Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracellular glucose concentration in mammalian brain: continuous monitoring of changes during increased neuronal activity and upon limitation in oxygen supply in normo-, hypo-, and hyperglycemic animals

The concentration of extracellular glucose in anesthetized rat brain was measured continuously with two types of substrate-specific microelectrodes in a number of physiological and pathological conditions. Extracellular glucose level increased in hyperglycemia and decreased in hypoglycemia, paralleling the changes in blood sugar. Increased neuronal activity and in particular spreading depression, evoked triphasic alterations in extracellular glucose concentration: an initial rapid fall was followed by an equally swift overshoot above the baseline and a subsequent return to it. Limitation in O2 supply led to a decline in extracellular content of glucose: respiration with 5% O2 reduced the level by 7–20% and that with 3% O2 by 75–85%. Decreases to undetectable concentrations were seen in ischemia despite the use of an oxygen-insensitive microglucose sensor. Restoration of oxygen supply to the brain was accompanied by increases in extracellular glucose content above the original normoxic level, which returned to baseline values after 10–15 min. In hyperglycemic animals ischemia-induced leakage of K+ was delayed while the rate of recovery to control levels after restitution of blood flow was enhanced. It is concluded that continuous monitoring of glucose with glucose-specific microelectrodes provides a new and important insight into brain energy metabolism.
Classification of power system disturbances using a fuzzy expert system and a Fourier linear combiner

This paper presents a hybrid scheme using a Fourier linear combiner and a fuzzy expert system for the classification of transient disturbance waveforms in a power system. The captured voltage or current waveforms are passed through a Fourier linear combiner block to provide normalized peak amplitude and phase at every sampling instant. The normalized peak amplitude and computed slope of the waveforms are then passed on to a diagnostic module that computes the truth value of the signal combination and determines the class to which the waveform belongs. Several numerical tests have been conducted using EMTP programs to validate the disturbance waveform classification with the help of the new hybrid approach which is much simpler than the recently postulated ANN or wavelet based approaches.
VLIW Code Generation for a Convolutional Network Accelerator

This paper presents a compiler flow to map Deep Convolutional Networks (ConvNets) to a highly specialized VLIW accelerator core targeting the low-power embedded market. Earlier works have focused on energy efficient accelerators for this class of algorithms, but none of them provides a complete and practical programming model. Due to the large parameter set of a ConvNet it is essential that the user can abstract from the accelerator architecture and does not have to rely on an error prone and ad-hoc assembly programming model. By using modulo scheduling for software pipelining we demonstrate that our automatic generated code achieves equal or within 5-20% less hardware utilization w.r. t. code written manually by experts. Our compiler removes the huge manual workload to efficiently map ConvNets to an energy-efficient core for the next-generation mobile and wearable devices.
Biological Effects of AL622, a Molecule Rationally Designed to Release an EGFR and a c‐Src Kinase Inhibitor

In breast cancer cells expressing c‐Src and EGFR, a control of one of the two oncogenes over proliferation and invasion is observed, whereas in others, the synergistic interaction between them is required for tumor progression. With the purpose of developing molecules with the highest probability for blocking the adverse effects of these two oncogenes, we designed AL622, which contains a quinazoline head targeted to EGFR and a linker that bridges it to the PP2‐like structure for targeting c‐Src. In case the entire molecule would not be capable of blocking c‐Src, we designed AL622 to hydrolyze to an intact c‐Src‐targeting PP2 molecule. After confirming its binary c‐Src‐EGFR targeting potency of AL622, we analyzed its potency in isogenic NIH3T3 cells transfected with EGFR and HER2 and human breast cancer cells known to be dominated by c‐Src function. The results showed that in EGFR/HER‐2‐driven cells, it was more potent than PP2 and its activity was in the same range as the latter in more c‐Src‐driven cells. Its ability to block motility and invasion was comparable with that of PP2 and corresponding combinations, indicating that AL622 could be a better antitumor agent in cells where c‐Src and/or EGFR play a role.
Light Sheet Fluorescence Microscopy

Light sheet fluorescence microscopy (LSFM) functions as a non-destructive microtome and microscope that uses a plane of light to optically section and view tissues with subcellular resolution. This method is well suited for imaging deep within transparent tissues or within whole organisms, and because tissues are exposed to only a thin plane of light, specimen photobleaching and phototoxicity are minimized compared to wide-field fluorescence, confocal, or multiphoton microscopy. LSFMs produce well-registered serial sections that are suitable for three-dimensional reconstruction of tissue structures. Because of a lack of a commercial LSFM microscope, numerous versions of light sheet microscopes have been constructed by different investigators. This review describes development of the technology, reviews existing devices, provides details of one LSFM device, and shows examples of images and three-dimensional reconstructions of tissues that were produced by LSFM.
MMSE Criterion Fast Decision Feedback Equalization Algorithm for Spatial Multiplexing Systems

Recent studies indicate that spatial multiplexing (SM) scheme has enormous potential for increasing the capacity of MIMO channels in rich scattering environments. In this paper, we present a new MMSE decision feedback equalization algorithm for signal detection in SM systems. The new algorithm separates the order search and the filter generation to avoid recursive ordering operations. Compared to the earlier MMSE-DFE detectors with optimal and suboptimal ordering rules, the new algorithm is less complex and achieves a bit error rate performance that closely approximates that of the standard BLAST algorithm.
Nerve growth factor.

