Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach

The book is divided into four chapters. The first one introduces the structure of deregulated, competitive electricity markets with the power pools and power exchanges as the basic marketplaces for price discovery. Chapter 2 reviews the so-called stylized facts of selected power markets. In particular, the spiky nature of electricity prices, the different levels of seasonality inherent in load and price time series, the anti-persistent behavior of prices and the heavy-tailed distributions of returns. Chapter 3 reviews load forecasting techniques, with particular emphasis on statistical methods. Various models with and without exogenous variables are illustrated and compared in two comprehensive case studies. Finally, Chapter 4 discusses price modeling and forecasting. Six different approaches are surveyed and two – statistical and quantitative – are further studied. As in the previous chapter, the theoretical considerations and techniques are illustrated and evaluated using real-world data.
A X-band CMOS power amplifier with on-chip transmission line transformers

A X-band CMOS power amplifier (PA) has been fabricated using a 0.18-mum CMOS technology. On-chip transmission line transformers are used as matching elements for output, input, and inter-stage matching. The power amplifier provides the saturated output power of 23.5 dBm and 1-dB gain-compressed output power (P1dB) is 21 dBm at 8.5 GHz with 3.3 V supply. The gain is 29 dB and power-added-efficiency (PAE) is 19 % at 8.5 GHz. Among the reported X/Ku band CMOS power amplifiers, this amplifier has the largest output power.
Modal and harmonic experimental validation of the vibration model of an elastic structure

In this paper it is shown that the problem of applying active control to a simple elastic plate structure can be introduced in a form which allows the application of optimal control theory. In particular, a modal model for the vibration of an elastic structure and the state space realization of this model are given. In the first part of the paper a modal analysis of the structure is introduced and the natural frequencies are computed both in analytic form and by a set of experimental tests. In the second part an harmonic analysis is performed and the output of the model is developed and compared with experimental results. This shows that the introduced model is a good description of the real process and an optimal active control of the elastic plate structure is feasible.
Comparing nonlinear derivative method and Canny algorithm to tongue diagnosis in Traditional Chinese Medicine

The tongue diagnosis is an important diagnostic method in Traditional Chinese Medicine (TCM). Human tongue is one of the important organs which contain the information of health status. In order to achieve an automatic tongue diagnostic system, an effective segmentation method for detecting the edge of tongue is very important. We mainly compare the Canny and nonlinear derivative methods for edge segmentation. The segmentation using Canny algorithm may produce many false edges after cutting; thus, it is not suitable for use. But, nonlinear derivative method can automatically select the best edge information. Therefore, it may be useful in clinical automated tongue diagnosis system. Experiments show the results of these techniques.
Distributed knowledge management in health care administration

The paper addresses the electronic commerce application field of health care administration. Models for knowledge distribution is a rare commodity in health care administration. Distributed knowledge management (DKM) is a concept that originated as an abstraction of a business model prepared for the mechanical and agricultural industry but holds promises for a more general use. The contribution of the paper is to suggest a new business model based on DKM and show the relevance and applicability of this concept in a totally new context of health care administration.
Characterization of the Binding of [3H][Dmt1]H-Dmt-d-Arg-Phe-Lys-NH2, a Highly Potent Opioid Peptide

The dermorphin-derived peptide [Dmt1]DALDA (H-Dmt-d-Arg-Phe-Lys-NH2; Dmt, 2′,6′-dimethyltyrosine) labels μ-opioid receptors with high affinity and selectivity in receptor binding assays. In previous studies, [Dmt1]DALDA displayed a mechanism of action distinct from that of morphine, as evidenced by its insensitivity to antisense probes reducing morphine analgesia and incomplete cross tolerance to morphine. In an effort to further elucidate the unusual mechanism of action, [3H][Dmt1]DALDA has been synthesized and its binding profile studied. [3H][Dmt1]DALDA binding was high affinity (KD = 0.22 nM) and showed a regional distribution consistent with μ-receptors with highest levels in calf striatal membranes. [3H][Dmt1]DALDA binding was far less sensitive than [3H][d-Ala2,N-Me-Phe4,Gly5-ol]-enkephalin (DAMGO) to the effects of divalent and sodium cations and guanine nucleotides, although NaCl and guanosine 5′-(β,γ-imido)triphosphate together reduced specific [3H][Dmt1]DALDA binding levels by almost 75%. Competition studies confirmed the μ-selectivity of the binding, with Ki values that were not appreciably different from those seen against [3H]DAMGO. In guanosine 5′-O-(3-[35S]thio)-triphosphate ([35S]GTPγS) binding assays in brain and spinal cord membranes, [Dmt1]DALDA was more potent than DAMGO, but showed plateaus suggestive of a partial agonist. [Dmt1]DALDA bound to μ-opioid receptor clone 1 (MOR-1) and its splice variants with high affinity. Unlike [3H]DAMGO, [3H][Dmt1]DALDA seemed to label both agonist and antagonist conformations of MOR-1 expressed in Chinese hamster ovary cells. In [35S]GTPγS assays [Dmt1]DALDA showed high efficacy with all the MOR-1 variants, but its potency (EC50) varied markedly among some of the splice variants despite similar affinities in receptor binding assays. Although [3H][Dmt1]DALDA is a very potent μ-selective analgesic, its binding characteristics and its ability to stimulate GTPγS binding differed from that of the classical μ-opioid peptide DAMGO.
Typical Non-verbal Behavior of Different Interpersonal Stances during Police Interrogations

