Miracle-dz/UniFAR-FTUs huggingface dataset:
A Security and Privacy Issues in Deep Learning

Ho Bae†, Seoul National University, Republic of Korea Jaehee Jang†, Seoul National University, Republic of Korea Dahuin Jung, Seoul National University, Republic of Korea Hyemi Jang, Seoul National University, Republic of Korea Heonseok Ha, Seoul National University, Republic of Korea Sungroh Yoon*, Seoul National University, Republic of Korea *E-mail: sryoon@snu.ac. kr ∗: To whom correspondence should be addressed, †: These authors contributed equally to this work.
The potential of young vegetative quinoa (Chenopodium quinoa) as a new sustainable protein-rich winter leafy crop under Mediterranean climate

The demand for protein products has significantly risen in the last few years. In western countries, animals are the primary source of protein; however, plants could take a share of this market due to lower production costs, among other advantages. Quinoa (Chenopodium quinoa Willd.) is a well- known but under-utilized protein-rich crop, commonly cultivated for grain production. These plants were recently evaluated for their use as a non-traditional, green leafy crop. Here we assessed the potential of young vegetative quinoa as a new sustainable winter leafy crop in Israel—serving as a model for Mediterranean semi-arid regions, by evaluating yield, protein content and quality. Five quinoa accessions were sown on three winter sowing dates over two consecutive years. Plants were harvested when they reached 10–13% dry matter (DM). DM yield ranged between 574 and 1,982 kg ha-1 and was generally higher in the second year. Protein content ranged from 14.4–34% and was generally higher in the first year. Protein yield ranged from 111–471 kg ha-1 and was greatest on the December sowing date. DM and protein yields were positively correlated with plant density. Protein content was negatively correlated with plant density and DM yield. Our findings show that 200 g DM of young vegetative quinoa can meet the protein and most essential amino acid requirements for a 70 kg human adult. Prospects for cultivating young vegetative quinoa in Mediterranean countries as a new sustainable, protein-rich winter leafy crop are therefore high, as supported by its high protein yields and quality, and its requirement for only scant irrigation. Further studies should examine economic and other agrotechnical parameters toward the geographical distribution and expansion of young vegetative quinoa cultivation.
Postural control in girls practicing volleyball is different than in non-playing peers: comparison of data on the center of pressure and ground reaction forces

A comprehensive explanation of the relationship between postural control and athletic performance requires evaluating body balance in athletes of different performance levels. To fill this gap in relation to volleyball, the aim of this study was to compare the balance of intermediate adolescent female players (VOL, n=61) with inactive peers (CON, n=57). The participants were investigated in normal quiet stance during 30 s trials on a Kistler force plate. The traditional spatial (amplitude and mean speed) and temporal (frequency, fractality and entropy) indices were computed for ground reaction forces (GRF) and center-of-pressure (COP) time-series. The spatial parameters of the both time-series did not discriminate the two groups. However, the temporal GRF parameters revealed much lower values in VOL than in CON (p<.0001). This leads to three important conclusions regarding posturography applications. First, GRF and COP provide different information regarding postural control. Second, measures based on GRF are more sensitive to changes in balance (at least those related to volleyball training and perhaps to similar training and sports activity regimens). And third, the indicators calculated on the basis of these two time series can complement each other and thus enrich the insight into the relationship between balance and sports performance level.
In vivo time-lapse imaging and analysis of mitochondria in neural progenitor cells in the developing brain

