Miracle-dz/UniFAR-FTUs huggingface dataset:
Experience‐dependent depression of vibrissae responses in adolescent rat barrel cortex

A short period of vibrissae deprivation in an adolescent (≈ 1 month old) rat can lead to depression of the cortical response to stimulation of the regrown vibrissae. In a barrel column representing the deprived vibrissa, depression is greater for neurons located close to the barrel column representing the spared vibrissa. One possible explanation is that the spared vibrissa produces heterosynaptic depression of the principal vibrissa response ( Glazewski & Fox 1996 ). To test this idea further, we compared the effect of depriving all vibrissae (no heterosynaptic influence at all) with depriving a single vibrissa (maximal heterosynaptic influence expected). In addition we tested the origin of the depression by recording from subcortical structures.
Cooperative end-to-end traffic redundancy elimination for reducing cloud bandwidth cost

The pay-as-you-go service model impels cloud customers to reduce the usage cost of bandwidth. Traffic Redundancy Elimination (TRE) has been shown to be an effective solution for reducing bandwidth costs, and has recently captured significant attention in the cloud environment. By studying the TRE techniques with a trace driven approach, we found that solely using either sender-based TRE or receiver-based TRE cannot simultaneously capture traffic redundancy in both short-term (time span of seconds) and long-term (time span of hours or days) data redundancy, which concurrently appear in the traffic. Additionally, the TRE efficiency of existing receiver-based TRE solution is susceptible to data changes compared to historical data in the cache. In this paper, we propose a sender and receiver Cooperative end-to-end TRE solution (CoRE) for efficiently identifying and removing both short-term and long-term redundancy. Through a two-layer redundancy detection design and one single pass algorithm for chunking and fingerprinting, CoRE efficiently carries out cooperative operations between the sender and the receiver. By extensive evaluation with several real traces, we show that CoRE is able to identify both short-term and longterm redundancy with low additional cost, while ensuring TRE efficiency from data changes.
Lattice dynamics of oxides with rutile structure and instabilities at the metal-semiconductor phase transitions of NbO2 and VO2.

The phonon dispersion curves of the rutile-structure compounds ${\mathrm{GeO}}_{2}$, ${\mathrm{SnO}}_{2}$, ${\mathrm{NbO}}_{2}$, and ${\mathrm{VO}}_{2}$ have been calculated in the framework of a shell model which had been used previously to reproduce the measured dispersion curves of rutile (${\mathrm{TiO}}_{2}$) rather satisfactorily. The parameters of the model for ${\mathrm{GeO}}_{2}$, ${\mathrm{SnO}}_{2}$, ${\mathrm{NbO}}_{2}$, and ${\mathrm{VO}}_{2}$ have been obtained by slightly readjusting the ${\mathrm{TiO}}_{2}$ parameters in such a way that a best fit of the measured infrared and Raman frequencies has been achieved. The calculated phonon dispersion curves of ${\mathrm{GeO}}_{2}$ and ${\mathrm{SnO}}_{2}$ do not exhibit any anomaly. However, the calculated dispersion curves of ${\mathrm{VO}}_{2}$ and ${\mathrm{NbO}}_{2}$ do reveal lattice instabilities at the R and P points of the Brillouin zone, respectively. The analysis of the eigenvectors shows that the soft modes of ${\mathrm{VO}}_{2}$ and ${\mathrm{NbO}}_{2}$ trigger the structural phase transitions which accompany metal-to-semiconductor transitions. The results of this study emphasize the importance of the hybridization of the oxygen p states with the transition-metal d states for the incipient ferroelectric properties of ${\mathrm{TiO}}_{2}$ and the lattice instabilities of ${\mathrm{NbO}}_{2}$ and ${\mathrm{VO}}_{2}$.
Obtain Datasets for Self-Driving Perception from Video Games Automatically

Perception in self-driving car is a challenging computer vision task that need to detect the location of vehicles, pedestrians and cyclists from images. Recent progress in object detection and localization developing is highly relied on the huge number of datasets. Unfortunately, when we try to create these large datasets we will find out it has been very costly on human work and professional equipment required. We will present an approach in this paper so that we can creating pixel-level segmentation label maps for images and the depth of the images extracted from some modern AAA computer games like GTA5. The fidelity of these computer games is very impressive so that it can be used even directly for the real-world image object detection and localization. Without any human efforts and depth camera we can generating datasets from a photorealistic computer game automatically that have pixel-level labels and depth map of cars and pedestrians. We generate thousands of datasets for testing and the amount of it is still growing. Our datasets can be used in real-world situation with transfer learning approach. Not only image segmentation and depth data, we also can extract a lot more interesting dates from games just like image to coordinate data and image to driving pose data whose labels are extract directly from the metadata of computer games.
From Device Aging Physics to Automated Circuit Reliability Sign Off

