Miracle-dz/UniFAR-FTUs huggingface dataset:
Properties of unitary IPSPs evoked by anatomically identified basket cells in the rat hippocampus

Hippocampal pyramidal cells receive GABA‐mediated synaptic input from several distinct interneurons. In order to define the effect of perisomatic synapses, intracellular recordings were made with biocytin‐containing microelectrodes from synaptically connected inhibitory and pyramidal cell pairs in subfields CA1 and CA3 of the rat hippocampus. Subsequent physiological analysis was restricted to the category of cells, here referred to as basket cells (n= 14), which had an efferent synaptic target profile (n= 282 synaptic contacts) of predominantly somatic (48.2%) and proximal dendritic synapses (45.0%). Electron microscopic analysis revealed that in two instances identified postsynaptic pyramidal cells received a total of 10 and 12 labelled basket cell synapses respectively. At an average membrane potential of ‐57.8 ± 4.6 mV, unitary inhibitory postsynaptic potentials (IPSPs; n= 24) had a mean amplitude of 450 ± 238 μV, a 10–90% rise time of 4.6 ± 3.2 ms and, measured at half‐amplitude, a mean duration of 31.6 ± 18.2 ms. In most instances (n= 19) the IPSP decay could be fitted with a single exponential with a mean time constant of 32.4 ± 18.0 ms. Unitary basket cell‐evoked IPSPs fluctuated widely in amplitude, ranging from the level of detectability to <2 mV. The response reversal of IPSPs (n= 5) was extrapolated to be at ‐74.9 ± 6.0 mV. Averages of unitary IPSPs had a mean calculated conductance of 0.95 ± 0.29 nS, ranging from 0.52 to 1.16 nS. Unitary basket cell IPSPs (n= 3) increased in amplitude by 26.3 ± 19.9% following bath application of the GABAB receptor antagonist CGP 35845A (1–4 μM), whereas subsequent addition of the GABAA receptor antagonist bicuculline (10–13 μM) reduced the IPSP amplitude to 13.5 ± 3.1% of the control response. Rapid presynaptic trains of basket cell action potentials resulted in the summation of up to four postsynaptic responses (n= 5). However, any increase in the rate of tonic firing (2‐ to 10‐fold) led to a <50% reduction of the postsynaptic response amplitude. At depolarized membrane potentials, averaged IPSPs could be followed by a distinct depolarizing overshoot or postinhibitory facilitation (n= 4). At firing threshold, pyramidal cells fired postinhibitory rebound‐like action potentials, the latter in close temporal overlap with the depolarizing overshoot. In conclusion, hippocampal basket cells have been identified as one source of fast, GABAA receptor‐evoked perisomatic inhibition. Unitary events are mediated by multiple synaptic release sites, thus providing an effective mechanism to avoid total transmission failures.
A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound

Characterization of carotid plaque composition, more specifically the amount of lipid core, fibrous tissue, and calcified tissue, is an important task for the identification of plaques that are prone to rupture, and thus for early risk estimation of cardiovascular and cerebrovascular events. Due to its low costs and wide availability, carotid ultrasound has the potential to become the modality of choice for plaque characterization in clinical practice. However, its significant image noise, coupled with the small size of the plaques and their complex appearance, makes it difficult for automated techniques to discriminate between the different plaque constituents. In this paper, we propose to address this challenging problem by exploiting the unique capabilities of the emerging deep learning framework. More specifically, and unlike existing works which require a priori definition of specific imaging features or thresholding values, we propose to build a convolutional neural network (CNN) that will automatically extract from the images the information that is optimal for the identification of the different plaque constituents. We used approximately 90 000 patches extracted from a database of images and corresponding expert plaque characterizations to train and to validate the proposed CNN. The results of cross-validation experiments show a correlation of about 0.90 with the clinical assessment for the estimation of lipid core, fibrous cap, and calcified tissue areas, indicating the potential of deep learning for the challenging task of automatic characterization of plaque composition in carotid ultrasound.
Nucleotide Variation in Wild and Inbred Mice

