cssi/SciSciGPT-SciSciNet huggingface dataset:
Germans in Germany's Ethnic Neighborhoods

Abstract In contrast to most research on the effects on residents of living in an ethnic neighborhood, this paper explores how living within an ethnic neighborhood affects members of the dominant ethnic group – in this case Germans – rather than the minorities that define it. The results indicate that Germans living within ethnic neighborhoods are less well off financially than their peers in other parts of the city, and are more likely to be living in large buildings in need of repair. The analysis did not however suggest that Germans living in ethnic neighborhoods have fewer social contacts, or that they are more likely to be unemployed. Indeed, Germans living within ethnic neighborhoods reported levels of satisfaction with their housing and standard of living equal to Germans elsewhere. These results would seem to paint a rosy picture of the lives of German residents of ethnic neighborhoods, were it not for a notable absence of school-aged German children within these spaces. JEL Classifications: J15, R21
9 – Additional Topics

Publisher Summary This chapter discusses a few topics that are common to intermediate algebra. It discusses compound inequalities, wherein two inequalities connecting by the word “and” or “or” form a compound inequality. If the connecting word is “and,” only those points are used in graphs that are common to both graphs. It also explains the steps necessary to graph a linear inequality in two variables. The first step involves replacing the inequality symbol with an equal sign. The resulting equation represents the boundary for the solution set. Graph the boundary found in the first step using a solid line if the original inequality symbol was either , otherwise use a broken line. Any convenient point that is chosen should not be on the boundary and substitute the coordinates into the original inequality. If the resulting statement is true, the graph lies on the same side of the boundary as the chosen point. If the resulting statement is false, the solution set lies on the opposite side of the boundary.
Chapter 2 – Epidemiological Applications

This chapter discusses four projects. The first matches theory with empirical data, the second uses the proven model to make an important prediction, the third explores a change in basic assumptions and its consequences, while the fourth finds the “peak” of an epidemic. The four projects are the New York City Hong Kong flu epidemic, the vaccination strategies for herd immunity, the endemic S-I-S diseases, and the peak of an S-I-R epidemic.This project compares the S-I-R model with actual data of the Hong Kong flu epidemic in 1968-69. The second project is vaccination strategies for herd immunity. This project uses the mathematical model of an S-I-R disease to find a prediction of how many people in a population must be vaccinated to prevent the spread of an epidemic. The third project is endemic S-I-S diseases. Some infectious diseases such as strep throat, meningitis, or gonorrhea do not confer immunity. In these diseases, there is no removed class, only susceptibles and infectives. This project makes a mathematical model for the S-I-S diseases. The forth project is the peak of an S-I-R epidemic. There are various maxima associated with an epidemic; the largest portion of the population sick at one time, the fastest increase in the portion of sick people and the fastest increase in new cases.
Expression of ACE2, the SARS-CoV-2 Receptor, and TMPRSS2 in Prostate Epithelial Cells.

Author(s): Song, Hanbing; Seddighzadeh, Bobak; Cooperberg, Matthew R; Huang, Franklin W | Abstract: The COVID-19 pandemic has spread across more than 200 countries and resulted in over 170,000 deaths. For unclear reasons, higher mortality rates from COVID-19 have been reported in men compared to women. While the SARS-CoV-2 receptor ACE2 and serine protease TMPRSS2 have been detected in lung and other tissues, it is not clear what sex differences may exist. We analyzed a publicly-available normal human prostate single-cell RNA sequencing dataset and found TMPRSS2 and ACE2 co-expressing cells in epithelial cells, with a higher proportion in club and hillock cells. Then we investigated datasets of lung epithelial cells and also found club cells co-expressing TMPRSS2 and ACE2. A comparison of ACE2 expression in lung tissue between males and females showed higher expression in males and a larger proportion of ACE2+ cells in male type II pneumocytes, with preliminary evidence that type II pneumocytes of all lung epithelial cell types showed the highest expression of ACE2. These results raise the possibility that sex differences in ACE2 expression and the presence of double-positive cells in the prostate may contribute to the observed disparities of COVID-19.
Gaussian Process Regression for Estimating EM Ducting Within the Marine Atmospheric Boundary Layer

We show that Gaussian process regression (GPR) can be used to infer the electromagnetic(EM) duct height within the marine atmospheric boundary layer (MABL) from sparsely sampled propagation factors within the context of bistatic radars. We use GPR to calculate the posterior predictive distribution on the labels (i.e., duct height) from both noise-free and noise-contaminated array of propagation factors. For duct height inference from noise-contaminated propagation factors, we compare anaive approach, utilizing one random sample from the input distribution (i.e., disregarding the input noise), with an inverse-variance weighted approach, utilizing a few random samples to estimate the true predictive distribution. The resulting posterior predictive distributions from these two approaches are compared to a “ground truth” distribution, which is approximated using a large number of Monte-Carlo samples. The ability of GPR to yield accurate and fast duct height predictions using a few training examples indicates the suitability of the proposed method for real-time applications.
The Union Threat

