Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of lactate in the striatum without contamination of macromolecules by J‐difference editing MRS at 7 T

Lactate levels are measurable by MRS and are related to neural activity. Therefore, it is of interest to accurately measure lactate levels in the basal ganglia networks. If sufficiently stable, lactate measurements may be used to investigate alterations in dopaminergic signalling in the striatum, facilitating the detection and diagnosis of metabolic deficits. The aim of this study is to provide a J‐difference editing MRS technique for the selective editing of lactate only, thus allowing the detection of lactate without contamination of overlapping macromolecules. As a validation procedure, macromolecule nulling was combined with J‐difference editing, and this was compared with J‐difference editing with a new highly selective editing pulse. The use of a high‐field (7T) MR scanner enables the application of editing pulses with very narrow bandwidth, which are selective for lactate. We show that, despite the sensitivity to B0 offsets, the use of a highly selective editing pulse is more efficient for the detection of lactate than the combination of a broad‐band editing pulse with macromolecule nulling. Although the signal‐to‐noise ratio of uncontaminated lactate detection in healthy subjects is relatively low, this article describes the test–retest performance of lactate detection in the striatum when using highly selective J‐difference editing MRS at 7 T. The coefficient of variation, σw and intraclass correlation coefficients for within‐ and between‐subject differences of lactate were determined. Lactate levels in the left and right striatum were determined twice in 10 healthy volunteers. Despite the fact that the test–retest performance of lactate detection is moderate with a coefficient of variation of about 20% for lactate, these values can be used for the design of new studies comparing, for example, patient populations with healthy controls. Copyright © 2015 John Wiley & Sons, Ltd.
A Kind of Content-Based Music Information Retrieval Method in Peer-to-peer Environment

In this paper, we propose four peer-to-peer models for content-based music information retrieval (CBMIR) and carefully evaluate them on network load, retrieval time, system update and robustness qualitatively and quantitatively. And we bring forward an algorithm to improve the speed of CBP2PMIR and a simple but effective method to filter out the replica in the final results. And we present the architecture of QUIND, a content-based peer-to-peer music information retrieval system, which can implement CBMIR. QUIND combines content-based music information retrieval technologies and peer-to-peer environments, and has strong robustness and good expansibility. Music stored and shared on each PC makes up of the whole available music resource. When a user puts forward a music request, e.g. a song or a melody, QUIND can retrieve a lot of similar music quickly and accurately according to the content of music. After the user selects his favorite ones, he can download and enjoy them.
Analyzing Data Streams by Online DFT

Sensor data have become very huge and single measures are produced at high rates, resulting in streaming sensor data. In this paper, we present a new mining tool called Online DFT, which is particularly powerful for estimating the spectrum of a data stream. Unique features of our new method include low update complexity with high-accuracy estimations for very long periods, and the ability of long-range forecasting based on our Online DFT. Furthermore, we describe some applications of our Online DFT
Understanding a Socially Awkward Digital Play Journey

Socially awkward experiences are often considered as something to be avoided. Interestingly, examples from the traditional games domain suggest that social awkwardness can enable novel and engaging play experiences. We note that there has been little research into exploring social awkwardness when it comes to digital games. In response we present our experiences with Musical Embrace, a digital game that requires close physical proximity and whole body interactions to explore socially awkward play between players. Our observations from users experiencing Musical Embrace at a number of events suggest that social awkwardness experienced by participants often rises and falls as part of the digital play journey. As such, we draw upon the classic five-act performance structure (consisting of exposition, rising action, climax, falling action and denouement) to examine the experiences of players and understand the way in which social awkwardness engages players as the game progresses. With our work we hope to inspire game designers to consider the potential of social awkwardness in digital games.
First Year District Superintendents: Women Reflect on Contradictions between Education and Politics.

