Comment on "Quantitative x-ray photoelectron spectroscopy: Quadrupole effects, shake up, Shirley background, and relative sensitivity factors from a database of true x-ray photoelectron spectra"

This Comment demonstrates that a comparison analysis by Seah and Gilmore between experimental data on the X-ray photoelectron spectroscopy intensities and theoretical data by Trzhaskovskaya et al. is misleading due to a number of serious errors made by Seah and Gilmore (Phys. Rev. B, 73, 174113).Comment: 7 pages, 3 figures, submitted to Phys. Rev.

Integral constraints on the monodromy group of the hyperkahler resolution of a symmetric product of a K3 surface

Let M be a 2n-dimensional Kahler manifold deformation equivalent to the Hilbert scheme of length n subschemes of a K3 surface S. Let Mon be the group of automorphisms of the cohomology ring of M, which are induced by monodromy operators. The second integral cohomology of M is endowed with the Beauville-Bogomolov bilinear form. We prove that the restriction homomorphism from Mon to the isometry group O[H^2(M)] is injective, for infinitely many n, and its kernel has order at most 2, in the remaining cases. For all n, the image of Mon in O[H^2(M)] is the subgroup generated by reflections with respect to +2 and -2 classes. As a consequence, we get counter examples to a version of the weight 2 Torelli question, when n-1 is not a prime power.Comment: Version 3: Latex, 54 pages. Expository change

Sensorimotor functional connectivity: A neurophysiological factor related to BCI performance

Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. About 20% of potential users of sensorimotor BCIs do not gain reliable control of the system. The inefficiency to decode user's intentions requires the identification of neurophysiological factors determining “good” and “poor” BCI performers. One of the important neurophysiological aspects in BCI research is that the neuronal oscillations, used to control these systems, show a rich repertoire of spatial sensorimotor interactions. Considering this, we hypothesized that neuronal connectivity in sensorimotor areas would define BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in a calibration and an online feedback session recorded on the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post- as well as pre-stimulus connectivity in the calibration recording is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study demonstrates that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sensorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance

The Kodaira dimension of the moduli of K3 surfaces

The moduli space of polarised K3 surfaces of degree 2d is a quasi-projective variety of dimension 19. For general d very little has been known about the Kodaira dimension of these varieties. In this paper we present an almost complete solution to this problem. Our main result says that this moduli space is of general type for d>61 and for d=46,50,54,58,60.Comment: 47 page

Mapping of multiple muscles with transcranial magnetic stimulation: Absolute and relative test-retest reliability

The spatial accuracy of transcranial magnetic stimulation (TMS) may be as small as a few millimeters. Despite such great potential, navigated TMS (nTMS) mapping is still underused for the assessment of motor plasticity, particularly in clinical settings. Here, we investigate the within‐limb somatotopy gradient as well as absolute and relative reliability of three hand muscle cortical representations (MCRs) using a comprehensive grid‐based sulcus‐informed nTMS motor mapping. We enrolled 22 young healthy male volunteers. Two nTMS mapping sessions were separated by 5–10 days. Motor evoked potentials were obtained from abductor pollicis brevis (APB), abductor digiti minimi, and extensor digitorum communis. In addition to individual MRI‐based analysis, we studied normalized MNI MCRs. For the reliability assessment, we calculated intraclass correlation and the smallest detectable change. Our results revealed a somatotopy gradient reflected by APB MCR having the most lateral location. Reliability analysis showed that the commonly used metrics of MCRs, such as areas, volumes, centers of gravity (COGs), and hotspots had a high relative and low absolute reliability for all three muscles. For within‐limb TMS somatotopy, the most common metrics such as the shifts between MCR COGs and hotspots had poor relative reliability. However, overlaps between different muscle MCRs were highly reliable. We, thus, provide novel evidence that inter‐muscle MCR interaction can be reliably traced using MCR overlaps while shifts between the COGs and hotspots of different MCRs are not suitable for this purpose. Our results have implications for the interpretation of nTMS motor mapping results in healthy subjects and patients with neurological conditions

