Miracle-dz/UniFAR-FTUs huggingface dataset:
A first estimate of the Milky Way dark matter halo spin

The spin, $\lambda$, of dark matter (DM) halos in cosmological simulations follows a log normal distribution and has little correlation with galaxy observables. As such, there is currently no way to infer the $\lambda$ parameter of individual halos hosting observed galaxies. We present here a first attempt to measure $\lambda$ starting from the dynamically distinct stellar components identified in high-resolution cosmological simulations with Galactic Structure Finder. In a subsample of NIHAO galaxies, we find tight correlations between the total angular momentum (AM) of the DM halos, $J_h$, and the azimuthal AM, $J_z$, of the stellar components of the form: log($J_h$)=$\alpha$+$\beta\cdot$log($J_z$). The stellar halos have the tightest relation with $\alpha=9.50\pm0.42$ and $\beta=0.46\pm0.04$. The other tight relation is with the disks: $\alpha=6.15\pm0.92$ and $\beta=0.68\pm0.07$. We used Gaia DR2 and APOGEE to generate a combined kinematics-abundance space, where the Galaxy's thin and thick stellar disks stars can be neatly separated and their rotational velocity profiles, $v_{\phi}(R)$, can be computed. For both disks, $v_{\phi}(R)$ decreases with radius with $\sim$2 km s$^{-1}$ kpc$^{-1}$ for $R\gtrsim5$ kpc, resulting in $v_{\phi,thin}\backsimeq221$ km s$^{-1}$ and $v_{\phi,thick}\backsimeq188$ km s$^{-1}$ at $R_{\odot}$. These velocity profiles together with the Galaxy mass model of Cautun et al. (2020) result in the AM for the two disks: $J_{z,thin}=(3.26\pm0.43)\times10^{13}$ and $J_{z,thick}=(1.20\pm0.30)\times10^{13}$ M$_{\odot}$ kpc km s$^{-1}$, where the DM halo is assumed to have a contracted NFW profile. Adopting the correlation found in simulations, the spin estimate of the Galaxy's DM halo is $\lambda_{MW}=0.061^{+0.022}_{-0.016}$. If the DM halo has a NFW profile instead, the spin becomes $\lambda_{MW}=0.088^{+0.024}_{-0.020}$, making the Galaxy a more extreme outlier.
Cortico-cerebellar networks as decoupling neural interfaces

The brain solves the credit assignment problem remarkably well. For credit to be assigned across neural networks they must, in principle, wait for specific neural computations to finish. How the brain deals with this inherent locking problem has remained unclear. Deep learning methods suffer from similar locking constraints both on the forward and feedback phase. Recently, decoupled neural interfaces (DNIs) were introduced as a solution to the forward and feedback locking problems in deep networks. Here we propose that a specialised brain region, the cerebellum, helps the cerebral cortex solve similar locking problems akin to DNIs. To demonstrate the potential of this framework we introduce a systems-level model in which a recurrent cortical network receives online temporal feedback predictions from a cerebellar module. We test this cortico-cerebellar recurrent neural network (ccRNN) model on a number of sensorimotor (line and digit drawing) and cognitive tasks (pattern recognition and caption generation) that have been shown to be cerebellar-dependent. In all tasks, we observe that ccRNNs facilitates learning while reducing ataxia-like behaviours, consistent with classical experimental observations. Moreover, our model also explains recent behavioural and neuronal observations while making several testable predictions across multiple levels. Overall, our work offers a novel perspective on the cerebellum as a brain-wide decoupling machine for efficient credit assignment and opens a new avenue between deep learning and neuroscience.
MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding

To reduce a model size but retain performance, we often rely on knowledge distillation (KD) which transfers knowledge from a large"teacher"model to a smaller"student"model. However, KD on multimodal datasets such as vision-language tasks is relatively unexplored, and digesting multimodal information is challenging since different modalities present different types of information. In this paper, we perform a large-scale empirical study to investigate the importance and effects of each modality in knowledge distillation. Furthermore, we introduce a multimodal knowledge distillation framework, modality-specific distillation (MSD), to transfer knowledge from a teacher on multimodal tasks by learning the teacher's behavior within each modality. The idea aims at mimicking a teacher's modality-specific predictions by introducing auxiliary loss terms for each modality. Furthermore, because each modality has different saliency for predictions, we define saliency scores for each modality and investigate saliency-based weighting schemes for the auxiliary losses. We further study a weight learning approach to learn the optimal weights on these loss terms. In our empirical analysis, we examine the saliency of each modality in KD, demonstrate the effectiveness of the weighting scheme in MSD, and show that it achieves better performance than KD on four multimodal datasets.
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning

