Miracle-dz/UniFAR-FTUs huggingface dataset:
Working Paper Series Monetary and macroprudential policy with foreign currency loans Macroprudential Research Network

In a number of countries a substantial proportion of mortgage loans is denominated in foreign currency. In this paper we demonstrate how their presence affects economic policy and agents’ welfare. To this end we construct a small open economy model with housing loans denominated in domestic or foreign currency. The model is calibrated for Poland a typical small open economy with a large share of foreign currency loans (FCL). We show that FCLs negatively affect the transmission of monetary policy. In contrast, their impact on the effectiveness of macroprudential policy is much weaker but positive. We also demonstrate that FCLs increase welfare when domestic interest rate shocks prevail and decrease it when risk premium (exchange rate) shocks dominate. Under a realistic calibration of the stochastic environment FCLs are welfare reducing. Finally, we show that regulatory policies that correct the share of FCLs may cause a short term slowdown. JEL: E32, E44, E58
A Robust Equalization Feature for Language Recognition

Wenjie Song, Chen Chen, Tianyang Sun, Wei Wang* School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China 64228128@qq.com, 794452272@qq.com, sun_tianyang@yahoo.com, wangwei_hitwh@126.com Abstract:The performance of language recognition system is mainly determined by feature extraction and model training. In this paper, a robust equalization feature for language recognition is proposed, which utilizes the common features of the speech spectrum mean vector to calculate a global mean vector. The spectrum mean vector of each segment is equalized on the global mean vector, and the equalization features are obtained. In model training, Gated Recurrent Unit (GRU) of Recurrent Neural Network (RNN) is applied to language recognition, in which GRU can reduce the amount of computation and shorten the training time. The experimental results show that the proposed method outperforms the baseline system on the NIST LRE 2007 corpus.
Evaluation of microbial contamination of feces and soil on a laying-hen farm depending on sampling site and season

The objective of the present study was to evaluate soil collected from a laying-hen farm and bird manure according to the season of the year and sampling site. Soil samples were taken at the poultry facility wall and at the distances of 15 m and 45 m from the building. Bird feces samples were collected inside the poultry house at the entrance and at 1/4 and 1/2 length of the building. Soil and bird feces samples were evaluated by bacteriological qualitative and quantitative analyses. The largest bacterial load was determined in the samples taken at the poultry facility wall in December/January. Soil microbial contamination degree was low. The highest bacterial count in bird manure was found in the samples collected at 1/2 length of the hen house at the end of December/January. The qualitative study of bird feces showed the presence of E. coli bacteria all through the research period and Enterobacter spp. in the samples taken from July until September. Microbial contamination of soil environment and bird feces is most likely to be affected by winter period as at that time the highest microbial population can be determined. This fact may be linked to the prevailing climatic and microclimatic conditions.
Prediction of speech masking release for fluctuating interferers based on the envelope power signal-to-noise ratio

The speech-based envelope power spectrum model (sEPSM) presented by Jo/ rgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope signal-to-noise ratio (SNRenv) after modulation-frequency selective processing, which accurately predicts the speech intelligibility for normal-hearing listeners in conditions with additive stationary noise, reverberation, and nonlinear processing with spectral subtraction. The latter condition represents a case in which the standardized speech intelligibility index and speech transmission index fail. However, the sEPSM is limited to conditions with stationary interferers due to the long-term estimation of the envelope power and cannot account for the well known phenomenon of speech masking release. Here, a short-term version of the sEPSM is presented, estimating the envelope SNR in 10-ms time frames. Predictions obtained with the short-term sEPSM are compared to data from Kjems et al. [(2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mi.
Peace, Terrorism, or Civil Conflict? Understanding the Decision of an Opposition Group

When do opposition groups decide to mount a terrorism campaign and when do they enter an open civil conflict against the ruling government? This paper models an opposition group's choice between peace, terrorism, and open conflict. Terrorism emerges if executive constraints are intermediate and rents are sizeable. Open conflict is predicted to emerge under poor executive constraints. Analyzing country-level panel data firmly supports these hypotheses, even when relying on within-country variation only in a fixed-effects framework. In particular, both the incidence of terrorism and the likelihood of terrorism onset increase under intermediate executive constraints (following an inverted U-shape) and if large rents are available from natural resources, oil, or foreign development assistance. A one-standard-deviation increase in rents raises casualties by approximately 15 percentage points. Related to civil conflict, moving from an authoritarian regime to comprehensive executive constraints is associated with a decrease in the number of battle-related deaths by approximately 74 percentage points. These findings can help us to better understand and anticipate the underlying decision of opposition groups and their choice between peace, a terrorism campaign, and open conflict.
Collaborative Sleep Mechanism between Cross-domain Nodes in FiWi Network Based on Load Balancing and QoS Awareness