This article develops a search theory of labour unions in which the possibility of unionization distorts the behaviour of non-union firms. In the model, unions arise endogenously through a majority election within firms. As union wages are set through a collective bargaining process, unionization compresses wages and lowers profits. To prevent unionization, non-union firms over-hire high-skill workers— who vote against the union— and under-hire low-skill workers— who vote in its favour. As a consequence of this distortion in hiring, firms that are threatened by unionization hire fewer workers, produce less and pay a more concentrated distribution of wages. In the calibrated economy, the threat of unionization has a significant negative impact on aggregate output, but it also reduces wage inequality.
Paradoxical aortic stiffening and subsequent cardiac dysfunction in Hutchinson–Gilford progeria syndrome

Hutchinson–Gilford progeria syndrome (HGPS) is an ultra-rare disorder with devastating sequelae resulting in early death, presently thought to stem primarily from cardiovascular events. We analyse ...
One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases.

Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, we address this problem from both modeling and evaluation perspectives. We first propose a recurrent generative model that generates multiple keyphrases as delimiter-separated sequences. Generation diversity is further enhanced with two novel techniques by manipulating decoder hidden states. In contrast to previous approaches, our model is capable of generating diverse keyphrases and controlling number of outputs. We further propose two evaluation metrics tailored towards the variable-number generation. We also introduce a new dataset StackEx that expands beyond the only existing genre (i.e., academic writing) in keyphrase generation tasks. With both previous and new evaluation metrics, our model outperforms strong baselines on all datasets.
D-region electron density measurements during the solar eclipse of May 20, 1966

Rocket (Underwood and Muney, 1967) and satellite observations of 2–8 A X-ray emissions indicate that the solar eclipse of May 20, 1966, occurred during a period in which the Sun was moderately active. The Goddard Space Flight Center conducted a series of small sounding rocket experiments to measure the ionospheric D-region electron density profile during successive stages of the eclipse. Compared to the uneclipsed profile, an order of magnitude reduction is observed in the D-region profile obtained near totality. From the electron density measurements together with the X-ray spectral data of Underwood and Muney it is concluded that on May 20, 1966, 2–8 A X-rays were not the dominant source of D-region ionization below approximately 80 km.
Effects of tone on the three-way laryngeal distinction in Korean: An acoustic and aerodynamic comparison of the Seoul and South Kyungsang dialects

The three-way laryngeal distinction among voiceless Korean stops has been well documented for the Seoul dialect. The present study compares the acoustic and aerodynamic properties of this stop series between two dialects, non-tonal Seoul and tonal South Kyungsang Korean. Sixteen male Korean speakers (eight from Seoul and eight from Kyungsang) participated. Measures collected included VOT, f0 at vowel onset, H1-H2, and air pressure and airflow. The presence versus absence of lexical pitch accent affects both the acoustic and aerodynamic properties. First, Seoul speakers use a combination of f0 and VOT to distinguish the three-way contrast of Korean stops, while Kyungsang speakers mainly use VOT. Second, the presence of lexical pitch for Kyungsang speakers makes f0 an unreliable acoustic cue for the three Korean stops. Third, dialectal differences in VOT to mark the three-way distinction support the notion of a diachronic transition whereby VOT differences between the lenis and aspirated stops in Seoul Korean have been decreasing over the past 50 years. Finally, the aerodynamic results make it possible to postulate the articulatory state of the glottis, indicating a positive correlation with acoustic parameters. Based on the acoustic and aerodynamic results, phonological representations of Korean stops for the tonal and non-tonal dialects are suggested.
In silico assessment of binding affinities of three dementia-protective Human Leukocyte Antigen (HLA) alleles to nine human herpes virus antigens.

Abstract Background Human herpes viruses (HHV) have been implicated in dementia. Class II Human Leukocyte Antigens (HLA) play a critical role in host protection from foreign antigens including herpes viruses through stimulating antibody production against them. In the present study we investigated the in silico binding affinity of 9 H HV to three Class II HLA alleles that have been found to protect against dementia: DRB1*01:01, DRB1*13:02, and DRB1*15:01. Methods A sliding window approach was used to partition the amino acid sequences of surface glycoproteins from HHV 1–8 into subsequences. The binding affinity of the HHV subsequences to Class II HLA surface receptor proteins was predicted using the Sturniolo method in the Immune Epitope Database and reported as a percentile rank. The binding affinity of HHV subsequences to protective alleles was compared to that of three dementia-neutral Class II HLA alleles: DRB1*03:01, DRB1*07:01, and DRB1*08:01. Findings Binding affinity varied widely for each HLA allele, HHV type, and HHV subsequence. The protective alleles had significantly higher binding affinity that than the neutral alleles. The largest differences in binding affinity between the protective and neutral alleles was shown for HHV-6A and HHV-6B, which had the best overall binding affinity with the protective alleles. Interpretation The dementia protection conferred by the three protective HLA alleles investigated here is related to their superior ability to bind and successfully eliminate HHV epitopes – in particular, HHV6 - that could otherwise cause dementia if they persisted.
Global targetome analysis reveals critical role of miR-29a in pancreatic stellate cell mediated regulation of PDAC tumor microenvironment