Nerve growth factor (NGF) is a signaling protein [4] and growth factor implicated in a wide range of development and maintenance functions. NGF was discovered through a series of experiments in the 1950s on the development of the chick [5] nervous system. Since its discovery, NGF has been found to act in a variety of tissues throughout development and adulthood. It has been implicated in immune function, stress response, nerve maintenance, and in neurodegenerative diseases. It is named for its effect on the critical role it plays in the growth and organization [6] of the nervous system during embryonic development. The discovery proceeded in several steps. Mouse sarcoma 180 was discovered to have nerve growth properties. Rita Levi-Montalcini [7] , working with Viktor Hamburger [8] , showed the abnormal growth in vivo [9] of chick [5] sympathetic and sensory ganglia in the presence of that tumor. The conclusions of this study left two options for the action of the tumor: it may have acted directly to stimulate nerve growth of the ganglia or it may simply have disrupted the normal development, indirectly allowing increased development of the nerve fibers. Levi-Montalcini conducted a study on the effects of various tumors in vitro [10] to isolate the effect of the tumor and the ganglia. She demonstrated that specific tumors were capable of inducing nerve growth. The experiments conducted by Levi-Montalcini demonstrated that NGF was diffusible, by revealing that the tumors never made direct contact with the ganglia they stimulated. The next step was to isolate an extract of NGF to show the activity of only the substance itself. Stanley Cohen [11] , a biochemist, joined Hamburger’s lab and successfully purified NGF. He also determined the factor to be mostly composed of protein with some nucleic acids. Certain types of snake [12] venom contain an enzyme that degrades nucleic acids. Cohen used this snake [12] venom to determine whether this protein was a nucleoprotein, which would require nucleic acids for function. When the snake [12] venom mixture was added to ganglia, even more growth was observed, contrary Nerve growth factor (NGF) is a signaling protein and growth factor implicated in a wide range of development and maintenance functions. NGF was discovered through a series of experiments in the 1950s on the development of the chick nervous system. Since its discovery, NGF has been found to act in a variety of tissues throughout development and adulthood. It has been implicated in immune function, stress response, nerve maintenance, and in neurodegenerative diseases. It is named for its effect on the critical role it plays in the growth and organization of the nervous system during embryonic development.
One query at a time: incremental, collective ontology matching

Ontology matching is not an end in itself but a prerequisite for applications like query answering over different data sources. In software repository analysis, for example, queries reflect process metrics that researchers want to investigate. Hence, being able to answer such queries on multiple data sets without having to perform data transformations or manual query rewriting is a desirable objective. Unfortunately, the terminological differences and often complex correspondences between different software repository representations impede a completely automatic matching and necessitate user input to create more comprehensive alignments [4]. Our work is concerned with the question of when and how users should introduce their expertise into the matching process. Similar to other approaches, such as the keyword-based information retrieval tasks, which Ellis et al. [1] use to extract user knowledge about ontology alignments, we integrate the input process into the desired application – query translation between different software repositories. From the way this task is carried out, both simple and complex correspondences are inferred. In future translation tasks, these correspondences are reused to incrementally reduce the number of required user interactions. As users only translates their queries of interest, the overall effort for alignment creation is collectivized. In this poster, we present the general architecture of our system and the rules used for complex alignment extraction.
Evaluating automatically parallelized versions of the support vector machine

The support vector machine (SVM) is a supervised learning algorithm used for recognizing patterns in data. It is a very popular technique in machine learning and has been successfully used in applications such as image classification, protein classification, and handwriting recognition. However, the computational complexity of the kernelized version of the algorithm grows quadratically with the number of training examples. To tackle this high computational complexity, we have developed a directive‐based approach that converts a gradient‐ascent based training algorithm for the CPU to an efficient graphics processing unit (GPU) implementation. We compare our GPU‐based SVM training algorithm to the standard LibSVM CPU implementation, a highly optimized GPU‐LibSVM implementation, as well as to a directive‐based OpenACC implementation. The results on different handwritten digit classification datasets demonstrate an important speed‐up for the current approach when compared to the CPU and OpenACC versions. Furthermore, our solution is almost as fast and sometimes even faster than the highly optimized CUBLAS‐based GPU‐LibSVM implementation, without sacrificing the algorithm's accuracy. Copyright © 2014 John Wiley & Sons, Ltd.
Reimplantation of Infected Hip Arthroplasties Using Bone Allografts