Contrastive learning (CL) has recently emerged as an effective approach to learning representation in a range of downstream tasks. Central to this approach is the selection of positive (similar) and negative (dissimilar) sets to provide the model the opportunity to `contrast' between data and class representation in the latent space. In this paper, we investigate CL for improving model robustness using adversarial samples. We first designed and performed a comprehensive study to understand how adversarial vulnerability behaves in the latent space. Based on this empirical evidence, we propose an effective and efficient supervised contrastive learning to achieve model robustness against adversarial attacks. Moreover, we propose a new sample selection strategy that optimizes the positive/negative sets by removing redundancy and improving correlation with the anchor. Extensive experiments show that our Adversarial Supervised Contrastive Learning (ASCL) approach achieves comparable performance with the state-of-the-art defenses while significantly outperforms other CL-based defense methods by using only $42.8\%$ positives and $6.3\%$ negatives.
Estimates of the social cost of carbon have increased over time

A meta-analysis of published estimates shows that the social cost of carbon has increased as knowledge about climate change accumulates. Correcting for inflation and emission year and controlling for the discount rate, kernel density decomposition reveals a non-stationary distribution. In the last 10 years, estimates of the social cost of carbon have increased from $33/tC to $146/tC for a high discount rate and from $446/tC to $1925/tC for a low discount rate. Actual carbon prices are almost everywhere below its estimated value and should therefore go up. Significance statement Greenhouse gas emissions should be taxed at the social cost of carbon. Many estimates have been published, ranging from -$1,000/tC to +$110,000,000/tC. I use kernel density estimation to reflect the large and asymmetric uncertainty, and kernel decomposition to test for changes over time. Correcting for inflation and emission year, and controlling for the discount rate, I show that estimates of the social cost of carbon have increased over time—estimates have more than quadrupled over the last 10 years. This justifies a tightening of climate policy. 1 ar X iv :2 10 5. 03 65 6v 3 [ ec on . G N ] 3 A ug 2 02 2
Alveolar-like Macrophages Attenuate Respiratory Syncytial Virus Infection

Respiratory Syncytial Virus (RSV) is the leading cause of acute lower respiratory infections in young children and infection has been linked to the development of persistent lung disease in the form of wheezing and asthma. Despite substantial research efforts, there are no RSV vaccines currently available and an effective monoclonal antibody targeting the RSV fusion protein (palivizumab) is of limited general use given the associated expense. Therefore, the development of novel approaches to prevent RSV infection is highly desirable to improve pediatric health globally. We have developed a method to generate alveolar-like macrophages (ALMs) from pluripotent stem cells. These ALMs have shown potential to promote airway innate immunity and tissue repair and so we hypothesized that ALMs could be used as a strategy to prevent RSV infection. Here, we demonstrate that ALMs are not productively infected by RSV and prevent the infection of epithelial cells. Prevention of epithelial infection was mediated by two different mechanisms: phagocytosis of RSV particles and release of an antiviral soluble factor different from type I interferon. Furthermore, intratracheal administration of ALMs protected mice from subsequent virus-induced weight loss and decreased lung viral titres and inflammation, indicating that ALMs can impair the pathogenesis of RSV infection. Our results support a prophylactic role for ALMs in the setting of RSV infection and warrant further studies on stem cell-derived ALMs as a novel cell-based therapy for pulmonary viral infections.
Protocol-Based and Hybrid Access Control for the IoT: Approaches and Research Opportunities

