cssi/SciSciGPT-SciSciNet huggingface dataset:
The Impact of Unlicensed Access on Small-Cell Resource Allocation

Small-cells in licensed spectrum and unlicensed access via Wi-Fi are two commonly used options to reduce the demand for conventional macro-cellular networks and to provide expanded wireless services to low mobility users. The mix of these technologies depends on both the decisions made by wireless service providers (SPs) that seek to maximize revenue, and the allocation of licensed and unlicensed spectrum by regulators. In this paper, we study these interactions and consider heterogeneous cellular networks together with unlicensed access. Both a single monopoly SP and multiple competing SPs are investigated. The SPs split any available licensed spectrum into two separate bands for macro- and small-cells, which are then used to serve two types of users: mobile and fixed. Mobile users must be served by macro-cells only, whereas fixed users can be served by either macro- or small-cells, or alternatively by unlicensed access service. While the providers charge a (different) price per unit rate for licensed access services (macro- or small-cell), unlicensed access is free. We formulate a sequential game in which the users choose a service that yields the highest payoff, and the providers allocate bandwidth across macro-/small-cells. In general, the competition from unlicensed access results in inefficient (albeit unique) market equilibria, and in many cases all or some SPs allocate no resources to small-cell deployment. We conclude by showing how our framework can also be used to optimize the fraction of unlicensed spectrum when new bandwidth becomes available.
Probabilistic Analysis of Cyclic Packet Transmission Scheduling in WDM Optical Networks

We study the packet transmission scheduling problem with tuning delay in wavelength-division multiplexed (WDM) optical communication networks with tunable transmitters and fixed-tuned receivers. By treating the numbers of packets as random variables, we conduct probabilistic analysis of the average-case performance ratio for the cyclic packet transmission scheduling algorithm. Our numerical data as well as simulation results demonstrate that the average-case performance ratio of cyclic schedules is very close to one for reasonable system configurations and probability distributions of the numbers of packets. In particular, when the number of receivers that share a channel and/or the granularity of packet transmission are large, the average-case performance ratio approaches one. Better performance can be achieved by overlapping tuning delays with packet transmission. We derive a bound for the normalized tuning delay Δ such that tuning delay can be completely masked with high probability. Our study implies that by using currently available tunable optical transceivers, it is possible to build single-hop WDM networks that efficiently utilize all the wavelengths.
De Morgan Semi-Heyting and Heyting Algebras

The variety DMSH of semi-Heyting algebras with a De Morgan negation was introduced in [12] and an increasing sequence DMSHn of level n, n being a natural number, of its subvarieties was investigated in the series [12], [13], [14], [15], [16], and [17], of which the present paper is a sequel. In this paper, we prove two main results: Firstly, we prove that DMSH1-algebras of level 1 satisfy Stone identity, generalizing an earlier result that regular DMSH1-algebras of level 1 satisfy Stone identity. Secondly, we prove that the variety of DmsStSH of dually ms, Stone semi-Heyting algebras is at level 2. As an application, it is derived that the variety of De Morgan semi-Heyting algebras is also at level 2. It is also shown that these results are sharp.
Open String Creation By S-Branes

An sp-brane can be viewed as the creation and decay of an unstable D(p+1)-brane. It is argued that the decaying half of an sp-brane can be described by a variant of boundary Liouville theory. The pair creation of open strings by a decaying s-brane is studied in the minisuperspace approximation to the Liouville theory. In this approximation a Hagedorn-like divergence is found in the pair creation rate, suggesting the s-brane energy is rapidly transferred into closed string radiation.
Large monochromatic components in 3‐edge‐colored Steiner triple systems

It is known that in any $r$-coloring of the edges of a complete $r$-uniform hypergraph, there exists a spanning monochromatic component. Given a Steiner triple system on $n$ vertices, what is the largest monochromatic component one can guarantee in an arbitrary 3-coloring of the edges? Gyarfas proved that $(2n+3)/3$ is an absolute lower bound and that this lower bound is best possible for infinitely many $n$. On the other hand, we prove that for almost all Steiner triple systems the lower bound is actually $(1-o(1))n$. We obtain this result as a consequence of a more general theorem which shows that the lower bound depends on the size of a largest \emph{3-partite hole} (that is, sets $X_1, X_2, X_3$ with $|X_1|=|X_2|=|X_3|$ such that no edge intersects all of $X_1, X_2, X_3$) in the Steiner triple system (Gyarfas previously observed that the upper bound depends on this parameter). Furthermore, we show that this lower bound is tight unless the coloring has a particular structure. We also suggest a variety of other Ramsey problems in the setting of Steiner triple systems.
Channel Estimation in mmWave Hybrid MIMO System via Off-Grid Dirichlet Kernels

