Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary study on contrast flow analysis of thoracic transforaminal epidural block

Background The thoracic transforaminal epidural block (TTFEB) is usually performed to treat herpes zoster or postherpetic neuralgia (PHN). Especially, multiple segmental involvements and approximate contrast medium spread range, according to volume, help to choose the proper drug volume in the transforaminal epidural block. This study investigated the contrast medium spread patterns of 1-ml to 3-ml TTFEBs. Methods A total of 26 patients with herpes zoster or PHN were enrolled in this study. All participants received 1 ml, 2 ml, or 3 ml of contrast medium. Results were divided into Groups A, B and C based on the volume (1, 2, or 3 ml), with n = 26 for each group. After the injection of contrast medium, the spread levels were estimated in both the lateral and anteroposterior (AP) images using fluoroscopy. Results The cephalad spread of contrast medium in the lateral image as expressed by the median (interquartile range) was 2.00 levels (1.00–2.00) for Group A, 2.50 (2.00–3.00) for Group B, and 3.00 (2.00-4.00) for Group C. The caudal spread level of contrast medium was 1.00 (1.00-2.00) for Group A, 2.00 (2.00–3.00) for Group B, and 2.00 (2.00–3.00) for Group C. There was ventral and dorsal spread of the 3-ml contrast medium injection in 88% (23/26) of cases in the lateral image. Conclusions Injection of 3 ml of contrast medium through the foramina spread 6 levels in a cephalocaudal direction. Spread patterns revealed a cephalad preference. TTFEB resulted in dorsal and ventral spread in a high percentage of cases. This procedure may be useful for transferring drugs to the dorsal and ventral roots.
Development of a Three-Station Creep Machine for Adhesive Joints Testing

Adhesives are increasingly proving their superiority over traditional joining methods. Notwithstanding, only in recent times have both the industry and the academia invested their efforts into the further exploration of these materials and so, additional studies are imperative. The phenomenon of creep in adhesives is particularly unexplored. In FEUP’s Adhesives Group (ADFEUP), the study and characterization of adhesives and adhesive bonds is the main focus of research. ADFEUP makes use of various testing equipments, but lacks a dedicated device capable of performing creep tests, which, by nature, are very time consuming. This work’s main goal was to conclude the task, already started in previous master dissertations, of developing and implementing a machine capable of carrying out multiple and independent creep tests on adhesive joints, simultaneously. The machine should be able to regulate and maintain a specific load on the specimens and to measure and record the loads and the specimens’ resulting displacements during testing. A revision of the hardware proposed by Freire and Pina’s master dissertations, was carried out, followed by the necessary adjustments and additions to each of the three essential sub-systems: the mechanical components, the pneumatic, and the electric circuits. The machine was then assembled and the system’s software defined and successfully implemented in LabVIEW. Lastly, tests were carried out, ascertaining the machine’s capabilities.
Characterization of Progressive Fatigue Damage in Solid Plates by Laser Ultrasonic Monitoring of Zero-Group-Velocity Lamb Modes

Many engineered objects endure stress throughout their lifetimes, typically leading to material fatigue and failure, which can turn to tragedy, as in the Versailles rail accident of 1842. Thus quantitatively assessing the level of cumulative fatigue damage is of great interest in many contexts, and should promote our insight into the underlying physics at the several stages of fatigue. The authors find that the frequency of a particular surface-acoustic-wave elastic Lamb mode is a reliable indicator of the fatigue level in a thin metal film. This technique should also work for other systems in which these Lamb modes are observable, including alloys, composites, glasses, and polymers.
On the optimal PID performance tuning for robotic manipulators

Although most robotic manipulators have used the conventional PID or PID plus something, e.g., gravity compensator, friction compensator, disturbance observer and so on, there exist still no general tuning rules which can adjust the PID control performance. The paper explains the tuning methods of inverse optimal PID control assuring the extended disturbance input-to-state stability and shows its validity through many experiments for a robotic manipulator.
1 2 4 Fe b 20 04 A poor man ’ s positive energy theorem

