Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency control strategies in a renewable energy intensive power system: options for South Africa

Inertia reduction due to high-level penetration of converter interfaced components may result in frequency stability issues. The paper analyses different frequency strategies for both solar photovoltaic (PV) and wind generators to support inertia, and also evaluates the contribution of synchronous condensers (SCs) to the system inertia of the power grid. Decommissioned power plants can potentially be retrofitted to SC mode in order to provide inertia support after they are retired. This paper investigates the various frequency control strategies available to the South Africa power grid in the face of increasing renewable energy integration, and makes a case for the modification of the many mothballed coal-fired power plants to SC mode.
Rhetorical appeals and legitimacy perceptions: How to induce Rhetorical appeals and legitimacy perceptions: How to induce information security policy compliance information security policy compliance

This paper intends to extend Protection Motivation Theory (one of the leading theories in Information Security research) based on innovation diffusion and institutional legitimacy theories. We postulate that legitimacy, in which fear is only a partial representation, is a more comprehensive antecedent to intention to comply with security policies. We argue the use of ethos, pathos, and logos appeals to complement the fear rhetoric traditionally present in information security research to elicit legitimacy judgments and indirectly intention to comply. We propose an experiment in which by manipulating the rhetorical elements of the communication, we can study its impact on legitimacy and ultimately intention to abide by the security policy.
Interaction Design on Interface of Web-Based Virtual Experiment

As an important branch of distance education to realize experiment teaching,Web-based virtual experiment needs strong interactive capability,and a perfect interactive interface is the foundation and guarantee for it.This paper analysed the main elements that decide the interactive capability of Web-based virtual experiment,and brought forward several design principles to improve the performance of interactive interface,and further combining some development examples to describe the detailed design and application schemes.
Real-Time Forward-Looking Skewness over the Business Cycle

This paper measures option-implied skewness for individual ﬁrms and the overall stock market between 1980 and 2020 giving a real-time measure of conditional micro skewness. There are three key results for ﬁrm-level skewness: 1. It is signiﬁcantly procyclical, while market skewness is acyclical; 2. It leads the business cycle, and it is strongly linked to credit spreads, suggesting one potential causal channel; 3. It is signiﬁcantly, and not mechanically, correlated with aggregate volatility, implying that there is a common shock driving them both, which is also linked to the business cycle.
A Comprehensive Taxonomy of PCB Defects

—Printed circuit boards (PCBs) contain complex, minuscule elements, that when defective, can be challenging to detect. The cause of PCB defects can be divided into malicious and non-malicious actions, although both can produce detrimental effects to a board. Malicious attacks on a board can be the result of intellectual property inﬁltration, secure data acquisition, counterfeiting, and denial of service. Non-malicious causes can result in unpredictable behavior or dangerous/unreliable operation. The lack of literature on various types of PCB defects hinders applications involving defect detection and classiﬁcation. The taxonomy proposed in this paper provides structured defect classes, defect image examples, various causes, and subsequent effects in order to create a comprehensive reference for hardware security and assurance purposes. 1
Forced displacement related to the impacts of climate change and disasters

Forced displacement related to the impacts of climate change and disasters is among the greatest global protection issues today. Significant progress has been made in research development and policy responses, but this progress also highlights the amplitude of the remaining challenges. In 2020 alone, disasters drove more than 30 million internal displacements. At a time when climate change is widely recognised as a global emergency, and as the seventieth anniversary of the Geneva Convention will coincide with the publication of the 6th Assessment report of the Intergovernmental Panel on Climate Change (IPCC) and the convening of the 26th conference of the parties to the UN Framework Convention on Climate Change (COP26) in Glasgow, this paper seeks to recognise how far we have come and also how to navigate the way forward.
SnowShoe hare uSe of SIlvIculturally altered conIfer foreStS In the greater yellowStone ecoSyStem