In this paper, we tackle channel estimation in millimeter-wave hybrid multiple-input multiple- output systems by considering off-grid effects. In particular, we assume that spatial parameters can take any value in the angular domain, and need not fall on predefined discretized angles. Instead of increasing the number of discretized points to combat off-grid effects, we use implicit Dirichlet kernel structure in the Fourier domain, which conventional compressed sensing methods do not use. We propose greedy low-complexity algorithms based on orthogonal matching pursuit (OMP); our core idea is to traverse the Dirichlet kernel peak using estimates of the discrete Fourier transform. We demonstrate the efficacy of our proposed algorithms compared to standard OMP reconstruction. Numerical results show that our proposed algorithms obtain smaller reconstruction errors when off-grid effects are accounted for.
Performance analysis of novel toxin-antidote CRISPR gene drive systems

CRISPR gene drive systems allow the rapid spread of a genetic construct throughout a population. Such systems promise novel strategies for the management of vector-borne diseases and invasive species by suppressing a target population or modifying it with a desired trait. However, current homing-type drives have two potential shortcomings. First, they can be thwarted by the rapid evolution of resistance. Second, they lack any mechanism for confinement to a specific target population. In this study, we conduct a comprehensive performance assessment of several new types of CRISPR-based gene drive systems employing toxin-antidote (TA) principles, which should be less prone to resistance and allow for the confinement of drives to a target population due to invasion frequency thresholds. The underlying principle of the proposed CRISPR toxin-antidote gene drives is to disrupt an essential target gene while also providing rescue by a recoded version of the target as part of the drive allele. Thus, drive alleles tend to remain viable, while wild-type targets are disrupted and often rendered nonviable, thereby increasing the relative frequency of the drive allele. Using individual-based simulations, we show that Toxin-Antidote Recessive Embryo (TARE) drives targeting an haplosufficient but essential gene (lethal when both copies are disrupted) can enable the design of robust, regionally confined population modification strategies with high flexibility in choosing promoters and targets. Toxin-Antidote Dominant Embryo (TADE) drives require a haplolethal target gene and a germline-restricted promoter, but they could permit faster regional population modification and even regionally confined population suppression. Toxin-Antidote Dominant Sperm (TADS) drives can be used for population modification or suppression. These drives are expected to spread rapidly and could employ a variety of promoters, but unlike TARE and TADE, they would not be regionally confined and also require highly specific target genes. Overall, our results suggest that CRISPR-based TA gene drives provide promising candidates for flexible ecological engineering strategies in a variety of organisms.
Rapid Circadian Entrainment in Models of Circadian Genes Regulation

The light-based minimum-time circadian entrainment problem for mammals, Neurospora, and Drosophila is studied based on the mathematical models of their circadian gene regulation. These models contain high order nonlinear differential equations. Two model simplification methods are applied to these high-order models: the phase response curves (PRC) and the Principal Orthogonal Decomposition (POD). The variational calculus and a gradient descent algorithm are applied for solving the optimal light input in the high-order models. As the results of the gradient descent algorithm rely heavily on the initial guesses, we use the optimal control of the PRC and the simplified model to initialize the gradient descent algorithm. In this paper, we present: (1) a general process for solving the minimum-time optimal control problem on highorder models; (2) the impacts of minimum-time optimal light on circadian gene transcription and protein synthesis.
A density gradient approach to topology optimization under design-dependent boundary loading

Abstract The paper proposes a density gradient based approach to topology optimization under design-dependent boundary loading. Since there is no explicit boundary representation in density-based topology optimization, the design-dependent boundary loads are implicitly imposed through a domain integration of spatial gradient of the density field. The density gradient based loading is formally derived and justified based on the smoothed boundary method for numerical solution of PDE. The Heaviside projection, density filtering and local refinement are combined to efficiently control the thickness of the loading interface and the number of elements within it. For problems with both loading and non-loading boundary, an auxiliary density field is introduced to keep track of the loading boundary. Both 2D and 3D heat conduction problems, linear elasticity problems and coupled thermoelastic problems under design-dependent boundary loading are presented to illustrate the effectiveness and efficiency of the method.
Enforcing Constraints for Time Series Prediction in Supervised, Unsupervised and Reinforcement Learning.