We show that positivity of energy for stationary, asymptotically flat, non-singular domains of outer communications is a simple corollary of the Lorentzian splitting theorem. A milestone in mathematical general relativity is the positive energy theorem [8, 10]. It is somewhat surprising that the standard proofs of this result do not have anything to do with Lorentzian geometry. In this note we prove energy positivity using purely Lorentzian techniques, albeit for a rather restricted class of geometries; it seems that in practice our proof only applies to stationary (with or without black holes) space-times. This is a much weaker statement than the theorems in [8, 10] and their various extensions, but the proof here seems of interest because the techniques involved are completely different and of a quite elementary nature. Using arguments rather similar in spirit to those of the classical singularity theorems [5], our proof is a very simple reduction of the problem to the Lorentzian splitting theorem [4]. (In lieu of the Lorentzian splitting theorem, one can impose Partially supported by a Polish Research Committee grant 2 P03B 073 24; email piotr@gargan.math.univ-tours.fr, URL www.phys.univ-tours.fr/∼piotr Partially supported by NSF grant # DMS-0104042; email galloway@math.miami. edu
Error resilience analysis for systematically employing approximate computing in convolutional neural networks

Approximate computing is an emerging paradigm for error resilient applications as it leverages accuracy loss for improving power, energy, area, and/or performance of an application. The spectrum of error resilient applications includes the domains of Image and video processing, Artificial Intelligence (AI) and Machine Learning (ML), data analytics, and other Recognition, Mining, and Synthesis (RMS) applications. In this work, we address one of the most challenging question, i.e., how to systematically employ approximate computing in Convolution Neural Networks (CNNs), which are one of the most compute-intensive and the pivotal part of AI. Towards this, we propose a methodology to systematically analyze error resilience of deep CNNs and identify parameters that can be exploited for improving performance/efficiency of these networks for inference purposes. We also present a case study for significance-driven classification of filters for different convolutional layers, and propose to prune those having the least significance, and thereby enabling accuracy vs. efficiency tradeoffs by exploiting their resilience characteristics in a systematic way.
Using a Rayleigh Fading Channel and Finite State Markov Model for Analyzing the 'WBC over DVB-H' Performance

For the new proposal of using digital video broadcasting for handheld terminals (DVB-H) as a broadcast platform for wireless billboard channels (WBCs), this paper proposes to use classical Rayleigh fading channel modeling techniques to analyze the performance of such a broadcast platform for this usage. Effectively the performance figure of merit employed is the DVB-H transport stream packet error rate (TSPER). Some early performance results are found assuming a Rayleigh fading channel with a central chi-square distribution and utilizing a corresponding finite state Markov model (FSMM).
Carbon nanotube film

The present invention relates to a carbon nanotube film, comprising between the carbon nanotube film includes a plurality of carbon nanotube wires parallel with and spaced from and adjacent to at least one carbon nanotube carbon nanotube wires, the plurality of carbon nanotube wires changes in the distance between the rear force.
BLISP: Enhancing backscatter radio with active radio for computational RFIDs

We introduce the world's first hybrid radio platform which combines the strengths of active radio (long range and robustness to interference) and Computational RFID (CRFID) (low power consumption). By a set of laboratory experiments, we show that our hybrid radio - composed of Wireless Identification and Sensing Platform (WISP) CRFID radio and Bluetooth Low Energy (BLE) - obtains higher goodput than WISP and lower energy consumption than BLE, both as stand-alone platforms.
Scenario based uncertainty modeling of electricity market prices

Energy trading in liberalized electricity markets is a decision-making problem that is modeled considering price uncertainty. Stochastic programming is a natural platform for modeling such decision-making problems, where uncertainties are characterized through scenarios. Scenarios are possible outcomes of random process with corresponding occurrence probabilities. A large number of scenarios are required for accurate modeling of any uncertainty. However, due to computational complexity and time limitations, generated scenarios are required to be reduced. This paper presents a efficacious algorithm for generation and reduction of electricity market price scenarios. Time series based Auto Regressive Moving Average (ARMA) model is used for scenario generation while Probability Distance Based Backward reduction method is utilized for scenario reduction. Proposed algorithm is illustrated through practical case study based on PJM day-ahead electricity market. Statistical analysis validates the proposed algorithm and comparison between ARMA and heuristic model for scenario generation reflect strength of proposed algorithm for modeling electricity market price uncertainty.
An empirical analysis of the determinants of corporate crime in Malaysia