Fiber-Wireless Broadband Access Network (FiWi) not only has the advantages of high bandwidth and low data loss in optical network, but also has the characteristics of mobility and flexibility in wireless network. However, a large number of active devices in the FiWi network cause high energy consumption. Aiming at saving energy of FiWi network, this paper studies the collaborative sleep mechanism between cross-domain nodes in FiWi network based on load balancing and QoS awareness. Firstly, the energy consumption model of FiWi network is established to describe the device startup/shutdown energy consumption and service forwarding energy consumption. Secondly, a service route planning method for FiWi network based on load balancing and priority is proposed. The method is implemented by dividing network regions and allocating end-to-end routes for services within the region. Finally, a collaborative region sleep mechanism between ONU and wireless nodes is proposed. At the same time, the routes are redistributed for the affected services according to the service priority to ensure the accelerated forwarding of high-priority services. The simulation results show that the proposed mechanism can reduce the energy consumption, ensure the load balancing of the network, and improve the transmission rate of high-priority services.
GJI Geomagnetism, rock magnetism and palaeomagnetism Comment on 'Electrical conductivity and crustal structure beneath the central Hellenides around the Gulf of Corinth (Greece) and their relationship with the seismotectonics' by Pham et al.

SUMMARY This comment discusses the analysis of magnetotelluric data from the Corinth Gulf area carried out by Pham et al. It is shown that a consistent analysis should include the conducting sea water of the Gulf, which has a longitudinal conductance of about 2000 S. This was overlooked in the above study. The magnitude of the sea-water effect is demonstrated by 2-D modelling and new induction vector data.
BROADBAND EXTENDED EMISSION IN GRAVITATIONAL WAVES FROM CORE-COLLAPSE SUPERNOVAE

Immediately following their formation, black holes in the core-collapse stage of massive stars are expected to surge in mass and angular momentum by hyper-accretion. Here we describe a general framework of extended emission in gravitational waves from non-axisymmetric accretion flows from the fallback matter of the progenitor envelope. This framework shows (a) a maximum efficiency in the conversion of accretion energy into gravitational waves at hyper-accretion rates exceeding a critical value set by the ratio of the quadrupole mass inhomogeneity and viscosity, with (b) a peak characteristic strain amplitude at the frequency fb = Ωb/π, where Ωb is the Keplerian angular velocity at which viscous torques equal angular momentum loss in gravitational radiation, with hchar ∝ f1/6 at f < fb and hchar ∝ f−1/6 at f > fb. Upcoming gravitational wave observations may probe this scaling by extracting broadband spectra using time-sliced matched filtering with chirp templates, which were recently developed for identifying turbulence in noisy time series.
The Student Management Based on Participants in Improving Quality of Tahfidz Program with Supply Chain Practices

Abstract- Many global supply chains are unequipped to cope with the world we are entering. For that reason, supply chain managers need to shift their attention from cu tting costs to enabling new processes, and make corporations more connected and agile to create value across the enterprise. Student management is very important in improving the quality of education programs in Islamic boarding schools, especially in memorizing Alquran (tahfidz) programs. Tahfidz program provides learning for the students to be disciplined, independent, and good attitude. Islamic boarding schools are one of the educational institutions that conduct non-formal education in the field of Islamic materials. In transferring the knowledge from the teacher to students, Islamic boarding schools have two programs, namely the madrasah diniyyah program for, learning books. Secondly, the Alquran education program (TPQ) for learning the correct and fluent in the reading of the Alquran. Moreover, today there are a lot of Islamic boarding schools that run memorization programs of the Qur'an (Tahfidzul Quran). In order to succeed in the tahfidzul Quran program in Islamic boarding schools, resources that are needed to carry out management activities such as supply chain management. In this case, to support the implementation of the Tahfidzul Qur'an program based on its purpose, a management activity is needed. The management in question is how the institution plans, implements, and conducts evaluation activities. One management that can support the achievement of the objectives of the institution here is the management of students.
Optimal Distributed Resource Allocation in 5G Virtualized Networks

The concepts of network function virtualization (NFV) and end-to-end (E2E) network slicing are two promising technologies empowering 5G networks for efficient, flexible and dynamic network deployment and service management. Optimal resource allocation is one of the challenging problems to address in such networks. In this paper, we propose a resource allocation model for 5G virtualized networks in a heterogeneous cloud infrastructure. In our model, each network slice has a resource demand vector for each of its building virtual network functions (VNFs). We then formulate the optimal resource allocation as a convex optimization problem maximizing the overall system utility as a function of the slice thicknesses with the constraints of the data centers’ resource capacities. The slice thickness variables together with the demand vectors determine the amount of resources allocated to each slice. We further propose a distributed solution for the resource allocation problem based on auction/game theory by forming a resource auction between the slices and the data centers (DCs). It is shown that the resource allocation game has a unique Nash equilibrium and its solution is the same as the solution of the centralized system optimization problem, i.e., in equilibrium the slice thicknesses maximize the overall system utility. Numerical analysis are provided to show the validity of the results, evaluate the convergence of the distributed solution and also comparing the performance of the optimal scheme with heuristic ones.
Did f iscal policy makers know what they were doing ? Reassessing f iscal policy with real-time data