We assume that we are given a time series of data from a dynamical system and our task is to learn the flow map of the dynamical system. We present a collection of results on how to enforce constraints coming from the dynamical system in order to accelerate the training of deep neural networks to represent the flow map of the system as well as increase their predictive ability. In particular, we provide ways to enforce constraints during training for all three major modes of learning, namely supervised, unsupervised and reinforcement learning. In general, the dynamic constraints need to include terms which are analogous to memory terms in model reduction formalisms. Such memory terms act as a restoring force which corrects the errors committed by the learned flow map during prediction. For supervised learning, the constraints are added to the objective function. For the case of unsupervised learning, in particular generative adversarial networks, the constraints are introduced by augmenting the input of the discriminator. Finally, for the case of reinforcement learning and in particular actor-critic methods, the constraints are added to the reward function. In addition, for the reinforcement learning case, we present a novel approach based on homotopy of the action-value function in order to stabilize and accelerate training. We use numerical results for the Lorenz system to illustrate the various constructions.
The giant pouched rat (Cricetomys ansorgei) olfactory receptor repertoire

For rodents, olfaction is essential for locating food, recognizing mates and competitors, avoiding predators, and navigating their environment. It is thought that rodents may have expanded olfactory receptor repertoires in order to specialize in olfactory behavior. Despite being the largest clade of mammals and depending on olfaction relatively little work has documented olfactory repertoires outside of conventional laboratory species. Here we report the olfactory receptor repertoire of the African giant pouched rat (Cricetomys ansorgei), a Muroid rodent distantly related to mice and rats. The African giant pouched rat is notable for its large cortex and olfactory bulbs relative to its body size compared to other sympatric rodents, which suggests anatomical elaboration of olfactory capabilities. We hypothesized that in addition to anatomical elaboration for olfaction, these pouched rats might also have an expanded olfactory receptor repertoire to enable their olfactory behavior. We examined the composition of the olfactory receptor repertoire to better understand how their sensory capabilities have evolved. We identified 1145 intact olfactory genes, and 260 additional pseudogenes within 301 subfamilies from the African giant pouched rat genome. This repertoire is similar to mice and rats in terms of size, pseudogene percentage and number of subfamilies. Analyses of olfactory receptor gene trees revealed that the pouched rat has 6 expansions in different subfamilies compared to mice, rats and squirrels. We identified 81 orthologous genes conserved among 4 rodent species and an additional 147 conserved genes within the Muroid rodents. The orthologous genes shared within Muroidea suggests that there may be a conserved Muroid-specific olfactory receptor repertoire. We also note that the description of this repertoire can serve as a complement to other studies of rodent olfaction, as the pouched rat is an outgroup within Muroidea. Thus, our data suggest that African giant pouched rats are capable of both natural and trained olfactory behaviors with a typical Muriod olfactory receptor repertoire.
The Development and Characterization of an scFv-Fc Fusion-Based Gene Therapy to Reduce the Psychostimulant Effects of Methamphetamine Abuse

Methamphetamine (METH) continues to be among the most addictive and abused drugs in the United States. Unfortunately, there are currently no Food and Drug Administration-approved pharmacological treatments for METH-use disorder. We have previously explored the use of adeno-associated viral (AAV)-mediated gene transfer of an anti-METH monoclonal antibody. Here, we advance our approach by generating a novel anti-METH single-chain variable fragment (scFv)-Fc fusion construct (termed 7F9-Fc) packaged into AAV serotype 8 vector (called AAV-scFv-Fc) and tested in vivo and ex vivo. A range of doses [1 × 1010, 1 × 1011, and 1 × 1012 vector copies (vcs)/mouse] were administered to mice, eliciting a dose-dependent expression of 7F9-Fc in serum with peak circulating concentrations of 48, 1785, and 3831 µg/ml, respectively. Expressed 7F9-Fc exhibited high-affinity METH binding, IC50 = 17 nM. Between days 21 and 35 after vector administration, at both 1 × 1011 vc/mouse and 1 × 1012 vc/mouse doses, the AAV-7F9-Fc gene therapy significantly decreased the potency of METH in locomotor assays. On day 116 post-AAV administration, mice expressing 7F9-Fc sequestered over 2.5 times more METH in the serum than vehicle-treated mice, and METH concentrations in the brain were reduced by 1.2 times the value for vehicle mice. These data suggest that an AAV-delivered anti-METH Fc fusion antibody could be used to persistently reduce concentrations of METH in the central nervous system. SIGNIFICANCE STATEMENT: In this manuscript, we describe the testing of a novel antimethamphetamine (METH) single-chain variable fragment-Fc fusion protein delivered in mice using gene therapy. The results suggest that the gene therapy delivery system can lead to the production of significant antibody concentrations that mitigate METH's psychostimulant effects in mice over an extended time period.
Binaural Audio Source Remixing with Microphone Array Listening Devices

Augmented listening devices, such as hearing aids and augmented reality headsets, enhance human perception by changing the sounds that we hear. Microphone arrays can improve the performance of listening systems in noisy environments, but most array-based listening systems are designed to isolate a single sound source from a mixture. This work considers a source-remixing filter that alters the relative level of each source independently. Remixing rather than separating sounds can help to improve perceptual transparency: it causes less distortion to the signal spectrum and especially to the interaural cues that humans use to localize sounds in space.
Anomalous Muscles and Nerves in the Hand of a 94‐year‐old Cadaver‐A Case Report