Information about snowshoe hare habitat use in key Canada lynx recovery areas, such as the Greater Yellowstone Ecosystem, is critical for the conservation of lynx. Although research conclusions differ in regard to the types and ages of forests preferred by snowshoe hares, restrictions on silvicultural practice have been implemented by forest managers to protect snowshoe hares in this area. However, some research suggests that regenerating lodgepole pine stands associated with silvicultural treatments benefit snowshoe hares. We evaluated three indices of snowshoe hare use within a timber management area in southwest Montana, inside the Greater Yellowstone Ecosystem (1999–2012) to assess the relative use of forest types. We analyzed: 1) 11 years of data collected from 280 pellet plots using linear mixed models and AICc model selection, 2) 13 years of track counts from 2,202 km of roadway travel using Chi-squared goodness-of-fit tests of proportional segment lengths and the associated cover types, and 3) 76 nights over one winter of live-trapping using a hare/night index. Overall, we observed the greatest use within the youngest two classes of regenerating lodgepole pine stands that were associated with clear cutting and pre-commercial thinning. These results suggest snowshoe hares prefer silviculturally influenced 30–60 years old lodgepole pine forests
Ciprofol: A Novel Medication from Development towards Clinical Use

most common adverse reactions elicited by propofol [5]. Therefore, in order to find new medications that can overcome these limitations and have the anesthetic effect similar to propofol, Haisco Pharmaceutical Group Co., Ltd. independently developed the new anesthetic medication HSK3486 (ciprofol) [6,7], which is expected to become a widely used anesthesia/sedation medication in clinical practice. This review summarizes the current relevant research literature and clinical trial information available globally, so as to facilitate the readers to understand its mechanism of action and clinical characteristics, and thereby provide the theoretical basis for its further use in clinical practice.
Physical causation

Causation is a frustrating subject. Suppose one begins with some promising idea such as that causation is counterfactual dependence or statistical relevance. One then develops this idea with care and intelligence, revises and improves it to cope with criticisms, and by the time one is finished, sane people will be looking elsewhere. If one wants conclusive reasons to reject the counterfactual theory of causation, one can do no better than to read Lewis’ (1986) many postscripts. If one wants the best refutation of a probabilistic theory of causation, then one should read my colleague, Ellery Eells’ (1991) magisterial defense. In Physical Causation, Phil Dowe performs the same service for physical process/interaction theories of causation. Although he does a superb job at clearing away some objections to the theory, by the time Dowe is done, I think it is evident that his conserved quantity theory of causation is not tenable. Causation continues to stump us all. In saying this, I do not at all mean to imply that Dowe has nothing to teach us. On the contrary, ‘‘failures’’ such as Lewis’, Eells’, and Dowe’s are proud moments for philosophy. In learning just how counterfactual, probabilistic, and process/ interaction theories fail, we learn a great deal about causation. What we learn does not constitute a ‘‘theory. ’’ It is not a set of necessary and sufficient conditions for ‘‘C causes E:’’ But it is knowledge all the same. There are important lessons to learn concerning how causation escapes our grasp, and these lessons are best learned from those who have reached the furthest. Dowe’s Physical Causation has a great deal to teach everyone who seeks to understand causation.
Combining Performance and Diversity Measures for Optimizing Classification Ensembles via a Genetic Algorithm in the miRNA-Target Prediction Problem

MicroRNAs, also called miRNAs, are a large family of non-coding RNAs of approximately 22 nucleotides (nt) in length, which act as post-transcriptional gene silencers via translational repression or degradation of targets mRNAs, and have an important role in metabolism and genesis of different genetic diseases, such as cancers. The miRNA target prediction problem is considered a difficult challenge in the molecular biology area. There are millions of possible miRNA-mRNA possible combinations, and to experimentally find the functional combinations takes a large quantity of effort, therefore time and investment. The scientific community is actively researching computational approaches to overcome this cost with Machine Learning and their predictive models to better understand the interactions between miRNA-mRNA, and how they influence metabolic and disease processes. The purpose of this work is to study the effect of combining performance and diversity measures in a Genetic Algorithm’s (GA) fitness function that learns the best combination of classifiers in an heterogeneous ensemble classifier in the miRNA-Target prediction problem. Through experimentation, we’ve concluded that the challenge presented by the unbalanced and relatively small available datasets overshadows the possible benefits that the diversity measure could bring to the GA fitness function. Although the ensemble optimization combining performance and diversity measures has achieved better solutions than performance-based optimization in some cases, on average, the former solution did not surpass the latter. This doesn’t allow us to conclude if the combination of performance and diversity measures results in better ensembles or not in our problem.
Three-dimensional model reconstruction from industrial computed tomography-scanned data for reverse engineering