Empirical fiscal policy reaction functions based on ex post data cannot be said to describe fiscal policymakers intentions, since they utilise data which did not exist when their decisions were made. A characterisation of what fiscal policymakers were trying to do requires real time data. This paper compares fiscal policy reaction functions for 14 European countries over the period 1994-2006 using both types of data. We exploit the information contained in real-time and ex post data and develop a new approach to estimate the automatic and discretionary fiscal policy responses to changing economic conditions. This avoids the uncertainties and inaccuracies associated with filtering the data upfront in an attempt to estimate potential output or the structural budget. We find that the often commented upon pro-cyclicality of discretionary policy arises only with ex post data; the real time data suggests that policymakers are seeking to run counter cyclical discretionary policy, but find it hard to do so in practice due to data constraints. Compared to elsewhere in the literature, our model yields lower estimates of the automatic fiscal response and stronger estimates of the discretionary fiscal response to an output gap. JEL Codes: E62 (Fiscal Policy); E61 (Policy Design and Consistency)
FPGA-Assisted Assertion-Based Verification Platform

In this paper, field programmable gate array (FPGA)-assisted verification platform is devised to enhance the assertion-based verification methodology to address the issues of high demand of integrated circuit with the advanced features to be delivered to market within tight Time-To-Market. The concept of SystemVerilog Assertion (SVA) checker generator is introduced to translate non-synthesizable verification coding into hardware so-called assertion checker in Verilog. A lookup table, which comprises of SVA operators mapped to their corresponding synthesizable Verilog coding was developed to generate assertion checker, which produces a single bit 1 when the assertion fails. Collection module implemented using a memory block and an arbiter was devised to be simple and fast enough to collect assertion results from the assertion checker. Since assertion checker can produce assertion result at any time, an arbiter is required to act as an interface between assertion checker and collection module. Case studies have been conducted on the proof-of-concept designs, which are the firstin-first-out (FIFO), up-down counter and Context Adaptive Variable Length Coding (CAVLC) to evaluate the effectiveness of the proposed FPGA-assisted verification platform. In the case studies, we have shown that the proposed FPGA-assisted verification platform works correctly. Besides, we also evaluated the method in area utilizations (ALMs). It has been proven that simulation-based verification time can be reduced for as much as 50% for complexity of VLSI design. Thus, implementing assertions using hardware such as FPGA becomes a solution to alleviate issue of long simulation time.
Modelling Global Burden of Disease Measures in Selected European Countries Using Robust Dynamic Spatial Panel Data Models

The aim of the paper is to study relationships between selected socio‐economic factors and health of European citizens. The health level is measured by selected global burden of disease measures – DALYs (Disability Adjusted Life Years) and its two components: YLL (Years of Life Lost) and YLD (Years Lived with Disability). We identify which factors significantly affect these indicators of health. The empirical study uses a panel data comprising 16 countries mostly from the old‐EU in the period 2003–2013. Fixed‐effects dynamic spatial panel data (DSPD) models are used to account for autocor‐ relations of the dependent variables across time and space. The models are estimated with a novel, modified quasi maximum likelihood Yang method based on M‐estimators. The approach is robust on the distribution of the initial observations. The empirical analysis covers specification, estimation, and verification of the models. The results show that changes in YLD are significantly related to al‐ cohol consumption, healthcare spending, social spending, GDP growth rate and years of education. Exactly the same set of factors is associated with variation in DALYs. Sensitivity of the YLL component to the socio‐economic factors is considerably weaker.
Anomalous Spin Correlations and Mass-Generating Excitonic Instability of Interacting Weyl Fermions

Michihiro Hirata, Kyohei Ishikawa, Genki Matsuno, Akito Kobayashi, Kazuya Miyagawa, Masafumi Tamura, Claude Berthier, Kazushi Kanoda Institute for Materials Research, Tohoku University, Aoba-ku, Sendai 980-8577, Japan Deparment of Applied Physics, University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan Department of Physics, Nagoya University, Chikusa-ku, Nagoya 464-8602, Japan Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
Assessment of dried blood spots for DNA methylation profiling