Abstract Introduction During an anatomical dissection of the distal upper extremities, numerous muscular and nervous anomalies were found in the forearm and hand of a 94-year-old cadaver. These anomalies are clinically relevant with regard to medical or surgical interventions. Presentation of case The presence of a “flexor digiti minimi longus” muscle was observed passing through Guyon’s canal; to our knowledge this passageway has never been previously reported. An aberrant first lumbrical with three origins was noted. Additionally, numerous atypical nerves were found innervating the hand; the dorsal branch of the ulnar nerve contributed to cutaneous innervation of the palm of the hand (Kaplan’s anastomosis), the superficial ulnar nerve provided muscular innervation to the flexor digiti minimi brevis muscle, and two connections between the common palmar digital branches of the median and superficial ulnar nerves were observed (Berrettini anastomosis). Discussion Here, we describe an extranumerary muscle associated with the hypothenar group of muscles. We also describe unusual origins of the first lumbrical muscle, and atypical cutaneous and muscular innervation to the palm of the hand. Conclusion Clinically, understanding the existence of these anatomical variations may influence medical care or surgical procedures.
In search of substitution between foreign production and exports

Abstract Are foreign production and exports substitutes or complements? Standard theory of the multinational corporation (MNC) assumes substitution, while previous empirical work examining the relationship has generally found strong evidence of complementarity. This study examines product-level data, which more closely fits the assumption of a single-product firm often used in MNC theory, and finds substantial evidence for both a substitution and a complementarity effect between affiliate production and exports with Japanese automobile parts for the US market. I also test for and find evidence of substitution using product-level data on a set of Japanese-produced final consumer goods.
Default, Currency Crises, and Sovereign Credit Ratings

Sovereign credit ratings play an important part in determining countries' access to international capital markets and the terms of that access. In principle, there is no reason to expect that sovereign credit ratings should systematically predict currency crises. In practice, in emerging market economies there is a strong link between currency crises and default. Hence if credit ratings are forward-looking and currency crises in emerging market economies are linked to defaults, it follows that downgrades in credit ratings should systematically precede currency crises. This article presents results suggesting that sovereign credit ratings systematically fail to predict currency crises but do considerably better in predicting defaults. Downgrades in credit ratings usually follow currency crises, possibly suggesting that currency instability increases the risk of default.
Nominal GDP targeting for developing countries

Abstract Interest in nominal GDP (NGDP) targeting has come in the context of large advanced economies. Developing countries are better suited for it, however, in light of big supply shocks and terms of trade shocks, such as monsoon rains and oil import price shocks in the case of India. Under annual inflation targeting (IT), the full impact of adverse supply shocks is felt as lost real GDP. NGDP targeting automatically accommodates such shocks, while retaining the advantage of anchoring expectations. We derive the condition under which NGDP targeting would dominate other regimes such as annual IT, to achieve objectives of output and price stability. We estimate key parameters for the case of India and conclude that the condition may indeed hold.
Credit in a Random Matching Model with Private Information

We consider a random matching model where agents have complete access to each others' histories. Exchange is motivated by risk sharing, given random unobservable incomes. There is capital accumulation and an endogenous interest rate. The key feature of this environment is that information is mobile across locations, while there are frictions associated with transporting goods. Optimal allocations in the dynamic private information environment resemble real-world credit arrangements in that there are credit balances, credit limits, and installment payments. The steady state has the property that there is a limiting distribution of expected utility entitlements with mobility and a positive fraction of agents who are credit constrained.Journal of Economic LiteratureClassification Numbers: D8, E1.
Addressing the natural resource curse: An illustration from Nigeria

Nigeria has been a disastrous development experience. On just about every conceivable metric, Nigeria’s performance since independence has been dismal. In PPP terms, Nigeria’s per capita GDP was $1113 in 1970 and is estimated to have remained at $1084 in 2000. The latter figure places Nigeria amongst the 15 poorest nations in the world for which such data are available.
Income convergence and the catch-up index

Abstract Defining a catch-up index that measures rich-poor country income convergence and comparing it to within group convergence (β-convergence), defining relative convergence as decrease in rich-poor country income ratio and absolute convergence as decrease in rich-poor country income gap, we derive an equation for years for income equality to the frontier (full convergence). Focusing on relatively homogeneous countries of Sub-Saharan Africa and South Asia, we show neither region has achieved either within group convergence or significant catching-up since 1951, and 21 of the 28 countries exhibiting catching-up in the most recent 21-years period, using US as the frontier, show falling behind over the longer period. We show years for full convergence depend also on the initial conditions; the neo-classical hypothesis that poorer countries grow faster means relative convergence, relative convergence is a necessary but not sufficient condition for absolute convergence; “Iron law of convergence” does not hold; and within group convergence is consistent with poorer countries in the group diverging absolutely while richer countries converge.
Estimating Restricted Cointegrating Vectors