Despite passage of affirmative-action legislation in the United States, the percentage of women school superintendents has increased at a very slow pace. This paper identifies the major challenges faced by four female entry-level superintendents and the strategies they used to deal with them. Data were collected during a group interview with the four superintendents at the end of their first year on the job. All had entered new school districts after gaining experience as assistant superintendents. The superintendents, three white and one African-American, utilized some similar strategies to handle issues. During their first year on the job, the women: (1) learned to recognize and accept politics as a reality; (2) entered the job with a formal entry plan and later developed a district plan; (3) engaged in learning and open communication with all stakeholders; (4) studied past practices; (5) practiced creative problem solving rather than confrontation; (6) protected their personal/family time; and (7) educated and provided information to the school board. (Contains 17 references.) (LMI) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * from the original document. ***********************************************************************
Construction of interpretable Radial Basis Function classifiers based on the Random Forest kernel

In many practical applications besides a small generalization error also the interpretability of classification systems is of great importance. There is always a tradeoff among these two properties of classifiers. The similarity measure in the input space as defined by one of the most powerful classifiers, the Random Forest (RF) algorithm, is used in this paper as basis for the construction of Generalized Radial Basis Function (GRBF) classifiers. Hereby, interpretability and a low generalization error can be achieved. The main idea is to approximate the RF kernel by Gaussian functions in a GRBF network. This way the GRBF network can be constructed to approximate the conditional probability of each class given a query input. Since each center in the GRBF is used for the representation of the distribution of a single target class in a localized area of the classifiers input space, interpretability can be achieved by taking account for the membership of a query input to the different localized areas. Whereas in most algorithms the pruning technique is used only to improve the generalization property, here a method is proposed how pruning can be applied to additionally improve the interpretability. Another benefit that comes along with the resulting GRBF classifier is the possibility to detect outliers and to reject decisions that have a low confidence. Experimental results underline the advantages of the classification system.
Barrett’s esophagus: review of diagnosis and treatment

Barrett's esophagus (BE) is an acquired condition characterized by replacement of stratified squamous epithelium by a cancer predisposing metaplastic columnar epithelium. Endoscopy with systemic biopsy protocols plays a vital role in diagnosis. Technological advancements in dysplasia detection improves outcomes in surveillance and treatment of patients with BE and dysplasia. These advances in endoscopic technology radically changed the treatment for dysplastic BE and early cancer from being surgical to organ-sparing endoscopic therapy. A multimodal treatment approach combining endoscopic resection of visible and/or raised lesions with ablation techniques for flat BE mucosa, followed by long-term surveillance improves the outcomes of BE. Safe and effective endoscopic treatment can be either tissue acquiring as in endoscopic mucosal resection and endoscopic submucosal dissection or tissue ablative as with photodynamic therapy, radiofrequency ablation and cryotherapy. Debatable issues such as durability of response, recognition and management of sub-squamous BE and optimal management strategy in patients with low-grade dysplasia and non-dysplastic BE need to be studied further. Development of safer wide field resection techniques, which would effectively remove all BE and obviate the need for long-term surveillance, is another research goal. Shared decision making between the patient and physician is important while considering treatment for dysplasia in BE.
Synchronization Controller Synthesis of Multi-Axis Motion System

This paper investigates on motion synchronization of a multiple axes system. Two different control strategies, a cross-coupling controller in feedback loop and a linear quadratic optimal controller, were used to synthesize the synchronization compensator with the cross-coupling dynamics among the axes. These two methods are corresponding to SISO and MIMO approaches. With the strategies, the asymptotic convergence of both tracking and synchronization errors can be achieved. Simulation and experimental results of a three-axis motion system illustrate the effectiveness of the proposed approach.
Adaptation of Speaker-Specific Bases in Non-Negative Matrix Factorization for Single Channel Speech-Music Separation

This paper introduces a speaker adaptation algorithm for nonnegative matrix factorization (NMF) models. The proposed adaptation algorithm is a combination of Bayesian and subspace model adaptation. The adapted model is used to separate speech signal from a background music signal in a single record. Training speech data for multiple speakers is used with NMF to train a set of basis vectors as a general model for speech signals. The probabilistic interpretation of NMF is used to achieve Bayesian adaptation to adjust the general model with respect to the actual properties of the speech signals that is observed in the mixed signal. The Bayesian adapted model is adapted again by a linear transform, which changes the subspace that the Bayesian adapted model spans to better match the speech signal that is in the mixed signal. The experimental results show that combining Bayesian with linear transform adaptation improves the separation results. Copyright © 2011 ISCA.
Text Generation for Explaining the Behavior of 2D Charts: With an Example of Stock Price Trends

We propose a method to generate a verbal report on the trends of stock price. The trends of the stock price is observed by the behavior of numerical data expressed in a 2D chart. Since its behavior reflects the shape of a chart, in order to recognize the behaviorin qualitativeand quantitative ways, we use the least squares to mathematically recognize the shape and expressed it with words that often appear in news articles reporting the trends of stock prices. Our proposed method can change non-verbal information into verbal information — this provide us with high accessibility and usability for various kinds of information.
A New Semantic-based Query Processing Architecture

