Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative electron probe microanalysis of carbon in binary carbides

Introductory investigations performed in order to make quantitative electron-probe microanalysis of very light elements such as boron, carbon, nitrogen or oxygen possible are described. The practical problems encountered in this kind of work are discussed in detail and, where possible, solutions are proposed. It is shown that with very light elements such as carbon it is no longer permitted to measure x-ray intensities at the position of the maximum of the emission peak as the shape of the carbon Ka peak is subject to strong alterations, depending on the type of chemical bond involved. As a consequence, integral measurements have to be performed and it is shown that errors of 3040% can easily be made if this is neglected. The lengthy procedures, connected with integral intensity measurements, can be shortened considerably by the
EJAL Article template

The aim of the study is to show emerging identity performances of Turkish Fulbright foreign teaching language assistants (FLTAs) in social and academic contexts during their sojourn experiences in the US. The grant program brings institutional roles of being a teacher and a learner and social duties of culture transmission in the host country. The dynamic triad of these roles yields negotiated identities manifested through reflections to the experiences of interaction, communication, and participation in the host community. In an attempt to reveal the interplay of these roles, 5 Turkish grantees were interviewed to elicit personal storylines. The narratives were analyzed adopting Davies and Harré’s (1990) positioning theory rooted in discursive psychology relying on Bauman’s (2013) postmodern conception of identity where identity is seen as fluid, multilayered, and negotiated. The participants’ emerging identities formulated in the personal narratives are depicted through the negotiation of self-other positioning. The findings showed that affinity, racial, national, gender, cultural, second language, professional, and learner identities were revealed as emerging identity performances with an intersectional structure. This study provides a useful depiction of the FLTAs' sojourn experiences with a microanalytic eye and recommends covering different aspects with various focal points to better understand the educational and cultural aspects of such sojourn experiences. © 2021 EJAL & the Authors. Published by Eurasian Journal of Applied Linguistics (EJAL). This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (CC BY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Time domain hybrid modulation scheme for visible light communication

Time division multiplexing (TDM) is common in visible light communication system, which means a channel carries two or more services and different services have the same communication demand. If a channel carries two businesses that have different communication requirement, for example, the bit error ratio (BER) for one is 10-3 and for the other is 10-5 , what can be done to help solve the problem. This paper proposes a time-domain hybrid modulation scheme for visible light communication with different service requirements. By appropriately designing a time division multiplexing frame and time slot occupancy ratios of different modulation formats, a continuous adaptation between spectral efficiency and different tiers of BER requirements can be realized for an optical channel. Such a transmission approach is called time domain hybrid modulation (TDHM). Common on-off keying modulation (OOK) and pulse position modulation (PPM) are used in the time domain hybrid modulation scheme in this paper because its simplicity of OOK and high power efficiency of PPM, which can solve the problem of different communication requirements in VLC. In this paper, when the demand of BER for OOK is 10-3 and for PPM is 10-5 , SNR for OOK and PPM are 16dB and 12dB. But if Hybrid modulation is used, the system can satisfy the demand of BER=10-3 when SNR is just 14dB.
University of Birmingham Wall effects for spherical particle in confined shear-thickening fluids

Flow past rigid sphere in cylindrical tubes filled with shear-thickening power law fluids is simulated by Computational Fluid Dynamic (CFD) model in steady-state mode with fixed computational domain. The CFD model is validated with previous researchers‟ work for Newtonian and shear-thinning power law rheologies in both bounded and unbounded mediums. New simulations are executed over flow conditions of Reynolds number, Re: . Wall effects on flow patterns and drag phenomena are investigated and found to be functions of Reynolds number, diameter ratio and flow behaviour index. Numerical results reveal that drag coefficient decreases with the increase in Reynolds number. Contribution on the drag coefficient from pressure force drops with increasing flow behaviour index, and is generally smaller than that from friction force. Length of recirculation wake increases with enhancement in flow behaviour index in the case of less severe wall effects. Wall effects on flow can be neglected if the wall is far enough from the particle.
Portfolio Efficiency and Discount Factor Bounds with Conditioning Information : An Empirical Study November 2005

