Miracle-dz/UniFAR-FTUs huggingface dataset:
Kallikrein 13 serves as a priming protease during infection by the human coronavirus HKU1

The protease kallikrein 13 cleaves the spike protein of the human coronavirus HKU1 to facilitate viral entry. Priming viral entry Unlike SARS-CoV-2, the human coronavirus HKU1 normally causes relatively mild respiratory tract infections; however, it shares with SARS-CoV-2 the mechanism of using its surface spike (S) protein to enter target cells. Because the host receptor for HCoV-HKU1 is unknown, efforts to study the virus in cell culture systems have proved difficult. Milewska et al. found that knockout of the protease kallikrein 13 (KLK13) in human airway epithelial cells blocked their infection by HCoV-HKU1, that overexpression of KLK13 in nonpermissive cells enabled their infection by the virus, and that KLK13 cleaved the viral S protein. Together, these findings suggest that KLK13 is a priming enzyme for viral entry and may help to establish cell lines that can facilitate further investigation of the mechanism of viral pathogenesis. Human coronavirus HKU1 (HCoV-HKU1) is associated with respiratory disease and is prevalent worldwide, but an in vitro model for viral replication is lacking. An interaction between the coronaviral spike (S) protein and its receptor is the primary determinant of tissue and host specificity; however, viral entry is a complex process requiring the concerted action of multiple cellular elements. Here, we found that the protease kallikrein 13 (KLK13) was required for the infection of human respiratory epithelial cells and was sufficient to mediate the entry of HCoV-HKU1 into nonpermissive RD cells. We also demonstrated the cleavage of the HCoV-HKU1 S protein by KLK13 in the S1/S2 region, suggesting that KLK13 is the priming enzyme for this virus. Together, these data suggest that protease distribution and specificity determine the tissue and cell specificity of the virus and may also regulate interspecies transmission.
Representations of common event structure in medial temporal lobe and frontoparietal cortex support efficient inference

Prior work has shown that the brain represents memories within a cognitive map that supports inference about connections between individual related events. Real-world adaptive behavior is also supported by recognizing common structure among numerous distinct contexts; for example, based on prior experience with restaurants, when visiting a new restaurant one can expect to first get a table, then order, eat, and finally pay the bill. We used a neurocomputational approach to examine how the brain extracts and uses abstract representations of common structure to support novel decisions. Participants learned image pairs (AB, BC) drawn from distinct triads (ABC) that shared the same internal structure and were then tested on their ability to infer indirect (AC) associations. We found that hippocampal and frontoparietal regions formed abstract representations that coded cross-triad relationships with a common geometric structure. Critically, such common representational geometries were formed despite the lack of explicit reinforcement to do so. Furthermore, we found that representations in parahippocampal cortex are hierarchical, reflecting both cross-triad relationships and distinctions between triads. We propose that representations with common geometric structure provide a vector space that codes inferred item relationships with a direction vector that is consistent across triads, thus supporting faster inference. Using computational modeling of response time data, we found evidence for dissociable vector-based retrieval and pattern-completion processes that contribute to successful inference. Moreover, we found evidence that these processes are mediated by distinct regions, with pattern completion supported by hippocampus and vector-based retrieval supported by parahippocampal cortex and lateral parietal cortex.
Editors’ Introduction

Virtually all the professional mental health providers in China are hospital-based. Care for the mentally ill is also provided by family members, by folk healers in the community, and in the large urban centres by a small number of community-based mental health services, but for most Chinese people psychiatric care means hospital care. As discussed in our paper in section I of this supplement, the current changes in the financing of health care in China are likely to perpetuate this concentration of mental health resources and personnel in the hospital sector. This is, of course, a situation that is common in Asia and in most of the non-Western world. Nagaswami (1993) claims that much severe mental disorder in Asia (and this would also apply to China) goes untreated, and what treatment there is tends to take place in hospitals, for lack of any other facility. In a description of mental health services in Japan that is also relevant for China, Lin et al (1991) point out that in Japan mental hospitals were, and probably still are, the only mental health facilities where a concentration of trained mental health personnel are available. This focus on hospital-based care has important implications for the evolution of psychiatric rehabilitation in non-Western countries. The cadre of professionally trained rehabilitation experts who provide services and train non-professional care-givers will, necessarily, come from psychiatric hospitals. The first steps in the development of rehabilitation services are, therefore, to convince these hospital-based biomedical practitioners of the importance of the psychosocial aspects of care, to expose them to the Western theory and practice of rehabilitation, and to encourage them to experiment with rehabilitative approaches that will, eventually, lead to culture-specific theories and methods for the provision of psychiatric rehabilitation in their own communities. Given the reluctance of professionals to leave the security of the hospital, most experiments in rehabilitative care will be based in hospitals, and community-based experiments will involve the training of nonprofessionals in the community by hospital-based professionals. For example, with the unique exception of the paper by X. Wang, all the
Anticonvulsants and Chromatin-Genes Expression: A Systems Biology Investigation