The recent growth of industrial computed tomography (CT) scanning systems facilitates volumetric data acquisition for complete industrial components in a non-destructive manner. A potential application of this technology is reverse engineering. However, reconstructing a computer-aided design (CAD) model using industrial CT-scanned data involves many problems. In this paper, we present a semi-automatic method for reconstructing a CAD model from industrial CT-scanned data for reverse engineering. First, the methods to generate a point cloud and feature points from industrial CT-scanned data are presented. Then, two integrated solutions, namely surface feature-based strategy and geometric primitive feature-based strategy, are introduced to reconstruct the surfaces. Finally, modelling operations such as surface trimming and surface deformation are performed to generate the final model. A variety of industrial components were tested to demonstrate the applicability of our method. We also conducted an experiment to validate the accuracy of our method.
Supplemental Material for “Higher-Order Weyl-Exceptional-Ring Semimetals”

Tao Liu,1, ∗ James Jun He,2, ∗ Zhongmin Yang,1, 3, 4, † and Franco Nori5, 6, 7, ‡ School of Physics and Optoelectronics, South China University of Technology, Guangzhou 510640, China RIKEN Center for Emergent Matter Science, Wako, Saitama 351-0198, Japan South China Normal University, Guangzhou 510006, China State Key Laboratory of Luminescent Materials and Devices and Institute of Optical Communication Materials, South China University of Technology, Guangzhou 510640, China Theoretical Quantum Physics Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Saitama 351-0198, Japan RIKEN Center for Quantum Computing (RQC), Wako-shi, Saitama 351-0198, Japan Department of Physics, University of Michigan, Ann Arbor, Michigan 48109-1040, USA
LTE Uplink Transmission

LTE and LTE-Advance communication are based on the uplink reference signals to estimate the channel characteristics. A split transmission of sounding and demodulation signaling will cause many constraints; such as layers and reference signal symbols interferences, increase in delay and reduction in the overall throughput of the LTE uplink transmission. In this paper, we propose an energy efficient LTE uplink transmission by eliminating the demodulation reference signal (DM-RS) information from the LTE uplink resource grid. Initially, the DM-RS signaling data is eliminated from the data resource grid to provide spare capacity for data to increase the data rate within the same energy consumption. After that, the DM-RS signaling information within SRS signaling symbols is amalgamate. Finally, the model of single value sounding reference signal (SV-SRS) is designed to merge the DM-RS features in SRS symbols, which are helpful to estimate the fine channel parameters for LTE downlink transmission. SV-SRS also overcomes the symbols and channel interference to enhance the overall throughput and reduces the BER of LTE uplink system. The simulation results of proposed strategy show that the SV-SRS improvement in the LTE uplink data by eliminating the DM-RS symbols. 
Ekstraksi Sinyal EEG Menggunakan Koefi sien dari Subband Transformasi Wavelet Diskrit (Extraction of EEG Signals using Subband Coefficients of the Discrete Wavelet Transforms)