The house mouse is a well-established model organism, particularly for studying the genetics of complex traits. However, most studies of mice use classical inbred strains, whose genomes derive from multiple species. Relatively little is known about the distribution of genetic variation among these species or how variation among strains relates to variation in the wild. We sequenced intronic regions of five X-linked loci in large samples of wild Mus domesticus and M. musculus, and we found low levels of nucleotide diversity in both species. We compared these data to published data from short portions of six X-linked and 18 autosomal loci in wild mice. We estimate that M. domesticus and M. musculus diverged <500,000 years ago. Consistent with this recent divergence, some gene genealogies were reciprocally monophyletic between these species, while others were paraphyletic or polyphyletic. In general, the X chromosome was more differentiated than the autosomes. We resequenced classical inbred strains for all 29 loci and found that inbred strains contain only a small amount of the genetic variation seen in wild mice. Notably, the X chromosome contains proportionately less variation among inbred strains than do the autosomes. Moreover, variation among inbred strains derives from differences between species as well as from differences within species, and these proportions differ in different genomic regions. Wild mice thus provide a reservoir of additional genetic variation that may be useful for mapping studies. Together these results suggest that wild mice will be a valuable complement to laboratory strains for studying the genetics of complex traits.
Symbolic noise analysis of low voltage amplifiers by using nullors

We present the calculation of noise expressions of low voltage amplifiers by applying symbolic nodal analysis and using nullors. The nullor equivalents of the MOSFETs include only the dominant parasitic elements in order to generate a simplified symbolic noise expression, which provides a good insight to improve the design of low voltage amplifiers. The generated symbolic noise expressions are compared with HSPICE simulations, so that one can appreciate the good agreement with our proposed symbolic noise analysis approach.
Automatic classification of deep web databases with simple query interface

Deep Web database classify is a key operation in organizing Deep Web resources. We address the problem of identifying the domain of web databases with simple query interface. The existing methods can not effectively classify this type of web databases, to solve this problem, we propose an new framework that can automatically and accurately classify web databases with simple query interface based on probing query. The core of this framework is a domain specific classifier(DSC). DSC is constructed by using the features that can be easily extracted from advanced query interfaces(forms) in domain. According to the similar relation among result schemas, interface schemas and global schemas of web database, Based on its result schemas, a new web database with simple query interface can be classified by DSC. Experiments running on real structured web databases collected from the internet show that our provides an effective and scalable solution for classifying web databases with simple query interface.
The Effects of Tax Reform on Real Estate: Some Empirical Results

This paper uses data on publicly traded real estate firms to examine the effects of two major tax reforms. Specifically, we analyze the effects of the 1976 and 1986 Tax Reform Acts (TRAs) on the risks and returns of real estate investment trusts (REITs) and other real estate firms, using intervention analysis. Since REITs have been a dominant force in the real estate equity markets, and since they are treated differently for tax purposes than corporations investing in real estate, we examine the two groups of firms separately. ' While there exists much popular press literature which discusses the impact of tax reform on real estate, little empirical work has directly examined the market's response to these changes.2 Most previous work undertaken to examine the potential impact of tax changes has used simulation modeling to estimate the effects on real estate firms' values (e.g., Fisher and Lentz 1986; Hendershott, Follain, and Ling 1986). A review of the simulation literature is presented in Follain and Brueckner (1986). Turning away from the simulation technique, Nourse (1987) uses appraisal data to empirically estimate how the 1976 and 1981 tax laws affect capitalization rates (i.e., net income divided by value) for real estate. In contrast with the existing literature, we use market data to evaluate the empirical effects of the 1976 and 1986 law changes. The empirical results provide insights into the interaction between tax laws and the market for real estate assets. In the next section of the paper we discuss the historical background of the 1976
A Mini-Slot Router Architecture for TDM Optical WDM Networks

Many routing and wavelength assignment algorithms have been proposed for optical networks, but they lack the refinement of being able to further share the gigabit bandwidth in each wavelength. Obviously, TDM wavelength routing networks can offer better network throughput than traditional wavelength routed networks. However, with the advancement of optical technology, it is possible to divide a wavelength in a fiber into time-slots, and further divide a time-slot into mini-slots so that the fiber bandwidth can be more efficiently utilized. This paper proposes a router architecture with an electronic system controller to support optical data transfer at the mini-slots of a time-slot in a wavelength for each hop of a route. No wavelength converter is employed in the proposed router architecture. The effectiveness of this network in blocking probability and throughput is demonstrated by simulation
Direct observation of mobility state transitions in RNA trajectories by sensitive single molecule feedback tracking

Observation and tracking of fluorescently labeled molecules and particles in living cells reveals detailed information about intracellular processes on the molecular level. Whereas light microscopic particle observation is usually limited to two-dimensional projections of short trajectory segments, we report here image-based real-time three-dimensional single particle tracking in an active feedback loop with single molecule sensitivity. We tracked particles carrying only 1–3 fluorophores deep inside living tissue with high spatio-temporal resolution. Using this approach, we succeeded to acquire trajectories containing several hundred localizations. We present statistical methods to find significant deviations from random Brownian motion in such trajectories. The analysis allowed us to directly observe transitions in the mobility of ribosomal (r)RNA and Balbiani ring (BR) messenger (m)RNA particles in living Chironomus tentans salivary gland cell nuclei. We found that BR mRNA particles displayed phases of reduced mobility, while rRNA particles showed distinct binding events in and near nucleoli.
Neurologic evaluations in normal-tension glaucoma workups: are they worth the effort?

