Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonthermal ablation of deep brain targets: A simulation study on a large animal model

Purpose: Thermal ablation with transcranial MRI-guided focused ultrasound (FUS) is currently limited to central brain targets because of heating and other beam effects caused by the presence of the skull. Recently, it was shown that it is possible to ablate tissues without depositing thermal energy by driving intravenously administered microbubbles to inertial cavitation using low-duty-cycle burst sonications. A recent study demonstrated that this ablation method could ablate tissue volumes near the skull base in nonhuman primates without thermally damaging the nearby bone. However, blood–brain disruption was observed in the prefocal region, and in some cases, this region contained small areas of tissue damage. The objective of this study was to analyze the experimental model with simulations and to interpret the cause of these effects. Methods: The authors simulated prior experiments where nonthermal ablation was performed in the brain in anesthetized rhesus macaques using a 220 kHz clinical prototype transcranial MRI-guided FUS system. Low-duty-cycle sonications were applied at deep brain targets with the ultrasound contrast agent Definity. For simulations, a 3D pseudospectral finite difference time domain tool was used. The effects of shear mode conversion, focal steering, skull aberrations, nonlinear propagation, and the presence of skull base on the pressure field were investigated using acoustic and elastic wave propagation models. Results: The simulation results were in agreement with the experimental findings in the prefocal region. In the postfocal region, however, side lobes were predicted by the simulations, but no effects were evident in the experiments. The main beam was not affected by the different simulated scenarios except for a shift of about 1 mm in peak position due to skull aberrations. However, the authors observed differences in the volume, amplitude, and distribution of the side lobes. In the experiments, a single element passive cavitation detector was used to measure the inertial cavitation threshold and to determine the pressure amplitude to use for ablation. Simulations of the detector’s acoustic field suggest that its maximum sensitivity was in the lower part of the main beam, which may have led to excessive exposure levels in the experiments that may have contributed to damage in the prefocal area. Conclusions: Overall, these results suggest that case-specific full wave simulations before the procedure can be useful to predict the focal and the prefocal side lobes and the extent of the resulting bioeffects produced by nonthermal ablation. Such simulations can also be used to optimally position passive cavitation detectors. The disagreement between the simulations and the experiments in the postfocal region may have been due to shielding of the ultrasound field due to microbubble activity in the focal region. Future efforts should include the effects of microbubble activity and vascularization on the pressure field.
Free Probability, Sample Covariance Matrices and Stochastic Eigen-Inference

Free probability provides tools and techniques for studying the spectra of large Hermitian random matrices. These stochastic eigen-analysis techniques have been invaluable in providing insight into the structure of sample covariance matrices. We briefly outline how these techniques can be used to analytically predict the spectrum of large sample covariance matrices. We discuss how these eigen-analysis tools can be used to develop eigen-inference methodologies.
Learning with the Optimized Data-Dependent Kernel

This paper presents a method of optimizing a data-dependent kernel by maximizing a measure of class separability in the empirical feature space, an Euclidean space in which the training data are embedded in such a way that the geometrical structure of the data in the feature space is preserved. An effective algorithm is derived to perform the optimization. The optimized kernel show more adaptive to the data and leads to a substantial improvement in the performance of the kernel machines. Simulations are carried out to demonstrate this improvement.
Tremor varies as a function of the temporal regularity of deep brain stimulation

The frequency of stimulation is one of the primary factors determining the effectiveness of deep brain stimulation (DBS) in relieving tremor. DBS efficacy, however, may depend not only on the average frequency of stimulation, but also on the temporal pattern of stimulation. We conducted intraoperative measurements of the effect of temporally irregular DBS (nonconstant interpulse intervals) on tremor. As the coefficient of variation of irregular high frequency DBS trains increased, they became less effective at reducing tremor (mixed effects regression model, P<0.04). These data provide evidence that the effects of DBS are dependent not only on the average frequency of DBS, but also on the regularity of the temporal spacing of DBS pulses.
Sex-Dependent Effects of Perinatal Inflammation on the Brain: Implication for Neuro-Psychiatric Disorders

Individuals born preterm have higher rates of neurodevelopmental disorders such as schizophrenia, autistic spectrum, and attention deficit/hyperactivity disorders. These conditions are often sexually dimorphic and with different developmental trajectories. The etiology is likely multifactorial, however, infections both during pregnancy and in childhood have emerged as important risk factors. The association between sex- and age-dependent vulnerability to neuropsychiatric disorders has been suggested to relate to immune activation in the brain, including complex interactions between sex hormones, brain transcriptome, activation of glia cells, and cytokine production. Here, we will review sex-dependent effects on brain development, including glia cells, both under normal physiological conditions and following perinatal inflammation. Emphasis will be given to sex-dependent effects on brain regions which play a role in neuropsychiatric disorders and inflammatory reactions that may underlie early-life programming of neurobehavioral disturbances later in life.
New technologies in assessment and neuropsychological rehabilitation

