Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic CT measurement of cerebral blood flow: a validation study.

BACKGROUND AND PURPOSE Our objective was to develop a method to correct for the effect of partial volume averaging (PVA) in the CT measurement of contrast enhancement in small arteries, and to validate a dynamic contrast-enhanced CT method for the measurement of regional cerebral blood flow (rCBF). METHODS Contrast-enhanced CT scans of tubes of known inner diameters were obtained to estimate the size-dependent scaling factors (PVSF) due to PVA. The background-subtracted image profiles of the contrast-filled tubes were fitted to gaussian curves, and the standard deviations (SDs) of these curves were correlated with the PVSF of each tube. In the second part of this investigation, 13 studies were performed in six New Zealand white rabbits under normal conditions. Dynamic CT measurements of rCBF, regional cerebral blood volume (rCBV), and regional mean transit time (rMTT) were calculated in the left and right parietal lobes and the basal ganglia. The CT rCBF values were compared with those obtained by the microsphere method, which is the standard of reference. RESULTS We found strong correlations for the SDs of the gaussian curves to the known inner diameters of the tubes and to their size-related PVSF. These correlations demonstrated that the error from PVA in the measurement of arterial enhancement can be corrected without knowledge of the actual size of the artery. The animal studies revealed a mean (+/- SD) rCBF of 73.3 +/- 31.5 mL/100 g per minute, a mean rCBV of 1.93 +/- 0.74 mL/100 g, and a mean rMTT of 1.81 +/- 1.02 seconds. A strong correlation was found between rCBF values derived by the CT and the microsphere methods. CONCLUSION We have validated a new dynamic CT method for measuring rCBF. The accuracy of this technique suggests that it can be used as an alternative diagnostic tool to assess the cerebral hemodynamics in experimental and clinical situations.
Semen culture and the assessment of genitourinary tract infections

The male factor contributes approximately 50% to infertility-related cases in couples with an estimated 12%–35% of these cases attributable to male genital tract infections. Depending on the nature of the infection, testicular sperm production, sperm transport, and sperm function can be compromised. Yet, infections are potentially treatable causes of infertility. Male genital tract infections are increasingly difficult to detect. Moreover, they often remain asymptomatic (“silent”) with the result that they are then passed on to the relevant sexual partner leading to fertilization and pregnancy failure as well as illness of the offspring. With the worldwide increasing problem of antibiotic resistance of pathogens, proper diagnosis and therapy of the patient is important. This testing, however, should include not only aerobic microbes but also anaerobic as these can be found in almost all ejaculates with about 71% being potentially pathogenic. Therefore, in cases of any indication of a male genital tract infection, a semen culture should be carried out, particularly in patients with questionable semen quality. Globally, an estimate of 340 million new infections with sexually transmitted pathogens is recorded annually. Among these, the most prevalent pathogens including Chlamydia trachomatis, Ureaplasma urealyticum, Neisseria gonorrhoeae, and Mycoplasma hominis. Escherichia coli are considered the most common nonsexually transmitted urogenital tract microbes. These pathogens cause epididymitis, epididymo-orchitis, or prostatitis and contribute to increased seminal leukocyte concentrations.
Treatment Effect of Repairs to an Electrical Grid Leveraging a Machine Learned Model of Structure Vulnerability

Consolidated Edison of New York is the utility company that provides electrical power to New York City. As of late 2004, the Public Service Commission of the State of New York requires Con Edison to inspect all electrical structures in the power grid, such as manholes and service boxes, at least once every five years. In our previous work, we implemented a process to assemble a wide array of textual and semi-structured data and from it to produce a machine learned ranking of vulnerability of secondary structures for a given year. For the work reported here, we were asked to analyze the inspections data from the first five-year cycle for Manhattan, to determine if a relation could be found with our structure ranking. This paper describes the results of causal inference using the inspections data. We tested whether repairs carried out in response to inspections have a positive impact on the health of structures. Results indicate a highly significant effect in which repairs triggered by inspections reduce events in the immediately following year. We then partitioned the structures into distinct strata based on their structure rank, and again tested for a treatment effect of repairs. This stratified analysis yields a decreasing incidence of events for each next stratum with lower vulnerability. The results both confirm the empirical adequacy of the structure ranking we produce, and demonstrate its utility for assessment of maintenance and repair activities carried out on the secondary grid. In turn, these results can have a positive impact on sustainability through more directed allocation of resources, by allowing structures that are more vulnerable to be inspected earlier. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. SustKDD 2011 August 2011, San Diego, CA, USA Copyright 2011 ACM 978-1-4503-0840-3 . $10.00.
Primary relaxation in a hard-sphere system.