Corporate crime is not new in Malaysia. Each year the cases reported have increased dramatically. The phenomenon will undermine the confidence of both existing and potential investors. In this study, we aim to investigate the determinants of corporate crime activities in organizations, in order to minimize the occurrence of fraud. A survey involving existing and potential investors was undertaken. The findings indicate that the corporate crime determinants ranked by most of the respondents are insufficient controls, followed by personal financial pressure and expensive lifestyle. To minimize the occurrence of corporate crime activities in the organizations, the management team should impose tighter control over internal operations.
Part-of-Speech Tagging With Neural Networks

Text corpora which are tagged with part-of-speech information are useful in many areas of linguistic research. In this paper, a new part-of-speech tagging method based on neural networks (Net-Tagger) is presented and its performance is compared to that of a HMM-tagger (Cutting et al., 1992) and a trigram-based tagger (Kempe, 1993). It is shown that the Net-Tagger performs as well as the trigram-based tagger and better than the HMM-tagger.
A fast and efficient two-dimensional frame composer for OFDMA WiMAX base-stations using floorplan slicing

The WiMAX OFDMA environment is unique in that it requires a two-dimensional allocation i.e. simultaneously in time and frequency on the downlink. The downlink resource has to be broken into sub-rectangles, each of which is allocated to one or more flows. In this paper, we have proposed a fast allocation algorithm to allocate the downlink resource to multiple flows while honouring Quality of Service and concurrency requirements. We present simulation results to show the performance of the algorithm.
Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning

This paper introduces a novel method for forming efficient one-class classifier ensembles. A common problem in one-class classification is a complex structure of the target class, which often leads to creation of a too expanded decision boundary. We propose to employ a clustering step in order to partition the target class into atomic subsets and using these as input for one-class classifiers. By this, we are able to detect sub-structures in the target concept. Additionally, to increase the diversity and robustness of our method weighted one-class classifiers are used. We introduce a novel scheme for calculating weights for training objects. Membership functions, obtained from the fuzzy clustering, are used to initialize the weighted classifiers. Based on the results of a number of computational experiments we show that the proposed method outperforms both the single one-class methods, as well as popular one-class ensembles. Other advantages are the highly parallel structure of the proposed solution, which facilitates parallel training and execution stages, and the relatively small number of control parameters.
Investigation of the antioxidant behavior of air- and freeze-dried aromatic plant materials in relation to their phenolic content and vegetative cycle.

The total phenolic and flavonoid content of the aerial parts of five aromatic plants harvested at different periods was estimated, and their antioxidant capacity was evaluated. Major phenolic compounds present in their extracts were determined by RP-HPLC. The results demonstrated different amounts of total phenolic compounds and various degrees of antioxidant activity depending on the plant species, the time of harvest, and the drying method employed. Extracts from air-dried Mentha viridis L. , Origanum majorana L. , and Rosmarinus officinalis L. demonstrated the greatest efficacy during the flowering stage, in which the identified flavonoids were found in significantly higher amounts, whereas phenolic acids were found in their lowest concentration. Extracts from air-dried Laurus nobilis L. and Foeniculum vulgare Mill were less efficient in terms of antioxidant activity, with the highest values being observed during the early fruiting stage. This stage was characterized by the lowest flavonoid content and high phenolic acid content, except for L. nobilis L. extracts. Overall, the amount of identified phenolic acids did not vary considerably within the investigated year. The total phenolic concentration in all plant extracts decreased significantly when freeze-dried rather than air-dried samples were used. The HPLC analysis further supported the above for most of the phenolic compounds present in the extracts, except for hydroxybenzoic acids, which were better retained during the freeze-drying process.
Atomic shared register access by asynchronous hardware