Neural progenitor cells (NPCs) are the highly polarized dividing stem cells of the developing brain that give rise to all neurons and glia. Early on, NPCs divide symmetrically and expand the pool of progenitor cells, but as development continues the NPCs begin to asymmetrically divide to produce neurons. The mechanisms that govern this irreversible commitment to neurogenesis are not fully understood, but in other stem cell populations the regulation of mitochondria and cell metabolism is key to controlling stem cell fate. Here we use timelapse 3D confocal microscopy to observe NPCs, their cellular progeny, and their mitochondria in the developing Xenopus tectum. Our results track individual NPCs over days and show that they contain abundant mitochondria that form complicated networks distributed throughout the cells. We find that NPCs preparing to divide shift mitochondria toward the cell body where they become asymmetrically distributed, suggesting that the cells control which progeny inherit mitochondria. This uneven distribution of mitochondria in cell preparing to divide led us to test the role that mitochondria play in cell division. We overexpressed the mitochondrial biogenesis master regulator, PGC-1a, which induced the NPCs to asymmetrically divide and produce neurons, while PGC-1a knockdown limited neurogenesis. Together these data suggest that the regulation of mitochondria by NPCs prior to cell division and their unequal inheritance during cell division, contributes to the fate of the newborn cells in the developing brain.
Effective Monitoring for Early Detection of Hypoxia in Fighter Pilots

ABSTRACT Objective This study evaluated various biological parameters in subjects exposed to hypoxia, to verify effective monitoring for early hypoxia detection. Background Hypoxic-hypoxia is a life-threatening condition, but no method of early detection in flight has been established. Method Six healthy male subjects underwent 2 experiments at different oxygen concentrations (O2) during hypoxic exposure on different days. Subjects inhaled approximately 21% O2 for 3 minutes, hypoxia using approximately 14% O2 in Experiment 1 and 7% O2 in Experiment 2 for 3.5 minutes using a reduced oxygen breathing device. During the experiments, pupil diameter (PD), cerebral oxygenated hemoglobin (O2Hb), peripheral tissue oxygen saturation (SpO2), heart rate (HR), and blood pressure (BP) were measured. Results All 6 subjects completed both Experiments 1 and 2. ΔO2Hb showed significant correlations with %HR (r = −0.6005, P < .0001), %PD (r = −0.5227, P = .0001), and %SpO2 (r = 0.8281, P < .0001) in Experiment 1. ΔO2Hb also showed significant correlations with %HR (r = −0.7904, P < .0001), %PD (r = −0.7933, P < .0001), and %SpO2 (r = 0.7240, P < .0001) in Experiment 2. Rapid hypoxic exposure caused increase in %PD and decrease in ΔO2Hb, followed by immediate increase in %HR, and then decrease in %SpO2. Conclusion The present study suggested that monitoring of HR, PD, and O2Hb were earlier parameters to detect hypoxia than SpO2.
A curved boundary treatment for discrete Boltzmann model of shallow water flows based on a partially saturated method

In the present study, a boundary treatment scheme named the partially saturated method (PSM) is incorporated into the discrete Boltzmann model (DBM) for shallow water flows to deal with complex curved boundaries. In this PSM-DBM, the two-dimensional 16 velocity levels scheme is adopted and the finite difference method is used to solve the governing equation. Then, the PSM-DBM has been applied to simulate four cases, i.e. such as steady flow in a bending channel, the flow past a stationary cylinder, a jet-forced flow in a circular basin and flow in a meandering channel with 90° consecutive bends. The simulated results have been compared with the experiments and the simulation by traditional numerical simulation. The study shows that the agreement between simulation and experiments is good. It is demonstrated that the PSM-DBM is stable and accurate to deal with the curved boundaries. Moreover, the implementation of the PSM is relatively straightforward in treating stationary curved geometries and is easy to be incorporated into the DBM for shallow water flows. In conclusion, the proposed PSM-DBM can be used widely for flows with curved boundaries.
Non-linear Conductance, Rectification, and Mechanosensitive Channel Formation of Lipid Membranes

Published in: Frontiers in Cell and Developmental Biology DOI: 10.3389/fcell.2020. 592520 Publication date: 2021 Document version Publisher's PDF, also known as Version of record Document license: CC BY Citation for published version (APA): Zecchi, K. A. , & Heimburg, T. (2021). Non-linear Conductance, Rectification, and Mechanosensitive Channel Formation of Lipid Membranes. Frontiers in Cell and Developmental Biology, 8, [592520]. https://doi.org/10.3389/fcell.2020. 592520
Proximal Online Gradient is Optimum for Dynamic Regret