There is increasing use of technological innovations in assessment and neuropsychological rehabilitation in research and clinical practice. Thus, the purpose of this narrative review is to present what and how new technologies has been historically embedded in clinical and experimental neuropsychology, with a demonstrated academic production increased in the last 10 years. The literature presents that neuropsychological assessment highlights the use of computerized versions of instruments which traditionally are used in pencil and paper; cognitive simulations, artifi cial intelligence, and problem solving tasks. However, computerized tests are the most established technologies in this fi eld. Further, a considerable part of the studies are performed in adults and elderly people, but few validations in children. In rehabilitation, the use of new technologies is more diversifi ed, such as electronic devices and cell phones, tablet computers, video games, virtual reality, robots, and videofeedback neurofeedback, transcranial direct current stimulation, among others. In neuropsychological rehabilitation, the new technologies have facilitated the development of compensatory strategies and real-world simulations. From this review we discuss the new possibilities of technological interfaces in neuropsychology, as well the need for development and validation of computerized batteries and more dynamic and versatile rehabilitation protocols.
OPTIMIZATION METHOD OF PILOT ALLOCATION FOR COOPERATIVE AMPLIFY-AND-FORWARD OFDM SYSTEM 1

Pilot-assisted channel estimation has been studied only in common cooperative AF (Amplify-and-Forward) OFDM which has no feedback mechanism. In this paper, for cooperative AF-OFDM system, we propose a feedback technique in which the pilot allocation mechanism is adapted to the cooperative mobile channel. Then we show how uniform pilots may no longer be optimal compared with our pilots. After deducing the instantaneous system SNR is the function of the pilot allocation, we optimize the pilot locations using optimization method at the destination node. We examine the feedback overhead that is associated with our method and make comparisons with the conventional uniform pilot allocation. To improve system capacity, we suggest reduce the feedback information using K-means clustering algorithm. Simulation results confirmed that the proposed optimization method has an ideal performance gains and the algorithm of feedback reduction can reduce the feedback information under the premise of ideal performance.
Genetic and Real-World Clinical Data, Combined with Empirical Validation, Nominate Jak-Stat Signaling as a Target for Alzheimer’s Disease Therapeutic Development

As genome-wide association studies (GWAS) have grown in size, the number of genetic variants that have been associated per disease has correspondingly increased. Despite this increase in the number of single-nucleotide polymorphisms (SNPs) identified per disease, their biological interpretation has in many cases remained elusive. To address this, we have combined GWAS results with orthogonal sources of evidence, namely the current knowledge of molecular pathways; real-world clinical data from six million patients; RNA expression across tissues from Alzheimer’s disease (AD) patients, and purpose-built rodent models for experimental validation. In more detail, first we show that when examined at a pathway level, analysis of all GWAS studies groups AD in a cluster with disorders of immunity and inflammation. Using clinical data, we show that the degree of comorbidity of these diseases with AD correlates with the strength of their genetic association with molecular participants in the Janus kinases/signal transducer and activator of transcription (JAK-STAT) pathway. Using four independent RNA expression datasets we then find evidence for the altered regulation of JAK-STAT pathway genes in AD. Finally, we use both in vitro and in vivo rodent models to demonstrate that Aβ induces gene expression of the key drivers of this pathway, providing experimental evidence to validate these data-driven observations. These results therefore nominate JAK-STAT anomalies as a prominent aetiopathological event in AD and hence a potential target for therapeutic development, and moreover demonstrate a de novo multi-modal approach to derive information from rapidly increasing genomic datasets.
Improvement on a Provable Secure Access Control using Smart Cards

An access control scheme integrating with user authentication is proposed. Though the scheme is provably secure in request messaging (authentication), there is a flaw in access control. This paper presents an attack on the access control system; and further, an improvement is proposed to remedy this flaw. Our improvement only increases the information size and the cost of computations during registration time, but these quantities are not increased during the login and verification phase.
Tunable coupled inductor Q-enhancement for parallel resonant LC tanks

A tunable transformer-based Q-enhancement method for monolithic inductors used in parallel resonant LC tanks is presented. The Q of the inductor that forms the transformer primary is enhanced by cancelling the voltage drop across the series loss resistance of the primary with a voltage of opposite polarity that is induced by a current in the secondary. The circuit allows DC voltage control of Q-enhancement. Techniques to address stability issues associated with the positive feedback are described. The circuit was fabricated in 0.18 /spl mu/m CMOS and the performance was verified experimentally.
One size fits many Westerners: How Cultural Abilities Challenge UI Design