This article suggests the use of simple minimum-distance methods to estimate restricted cointegrating vectors. The method directly employs minimum-distance methods on unrestricted cointegrating matrices estimated in the usual way to estimate restricted parameters that are linearly or nonlinearly related to the unrestricted cointegrating vector coefficients. The limiting distribution of the estimates and the usual test for the restrictions are derived. A Monte Carlo experiment is undertaken to examine the effectiveness of these methods for cointegrating vectors.
A Nested Mixture Model for Genomic Prediction Using Whole-Genome SNP Genotypes

We propose a novel model (BayesN) for genomic prediction, where multiple markers in a small segment are simultaneously fitted to jointly capture the effect of major genes (QTL) in the segment. Compared with BayesB, in which the effects of neighboring markers are a prioriassumed to be independent, BayesN gave higher accuracies of prediction and required less computing effort. BayesN is an accurate and practical method for analyzing high-density markers, especially for traits influenced by rare QTL alleles
Targeted cell ablation in zebrafish using optogenetic transcriptional control.

Cell ablation is a powerful method for elucidating the contributions of individual cell populations to embryonic development and tissue regeneration. Targeted cell loss in whole organisms has been typically achieved through expression of a cytotoxic or prodrug-activating gene product in the cell type of interest. This approach depends on the availability of tissue-specific promoters, and it does not allow further spatial selectivity within the promoter-defined region(s). To address this limitation, we have utilized the light-inducible GAVPO transactivator in combination with two genetically encoded cell-ablation technologies: the nitroreductase/nitrofuran system and a cytotoxic variant of the M2 ion channel. Our studies establish ablative methods that provide the tissue specificity afforded by cis-regulatory elements and the conditionality of optogenetics. Our studies also demonstrate differences between the nitroreductase and M2 systems that influence their efficacies for specific applications. Using this integrative approach, we have ablated cells in zebrafish embryos with both spatial and temporal control.
Cosmological constant in coherent quantum gravity

It is argued that quantum states of geometry, like those of particles, should be coherent on light cones of any size. An exact classical solution, the gravitational shock wave of a relativistic poi...
A Decision Tree Learning Approach for Mining Relationship-Based Access Control Policies

Relationship-based access control (ReBAC) provides a high level of expressiveness and flexibility that promotes security and information sharing, by allowing policies to be expressed in terms of chains of relationships between entities. ReBAC policy mining algorithms have the potential to significantly reduce the cost of migration from legacy access control systems to ReBAC, by partially automating the development of a ReBAC policy. This paper presents new algorithms, called DTRM (Decision Tree ReBAC Miner) and DTRM-, based on decision trees, for mining ReBAC policies from access control lists (ACLs) and information about entities. Compared to state-of-the-art ReBAC mining algorithms, our algorithms are significantly faster, achieve comparable policy quality, and can mine policies in a richer language.
Efficient and Round-Optimal Oblivious Transfer and Commitment with Adaptive Security

We construct the most efficient two-round adaptively secure bit-OT in the Common Random String (\(\text {CRS} \)) model. The scheme is UC secure under the Decisional Diffie-Hellman (DDH) assumption. It incurs \(\mathcal {O}(1)\) exponentiations and sends \(\mathcal {O}(1)\) group elements, whereas the state of the art requires \(\mathcal {O}(\kappa ^2)\) exponentiations and communicates \(\text {poly}(\kappa )\) bits, where \(\kappa \) is the computational security parameter. Along the way, we obtain several other efficient UC-secure OT protocols under DDH: The most efficient yet two-round adaptive string-OT protocol assuming global programmable random oracle. Furthermore, the protocol can be made non-interactive in the simultaneous message setting, assuming random inputs for the sender. The first two-round string-OT with amortized constant exponentiations and communication overhead which is secure in the global observable random oracle model. The first two-round receiver equivocal string-OT in the \(\text {CRS} \) model that incurs constant computation and communication overhead.
A DAA Scheme Requiring Less TPM Resources.

Direct anonymous attestation (DAA) is a special digital signature primitive, which provides a balance between signer authentication and privacy. One of the most interesting properties that makes this primitive attractive in practice is its construction of signers. The signer role of DAA is split between two entities, a principal signer (a trusted platform module (TPM)) with limited computational capability and an assistant signer (a computer platform into which the TPM is embedded) with more computational power but less security tolerance. Our first contribution in this paper is a new DAA scheme that requires very few TPM resources. In fact the TPM has only to perform two exponentiations for the DAA Join algorithm and three exponentiations for the DAA Signing algorithm. We show that this new scheme has better performance than the existing DAA schemes and is provable secure based on the q-SDH problem and DDH problem under the random oracle model. Our second contribution is a modification of the DAA security model defined in [13] to cover the property of non-frameability.
Separating the communication complexity of truthful and non-truthful combinatorial auctions