The ability to properly grasp and express social power is said to be the most significant predictor of a successful life. Especially for the police, it is essential for them to identify the interpersonal stance during interrogations. This research aims at finding typical non-verbal behavior of different interpersonal stances during police interrogations. The Leary’s model, also known as the interpersonal circumplex (IPC) was used as a framework to classify four types of interpersonal stances. An online survey was conducted, which contained 16 interrogation fragments, to investigate people’s perception of interpersonal stance. The best identified fragments were further annotated to extract the non-verbal behavior of the suspects. The findings of this research will be implemented into an interrogation game for the police trainees in the future.
The Two Futures of Governing: Decentering and Recentering Processes in Governing

The Two Futures of Governing: Decentering and Recentering Processes in Governing Reforms of the public sector have helped create a more efficient and effective public sector, but they have also created a number of problems. Both the New Public Management and "governance" reforms have contributed to the contemporary problems in governing. These problems have been political to a great extent, reflecting the tendency to emphasize administrative rather than democratic values. Governments have begun to react to the real and perceived problems within the public sector by developing a number of "meat-governance" instruments that can help steer public organizations but which involve less direct command and control. This paper addresses the contemporary governance tasks of restoring political direction and policy coherence while at the same time supporting the autonomy of public organizations, and the involvement of policy networks, in governing.
Empirical evaluation of multi-device profiling side-channel attacks

Side-channel analysis of cryptographic systems can allow for the recovery of secret information by an adversary even where the underlying algorithms have been shown to be provably secure. This is achieved by exploiting the unintentional leakages inherent in the underlying implementation of the algorithm in software or hardware. Within this field of research, a class of attacks known as profiling attacks, or more specifically as used here template attacks, have been shown to be extremely efficient at extracting secret keys. Template attacks assume a strong adversarial model, in that an attacker has an identical device with which to profile the power consumption of various operations. This can then be used to efficiently attack the target device. Inherent in this assumption is that the power consumption across the devices under test is somewhat similar. This central tenet of the attack is largely unexplored in the literature with the research community generally performing the profiling stage on the same device as being attacked. This is beneficial for evaluation or penetration testing as it is essentially the best case scenario for an attacker where the model built during the profiling stage matches exactly that of the target device, however it is not necessarily a reflection on how the attack will work in reality. In this work, a large scale evaluation of this assumption is performed, comparing the key recovery performance across 20 identical smart-cards when performing a profiling attack.
Lectures on quasi-invariants of Coxeter groups and the Cherednik algebra

The paper an elementary introduction for non-specialists to the theory of quasi-invariants of Coxeter groups. The main object of study is the variety X_m of quasi-invariants for a finite Coxeter group, which arose in a work of O.Chalykh and A.Veselov about 10 years ago, as the spectral variety of the quantum Calogero-Moser system. Despite being singular, this variety has very nice properties (Cohen-Macaulay, Gorenstein, simplicity of the ring of differential operators, explicitly given Hilbert series). It is interesting that although the definition of X_m is completely elementary, to understand the geometry of X_m it is helpful to use representation theory of the rational degeneration of Cherednik's double affine Hecke algebra, and the theory of integrable systems.
Robust affine projection algorithm using selectively shrunk error component

A novel robust affine projection algorithm (APA) is proposed, which selectively shrinks error components in an error vector according to their individual possibilities of being interrupted by the impulsive noise. In existing robust APAs, if there exists only one error component interrupted by the impulsive noise, all error components of an error vector are shrunk using common step sizes which are inversely proportional to the norm of the error vector. This improper scaling results in performance degradation with a high impulsive noise probability and projection order. In this paper, we derive a modified minimization criterion considering the individual possibilities of error components from a geometric interpretation. For a wide range of impulsive noise probability and a high projection order, the performance of the proposed algorithm is verified in various system identification events including an abrupt system change. The proposed algorithm showed the fastest convergence rate and the lowest steady-state mean square deviation compared to the previous robust APAs and a recent variable step-size affine projection sign algorithm.
Robust Face Recognition Using Skin Color and Lips Position