For modern semiconductor product design, reliability aspects have to be considered not only for technology process development but inevitable also during circuit design phase. Electronic design automation tools (EDA) have to support circuit designers to analyze the impact of device and interconnect reliability on the circuit behavior. The designers task is to ensure the specified characteristic of the circuits throughout the entire lifetime of the product. Meanwhile there are many different tools available for this task. They can be categorized according to their basic reliability assessment approach.
Microfluidic mixing by fluidic discretization

A new concept of microfluidic mixing based on fluid "discretization" is proposed in this paper. Polymer based micropumps, micromixer and microchannels have been designed and integrated in a single PMMA chip microfluidic system. The optically transparent and biocompatible material used to fabricate the microfluidic system enables many biomedical and chemical analysis applications. The idea of "discretized" microfluidic mixing is to manipulate fluids as "discretize" volumes by pumping fluids by two micropumps into a microchamber alternatively in order to increase the interfacial surface area. Hence, the diffusion between fluids can be completed in a shorter time and fluids can be mixed instantly without external energy in the chamber. The design, implementation and experimental results are presented in this paper.
Self-consistent quasi-particle model for relativistic plasma

Relativistic plasma with radiation at thermodynamic equilibrium is ageneral system of interest in astrophysics and high energy physics. We develop a new self-consistent quasi-particle model for such a system to take account of collective behaviour of plasma andthermodynamic properties are derived. It is applied to electrodynamic plasma and quark gluon plasma and compared with existing results.
Colon specific drug delivery of mesalamine using eudragit S100-coated chitosan microspheres for the treatment of ulcerative colitis

The purpose of the present study was to prepare, characterize and evaluate the colon-targeted microspheres of mesalamine for the treatment and management of ulcerative colitis (UC). Microspheres were prepared by the ionic-gelation emulsification method using tripolyphosphate (TPP) as cross linking agent. The microspheres were coated with Eudragit S-100 by the solvent evaporation technique to prevent drug release in the stomach. The prepared microspheres were evaluated for surface morphology, entrapment efficiency, drug loading, micromeritic properties and in-vitro drug release. The microspheres formed had rough surface as observed in scanning electron microscopy. The entrapment efficiency of microspheres ranged from 43.72%-82.27%, drug loading from 20.28%-33.26%. The size of the prepared microspheres ranged between 61.22-90. 41µm which was found to increase with increase in polymer concentration. All values are statistically significant as p<0.05. Micromeritic properties showed good flow properties and packability of prepared microspheres. The drug release of mesalamine from microspheres was found to decrease as the polymer concentration increases. The release profile of mesalamine from eudragit-coated chitosan microspheres was found to be pH dependent. It was observed that Eudragit S100 coated chitosan microspheres gave no release in the simulated gastric fluid, negligible release in the simulated intestinal fluid and maximum release in the colonic environment. It was concluded from the study that Eudragit-coated chitosan microspheres were promising carriers for colon-targeted delivery of Mesalamine. DOI: http://dx.doi. org/10.3329/icpj.v2i3. 13577 International Current Pharmaceutical Journal, February 2013, 2(3): 42-48
In vivo analysis of sequences required for translation of cytochrome b transcripts in yeast mitochondria

Respiratory chain proteins encoded by the yeast mitochondrial genome are synthesized within the organelle. Mitochondrial mRNAs lack a 5' cap structure and contain long AU-rich 5' untranslated regions (UTRs) with many potential translational start sites and no apparent Shine-Dalgarno-like complementarity to the 15S mitochondrial rRNA. However, translation initiation requires specific interactions between the 5' UTRs of the mRNAs, mRNA-specific activators, and the ribosomes. In an initial step toward identifying potential binding sites for the mRNA-specific translational activators and the ribosomes, we have analyzed the effects of deletions in the 5' UTR of the mitochondrial COB gene on translation of COB transcripts in vivo. The deletions define two regions of the COB 5' UTR that are important for translation and indicate that sequence just 5' of the AUG is involved in selection of the correct start codon. Taken together, the data implicate specific regions of the 5' UTR of COB mRNA as possible targets for the mitochondrial translational machinery.
Microalbuminuria, cardiovascular risk factors and cardiovascular morbidity in a British population: The EPIC-Norfolk Population-based Study