Internet of Things (IoT) applications and services are becoming more prevalent in our everyday life. However, such an interconnected network of intelligent physical entities needs appropriate security to sensitive information. That said, the need for proper authentication and authorization is paramount. Access control is in the front line of such mechanisms. Access control determines the use of resources only to the specified and authorized users based on appropriate policy enforcement. IoT demands more sophisticated access control in terms of its usability and efficiency in protecting sensitive information. This conveys the need for access control to serve system-specific requirements and be flexibly combined with other access control approaches. In this paper, we discuss the potential for employing protocol-based and hybrid access control for IoT systems and examine how that can overcome the limitations of traditional access control mechanisms. We also focus on the key benefits and constraints of this integration. Our work further enhances the need to build hierarchical access control for large-scale IoT systems (e.g., Industrial IoT (IIoT) settings) with protocol-based and hybrid access control approaches. We, moreover, list the associated open issues to make such approaches efficient for access control in large-scale IoT systems.
Cell Entry of Animal Coronaviruses

Coronaviruses (CoVs) are a group of enveloped positive-sense RNA viruses and can cause deadly diseases in animals and humans. Cell entry is the first and essential step of successful virus infection and can be divided into two ongoing steps: cell binding and membrane fusion. Over the past two decades, stimulated by the global outbreak of SARS-CoV and pandemic of SARS-CoV-2, numerous efforts have been made in the CoV research. As a result, significant progress has been achieved in our understanding of the cell entry process. Here, we review the current knowledge of this essential process, including the viral and host components involved in cell binding and membrane fusion, molecular mechanisms of their interactions, and the sites of virus entry. We highlight the recent findings of host restriction factors that inhibit CoVs entry. This knowledge not only enhances our understanding of the cell entry process, pathogenesis, tissue tropism, host range, and interspecies-transmission of CoVs but also provides a theoretical basis to design effective preventive and therapeutic strategies to control CoVs infection.
A Four-Step Purification Process for Gag VLPs: From Culture Supernatant to High-Purity Lyophilized Particles

Gag-based virus-like particles (VLPs) have high potential as scaffolds for the development of chimeric vaccines and delivery strategies. The production of purified preparations that can be preserved independently from cold chains is highly desirable to facilitate distribution and access worldwide. In this work, a nimble purification has been developed, facilitating the production of Gag VLPs. Suspension-adapted HEK 293 cells cultured in chemically defined cell culture media were used to produce the VLPs. A four-step downstream process (DSP) consisting of membrane filtration, ion-exchange chromatography, polishing, and lyophilization was developed. The purification of VLPs from other contaminants such as host cell proteins (HCP), double-stranded DNA, or extracellular vesicles (EVs) was confirmed after their DSP. A concentration of 2.2 ± 0.8 × 109 VLPs/mL in the lyophilized samples was obtained after its storage at room temperature for two months. Morphology and structural integrity of purified VLPs was assessed by cryo-TEM and NTA. Likewise, the purification methodologies proposed here could be easily scaled up and applied to purify similar enveloped viruses and vesicles.
A T-Cell Epitope-Based Multi-Epitope Vaccine Designed Using Human HLA Specific T Cell Epitopes Induces a Near-Sterile Immunity against Experimental Visceral Leishmaniasis in Hamsters

Visceral leishmaniasis is a neglected tropical disease affecting 12 million people annually. Even in the second decade of the 21st century, it has remained without an effective vaccine for human use. In the current study, we designed three multiepitope vaccine candidates by the selection of multiple IFN-γ inducing MHC-I and MHC-II binder T-cell specific epitopes from three previously identified antigen genes of Leishmania donovani from our lab by an immuno-informatic approach using IFNepitope, the Immune Epitope Database (IEDB) T cell epitope identification tools, NET-MHC-1, and NET MHC-2 webservers. We tested the protective potential of these three multiepitope proteins as a vaccine in a hamster model of visceral leishmaniasis. The immunization data revealed that the vaccine candidates induced a very high level of Th1 biased protective immune response in-vivo in a hamster model of experimental visceral leishmaniasis, with one of the candidates inducing a near-sterile immunity. The vaccinated animals displayed highly activated monocyte macrophages with the capability of clearing intracellular parasites due to increased respiratory burst. Additionally, these proteins induced activation of polyfunctional T cells secreting INF-γ, TNF-α, and IL-2 in an ex-vivo stimulation of human peripheral blood mononuclear cells, further supporting the protective nature of the designed candidates.
Genomic Characterization of Diverse Bat Coronavirus HKU10 in Hipposideros Bats

