Miracle-dz/UniFAR-FTUs huggingface dataset:
Climate Variability and the Energetic Pathways of Evolution: The Origin of Endothermy in Mammals and Birds

Large‐scale climate oscillations in earth’s history have influenced the directions of evolution, last but not least, through mass extinction events. This analysis tries to identify some unifying forces behind the course of evolution that favored an increase in organismic complexity and performance, paralleled by an increase in energy turnover, and finally led to endothermy. The analysis builds on the recent concept of oxygen‐limited thermal tolerance and on the hypothesis that unifying principles exist in the temperature‐dependent biochemical design of the eukaryotic cell in animals. The comparison of extant water‐breathing and air‐breathing animal species from various climates provides a cause‐and‐effect understanding of the trade‐offs and constraints in thermal adaptation and their energetic consequences. It is hypothesized that the high costs of functional adaptation to fluctuating temperatures, especially in the cold (cold eurythermy), cause an increase in energy turnover and, at the same time, mobility and agility. These costs are associated with elevated mitochondrial capacities at minimized levels of activation enthalpies for proton leakage. Cold eurythermy is seen as a precondition for the survival of evolutionary crises elicited by repeated cooling events during extreme climate fluctuations. The costs of cold eurythermy appear as the single most important reason why metazoan evolution led to life forms with high energy turnover. They also explain why dinosaurs were able to live in subpolar climates. Finally, they give insight into the pathways, benefits, and trade‐offs involved in the evolution of constant, elevated body temperature maintained by endothermy. Eurythermy, which encompasses cold tolerance, is thus hypothesized to be the “missing link” between ectothermy and endothermy. Body temperatures between 32° and 42°C in mammals and birds then result from trade‐offs between the limiting capacities of ventilation and circulation and the evolutionary trend to maximize performance at the warm end of the thermal tolerance window.
A Project for the Construction of an Italian Lexical Knowledge Base in the Framework of WordNet

This paper describes a project that aims to develop a large-size Lexical Knowledge Base (LKB) for the Italian language. The project began because presently there is no LKB available for Italian, on an electronic support, that can be used both for natural language processing and lexicography applications. To develop the LKB techniques developed in artificial intelligence that allow acquisition and automatic data structuring will be used
Impact of Shadowing Correlation on Spectrum E ffi ciency of a Power Controlled Cellular System

Independent shadowing losses are often assumed for computing the frequency reuse distance of cellular mobile communication systems. However, shadowing losses may be partially correlated since the obstacles surrounding a mobile station block similarly the desired signal and interfering signals. We investigate, by computer simulation, how the shadowing correlation impacts the frequency reuse distance of a power controlled cellular system. It is pointed out that the shadowing correlation impacts the frequency reuse distance differently for the uplink and downlink. key words: cellular system, frequency reuse distance, transmit power control, outage, shadowing correlation
An LTCC balanced-to-unbalanced extracted-pole bandpass filter with complex load

In this paper, the fundamental characteristics of a novel third-order RF balanced-to-unbalanced filter, namely, a balun filter, for integrated RF module applications are presented. This center-tapped transformer-based new device works concurrently as a balun, an extracted-pole bandpass filter, and a matching network. As coupled resonant tanks are employed to perform the balun type of operation, traditional coupled-resonator filter theory can thus be used to design and analyze such a new device. Moreover, an extracted-pole technique is used not only for creating a transmission zero, but also provides a capability to match the filter with a complex load. In addition to providing a simple design procedure for the device, its working mechanism is also revealed mathematically. Specifically, return-loss sensitivity with respect to each resonator admittance and complex load matching capability are discussed in details. This balun filter has been implemented in a multilayered low-temperature co-fired ceramic substrate, demonstrating its promising potentials in miniaturized RF front-end modules. Experimental measurements are also presented to validate the theory and computer simulations.
Type-2 Fuzzy PD Controller Tuning using Quantum-inspired Evolutionary algorithm

Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.
Engineering 'unbounded' reusable ada generics

Most current programming languages (including Ada) provide some means of allowing the programmer to dynamically allocate and deallocate heap storage. This permits construction of “unbounded” abstract data types, e.g., stacks, queues, one-way lists, etc. Unfortunately, the addition of dynamically allocated storage to the implementation of abstract data types is a complicated business. Unless special care is taken, it can lead to problems of storage leaks, dangling references, unwanted aliasing, and unexpected lengthy execution times (due to storage allocation and reclamation), among others. We propose a specific discipline for avoiding these problems.
A Toolchain For Profiling Virtual Machines

