Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural and functional recovery elicited by combined putrescine and aminoguanidine treatment after aspirative lesion of the fimbria–fornix and overlying cortex in the adult rat

Damage to the adult CNS often causes permanent deficits. Based on a lesion model of septohippocampal pathway aspiration in the rat, we attempted to promote neuronal cell survival and post‐traumatic recovery by using a pharmalogical treatment combining aminoguanidine and putrescine (AGP). The functional recovery was followed over 15 weeks before morphological analysis. AGP treatment produced a persistent attenuation (∼ 50%) of the lesion‐induced hyperactivity, a reduction (∼ 60%) in the sensorimotor impairments and an improved performance in the water‐maze task which did not, however, rely upon improved memory capabilities. AGP weakened the lesion‐induced decrease in ChAT‐positive neurons in the medial septum and the extent of thalamic retrograde necrosis (by ∼ 30% in each case) and resulted in a partial cholinergic reinnervation of the dentate gyrus. These promising results support the idea that coadministration of putrescine and aminoguanidine might become a potent way to foster structural and functional recovery (or compensation) in the adult mammalian CNS after injury.
Statistical analysis of neural data : Generalized linear models for spike trains

0.1 Generalized linear models for spike trains; relationship to the standard linear Gaussian model . 2 0.2 Generalized linear models for images in low-light conditions; incorporating nonnegativity constraints . 4 0.3 Sampling properties of the MLE; connections to spike-triggered averaging . 5 0.4 Incorporating nonlinear terms . 6 0.5 Incorporating spike history effects and interneuronal interactions . 7 0.6 Example: fitting time-varying terms / PSTH estimation . 8 0.7 Multiplicative models of spike history-dependence; connections to renewal models 9 0.8 Connection to biophysical models: soft-threshold integrate-and-fire models . 12 0.9 Avoiding overfitting: training error, generalization, and cross-validation . 14 0.10 Reducing the number of parameters can increase the prediction accuracy; basis choice . 18 0.11 Low-rank approximations provide a useful method for reducing the number of parameters . 19 0.12 Regularization; maximum penalized likelihood; maximum a posteriori estimation 22 0.13 The Fisher information matrix is useful for large-sample approximations of confidence ellipses and errorbars . 27 0.14 The Fisher information matrix may be used to help select stimuli adaptively 29 0.15 Extensions: latent variable models . 31
Learning to shoot in first person shooter games by stabilizing actions and clustering rewards for reinforcement learning

While reinforcement learning (RL) has been applied to turn-based board games for many years, more complex games involving decision-making in real-time are beginning to receive more attention. A challenge in such environments is that the time that elapses between deciding to take an action and receiving a reward based on its outcome can be longer than the interval between successive decisions. We explore this in the context of a non-player character (NPC) in a modern first-person shooter game. Such games take place in 3D environments where players, both human and computer-controlled, compete by engaging in combat and completing task objectives. We investigate the use of RL to enable NPCs to gather experience from game-play and improve their shooting skill over time from a reward signal based on the damage caused to opponents. We propose a new method for RL updates and reward calculations, in which the updates are carried out periodically, after each shooting encounter has ended, and a new weighted-reward mechanism is used which increases the reward applied to actions that lead to damaging the opponent in successive hits in what we term “hit clusters”.
A modified nonlinear dynamic inversion method for attitude control of UAVs under persistent disturbances

Nonlinear dynamic inversion (NDI) has been applied to the control law design of UAVs for many years mainly due to its good robustness. However, it has a weakness of relying on accurate model of the plant greatly, which restrains its application since UAVs are easy to be influenced by persistent disturbances such as model uncertainties, winds and gusts; thus, development of accurate model for attitude control of UAVs is difficult. To solve the problem, in this paper, a modified nonlinear dynamic inversion (MNDI) method based on linear extended state observer (LESO), which rejects the above disturbances by estimating them and then counteracting, is developed. Comparison with the traditional NDI (TNDI) method was carried out numerically; the results show that, in coping with persistent disturbances, the MNDI-based method presents significant superiority.
Continuation of Connecting orbits in 3D-ODES (I): Point-to-Cycle Connections

We propose new methods for the numerical continuation of point-to-cycle connecting orbits in three-dimensional autonomous ODE's using projection boundary conditions. In our approach, the projection boundary conditions near the cycle are formulated using an eigenfunction of the associated adjoint variational equation, avoiding costly and numerically unstable computations of the monodromy matrix. The equations for the eigenfunction are included in the defining boundary-value problem, allowing a straightforward implementation in AUTO, in which only the standard features of the software are employed. Homotopy methods to find connecting orbits are discussed in general and illustrated with several examples, including the Lorenz equations. Complete AUTO demos, which can be easily adapted to any autonomous three-dimensional ODE system, are freely available.
Hyperincident connected components of tagging networks