Security of a person is a crucial part of any industry. One of them is face recognition. Face recognition is an effective means of authenticating a person. This paper introduces a new approach to face detection systems using the skin color of a subject. This system can detect a face regardless of the background of the picture, which is an important phase for face identification. The images used in this system are color images which give additional information about the images than the gray images provide. The advantage of this approach is that, it enables us to detect changes in the face pattern of an individual to an appreciable extent. Hence face recognition can be used as a key factor in crime detection mainly to identify criminals. There are several approaches to face recognition of which Principal Component Analysis (PCA) has been incorporated in our project. The system consists of a database of a set of facial patterns for each individual. The characteristic features called ‘Eigen faces’ are extracted from the stored images using which the system is trained for subsequent recognition of new images. The entire project occurs in four different stages in which the first stage includes obtaining face region from the original image, the second stage includes mouth region extraction by background subtraction, the third stage includes key point’s extraction by considering the lip centric as origin of co-ordinates and the fourth stage includes storing the obtained feature vector in the database. This project will increase the accuracy level of biometric systems.
Design and Simulation of a High Speed CMOS Comparator

Analog-to-Digital conversion process is an electronic process in which an analog signal is changed, without changing its necessary contents, into a digital signal. Latched comparators use positive feedback mechanism (aids in the input signal) to re-generates (amplifies) the analog input signal into a Fullscale digital level output signal [2]. This paper presents a CMOS comparator that reduces the overall propagation delay and hence provides higher speed. The design is simulated in 0. 25μm CMOS Technology using Tanner EDA Tools. CMOS Comparator shows that the overall propagation delay of the comparator, TPD, is 1.7872e-9 seconds, with a 1.0 V supply voltage.
Investigations to the Antibacterial Mechanism of Action of Kendomycin

Purpose The emergence of bacteria that are resistant to many currently used drugs emphasizes the need to discover and develop new antibiotics that are effective against such multi-resistant strains. Kendomycin is a novel polyketide that has a unique quinone methide ansa structure and various biological properties. This compound exhibits strong antibacterial activity against Gram-negative and Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA). Despite the promise of kendomycinin in several therapeutic areas, its mode of action has yet to be identified. Methods In this study, we used a multidisciplinary approach to gain insight into the antibacterial mechanism of this compound. Results The antibacterial activity of kendomycin appears to be bacteriostatic rather than bactericidal. Kendomycin inhibited the growth of the MRSA strain COL at a low concentration (MIC of 5 μg/mL). Proteomic analysis and gene transcription profiling of kendomycin-treated cells indicated that this compound affected the regulation of numerous proteins and genes involved in central metabolic pathways, such as the tricarboxylic acid (TCA) cycle (SdhA) and gluconeogenesis (PckA and GapB), cell wall biosynthesis and cell division (FtsA, FtsZ, and MurAA), capsule production (Cap5A and Cap5C), bacterial programmed cell death (LrgA and CidA), the cellular stress response (ClpB, ClpC, ClpP, GroEL, DnaK, and GrpE), and oxidative stress (AhpC and KatA). Electron microscopy revealed that kendomycin strongly affected septum formation during cell division. Most kendomycin-treated cells displayed incomplete septa with abnormal morphology. Conclusions Kendomycin might directly or indirectly affect the cell division machinery, protein stability, and programmed cell death in S. aureus. Additional studies are still needed to obtain deeper insight into the mode of action of kendomycin.
Architecting an open system for querying large C and C++ code bases

Static code analysis offers a number of tools for the assessment of complexity, maintainability, modularity and safety of industry-size source code bases. Typically, such scenarios include three main phases. First, the code is parsed and ’raw’ data is extracted and saved, such as syntax trees, possibly annotated with semantic (type) information. In the second phase, the raw data is queried to check the presence or absence of specific code patterns which supports or invalidates specific claims on the code. In the third and last phase, the query results are presented (visualized) such that correlations between code structure and query results are emphasized in an easily understandable way. Whereas parsing source code is largely standardized, using several existing parsers, querying the outputs of such parsers is still a complex task. The main problem resides in the difficulty of easily translating high-level, cross-cutting concerns in the problem domain into queries in the raw data domain. We present here an open framework for constructing and executing queries on industry-size C++ code bases. Our query system adds several so-called query primitives atop a flexible C++ parser, offers options to combine these primitives into arbitrarily complex expressions, has a highly efficient way to evaluate such expressions on syntax trees of millions of nodes, and presents the query results in a visual, compact, intuitive way. We demonstrate our query framework, integratd in the SOLIDFX C++ reverse-engineering environment, with several real-world analyses on industrial codebases.
Integrated simulation and optimization scheme of real-time large-scale water supply network: applied to Catalunya case study