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of malignancies with a nearly equal incidence and mortality rates in patients. Pancreatic stellate cells (PSCs) are critical players in PDAC microenvironment to promote the aggressiveness and pathogenesis of the disease. Dysregulation of microRNAs (miRNAs) have been shown to play a significant role in progression of PDAC. Earlier, we observed a PSC-specific downregulation of miR-29a in PDAC pancreas, however, the mechanism of action of the molecule in PSCs is still to be elucidated. The current study aims to clarify the regulation of miR-29a in PSCs and identifies functionally important downstream targets that contribute to tumorigenic activities during PDAC progression. In this study, using RNAseq approach, we performed transcriptome analysis of paired miR-29a overexpressing and control human PSCs (hPSCs). Enrichment analysis was performed with the identified differentially expressed genes (DEGs). miR-29a targets in the dataset were identified, which were utilized to create network interactions. Western blots were performed with the top miR-29a candidate targets in hPSCs transfected with miR-29a mimic or scramble control. RNAseq analysis identified 202 differentially expressed genes, which included 19 downregulated direct miR-29a targets. Translational repression of eight key pro-tumorigenic and -fibrotic targets namely IGF-1, COL5A3, CLDN1, E2F7, MYBL2, ITGA6 and ADAMTS2 by miR-29a was observed in PSCs. Using pathway analysis, we find that miR-29a modulates effectors of IGF-1-p53 signaling in PSCs that may hinder carcinogenesis. We further observe a regulatory role of the molecule in pathways associated with PDAC ECM remodeling and tumor-stromal crosstalk, such as INS/IGF-1, RAS/MAPK, laminin interactions and collagen biosynthesis. Together, our study presents a comprehensive understanding of miR-29a regulation of PSCs, and identifies essential pathways associated with PSC-mediated PDAC pathogenesis. The findings suggest an anti-tumorigenic role of miR-29a in the context of PSC-cancer cell crosstalk and advocates for the potential of the molecule in PDAC targeted therapies.
Each post matters: a content analysis of #mentalhealth images on Instagram.

This study examined mental health-related content on a popular visual-based social media platform, Instagram. A content analysis was completed by using the search term ‘#mentalhealth’ on public Ins...
ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-CoV-2 COVID-19.

Background Pandemic COVID-19 by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) infection is facilitated by the ACE2 receptor and protease TMPRSS2. Modestly sized case series have described clinical factors associated with COVID-19, while ACE2 and TMPRSS2 expression analyses have been described in some cell types. Patients with cancer may have worse outcomes to COVID-19. Methods We performed an integrated study of ACE2 and TMPRSS2 gene expression across and within organ systems, by normal versus tumor, across several existing databases (The Cancer Genome Atlas, Census of Immune Single Cell Expression Atlas, The Human Cell Landscape, and more). We correlated gene expression with clinical factors (including but not limited to age, gender, race, body mass index, and smoking history), HLA genotype, immune gene expression patterns, cell subsets, and single-cell sequencing as well as commensal microbiome. Results Matched normal tissues generally display higher ACE2 and TMPRSS2 expression compared with cancer, with normal and tumor from digestive organs expressing the highest levels. No clinical factors were consistently identified to be significantly associated with gene expression levels though outlier organ systems were observed for some factors. Similarly, no HLA genotypes were consistently associated with gene expression levels. Strong correlations were observed between ACE2 expression levels and multiple immune gene signatures including interferon-stimulated genes and the T cell-inflamed phenotype as well as inverse associations with angiogenesis and transforming growth factor-β signatures. ACE2 positively correlated with macrophage subsets across tumor types. TMPRSS2 was less associated with immune gene expression but was strongly associated with epithelial cell abundance. Single-cell sequencing analysis across nine independent studies demonstrated little to no ACE2 or TMPRSS2 expression in lymphocytes or macrophages. ACE2 and TMPRSS2 gene expression associated with commensal microbiota in matched normal tissues particularly from colorectal cancers, with distinct bacterial populations showing strong associations. Conclusions We performed a large-scale integration of ACE2 and TMPRSS2 gene expression across clinical, genetic, and microbiome domains. We identify novel associations with the microbiota and confirm host immunity associations with gene expression. We suggest caution in interpretation regarding genetic associations with ACE2 expression suggested from smaller case series.
Exposure to the predator odor TMT induces early and late differential gene expression related to stress and excitatory synaptic function throughout the brain in male rats.

