Electronic structure of silicon-based nanostructures

We have developed an unifying tight-binding Hamiltonian that can account for the electronic properties of recently proposed Si-based nanostructures, namely, Si graphene-like sheets and Si nanotubes. We considered the $sp^3s^*$ and $sp^{3}$ models up to first- and second-nearest neighbors, respectively. Our results show that the Si graphene-like sheets considered here are metals or zero-gap semiconductors, and that the corresponding Si nanotubes follow the so-called Hamada's rule [Phys. Rev. Lett. {\bf 68}, 1579 1992]. Comparison to a recent {\it ab initio} calculation is made.Comment: 12 pages, 6 Figure

Hunter-gatherer children’s object play and tool use: An ethnohistorical analysis

Learning to use, make, and modify tools is key to our species’ success. Researchers have hypothesized that play with objects may have a foundational role in the ontogeny of tool use and, over evolutionary timescales, in cumulative technological innovation. Yet, there are few systematic studies investigating children’s interactions with objects outside the post-industrialized West. Here, we survey the ethnohistorical record to uncover cross-cultural trends regarding hunter-gatherer children’s use of objects during play and instrumental activities. Our dataset, consisting of 434 observations of children’s toys and tools from 54 hunter-gatherer societies, reveals several salient trends: Most objects in our dataset are used in play. Children readily manufacture their own toys, such as dolls and shelters. Most of the objects that children interact with are constructed from multiple materials. Most of the objects in our dataset are full-sized or miniature versions of adult tools, reflecting learning for adult roles. Children also engage with objects related to child culture, primarily during play. Taken together, our findings show that hunter-gatherer children grow up playing, making, and learning with objects

Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval

Accurately matching visual and textual data in cross-modal retrieval has been widely studied in the multimedia community. To address these challenges posited by the heterogeneity gap and the semantic gap, we propose integrating Shannon information theory and adversarial learning. In terms of the heterogeneity gap, we integrate modality classification and information entropy maximization adversarially. For this purpose, a modality classifier (as a discriminator) is built to distinguish the text and image modalities according to their different statistical properties. This discriminator uses its output probabilities to compute Shannon information entropy, which measures the uncertainty of the modality classification it performs. Moreover, feature encoders (as a generator) project uni-modal features into a commonly shared space and attempt to fool the discriminator by maximizing its output information entropy. Thus, maximizing information entropy gradually reduces the distribution discrepancy of cross-modal features, thereby achieving a domain confusion state where the discriminator cannot classify two modalities confidently. To reduce the semantic gap, Kullback-Leibler (KL) divergence and bi-directional triplet loss are used to associate the intra- and inter-modality similarity between features in the shared space. Furthermore, a regularization term based on KL-divergence with temperature scaling is used to calibrate the biased label classifier caused by the data imbalance issue. Extensive experiments with four deep models on four benchmarks are conducted to demonstrate the effectiveness of the proposed approach.Comment: Accepted by Pattern Recognitio

Microarray evidence for off target effects in tick RNA interference experiments, and the lack of strong correlation between DSRNA and antibody phenotypes in tick In vitro treatments for vaccine candidate screening

No abstract availabl

Whitehead's varnish nasal pack

Whitehead's varnish is a little known but excellent nasal packing agent. We review available literature on the historical aspects and clinical use of Whitehead's varnish. Our personal experience with Whitehead's varnish is described, and we strongly recommend its use

Spin orbit torque induced asymmetric depinning of chiral Néel domain wall in Co/Ni heterostructures

In this letter, we report on distinct depinning of a chiral Néel domain wall (DW) driven by spin-orbit torque (SOT) in Co/Ni nanowires with symmetric potential barriers. In these structures, DW propagation was shown to be in the opposite direction to the electron flow as evidenced from current assisted DW depinning measurements. A transition from field dominated DW depinning to SOT dominated DW depinning was observed as the bias current was increased. For SOT dominated DW depinning, the Up-Down DW exhibits a larger depinning field as compared to the Down-Up DW. This is attributed to the interplay between the SOT and Dzyaloshinskii-Moriya interaction in the structure