Cultural influences on our behavior are partly reflected in neuroanatomical changes in our brains, altering our abilities to perceive and interpret information. This paper points out possible consequences of such ”cultural abilities” for user interface design, and outlines challenges for systems that adapt to their users. Specifically, we describe how culture could influence our design decisions of when, how, what, why, and where to adapt.
Overcoming quantum decoherence with plasmonics

The use of nanoscale plasmonic metamaterials can optimize photon-matter interactions Photons occupy a special place as carriers of quantum information because they propagate information at the speed of light, with almost zero cross-talk, and interact relatively weakly with matter. They are primary candidates for implementing quantum networks (1), which are essential for both secure communication and transmission of quantum information. Nonclassical states of light (such as squeezed states) are also used in quantum simulation and emerging quantum sensing approaches. However, the robustness of photons as carriers of quantum information is a double-edged sword. In order to produce single photons or make them interact with each other, light must couple with matter. Photonic technologies, especially those implemented with nanoscale plasmonic metamaterials, can enable these interactions and help realize the full potential of photons in quantum information technology.
Wavelet Denoising for Multi-lead High Resolution ECG Signals

The aim of this study was to investigate the application of wavelet denoising in noise reduction of multichannel high resolution ECG signals. In particular, the influence of the selection of wavelet function and the choice of decomposition level on efficiency of denoising process were considered and whole procedures of noise reduction were implemented in MatLab environment. The Fast Wavelet Transform was use. The advantage of used denoising method is noise level decreasing in ECG signals, in which noise reduction by averaging has limited application, i.e. in case of arrhythmia, or in presence of extrasystols.
Eukaryotic initiation factor 4E (eIF4E): A recap of the cap‐binding protein

Eukaryotic initiation factor 4E (eIF4E), a fundamental effector and rate limiting element of protein synthesis, binds the 7‐methylguanosine cap at the 5′ end of eukaryotic messenger RNA (mRNA) specifically as a constituent of eIF4F translation initiation complex thus facilitating the recruitment of mRNA to the ribosomes. This review focusses on the engagement of signals contributing to growth factor originated maxim and their role in the activation of eIF4E to achieve a collective influence on cellular growth, with a key focus on conjuring vital processes like protein synthesis. The review invites considerable interest in elevating the appeal of eIF4E beyond its role in regulating translation viz a viz cancer genesis, attributed to its phosphorylation state that improves the prospect for the growth of the cancerous cell. This review highlights the latest studies that have envisioned to target these pathways and ultimately the translational machinery for therapeutic intervention. The review also brings forward the prospect of eIF4E to act as a converging juncture for signaling pathways like mTOR/PI3K and Mnk/MAPK to promote tumorigenesis.
Whole-Genome Sequence of Acinetobacter baumannii HUMV-3743, Isolated from a Human Wound Exudate

Acinetobacter baumannii strain HUMV-3743 was obtained from wound exudate from an adult patient. Here, we report its complete genome sequence using Illumina-based sequence analysis, which revealed a genome of 4 Mb, which includes 2 predicted plasmids of 78.9 and 107 kb. ABSTRACT Acinetobacter baumannii strain HUMV-3743 was obtained from wound exudate from an adult patient. Here, we report its complete genome sequence using Illumina-based sequence analysis, which revealed a genome of 4 Mb, which includes 2 predicted plasmids of 78.9 and 107 kb. A total of 3,881 protein-coding genes are predicted from this assembly.
Unsatisfied Variables in Local Search

Several local search algorithms for propositional satis ability have been pro posed which can solve hard random problems beyond the range of conventional backtracking procedures In this paper we explore the impact of focusing search in these procedures on the unsatis ed variables that is those variables which appear in clauses which are not yet satis ed For random problems we show that such a focus reduces the sensitivity to input parameters We also observe a simple scaling law in performance For non random problems we show that whilst this focus can improve performance many problems remain di cult We speculate that such problems will remain hard for local search unless constraint propagation techniques can be combined with hill climbing
Effect of an eight-week smartphone-guided HRV-biofeedback intervention on autonomic function and impulsivity in healthy controls