Twenty-two patients with deep infection of an hip prosthesis received delayed reimplantation using bone allografts. Sixteen were done using noncemented components and 6 using femoral components that were fixed with antibiotic impregnated cement. Bulk allografts were used at the acetabular site in 2 patients and at the femoral site in 4 patients. Morselizcd allografts were used at the acetabular site in 20 patients and at the femoral site in 10 patients. The causative organisms were virulent in 10 hips and low virulent in 12 hips. At an average followup of 4 years (range, 2–7 years), 91% of patients were free of infection and 73% had a successful functional result. Two had a recurrent infection; 1 of them had a pseudomonas infection and another had a methicillin resistant Staphylococcal infection. The recurrence of infection tended to be higher if the causative organism was virulent. The use of bone allografts at the staged reimplantation of the infected hip arthroplasty did not increase the incidence of recurrent infection. Both cemented and noncemented reimplanta-tions had a successful result in eradicating the infection. However, hybrid reimplantation with a cemented femoral component and fixed porous acetabular component had a better functional outcome than noncemented reimplantation using porous femoral component and non-fixed acetabular component.
Improving Performance Isolation on Chip Multiprocessors via an Operating System Scheduler

We describe a new operating system scheduling algorithm that improves performance isolation on chip multiprocessors (CMP). Poor performance isolation occurs when an application's performance is determined by the behaviour of its co-runners, i.e., other applications simultaneously running with it. This performance dependency is caused by unfair, co- runner-dependent cache allocation on CMPs. Poor performance isolation interferes with the operating system 's control over priority enforcement and hinders QoS provisioning. Previous solutions required modifications to the hardware. We present a new software solution. Our cache-fair algorithm ensures that the application runs as quickly as it would under fair cache allocation, regardless of how the cache is actually allocated. If the thread executes fewer instructions per cycle than it would under fair cache allocation, the scheduler increases that thread's CPU time slice. This way, the thread's overall performance does not suffer because it is allowed to use the CPU longer. We describe our implementation of the algorithm in Solaristrade 10, and show that it significantly improves performance isolation for SPEC CPU, SPEC JBB and TPC-C.
Multi Phase Analytical description Of Vaporization And Condensation In Nanofluid Droplets

Recently there has been a growing interest in nanodroplet engineering and the dynamics of vaporization and condensation of fluids at the nanoscale. The applications of nanodroplet engineering is in the biomolecular field, physical chemistry, and engineering power production and storage devices technology. other applications are in aerosols, fuels and turbulence in power source design. In this paper a theoretical model for multiphase nanofluids is derived from information theory and temperature dependent distributions are obtained for the Lennard-Jones potential interactions of the nanofluid droplets. The simple paradigm of a nanofluid is an inert material such as Argon, as a fluid at low temperatures, in a droplet of a diameter a few nano meters in scale. Such a nanodroplet contains from the tens to the hundreds of Argon atoms in a fluid phase. The kinematics of the fluid nanodroplet as it is accelerated and it interacts with other materials, gas, liquid, molecules or solid state materials is the dynamics we wish to address here. A simple example for what we will model by theory here is the nanodroplet of Argon, say containing a few hundred Argon atoms, moving at a uniform velocity towards a non chemically reactive solid surface that could represent in more complex experiments or applications a reactive or non reactive surface of a device for power production such as in fuel cell walls, a porous membrane in biological cellular reactions, or reactive chemistry analysis such as lab-on-a-chip. The medium here is a vacuum though more complex arrangements could be of secondary gases or liquids. At the nanoscale the aggregation of atoms and the screening effect that occurs as the number of atoms increases towards a size of the micron range
Perfect slice samplers

Perfect sampling allows the exact simulation of random variables from the stationary measure of a Markov chain. By exploiting monotonicity properties of the slice sampler we show that a perfect version of the algorithm can be easily implemented, at least when the target distribution is bounded. Various extensions, including perfect product slice samplers, and examples of applications are discussed.
Vagus Nerve Stimulation, Side Effects, and Long-Term Safety

Summary Vagus nerve stimulation (VNS) is an accepted therapy for the treatment of refractory epilepsy and now even depression. More than 10,000 people have had the device implanted over a period of 12 years. Initial side effects in the early years such as lower facial weakness and electrode lead breaks have now been resolved. Postoperative infections occur in approximately 3% of patients but can be treated with oral antibiotics. Side effects during the use of VNS are usually related to the “on” phase of stimulation. Common side effects are cough, hoarseness, voice alteration, and paresthesias. These side effects tend to diminish with time. Cognitive side effects often seen with antiepileptic drug use are not reported. The side effect profile of VNS is positive, and this treatment option offers patients with refractory epilepsy prospects of good efficacy with only minor and often resolvable side effects.
Random Valued Impulse Noise Removal Using Fuzzy Techniques