Stochastic discount factor bounds provide a useful diagnostic tool for testing asset pricing models by specifying a lower bound on the variance of any admissible discount factor. In this paper, we provide a unified derivation of such bounds in the presence of conditioning information, which allows us to compare their theoretical and empirical properties. We find that, while the location of the ‘unconditionally efficient (UE)’ bounds of Ferson and Siegel (2003) is statistically indistinguishable from the (theoretically) optimal bounds of Gallant, Hansen, and Tauchen (1990) (GHT), the former exhibit better sampling properties. We demonstrate that the difference in sampling variability of the UE and GHT bounds is due to the different behavior of the efficient return weights underlying their construction. JEL Classification: G11, G12
The Relationship Between Maternal Childhood Emotional Abuse / Neglect and Second Generation Parenting Outcomes : A Systematic Review

This paper reviews the evidence concerning the association between reported maternal childhood experience of emotional abuse and/or neglect and subsequent parenting outcomes. Relevant studies were identified through a systematic search of four electronic databases using a pre-determined keyword search. Reference lists of included papers were reviewed and key authors in the field contacted to ascertain whether other papers were available. Twelve studies which met our eligibility criteria were included for review. Tentative support was found for a relationship between maternal childhood emotionally abusive/neglectful experiences and a range of adverse parenting outcomes, including increased parenting stress and maltreatment potential, lower empathy and greater psychological control. However, limitations within the research (e.g. small sample sizes, retrospective designs) reduce the confidence with which we can draw firm conclusions. Recommendations are offered for future research together with an outline of clinical implications arising from this review. Key Practitioner messages:  There is tentative evidence that maternal childhood experience of emotional abuse/neglect may be associated with subsequent deficits in parenting.  Maternal childhood experiences of being parented should be considered when attempting to make sense of children's difficulties and/or problems in the parentchild relationship.
A Low Cost Indoor Positioning System Using Bluetooth Low Energy

In this paper, we present a Bluetooth Low Energy (BLE) based indoor positioning system developed for monitoring the daily living pattern of old people (e.g. people living with dementia) or individuals with disabilities. The proposed sensing system is composed of multiple sensors that are installed in different locations in a home environment. The specific location of the user in the building has been pre-recorded into the proposed sensing system that captures the raw Received Signal Strength Indicator (RSSI) from the BLE beacon that is attached on the user. Two methods are proposed to determine the indoor location and the tracking of the users: a trilateration-based method and fingerprinting-based method. Experiments have been carried out in different home environments to verify the proposed system and methods. The results show that our system is able to accurately track the user location in home environments and can track the living patterns of the user which, in turn, may be used to infer the health status of the user. Our results also show that the positions of the BLE beacons on the user and different quality of BLE beacons do not affect the tracking accuracy.
Has international financial co-movement changed? Emerging markets in the 2007-2009 financial crisis

Emerging market (EM) assets have historically been regarded as inherently risky and particularly vulnerable to international shocks that result in a general increase in investor risk perceptions. In this paper, we assess the ongoing relevance of this view by examining the linkages between EM and non-EM stock and bond markets in the past two decades, with a focus on how these relationships played out during the global financial crisis of 2007-2009. We evaluate how these linkages have evolved over the period 1992-2009, through statistical tests of whether the volatility of EM financial markets changed - either in their response to international shocks originating in advanced economy markets or in their independent fluctuations. We find that over the longer period EM bond and stock prices have on average moved in the same direction as the prices of non-EM risky assets, and this co-movement has persisted. However, these relationships have evolved somewhat over time. Both EM sensitivity to international shocks and EM-specific volatility in EM sovereign bond spreads appear to have decreased over time, consistent with the greater fundamental stability of EM economies and perhaps a reduced inclination by investors to sell off EM assets in response to a rise in risk perceptions. Somewhat in contrast, while an upward trend in co-variation between EM and non-EM stock prices suggests an increasing degree of global market integration, idiosyncratic volatility has declined, consistent with a diminished level of locally-driven risk in these markets. In addition, the response of EM asset prices to the latest financial crisis appears to be moderate in comparison to historical experience. This evidence may reflect reduced EM vulnerability to external shocks in general, which is consistent with some encouraging improvements in the underlying fundamentals of EM economies over the decade preceding the onset of the crisis.
Direct Learning of Sparse Changes in Markov 1 Networks by Density Ratio Estimation ? 2

We propose a new method for detecting changes in Markov 10 network structure between two sets of samples. Instead of naively fitting 11 two Markov network models separately to the two data sets and figuring 12 out their difference, we directly learn the network structure change by 13 estimating the ratio of Markov network models. This density-ratio formu14 lation naturally allows us to introduce sparsity in the network structure 15 change, which highly contributes to enhancing interpretability. Further16 more, computation of the normalization term, which is a critical compu17 tational bottleneck of the naive approach, can be remarkably mitigated. 18 Through experiments on gene expression and Twitter data analysis, we 19 demonstrate the usefulness of our method. 20
Direct Learning of Sparse Changes in 2 Markov Networks by Density Ratio Estimation