The \ensuremath{\alpha}-relaxation dynamics in a hard-sphere system is studied solving microscopic-mode-coupling equations. The solutions for coherent and incoherent dynamical structure factors, the transversal correlation functions, and the moduli are presented for all wave vectors. The wave-vector dependence of fitted Kohlrausch exponents \ensuremath{\beta} and of the relaxation times \ensuremath{\tau} is discussed. Recent experiments on the \ensuremath{\alpha} relaxation of colloidal systems are quantitatively analyzed.
Autonomous underground navigation of an LHD using a combined ICP-EKF approach

A new approach for the autonomous navigation of a load-haul-dump (LHD) truck in an underground mine is presented. The development of a minimal-structure combined ICP-EKF algorithm utilizing a scanning-laser range-finder for the localization of the vehicle is described. The iterative closest point (ICP) algorithm is employed for matching the scanned data to an existing map in the form of a poly-line. This combined approach efficiently deals with the uncertainty present in the range data. An extended Kalman filter (EKF) algorithm is employed, that exploits a nonlinear kinematic model incorporating the vehicle-slip, a nonlinear observation model based on the vertices of the poly-line map, and the bearing of the laser-observations. This provides reliable vehicle estimates. Real data gathered during a trial run in the mine is employed in testing the efficiency of this approach which is found to be robust with respect to occlusions and outliers, demonstrating the successful navigation of the LHD.
“Body coupled FingerRing”: wireless wearable keyboard

A really wearable input device “FingeRing” is developed for coming wearable PDAs. By attaching ring shaped sensors on each finger, many commands or characters can be input by finger-tip typing action. “FingeRing” can be used on any typing surface such as a knee or desk, so quick operation is realized in any situation while standing or walking. To improve wearability, a very small, ultra low power wireless transmitter is developed that uses the human body ss part of an electric circuit. “Direct Cou-pling” method enables stable communication even when body contacts any grounded surface. A new symbol coding method that combines order and chord typing is also proposed, and useful typing patterns are chosen by typing speed evaluations. Expert users of musical keyboards can input 52 different symbols at speeds of over 200 symbols per minute by using the combination of FingeRing and the new coding method.
RNA Chaperone Activity of Human La Protein Is Mediated by Variant RNA Recognition Motif*

La proteins are conserved factors in eukaryotes that bind and protect the 3′ trailers of pre-tRNAs from exonuclease digestion via sequence-specific recognition of UUU-3′OH. La has also been hypothesized to assist pre-tRNAs in attaining their native fold through RNA chaperone activity. In addition to binding polymerase III transcripts, human La has also been shown to enhance the translation of several internal ribosome entry sites and upstream ORF-containing mRNA targets, also potentially through RNA chaperone activity. Using in vitro FRET-based assays, we show that human and Schizosaccharomyces pombe La proteins harbor RNA chaperone activity by enhancing RNA strand annealing and strand dissociation. We use various RNA substrates and La mutants to show that UUU-3′OH-dependent La-RNA binding is not required for this function, and we map RNA chaperone activity to its RRM1 motif including a noncanonical α3-helix. We validate the importance of this α3-helix by appending it to the RRM of the unrelated U1A protein and show that this fusion protein acquires significant strand annealing activity. Finally, we show that residues required for La-mediated RNA chaperone activity in vitro are required for La-dependent rescue of tRNA-mediated suppression via a mutated suppressor tRNA in vivo. This work delineates the structural elements required for La-mediated RNA chaperone activity and provides a basis for understanding how La can enhance the folding of its various RNA targets.
Study and Analysis of Multi-Label Classification Methods in Data Mining

Multi-label classification is major research problem in machine learning domain. Multi-label classification is nothing but the variants of classification problem in which different target labels should be allocated to every instance. Multi-label classification is different from the multiclass classification. In general, multi-label classification is defined as problem of searching model which maps the input to binary vectors, rather than outputs in scalars. Basically there are two different techniques for handling the multi-label classification problem such as techniques of problem transformation and techniques of algorithm adaptation. In problem transformation approaches, multi-label classification problem is transformed to binary classification problems set and this can be further processed through single class classifiers. In algorithm adaptation approaches, algorithms are adapted in order to perform the multi-label classification directly. In this paper, different multi-label classification algorithms are studied and evaluated with current research problems. Methods such as binary relevance (BR), high-order approaches, hierarchical tree based algorithms, and the most recent method called ML-Forest are studied and evaluated with different real time datasets such as medical, emotions, yeast etc.
Tradeoffs Aware Design Procedure for an Adaptively Biased Capacitorless Low Dropout Regulator Using Nested Miller Compensation