We prove the first separation in the approximation guarantee achievable by truthful and non-truthful combinatorial auctions with polynomial communication. Specifically, we prove that any truthful auction guaranteeing a (34−1240+є)-approximation for two buyers with XOS valuations over m items requires exp(Ω(e2 · m)) communication whereas a non-truthful auction by Feige [J. Comput. 2009] is already known to achieve a 34-approximation in (m) communication. We obtain our lower bound for truthful auctions by proving that any simultaneous auction (not necessarily truthful) which guarantees a (34−1240+e)-approximation requires communication exp(Ω(e2 · m)), and then apply the taxation complexity framework of Dobzinski [FOCS 2016] to extend the lower bound to all truthful auctions (including interactive truthful auctions).
Regulating short‐term rental housing: Evidence from new orleans

This study examines the effects of regulations targeting Airbnb and other short-termrental (STR) suppliers in the urban center of New Orleans. I show that although the new ordinances reduced participation in the STR market as intended, STR usage actually increased in the neighborhoods adjacent to areas the most affected by the regulations.I subsequently show that the new regulations depressed property values in the neighborhoods facing the tightest regulations by approximately 30%, implying that homeowners factor into their housing purchasing decisions the option to participate in the STR market.
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings

Reinforcement learning (RL) in real-world safety-critical target settings like urban driving is hazardous, imperiling the RL agent, other agents, and the environment. To overcome this difficulty, we propose a "safety-critical adaptation" task setting: an agent first trains in non-safety-critical "source" environments such as in a simulator, before it adapts to the target environment where failures carry heavy costs. We propose a solution approach, CARL, that builds on the intuition that prior experience in diverse environments equips an agent to estimate risk, which in turn enables relative safety through risk-averse, cautious adaptation. CARL first employs model-based RL to train a probabilistic model to capture uncertainty about transition dynamics and catastrophic states across varied source environments. Then, when exploring a new safety-critical environment with unknown dynamics, the CARL agent plans to avoid actions that could lead to catastrophic states. In experiments on car driving, cartpole balancing, half-cheetah locomotion, and robotic object manipulation, CARL successfully acquires cautious exploration behaviors, yielding higher rewards with fewer failures than strong RL adaptation baselines. Website at this https URL.
Dietary sugar inhibits satiation by decreasing the central processing of sweet taste

From humans to vinegar flies, exposure to diets rich in sugar and fat lowers taste sensation, changes food choices, and promotes feeding. However, how these peripheral alterations influence eating is unknown. Here we used the genetically tractable organism D. melanogaster to define the neural mechanisms through which this occurs. We characterized a population of protocerebral anterior medial dopaminergic neurons (PAM DANs) that innervates the β'2 compartment of the mushroom body and responds to sweet taste. In animals fed a high sugar diet, the response of PAM-β'2 to sweet stimuli was reduced and delayed, and sensitive to the strength of the signal transmission out of the sensory neurons. We found that PAM-β'2 DANs activity controls feeding rate and satiation: closed-loop optogenetic activation of β'2 DANs restored normal eating in animals fed high sucrose. These data argue that diet-dependent alterations in taste weaken satiation by impairing the central processing of sensory signals.
SARS-CoV-2 infection in a neutropenic pediatric patient with leukemia: Addressing the need for universal guidelines for treatment of SARS-CoV-2-positive, immunocompromised patients.

In December 2019, a novel coronavirus (Sars-CoV-2 ) emerged from Wuhan, Hubei province, China, and has spread worldwide, with more than 4 million confirmed cases[1,2,3]. Available literature on the clinical characteristics and natural history of pediatric patients infected with Sars-CoV-2 is limited and less has been established regarding guidelines for the treatment of immunocompromised pediatric patients. This is a case report on the clinical course and management of a 6 year old female with acute lymphoblastic lymphoma with Sars-CoV-2. The goal is to highlight the need for management guidelines in the care of pediatric cancer patients with Sars-CoV-2.
Genetic architecture of a body colour cline in Drosophila americana.

Phenotypic variation within a species is often structured geographically in clines. In Drosophila americana, a longitudinal cline for body colour exists within North America that appears to be due to local adaptation. The tan and ebony genes have been hypothesized to contribute to this cline, with alleles of both genes that lighten body colour found in D. americana. These alleles are similar in sequence and function to the allele fixed in D. americana's more lightly pigmented sister species, Drosophila novamexicana. Here, we examine the frequency and geographic distribution of these D. novamexicana-like alleles in D. americana. Among alleles from over 100 strains of D. americana isolated from 21 geographic locations, we failed to identify additional alleles of tan or ebony with as much sequence similarity to D. novamexicana as the D. novamexicana-like alleles previously described. However, using genetic analysis of 51 D. americana strains derived from 20 geographic locations, we identified one new allele of ebony and one new allele of tan segregating in D. americana that are functionally equivalent to the D. novamexicana allele. An additional 5 alleles of tan also showed marginal evidence of functional similarity. Given the rarity of these alleles, however, we conclude that they are unlikely to be driving the pigmentation cline. Indeed, phenotypic distributions of the 51 backcross populations analysed indicate a more complex genetic architecture, with diversity in the number and effects of loci altering pigmentation observed both within and among populations of D. americana. This genetic heterogeneity poses a challenge to association studies and genomic scans for clinal variation, but might be common in natural populations.
Breakage of Hydrophobic Contacts Limits the Rate of Passive Lipid Exchange between Membranes.