– A fuzzy filter for the removal of random impulse noise in color video is presented. By working with successive filtering steps, a very good tradeoff between detail preservation and noise removal is obtained. Therefore, the noise is filtered step by step. In each step, noisy pixels are detected by the help of fuzzy rules. Pixels that are detected as noisy are filtered, the others remain unchanged. Filtering of detected pixels is done by median filtering techniques. The proposed method outperforms other filters both visually and in terms of objective quality measures such as the mean absolute error (MAE), and the peak-signal-to-noise ratio (PSNR).
RplTrc: A Tool for Emulating Real Network Dynamics for Performance Evaluation

Evaluating the performance of distributed applications, such as mobile telephone or video conferencing devices, has become increasingly complex as the diversity of scenarios and data rates in networks increase. In this paper, we present the design and implementation of RplTrc, a network emulation tool. RplTrc uses traces to drive interceptions of the Linux protocol stack to delay, drop or duplicate packets. The length of traces is not limited. Thus, unlike other well-known emulators such as NIST Net or the emulator module in the Linux 2.6 kernel, RplTrc is capable to account for important performance characteristics inherent to real networks such as long-range dependence and self-similarity of cross-traffic. Tests show that RplTrc installed on a commodity PC is capable to emulate a 100MBit/s or a lightly-loaded 1GBit/s network and has a precision in reproducing packet delays in the order of 100 mus. RplTrc thus enables extensive performance evaluation of distributed applications in lab environments.
Ethics in practice

A seventeen-year-old male, high-school football player presents to an orthopaedic surgeon because of recurrent right knee pain after having undergone an arthroscopic meniscal repair one year previously. The patient did well initially but now has recurrent medial joint-line pain in the knee, which developed when he planted the right leg to throw a pass during summer training camp. He was evaluated by the team’s athletic trainer and by an orthopaedic surgeon, both of whom, on the basis of their physical examination of the boy, believe that he may have sustained a recurrent meniscal tear. A magnetic resonance arthrogram is acquired, which confirms the presence of a large longitudinal tear of the medial meniscus in the ‘‘red-red’’ zone, with no signs of degenerative change, articular cartilage damage, or other ligamentous pathology. The patient had just started summer training camp before his senior year of high-school football, and he is considered to be a potential high-level candidate for a Division-I football scholarship.
Understanding community patterns in large attributed social networks

There is an inherent presence of communities in online social networks. These communities can be defined based on i) link structure or ii) the attributes of individuals. Attributes can indicate as interests in specific topics, like science-fiction books or romantic movies, or more in general their explicit affiliation to a group inside the network. In this paper, we analyze community structures as defined by how people are associated to third concepts like attributes. To understand the community patterns we analyze three large and one small social network datasets. Our analysis shows that, irrespective of the number of nodes for any particular interest in the network, at least 50% of the nodes are part of the same connected component in the graph induced by each interest. Another interesting result of our analysis is that the majority of sub-communities (50% or above) for any interest are separated by small hops (two to three) from each other.
Maintenance of behavior by postponement of scheduled injections of nicotine in squirrel monkeys.

Responding by squirrel monkeys was maintained under a schedule of i.v. nicotine postponement. Each lever-pressing response postponed an impending i.v. injection for 60 sec; in the absence of responding, injections occurred very 20 sec. The lowest dose of nicotine (10 micrograms/kg/injection) maintained rates of responding that were only slightly higher than those maintained by saline. Intermediate doses (30 or 56 micrograms/kg/injection), however, maintained rates and patterns of responding that were similar to those maintained by electric shock under an identical schedule of postponement. At the highest dose (100 micrograms/kg/injection), nicotine disrupted responding and induced vomiting in each monkey. Presession treatment with mecamylamine (1.0 mg/kg i.m.), a nicotinic antagonist with both central and peripheral effects, shifted the nicotine dose-response curve to the right by about 1 log unit and blocked nicotine-induced emesis. In contrast, presession treatment with hexamethonium (1.0 or 10.0 mg/kg i.m.), a nicotinic antagonist with primarily peripheral effects, did not produce an overall rightward shift in the nicotine dose-response curve, although it did reduce the rate of responding maintained by the intermediate doses of nicotine and blocked emesis. Neither mecamylamine nor hexamethonium systematically altered responding maintained by electric shock under the schedule of postponement. The results show that schedule-characteristic performances can be maintained by postponement of i.v. injections of nicotine and that the maintenance of responding under the postponement schedule depends largely on the actions of nicotine in the central nervous system.