Penelitian ini berfokus pada ekstraksi ciri untuk sinyal Electro Encephalo Graph (EEG) menggunakan metode Diskrit wavelet Transform. Sinyal EEG tersebut digunakan untuk menggerakkan kursor ke atas dan kursor ke bawah. Pada setiap subband dari gelombang sinyal Electro Encephalo Graph (EEG) diambil nilai rata-rata untuk dijadikan sebagai ciri dari sinyal EEG. Backpropagation Neural Network digunakan sebagai klasifi kasi sinyal EEG untuk menentukan apakah kursor bergerak keatas atau kursor bergerak ke bawah. Data yang digunakan dalam penelitian ini adalah data EEG yang berasal dari BCI kompetisi 2003 (BCI Kompetisi 2003). Pengambilan keputusan dilakukan dalam dua tahap. Pada tahap pertama, nilai rata-rata pada setiap subband wavelet digunakan sebagai ekstraksi ciri dari data sinyal EEG. Ciri ini sebagai input bagi Backpropagation Neural Network. Pada tahap kedua proses klasifi kasi ke dalam dua kelas kelas 0 (untuk kursor ke atas) dan kelas 1 (untuk kursor ke bawah), terdapat 260 data training fi le sinyal EEG dan 293 dari data testing fi le sinyal EEG, sehingga keseluruhan menjadi 553 fi le data sinyal EEG. Hasil yang diperoleh untuk pengklasifi kasian sinyal EEG adalah 77,2 % dari data sinyal yang diuji.
Analysis of the influence of an upstream rudder over the wake features of a submarine propeller

Large-Eddy Simulation is utilized to analyze the effect of an upstream rudder on the wake features of a submarine propeller. Three incidence conditions of the rudder, relative to the free-stream, are considered. Results are also compared with those of earlier similar computations in open-water conditions. The overall approach on the same propeller was validated by an earlier study on the openwater configuration and the same advance coefficient, via comparisons with Particle Image Velocimetry experiments of the wake flow and dynamometric measurements on the parameters of global performance. Results reported in this work demonstrate that the disturbance at the inflow of the propeller does not change substantially the topology of the largest coherent structures within the near wake (the tip and hub vortices). In addition, as long as the flow over the rudder keeps attached, the levels of fluctuations downstream of the propeller are only slightly increased and thus the perturbation of the inflow keeps small. However, at the largest simulated incidence condition the separation occurring over the suction side of the hydrofoil causes instead more substantial changes in wake turbulence, although also in that case the near wake coherence of tip and hub vortices is almost unchanged. At the same condition, downstream of the instability of the wake system, the interaction with the vortices shed from the ends of the hydrofoil further increases the unsteady nature of the wake flow and the extent of the flow region affected by large values of turbulent fluctuations.
Design Process Modeling of Hydraulic Manifold Blocks Based on Generalized Assembly

A modeling method of design process of hydraulic manifold blocks ( HMB) was studied to improve the design efficiency and quality. Based on analyses of the main design activities and function model of HMB design process, the concept of generalized assembly was introduced, so that the design process, including design activities, middle and final results, was described with the pattern of components or parts in the assembly model with the aid of assembly technology and association among components or parts of Computer-Aided Design software. And a generalized assembly platform for design of HMB was constructed. The design process of a concrete HMB which has been finished on the prototype software of rapid design of HMB testifies that the design process model of HMB based on generalized assembly can completely record the information of design process, keep design association, improve design efficiency and manage design changes easily.
Asset Purchases and Default-Inflation Risks in Noisy Financial Markets