Performance tuning is a common topic in the research domain High Performance Computing. Currently, various tools have been developed to help programmers understand the runtime execution behavior of their applications. It is clear that such tools are also required for performance analysis on virtual machines, where applications, together with their execution environment, sit on top of a virtualization layer rather than running directly on the physical machines. This work developed a toolchain (also called workflow system in the following), specifically for performance analysis on virtual machines. Starting with a profiling tool, the workflow system first collects the runtime performance data on both physical and virtual machines. The performance data are filtered, combined, transformed, and then delivered to a visualization tool, where graphical views are produced to demonstrate the performance difference between native executions and the execution on virtual machines. We tested the toolchain with standard benchmark applications running either sequentially or in parallel with multiple threads.
On Improved Learning Algorithms with Adaptive ParameterRegulation in Feedforward

This paper should contribute to a structured and theoretical view of the backpropagation algorithm and some of its well-known extensions. Basing on a mathematical investigation of the algorithms conditions for structured improvements and developments of these techniques will be described. The construction of adaptive parameter regulations for learning and momentum rate will follow. These parameter regulations allow the presentation of adaptive learning techniques. It will be shown that oo-line versions of these techniques represent minimization methods which are exact in mathematical sense. Under consideration of complexity conditions on-line algorithms will be preferred and described in detail. Finally their numerical behaviour will be investigated and simulation results will be presented in comparision with standard algorithms.
The Signaling Role of Promotions: Further Theory and Empirical Evidence

An extensive theoretical literature investigates the role of promotions as a signal of worker ability. We extend the theory by focusing on how the signaling role of promotion varies with education and then investigate the resulting predictions using a longitudinal data set that contains detailed information concerning the internal-labor-market history of a medium-sized firm in the financial services industry. Our results support signaling being important for understanding the differences between promotion practices concerning bachelor’s and master’s degree holders, while the evidence concerning the importance of signaling for high school graduates and PhDs is mixed.
Web Server Power Estimation, Modeling and Management

An Internet server center provides multiple service sites by means of a multiple server pool. This paper presents a scalable multiple server (SMS) architecture design for resource management in a server center, with an emphasis on the proper balance of energy and performance. The goals are to provide different servers for different service sites in a way that automatically adapts to the offered load and improve the energy efficiency of the server pool by dynamically reconfiguring the server pool in accordance with an analytic model. We analyze the power consumption of a Web server as a function of a server's utilization based on experimental arrival data. Two power models such as linear and exponential are shown to fit the experimental arrival data. The linear model is used with a flow-equivalent approximate queuing analysis to minimize power consumption of the Web server. We validated our model by comparing the various working loads generated by a benchmark against measurements. The experimental results demonstrate the calculated values of the model tracks and the results generated by real machines. We also tested our SMS architecture by applying it to a real-life Web server center, and achieving a 16.9 % reduction in energy consumption
rms Angular Spread Estimation Using CDM Based MIMO Channel Sounder with Loosely Synchronous Codes and Kasami Codes

This paper presents rms angular spread estimation using the code-division multiplexing (CDM) based MIMO channel sounder applied loosely synchronous (LS) codes and Kasami codes for real time measurement of MIMO radio channel. Since this scheme has drawback of reduced dynamic range depending on the number of transmit antennas, it is important that low correlation codes should be utilized to get reliable performance. In this paper, the proposed scheme adopts two efficient codes, LS codes and Kasami codes, of which performance is investigated through Monte-Carlo simulation in 2 times 8 and 4 times 8 MIMO channel environment, respectively. According to the simulation focused on rms angular spread estimation, LS codes can be used for 2times8 MIMO channel measurement and Kasami codes is suitable for measuring 4times8 MIMO channel. For measuring 4times8 MIMO channel with LS codes properly, some modification is taken to the LS codes. Unitary ESPRIT is chosen for DOA estimation and rms angular spread is taken for the performance comparison
Received ; Accepted