Data created by social bookmarking systems can be described as 3-partite 3-uniform hypergraphs connecting documents, users, and tags (tagging networks), such that the toolbox of complex network analysis can be applied to examine their properties. One of the most basic tools, the analysis of connected components, however cannot be applied meaningfully: Tagging networks tend to be almost entirely connected. We therefore propose a generalization of connected components, m-hyperincident connected components. We show that decomposing tagging networks into 2-hyperincident connected components yields a characteristic component distribution with a salient giant component that can be found across various datasets. This pattern changes if the underlying formation process changes, for example, if the hypergraph is constructed from search logs, or if the tagging data is contaminated by spam: It turns out that the second- to 129th largest components of the spam-labeled Bibsonomy dataset are inhabited exclusively by spam users. Based on these findings, we propose and unsupervised method for spam detection.
Quality assurance and quality control in the routine molecular diagnostic laboratory for infectious diseases

Abstract Molecular diagnostics has become one of the dominant platforms in clinical laboratory medicine. Technological improvements, from automated sample preparation to real time amplification technology, provide the possibility to develop and run assays for a growing number of clinical questions. However, quality assurance and quality control issues have often remained underdeveloped but are still critical. To relate patient results to prior results or to absolute values in clinical practice guidelines, those results need to be comparable across time and methods. This may be achieved either by producing the identical value across methods and test versions or by using reliable and stable conversions. The establishment of international standards and reference materials is thus of paramount importance. This review focuses on general and specific issues relevant for quality assurance and quality control in the routine molecular diagnostics laboratory.
Research on MEMS Phthalocyanine-Based Gas Sensor

A gas sensor based on MEMS (microelectro-machine system) has been developed to provide a sensitive means of detecting nitrogen dioxide. The structure, configuration and fabrication steps were described. The sensor was copper phthalocyanine (CuPc) films which caused a resistance change upon exposure to nitrogen dioxide. The sensor demonstrated a good response and recovery time about 4s and 7s separately. Results also indicate to be accordance with the sensitive mechanism of CuPc in terms of semiconductor theory.
Discovering Students' Complex Problem Solving Strategies in Educational Assessment

A huge amount of log data accumulates automatically during computer-based educational assessments that can be analyzed for diagnostic or educational purposes using data mining techniques. In this paper, we describe our work of mining students’ complex problem solving interactions when tackling previously unknown and dynamically changing situations. Based on log data analyses, we discovered several problem solving strategies and examined relationships of these strategies and test outcomes. We applied clustering algorithms to discriminate between students with different levels of proficiency in problem solving. We identified four groups of students: two clusters represent successful problem solvers who differ in their level of efficiency, one group of inefficient students might need further practice to be able to solve these kinds of tasks, and finally we found a mixed-strategy group of students. Students in this last group were dynamically developing their problem solving strategy and in parallel, the ratio of correct responses increased from task to task during assessment. In sum, our findings help to advance research on cognitive processes; we support educational researchers in better understanding complex problem solving behavior and identify levels of problem solving proficiency.
Observer-based output feedback control of sampled-data system under stochastic sampling

This paper is concerned with output feedback stabilization problem for a class of sampled-data systems under stochastic sampling. Different from the existing results, a systems matrix A whose eigenvalues contain zero is allowed. By combining the Kronecker product operation with the Vandermonde matrix, a sufficient condition is developed to guarantee the stochastic stability of the closed-loop system. Based on linear matrix inequality (LMI) and a cone complementarity linearization algorithm, a method of designing an observer-based output feedback controller for the system is given. Finally, a simulation example is given to show the effectiveness of the proposed method.
Joint semantics and feature based image retrieval using relevance feedback

Relevance feedback is a powerful technique for image retrieval and has been an active research direction for the past few years. Various ad hoc parameter estimation techniques have been proposed for relevance feedback. In addition, methods that perform optimization on multilevel image content model have been formulated. However, these methods only perform relevance feedback on low-level image features and fail to address the images' semantic content. In this paper, we propose a relevance feedback framework to take advantage of the semantic contents of images in addition to low-level features. By forming a semantic network on top of the keyword association on the images, we are able to accurately deduce and utilize the images' semantic contents for retrieval purposes. We also propose a ranking measure that is suitable for our framework. The accuracy and effectiveness of our method is demonstrated with experimental results on real-world image collections.
Design, development and clinical validation of a wrist-based optical heart rate monitor