In online learning, the dynamic regret metric chooses the reference (optimal) solution that may change over time, while the typical (static) regret metric assumes the reference solution to be constant over the whole time horizon. The dynamic regret metric is particularly interesting for applications such as online recommendation (since the customers' preference always evolves over time). While the online gradient method has been shown to be optimal for the static regret metric, the optimal algorithm for the dynamic regret remains unknown. In this paper, we show that proximal online gradient (a general version of online gradient) is optimum to the dynamic regret by showing that the proved lower bound matches the upper bound that slightly improves existing upper bound.
Single-cell and spatial transcriptomics reveals the human liver immunological landscape and myeloid dysfunction in PSC

Background Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease characterized by bile retention, biliary tree destruction, and progressive fibrosis leading to end stage liver disease and transplantation. There is an unmet need to understand the cellular composition of the PSC liver and how it underlies disease pathogenesis. As such, we generated a comprehensive atlas of the PSC liver and a reference healthy liver dataset using multiple multi-omic modalities and functional validation. Methods In this work, we employed single-cell (12,000 cells), single-nuclei (23,000 nuclei), and spatial transcriptomics (1 sample by 10x Visium and 3 samples with multi-region profiling by Nanostring GeoMx DSP) to profile the cellular ecosystem in 5 patients with PSC. Transcriptomic profiles were compared to 100k single cell transcriptomes and spatial transcriptomics controls from 24 healthy neurologically deceased donor (NDD) livers. Flow cytometry and intracellular cytokine staining was performed to validate PSC-specific differences in immune phenotype and function. Results PSC explants with cirrhosis of the liver parenchyma and prominent periductal fibrosis were associated with a unique population of hepatocytes which transformed to a cholangiocyte-like phenotype. These hepatocytes were surrounded by diverse immune cell populations, including monocyte-like macrophages, liver-resident and circulating natural killer (NK) cells. Inflamed cholangiocytes, fibrosis-resident hepatic stellate cells, and endothelial cells released cytokines that recruited CD4+T-cells, dendritic cells, and neutrophils to the PSC liver. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional inflammatory response to LPS and IFN-Ɣ stimulation. Conclusions We present the first comprehensive atlas of the PSC liver and demonstrate hyper-activation and exhaustion-like phenotypes of myeloid cells and markers of chronic cytokine expression in late-stage PSC lesions. Lay Summary Primary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts. Due to a limited understanding of the underlying pathogenesis of disease, there remains a paucity of treatment options. As such, we sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that outside PSC scar regions, hepatocytes are transitioning to bile duct cells, whereas within the scars, there is an accumulation of immune cells. Of these cells, macrophages that typically contribute to tissue repair were enriched in immunoregulatory genes and were less responsive to stimulation. These cells are likely involved in maintaining hepatic inflammation and could be targeted in novel therapeutic development.
Recombinant rotavirus expressing the glycosylated S1 protein of SARS-CoV-2

Reverse genetic systems have been used to introduce heterologous sequences into the rotavirus segmented double-stranded (ds)RNA genome, enabling the generation of recombinant viruses that express foreign proteins and possibly serve as vaccine vectors. Notably, insertion of SARS-CoV-2 sequences into the segment 7 (NSP3) RNA of simian SA11 rotavirus was previously shown to result in the production of recombinant viruses that efficiently expressed the N-terminal domain (NTD) and the receptor-binding domain (RBD) of the S1 region of the SARS-CoV-2 spike protein. However, efforts to generate a similar recombinant (r) SA11 virus that efficiently expressed full-length S1 were less successful. In this study, we describe modifications to the S1-coding cassette inserted in the segment 7 RNA that allowed recovery of second-generation rSA11 viruses that efficiently expressed the ∼120-kDa S1 protein. The ∼120-kDa S1 products were shown to be glycosylated, based on treatment with endoglycosidase H, which reduced the protein to a size of ∼80 kDa. Co-pulldown assays demonstrated that the ∼120-kDa S1 proteins had affinity for the human ACE2 receptor. Although all the second-generation rSA11 viruses expressed glycosylated S1 with affinity for the ACE receptor, only the S1 product of one virus (rSA11/S1f) was appropriately recognized by anti-S1 antibody, suggesting the rSA11/S1f virus expressed an authentic form of S1. Probably due to the presence of FLAG tags on their S1 signal peptides, the S1 products of the other viruses (rSA11/3fS1 and rSA11/3fS1-His) may have undergone defective glycosylation, impeding antibody binding. In summary, these results indicate that recombinant rotaviruses can serve as expression vectors of foreign glycosylated proteins, raising the possibility of generating rotavirus-based vaccines that can induce protective immune responses against enteric and mucosal viruses with glycosylated capsid components, including SARS-CoV-2.
Dielectric spectroscopic study of (K0.44Na0.52Li0.04)0.97 La0.01Nb0.9Ta0.103 ceramics