Embryofetal development is a critical process that needs a strict epigenetic control, however, perturbations in this balance might lead to the occurrence of congenital anomalies. It is known that anticonvulsants potentially affect epigenetics-related genes, however, it is not comprehended whether this unbalance could explain the anticonvulsants-induced fetal syndromes. In the present study, we aimed to evaluate the expression of epigenetics-related genes in valproic acid, carbamazepine, or phenytoin exposure. We selected these three anticonvulsants exposure assays, which used murine or human embryonic stem-cells and were publicly available in genomic databases. We performed a differential gene expression (DGE) and weighted gene co-expression network analysis (WGCNA), focusing on epigenetics-related genes. Few epigenetics genes were differentially expressed in the anticonvulsants’ exposure, however, the WGCNA strategy demonstrated a high enrichment of chromatin remodeling genes for the three drugs. We also identified an association of 46 genes related to Fetal Valproate Syndrome, containing SMARCA2 and SMARCA4, and nine genes to Fetal Hydantoin Syndrome, including PAX6, NEUROD1, and TSHZ1. The evaluation of stem-cells under drug exposure can bring many insights to understand the drug-induced damage to the embryofetal development. The candidate genes here presented are potential biomarkers that could help in future strategies for the prevention of congenital anomalies.
Effects of Noise Exposure on the Vestibular System: A Systematic Review

Despite our understanding of the impact of noise-induced damage to the auditory system, much less is known about the impact of noise exposure on the vestibular system. In this article, we review the anatomical, physiological, and functional evidence for noise-induced damage to peripheral and central vestibular structures. Morphological studies in several animal models have demonstrated cellular damage throughout the peripheral vestibular system and particularly in the otolith organs; however, there is a paucity of data on the effect of noise exposure on human vestibular end organs. Physiological studies have corroborated morphological studies by demonstrating disruption across vestibular pathways with otolith-mediated pathways impacted more than semicircular canal-mediated pathways. Similar to the temporary threshold shifts observed in the auditory system, physiological studies in animals have suggested a capacity for recovery following noise-induced vestibular damage. Human studies have demonstrated that diminished sacculo-collic responses are related to the severity of noise-induced hearing loss, and dose-dependent vestibular deficits following noise exposure have been corroborated in animal models. Further work is needed to better understand the physiological and functional consequences of noise-induced vestibular impairment in animals and humans.
Emerging Autophagy Functions Shape the Tumor Microenvironment and Play a Role in Cancer Progression - Implications for Cancer Therapy

The tumor microenvironment (TME) is a complex environment where cancer cells reside and interact with different types of cells, secreted factors, and the extracellular matrix. Additionally, TME is shaped by several processes, such as autophagy. Autophagy has emerged as a conserved intracellular degradation pathway for clearance of damaged organelles or aberrant proteins. With its central role, autophagy maintains the cellular homeostasis and orchestrates stress responses, playing opposite roles in tumorigenesis. During tumor development, autophagy also mediates autophagy-independent functions associated with several hallmarks of cancer, and therefore exerting several effects on tumor suppression and/or tumor promotion mechanisms. Beyond the concept of degradation, new different forms of autophagy have been described as modulators of cancer progression, such as secretory autophagy enabling intercellular communication in the TME by cargo release. In this context, the synthesis of senescence-associated secretory proteins by autophagy lead to a senescent phenotype. Besides disturbing tumor treatment responses, autophagy also participates in innate and adaptive immune signaling. Furthermore, recent studies have indicated intricate crosstalk between autophagy and the epithelial-mesenchymal transition (EMT), by which cancer cells obtain an invasive phenotype and metastatic potential. Thus, autophagy in the cancer context is far broader and complex than just a cell energy sensing mechanism. In this scenario, we will discuss the key roles of autophagy in the TME and surrounding cells, contributing to cancer development and progression/EMT. Finally, the potential intervention in autophagy processes as a strategy for cancer therapy will be addressed.
EarphoneTrack: involving earphones into the ecosystem of acoustic motion tracking