We present a luminosity function (LF) for lower main sequence stars in the Galactic bulge near (l, b) = (0 • , −6 •) to J = 24, corresponding to M J ∼ 9.3. This LF is derived from Hubble Space Telescope (HST) + Near Infrared Camera and Multi Object Spectrometer (NICMOS) observations with the F110W and F160W filters. Our derived mass function (which is not corrected for unseen companions) is the deepest measured to date, and extends to 0.15 M ⊙ with a power law slope of α = −1.33 ± 0.07; a Salpeter mass function would have α = −2.35. We also combine our J band LF with previously published data for the evolved stars to produce a LF spanning 15 magnitudes. We show that our derived mass function has negligible dependence on metallicity and adopted bulge distance modulus. The main sequence locus in the infrared shows a strong change in color at M J = +5.5 which is well fit by new low mass models that incorporate atmospheres with water and molecular hydrogen opacity. Although shallower than the Salpeter slope, our slope is steeper than has been recently found for the Galactic disk (α = −0.8 and α = −0.54 from the data of Reid & Gizis, 1997, and Gould et al. 1997, respectively, in the same mass interval). Our mass function also is in good agreement with deep mass functions derived for those globular clusters which are believed to have experienced little or no dynamical evolution. The new mass function may account for the number and duration of bulge microlensing events using normal low mass stars, without requiring an extraordinarily large brown dwarf population. – 3 – mass function — galaxy: stellar content – 4 –
State control of DFIG in converter-fixed reference frame for wind-energy plants

Doubly-fed induction generators (DFIG) still play an important role in wind-energy applications. One of the major challenges concerning their operation is to meet not only steady-state, but also dynamic requirements. State-of-the-art DFIGs are often controlled applying dq-control structures to guarantee steady-state power-quality requirements. The need of an exactly known transformation angle causes problems, especially under grid faults. Flux-based approaches offer more potential under grid faults, but no current control which is essential to fulfil certain requirements under grid conditions. A new control approach based on inverter-fixed coordinates is presented, allowing fast reaction to dynamics and satisfying also the steady-state power-quality requirements. The advantages of both, current control and inverter-fixed reference frame, are combined in this control concept. Even at grid faults, the new approach provides highly dynamic behaviour which is under analysis in this paper.
Learning-based entity resolution with MapReduce

Entity resolution is a crucial step for data quality and data integration. Learning-based approaches show high effectiveness at the expense of poor efficiency. To reduce the typically high execution times, we investigate how learning-based entity resolution can be realized in a cloud infrastructure using MapReduce. We propose and evaluate two efficient MapReduce-based strategies for pair-wise similarity computation and classifier application on the Cartesian product of two input sources. Our evaluation is based on real-world datasets and shows the high efficiency and effectiveness of the proposed approaches.
KETAMINE'S MECHANISM OF ACTION: A PATH TO RAPID‐ACTING ANTIDEPRESSANTS

Major depressive disorder (MDD) is a common and debilitating psychiatric disorder. Traditional antidepressants are of limited efficacy and take weeks to months to yield full therapeutic effects. Thus, there is a clear need for effective rapid‐acting antidepressant medications. The N‐methyl‐d‐aspartate receptor (NMDA‐R) antagonist, ketamine, has received a great deal of attention over the last 20 years due to the discovery that a single subanesthetic dose leads to a rapid antidepressant effect in individuals with treatment‐resistant depression. Animal and human research suggest that ketamine's antidepressant effects are mediated by a glutamate surge that leads to a cascade of events that result in synaptogenesis and reversal of the negative effects of chronic stress and depression, particularly within the prefrontal cortex (PFC). Preclinical and clinical data have provided compelling insights into the mechanisms underlying the rapid‐acting antidepressant effects of ketamine. This review discusses stress‐related neurobiology of depression and the safety, tolerability, and efficacy of ketamine for MDD, along with a review of ketamine's mechanism of action and prospective predictors of treatment response. Research limitations and future clinical prospects are also discussed.
Goal-Driven Development Method for Managing Embedded System Projects: An Industrial Experience Report

Technologies and methods for the development of embedded system projects are highly constrained by predefined hardware and software platforms. In this sense, embedded system projects may have more goals (derived from constraints) to achieve than regular software projects. Without pragmatic support, engineers from different disciplines are likely to neglect some project goals in the real-world embedded system projects. As a consequence, the success of embedded system projects may be more difficult to achieve than regular software projects. In this paper we report experiences gained during applying a goal driven project management methodology on several embedded system projects in a software company. We evaluated the effectiveness and efficiency of our Goal-Driven Development (GDD) methodology in practice by both projects results and feedbacks from relevant stakeholders. The results of our study show that GDD enables embedded system project teams to systematically and effectively identify, understand, track, and ultimately realize the project goals to meet relevant stakeholders' expectations. Being supported by GDD, explicit linkages and assignments are established between goals and solutions with project team's commitments.
A point-based POMDP algorithm for robot planning

