW of CP and 40mg/kg BW of Cd), Group D (200mg/kg BW of CP and 40mg/kg BW), Group E (40mg/kg BW and 100mg/kg BW of CP), Group F (40mg/kg BW and 200mg/kg BW of CP), Group G (200mg/kg BW of CP). Both cadmium and Chanca Piedra were administered orally through oro-gastric cannula. Results showed that exposure to Cd lowered the activities of the kidney by increasing the plasma creatinine and urea levels. Exposure to CP also lowered the activities of the kidney by increasing the plasma creatinine and urea levels. The findings suggest that the administration of CP extract has no prophylactic or ameliorative effects on cadmium induced kidney damage and continue use of this extracts in the treatment of some diseases may be deleterious to the kidney.
Complex Hadamard matrices

R. J. Turyn introduced complex Hadamard matrices and showed that if there is a complex Hadamard matrix of order c and a real Hadamard matrix of order h> > 1, then there is a real Hadamard matrix of order he. Previously, complex Hadamard matrices were only known for a few small orders and the orders for which symmetric conference matrices were known. These latter are known only to exist for orders which can be written as 1+a2 +b2 where a, b are integers. We give many constructions for new infinite classes of complex Hadamard matrices and show that they exist for orders 306,650, 870,1406,2450 and 3782: for the orders 650, 870, 2450 and 3782, a symmetric conference matrix cannot exist.
Fast Video Object Segmentation by Reference-Guided Mask Propagation

We present an efficient method for the semi-supervised video object segmentation. Our method achieves accuracy competitive with state-of-the-art methods while running in a fraction of time compared to others. To this end, we propose a deep Siamese encoder-decoder network that is designed to take advantage of mask propagation and object detection while avoiding the weaknesses of both approaches. Our network, learned through a two-stage training process that exploits both synthetic and real data, works robustly without any online learning or post-processing. We validate our method on four benchmark sets that cover single and multiple object segmentation. On all the benchmark sets, our method shows comparable accuracy while having the order of magnitude faster runtime. We also provide extensive ablation and add-on studies to analyze and evaluate our framework.
When corporate social responsibility motivates employee citizenship behavior : The sensitizing role of task signi fi cance

Scholars have proposed that organizations’ corporate social responsibility (CSR) efforts are often positively associated with employees’ organizational citizenship behaviors (OCB) and have invoked identity-based mechanisms to explain this relationship. Complementing these perspectives, we develop a CSR sensitivity framework that explains how task significance, a micro-level job characteristic, can sensitize employees to their organizations’ macro-level CSR efforts, thereby strengthening the association between CSR and OCB. Across three field studies, we find that CSR and task significance interact to predict OCB, such that an organization’s CSR is more positively associated with OCB among employees who report higher task significance than among those who report lower task significance. Furthermore, we find support for prosocial motivation as a mediator of this interactive effect, but we do not find evidence for several alternative mediators. We discuss the implications of our findings for the literatures on CSR, job design, and other-oriented approaches to organizational behavior.
Investigating the Acceptance of Mobile Health Application User Interface Cultural-Based Design to Assist Arab Elderly Users

Mobile health (m-health) applications are a way to provide solutions to the non-availability of physical health services in the Arab world. However, end users of m-health around the world have their cultural and personal differences that distinguish them from others. Studies suggest that culture is an essential component of the success of any product or technology usage. In view of this, the study investigated acceptance towards mobile health application User Interface (UI) designed for Arab elderly users based on their culture. The TAM model formed the theoretical basis upon which a quantitative design was adopted, with a questionnaire as data collection instrument from 134 participants. The findings showed that perceived Ease of Use (PEOU) and Attitude Towards Use (ATU) had a significant positive influence on Behavioural Intention (BI) to use mobile health application User Interface. Overall, the results indicated that Arab elderly users found the mobile health application UI as acceptable due to its cultural-based design. To improve designs of mobile applications UI targeting elderly users, it is vital to gain insight into cultural aspects that influence the usability of mHealth application UI as well as insights into their personal characteristics and experiences.
Gaze Prediction in Dynamic 360° Immersive Videos

This paper explores gaze prediction in dynamic 360° immersive videos, i.e., based on the history scan path and VR contents, we predict where a viewer will look at an upcoming time. To tackle this problem, we first present the large-scale eye-tracking in dynamic VR scene dataset. Our dataset contains 208 360° videos captured in dynamic scenes, and each video is viewed by at least 31 subjects. Our analysis shows that gaze prediction depends on its history scan path and image contents. In terms of the image contents, those salient objects easily attract viewers' attention. On the one hand, the saliency is related to both appearance and motion of the objects. Considering that the saliency measured at different scales is different, we propose to compute saliency maps at different spatial scales: the sub-image patch centered at current gaze point, the sub-image corresponding to the Field of View (FoV), and the panorama image. Then we feed both the saliency maps and the corresponding images into a Convolutional Neural Network (CNN) for feature extraction. Meanwhile, we also use a Long-Short-Term-Memory (LSTM) to encode the history scan path. Then we combine the CNN features and LSTM features for gaze displacement prediction between gaze point at a current time and gaze point at an upcoming time. Extensive experiments validate the effectiveness of our method for gaze prediction in dynamic VR scenes.
Two-Step Quantization for Low-bit Neural Networks