Development in the field of sensor technology, hardware miniaturization, ubiquitous computing and connected solutions paved the way for the development of wearables for continuous physiological parameter monitoring. Continuous heart rate monitoring with clinical accuracy using reflectance photoplethysmogram signals from wrist is highly challenging and presents a potential area of research. In this work, we present a wearable device in a wrist watch form factor for heart rate monitoring. The device runs on a low power ARM cortex M4 microcontroller and integrates a BLE (Bluetooth Low energy) module for wireless connectivity. A heart rate computation algorithm using reflectance photoplethysmography and a 3 axes accelerometer for motion artifact removal is presented in the paper. Heart rate computed by the wrist worn device was validated against heart rate measured using Masimo Radical-7 on 256 subjects. The validation study was conducted in a hospital setting for a duration of 1 month, after obtaining the ethics committee approval and informed consent from the subjects. Details of the experimental setup, clinical validation protocol and observations and inferences made from the study are presented.
The Automatic Defense Mechanism for Malicious Injection Attack

Injection attack is a technique to inject codes into a computer program or system by taking advantage of the unchecked assumptions the system makes about its inputs. The purpose of the injected code is typically to bypass or modify the originally intended functionality of the program. It is popular in system hacking or cracking to gain information, privilege escalation or unauthorized access to a system. Many application's security vulnerabilities result from generic injection problems. Examples of such vulnerabilities are SQL injection, shell injection and script injection (cross site scripting). Some applications attempt to protect themselves by filtering malicious input data, but it may not be viable to modify the source of such components (either because the code was shipped in binary form or because the license agreement is prohibitive). We have tried to develop a defense mechanism that can automatically produce a proper input validation function on security gateway to filter malicious injection. The security gateway is allocated in front of application server to eliminate malicious injection vulnerabilities. To verify the efficiency of the tool, we pick the Websites made up of some Web applications that often contain third-party vulnerable components shipped in binary form. Among these experiments, our defense mechanism has proved their efficiency to avoid malicious injection attack.
Chapter 5 : Photometry and Polarimetry

Most of what we know about astronomical sources comes from measuring their spectral energy distributions (SEDs) or from taking spectra. We can distinguish the two approaches in terms of the spectral resolution, defined as R = where  is the wavelength of observation and  is the range of wavelengths around  that are combined into a single flux measurement. Photometry refers to the procedures for measuring or comparing SEDs and is typically obtained at R ~ 2 10. It is discussed in this chapter, while spectroscopy is described in the following one.
Nominals, Inverses, Counting, and Conjunctive Queries or: Why Infinity is your Friend!

Description Logics are knowledge representation formalisms that provide, for example, the logical underpinning of the W3C OWL standards. Conjunctive queries, the standard query language in databases, have recently gained significant attention as an expressive formalism for querying Description Logic knowledge bases. Several different techniques for deciding conjunctive query entailment are available for a wide range of DLs. Nevertheless, the combination of nominals, inverse roles, and number restrictions in OWL 1 and OWL 2 DL causes unsolvable problems for the techniques hitherto available. We tackle this problem and present a decidability result for entailment of unions of conjunctive queries in the DL ALCHOIQb that contains all three problematic constructors simultaneously. Provided that queries contain only simple roles, our result also shows decidability of entailment of (unions of) conjunctive queries in the logic that underpins OWL 1 DL and we believe that the presented results will pave the way for further progress towards conjunctive query entailment decision procedures for the Description Logics underlying the OWL standards.
Assessment of treatment response during chemoradiation therapy for pancreatic cancer based on quantitative radiomic analysis of daily CTs: An exploratory study

Purpose In an effort for early assessment of treatment response, we investigate radiation induced changes in quantitative CT features of tumor during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. On each daily CT, the pancreatic head, the spinal cord and the aorta were delineated and the histograms of CT number (CTN) in these contours were extracted. Eight histogram-based radiomic metrics including the mean CTN (MCTN), peak position, volume, standard deviation (SD), skewness, kurtosis, energy and entropy were calculated for each fraction. Paired t-test was used to check the significance of the change of specific metric at specific time. GEE model was used to test the association between changes of metrics over time for different pathology responses. Results In general, CTN histogram in the pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the 1st to the 26th fraction in MCTN ranged from -15.8 to 3.9 HU with an average of -4.7 HU (p<0.001). Meanwhile the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less peaked). The changes of MCTN, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response is associated with the changes of MCTN, SD, and skewness. In cases of good response, patients tend to have large reductions in MCTN and skewness, and large increases in SD and kurtosis. Conclusions Significant changes in CT radiomic features, such as the MCTN, skewness, and kurtosis in tumor were observed during the course of CRT for pancreas cancer based on quantitative analysis of daily CTs. These changes may be potentially used for early assessment of treatment response and stratification for therapeutic intensification.
Exports and Wages: Rent Sharing, Workforce Composition or Returns to Skills?