Bats have been identified as natural reservoirs of a variety of coronaviruses. They harbor at least 19 of the 33 defined species of alpha- and betacoronaviruses. Previously, the bat coronavirus HKU10 was found in two bat species of different suborders, Rousettus leschenaultia and Hipposideros pomona, in south China. However, its geographic distribution and evolution history are not fully investigated. Here, we screened this viral species by a nested reverse transcriptase PCR in our archived samples collected over 10 years from 25 provinces of China and one province of Laos. From 8004 bat fecal samples, 26 were found to be positive for bat coronavirus HKU10 (BtCoV HKU10). New habitats of BtCoV HKU10 were found in the Yunnan, Guangxi, and Hainan Provinces of China, and Louang Namtha Province in Laos. In addition to H. pomona, BtCoV HKU10 variants were found circulating in Aselliscus stoliczkanus and Hipposideros larvatus. We sequenced full-length genomes of 17 newly discovered BtCoV HKU10 strains and compared them with previously published sequences. Our results revealed a much higher genetic diversity of BtCoV HKU10, particularly in spike genes and accessory genes. Besides the two previously reported lineages, we found six novel lineages in their new habitats, three of which were located in Yunnan province. The genotypes of these viruses are closely related to sampling locations based on polyproteins, and correlated to bat species based on spike genes. Combining phylogenetic analysis, selective pressure, and molecular-clock calculation, we demonstrated that Yunnan bats harbor a gene pool of BtCoV HKU10, with H. pomona as a natural reservoir. The cell tropism test using spike-pseudotyped lentivirus system showed that BtCoV HKU10 could enter cells from human and bat, suggesting a potential interspecies spillover. Continuous studies on these bat coronaviruses will expand our understanding of the evolution and genetic diversity of coronaviruses, and provide a prewarning of potential zoonotic diseases from bats.
The Holin-Endolysin Lysis System of the OP2-Like Phage X2 Infecting Xanthomonas oryzae pv. oryzae

Most endolysins of dsDNA phages are exported by a holin-dependent mechanism, while in some cases endolysins are exported via a holin-independent mechanism. However, it is still unclear whether the same endolysins can be exported by both holin-dependent and holin-independent mechanisms. This study investigated the lysis system of OP2-like phage X2 infecting Xanthomonas oryzae pv. oryzae, causing devastating bacterial leaf blight disease in rice. Based on bioinformatics and protein biochemistry methods, we show that phage X2 employs the classic "holin-endolysin" lysis system. The endolysin acts on the cell envelope and exhibits antibacterial effects in vitro, while the holin facilitates the release of the protein into the periplasm. We also characterized the role of the transmembrane domain (TMD) in the translocation of the endolysin across the inner membrane. We found that the TMD facilitated the translocation of the endolysin via the Sec secretion system. The holin increases the efficiency of protein release, leading to faster and more efficient lysis. Interestingly, in E. coli, the expression of either holin or endolysin with TMDs resulted in the formation of long rod shaped cells. We conclude that the TMD of X2-Lys plays a dual role: One is the transmembrane transport while the other is the inhibition of cell division, resulting in larger cells and thus in a higher number of released viruses per cell.
Reactogenicity Correlates Only Weakly with Humoral Immunogenicity after COVID-19 Vaccination with BNT162b2 mRNA (Comirnaty®)

mRNA vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), such as BNT162b2 (Comirnaty®), have proven to be highly immunogenic and efficient but also show marked reactogenicity, leading to adverse effects (AEs). Here, we analyzed whether the severity of AEs predicts the antibody response against the SARS-CoV-2 spike protein. Healthcare workers without prior SARS-CoV-2 infection, who received a prime-boost vaccination with BNT162b2, completed a standardized electronic questionnaire on the duration and severity of AEs. Serum specimens were collected two to four weeks after the boost vaccination and tested with the COVID-19 ELISA IgG (Vircell-IgG), the LIAISON® SARS-CoV-2 S1/S2 IgG CLIA (DiaSorin-IgG) and the iFlash-2019-nCoV NAb surrogate neutralization assay (Yhlo-NAb). A penalized linear regression model fitted by machine learning was used to correlate AEs with antibody levels. Eighty subjects were enrolled in the study. Systemic, but not local, AEs occurred more frequently after the boost vaccination. Elevated SARS-CoV-2 IgG antibody levels were measured in 92.5% of subjects with Vircell-IgG and in all subjects with DiaSorin-IgG and Yhlo-NAb. Gender, age and BMI showed no association with the antibody levels or with the AEs. The linear regression model identified headache, malaise and nausea as AEs with the greatest variable importance for higher antibody levels (Vircell-IgG and DiaSorin-IgG). However, the model performance for predicting antibody levels from AEs was very low for Vircell-IgG (squared correlation coefficient r2 = 0.04) and DiaSorin-IgG (r2 = 0.06). AEs did not predict the surrogate neutralization (Yhlo-NAb) results. In conclusion, AEs correlate only weakly with the SARS-CoV-2 spike protein antibody levels after COVID-19 vaccination with BNT162b2 mRNA.
HIV-1 Envelope Glycoprotein Cell Surface Localization Is Associated with Antibody-Induced Internalization