5 We propose a new method for detecting changes in Markov network structure be6 tween two sets of samples. Instead of naively fitting two Markov network models 7 separately to the two data sets and figuring out their difference, we directly learn the 8 network structure change by estimating the ratio of Markov network models. This 9 density-ratio formulation naturally allows us to introduce sparsity in the network 10 structure change, which highly contributes to enhancing interpretability. Further11 more, computation of the normalization term, which is a critical bottleneck of the 12 naive approach, can be remarkably mitigated. We also give the dual formulation 13 of the optimization problem, which further reduces the computation cost for large14 scale Markov networks. Through experiments, we demonstrate the usefulness of our 15 method. 16 An earlier version of this work was presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD2013) on Sep. 23-27, 2013. 1 Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation 2
Borders And Boundaries : Women In India ' s Partition

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Sediment classification using Sub-bottom profiler

Sub bottom profilers are commonly used as mapping tool for the seafloor and sub-bottom structure in the upper few meters of the seafloor. Their recent enhanced performance in terms of resolution adds the potential to classify the sediment layers as well. In this research, the seabed surface and sub layers classification are investigated using model based techniques. The remote sediment classification technique of the seabed surface is achieved by matching the back scatter measurements to the predicted backscatter intensity of the model. The model simulates the returned signals of a monostatic sub bottom profiler operating at 100 kHz. The back scattering strength in the angle domain is estimated using the APL-UW backscattering model. The matching procedure was applied on averaged echo envelopes performed by Hilbert transform. The averaging process is essential to reduce the stochastic variability of the acquired data. The sub layers data was obtained by operating frequencies of (5, 10 and 15 kHz). The layer classification was achieved by estimating the geoacoustic parameters such as reflectivity and impedance contrast. Two techniques were investigated based on a reflectivity model. The first technique is an extension work of D.Simons [11] which aims to estimate the reflection coefficients via the received and transmitted energy ratio. The second technique is an implementation of a similar approach but applies the attenuation on the received frequency components in place of the nominal components. Both models accounted for energy propagation and its corresponding geometrical and sediment attenuation losses. The classification techniques were carried out to a dataset that was acquired in the Baltic Sea near Rostock in 2004. The acquired dataset is characterized by various bottom types such as mud, sand and coarse sediments. The general description of the acquired areas was used as a reference for the final results. Due to the lack of core samples, the classification was evaluated by comparing the results of the backscatter to the energy model. The results were consistent with the general description of the dataset. However, the matching process of the backscatter model is a cumbersome and very sensible to the envelope averaging technique. Averaging the reflected signals from the soft sediments has to ensure to preserve the surficial and volume back scatter information. On the other hand, at rough surfaces, the late arrivals are likely to be irregular reflections or noise that has to be averaged to avoid ambiguous results. The initial results of sub layers reflection models were consistent with the data description. However, due to the high resolution of the sub bottom profile, the computation procedure can easily fail by missing sub layers. In order to reduce the probability of missing layers, an overlapping window concept was implemented, where the reflection coefficients are estimated at shorter intervals. The methods investigated here leaves room for further optimization through model adjustment such as signal interference, backscatters and error propagation.
(Invited) Predictive analytics for cryogenic CMOS in future quantum computing systems

This paper presents predictive techniques that suggest a path to accelerated analysis and optimization of the yield of ultra-low power analog/mixed signal designs operating at cryogenic temperatures for use in future quantum computing applications. Analysis of 6σ variation is accelerated using mixture importance sampling (MixIS) techniques, with key studied specifications being compliance to spurious tone requirements at the quantum state controller output and optimization of design power consumption, both in the context of the high levels of modeling and matching uncertainties associated with cryogenic circuit design.
Design and Evaluation of a High-Performance Extensible DC-DC Converter Integrated with ANN Based MPPT Controller

Boosting the low voltage output to achieve the required utility voltage is one of the main issues with solar photovoltaic sources. To effectively utilize solar energy at the highest power, point these systems frequently utilize high-performance boost DC-DC converters as interfacing circuits to fulfill the load demand. A novel expandable non-isolated step-up DC-DC converter with 94% transformation efficiency is reported here. Moreover, a comparison of converters in terms of efficiency, gain in output voltage, the potential stress on semiconductors, and operating principle among various topologies has been executed. The basic design of the suggested converter features a large voltage gain (more than 20) and lessened stress on the diode and Metal Oxide Semiconductor Field Effect Semiconductor (MOSFET) as compared to the typical existing topology. Artificial Neural Networks (ANN) based algorithm is used in the construction of Maximum Power Point Tracking (MPPT) controllers as they are thought to be a faster, more accurate, and more reliable estimating technique than other techniques. Utilizing MATLAB/SIMULINK, simulation results are performed to verify theoretical notions.
Formulation and evaluation of self microemulsifying drug delivery system of carbamazepine