Background Microalbuminuria is independently associated with increased cardiovascular risk and renal function deterioration in diabetes and hypertension, but the clinical relevance of raised albuminuria in the general population is less certain. We examined the prevalence of microalbuminuria and its relationship to cardiovascular risk factors and cardiovascular morbidity in the UK general population. Methods Cross-sectional population-based study of 23,964 individuals, aged 40–79 years recruited in 1993–1997 for the EPIC-Norfolk Study. Smoking status, prevalent physician diagnosed diabetes, hypertension, cardiovascular disease and cancer were derived from a health and lifestyle questionnaire. Albumin-to-creatinine ratios were estimated from random spot urine specimens collected at the survey visit, and using these ratios participants were categorized into normoalbuminuria, microalbuminuria (2.5–25 mg/mmol), and macroalbuminuria. Results The prevalence of microalbuminuria and macroalbuminuria was 11.8% and 0.9% respectively in the total population and significantly higher in women (14.4%) compared with men (8.9%) (P<0.001). Independent determinants of microalbuminuria were age, sex, systolic blood pressure and current smoking. Microalbuminuria was independently associated with cardiovascular morbidity, after adjusting for known cardiovascular risk factors, with odds ratio (95% confidence interval) for prevalent cardiovascular disease of 1.30 (1.12–1.51) in all men and women. Conclusion Microalbuminuria was present in approximately 12% of this population. It was independently associated with cardiovascular risk factors and prevalent cardiovascular disease. Microalbuminuria may be a useful indicator of high absolute cardiovascular risk in the community but prospective data are needed to establish its independent predictive value for future events.
Roadmap on quantum optical systems

This roadmap bundles fast developing topics in experimental optical quantum sciences, addressing current challenges as well as potential advances in future research. We have focused on three main areas: quantum assisted high precision measurements, quantum information/simulation, and quantum gases. Quantum assisted high precision measurements are discussed in the first three sections, which review optical clocks, atom interferometry, and optical magnetometry. These fields are already successfully utilized in various applied areas. We will discuss approaches to extend this impact even further. In the quantum information/simulation section, we start with the traditionally successful employed systems based on neutral atoms and ions. In addition the marvelous demonstrations of systems suitable for quantum information is not progressing, unsolved challenges remain and will be discussed. We will also review, as an alternative approach, the utilization of hybrid quantum systems based on superconducting quantum devices and ultracold atoms. Novel developments in atomtronics promise unique access in exploring solid-state systems with ultracold gases and are investigated in depth. The sections discussing the continuously fast-developing quantum gases include a review on dipolar heteronuclear diatomic gases, Rydberg gases, and ultracold plasma. Overall, we have accomplished a roadmap of selected areas undergoing rapid progress in quantum optics, highlighting current advances and future challenges. These exciting developments and vast advances will shape the field of quantum optics in the future.
Distortion correction for diffusion‐weighted MRI tractography and fMRI in the temporal lobes

Single shot echo‐planar imaging (EPI) sequences are currently the most commonly used sequences for diffusion‐weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) as they allow relatively high signal to noise with rapid acquisition time. A major drawback of EPI is the substantial geometric distortion and signal loss that can occur due to magnetic field inhomogeneities close to air‐tissue boundaries. If DWI‐based tractography and fMRI are to be applied to these regions, then the distortions must be accurately corrected to achieve meaningful results. We describe robust acquisition and processing methods for correcting such distortions in spin echo (SE) EPI using a variant of the reversed direction k space traversal method with a number of novel additions. We demonstrate that dual direction k space traversal with maintained diffusion‐encoding gradient strength and direction results in correction of the great majority of eddy current‐associated distortions in DWI, in addition to those created by variations in magnetic susceptibility. We also provide examples to demonstrate that the presence of severe distortions cannot be ignored if meaningful tractography results are desired. The distortion correction routine was applied to SE‐EPI fMRI acquisitions and allowed detection of activation in the temporal lobe that had been previously found using PET but not conventional fMRI. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.
Comparison of Deep Learing Algorithms for Indoor Monitoring using Bioelectric Potential of Living Plants

This study aims to develop a monitoring system for an indoor space. We are investigating to use the bioelectric potential of living plants as a human sensor system in an indoor environment. The system utilizes a change of the bioelectric potential to estimate a resident’s location in a room. To build an estimation model, a lot of the bioelectric potential data are collected and processed by a machine learning method. We have studied to build the estimation model using a convolutional neural network. However, recently, there are many applications that utilize Long-Short Term Memory method for a time sequential data, and they obtained a good result successfully. Therefore, in this study we applied LSTM for the bioelectric potential data and investigate the availability of CNN and LSTM to estimate the location with the bioelectric potential. As the result of classification experiments with the model trained with collected bioelectric data, we obtained that CNN is better than LSTM for this problem. However, we need to improve the accuracy by adjusting parameters in future.
A Little Energy Goes a Long Way: Build an Energy-Efficient, Accurate Spiking Neural Network From Convolutional Neural Network