BACKGROUND Normal-tension glaucoma is a chronic progressive optic neuropathy of unknown etiology. Neuro-imaging workup in these patients is controversial. OBJECTIVES To determine the value of routine neurologic and neuro-ophthalmologic evaluations in patients with NTG. METHODS We conducted a retrospective review of all patients diagnosed with NTG in our institution between 2001 and 2006. Neurologic and neuro-ophthalmologic data were evaluated. RESULTS Sixty-eight patients were considered suitable for the study 135 males, 33 females; age range 43-90 years). Neurologic and neuro-ophthalmologic findings were normal in all of them. The computed tomography brain scan was normal in 88% and duplex carotid Doppler scan was normal in 92%. CONCLUSIONS Pathologic findings in neurologic and neuro-ophthalmologic assessments were uncommon in NTG. Therefore, contrary to earlier suggestions, neurologic and neuro-ophthalmologlc evaluations in typical normal-tension glaucoma patients appear to have no added value.
Reconnaissance support for juggling multiple processing options

A large proportion of computer-supported tasks—such as design exploration, decision analysis, data presentation, and many kinds of retrieval—can be characterised as user-driven processing of a body of data in search of an outcome that satisfies the user. Clearly such tasks can never be automated fully, but few existing tools offer support for mechanising more than the simplest repetitive aspects of the search. Reconnaissance facilities, in which the computer produces summary reports from exploration in directions suggested by the user, can save the user time and effort by revealing which areas are the most deserving of detailed investigation. The time users are prepared to spend on searching will be more effectively used, improving the likelihood of finding solutions that really meet their needs rather than merely being the first to appear satisfactory. This note describes an implemented example of reconnaissance, based on the parallel coordinates presentation technique.
ECS 201 A Survey Recent Advances in Caching Techniques

Replacement and Insertion policies play a key part in determining the effectiveness of caching in both uni-processor and multi-processor systems. General strategies have been designed to take advantage of the principle of locality obeyed by a large class of computer programs-Temporal Locality and Spatial Locality. On this note, the LRU replacement policy and its variations have been the de-facto standard in processor systems, but it has several shortcomings. Performance of LRU is severely affected when there is little locality in the behavior of the application program. To overcome this, some novel replacement strategies have been proposed that can fare well in both LRU-friendly and LRU-averse scenarios. We take a look at two of them-Adaptive Insertion Policies [15] and Re-Reference Interval Prediction (RRIP) [5]. Electrical interconnects are viewed as a major limiting factor with respect to designing high performance caches, with regard to latency, bandwidth, and power. Several hybrid architectures have been proposed which sought to provide lower average latency, lower cost and better overall performance. The increasing sizes of on-chip caches and the growing domination of wire delay necessitate significant changes to cache hierarchy design methodologies. To solved the scal-ability issues in multi-banked caches which form a Uniform Cache Architecture (UCA), non-uniform cache architectures (NUCA) have been proposed, where the banks are connected with an interconnect fabric and access time for a block is a function of the delays experienced in traversing the network path from the cache controller to the bank that contains the block. We take a look at Interconnect Design Delays for large NUCA caches [12], Reactive NUCA [4], PageNUCA [3] and ESP-NUCA [11]. Modern multi-core processors employ large last-level caches (LLC) shared between all of the cores. Researchers have proposed a variety of techniques to manage the LLC to provide better performance and fairness. Most of these schemes follow a pattern of observation, policy selection, and enforcement. Caches for multi-core processors can be managed both by hardware and software. Here we focus on two novel proposals of both mechanisms. Improvements in computational capability attained by Moore's law and microprocessor architectural innovations are over time balanced by corresponding improvements in I/O capability. 10GbE connectivity is expected to be a standard feature of server platforms in the near future. Among the numerous methods and features proposed to improve network performance of such platforms is Direct Cache Access (DCA) to route incoming I/O to CPU caches directly. We take …
What is Equality? Part 2: Equality of Resources