Persistent changes in brain stress and glutamatergic function are associated with post-traumatic stress disorder (PTSD). Rodent exposure to the predator odor trimethylthiazoline (TMT) is an innate stressor that produces lasting behavioral consequences relevant to PTSD. As such, the goal of the present study was to assess early (6 hours and 2 days-Experiment 1) and late (4 weeks-Experiment 2) changes to gene expression (RT-PCR) related to stress and excitatory function following TMT exposure in male, Long-Evans rats. During TMT exposure, rats engaged in stress reactive behaviors, including digging and immobility. Further, the TMT group displayed enhanced exploration and mobility in the TMT-paired context 1 week after exposure, suggesting a lasting contextual reactivity. Gene expression analyses revealed upregulated FKBP5 6 hours post-TMT in the hypothalamus and dorsal hippocampus. Two days after TMT, GRM3 was downregulated in the prelimbic cortex and dorsal hippocampus, but upregulated in the nucleus accumbens. This may reflect an early stress response (FKBP5) that resulted in later glutamatergic adaptation (GRM3). Finally, another experiment 4 weeks after TMT exposure showed several differentially expressed genes known to mediate excitatory tripartite synaptic function in the prelimbic cortex (GRM5, DLG4 and SLC1A3 upregulated), infralimbic cortex (GRM2 downregulated, Homer1 upregulated), nucleus accumbens (GRM7 and SLC1A3 downregulated), dorsal hippocampus (FKBP5 and NR3C2 upregulated, SHANK3 downregulated) and ventral hippocampus (CNR1, GRM7, GRM5, SHANK3 and Homer1 downregulated). These data show that TMT exposure induces stress and excitatory molecular adaptations, which could help us understand the persistent glutamatergic dysfunction observed in PTSD.
Physics-Informed Neural Network for Ultrasound Nondestructive Quantification of Surface Breaking Cracks

We introduce an optimized physics-informed neural network (PINN) trained to solve the problem of identifying and characterizing a surface breaking crack in a metal plate. PINNs are neural networks that can combine data and physics in the learning process by adding the residuals of a system of partial differential equations to the loss function. Our PINNs is supervised with realistic ultrasonic surface acoustic wave data acquired at a frequency of 5 MHz. The ultrasonic surface wave data is represented as a deformation on the top surface of a metal plate, measured by using the method of laser vibrometry. The PINN is physically informed by the acoustic wave equation and its convergence is sped up using adaptive activation functions. The adaptive activation function uses a trainable hyperparameter, which is optimized to achieve the best performance of the network. The adaptive activation function changes dynamically, involved in the optimization process. The usage of the adaptive activation function significantly improves the convergence, evidently observed in the current study. We use PINNs to estimate the speed of sound of the metal plate, which we do with an error of 1%, and then, by allowing the speed of sound to be space dependent, we identify and characterize the crack as the positions where the speed of sound has decreased. Our study also shows the effect of sub-sampling of the data on the sensitivity of sound speed estimates. More broadly, the resulting model shows a promising deep neural network model for ill-posed inverse problems.
Versatile Optothermal Micro/Nanorobots for Cellular Biology

We develop a new type of low-power optical platform - optothermal robots - to achieve versatile three-dimensional (3D) manipulation of colloidal particles and biological cells at nanoscale resolution for single-cell study.
Behavior Associations in Lone-Actor Terrorists

Terrorist attacks carried out by individuals have significantly accelerated over the last twenty years. This type of lone-actor (LA) terrorism stands as one of the greatest security threats of our ...
Nilmanifolds and their associated non-local fields

For six dimensional nilmanifolds we build a module $\mathcal{H}$ of an affine Kac Moody vertex algebras. Then, we associate some logarithmic fields for the module $\mathcal{H}$ and we study their singularities. We also presented a physics motivation behind this construction. We study a particular case, we show that when the nilmanifold $N$ is a $k$ degree $S^1$--fibration over the two torus and a choice of $l \in \mathbb{Z} \simeq H^3(N, \mathbb{Z})$ the fields associated to the space $\mathcal{H}$ have tri-logarithm singularities whenever $kl \neq 0$.
Dark Matter Through the Quark Vector Current Portal

We consider models of light dark matter coupled to quarks through a vector current interaction. For low energies, these models must be treated through the effective couplings to mesons, which are implemented here through the chiral Lagrangian. We find the signals of dark matter annihilation and decay to the light mesons, and find the expected photon spectrum from the decay of the hadrons. We compare the current and future observations, and show that there is a significant discovery reach for these models.
Computational Resource Allocation for Edge Computing in Social Internet-of-Things

The heterogeneity of the Internet-of-things (IoT) network can be exploited as a dynamic computational resource environment for many devices lacking computational capabilities. A smart mechanism for allocating edge and mobile computers to match the need of devices requesting external computational resources is developed. In this paper, we employ the concept of Social IoT and machine learning to downgrade the complexity of allocating appropriate edge computers. We propose a framework that detects different communities of devices in SIoT enclosing trustworthy peers having strong social relations. Afterwards, we train a machine learning algorithm, considering multiple computational and non-computational features of the requester as well as the edge computers, to predict the total time needed to process the required task by the potential candidates belonging to the same community of the requester. By applying it to a real-world data set, we observe that the proposed framework provides encouraging results for mobile computer allocation.
Statistical Properties of Magnetic Structures and Energy Dissipation during Turbulent Reconnection in the Earth's Magnetotail

We present the first statistical study of magnetic structures and associated energy dissipation observed during a single period of turbulent magnetic reconnection, by using the \textit{in-situ} measurements of the Magnetospheric Multiscale mission in the Earth's magnetotail on July 26, 2017. The structures are selected by identifying a bipolar signature in the magnetic field and categorized as plasmoids or current sheets via an automated algorithm which examines current density and plasma flow. The size of the plasmoids forms a decaying exponential distribution ranging from sub-electron up to ion scales. The presence of substantial number of current sheets is consistent with a physical picture of dynamic production and merging of plasmoids during turbulent reconnection. The magnetic structures are locations of significant energy dissipation via electric field parallel to the local magnetic field, while dissipation via perpendicular electric field dominates outside of the structures. Significant energy also returns from particles to fields.
Low-pass whole genome bisulfite sequencing of neonatal dried blood spots identifies a role for RUNX1 in Down syndrome DNA methylation profiles.

