Miracle-dz/UniFAR-FTUs huggingface dataset:
Low voltage ride-through of single-phase transformerless photovoltaic inverters

Transformerless photovoltaic (PV) inverters are going to be more widely adopted in order to achieve high efficiency, as the penetration level of PV systems is continuously booming. However, problems may arise in highly PV-integrated distribution systems. For example, a sudden stoppage of all PV systems due to anti-islanding protection may trigger grid disturbances. Thus, standards featuring with ancillary services for the next generation PV systems are under a revision in some countries. The future PV systems have to provide a full range of services as what the conventional power plants do, e.g. Low Voltage Ride-Through (LVRT) under grid faults and grid support service. In order to map future challenges, the LVRT capability of three mainstream single-phase transformerless PV inverters under grid faults are explored in this paper. Control strategies with reactive power injections are also discussed. The selected inverters are the full-bridge inverter with bipolar modulation, full-bridge inverter with DC bypass and the Highly Efficient and Reliable Inverter Concept (HERIC). A 1 kW single-phase grid-connected PV system is analyzed to verify the discussions. The tests confirmed that, although the HERIC inverter is the best candidate in terms of efficiency, it is not very feasible in case of a voltage sag. The other topologies are capable of providing reactive current during LVRT. A benchmarking of those inverters is also provided, which offers the possibility to select appropriate devices and to further optimize the system.
Modulation spectrum factorization for robust speech recognition

This paper presents a novel approach to improving the noise robustness of speech features built on top of nonnegative matrix factorization (NMF). To do this, we employ NMF to extract a common set of basis spectral vectors that cover the intrinsic temporal structure inherent in the modulation spectra of clean training speech features. The new modulation spectra of the speech features, constructed by mapping the original modulation spectra into the space spanned by these basis vectors, are demonstrated with good noise-robust capabilities. All experiments were conducted using the Aurora-2 database and task. The results show that the proposed NMF-based approach, together with mean and variance normalization (MVN), can provide average error reduction rates of over 65% and 12% relative as compared with the baseline MFCC system and that using the MVN method alone, respectively.
Book Review: David Collins Narrating the Management Guru: In search of Tom Peters 2007, Routledge, London: 168 pp, hard cover and ppb

There was a time when Tom Peters could rightly be said not to be a mere human – he was, instead, a ‘climate of opinion’, representing a set of attitudes, ideas, problems and assumptions, in short a discourse, that dominated the actions and thoughts of managers. Nor was this discourse altogether separate from the preoccupations of many management academics, especially those like myself interested in organizational culture and symbolism. Younger scholars may find it hard to appreciate how seriously Peters, and in particular the book that launched him, In Search of Excellence (co-authored with Robert H. Waterman), was taken at one point by the academy; older academics have probably long forgotten it. Yet, it is worth noting that this is a book cited more than 3000 times in academic journals since its publication, continuing to draw about 60 or more citations annually. Even if many or most of these citations are not favourable, it remains a considerably larger number than the 1600 citings of Gareth Morgan’s Images of Organization or the 1500 citings of Mintzberg’s Nature of Managerial Work. David Collins’s book is an exploration of Tom Peters, his evolving message and the factors that account for his influence among practitioners and academics. Published to coincide with the 25 anniversary of In Search of Excellence, it is a book written with clarity, energy and passion. Collins is not content, as is currently fashionable, to ‘debunk’ Tom Peters; he wants to understand his man, one with whom he shares certain qualities. And understanding the man means understanding the times that account for the man’s moment of glory, his subsequent institutionalization and, as many would say, eventual decline. In short, Collins wants to come up with a Tom Peters story rather than a Tom Peters caricature. In his mission, he combines a sensitive examination of historical context with a close reading of Peters’ texts. While most academics, like myself, gave up reading Peters’ books at some point before or after Thriving on Chaos (1987), Collins has continued to read every single one of Peters’ books and, as we shall see presently, analyzed all of them in revealing detail. First, then, who is Tom Peters and does he matter? Why should academics take him seriously? Peters is usually thought of as the arch-management guru, the guru of gurus. But Collins is unwilling to treat him, as so many have done, as a mere signifier inviting deconstruction, debunking and critique. Starting with a detailed analysis References
Detection of code clones in software generators

Macro-based generators are in use for more than 40 years to generate Cobol source code and implement variability. Over the course of time, the systems were extended with many similar functionalities by copying and adapting existing pieces of code. The resulting generators are hard to understand and difficult to maintain. Clone detection can identify similar pieces of code which is a prerequisite to extract common features thus enabling a move to a feature-oriented product line. This paper presents Hanni, a tool that combines clone detection of the input and output of generators to improve detection quality. Hanni uses standard textual clone detection tools on macro-based generators to detect clones in the macros and the generated Cobol. A mapping of the clones from the two sources is used to verify the detected clones and even suggest possible semantic clones. We are using generator examples from different industries based on the ADS generator framework to evaluate our tool. The results show that code clones are very common in these generators and possible problems in the detection can be identified using the generated files.
Anti-CD146 monoclonal antibody AA98 inhibits angiogenesis via suppression of nuclear factor-κB activation