With rapid development of sensor networks technology, it becomes feasible to deploy multiple sensor networks in relevant area to collect interested information. Sensor nodes belonging to different sensor networks may not be able to collaborate properly to gain the capacity or performance due to inability to exchange information with each other. In this paper we propose a semantic-based query processing architecture that enables in-network processing of multiple sensor networks with unified protocol. In this architecture, there are low-level semantics in raw sensory data which are the mapping of the physical world. Semantics will be attached to the data to make the sensory data be understood more easily. In the process of matching, aggregated data are generated and semantics are attached to the aggregated data. The advantage of semantic-based architecture is that it can solve the problems in more complex situations. It makes the exchange of sensory data in multiple sensor networks possible and efficiently. The process of semantic creation and maintenance is described. We also introduce the concept of semantic data model. This infrastructure enables efficient information exchange and information extraction among multiple sensor networks.
An Integration of Deep Learning and Neuroscience for Machine Consciousness

Conscious processing is a useful aspect of brain function that can be used as a model to design artificial-intelligence devices. There are still certain computational features that our conscious brains possess, and which machines currently fail to perform those. This paper discusses the necessary elements needed to make the device conscious and suggests if those implemented, the resulting machine would likely to be considered conscious. Consciousness mainly presented as a computational tool that evolved to connect the modular organization of the brain. Specialized modules of the brain process information unconsciously and what we subjectively experience as consciousness is the global availability of data, which is made possible by a nonmodular global workspace. During conscious perception, the global neuronal work space at parieto-frontal part of the brain selectively amplifies relevant pieces of information. Supported by large neurons with long axons, which makes the long-distance connectivity possible, the selected portions of information stabilized and transmitted to all other brain modules. The brain areas that have structuring ability seem to match to a specific computational problem. The global workspace maintains this information in an active state for as long as it is needed. In this paper, a broad range of theories and specific problems have been discussed, which need to be solved to make the machine conscious. Later particular implications of these hypotheses for research approach in neuroscience and machine learning are debated.
An optimization approach for analysing nonlinear stability with transition to turbulence in fluids as an exemplar

This article introduces and reviews recent work using a simple optimization technique for analysing the nonlinear stability of a state in a dynamical system. The technique can be used to identify the most efficient way to disturb a system such that it transits from one stable state to another. The key idea is introduced within the framework of a finite-dimensional set of ordinary differential equations (ODEs) and then illustrated for a very simple system of two ODEs which possesses bistability. Then the transition to turbulence problem in fluid mechanics is used to show how the technique can be formulated for a spatially-extended system described by a set of partial differential equations (the well-known Navier–Stokes equations). Within that context, the optimization technique bridges the gap between (linear) optimal perturbation theory and the (nonlinear) dynamical systems approach to fluid flows. The fact that the technique has now been recently shown to work in this very high dimensional setting augurs well for its utility in other physical systems.
Heating and Ionization of X-Winds

In order to compare the X-wind with observations, one needs to be able to calculate its thermal and ionization properties. We formulate the physical basis for the streamline-by-streamline integration of the ionization and heat equations of the steady X-wind. In addition to the well-known processes associated with the interaction of stellar and accretion funnel hot spot radiation with the wind, we include X-ray heating and ionization, mechanical heating, and a revised calculation of ambipolar diffusion heating. The mechanical heating arises from fluctuations produced by star-disk interactions of the time-dependent X-wind that are carried by the wind to large distances where they are dissipated in shocks, MHD waves, and turbulent cascades. We model the time-averaged heating by the scale-free volumetric heating rate, Γmech = αρv3s-1, where ρ and v are the local mass density and wind speed, respectively, s is the distance from the origin, and α is a phenomenological constant. When we consider a partially revealed but active young stellar object, we find that choosing α ~ 10-3 in our numerical calculations produces temperatures and electron fractions that are high enough for the X-wind jet to radiate in the optical forbidden lines at the level and on the spatial scales that are observed. We also discuss a variety of applications of our thermal-chemical calculations that can lead to further observational checks of X-wind theory.
Game theory and international environmental cooperation: any practical application?