Neonatal dried blood spots (NDBS) are a widely banked sample source that enables retrospective investigation into early life molecular events. Here, we performed low-pass whole genome bisulfite sequencing (WGBS) of 86 NDBS DNA to examine early life Down syndrome (DS) DNA methylation profiles. DS represents an example of genetics shaping epigenetics, as multiple array-based studies have demonstrated that trisomy 21 is characterized by genome-wide alterations to DNA methylation. By assaying over 24 million CpG sites, thousands of genome-wide significant (q < 0.05) differentially methylated regions (DMRs) that distinguished DS from typical development and idiopathic developmental delay were identified. Machine learning feature selection refined these DMRs to 22 loci. The DS DMRs mapped to genes involved in neurodevelopment, metabolism, and transcriptional regulation. Based on comparisons with previous DS methylation studies and reference epigenomes, the hypermethylated DS DMRs were significantly (q < 0.05) enriched across tissues while the hypomethylated DS DMRs were significantly (q < 0.05) enriched for blood-specific chromatin states. A ~28 kb block of hypermethylation was observed on chromosome 21 in the RUNX1 locus, which encodes a hematopoietic transcription factor whose binding motif was the most significantly enriched (q < 0.05) overall and specifically within the hypomethylated DMRs. Finally, we also identified DMRs that distinguished DS NDBS based on the presence or absence of congenital heart disease (CHD). Together, these results not only demonstrate the utility of low-pass WGBS on NDBS samples for epigenome-wide association studies, but also provide new insights into the early life mechanisms of epigenomic dysregulation resulting from trisomy 21.
Health assessment and prognostics based on higher-order hidden semi-Markov models

This paper presents a new and flexible prognostics framework based on a higher‐order hidden semi‐Markov model (HOHSMM) for systems or components with unobservable health states and complex transition dynamics. The HOHSMM extends the basic hidden Markov model (HMM) by allowing the hidden state to depend on its more distant history and assuming generally distributed state duration. An effective Gibbs sampling algorithm is designed for statistical inference of the HOHSMM. We conduct a simulation study to evaluate the performance of the proposed HOHSMM sampler and examine the impacts of the distant‐history dependency. We design a decoding algorithm to estimate the hidden health states using the learned model. Remaining useful life is predicted using a simulation approach given the decoded hidden states. The practical utility of the proposed prognostics framework is demonstrated by a case study on National Aeronautics and Space Administration (NASA) turbofan engines. We further compare the RUL prediction performance between the proposed HOHSMM and a benchmark mixture of Gaussians HMM prognostics method. The results show that the HOHSMM‐based prognostics framework provides good hidden health‐state assessment and RUL estimation for complex systems.
Protocol of a randomized trial of acceptance and commitment therapy for fatigue interference in metastatic breast cancer.

Abstract Fatigue interference with activities, mood, and cognition is one of the most prevalent and distressing concerns of metastatic breast cancer patients. To date, there are no evidence-based interventions for reducing fatigue interference in metastatic breast cancer and other advanced cancer populations. In pilot studies, Acceptance and Commitment Therapy (ACT) has shown potential for reducing symptom-related suffering in cancer patients. The current Phase II trial seeks to more definitively examine the efficacy of telephone-based ACT for women with metastatic breast cancer who are experiencing fatigue interference. In this trial, 250 women are randomly assigned to either the ACT intervention or an education/support control condition. Women in both conditions attend six weekly 50-min telephone sessions. The primary aim of this study is to test the effect of telephone-based ACT on fatigue interference. Secondary outcomes include sleep interference, engagement in daily activities, and quality of life. Outcomes are assessed at baseline, 2 weeks post-intervention, and 3 and 6 months post-intervention. This trial also examines whether increases in psychological flexibility, defined as full awareness of the present moment while persisting in behaviors aligned with personal values, account for the beneficial effect of ACT on fatigue interference. After demonstrating ACT's efficacy, the intervention can be widely disseminated to clinicians who care for metastatic breast cancer patients. Our findings will also inform future ACT trials with various cancer populations and functional outcomes.
Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods

Representation learning with small labeled data have emerged in many problems, since the success of deep neural networks often relies on the availability of a huge amount of labeled data that is expensive to collect. To address it, many efforts have been made on training sophisticated models with few labeled data in an unsupervised and semi-supervised fashion. In this paper, we will review the recent progresses on these two major categories of methods. A wide spectrum of models will be categorized in a big picture, where we will show how they interplay with each other to motivate explorations of new ideas. We will review the principles of learning the transformation equivariant, disentangled, self-supervised and semi-supervised representations, all of which underpin the foundation of recent progresses. Many implementations of unsupervised and semi-supervised generative models have been developed on the basis of these criteria, greatly expanding the territory of existing autoencoders, generative adversarial nets (GANs) and other deep networks by exploring the distribution of unlabeled data for more powerful representations.
On induced subgraphs of the Hamming graph