ТРАНСФОРМАЦІЯ НАПРЯМІВ ВЗАЄМОДІЇ ПОДАТКОВИХ ОРГАНІВ ТА ПІДПРИЄМСТВ У ПРОЦЕСІ РЕАЛІЗАЦІЇ ПОДАТКОВОГО КОНТРОЛЮ

The focus of tax reforms in Ukraine, the development of partnerships between payers and supervisors requires new approaches to tax control. The current state of the functioning of the tax control system in Ukraine shows the necessity and at the same time its unpreparedness to transition to more advanced forms, including horizontal monitoring. The purpose of the article is to substantiate the need for effective interaction between taxpayers and controlling bodies in the context of improving the quality of tax control. The methodological basis of the study, in particular the theoretical positions, is the methods of scientific abstraction, induction, deduction, logical method, etc. For analytical research mathematical methods were used, in particular correlation-regression analysis, methods of comparison and grouping, synthesis, tabular and graphical methods. As a result of the research, it was found that the main factors hindering the implementation of horizontal monitoring in Ukraine are the lack of compliance with the legislative framework, the insecurity of the confidentiality of information on the activities of taxpayers, corruption in the DFS, large amounts of shadow economy in the country, etc. At the same time, the high level of inconsistency of the assessed tax liabilities and a considerable number of disputes as a result of this also confirm the low level of trust and cooperation between the DFS authorities and the payers. The analysis of the state of tax audits and the dynamics of tax debt — the calculation of correlation relationships between these indicators (R2 = -0,92) and the forecast of tax debt — showed that preventive tax control measures do not discipline payers to pay them tax arrears, the conducted tax inspections have a positive effect on the repayment of the tax debt by the payers. Such research results indicate that there are problems in establishing trusting relationships between payers and supervisors and the need to find ways to adjust them in the context of the development of progressive forms of tax control.Спрямованість податкових реформ в Україні, розвиток партнерських взаємовідносин між платниками та органами контролю вимагає нових підходів до проведення податкового контролю. Сучасний стан функціонування системи податкового контролю в Україні свідчить про необхідність та одночасно неготовність її до переходу на нові прогресивніші форми, зокрема горизонтальний моніторинг. Метою статті є обґрунтування необхідності налагодження ефективної взаємодії платників та органів контролю в контексті підвищення якості податкового контролю. Методологічною базою дослідження, зокрема теоретичних положень, є методи наукової абстракції, індукції, дедукції, логічний метод тощо. Для аналітичного дослідження використано математичні методи, зокрема кореляційно-регресійний аналіз, методи порівняння та групування, синтезу, табличний і графічний методи. У результаті дослідження з’ясовано, що основними чинниками, які перешкоджають запровадженню горизонтального моніторингу в Україні, є невідповідність законодавчої бази, незахищеність конфіденційності інформації про діяльність платників податків, корупція в органах ДФС, великі обсяги тіньової економіки в країні тощо. Поряд з цим високий рівень неузгодженості донарахованих податкових зобов’язань і значна кількість спорів унаслідок цього також підтверджують низький рівень довіри та співпраці між органами ДФС і платниками. Проведений аналіз стану податкових перевірок та динаміки податкового боргу — розрахунок кореляційних взаємозв’язків між цими показниками (R2 = -0,92) і прогноз податкового боргу — показав, що превентивні заходи податкового контролю не дисциплінують платників щодо погашення ними податкової заборгованості, натомість кількість фактично проведених податкових перевірок позитивно впливають на погашення податкового боргу платниками. Такі результати дослідження свідчать про наявність проблем у налагодженні довірливих взаємин між платниками та органами контролю і необхідність пошуку шляхів їх налагодження в контексті розвитку прогресивних форм податкового контролю

Lifelong Person Re-Identification via Adaptive Knowledge Accumulation

Person ReID methods always learn through a stationary domain that is fixed by the choice of a given dataset. In many contexts (e.g., lifelong learning), those methods are ineffective because the domain is continually changing in which case incremental learning over multiple domains is required potentially. In this work we explore a new and challenging ReID task, namely lifelong person re-identification (LReID), which enables to learn continuously across multiple domains and even generalise on new and unseen domains. Following the cognitive processes in the human brain, we design an Adaptive Knowledge Accumulation (AKA) framework that is endowed with two crucial abilities: knowledge representation and knowledge operation. Our method alleviates catastrophic forgetting on seen domains and demonstrates the ability to generalize to unseen domains. Correspondingly, we also provide a new and large-scale benchmark for LReID. Extensive experiments demonstrate our method outperforms other competitors by a margin of 5.8% mAP in generalising evaluation.Comment: 10 pages, 5 figures, Accepted by CVPR202

Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification

Visible-infrared person re-identification (VI-ReID) is a challenging and essential task in night-time intelligent surveillance systems. Except for the intra-modality variance that RGB-RGB person re-identification mainly overcomes, VI-ReID suffers from additional inter-modality variance caused by the inherent heterogeneous gap. To solve the problem, we present a carefully designed dual Gaussian-based variational auto-encoder (DG-VAE), which disentangles an identity-discriminable and an identity-ambiguous cross-modality feature subspace, following a mixture-of-Gaussians (MoG) prior and a standard Gaussian distribution prior, respectively. Disentangling cross-modality identity-discriminable features leads to more robust retrieval for VI-ReID. To achieve efficient optimization like conventional VAE, we theoretically derive two variational inference terms for the MoG prior under the supervised setting, which not only restricts the identity-discriminable subspace so that the model explicitly handles the cross-modality intra-identity variance, but also enables the MoG distribution to avoid posterior collapse. Furthermore, we propose a triplet swap reconstruction (TSR) strategy to promote the above disentangling process. Extensive experiments demonstrate that our method outperforms state-of-the-art methods on two VI-ReID datasets.Comment: Accepted by ACM MM 2020 poster. 12 pages, 10 appendixe