Background DNA methylation reflect health-related environmental exposures and genetic risk, providing insights into aetiological mechanisms and potentially predicting disease onset, progression and treatment response. An increasingly recognised need for large-scale, longitudinally-profiled samples collected world-wide has made the development of efficient and straightforward sample collection and storage procedures a pressing issue. An alternative to the low-temperature storage of EDTA tubes of venous blood samples, which are frequently the source of the DNA used in such studies, is to collect and store at room temperature blood samples using filter paper engineered for the purpose, such as Whatman FTA® cards. Our goal was to determine whether DNA stored in this manner can be used to generate DNA methylation profiles comparable to those generated using blood samples frozen in EDTA tubes. Methods DNA methylation profiles were obtained from matched EDTA tube and Whatman FTA® card whole-blood samples from 62 Generation Scotland: Scottish Family Health Study participants using the Infinium HumanMethylation450 BeadChip. Multiple quality control procedures were implemented, the relationship between the two sample types assessed, and EWASs performed for smoking status, age and the interaction between these variables and sample storage method. Results: Dried blood spot (DBS) DNA methylation profiles were of good quality and DNA methylation profiles from matched DBS and EDTA tube samples were highly correlated (mean r = 0.991) and could distinguish between participants. EWASs replicated established associations for smoking and age, with no evidence for moderation by storage method. Conclusions Our results support the use of Whatman FTA® cards for collecting and storing blood samples for DNA methylation profiling. This approach is likely to be particularly beneficial for large-scale studies and those carried out in areas where freezer access is limited. Furthermore, our results will inform consideration of the use of newborn heel prick DBSs for research use.
Introducing Research-based Instructional Strategies in a Rural Engineering College in India

Dr Pradeep Waychal is a founder trustee of Guruji Education Foundation that provides holistic support to the higher education of underprivileged students and a visiting professor of Engineering Education at CRICPE of Western Michigan University, US. Earlier, Dr Waychal has worked at Patni Computer Systems for 20 years in various positions including the head of innovations, NMIMS as the director Shirpur campus, and at College of Engineering Pune (COEP) as the founder head of the innovation Center.
Applying Deep Neural Networks for Duty Cycle Estimation

A pro-active spectrum usage prediction is a key technique in decision making and spectrum selection for dynamic spectrum access systems. This work focuses on the estimation of the duty cycle (DC) metric to reflect spectrum usage. The prediction is formulated as a time-series regression problem. Deep neural networks (DNNs) is selected to obtain accurate predictions of channel usage. Namely, Multilayer perceptron (MLP), Long short term memory (LSTM) and a hybrid model based on convolutional neural network followed by an LSTM (CNN-LSTM) layer are selected. The hyper-parameters selection has been optimised utilising both grid search and multi-stage grid search. Moreover, in many cases, the spectrum usage is measured on a smaller time scale from the actual required one. Hence, down-sampling and averaging is required. Averaging operation results in flattening the data and losing essential features to assist DNN to predict the channel usage. We show what is the minimum required time resolution to have a pro-active prediction system. Then, we propose utilising feature engineering to improve prediction accuracy. All the proposed DNNs approaches are trained on real-life measurements. The experimental evaluation demonstrated a high potential of DNNs to learn from previous spectrum usage and accurately predict the spectrum usage. Moreover, adding input features significantly assists the system to achieve accurate predictions in a pro-active manner.
Serving Recurrent Neural Networks Efficiently with a Spatial Accelerator

Recurrent Neural Network (RNN) applications form a major class of AI-powered, low-latency data center workloads. Most execution models for RNN acceleration break computation graphs into BLAS kernels, which lead to significant inter-kernel data movement and resource underutilization. We show that by supporting more general loop constructs that capture design parameters in accelerators, it is possible to improve resource utilization using cross-kernel optimization without sacrificing programmability. Such abstraction level enables a design space search that can lead to efficient usage of on-chip resources on a spatial architecture across a range of problem sizes. We evaluate our optimization strategy on such abstraction with DeepBench using a configurable spatial accelerator. We demonstrate that this implementation provides a geometric speedup of 30x in performance, 1.6x in area, and 2x in power efficiency compared to a Tesla V100 GPU, and a geometric speedup of 2x compared to Microsoft Brainwave implementation on a Stratix 10 FPGA.
A REVIEW OF RECENT APPLICATIONS OF NEAR INFRARED SPECTROSCOPY, AND OF THE CHARACTERISTICS OF A NOVEL PbS CCD ARRAY-BASED NEAR-INFRARED SPECTROMETER

ABSTRACT Near-infrared spectroscopy (NIRS) has been gaining popularity as an analytical tool due to advances in the power of personal computers, which allow the extraction of chemical and physical information about a sample, and the utilization of cost efficient and robust CCD array-based spectrometers. In this review, applications of NIRS are explored, within various fields of analytical chemistry, which take advantage of the inherent rapid analysis time and minimal sample preparation that is possible. For the purposes of illustration, the usefulness and limitations of a novel, PbS array-based spectrometer are described in the context of its application to the analysis of a variety of samples.