A large body of scientific studies suggest a close relationship between increased vagal function and better cognitive performance. Objective: In the current study, we investigated the association between autonomic function and behavioral impulsivity. We hypothesized that heart rate variability (HRV) biofeedback training increases HRV and enhances inhibitory control. Approach: A total of 28 healthy participants were recruited. After drop-out, 14 participants completed an eight-week HRV biofeedback training with five training sessions per week including one session at the clinic’s laboratory and four sessions at home using a mobile application running on their smartphone. Ten control subjects matched with respect to age and gender played a mobile game according to the same schedule as the biofeedback group. The assessment of autonomic status and the stop-signal task were conducted before the beginning of the training (T1) and after finishing the schedule (T2). Main results: We found a relationship of reaction times in the stop-signal task and standard HRV as well as cardiorespiratory indices. After biofeedback training, short-term HRV and baroreflex function significantly increased by 33% (CI [2%, 64%], p < 0.05) and 21% (CI [5%, 36%], p < 0.05), respectively. The performance in the stop-signal task was not affected by the biofeedback intervention. Compared to the changes of autonomic indices in the control group, only a decrease of skin conductance levels in the biofeedback group remained statistically significant. Significance: Our results indicate that a smartphone-based HRV biofeedback intervention can be applied to improve cardiovagal function in healthy subjects. Although higher HRV was associated with higher levels of inhibitory control, HRV biofeedback had no effect on measures of impulsivity.
CONIVAS: content-based image and video access system

We have developed a CO Ntent-based Image and Video Access System (CO NIVAS). The system consists of a collection of tools to help users retrieve still images and videos from databases by content. This system includes new algorithms for image and video retrieval in addition to algorithms that are adopted from the literature. The system can be used in many applications that require searching large collections of images and video clips such as digital video library, professional video editing, TV news retrieval and copyright protection applications,
Critical slope p‐adic L‐functions

Let g be an eigenform of weight k+2 on Γ0(p)∩Γ1(N) with p ∤ N. If g is non‐critical (that is, of slope less than k+1), using the methods of Amice–Vélu and Višik, one can attach [‘Distributions p‐adiques associées aux séries de Hecke’, Journées Arithmétiques de Bordeaux (Conf., Univ. Bordeaux, Bordeaux, 1974), Astérisque 24–25 (Soc. Math. France, Paris, 1975) 119–131 (French)] and Višik [Mat. Sb. (N.S.) 99 (1976) 248–260], then one can attach a p‐adic L‐function to g which is uniquely determined by its interpolation property together with a bound on its growth. However, in the critical slope case, the corresponding growth bound is too large to uniquely determine the p‐adic L‐function with its standard interpolation property.
Effect of the Compaction and the Size of DNA on the Nuclear Transfer Efficiency after Microinjection in Synchronized Cells

The nuclear transfer process is one of the critical rate-limiting processes in transgene expression. In the present study, we report on the effect of compaction and the size of the DNA molecule on nuclear transfer efficiency by microinjection. A DNA/protamine complex- or variously-sized naked DNA molecules were injected into the cytoplasm or nucleus of synchronized HeLa cells. To evaluate the nuclear transfer process, a nuclear transfer score (NT score), calculated based on transgene expression after cytoplasmic microinjection divided by that after nuclear microinjection, was employed. The compaction of DNA with protamine decreased the NT score in comparison with the injection of naked DNA when the N/P ratio was increased to >2.0. Moreover, when naked DNA was microinjected, gene expression increased in parallel with the size of the DNA in the following order: minicircle DNA (MC07.CMV-EGFP; 2257 bp) > middle-sized plasmid DNA (pBS-EGFP; 3992 bp) > conventional plasmid DNA (pcDNA3.1-EGFP; 6172 bp), while the level of gene expression was quite comparable among them when the DNAs were injected into the nucleus. The above findings suggest that the intrinsic size of the DNA molecule is a major determinant for nuclear entry and that minicircle DNA has a great advantage in nuclear transfer.
Toward Flexible Information Processing in the Real World

Human and creatures are flexibly processing information in the diverse environment in the real world. The Real World Computing (RWC) Program aims at establishing theoretical and technological foundation for such flexible information processing in the real world as a new paradigm beyond the conventional framework. The key words, “flexibility” and “real world,” contain a strong antithesis to the conventional rigid information processing based on serial and procedural scheme, or algorithm. The aim of this paper is to review information processing schemes and to emphasize the importance of reconsidering pattern recognition and of understanding a Bayesian framework underlying toward a theoretical foundation for flexible information processing in the real world.
Kernel Fukunaga–Koontz Transform Subspaces for Classification of Hyperspectral Images With Small Sample Sizes

In this letter, a novel supervised classification approach is presented for the classification of hyperspectral images using kernel Fukunaga-Koontz transform (KFKT). The Fukunaga-Koontz transform (FKT) is originally a powerful target detection method used in remote sensing tasks, and it is an especially good classification tool for two-class problems. The traditional FKT method has been kernelized for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this letter aims to solve the multiclass problem by regarding one class as target that is tried to be separated from the remaining classes (as clutter) like one-against-all methodology. The KFKT provides superior performance in the classification of hyperspectral data even using small number of samples because of nonlinear separability of data in higher dimensional space. The experiments confirm that KFKT has better and promising results than FKT and support vector machine in classification of hyperspectral images.