In connection with his solution of the Sensitivity Conjecture, Hao Huang (arXiv: 1907.00847, 2019) asked the following question: Given a graph $G$ with high symmetry, what can we say about the smallest maximum degree of induced subgraphs of $G$ with $\alpha(G)+1$ vertices, where $\alpha(G)$ denotes the size of the largest independent set in $G$? We study this question for $H(n,k)$, the $n$-dimensional Hamming graph over an alphabet of size $k$. Generalizing a construction by Chung et al. (JCT-A, 1988), we prove that $H(n,k)$ has an induced subgraph with more than $\alpha(H(n,k))$ vertices and maximum degree at most $\lceil\sqrt{n}\rceil$. Chung et al. proved this statement for $k=2$ (the $n$-dimensional cube).
SpectreRewind: Leaking Secrets to Past Instructions

Transient execution attacks use microarchitectural covert channels to leak secrets that should not have been accessible during logical program execution. Commonly used micro-architectural covert channels are those that leave lasting footprints in the micro-architectural state, for example, a cache state change, from which the secret is recovered after the transient execution is completed. In this paper, we present SpectreRewind, a new approach to create and exploit contention-based covert channels for transient execution attacks. In our approach, a covert channel is established by issuing the necessary instructions logically before the transiently executed victim code. Unlike prior contention based covert channels, which require simultaneous multi-threading (SMT), SpectreRewind supports covert channels based on a single hardware thread, making it viable on systems where the attacker cannot utilize SMT. We show that contention on the floating point division unit on commodity processors can be used to create a high-performance (~100 KB/s), low-noise covert channel for transient execution attacks instead of commonly used flush+reload based cache covert channels. We also show that the proposed covert channel works in the JavaScript sandbox environment of a Chrome browser.
Luminous Quasars in Luminous Early-Type Host Galaxies

Some recent observations of nearby quasars with Hubble Space Telescope (HST) have apparently failed to detect host galaxies. We review the HST observations as well as near-infrared ground-based observations of the same objects. We find that the quasar hosts can be detected in the HST data if they are smoothed sufficiently to reveal low surface brightness. The smooth hosts are very difficult to detect with HST but are more easily visible in the deeper, ground-based IR images. The V - H colors obtained by combining the HST and IR data are compatible with normal galaxy colors at the redshifts of the quasars. This behavior can be explained if the hosts are massive early-type galaxies. All together, HST images have been reported for 15 luminous quasars, ~13 of which have smooth early-type hosts. This kind of galaxy therefore appears to be the most common host for a luminous quasar.
Hamiltonian Light-Front Field Theory: Recent Progress and Tantalizing Prospects

Fundamental theories, such as quantum electrodynamics and quantum chromodynamics promise great predictive power addressing phenomena over vast scales from the microscopic to cosmic scales. However, new non-perturbative tools are required for physics to span from one scale to the next. I outline recent theoretical and computational progress to build these bridges and provide illustrative results for Hamiltonian Light Front Field Theory. One key area is our development of basis function approaches that cast the theory as a Hamiltonian matrix problem while preserving a maximal set of symmetries. Regulating the theory with an external field that can be removed to obtain the continuum limit offers additional possibilities as seen in an application to the anomalous magnetic moment of the electron. Recent progress capitalizes on algorithm and computer developments for setting up and solving very large sparse matrix eigenvalue problems. Matrices with dimensions of 20 billion basis states are now solved on leadership-class computers for their low-lying eigenstates and eigenfunctions.
Dynamic density functional theory with hydrodynamic interactions and fluctuations.

We derive a closed equation for the empirical concentration of colloidal particles in the presence of both hydrodynamic and direct interactions. The ensemble average of our functional Langevin equation reproduces known deterministic Dynamic Density Functional Theory (DDFT) [M. Rex and H. Lowen, "Dynamical density functional theory with hydrodynamic interactions and colloids in unstable traps," Phys. Rev. Lett. 101(14), 148302 (2008)], and, at the same time, it also describes the microscopic fluctuations around the mean behavior. We suggest separating the ideal (non-interacting) contribution from additional corrections due to pairwise interactions. We find that, for an incompressible fluid and in the absence of direct interactions, the mean concentration follows Fick's law just as for uncorrelated walkers. At the same time, the nature of the stochastic terms in fluctuating DDFT is shown to be distinctly different for hydrodynamically-correlated and uncorrelated walkers. This leads to striking differences in the behavior of the fluctuations around Fick's law, even in the absence of pairwise interactions. We connect our own prior work [A. Donev, T. G. Fai, and E. Vanden-Eijnden, "A reversible mesoscopic model of diffusion in liquids: from giant fluctuations to Fick's law," J. Stat. Mech.: Theory Exp. (2014) P04004] on fluctuating hydrodynamics of diffusion in liquids to the DDFT literature, and demonstrate that the fluid cannot easily be eliminated from consideration if one wants to describe the collective diffusion in colloidal suspensions.
Deterministic single soliton generation and compression in microring resonators avoiding the chaotic region