A dielectric spectroscopic study and an ac conductivity analysis in the 100 Hz–1 MHz frequency and 30–450 °C temperature ranges are presented for the piezoceramic compound (K0.44Na0.52Li0.04)0.97La0. 01Nb0.9Ta0. 103, synthesized by the traditional ceramic method using NaNbO3 as a precursor obtained by the reactive templated grain growth method technique. La doping of KxNa1-xNbO3 (KNN) produces a shift of the phase transition temperatures (orthorhombic-tetragonal and tetragonal-cubic) toward lower temperatures. The measured relative permittivity maximum and the relative permittivity at room temperature are remarkably high. Conductivity behaves according to Jonscher's law in the 400 Hz–1500 Hz frequency range at temperatures between 75 and 300 °C, with values of n1≤ 0.70, lower than those reported in the literature for similar compounds. The activation energy in the case of dc (long range) conductivity, 1.72 eV, points out to double ionized oxygen vacancies. This value is higher than the 1.46 eV of undoped KN.
The Local Group in LCDM - Shapes and masses of dark halos

In dit proefschrift bestuderen we de eigenschappen van donkere materie halo's in het LCDM paradigma. Het eerste deel richt zich op de vorm van de massadistributie van dergelijke objecten. We hebben gevonden dat de vorm van ge"isoleerde Melkweg-achtige donkere materie halo's significant afwijkt van bolsymmetrie. De lokale omgeving heeft invloed op de halo's en deze worden daarbij sterk be"invloed door de manier waarop massa aangroeit. We hebben ook de structuur en de baanstructuur van de satellieten van dergelijke halo's in detail onderzocht. In het algemeen zijn deze objecten sferischer dan de halo's zelf. Ze vertonen ook duidelijke afdrukken van getijdenwerking in zowel hun geometrische vorm als in de baanstructuur. Daarna gebruiken we het aantal massieve objecten rond de Melkweg om limieten te zetten op de totale massa van de donkere materie halo van de Melkweg. De eigenschappen van de massaverdeling van de Melkweg worden verder onderzocht in het laatste hoofdstuk. Daar maken we gebruik van de Sagittarius sterstroom om de vorm van de galactische potentiaal beter te bepalen. We komen met een nieuw model dat rekening houdt met de galactische schijf en de invloed van satellietstelsels en die bovendien consistent is met het LCDM paradigma.
Electronic Phenomena in Two-Dimensional Topological Insulators