An adaptively biased, low dropout regulator (AB-LDR) that uses the nested Miller type frequency compensation has been explored in the literature for system-on-chip applications. However, those are mostly focused to solve only specific issues without accounting for all the design tradeoffs. Due to this, additional components/circuits are needed to mitigate the issues like Q-peaking and poor dynamic response in capacitorless condition. In this paper, the various design tradeoffs particularly relevant to the nested Miller compensated regulator architecture, are clearly brought out. Then a detailed design procedure for the same architecture is proposed to achieve a low quiescent current, wide dynamic range, desired dynamic response and a high current efficiency over a given load range. An AB-LDR has been implemented in standard 0.18- μm CMOS technology to validate the effectiveness of the proposed approach. Experimental results show a very good agreement with the theoretical analysis.
Constant Envelope Precoding for MIMO Systems

Constant envelope (CE) precoding is an appealing transmission technique which enables highly efficient power amplification. In this paper, we consider a point-to-point multiple-input multiple-output (MIMO) system with CE precoding under frequency-flat fading, and investigate the joint transceiver design by exploiting multiple antennas at both the transmitter and the receiver, which has not been addressed in prior work. We consider both single-stream transmission (i.e., beamforming) and multi-stream transmission (i.e., spatial multiplexing). For single-stream transmission, we optimize the receive beamforming vector to minimize the symbol error rate (SER) for any given channel realization and desired constellation at the combiner output. By reformulating the problem as an equivalent quadratically constrained quadratic program, we propose an efficient semi-definite relaxation based algorithm to find an approximate solution. Next, for multi-stream transmission, we propose a new scheme based on antenna grouping at the transmitter and minimum mean squared error or zero-forcing based beamforming at the receiver. The transmit antenna grouping and receive beamforming vectors are then jointly designed to minimize the maximum SER over all data streams. Numerical results show that our proposed schemes for both single- and multi-stream transmissions achieve superior error-rate performances as compared with various benchmark schemes. Finally, the error-rate performances of our proposed single- versus multi-stream transmission schemes are compared via simulations under different setups, which provide useful insights to the transmission mode selection for CE-precoded MIMO systems.
On the Optimization of non-Dense Metabolic Networks in non-Equilibrium State Utilizing 2D-Lattice Simulation

Modeling and optimization of metabolic networks has been one of the hottest topics in computational systems biology within recent years. However, the complexity and uncertainty of these networks in addition to the lack of necessary data has resulted in more efforts to design and usage of more capable models which fit to realistic conditions. In this paper, instead of optimizing networks in equilibrium condition, the optimization of dynamic networks in non-equilibrium states including low number of molecules has been studied using a 2-D lattice simulation. A prototyped network has been simulated with such approach, and has been optimized using Swarm Particle Algorithm the results of which are presented in addition to the relevant plots.
A new randomized algorithm for Document Fingerprinting

In today’s world, copy detection is a major problem. Students plagiarize assignments from the web and from each other. In such a scenario, we need a technique that can detect even partial copies between assignments subject to relocation. This problem also finds uses in the context of the web. Search engines are highly interested in detecting copies of entire web documents to avoid displaying the same content multiple times in the result. Document fingerprinting is an efficient technique for the accurate detection of full and partial copies between documents. We have come up with a new randomized algorithm that provides a guarantee that with very high probability, any match of greater than or equal to W characters (an input parameter) will be detected. Moreover, we have small deterministic bounds on the amount of space needed for our algorithm. This is the key way in which it differs from previous work, where either there are no guarantees [1] or the space bounds are very poor [2].
Comparison of nutritional intake in US adolescent swimmers and non-athletes

Swimming is a very popular sport among adolescents in the US. Little is known about the diet of competitive adolescent swimmers in the US but data from other countries indicate several inadequacies, including excessive intake of fat and lower than recommended intake of carbohydrate and several micronutrients that may affect athletic performance and bone accrual. We assessed usual diet, using a food frequency questionnaire and calcium checklist, among 191 adolescent males and females [91 swimmers (mean 13.7, s = 2.5 years) and 100 non-athletes (mean 14.4, s = 2.8 years)]. For both males and females, swimmers and non-athletes generally had similar average intakes of macro- and micro-nutrients, including higher than recommended amounts of total fat (36%) and saturated fat (12%), and inadequate amounts of calcium, vitamin D, and daily servings of fruits, vegetables, grains, and dairy products. This first study of nutritional intake among adolescent swimmers in the US suggests that dietary habits of adolescents who swim competitively may jeopardize optimal athletic performance and place them at risk for future chronic diseases, including osteoporosis.
Re-conceptualizing IT training for the workforce of the future