We use linked employer-employee data from Italy to explore the relationship between exports and wages. Our empirical strategy exploits the 1992 devaluation of the Italian Lira, which represented a large and unforeseen shock to Italian firms' incentives to export. The results indicate that the export wage premium is due to exporting firms both (1) paying a wage premium above what their workers would earn in the outside labor market – the "rent-sharing" effect, and (2) employing workers whose skills command a higher price after the devaluation – the "skill composition" effect. The latter effect only emerges once we allow for the value of individual skills to differ in the pre- and post-devaluation periods. In fact, using a fixed measure of skills, as typically done in the literature, we would attribute the wage increase only to rent sharing. We also document that the export wage premium is larger for workers with more export-related experience. This indicates that the devaluation increased the demand for skills more useful for exporting, driving their relative price up.
Histogram-Based Prefiltering for Luminance and Chrominance Compensation of Multiview Video

Significant advances have recently been made in the coding of video data recorded with multiple cameras. However, luminance and chrominance variations between the camera views may deteriorate the performance of multiview codecs and image-based rendering algorithms. A histogram matching algorithm can be applied to efficiently compensate for these differences in a prefiltering step. A mapping function is derived which adapts the cumulative histogram of a distorted sequence to the cumulative histogram of a reference sequence. If all camera views of a multiview sequence are adapted to a common reference using histogram matching, the spatial prediction across camera views is improved. The basic algorithm is extended in three ways: a time-constant calculation of the mapping function, RGB color conversion, and the use of global disparity compensation. The best coding results are achieved when time-constant histogram calculation and RGB color conversion are combined. In this case, the usage of histogram matching prior to multiview encoding leads to substantial gains in the coding efficiency of up to 0.7 dB for the luminance component and up to 1.9 dB for the chrominance components. This prefiltering step can be combined with block-based illumination compensation techniques that modify the coder and decoder themselves, especially with the approach implemented in the multiview reference software of the joint video team (JVT). Additional coding gains up to 0.4 dB can be observed when both methods are combined.
SpecTLB: A mechanism for speculative address translation

Data-intensive computing applications are using more and more memory and are placing an increasing load on the virtual memory system. While the use of large pages can help alleviate the overhead of address translation, they limit the control the operating system has over memory allocation and protection. We present a novel device, the SpecTLB, that exploits the predictable behavior of reservation-based physical memory allocators to interpolate address translations. Our device provides speculative translations for many TLB misses on small pages without referencing the page table. While these interpolations must be confirmed, doing so can be done in parallel with speculative execution. This effectively hides the execution latency of these TLB misses. In simulation, the SpecTLB is able to overlap an average of 57% of page table walks with successful speculative execution over a wide variety of applications. We also show that the SpecTLB outperforms a state-of-the-art TLB prefetching scheme for virtually all tested applications with significant TLB miss rates. Moreover, we show that the SpecTLB is efficient since mispredictions are extremely rare, occurring in less than 1% of TLB misses. In essense, the SpecTLB effectively enables the use of small pages to achieve fine-grained allocation and protection, while avoiding the associated latency penalties of small pages.
Linguistically Motivated Bigrams in Part-of-Speech Tagging of Language Corpora

After some discussion concerning the issues of corpus representativity in the first paragraphs, this paper presents a simple yet in practice very efficient technique serving for automatic detection of those positions in a Part-ofSpeech tagged corpus where an error is to be suspected. The approach is based on the idea of creating and then applying a set of "invalid bigrams", i.e. of pairs of adjacent Part-of-Speech tags which constitute an incorrect configuration in a tagged text of a particular language (in English, e.g., the bigram [ARTICLE, FINITE VERB]). Further, the paper describes the generalization of the "invalid bigrams" into a certain set of "invalid n-grams", for any natural n, which indeed provides a powerful tool for error detection in a corpus. Some implementation issues are also presented, as well as evaluation of results of the approach when used for error detection in the NEGRA corpus of German. Finally, general implications for the quality of results of statistical taggers are discussed. Illustrative examples in the text are taken mainly from German, and hence at least a basic command of this language would be helpful for their understanding – due to the complexity of the necessary accompanying explanation, the examples are neither glossed nor translated. However, the central ideas of the paper should be understandable also without any knowledge of German.