ОСОБЛИВОСТІ ФУНКЦІОНУВАННЯ КОМП’ЮТЕРНОЇ МЕРЕЖІ ДЛЯ ЗАБЕЗПЕЧЕННЯ ІНФОРМАЦІЙНОЇ СИСТЕМИ СУДОВО-ЕКСПЕРТНОЇ ДІЯЛЬНОСТІ

The analysis of the quality control of data transmission process in computer network of the forensic information system is carried out. The role of a specialized network in the information system of forensic science in Ukraine is determined. The causes that lead to overload and packet loss in data transfer networks of the information system are analyzed. Quite high requirements are imposed on modern computer networks, but, unfortunately, in conditions of limited funding and of a variety of sectoral informatization programs (typical for the present realia of Ukraine), most computer networks are heterogeneous, that is they consist of various software and hardware under various operating systems and provide consumers with a wide range of information services. Due to rapid growth in the volume of information, load on computer network keep significantly increasing. A single error in computer network operation may lead either to loss of information or to modification of a large amount of data. It can drastically reduce the quality and efficiency of forensic examination. Unfortunately, such errors can be undetected for many reasons: software and/or hardware failure, incorrect administration, etc. Software bugs are highly dangerous (buffer overflow, program crash, system overload, gaining administrator rights). There is a need to manage data transfer process. To improve the quality of computer network functioning, it is proposed to create a system for evaluating network parameters. As a result of theoretical studies on network bandwidth controlled by the TCP protocol, based on an approach aimed at studying the network structure, a new way to control network’s computational capacity is suggested as well as it is also established that the suggested system for evaluating network parameters of the forensic information system allows you to determine location of telecommunication network segments with limited bandwidth. Using STAB allows you to accurately assess the available channel bandwidth, due to its calculation to m connections at any time. Thus, it will help to develop alternative virtual routes which will significantly reduce the number of lost packets and, ultimately, improve the quality of information transfer in the computer network of the forensic information system.Проаналізовано якість управління процесом передавання даних у комп’ютерній мережі інформаційної системи судової експертизи. Визначено роль спеціалізованої комп’ютерної мережі в інформаційній системі судової експертизи України. Досліджено причини перенавантаження та втрати пакетів у мережах передавання даних інформаційної системи. Для підвищення якості функціонування комп’ютерної мережі запропоновано створити систему оцінювання параметрів мережі. У результаті проведених теоретичних досліджень пропускної здатності, керованої протоколом TCP, на основі підходу, орієнтованого на вивчення структури мережі, запропоновано новий вид управління обчислювальною здатністю мережі, а також з’ясовано, що пропонована система оцінювання параметрів мережі інформаційної системи судово-експертної діяльності дає змогу визначати місце розташування ділянок телекомунікаційної мережі з обмеженою пропускною спроможністю

Improving motor imagery classification during induced motor perturbations

Objective.Motor imagery is the mental simulation of movements. It is a common paradigm to design brain-computer interfaces (BCIs) that elicits the modulation of brain oscillatory activity similar to real, passive and induced movements. In this study, we used peripheral stimulation to provoke movements of one limb during the performance of motor imagery tasks. Unlike other works, in which induced movements are used to support the BCI operation, our goal was to test and improve the robustness of motor imagery based BCI systems to perturbations caused by artificially generated movements.Approach.We performed a BCI session with ten participants who carried out motor imagery of three limbs. In some of the trials, one of the arms was moved by neuromuscular stimulation. We analysed 2-class motor imagery classifications with and without movement perturbations. We investigated the performance decrease produced by these disturbances and designed different computational strategies to attenuate the observed classification accuracy drop.Main results.When the movement was induced in a limb not coincident with the motor imagery classes, extracting oscillatory sources of the movement imagination tasks resulted in BCI performance being similar to the control (undisturbed) condition; when the movement was induced in a limb also involved in the motor imagery tasks, the performance drop was significantly alleviated by spatially filtering out the neural noise caused by the stimulation. We also show that the loss of BCI accuracy was accompanied by weaker power of the sensorimotor rhythm. Importantly, this residual power could be used to predict whether a BCI user will perform with sufficient accuracy under the movement disturbances.Significance.We provide methods to ameliorate and even eliminate motor related afferent disturbances during the performance of motor imagery tasks. This can help improving the reliability of current motor imagery based BCI systems

Separating neural oscillations from aperiodic 1/f activity: Challenges and recommendations

Electrophysiological power spectra typically consist of two components: An aperiodic part usually following an 1/f power law [Formula: see text] and periodic components appearing as spectral peaks. While the investigation of the periodic parts, commonly referred to as neural oscillations, has received considerable attention, the study of the aperiodic part has only recently gained more interest. The periodic part is usually quantified by center frequencies, powers, and bandwidths, while the aperiodic part is parameterized by the y-intercept and the 1/f exponent [Formula: see text]. For investigation of either part, however, it is essential to separate the two components. In this article, we scrutinize two frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) and IRASA (Irregular Resampling Auto-Spectral Analysis), that are commonly used to separate the periodic from the aperiodic component. We evaluate these methods using diverse spectra obtained with electroencephalography (EEG), magnetoencephalography (MEG), and local field potential (LFP) recordings relating to three independent research datasets. Each method and each dataset poses distinct challenges for the extraction of both spectral parts. The specific spectral features hindering the periodic and aperiodic separation are highlighted by simulations of power spectra emphasizing these features. Through comparison with the simulation parameters defined a priori, the parameterization error of each method is quantified. Based on the real and simulated power spectra, we evaluate the advantages of both methods, discuss common challenges, note which spectral features impede the separation, assess the computational costs, and propose recommendations on how to use them

2-elementary subgroups of the space Cremona group

We give a sharp bound for orders of elementary abelian 2-groups of birational automorphisms of rationally connected threefolds