Our previous study showed that an anti-CD146 monoclonal antibody (mAb), AA98, which was raised against the vascular endothelial cells stimulated by a conditioned medium from hepatocarcinoma SMMC 7721 cells (SMMC 7721-CM), inhibited cell migration, angiogenesis, and tumor growth. However, the underlying mechanism was not elucidated. The objective of this study was to understand the mechanism by which mAb AA98 inhibits the endothelial cell migration and angiogenesis that is induced by SMMC 7721-CM. Using confocal imaging and biochemical studies, we found that SMMC 7721-CM induced nuclear factor κB (NF-κB) activation through the upstream p38 mitogen-activated protein kinase pathway, leading to the up-regulation of matrix metalloproteinase 9 and intercellular adhesion molecule 1 expression. Interestingly, all these activities stimulated by SMMC 7721-CM could be effectively inhibited by mAb AA98 in a dose- and time-dependent manner. Our data showed that the engagement of mAb AA98 with membrane protein CD146 inhibited p38 mitogen-activated protein kinase phosphorylation, suppressed NF-κB activation, and down-regulated matrix metalloproteinase 9 and intercellular adhesion molecule 1 expression, suggesting that the suppression of NF-κB is a critical point for the inhibitory function of mAb AA98 on endothelial cell migration, angiogenesis, and tumor metastasis. These results will provide clues for a better understanding of the mechanisms underlying tumor angiogenesis as well as antiangiogenesis therapy. [Mol Cancer Ther 2006;5(11):2872–8]
Persons and Moral Agency

Charles Taylor’s claim that personhood consists in its relation to moral goods and commitments, and that persons are moral agents, is summarized and examined. According to this view, persons not only have an understanding of themselves as moral agents, they are partially constituted by this understanding. It is argued that as moral agents, persons are capable of effecting changes in their lives through enacting understandings of the good. Moreover, they have the capacity not only to adopt and wield social and cultural moral practices, but also to revise and transform them. Particular features of human psychology and its development are discussed that assist in clarifying the relation between persons and moral agency. Further, it is suggested that moral development might be understood as the gradual process whereby traditions are interpreted and reinterpreted toward the end of fashioning more virtuous persons.
Matrix Reordering Using Multilevel Graph Coarsening for ILU Preconditioning

Incomplete LU factorization (ILU) techniques are a well-known class of preconditioners, often used in conjunction with Krylov accelerators for the iterative solution of linear systems of equations. However, for certain problems, ILU factorizations can yield factors that are unstable and in some cases quite dense. Reordering techniques based on permuting the matrix prior to performing the factorization have been shown to improve the quality of the factorization, and the resulting preconditioner. In this paper, we examine the effect of reordering techniques based on multilevel graph coarsening ideas on one-level ILU factorizations, such as the level-based ILU($k$) or the dual threshold ILUT algorithms. We consider an aggregation-based coarsening idea that implements two main coarsening frameworks---a top-down approach, and a bottom-up approach---each utilizing one of two different strategies to select the next-level coarse graph. Numerical results are presented to support our findings.
Transformation of Person, Identity and Understanding: A case study

The notion of identity is commonly utilised by individuals as a shorthand, both to describe themselves and other individuals or groups of people. While I show that descriptive uses of identity are valuable for explanatory purposes, they are of limited use in elucidating the tranformational relation between social and structural change and individual personhood through which young people come to understand themselves and the world around them. Focusing upon a single case study, I show that identity is not simply a product or outcome of change, but is itself an input into the processes that produce change. The 2-year period between the ages of 15 and 17 was a critical period for Lesley, during which she challenged and questioned previously accepted ways of knowing and doing. Lesley did not ignore her experiences or her understanding of them. She utilised her new self-understandings and the meanings that she associated with them to construct and produce a sustainable and coherent self-narrative for her future use.
The Matrix-Forest Theorem and Measuring Relations in Small Social Groups

We propose a family of graph structural indices related to the Matrix-forest theorem. The properties of the basic index that expresses the mutual connectivity of two vertices are studied in detail. The derivative indices that measure "dissociation," "solitariness," and "provinciality" of vertices are also considered. A nonstandard metric on the set of vertices is introduced, which is determined by their connectivity. The application of these indices in sociometry is discussed.
A Joint Design of Physical Layer Network Coding and Channel Coding for Wireless Networks