The maintenance of heterogeneous lipid compositions among cellular membranes is key to biological function. Yet, even the simplest process that could be responsible for maintaining proper lipid dis...
Evidence for a Growth Zone for Deep-Subsurface Microbial Clades in Near-Surface Anoxic Sediments.

ABSTRACT Global marine sediments harbor a large and highly diverse microbial biosphere, but the mechanism by which this biosphere is established during sediment burial is largely unknown. During burial in marine sediments, concentrations of easily metabolized organic compounds and total microbial cell abundance decrease. However, it is unknown whether some microbial clades increase with depth. We show total population increases in 38 microbial families over 3 cm of sediment depth in the upper 7.5 cm of White Oak River (WOR) estuary sediments. Clades that increased with depth were more often associated with one or more of the following: anaerobes, uncultured, or common in deep marine sediments relative to those that decreased. Maximum doubling times (in situ steady-state growth rates could be faster to balance cell decay) were estimated as 2 to 25 years by combining sedimentation rate with either quantitative PCR (qPCR) or the product of the fraction read abundance of 16S rRNA genes and total cell counts (FRAxC). Doubling times were within an order of magnitude of each other in two adjacent cores, as well as in two laboratory enrichments of Cape Lookout Bight (CLB), NC, sediments (average difference of 28% ± 19%). qPCR and FRAxC in sediment cores and laboratory enrichments produced similar doubling times for key deep subsurface uncultured clades Bathyarchaeota (8.7 ± 1.9 years) and Thermoprofundales/MBG-D (4.1 ± 0.7 years). We conclude that common deep subsurface microbial clades experience a narrow zone of growth in shallow sediments, offering an opportunity for selection of long-term subsistence traits after resuspension events. IMPORTANCE Many studies show that the uncultured microbes that dominate global marine sediments do not actually increase in population size as they are buried in marine sediments; rather, they exist in a sort of prolonged torpor for thousands of years. This is because, although studies have shown biomass turnover in these clades, no evidence has ever been found that deeper sediments have larger populations for specific clades than shallower layers. We discovered that they actually do increase population sizes during burial, but only in the upper few centimeters. This suggests that marine sediments may be a vast repository of mostly nongrowing microbes with a thin and relatively rapid area of cell abundance increase in the upper 10 cm, offering a chance for subsurface organisms to undergo natural selection.
Kratos: multi-user multi-device-aware access control system for the smart home

In a smart home system, multiple users have access to multiple devices, typically through a dedicated app installed on a mobile device. Traditional access control mechanisms consider one unique trusted user that controls the access to the devices. However, multi-user multi-device smart home settings pose fundamentally different challenges to traditional single-user systems. For instance, in a multi-user environment, users have conflicting, complex, and dynamically changing demands on multiple devices, which cannot be handled by traditional access control techniques. To address these challenges, in this paper, we introduce Kratos, a novel multi-user and multi-device-aware access control mechanism that allows smart home users to flexibly specify their access control demands. Kratos has three main components: user interaction module, back-end server, and policy manager. Users can specify their desired access control settings using the interaction module which are translated into access control policies in the backend server. The policy manager analyzes these policies and initiates negotiation between users to resolve conflicting demands and generates final policies. We implemented Kratos and evaluated its performance on real smart home deployments featuring multi-user scenarios with a rich set of configurations (309 different policies including 213 demand conflicts and 24 restriction policies). These configurations included five different threats associated with access control mechanisms. Our extensive evaluations show that Kratos is very effective in resolving conflicting access control demands with minimal overhead, and robust against different attacks.
Genomic Characterization and Curation of UCEs Improves Species Tree Reconstruction.