A path within the parameter space of detuning and pump power is demonstrated in order to obtain a single cavity soliton (CS) with certainty in SiN microring resonators in the anomalous dispersion regime. Once the single CS state is reached, it is possible to continue a path to compress it, broadening the corresponding single free spectral range (FSR) Kerr frequency comb. The first step to achieve this goal is to identify the stable regions in the parameter space via numerical simulations of the Lugiato-Lefever equation (LLE). Later, using this identification, we define a path from the stable modulation instability (SMI) region to the stable cavity solitons (SCS) region avoiding the chaotic and unstable regions.
Decay of tails at equilibrium for FIFO join the shortest queue networks.

In join the shortest queue networks, incoming jobs are assigned to the shortest queue from among a randomly chosen subset of $D$ queues, in a system of $N$ queues; after completion of service at its queue, a job leaves the network. We also assume that jobs arrive into the system according to a rate-$\alpha N$ Poisson process, $\alpha 1$. We show under the above ansatz that, as $N\rightarrow\infty$, the tail of the equilibrium queue size exhibits a wide range of behavior depending on the relationship between $\beta$ and $D$. In particular, if $\beta>D/(D-1)$, the tail is doubly exponential and, if $\beta<D/(D-1)$, the tail has a power law. When $\beta=D/(D-1)$, the tail is exponentially distributed.
Optimal simultaneous detection and signal and noise power estimation

Simultaneous detection and estimation is important in many engineering applications. In particular, there are many applications where it is important to perform signal detection and Signal-to-Noise-Ratio (SNR) estimation jointly. Application of existing frameworks in the literature that handle simultaneous detection and estimation is not straightforward for this class of application. This paper therefore aims at bridging the gap between an existing framework, specifically the work by Middleton et al., and the mentioned application class by presenting a jointly optimal detector and signal and noise power estimators. The detector and estimators are given for the Gaussian observation model with appropriate conjugate priors on the signal and noise power. Simulation results affirm the superior performance of the optimal solution compared to the separate detection and estimation approaches.
Visibility-Aware Optimal Contagion of Malware Epidemics

Recent innovations in the design of computer viruses have led to new trade-offs for the attacker. Multiple variants of a malware may spread at different rates and have different levels of visibility to the network. In this work we examine the optimal strategies for the attacker so as to trade off the extent of spread of the malware against the need for stealth. We show that in the mean-field deterministic regime, this spread-stealth trade-off is optimized by computationally simple single-threshold policies. Specifically, we show that only one variant of the malware is spread by the attacker at each time, as there exists a time up to which the attacker prioritizes maximizing the spread of the malware, and after which she prioritizes stealth.
Prospects for identifying dark matter with CoGeNT

It has previously been shown that the excess of events reported by the CoGeNT collaboration could be generated by elastically scattering dark matter particles with a mass of approximately 5–15 GeV. This mass range is very similar to that required to generate the annual modulation observed by DAMA/LIBRA and the gamma rays from the region surrounding the Galactic Center identified within the data of the Fermi Gamma Ray Space Telescope. To confidently conclude that CoGeNT's excess is the result of dark matter, however, further data will likely be needed. In this paper, we make projections for the first full year of CoGeNT data, and for its planned upgrade. Not only will this body of data more accurately constrain the spectrum of nuclear recoil events, and corresponding dark matter parameter space, but will also make it possible to identify seasonal variations in the rate. In particular, if the CoGeNT excess is the product of dark matter, then one year of CoGeNT data will likely reveal an annual modulation with a significance of 2-3σ. The planned CoGeNT upgrade will not only detect such an annual modulation with high significance, but will be capable of measuring the energy spectrum of the modulation amplitude. These measurements will be essential to irrefutably confirming a dark matter origin of these events.
Temporally multiplexed storage of images in a gradient echo memory

We study the storage and retrieval of images in a hot atomic vapor using the gradient echo memory protocol. We demonstrate that this technique allows for the storage of multiple spatial modes. We study both spatial and temporal multiplexing by storing a sequence of two different images in the atomic vapor. The effect of atomic diffusion on the spatial resolution is discussed and characterized experimentally. For short storage time a normalized spatial cross-correlation between a retrieved image and its input of 88 % is reported.
Renormalizing an initial state

The intricate machinery of perturbative quantum field theory has largely been devoted to the 'dynamical' side of the theory: simple states are evolved in complicated ways. This article begins to address this lopsided treatment. Although it is rarely pos- sible to solve for the eigenstates of an interacting theory exactly, a general state and its evolution can nonetheless be constructed perturbatively in terms of the propagators and structures defined with respect to the free theory. The detailed form of the initial state in this picture is fixed by imposing suitable 'renormalization conditions' on the Green's functions. This technique is illustrated with an example drawn from inflation, where the presence of nonrenormalizable operators and where an expansion that naturally couples early times with short distances make the ability to start the theory at a finite initial time especially desirable.
WIYN open cluster study. LIX. Radial velocity membership of the evolved population of the old open cluster NGC 6791