Network coding has been receiving much attention recently for its ability to improve spectral efficiency and achieve throughput optimality. In this paper, we propose a practical scheme of joint physical layer network-channel coding for two-way relay scenario. At relay node physical-layer network coding (PNC) is employed to make use of the additive nature of simultaneously arriving electromagnetic wave (EW) for equivalent coding operation. In doing so, PNC can potentially achieve 50% throughput increase compared with straightforward network coding. Meanwhile, we take advantage of the linearity of Turbo code and soft detection module, which not only reduce the complexity of encoding and decoding, but also achieve good performance in high Signal Noise Ratio (SNR). Simulation results show that the proposed scheme outperforms the straightforward network coding in terms of channel capacity and Bit Error Rate (BER) performance when applied to wireless networks.
Delayed treatment of Ebola virus infection with plant-derived monoclonal antibodies provides protection in rhesus macaques

Filovirus infections can cause a severe and often fatal disease in humans and nonhuman primates, including great apes. Here, three anti-Ebola virus mouse/human chimeric mAbs (c13C6, h-13F6, and c6D8) were produced in Chinese hamster ovary and in whole plant (Nicotiana benthamiana) cells. In pilot experiments testing a mixture of the three mAbs (MB-003), we found that MB-003 produced in both manufacturing systems protected rhesus macaques from lethal challenge when administered 1 h postinfection. In a pivotal follow-up experiment, we found significant protection (P < 0.05) when MB-003 treatment began 24 or 48 h postinfection (four of six survived vs. zero of two controls). In all experiments, surviving animals that received MB-003 experienced little to no viremia and had few, if any, of the clinical symptoms observed in the controls. The results represent successful postexposure in vivo efficacy by a mAb mixture and suggest that this immunoprotectant should be further pursued as a postexposure and potential therapeutic for Ebola virus exposure.
Combining Stacking With Bagging To Improve A Learning Algorithm

In bagging Bre94a] one uses bootstrap replicates of the training set Efr79, ET93] to improve a learning algorithm's performance, often by tens of percent. This paper presents several ways that stacking Wol92b, Bre92] can be used in concert with the bootstrap procedure to achieve a further improvement on the performance of bagging for some regression problems. In particular, in some of the work presented here, one rst converts a single underlying learning algorithm into several learning algorithms. This is done by bootstrap resampling the training set, exactly as in bagging. The resultant algorithms are then combined via stacking. This procedure can be viewed as a variant of bagging, where stacking rather than uniform averaging is used to achieve the combining. The stacking improves performance over simple bagging by up to a factor of 2 on the tested problems, and never resulted in worse performance than simple bagging. In other work presented here, there is no step of converting the underlying learning algorithm into multiple algorithms, so it is the improve-a-single-algorithm variant of stacking that is relevant. The precise version of this scheme tested can be viewed as using the bootstrap and stacking to estimate the input-dependence of the statistical bias and then correct for it. The results are preliminary, but again indicate that combining stacking with the bootstrap can be helpful.
The Importance of Hope in Coping with Severe Acquired Disability

Abstract Traditionally, adjustment to a serious injury such as spinal cord injury has been conceptualised as staged grieving process. Hope, in this tradition, is commonly defined as denial and considered counterproductive to positive adjustment. These concepts were challenged as the author observed the strength of clients' hope in the face of extremely confronting physical, social and environmental challenges following spinal cord injury. This paper presents qualitative data about the role of hope from the perspective of the person with spinal cord injury and considers the theoretical and clinical aspects of hope in the coping process. The data presented are a subset of data from a 10 year longitudinal study of a sample of 46 people with spinal cord injury. Semi-structured qualitative interviews were conducted at discharge from hospital, 6, 12, 24, and 36 months post-discharge and again at 10 years post discharge. Results showed that 73% of the participants identified hope as an essential factor that helped them cope following their injury. Three main foci of hope emerged from the data set: (a) hope for a complete recovery, (b) hope for a cure, and (c) hope for a satisfying quality of life. Hope emerged as a strong theme in the overall adjustment and coping process. Clinical implications for working with people who sustain spinal cord injury are discussed. It is recommended that interventions that support and facilitate hope need to be developed and tested.
Selective harmonic current mitigation with shunt active power filter

The paper presents three methods of selective harmonic compensation with shunt active power filters in different reference frames: harmonic dq-frame, stationary frame and fundamental dq-frame; and shows that the last two methods are derived from the first one. By analyzing their advantages and drawbacks, the paper shows that the last two methods have a more compact mathematical representation which may extend to straightforward DSP implementation. However, the first method, i.e. selective compensation in harmonic dq-frame, is more flexible and allows a better tuning and adjustment, which is of a great importance in practice. For experimental tests only the selective harmonic control in fundamental dq-frame is presented, to demonstrate the selectiveness harmonic current compensation. The experimental results are performed in laboratory conditions on a 7 kVA active filter prototype, indicating a reduction in current THDi factor from the existing 27% to 2%.
Development of real-time ECG signal monitoring system for telemedicine application