To minimize immune responses against infected cells, HIV-1 has evolved different mechanisms to limit the surface expression of its envelope glycoproteins (Env). Recent observations suggest that the binding of certain broadly neutralizing antibodies (bNAbs) targeting the ‘closed’ conformation of Env induces its internalization. On the other hand, non-neutralizing antibodies (nNAbs) that preferentially target Env in its ‘open’ conformation, remain bound to Env on the cell surface for longer periods of time. In this study, we attempt to better understand the underlying mechanisms behind the differential rates of antibody-mediated Env internalization. We demonstrate that ‘forcing’ open Env using CD4 mimetics allows for nNAb binding and results in similar rates of Env internalization as those observed upon the bNAb binding. Moreover, we can identify distinct populations of Env that are differentially targeted by Abs that mediate faster rates of internalization, suggesting that the mechanism of antibody-induced Env internalization partially depends on the localization of Env on the cell surface.
Smart Wearables with Sensor Fusion for Fall Detection in Firefighting

During the past decade, falling has been one of the top three causes of death amongst firefighters in China. Even though there are many studies on fall-detection systems (FDSs), the majority use a single motion sensor. Furthermore, few existing studies have considered the impact sensor placement and positioning have on fall-detection performance; most are targeted toward fall detection of the elderly. Unfortunately, floor cracks and unstable building structures in the fireground increase the difficulty of detecting the fall of a firefighter. In particular, the movement activities of firefighters are more varied; hence, distinguishing fall-like activities from actual falls is a significant challenge. This study proposed a smart wearable FDS for firefighter fall detection by integrating motion sensors into the firefighter’s personal protective clothing on the chest, elbows, wrists, thighs, and ankles. The firefighter’s fall activities are detected by the proposed multisensory recurrent neural network, and the performances of different combinations of inertial measurement units (IMUs) on different body parts were also investigated. The results indicated that the sensor fusion of IMUs from all five proposed body parts achieved performances of 94.10%, 92.25%, and 94.59% in accuracy, sensitivity, and specificity, respectively.
First Clinical Case of Equine Parvovirus-Hepatitis-Related Theiler’s Disease in Asia

Equine parvovirus-hepatitis (EqPV-H) is a newly identified etiologic agent of Theiler’s disease (TD). We present a case of EqPV-H-related fulminant hepatitis in a 14-year-old thoroughbred mare in Korea. The mare had acute hepatopathy and gastrointestinal symptoms, with abnormal liver-related blood parameters. The horse was born in the USA and imported to Korea in 2017, with no history of administration of equine biological products after entry into Korea. The horse was diagnosed with EqPV-H-associated hepatitis after abdominal ultrasonography, laparotomy, and nested polymerase chain reaction (PCR) and in situ hybridization (ISH) assays. The serum, nasal swab, oral swab, and liver biopsy were positive for EqPV-H according to the PCR assay. Genetic analysis of the partial NS1 gene of EqPV-H showed a unique nucleotide substitution, distinct from that in previously deposited strains. EqPV-H DNA was found not only in hepatocytes but also in bile duct epithelium and Kupffer cells, particularly via ISH. To the best of our knowledge, this is the first case of EqPV-H-associated TD in Asia, providing the first clinical evidence for viral shedding from the mouth and nose, and identification of EqPV-H in the liver. This study contributes to a better understanding of the pathological features of EqPV-H-associated TD.