The open cluster NGC 6791 has been the focus of much recent study due to its intriguing combination of old age and high metallicity (∼8 Gyr, [Fe/H] = +0.30), as well as its location within the Kepler field. As part of the WIYN Open Cluster Study, we present precise (σ = 0.38 km s{sup –1}) radial velocities for proper motion candidate members of NGC 6791 from Platais et al. Our survey, extending down to g' ∼ 16.8, is comprised of the evolved cluster population, including blue stragglers, giants, and horizontal branch stars. Of the 280 proper-motion-selected stars above our magnitude limit, 93% have at least one radial velocity measurement and 79% have three measurements over the course of at least 200 days, sufficient for secure radial-velocity-determined membership of non-velocity-variable stars. The Platais et al. proper motion catalog includes 12 anomalous horizontal branch candidates blueward of the red clump, of which we find only 4 to be cluster members. Three fall slightly blueward of the red clump and the fourth is consistent with being a blue straggler. The cleaned color-magnitude diagram shows a richly populated red giant branch and a blue straggler population. Half of the blue stragglers are in binaries.more » From our radial velocity measurement distribution, we find the cluster's radial velocity dispersion to be σ {sub c} = 0.62 ± 0.10 km s{sup –1}. This corresponds to a dynamical mass of ∼4600 M {sub ☉}.« less
Appearance of stable minimal spheres along the Ricci flow in positive scalar curvature

We construct spherical space forms (S3∕Γ,g) with positive scalar curvature and containing no stable embedded minimal surfaces such that the following happens along the Ricci flow starting at (S3∕Γ,g): a stable embedded minimal 2–sphere appears and a nontrivial singularity occurs. We also give in dimension 3 a general construction of Type I neckpinching and clarify the relationship between stable spheres and nontrivial Type I singularities of the Ricci flow. Some symmetry assumptions prevent the appearance of stable spheres, and this has consequences on the types of singularities which can occur for metrics with these symmetries.
The Supergravity dual of the BMN matrix model

We propose type IIA supergravity solutions dual to the 1/2 BPS vacua of the BMN matrix model. These dual solutions are analyzed using the Polchinski-Strassler method and have brane configurations of concentric shells of D2 branes (or NS5 branes) with various radii and D0 charge. These branes can be viewed as polarized from N D0 branes by a transverse R-R magnetic 6-form flux and an NS-NS 3-form flux. In the region far from branes, the solutions reduce to perturbation around the near horizon geometry of N D0 branes, by turning on these R-R and NS-NS fluxes, which are dual to the deformation of the BFSS matrix model by adding mass terms and the Myers term. The solutions with these additional fluxes preserve 16 supersymmetries. We also briefly discuss these fluxes in the possible supergravity duals of M(atrix) theories on less supersymmetric plane-waves.
Crater Mound Formation by Wind Erosion on Mars

Most of Mars' ancient sedimentary rocks by volume are in wind-eroded sedimentary mounds, but the connections between mound form and wind erosion are unclear. We perform mesoscale simulations of different crater and mound morphologies to understand the formation of sedimentary mounds. As crater depth increases, slope winds produce increased erosion near the base of the crater wall, forming mounds. Peak erosion rates occur when the crater depth is ~2 km. Mound evolution depends on the size of the host crater. In smaller craters mounds preferentially erode at the top, becoming more squat, while in larger craters mounds become steeper-sided. This agrees with observations where smaller craters tend to have proportionally shorter mounds, and larger craters have mounds encircled by moats. If a large-scale sedimentary layer blankets a crater, then as the layer recedes across the crater it will erode more towards the edges of the crater, resulting in a crescent-shaped moat. When a 160 km diameter mound-hosting crater is subject to a prevailing wind, the surface wind stress is stronger on the leeward side than on the windward side. This results in the center of the mound appearing to `march upwind' over time, and forming a `bat-wing' shape, as is observed for Mt. Sharp in Gale crater.
Whole-Disk Observations of Jupiter, Saturn, and Mars in Millimeter/Submillimeter Bands

New balloon-borne observations of whole-disk brightness ratios for Jupiter, Saturn, and Mars are reported in four millimeter/submillimeter bands of bandwidth ?? ? 1-2 cm-1. Using the effective planetary radii of Hildebrand et al., we find that TMars${r Mars}$ -->/TJupiter${r Jupiter}$ -->=1.158 ? 0.015, 1.189 ? 0.015, 1.470 ? 0.019, and 1.515 ? 0.019 and TSaturn${r Saturn}$ -->/TJupiter${r Jupiter}$ -->=0.833 ? 0.012, 0.758 ? 0.010, 0.818 ? 0.012, and 0.840 ? 0.012, at ?=5.7, 9.5, 16.5, and 22.5 cm-1, respectively. Using models for the brightness temperature of Mars, we also give the whole-disk brightness temperatures for Jupiter and Saturn for the four frequencies.