Ultraconserved genomic elements (UCEs) are generally treated as independent loci in phylogenetic analyses. The identification pipeline for UCE probes does not require prior knowledge of genetic identity, only selecting loci that are highly conserved, single copy, without repeats, and of a particular length. Here, we characterized UCEs from 11 phylogenomic studies across the animal tree of life, from birds to marine invertebrates. We found that within vertebrate lineages, UCEs are mostly intronic and intergenic, while in invertebrates, the majority are in exons. We then curated four different sets of UCE markers by genomic category from five different studies including: birds, mammals, fish, Hymenoptera (ants, wasps, and bees), and Coleoptera (beetles). Of genes captured by UCEs, we find that many are represented by two or more UCEs, corresponding to nonoverlapping segments of a single gene. We considered these UCEs to be nonindependent, merged all UCEs that belonged to a particular gene, constructed gene and species trees, and then evaluated the subsequent effect of merging cogenic UCEs on gene and species tree reconstruction. Average bootstrap support for merged UCE gene trees was significantly improved across all data sets apparently driven by the increase in loci length. Additionally, we conducted simulations and found that gene trees generated from merged UCEs were more accurate than those generated by unmerged UCEs. As loci length improves gene tree accuracy, this modest degree of UCE characterization and curation impacts downstream analyses and demonstrates the advantages of incorporating basic genomic characterizations into phylogenomic analyses. [Anchored hybrid enrichment; ants; ASTRAL; bait capture; carangimorph; Coleoptera; conserved nonexonic elements; exon capture; gene tree; Hymenoptera; mammal; phylogenomic markers; songbird; species tree; ultraconserved elements; weevils.]
Conditional Expectation, Entropy, and Transport for Convex Gibbs Laws in Free Probability

Let $(X_1,\dots,X_m)$ be self-adjoint non-commutative random variables distributed according to the free Gibbs law given by a sufficiently regular convex and semi-concave potential $V$, and let $(S_1,\dots,S_m)$ be a free semicircular family. We show that conditional expectations and conditional non-microstates free entropy given $X_1$, \dots, $X_k$ arise as the large $N$ limit of the corresponding conditional expectations and entropy for the random matrix models associated to $V$. Then by studying conditional transport of measure for the matrix models, we construct an isomorphism $\mathrm{W}^*(X_1,\dots,X_m) \to \mathrm{W}^*(S_1,\dots,S_m)$ which maps $\mathrm{W}^*(X_1,\dots,X_k)$ to $\mathrm{W}^*(S_1,\dots,S_k)$ for each $k = 1, \dots, m$, and which also witnesses the Talagrand inequality for the law of $(X_1,\dots,X_m)$ relative to the law of $(S_1,\dots,S_m)$.
A Predictive Model of the Temperature-Dependent Inactivation of Coronaviruses

The COVID-19 pandemic has stressed healthcare systems and supply lines, forcing medical doctors to risk infection by decontaminating and reusing single-use personal protective equipment. The uncertain future of the pandemic is compounded by limited data on the ability of the responsible virus, SARS-CoV-2, to survive across various climates, preventing epidemiologists from accurately modeling its spread. However, a detailed thermodynamic analysis of experimental data on the inactivation of SARS-CoV-2 and related coronaviruses can enable a fundamental understanding of their thermal degradation that will help model the COVID-19 pandemic and mitigate future outbreaks. This work introduces a thermodynamic model that synthesizes existing data into an analytical framework built on first principles, including the rate law for a first-order reaction and the Arrhenius equation, to accurately predict the temperature-dependent inactivation of coronaviruses. The model provides much-needed thermal decontamination guidelines for personal protective equipment, including masks. For example, at 70 °C, a 3-log (99.9%) reduction in virus concentration can be achieved, on average, in 3 min (under the same conditions, a more conservative decontamination time of 39 min represents the upper limit of a 95% interval) and can be performed in most home ovens without reducing the efficacy of typical N95 masks as shown in recent experimental reports. This model will also allow for epidemiologists to incorporate the lifetime of SARS-CoV-2 as a continuous function of environmental temperature into models forecasting the spread of the pandemic across different climates and seasons.
Active learning for efficiently training emulators of computationally expensive mathematical models

An emulator is a fast-to-evaluate statistical approximation of a detailed mathematical model (simulator). When used in lieu of simulators, emulators can expedite tasks that require many repeated evaluations, such as sensitivity analyses, policy optimization, model calibration, and value-of-information analyses. Emulators are developed using the output of simulators at specific input values (design points). Developing an emulator that closely approximates the simulator can require many design points, which becomes computationally expensive. We describe a self-terminating active learning algorithm to efficiently develop emulators tailored to a specific emulation task, and compare it with algorithms that optimize geometric criteria (random latin hypercube sampling and maximum projection designs) and other active learning algorithms (treed Gaussian Processes that optimize typical active learning criteria). We compared the algorithms' root mean square error (RMSE) and maximum absolute deviation from the simulator (MAX) for seven benchmark functions and in a prostate cancer screening model. In the empirical analyses, in simulators with greatly varying smoothness over the input domain, active learning algorithms resulted in emulators with smaller RMSE and MAX for the same number of design points. In all other cases, all algorithms performed comparably. The proposed algorithm attained satisfactory performance in all analyses, had smaller variability than the treed Gaussian Processes, and, on average, had similar or better performance as the treed Gaussian Processes in six out of seven benchmark functions and in the prostate cancer model.