Many researchers have found game theory a useful method for analyzing international environmental problems. However, game theory has been criticized for being too theoretical, abstracting from too many practical problems and being based on very specific assumptions. This article tries to qualify this critic. First, it lays out the fundamental assumptions underlying the game theoretical analysis of international environmental problems. Second it summarizes important findings which help to explain the difficulties of cooperation and discusses remedies. Chapter 3 looks at measures to avoid asymmetric welfare distributions and to enforce an IEA. Chapter 4 discusses policy instruments in global pollution control and chapter 5 summarizes the results on the formation of coalitions. Third, the results of chapters 3, 4 and 5 are critically reviewed. On the one hand, open issues with respect to the theoretical analysis are characterized. On the other hand, practical problems which are not covered by theory are mentioned and evaluated as to their effect to influence policy conclusions. Fourth, the theoretical results and the derived conclusions of chapters 3 to 5 are applied to the analysis of the Kyoto-Protocol (chapter 6). The article stresses the intuition behind all results, though formal proofs of new results are given.
Transfinite semantics in program slicing

This paper studies mathematically some special kinds of transfinite trace semantics and investigates program slicing w.r. t. these semantics. S everal general facts about slicing, which hold for a wide class of programming languages and their transfinite semantics, are proven. The principal part of the work is done on control flow g raphs keeping the treatment abstracted from any concrete programming language. Structured control flow is not assumed but programs written in standard programming languages with structured control flow are among those to which our theory applies.
The current practice and promotion strategy of dry-mix mortars in Taiwan — Taking technology acceptance model as an approach

Compared with traditional cement processing methods, dry-mix mortars are more environmental friendly by reducing air pollution or waste production on construction sites. It can also reduce carbon dioxide emissions, helps to keep the construction site clean, and allow for more flexibility in storage space for materials while reducing cement redundancy after the cement finishing is completed. It can be said that this new and advanced construction material is environmental friendly and convenient to deploy and transport, delivers product of stable quality, helps to facilitate construction, and saves materials. In this study, a questionnaire survey was conducted on people in the construction industry in Taiwan to explore their perceptions of the characteristics of dry mix mortars and their acceptance of this material. Totally 133 valid samples were returned. After the analysis of the questionnaire results, this research found the more the respondents find dry-mix mortars useful, the more satisfied they are with the material; the more they are satisfied, the more willing they are to promote it. Among all the factors, the perceived usefulness of this material has a particularly significant influence.
Optimal transmission rate for MISO channels with joint sum and per-antenna power constraints

We consider multiple-input single-output (MISO) Gaussian channels with joint sum and per-antenna power constraints. A closed-form solution of the optimal beamforming vector is derived which achieves the maximal transmission rate. The result shows that if the sum power constraint only optimal power allocation violates a per-antenna power constraint then the joint power constraint optimal power allocation is at the intersection of the sum power constraint and the per-antenna power constraints.
Design and methods for a Scandinavian pharmacovigilance study of osteonecrosis of the jaw and serious infections among cancer patients treated with antiresorptive agents for the prevention of skeletal-related events

Objective Osteonecrosis of the jaw (ONJ) is a recognized complication of potent antiresorptive therapies, especially at the doses indicated to prevent skeletal complications for cancer patients with bone metastases. This paper describes the rationale and methods for a prospective, post-authorization safety study of cancer patients treated with antiresorptive therapies. Methods As part of a comprehensive pharmacovigilance plan, developed with regulators’ input, the study will estimate incidence of ONJ and of serious infections among adult cancer patients with bone metastases treated with denosumab (120 mg subcutaneously) or zoledronic acid (4 mg intravenously, adjusted for renal function). Patients will be identified using routinely collected data combined with medical chart review in Denmark, Sweden, and Norway. Followup will extend from the first administration of antiresorptive treatment to the earliest of death, loss-to-follow-up, or 5 years after therapy initiation. Results will be reported for three treatment cohorts: denosumab-naïve patients, zoledronic acid-naïve patients, and patients who switch from bisphosphonate treatment to denosumab. ONJ cases will be identified in three newly established national ONJ databases and adjudicated by the committee that functioned during the XGEVA® clinical trials program. Conclusion This study will provide a real world counterpart to the clinical trial-estimated risks for ONJ and serious infections for cancer patients initiating denosumab or zoledronic acid. The establishment of ONJ databases in the three Scandinavian countries will have potential benefits outside this study for the elucidation of ONJ risk factors and the evaluation of ONJ treatment strategies.