T-g in information technology (IT) tools has tradit.ionnaHy been defined in terms of skills. Consequently, training methods and appmacbes have focused almost exchwively on ensuring that a trainee acquire the skills required to use an IT tool, and in a specific ihmin. With the advent and increasing use of enterprise wide ET architectures, such as client/server, integrated processes such as work flow systems and integrated packages such as SAP, this narrow view of training will prove to be inadequate in preparing the workforce of tbe future. To train such a workforce, we propose a re-conceptualization ctf training based on a hierarchy of knowledge levels that a trainee will need. We then use this hierarchy to propose an integrated framework that can be wed to develop a comprehensive training strategy. We offer d.irecticms for research that is needed to use cur model to develop effective training strategies. 1.1
Why Lethal autonomous weapon systems are unacceptable

This paper presents an overview of some the issues concerning Lethal Autonomous Weapon Systems (LAWS), mostly with respect to the current state-of-the-art in the concerned areas of technology, but also — albeit to a somewhat lesser degree — in a more general context that will, perhaps, not be so easily invalidated by technological progress. When all is considered, the paper attempts to answer the question: "Why artificial intelligence should not be allowed to make decisions about killing human beings? " The authors are by no means refusing non-lethal autonomous systems, or remotely controlled (non-autonomous) weapons. They merely point to the fact that "lethal" and "autonomous" is not an acceptable combination.
Human Behaviour Analysis based on Sparse Coding

Sparse coding and compressive sensing have attracted lots of interest in the computer vision area. This paper proposes a new scheme to recognize human motions in video sequences based on the sparse representation of image frames. Each frame of a video is transformed to a linear combination of a few elements in a dictionary. The class label of the video is determined based on the reconstruction errors of individual frames or the overall reconstruction error of the video. A series of experiments were conducted to evaluate the performance of the proposed method. Experimental results demonstrate that the sparse representation method achieves an accuracy on par with or exceeding that of existing methods.
*The Impact of Diagnostic Feedback to Teachers on Student Learning: Experimental Evidence from India

We present experimental evidence on the impact of a programme that provided low-stakes diagnostic tests and feedback to teachers, and low-stakes monitoring of classroom processes across a representative set of schools in the Indian state of Andhra Pradesh. We find teachers in treatment schools exerting more effort when observed in the classroom but students in these schools do no better on independently-administered tests than students in schools that did not receive the programme. This suggests that though teachers in the programme schools worked harder while being observed, there was no impact of the feedback and monitoring on student learning outcomes.
Detection of Neuropathic Pain in a Rat Model of Peripheral Nerve Injury

Background:Behavioral criteria that confirm neuropathic pain in animal injury models are undefined. Therefore, the authors sought clinically relevant measures that distinguish pain behavior of rats with peripheral nerve injury from those with sham injury. Methods:The authors examined mechanical and thermal sensory sensitivity, comparing responses at baseline to responses after spinal nerve ligation (SNL group), sham nerve injury (sham group), or skin incision alone (control group). Results:Substantial variance was evident in all sensory tests at baseline. After surgery, tests using brush, cold, or heat stimulation showed minimal distinctions between surgical groups. Postsurgical thresholds for flexion withdrawal from mechanical stimulation with von Frey fibers were decreased bilaterally in SNL and sham groups. In contrast, the probability of a complex hyperalgesia-type response with prolonged elevation, shaking, or licking of the paw was selectively increased on the ipsilateral side in the SNL group. Nonetheless, the effect of SNL on behavior was inconsistent, regardless of the sensory test. The behavioral measure that best distinguishes between SNL and sham groups and thereby best identifies animals with successful SNL-induced neuropathic pain is increased ipsilateral postsurgical probability of a hyperalgesia-type response to noxious mechanical stimulation. Using receiver operating characteristics analysis, mechanical hyperalgesia identifies a local SNL effect in approximately 60% of animals when specificity is required to be 90% or higher. Conclusions:Simple withdrawal from von Frey tactile stimulation, although frequently used, is not a valid measure of peripheral nerve injury pain in rats, whereas a complex hyperalgesic-type response is a specific neuropathy-induced behavior.
THE AUSTRALIAN NATIONAL UNIVERSITY

I u n d e r s t a n d t h a t t h e U n i v e r s i t y ' s r e g u l a t i o n s p r o v i d e , i n t e r a l i a , t h a t t h e s e s a c c e p t e d f o r d e g r e e s o f The A u s t r a l i a n N a t i o n a l U n i v e r s i t y may, f o r a p e r i o d o f f i v e y e a r s a f t e r b e in g d e p o s i t e d i n t h e L i b r a r y , be c o n s u l t e d by p e r s o n s o t h e r t h a n s t a f f and s t u d e n t s o f th e U n i v e r s i t y o n ly w i t h t h e w r i t t e n c o n s e n t o f th e a u t h o r .