This article conforms to a recent trend of developing an energy-efficient Spiking Neural Network (SNN), which takes advantage of the sophisticated training regime of Convolutional Neural Network (CNN) and converts a well-trained CNN to an SNN. We observe that the existing CNN-to-SNN conversion algorithms may keep a certain amount of residual current in the spiking neurons in SNN, and the residual current may cause significant accuracy loss when inference time is short. To deal with this, we propose a unified framework to equalize the output of the convolutional or dense layer in CNN and the accumulated current in SNN, and maximally align the spiking rate of a neuron with its corresponding charge. This framework enables us to design a novel explicit current control (ECC) method for the CNN-to-SNN conversion which considers multiple objectives at the same time during the conversion, including accuracy, latency, and energy efficiency. We conduct an extensive set of experiments on different neural network architectures, e.g., VGG, ResNet, and DenseNet, to evaluate the resulting SNNs. The benchmark datasets include not only the image datasets such as CIFAR-10/100 and ImageNet but also the Dynamic Vision Sensor (DVS) image datasets such as DVS-CIFAR-10. The experimental results show the superior performance of our ECC method over the state-of-the-art.
Diet Soda Consumption and Risk of Incident End Stage Renal Disease.

BACKGROUND AND OBJECTIVES Diet soda consumption is common in the United States and is associated with impaired glucose metabolism, diabetes, and metabolic syndrome. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS We prospectively analyzed diet soda consumption, assessed by food frequency questionnaire at baseline (1987-1989) and a follow-up examination (1993-1995), and incident ESRD through December 31, 2012 in the Atherosclerosis Risk in Communities study (n=15,368). RESULTS Baseline mean age of participants was 54 years, 55% were female, and 27% were black. The majority of participants (43.5%) consumed <1 glass/wk of diet soda; 17.8% consumed 1-4 glasses/wk; 25.3% consumed 5-7 glasses/wk; and 13.5% consumed >7 glasses/wk. Over a median follow-up of 23 years, 357 incident ESRD cases were observed. Relative to <1 glass/wk of diet soda, consuming 1-4 glasses/wk, 5-7 glasses/wk, and >7 glasses/wk, respectively, was associated with 1.08-times (95% confidence interval [95% CI], 0.75 to 1.55), 1.33-times (95% CI, 1.01 to 1.75), and 1.83-times (95% CI, 1.01 to 2.52) higher risk of ESRD after adjusting for age, sex, race-center, education level, smoking status, physical activity, total caloric intake, eGFR, body mass index category, diabetes, systolic BP, and serum uric acid (P value for trend <0.001). Results were similar after additional adjustment for dietary acid load, diet quality, dietary sodium, dietary fructose, sugar-sweetened beverages, and dietary phosphorus. Risk estimates were similar by body mass index category (P value for interaction = 0.82), but the association between diet soda and ESRD was only significant for those who were overweight or obese at baseline. Sugar-sweetened beverage consumption was not significantly associated with ESRD in the fully adjusted model. CONCLUSIONS Diet soda consumption was associated with higher ESRD risk in this general population sample. Further research is necessary to validate these findings in other study populations and to examine potential mechanisms through which diet soda could impact kidney disease.
Parameter Optimization of Elliptical Microstrip Patch Antenna using Genetic Algorithms

In this paper, Genetic Algorithms (GA) has been applied to calculate the optimized parameters of Elliptical Microstrip antenna. The fitness function has been developed in GA and the optimized dimensions of the antenna have been calculated. The output obtained is the optimized semi- major axis length ‘a’ from which the other parameters i.e. semi-minor axis length and odd mode frequency are calculated. The results obtained by GA are compared with the targeted results. The results are in good agreement. Results are also obtained for feed point in different quadrants and the comparison is made. GA results are also compared with IE3D simulation results. These results are also comparable and thus validate the GA based code.
The Effects of Number-related Factors on Entry Performance

Number entry is ubiquitous in user interface (UI) design, and in many applications --- such as finance, aviation, healthcare --- here, mitigating errors is critical. This paper examines the effects of factors such as the type of number (e.g., integer or decimal), number length (i.e., short or long) and display position (i.e., near or far) on entry errors. Until now, these factors have not been explored together. Using a touch-based numeric keypad, we found that number length influenced the probability of committing errors, while the position of presentation did not. Number type impacted user-corrected errors but not uncorrected errors. Number length, number type and display position affected input timings. The findings provide implications for the design of both number representations (e.g., decimal point appearance) and the sociotechnical systems that surround them (e.g., training practice).
Parallel Apriori based Distributed Association Rule Mining: A Comprehensive Survey

Association rule mining (ARM) has been paid more attention of both data mining users and database researchers in the last decade. Generation of various association rules from large distributed databases is the crucial task due to its intrinsic distribution of data sources. Identifying these type of distributed data sources requires a deep knowledge on data mining and planning for deployment in distributed environment. In this paper, a survey of the distributed framework for ARM is presented. It is observed that the parallelized nature of Apriori, Hadoop, MapReduce and Spark proves to be very efficient in Distributed association rule mining (DARM) environment. We expect that, the comprehensive review, references cited will convey foremost hypothetical issues and a guideline to the researcher in interesting research direction.