The contribution of this paper is two-fold. First, we describe two ways to construct multivalued atomic n-writer n-reader registers. The first solution uses atomic 1-writer 1-reader registers and unbounded tags. the other solution uses atomic 1-writer n-reader registers and bounded tags. The second part of the paper develops a general methodology to prove atomicity, by identifying a set of criteria which guaranty an effective construction for the required atomic mapping. We apply the method to prove atomicity of the two implementations for atomic multiwriter multireader registers.
A web application for the unspecific detection of differentially expressed DNA regions in strand-specific expression data

UNLABELLED Genomic technologies allow laboratories to produce large-scale data sets, either through the use of next-generation sequencing or microarray platforms. To explore these data sets and obtain maximum value from the data, researchers view their results alongside all the known features of a given reference genome. To study transcriptional changes that occur under a given condition, researchers search for regions of the genome that are differentially expressed between different experimental conditions. In order to identify these regions several algorithms have been developed over the years, along with some bioinformatic platforms that enable their use. However, currently available applications for comparative microarray analysis exclusively focus on changes in gene expression within known transcribed regions of predicted protein-coding genes, the changes that occur in non-predictable genetic elements, such as non-coding RNAs. Here, we present a web application for the visualization of strand-specific tiling microarray or next-generation sequencing data that allows customized detection of differentially expressed regions all along the genome in an unspecific manner, that allows identification of all RNA sequences, predictable or not. AVAILABILITY AND IMPLEMENTATION The web application is freely accessible at http://tilingscan.uv.es/. TilingScan is implemented in PHP and JavaScript. CONTACT vicente.arnau@uv.es SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
BaTiO3-Based Lead-Free Electroceramics with Their Ferroelectric and Piezoelectric Properties Tuned by Ca2+, Sn4+ and Zr4+ Substitution Useful for Electrostrictive Device Application

Dense microstructure BaTiO3 (BT) ceramic with c/a ~1.0144 and average grain size ~7.8 μm is developed by achieving the ferroelectric parameters Psat. = 24.13 μC/cm2 and Pr = 10.42 μC/cm2 with lower coercive field of Ec = 2.047 kV/cm. For BT ceramic, the “sprout” shape nature is observed for strain-electric field measurements with remnant strain ~ 0.212%, converse piezoelectric constant ~376.35 pm/V and electrostrictive coefficient Q33~ 0.03493 m4/C2. To tune the piezoelectric properties of BT ceramic, the substitutions of Ca2+ and Sn4+, Zr4+ are done for Ba2+ and Ti4+ sites respectively. The Ba0.7Ca0. 3Ti1-xSnxO3 (x = 0.00, 0.025, 0.050, 0.075, and 0.1, BCST) system was studied with ferroelectric, piezoelectric and electrostrictive properties. The electrostrictive coefficient (Q33) ~ 0.0667 m4/C2 was observed for x = 0.075 and it is higher than the lead-based electrostrictive materials. Another (1-X) Ba0.95Ca0. 05Ti0.92Sn0. 08O3 (BCST) – (X) Ba0.95Ca0. 05Ti0.92Zr0. 08O3 (BCZT), ceramics (x = 0.00, 0.25, 0.50, 0.75, and 1) is studied. The BCST-BCZT ceramic system shows the increase of polymorphic phase transition temperatures toward the room temperature by Ca2+, Sn4+ and Zr4+ substitution. For BCST-BCZT system the composition x = 0.75 exhibits the d33, and Q33 values of 310 pC/N, 385 pm/V and 0.089 m4/C2 respectively which is greater than BT ceramics.
Games in dynamic epistemic logic

The author discusses games of both perfect and imperfect information at two levels of structural detail: players' local actions, and their global powers for determining outcomes of the game. Matching logical languages are proposed for both. In particular, at the "action level", imperfect information games naturally model a combined "dynamic-epistemic language"--and correspondences are found between special axioms in this language and particular modes of playing games with their information dynamics. At the "outcome level", the paper presents suitable notions of game equivalence, and some simple representation results. Copyright 2001 by Blackwell Publishing Ltd and the Board of Trustees of the Bulletin of Economic Research
Minor Traumatic Brain Injury: A Primer for the Orthopaedic Surgeon