L'egalite des ressources privees presuppose une forme de marche economique. L'A. tente de definir un modele pertinent de ce marche, fonde sur une adjudication prenant en compte les desirs de chacun. Une fois les biens distribues a la satisfaction de tous, comment maintenir cette egalite premiere en contrebalancant par des assurances, des impots, sinon une redistribution periodique, les effets du hasard et du travail sur le developpement de ces biens? Confrontation de cette proposition avec les theories de la justice de Nozick, Chamberlain et surtout Rawls.
Examining Population Stratification via Individual Ancestry Estimates versus Self-Reported Race

Population stratification has the potential to affect the results of genetic marker studies. Estimating individual ancestry provides a continuous measure to assess population structure in case-control studies of complex disease, instead of using self-reported racial groups. We estimate individual ancestry using the Federal Bureau of Investigation CODIS Core short tandem repeat set of 13 loci using two different analysis methods in a case-control study of early-onset lung cancer. Individual ancestry proportions were estimated for “European” and “West African” groups using published allele frequencies. The majority of Caucasian, non-Hispanics had >50% European ancestry, whereas the majority of African Americans had <20% European ancestry, regardless of ancestry estimation method, although significant overlap by self-reported race and ancestry also existed. When we further investigated the effect of ancestry and self-reported race on the frequency of a lung cancer risk genotype, we found that the frequency of the GSTM1 null genotype varies by individual European ancestry and case-control status within self-reported race (particularly for African Americans). Genetic risk models showed that adjusting for individual European ancestry provided a better fit to the data compared with the model with no group adjustment or adjustment for self-reported race. This study suggests that significant population substructure differences exist that self-reported race alone does not capture and that individual ancestry may be confounded with disease status and/or a candidate gene risk genotype.
Robust Euclidean Alignment of 3D Point Sets

The problem of geometric alignment of two roughly pre-registered, partially overlapping, rigid, noisy 3D point sets is considered. A new natural and simple, robustified extension of the popular Iterative Closest Point (ICP) algorithm 1 is presented, called the Trimmed ICP (TrICP). The new algorithm is based on the consistent use of the Least Trimmed Squares (LTS) approach in all phases of the operation. Convergence is proved and an efficient implementation is discussed. TrICP is fast, applicable to overlaps under 50%, robust to erroneous measurements and shape defects, and has easy-to-set parameters. ICP is a special case of TrICP when the overlap parameter is 100%. Results of testing the new algorithm are shown.
CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of different social, economic and technical actors, which may be defined at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power flow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profitability of energy suppliers. The development of CASCADE has already yielded some interesting early findings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demand flattening across groups of domestic households fitted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profile. Ongoing and planned refinements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.
Performance of Automated Scoring for Children’s Oral Reading

For adult readers, an automated system can produce oral reading fluency (ORF) scores (e.g., words read correctly per minute) that are consistent with scores provided by human evaluators (Balogh et al., 2005, and in press). Balogh's work on NAAL materials used passage-specific data to optimize statistical language models and scoring performance. The current study investigates whether or not an automated system can produce scores for young children's reading that are consistent with human scores. A novel aspect of the present study is that text-independent rule-based language models were employed (Cheng and Townshend, 2009) to score reading passages that the system had never seen before. Oral reading performances were collected over cell phones from 1st, 2nd, and 3rd grade children (n = 95) in a classroom environment. Readings were scored 1) in situ by teachers in the classroom, 2) later by expert scorers, and 3) by an automated system. Statistical analyses provide evidence that machine Words Correct scores correlate well with scores provided by teachers and expert scorers, with all (Pearson's correlation coefficient) r's > 0.98 at the individual response level, and all r's > 0.99 at the "test" level (i.e., median scores out of 3).
Implement for Stomach Epidermis Tumor Diagnosis Based on Watershed Algorithm and Boundary Tracing Algorithm

Image segmentation is a key process of any image recognition system. Loose repeat algorithm and K-means algorithm are used to resolve the stomach epidermis tumor segmentation, but many conglutinated cells cannot be separated by others with the help of traditional segmentation algorithms. So the Vincent watershed algorithm as well as the Inver watershed algorithm is designed to do segmentation experiments about stomach epidermis tumors. A lot of experiments about several kinds’ images were done to build the right segmentation theory. The conclusion of these experiments show that these two algorithms could get good segmentation results while the image has few conglutinated areas. Moreover, the Inver algorithm may get better result than the Vincent algorithm while the image has many conglutinated areas. As a defect of the Inver algorithm, it may take many very small areas after segmentation. Finally, boundary tracing algorithm is designed to obtain the boundaries of tumor cells.