This work presents the development of low cost, portable real-time Electrocardiogram (ECG) signal monitoring system with abnormality detection capability. The 3-lead Electrocardiogram device takes the physical pulse input using electrodes stuck to the arms and right leg of the patient under observation. The ECG signal is processed by the microcontroller AT89S52 in the portable wireless unit to count the heart beat for a duration of one minute and the Heart Rate is displayed on LCD display. The amplitude and intervals of some critical components are obtained, processed and displayed in a graphical user interface. If an abnormality is detected in the ECG signal, an alert SMS is sent by the system to the doctor through GSM modem to enable him to take appropriate protective measures. The system is intended to use for telemedicine application. Further, the system can be improved to monitor multiple physiological signals and to allow patient mobility by transmitting signals wirelessly.
Fractionally Spaced Frequency-Domain Equalizer for Broadband Wireless Systems

This paper proposes a new approach to apply fractionally spaced frequency-domain equalizer for the single carrier broadband wireless systems in the presence of colored noise. The complexity of this equalizer can be significantly reduced with the help of performing the equalization in the frequency domain, when the channel is highly dispersive. In addition, the overlap-cut method, which can be applied to the existing single carrier air interfaces directly, takes the place of the well-known cyclic-prefix method. It is shown that the fractionally spaced frequency- domain equalizer is superior to the conventional baud spaced ones.
A Monitoring Technique for Reversed Power Flow Detection With High PV Penetration Level

The integration of renewable energy resources (RESs) in power systems poses many research challenges. Research shows that the RES output may exceed the consumed power during the day. Consequently, the direction of the power flow on distribution lines can be reversed during some periods. As the voltage regulator is normally designed for unidirectional power flow, this may cause voltage violations on the distribution feeder. Therefore, most utilities try to set a penetration level (PL) limit for safe operation. On the other hand, time varying and unbalanced loading are the main characteristics of distribution systems. Moreover installation of intermittent and nondispatchable photovoltaic (PV) devices increases the control problems of distribution system. This paper presents an impedance-based monitoring method for detection of distribution system current behavior. It will be shown that by utilizing this monitoring technique, not only the small variation of PV PL can be easily detected, but also some fast transients such as the effect of cloud movement on PV system can be monitored. This monitoring technique employs only local measurements of bus voltages and line current to measure the apparent impedance seen at the installation point. The practical application of measured impedance as a monitoring technique shows its effectiveness for distribution system monitoring in presence of various PV PL.
Fast, Responsive Decentralised Graph Colouring

We solve, in a fully decentralised way (\ie with no message passing), the classic problem of colouring a graph. We propose a novel algorithm that is automatically responsive to topology changes, and we prove that it converges quickly to a proper colouring in $O(N\log{N})$ time with high probability for generic graphs (and in $O(\log{N})$ time if $\Delta=O(1)$) when the number of available colours is greater than $\Delta$, the maximum degree of the graph. We believe the proof techniques used in this work are of independent interest and provide new insight into the properties required to ensure fast convergence of decentralised algorithms.
On Factors Affecting MFCC-Based Speaker Recognition Accuracy

We evaluate the accuracy of an MFCC-based speaker recognition method. We analyse the recognition results using speech signal from everyday life environments. We study the mismatch effects of text-dependency, sample length, language, style of speaking, cheating, microphone, sample quality, and noise. The experiments on a self-collected corpus of 30 subjects indicate that any mismatch degrades recognition accuracy. The most dominating factors are noise, microphone, disguise, and degrading of the sample rate and quality. Speech-related factors and sample length are less critical.
An enhanced dimensionality reduction for multi-label learning

Locally Linear Embedding (LLE) manifold algorithm is a kind of unsupervised dimensionality reduction algorithm, which preserves geometric structure of the local patches when high-dimensional data is mapped to a low-dimensional space. To solve `curse of dimensionality' problem and enhance the accuracy of multi-label learning, Variable K-nearest Locally Linear Embedding (VKLLE) and Variable K-nearest Semi-Supervised Locally Linear Embedding (VKSSLLE) are proposed. Different from existing approaches, the proposed algorithms calculate the proper number of nearest neighbors according to the distribution of sample points in dataset, which avoids smoothing or elimination of small-scale structure in the manifold as well as false division of the continuous manifold into irrelevant sub-manifolds. To verify the performances of the proposed algorithms, different dimensionality reduction algorithms are respectively incorporated with multi-label naive Bayes classifier to solve multi-label learning problem. Results on artificial dataset and two real-world datasets show that proposed algorithms can effectively enhance the accuracy of multi-label learning.