Abstract Minor traumatic brain injury (mTBI) is a major public health problem. The Centers for Disease Control and Prevention and the National Center for Injury Prevention and Control label it a “silent epidemic. ” Subtle signs and symptoms of mTBI, including headache, fatigue, and memory loss, are often seen in conjunction with musculoskeletal trauma. Although sometimes evident immediately, mTBI may not manifest until patients return to work and their personal lives. In the patient with acute concurrent mTBI, skeletal management must be based on either a period of observation to rule out evolving neurologic symptoms or, when warranted, the recommendations of a neurosurgeon. Such input is particularly important when mTBI is associated with a prolonged loss of consciousness or posttraumatic amnesia. In the outpatient setting, when concern for mTBI exists weeks after an injury, familiarity with and referral to locally available mTBI specialists and programs can facilitate proper care. Armed with this knowledge, the orthopaedic surgeon has an opportunity to positively influence outcomes and help provide crucial care that extends beyond the management of musculoskeletal injuries.
Trajectories of Cognitive Function and Associated Phenotypic and Genotypic Factors in Breast Cancer.

OBJECTIVES This study identified women with unique trajectories of executive function, concentration, and visual working memory before and during adjuvant therapy for breast cancer, and examined phenotypic and genotypic predictors associated with subgroups. SAMPLE & SETTING 399 postmenopausal women, of whom 288 were women with early-stage breast cancer and 111 were women without breast cancer, matched on age and years of education to the women with breast cancer, and all at an urban cancer center. METHODS & VARIABLES A repeated-measures design was used; assessments occurred before adjuvant therapy and every six months post-therapy initiation. Group-based trajectory modeling determined subgroups. Multinomial logistic regression identified phenotypic and genotypic characteristics. RESULTS Three executive function and concentration trajectory subgroups were identified. IMPLICATIONS FOR NURSING Advancing age, greater pretherapy fatigue, and poorer pretherapy cognitive function are associated with the low subgroups. DNA repair and oxidative stress mechanisms may be involved in the cognitive changes that women experience.
Simulations for Structural and Dynamic Properties of Dense Polymer Systems

Recent attempts to investigate the properties of dense and semidilute polymer systems are reviewed. Both molecular dynamics (MD) and Monte Carlo (MC) methods provide direct evidence for the reptation model and give a rather detailed picture of the motion of linear polymers at high density. Mapping the results onto various chemical polymers allow one to predict the time and length scale for the crossover from Rouse to reptation for a variety of polymers. In the free-draining limit one finds that the entanglement length is proportional to the excluded volume screening length of the semidilute solution. Finally, a first attempt to incorporate materialspecific properties into a computer model is discussed.
Adaptive Interest Modeling Enables Proactive Content Services at the Network Edge

We have successfully applied user modeling in a networking project. The goal of the project was to develop the network services to enable efficient and transparent distribution of content in mobile ad-hoc network (MANET) environments often deployed in emergency and tactical situations. How to get the relevant content to the right user quickly, in the midst of network disruptions and resource constraints, is a key research challenge. To address this problem, we have developed adaptive interest modeling (AIM) to capture user interests and information needs and build an interest model (IM) for each node. One key contribution of our approach is to anchor AIM at the content-based network layer, which allows all upper level mobile applications to benefit without modification. This adaptive IM can enable many user-aware features including content prefetching and IM sharing. We have developed a unique type of prefetching that is based on recognizing user situations. IM sharing is a novel and efficient way of automatically keeping users up to date with each other. This is especially useful in tactical scenarios where it is important to have a common operational picture among users. Our network emulation experiments show that IM-enabled prefetching significantly reduces response time while increasing data availability at the same time. When combined with IM sharing, additional sizable reduction in response time is achieved. Keywords—user modeling; context awareness; mobile device; interest; MANET; network layer; content availability; prefetch; sharing