This paper studies how central banks’ asset purchases (APs) of nominal public debt affects perceived default and inflation risks when investors learn from market prices. We design a stylised model of monetary-fiscal interactions where a government issues nominal debt and repays it by collecting distortionary taxes, and a central bank issues money and buys bonds at market prices. Bond pricing takes place in financial markets and is disciplined by private arbitrage against money and a safe real asset. For a given market valuation, a stochastic and unobservable fundamental determines the government decision to default, which affects nominal bond returns. The return on money – and thus inflation – depends instead on the composition of the central bank balance sheet. In particular, when the central bank invests in bonds, a default generates inflation, which reduces the real value of debt service even further. In our framework, APs are either irrelevant or reduce social welfare in the absence of beliefs heterogeneity. With heterogeneous beliefs instead we show that a positive amount of APs is optimal and increases welfare. This happens through two main channels. First, by crowding out the asset demand of more pessimistic agents, APs have a positive price effect which lowers interest rates, debt service and tax distortions in all states. This leverage on market optimism amplifies the beneficial effect of unexpected inflation in default states, taming the symmetric harmful effect of unexpected deflation in repayment states. Second, APs have a negative effect because they increase the precision of market information in default states. This makes surprise default less likely to happen, reducing the scope for beneficial unexpected inflation. We show that the net welfare effect of the two channels is positive when APs are small, and becomes negative as APs increase and the precision effect eventually overturns the benefits of leverage on optimism.
Exponential escape efficiency of SGD from sharp minima in non-stationary regime

We show that stochastic gradient descent (SGD) escapes from sharp minima exponentially fast even before SGD reaches stationary distribution. SGD has been a de-facto standard training algorithm for various machine learning tasks. However, there still exists an open question as to why SGDs find highly generalizable parameters from non-convex target functions, such as the loss function of neural networks. An"escape efficiency"has been an attractive notion to tackle this question, which measures how SGD efficiently escapes from sharp minima with potentially low generalization performance. Despite its importance, the notion has the limitation that it works only when SGD reaches a stationary distribution after sufficient updates. In this paper, we develop a new theory to investigate escape efficiency of SGD with Gaussian noise, by introducing the Large Deviation Theory for dynamical systems. Based on the theory, we prove that the fast escape form sharp minima, named exponential escape, occurs in a non-stationary setting, and that it holds not only for continuous SGD but also for discrete SGD. A key notion for the result is a quantity called"steepness,"which describes the SGD's stochastic behavior throughout its training process. Our experiments are consistent with our theory.
Refinements of strong multiplicity one for $\mathrm{GL}(2)$

For distinct unitary cuspidal automorphic representations π1 and π2 for GL(2) over a number field F and any α ∈ R, let Sα be the set of primes v of F for which λπ1(v) 6= eλπ2(v), where λπi(v) is the Fourier coefficient of πi at v. In this article, we show that the lower Dirichlet density of Sα is at least 1 16 . Moreover, if π1 and π2 are not twist-equivalent, we show that the lower Dirichlet densities of Sα and ∩α Sα are at least 2 13 and 1 11 , respectively. Furthermore, for non-twist-equivalent π1 and π2, if each πi corresponds to a non-CM newform of weight ki ≥ 2 and with trivial nebentypus, we obtain various upper bounds for the number of primes p ≤ x such that λπ1(p) 2 = λπ2(p) . These present refinements of the works of Murty-Pujahari, Murty-Rajan, Ramakrishnan, and Walji.
Microelectrode Ion Flux Estimation (MIFE) technique in microbiology: A cutting edge approach to study bacterial stress responses

The idea of measuring net ion fluxes at the proximity of a living organism using non-invasive microelectrodes was first proposed by Prof B Lucas at the NATO Advanced Studies Institute in Italy in 1984. This led to creation of the National Vibrating Probe Facility at Woods Hole, USA, which is widely used for electrophysiological studies in medical and animal physiology research.An alternative approach was developed by Dr Ian Newman (School of Mathematics and Physics, University of Tasmania) and resulted in the construction of the MIFER system, which is now commercially available. Since the late 1990s, MIFE has been successfully applied to the study of various aspects of membrane-transport processes in plants and protoplasts derived from the plant tissues.
Small Batch Sizes Improve Training of Low-Resource Neural MT

We study the role of an essential hyper-parameter that governs the training of Transformers for neural machine translation in a low-resource setting: the batch size. Using theoretical insights and experimental evidence, we argue against the widespread belief that batch size should be set as large as allowed by the memory of the GPUs. We show that in a low-resource setting, a smaller batch size leads to higher scores in a shorter training time, and argue that this is due to better regularization of the gradients during training.