Acoustic motion tracking is an exciting new research area with promising progress in the last few years. Due to the inherent low propagation speed in the air, acoustic signals have the unique advantage of fine sensing granularity compared to RF signals. Speakers and microphones nowadays are pervasively available in devices surrounding us, such as smartphones and voice-controlled smart speakers. Though promising, one fundamental issue hindering the adoption of acoustic-based motion tracking is that the positions of microphones and speakers inside a device are fixed, which greatly limits the flexibility of acoustic motion tracking. In this work, we propose a new modality of acoustic motion tracking using earphones. Earphone-based tracking mitigates the constraints associated with traditional smartphone-based tracking. With novel designs and comprehensive experiments, we show earphone-based motion tracking can achieve a great flexibility and a high accuracy at the same time. We believe this is an important step towards "earable" sensing.
RF-net: a unified meta-learning framework for RF-enabled one-shot human activity recognition

Radio-Frequency (RF) based device-free Human Activity Recognition (HAR) rises as a promising solution for many applications. However, device-free (or contactless) sensing is often more sensitive to environment changes than device-based (or wearable) sensing. Also, RF datasets strictly require on-line labeling during collection, starkly different from image and text data collections where human interpretations can be leveraged to perform off-line labeling. Therefore, existing solutions to RF-HAR entail a laborious data collection process for adapting to new environments. To this end, we propose RF-Net as a meta-learning based approach to one-shot RF-HAR; it reduces the labeling efforts for environment adaptation to the minimum level. In particular, we first examine three representative RF sensing techniques and two major meta-learning approaches. The results motivate us to innovate in two designs: i) a dual-path base HAR network, where both time and frequency domains are dedicated to learning powerful RF features including spatial and attention-based temporal ones, and ii) a metric-based meta-learning framework to enhance the fast adaption capability of the base network, including an RF-specific metric module along with a residual classification module. We conduct extensive experiments based on all three RF sensing techniques in multiple real-world indoor environments; all results strongly demonstrate the efficacy of RF-Net compared with state-of-the-art baselines.
The ABCs of petri net reachability relaxations

Petri nets form a widespread model of concurrency well suited for the verification of systems with infinitely many configurations. Deciding configuration reachability in Petri nets, which plays a central role in their formal analysis, suffers from a nonelementary time complexity lower bound. We survey relaxations that alleviate this tremendous complexity, both for classical Petri nets and for extensions with affine transformations, branching rules and colored tokens.
Numeric domains meet algebraic data types

We report on the design and formalization of a novel abstract domain, called numeric path relations (NPRs), that combines numeric relational domains with algebraic data types. This domain expresses relations between algebraic values that can contain scalar data. The construction of the domain is parameterized by the choice of a relational domain on scalar values. The construction employs projection paths on algebraic values, and in particular projections on variant cases, whose sound treatment is subtle due to mutual exclusiveness.
MPCC: online learning multipath transport

Multipath transport, as embodied in MPTCP, is deployed to improve throughput and reliability in mobile and residential access networks, with additional use-cases including spreading load in data centers and WANs. However, MPTCP is fundamentally tied to TCP Reno's legacy AIMD algorithm, and significantly lags behind the performance of modern single-path designs. Consequently, MPTCP fails to achieve high performance in many real-world environments. We present MPCC, a high-performance multipath congestion control architecture. To achieve our combined goals of fairness and high performance in challenging environments, MPCC employs online convex optimization (a.k.a. online learning). In experiments with a kernel implementation on emulated and live networks, MPCC significantly outperforms MPTCP.
Side-channel information leaks of Z-wave smart home IoT devices: demo abstract

Z-Wave is one of the key access protocols of the Internet of Things (IoT). It is highly popular in home automation and security system applications due to its minimum power consumption, reliability, and cost effectiveness. With an estimate of over 100 million deployed Z-Wave devices around the globe, it is essential to understand their security landscape. For instance, Z-Wave devices can leak personal information about the home dwellers as well as their possessions and buglers can use compromised Z-Wave devices to disable security systems or even to feed incorrect information. In this paper, we present an experiment setup and early results of side-channel information leaks of Z-Wave. We show that Z-Wave traffic despite being encrypted, leaks information through side-channels and an attacker who can passively capture Z-Wave frames by simply being in the vicinity of a house can identify Z-Wave devices inside the house.
LiTag: localization and posture estimation with passive visible light tags