We present an approximate POMDP solution method for robot planning in partially observable environments. Our algorithm belongs to the family of point-based value iteration solution techniques for POMDP, in which planning is performed only on a sampled set of reachable belief points. We describe a simple, randomized procedure that performs value update steps that strictly improve the value of all belief points in each step. We demonstrate our algorithm on a robotic delivery task in an office environment and on several benchmark problems, for which we compute solutions that are very competitive to those of state-of-the-art methods in terms of speed and solution quality.
Lifting parameterisation of the 9/7 wavelet filterbank and its application in lossless image compression

The description of filter banks using lifting structures does not only benefit low-complexity implementation in software or hardware, but is also advantageous for the design of filter banks because of the guaranteed perfect reconstruction property. This paper proposes a new design method for wavelet filter banks, which is explained based on a single lifting structure suitable for 9/7 filter pairs. The modification of the standard design constraints leads to a family of related filter pairs with varying characteristics. The filters are derived directly, the factorisation of known filters is not necessary. The application of the designed filters to lossless image compression is investigated.
Usage intention of automated vehicles amongst elderly in the Netherlands

With the aim of investigating the perception of elderly on two types of automated vehicle (owned and shared) this thesis research questioned 123 elderly respondents on their intention of using AV in the (near) future and what the main reasons for (not) using these technologies are. By using behavioral modeling and a modified UTAUT model the main characteristic of AV were evaluated to see which has the biggest positive or negative influence on the behavioral intention. The research results show that elderly in the Netherlands are largely positive towards AV and that there is a preference for the owned AV compared to the shared AV system. It is also revealed that there are significant differences in usage intention between different groups of elderly. This thesis contributes to the research done on the potential impacts of AV and shows that the suggested methods create a valid estimation of the usage intention of AV by elderly.
Application for a postdoctoral position at CLT Göteborg – Project description – Theme : An environment for grammar engineering supporting different linguistic formalisms

For many NLP applications (e.g. generation, machine translation, etc.), large linguistic resources are needed. These resources include (but are not limited to) lexicons and grammars. The latter were originally written by hand. This task of grammar writing was requiring many human resources. Plus, the coherence between the grammatical structures was hard to guarantee (and maintain), as the number of structures / people involved were raising [5]. To deal with these issues, several proposals have been made to automate grammar production. The main proposals are grammar extraction, grammar inference and grammar generation. In this proposal, we focus on the latter. Grammar generation is based on a formal description of the grammar which is processed to produce a real-size grammar. This technique allows the grammar designer to express linguistic generalisations and to test different representation theories. Grammar generation systems can be divided in two main categories, systems based on transformation rules (e.g. meta-rules or lexical rules) and systems based on composition rules (e.g. metagrammars). While in the former, the factorisation needed to describe a real-size grammar is provided by transformation rules allowing for the expansion of canonical trees, in the latter, the factorisation arises from the definition of (i) elementary fragments, and (ii) composition rules over these fragments. This factorised definition of the grammatical structures is sometimes called a metagrammar.
Evaluation of the United States Food and Drug Administration-approved scoring and test system of HER-2 protein expression in breast cancer.

PURPOSE The purpose of this study was to investigate the prognostic significance of assessment of human epidermal growth factor receptor (HER)-2 oncogene protein overexpression of breast cancer tissue by the United States Food and Drug Administration (FDA)-approved HercepTest and grading system (negative, 0 or 1+; weakly positive, 2+; strongly positive, 3+). Furthermore, results of the HercepTest were correlated with immunohistochemical results obtained using different antibodies and protocols and with HER-2 oncogene gene amplification assessed by fluorescence in situ hybridization (FISH). EXPERIMENTAL DESIGN HER-2 status in 303 patients with lymph node-positive breast cancer was investigated by using a rabbit polyclonal antibody (DAKO) by conventional immunohistochemistry and by applying the HercepTest. Furthermore, the monoclonal antibody CB-11 was used in conventional immunohistochemistry and with the NexES automatic stainer, which is also under consideration for FDA approval for determination of eligibility for Herceptin therapy. Results were compared with FISH analysis performed in all 2+ and 3+ specimens (103 cases) and 104 HER-2-negative specimens. RESULTS 3+ positive carcinomas were found in 8.9-15.7% of specimens. FISH revealed that almost exclusively 3+ positive cases were amplified, with the HercepTest and the NexES automatic stainer giving the best results. In univariate analysis, staining with the HercepTest revealed a significantly worse prognosis in 3+ cases. Also, 3+ cases were significantly associated with lower estrogen receptor levels and histological grade III tumors. CONCLUSIONS This study shows that the results of the FDA-approved HER-2 grading and test system correlated strongly with findings in FISH. Furthermore, HercepTest proved to be of prognostic relevance. Strict adherence to the given protocols is critical.