In recent years, two-dimensional electron systems have played an integral role at the forefront of discoveries in condensed matter physics. These include the integer and fractional quantum Hall effects, massless electron physics in graphene, the quantum spin and quantum anomalous Hall effects, and many more. Investigation of these fascinating states of matter brings with it surprising new results, challenges us to understand new physical phenomena, and pushes us toward new technological capabilities. In this thesis, we describe a set of experiments aimed at elucidating the behavior of two such two-dimensional systems: the quantumHall effect, and the quantum spin Hall effect. The first experiment examines electronic behavior at the edge of a two-dimensional electron system formed in a GaAs/AlGaAs heterostructure, under the application of a strong perpendicular magnetic field. When the ratio between the number of electrons and flux quanta in the system is tuned near certain integer or fractional values, the electrons in the system can form states which are respectively known as the integer and fractional quantumHall effects. These states are insulators in the bulk, but carry gapless excitations at the edge. Remarkably, in certain fractional quantum Hall states, it was predicted that even as charge is carried downstream along an edge, heat can be carried upstream in a neutral edge channel. By placing quantum dots along a quantumHall edge, we are able to locally monitor the edge temperature. Using a quantum point contact, we can locally heat the edge and use the quantum dot thermometers to detect heat carried both downstream and upstream. We find that heat can be carried upstreamwhen the edge contains structure related to the ν = 2/3 fractional quantumHall state. We
Sub-Poissonian length distributions of vapor–liquid–solid nanowires induced by nucleation antibunching

Herein, we present an analytic length distribution of vapor–liquid–solid nanowires growing without the nucleation delays of the very first monolayer, by the direct impingement of material from vapor, and in the absence of desorption. We show that nucleation antibunching narrows the Poissonian length distribution to a time-independent asymptotic shape. The obtained distribution depends on the sole control parameter ε describing the effect of antibunching, and has a variance of 1/(2ε) rather than spreading infinitely with time. A good agreement is found between the analytic shapes obtained within the continuum growth theory and Green’s function of the discrete rate equations describing the length statistics of nanowires. Overall, this narrowing effect can be used to improve the size homogeneity of III–V and other semiconductor nanowires grown under the appropriate conditions.
Auto-Encoding Variational Neural Machine Translation

Translation data is often a byproduct of mixing different sources of data. This could be intentional such as by mixing data of different domains or including back-translated monolingual data, but often also is the result of how the bilingual dataset was constructed: a combination of different documents independently translated in different translation directions, by different translators, agencies, etc. Most neural machine translation models do not explicitly account for such variation in their probabilistic model. We attempt to model this by proposing a deep generative model that generates source and target sentences jointly from a shared sentence-level latent representation. The latent representation is designed to capture variations in the data distribution and allows the model to adjust its language and translation model accordingly. We show that such a model leads to superior performance over a strong conditional neural machine translation baseline in three settings: in-domain training where the training and test data are of the same domain, mixed-domain training where we train on a mix of domains and test on each domain separately, and in-domain training where we also include synthetic (noisy) back-translated data. We furthermore extend the model to be used in a semi-supervised setting in order to incorporate target monolingual data during training. Doing this we derive the commonly employed backtranslation heuristic in the form of a variational approximation to the posterior over the missing source sentence. This allows for training the back-translation network jointly with the rest of the model on a shared objective designed for source-to-target translation with minimal need of pre-processing. We find that the performance of this approach is not on par with the back-translation heuristic, but does lead to improvement over a model trained on bilingual data alone.
Chance-Constrained AC Optimal Power Flow : Reformulations and Efficient Algorithms Line Roald and

Higher levels of renewable electricity generation increase uncertainty in power system operation. To ensure secure system operation, new tools that account for this uncertainty are required. In this paper, we adopt a chance-constrained AC optimal power flow formulation, which guarantees that generation, power flows and voltages remain within their bounds with a pre-defined probability. We then discuss different chanceconstraint reformulations and solution approaches for the problem. We first describe an analytical reformulation based on partial linearization, which enables us to obtain a tractable representation of the optimization problem. We then provide an efficient algorithm based on an iterative solution scheme which alternates between solving a deterministic AC OPF problem and assessing the impact of uncertainty. The flexibility of the iterative scheme enables not only scalable implementations, but also alternative chance-constraint reformulations. In particular, we suggest two sample based reformulations that do not require any approximation or relaxation of the AC power flow equations. In a case study based on four different IEEE systems, we assess the performance of the method, and demonstrate scalability of the iterative scheme. We further show that the analytical reformulation accurately and efficiently enforces chance constraints in both inand out-of-sample tests, and that the analytical reformulations outperforms the two alternative, sample-based chance constraint reformulations.