This paper presents an integrated simulation and optimization modeling approach in order to provide the optimal configuration for large-scale water supply systems (LSWSS) in real time. Model predictive control (MPC) has been chosen to handle the complex set of objectives involved in the management of LSWSS. The computation of control strategies by MPC uses a simplified model of the network dynamics. The use of the combined approach of optimization and simulation contributes to making sure that the effect of more complex dynamics, better represented by the simulation model, may be taken into account. Coordination between simulator and optimizer works in a feedback scheme, from which both real-time interaction and extensive validation of the proposed solution have been realized using a case study based on the Catalunya regional water network.
A bacteriological study of non-chromogenic variants of Serratia marcescens from human sources

The culture and biochemical features of 10 non-chromogenic variants of S. marcescens isolated from clinical sources are reported. Autoagglutination titres were significantly high in sera from those patients in whom Serratia bacilli appeared to contribute to the illness. Since the taxonomic stature of the Serratia bacilli is not clear it might be better to limit the identification of this group to Serratia species.
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data

Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised learning algorithm that uses Gaussian fields and harmonic functions. This classifier is relational in nature: it relies on having the data presented as a partially labeled graph (also known as a within-network learning problem). This work showed yet again that empirical risk minimization (ERM) was the best method to find the next instance to label and provided an efficient way to compute ERM with the semi-supervised classifier. The computational problem with ERM is that it relies on computing the risk for all possible instances. If we could limit the candidates that should be investigated, then we can speed up active learning considerably. In the case where the data is graphical in nature, we can leverage the graph structure to rapidly identify instances that are likely to be good candidates for labeling. This paper describes a novel hybrid approach of using of community finding and social network analytic centrality measures to identify good candidates for labeling and then using ERM to find the best instance in this candidate set. We show on real-world data that we can limit the ERM computations to a fraction of instances with comparable performance.
Liaison Old Age Psychiatry Service in a Medical Setting: Description of the Newcastle Clinical Service

Liaison Old Age Psychiatry services (LOAP) have begun to emerge in the UK and further development of the service is supported by the latest health policies. Since qualitative and quantitative studies in this area are lacking, we have undertaken a detailed quantitative prospective review of referrals to the Newcastle LOAP to evaluate the clinical activity of the service. We report high referral rates and turnover for the LOAP service. Reasons for referral are diverse, ranging from requests for level of care and capacity assessments and transfer to other clinical services to management of behaviour, diagnosis, and treatment. We outline the value of a multidisciplinary model of LOAP activity, including the important role of the liaison nursing team, in providing a rapid response, screening, and followup of high number of clinical referrals to the service.
MATHAINO: SIMULTANEOUS LEGACY INTERFACE MIGRATION TO MULTIPLE PLATFORMS1

With the proliferation of different computing devices and platforms, it is becoming increasingly important for organizations to migrate their existing software systems to new environments, possibly more than one, with minimum effort and risk. In this paper, we introduce Mathaino, a platform independent, non-invasive tool that can be used to migrate, in a semiautomated manner, text-based legacy interfaces to modern web-centric target platforms, by constructing wrappers as frontends around the original legacy-system user interface.
Fast, functional, and fitting: expert response dynamics and response quality in an online newcomer help forum

In online communities a few experts are able to help a large number of help-seekers -- whether in Q&A communities or other forms of online forums. How is this efficiency achieved? How useful is this help? We show that expert help-giving can be characterized as: (1) Fast -- Most active help-givers gave response promptly and were most responsive during peak activity; (2) Functional -- There was little duplication of help-giving effort; and, (3) Fitting -- Initial responses were of high quality and reduced the need for further clarifications and corrections; high quality responses were provided earlier in the thread. Examination of differences across experts revealed that the most highly rated group of experts responded to 69% of the questions with a median response time of 16 minutes, twice as fast as other experts. Finally, we demonstrate the high quality of response through a taxonomy that characterizes expert responses as: framing, guiding, or engaged help.
Two Fields Are Better Than One: Developmental and Comparative Perspectives On Understanding Spatial Reorientation

Occasionally, we lose track of our position in the world, and must re-establish where we are located in order to function. This process has been termed the ability to reorient and was first studied by Ken Cheng in 1986. Reorientation research has revealed some powerful cross-species commonalities. It has also engaged the question of human uniqueness because it has been claimed that human adults reorient differently from other species, or from young human children, in a fashion grounded in the distinctive combinatorial power of human language. In this chapter, we consider the phenomenon of reorientation in comparative perspective, both to evaluate specific claims regarding commonalities and differences in spatial navigation, and also to illustrate, more generally, how comparative cognition research and research in human cognitive development have deep mutual relevance.