Carbamazepine is a common antiepileptic drug and due to its poor aqueous solubility absorbed very slowly and erratically after oral administration. To enhance its solubility, dissolution rate self microemulsifying drug delivery system (SMEDDS) was formulated and evaluated. The solubility of carbamazepine was determined in various vehicles. Pseudoternary phase diagrams were evaluated for microemulsification existence area, and the release rate of carbamazepine was investigated using an in vitro dissolution test. SMEDDS formulations were tested for microemulsifying properties and the resultant microemulsions were evaluated for clarity, precipitation and particle size distribution. Formulation development and screening was done based on results obtained from phase diagrams and characteristics of resultant microemulsion. The optimized formulation was studied for in vitro study and was found that the formulation containing Labrafac CC (28.5%), Tween 60 (53.64%) propylene glycol:ethanol (1:1) showed a complete release in 30 minutes as compared with the pure drug which showed a limited dissolution rate. The stability studies found that the formulations were stable over period of 3 months. Thus the study confirmed that the SMEDDS formulation can be used as a possible alternative to traditional oral formulation of carbamazepine to improve its solubility and dissolution rate.
Development of Energy Management Information System (EMIS) for Energy-Saving Awareness

Anticipated surge in electricity expenses within the confines of the International Islamic University of Malaysia (IIUM) campus stems from the pervasive absence of energy conservation consciousness among the IIUM community. On account of the rise of energy consumption, energy wastage happens, resulting in emission of greenhouse gas and carbon that harms the environment. An Energy Management System (EMS) under the control of IIUM Development Division does exist. However, this system is exclusively accessible to the said division, and the data it encompasses is intricate in nature. Hence, the primary objective of this project is to construct an Energy Management Information System (EMIS) with the aim of fostering energy-saving awareness among the IIUM Community, specifically emphasizing the Kulliyyah of Engineering (KOE), through the dissemination of pertinent information via the system. Based on the EMIS (Energy Management Information System) developed specifically for this project, it can be inferred that there is a notable enhancement in the level of energy-saving consciousness within the IIUM community in KOE as indicated by the conducted survey.
Trial by Media: An Empirical Investigation of Corporate Reputation and Stock Returns in Australia

This article examines whether investors are able to generate abnormal risk-adjusted returns in the Australian market based on media-specific firm reputational factors under market uncertainty between 2004 and 2012. The findings suggest that after controlling for crisis-centric time periods and market risk factors, contrarian trading strategies produce abnormal returns for poor corporate reputation firms but not for their good corporate reputation counterparts. Corporate reputation may be a driver of performance for poorly performing Australian firms and could be considered a stimulus for trading activity due to its explanatory capabilities.
Bumblebee: A MemCache Design for Die-stacked and Off-chip Heterogeneous Memory Systems

Emerging die-stacked memories can provide higher bandwidth than traditional off-chip DRAM and serve as an off-chip DRAM cache or part of OS-visible memory (POM). This paper presents Bumblebee, a new hybrid memory architecture combining the advantages of both DRAM cache and POM. The ratio of DRAM cache to POM is adjustable in real time to better exploit both temporal and spatial locality benefits for different memory access patterns. Our evaluations indicate at least 35.2% performance improvement and 10.9% ∼ 20.1% less memory dynamic energy consumption for Bumblebee over state-of-the-art designs, as well as orders of magnitude less metadata storage space.
ZoneKV: A Space-Efficient Key-Value Store for ZNS SSDs

In this paper, we propose a new space-efficient key-value store called ZoneKV for ZNS (Zoned Namespace) SSDs. We observe that existing work on adapting RocksDB to ZNS SSDs will cause fragmentation of zones and severe space amplification. Thus, we propose a lifetime-based zone storage model and a level-specific zone allocation algorithm to store SSTables with a similar lifetime in the same zone. We evaluate ZoneKV on a real ZNS SSD. The results show that ZoneKV can reduce up to 60% space amplification and maintain higher throughputs than two competitors, RocksDB and ZenFS.