AAV11 permits efficient retrograde targeting of projection neurons

Viral tracers that permit efficient retrograde targeting of projection neurons are powerful vehicles for structural and functional dissections of the neural circuit and for the treatment of brain diseases. Recombinant adeno-associated viruses (rAAVs) are the most potential candidates because they are low-toxic with high-level transgene expression and minimal host immune responses. Currently, some rAAVs based on capsid engineering for retrograde tracing have been widely used in the analysis and manipulation of neural circuits, but suffer from brain area selectivity and inefficient retrograde transduction in certain neural connections. Here, we discovered that the recombinant adeno-associated virus 11 (rAAV11) exhibits potent retrograde labeling of projection neurons with enhanced efficiency to rAAV2-retro in some neural connections. Combined with calcium recording technology, rAAV11 can be used to monitor neuronal activities by expressing Cre recombinase or calcium-sensitive functional probe. In addition, we further showed the suitability of rAAV11 for astrocyte targeting. These properties make rAAV11 a promising tool for the mapping and manipulation of neural circuits and gene therapy of some neurological and neurodegenerative disorders.

Selbstpräsenz auf Tonband (András Ferenc Kovács: Öninterjú)

This paper investigates an early poem of a contemporary Hungarian (Transylvanian) poet András Kovács Ferenc. The poem outlines a poetic framework for the gesture of self-address, turned into a situation where the lyrical voice is interrupted by recording technology. The reading offered here tries to connect the lyrical proposition with the philosophical problem of self-presence. It further discusses political references in the poem that relate to the revolutionary events that took place in Romania in 1989.

Unobtrusive Pedestrian Identification by Leveraging Footstep Sounds with Replay Resistance

The ability to identify pedestrians unobtrusively is essential for smart buildings to provide customized environments, energy saving, health monitoring and security-enhanced services. In this paper, we present an unobtrusive pedestrian identification system by passively listening to people's walking sounds. The proposed acoustic system can be easily integrated with the widely deployed voice assistant devices while providing the context awareness ability. This work focuses on two major tasks. Firstly, we address the challenge of recognizing footstep sounds in complex indoor scenarios by exploiting deep learning and the advanced stereo recording technology that is available on most voice assistant devices. We develop a Convolutional Neural Network-based algorithm and the footstep sound-oriented signal processing schemes to identify users by their footstep sounds accurately. Secondly, we design a "live" footstep detection approach to defend against replay attacks. By deriving the novel inter-footstep and intra-footstep characteristics, we distinguish live footstep sounds from the machine speaker's replay sounds based on their spatial variances. The system is evaluated under normal scenarios, traditional replay attacks and the advanced replays, which are designed to forge footstep sounds both acoustically and spatially. Extensive experiments show that our system identifies people with up to 94.9% accuracy in one footstep and shields 100% traditional replay attacks and up to 99% advanced replay attacks.

Broadening the scope of error categories in translation assessment through screen recording

To date, the assessment of student translations has been largely based on configurations of error categories that address some facet of the translation product. Focal points of such product-oriented error annotation include language mechanics (punctuation, grammar, lexis and syntax, for example) and various kinds of transfer errors. In recent years, screen recording technology has opened new doors for empirically informing translation assessment from a more process-oriented perspective (Massey and Ehrensberger-Dow, 2014; Angelone, 2019). Screen recording holds particular promise when tracing errors documented in the product back to potential underlying triggers in the form of processes that co-occur on screen in their presence. Assessor observations made during screen recording analysis can give shape to process-oriented error categories that parallel and complement product-oriented categories. This paper proposes a series of empirically informed, process-oriented error categories that can be used for assessing translations in contexts where screen recordings are applied as a diagnostic tool. The categories are based on lexical and semantic patterns derived from a corpus-based analysis of think-aloud protocols documenting articulations made by assessors when commenting on errors made in student translations while watching screen recordings of their work. It is hoped that these process-oriented error categories will contribute to a more robust means by which to assess and classify errors in translation.

Glitching the Gendered Voice

Since recording technology first severed the human voice from its originating body, the uncanniness of the sourceless voice has coincided with theoreticizations of queerness. The concept of homosexuality and the proliferation of home phonographs emerged at around the same point in history, and both interventions confounded traditional imaginings of domesticity, intimacy, and communion. As playback technology has grown more responsive and complex, so have defections from normative gender and heterosexuality. Electronic voice processing furthers the confusion of source presented by playback, making electronic music an especially rich field of expression for queer and transgender musicians in particular. This chapter traces the technologically mutated voice through the past century of recording, focusing on its relationship to unruly expressions of gender from electronic music’s origins to its present iterations. Though not only queer artists have participated in this evolutionary process, this chapter highlights the ways trans musicians in particular have used glitch and distortion to rupture the habit of listening for normative gender, sounding new ways of moving and being in their wake.

Piano Performance and Music Automatic Notation Algorithm Teaching System Based on Artificial Intelligence

Artificial intelligence is a subject that studies all kinds of human intelligent activities and their laws. It is developed on the basis of the cohesion of many disciplines such as computer science, politics, information system, neurophysiology, psychology, philosophy, and language. This paper aims to study how to build a computer or intelligent machine, including hardware and software, imitate and expand the human brain to perform thinking functions such as thinking, programming, arithmetic, and learning, solve complex problems that need to be handled by professionals, and better apply the artificial intelligence assistance system to the teaching of piano performance. In this paper, Prolog language and music-assisted learning system based on the ARM and SA algorithm are proposed, the principle and operation process of music automatic recording technology are deeply studied, and the system data of artificial intelligence are summarized and analyzed by using internal database, so as to find out the implementation principle and law of piano automatic recording system. So that the artificial intelligence assistant system can be better applied to music teaching. The experimental results show that, in the teaching system of piano performance and music automatic notation algorithm, the utilization rate of artificial intelligence auxiliary technology has reached 56.81 and is growing rapidly. Therefore, we can find that the artificial intelligence assistant system plays an important role in the teaching system of piano performance and automatic music notation.

Music and Memory in the Ancient Greek and Roman Worlds

In Greek mythology, the Muses are Memory's daughters. Their genealogy suggests a deep connection between music and memory in Graeco-Roman culture, but how was this connection understood and experienced by ancient authors, artists, performers, and audiences? How is music remembered and how does it memorialize in a world before recording technology, where sound accumulated differently than it does today? This volume explores music's role in the discourses of cultural memory, communication, and commemoration in ancient Greek and Roman societies. It reveals the many and varied ways in which musical memory formed a fundamental part of social, cultural, ritual, and political life in ancient Greek- and Latin-speaking communities, from classical Athens to Ptolemaic Alexandria and ancient Rome. Drawing on the contributors' interdisciplinary expertise in art history, philology, performance studies, history, and ethnomusicology, eleven original chapters and the editors' Introduction offer new approaches for the study of Graeco-Roman music and musical culture.

Bitmap and vectorial hologram recording by using femtosecond laser pulses

In this paper, we present two approaches for recording a quasi-hologram on the steel surface by femtosecond laser pulses. The recording process is done by rotating the polarization of the laser beam by a half-wave plate or a spatial light modulator (SLM), so we can control the spatial orientation of the formed laser-induced periodic surface structures (LIPSS). Two different approaches are shown, which use vector and bitmap images to record the hologram. For the first time to our knowledge, we managed to record a hologram of a bitmap image by continuously adjusting the laser beam polarization by SLM during scanning. The developed method can substantially improve hologram recording technology by eliminating complex processing procedures, which can lead to increasing the fabrication speed and reducing the cost.