Every bit matters in the hardware design of quantized neural networks. However, extremely-low-bit representation usually causes large accuracy drop. Thus, how to train extremely-low-bit neural networks with high accuracy is of central importance. Most existing network quantization approaches learn transformations (low-bit weights) as well as encodings (low-bit activations) simultaneously. This tight coupling makes the optimization problem difficult, and thus prevents the network from learning optimal representations. In this paper, we propose a simple yet effective Two-Step Quantization (TSQ) framework, by decomposing the network quantization problem into two steps: code learning and transformation function learning based on the learned codes. For the first step, we propose the sparse quantization method for code learning. The second step can be formulated as a non-linear least square regression problem with low-bit constraints, which can be solved efficiently in an iterative manner. Extensive experiments on CIFAR-10 and ILSVRC-12 datasets demonstrate that the proposed TSQ is effective and outperforms the state-of-the-art by a large margin. Especially, for 2-bit activation and ternary weight quantization of AlexNet, the accuracy of our TSQ drops only about 0.5 points compared with the full-precision counterpart, outperforming current state-of-the-art by more than 5 points.
A thermodynamic description for physiological transmembrane transport

A general formulation for both passive and active transmembrane transport is derived from basic thermodynamical principles. The derivation takes into account the energy required for the motion of molecules across membranes and includes the possibility of modeling asymmetric flow. Transmembrane currents can then be described by the general model in the case of electrogenic flow. As it is desirable in new models, it is possible to derive other well-known expressions for transmembrane currents as particular cases of the general formulation. For instance, the conductance-based formulation for current turns out to be a linear approximation of the general formula for current. Also, under suitable assumptions, other formulas for current based on electrodiffusion, like the constant field approximation by Goldman, can be recovered from the general formulation. The applicability of the general formulations is illustrated first with fits to existing data, and after, with models of transmembrane potential dynamics for pacemaking cardiocytes and neurons. The general formulations presented here provide a common ground for the biophysical study of physiological phenomena that depend on transmembrane transport.
A Survey on Tor Encrypted Traffic Monitoring

Tor (The Onion Router) is an anonymity tool that is widely used worldwide. Tor protect its user privacy against surveillance and censorship using strong encryption and obfuscation techniques which makes it extremely difficult to monitor and identify users’ activity on the Tor network. It also implements strong defense to protect the users against traffic features extraction and website fingerprinting. However, the strong anonymity also became the heaven for criminal to avoid network tracing. Therefore, numerous of research has been performed on encrypted traffic analyzing and classification using machine learning techniques. This paper presents survey on existing approaches for classification of Tor and other encrypted traffic. There is preliminary discussion on machine learning approaches and Tor network. Next, there are comparison of the surveyed traffic classification and discussion on their classification properties.
Supplementary Material for Few-Shot Image Recognition by Predicting Parameters from Activations Appendix

In Section 2.4, we briefly present the network architectures we use to train on the MiniImageNet dataset to get the activation function a(·). In total, we use two architectures for different purposes, and refer them as Ours-Simple and Ours-WRN, as shown in Table 3 of the paper. Ours-Simple is used to farily compare with the previous state-of-the-art methods on the MiniImageNet dataset. The architecture for a(·) is the same as that of Matching Network [4], and of the similar complexity with the other methods in comparison. Specifically, the following Table 1 shows the detailed configurations of Ours-Simple.
Versican Expression during Synovial Joint Morphogenesis

The extracellular matrix (ECM) plays a critical role in governing cell behavior and phenotype during limb skeletogenesis. Chondroitin sulfate proteoglycans (Cspgs) are highly expressed in the ECM of precartilage mesenchymal condensations and are important to limb chondrogenesis and cartilage structure, but little is known regarding their involvement in formation of synovial joints in the embryonic limb. Matrix versican Cspg expression has previously been reported in the epiphysis of developing long bones and presumptive joint; however, detailed analysis has not yet been conducted. In the present study we immunolocalized versican and aggrecan Cspgs during chick elbow joint morphogenesis between HH st25-41 of development. In this study we show that versican and aggrecan expression initially overlapped in the incipient cartilage model of long bones in the wing, but versican was also highly expressed in the perichondrium and presumptive joint interzone during early stages of morphogenesis (HH st25-34). By HH st36-41 versican localization was restricted to the future articular surfaces of the developing joint and surrounding joint capsule while aggrecan localized in an immediately adjacent and predominately non-overlapping region of chondrogenic cells at the epiphyses. These results suggest a potential role for versican proteoglycan in development and maintenance of the synovial joint interzone.