The development of Internet of Things calls for ubiquitous and low-cost localization and posture estimation. We present LiTag, a visible light based localization and posture estimation solution with COTS cameras. The core of LiTag is based on the design of a chip-less and battery-less optical tag which can show different color patterns from different observation directions. After capturing a photo containing the tag, LiTag can calculate the tag position and posture by combining the color pattern and the geometry relation between the camera image plane and the real world. Unlike existing marker-based visible localization and posture estimation approaches, LiTag can work with a single camera without calibration, which significantly reduces the calibration overhead and deployment costs. We implement LiTag and evaluate its performance extensively. Results show that LiTag can provide the tag position with a median error of 1.6 cm in the 2D plane, a median error of 12 cm in the 3D space, and posture estimation with a median error of 1°. We believe that LiTag has a high potential to provide a low-cost and easy-to-use solution for ubiquitous localization and posture estimation with existing widely deployed cameras.
Phase Coupled Firing of Prefrontal Parvalbumin Interneuron With High Frequency Oscillations

The prefrontal cortex (PFC) plays a central role in executive functions and inhibitory control over many cognitive behaviors. Dynamic changes in local field potentials (LFPs), such as gamma oscillation, have been hypothesized to be important for attentive behaviors and modulated by local interneurons such as parvalbumin (PV) cells. However, the precise relationships between the firing patterns of PV interneurons and temporal dynamics of PFC activities remains elusive. In this study, by combining in vivo electrophysiological recordings with optogenetics, we investigated the activities of prefrontal PV interneurons and categorized them into three subtypes based on their distinct firing rates under different behavioral states. Interestingly, all the three subtypes of interneurons showed strong phase-locked firing to cortical high frequency oscillations (HFOs), but not to theta or gamma oscillations, despite of behavior states. Moreover, we showed that sustained optogenetic stimulation (over a period of 10 s) of PV interneurons can consequently modulate the activities of local pyramidal neurons. Interestingly, such optogenetic manipulations only showed moderate effects on LFPs in the PFC. We conclude that prefrontal PV interneurons are consist of several subclasses of cells with distinct state-dependent modulation of firing rates, selectively coupled to HFOs.
Influence of Moral Education on Students’ Moral Values and Responsibility of Financial Information Disclosure

In the current complex economic environment, the phenomenon of financial fraud is endless. As accounting students play an important role in the future capital market, we aimed to focus on moral education, and analyze its influence on cultivating students' moral values and their strong responsibility of financial information disclosure. Therefore, our study recruited college students of Zhaoqing University, and delivered moral education. Finally, regression analysis was conducted on the collected questionnaire data. This paper intends to verify the relationship among the moral education, the establishment of moral values and the responsibility for financial information disclosure. We result show that moral education curriculum can positively influence students' moral values, and strong moral values can enhance students' sense of responsibility for financial information disclosure.
Battery-less zero-maintenance embedded sensing at the mithræum of circus maximus

We present the design and evaluation of a 3.5-year embedded sensing deployment at the Mithræum of Circus Maximus, a UNESCO-protected underground archaeological site in Rome (Italy). Unique to our work is the use of energy harvesting through thermal and kinetic energy sources. The extreme scarcity and erratic availability of energy, however, pose great challenges in system software, embedded hardware, and energy management. We tackle them by testing, for the first time in a multi-year deployment, existing solutions in intermittent computing, low-power hardware, and energy harvesting. Through three major design iterations, we find that these solutions operate as isolated silos and lack integration into a complete system, performing suboptimally. In contrast, we demonstrate the efficient performance of a hardware/software co-design featuring accurate energy management and capturing the coupling between energy sources and sensed quantities. Installing a battery-operated system alongside also allows us to perform a comparative study of energy harvesting in a demanding setting. Albeit the latter reduces energy availability and thus lowers the data yield to about 22% of that provided by batteries, our system provides a comparable level of insight into environmental conditions and structural health of the site. Further, unlike existing energy-harvesting deployments that are limited to a few months of operation in the best cases, our system runs with zero maintenance since almost 2 years, including 3 months of site inaccessibility due to a COVID19 lockdown.
Performance penalties of resilient SDN infrastructures

Secure software and hardware are critical to the functionality and stability of the Internet as well as to its clients and services. Unfortunately, benign vulnerabilities and maliciously infiltrated backdoors can often not be identified in advance, which eliminates the possibility to mitigate them. When security assurances are not known, robust combiners can be applied to ensure resilience of networks and systems. In this work we present resilient constructions based on robust combiners for network devices in Software Defined Networking, and perform extensive evaluations to show the impact of robust combiners on the efficiency of network devices. Our results demonstrate that combining devices and software provides a reasonable performance for practical systems and is a promising approach for ensuring resilience when using potentially faulty or malicious components.