A land of milk and honey with streets paved with gold: do emigrants have over-optimistic expectations about incomes abroad?

Millions of people emigrate every year in search of better economic and social opportunities. Anecdotal evidence suggests that emigrants may have over-optimistic expectations about the incomes they can earn abroad, resulting in excessive migration pressure, and in disappointment amongst those who do migrate. Yet there is almost no statistical evidence on how accurately these emigrants predict the incomes that they will earn working abroad. In this paper we combine a natural emigration experiment with unique survey data on would-be emigrants’ probabilistic expectations about employment and incomes in the migration destination. Our procedure enables us to obtain moments and quantiles of the subjective distribution of expected earnings in the destination country. We find a significant underestimation of both unconditional and conditional labor earnings at all points in the distribution. This under-estimation appears driven in part by potential migrants placing too much weight on the negative employment experiences of some migrants, and by inaccurate information flows from extended family, who may be trying to moderate remittance demands by understating incomes

High-Frequency Temperature Variability Mirrors Fixed Differences in Thermal Limits of the Massive Coral \u3ci\u3ePorites lobata\u3c/i\u3e

Spatial heterogeneity in environmental characteristics can drive adaptive differentiation when contrasting environments exert divergent selection pressures. This environmental and genetic heterogeneity can substantially influence population and community resilience to disturbance events. Here, we investigated corals from the highly variable back-reef habitats of Ofu Island in American Samoa that thrive in thermal conditions known to elicit widespread bleaching and mortality elsewhere. To investigate the relative importance of acclimation versus site of origin in shaping previously observed differences in coral tolerance limits at Ofu Island, specimens of the common Indo-Pacific coral Porites lobata from locations with differing levels of thermal variability were acclimated to low and high thermal variation in controlled common garden aquaria. Overall, there were minimal effects of the acclimation exposure. Corals native to the site with the highest level of daily variability grew fastest, regardless of acclimation treatment. When exposed to lethal thermal stress, corals native to both variable sites contained elevated levels of heat shock proteins and maintained photosynthetic performance for 1–2 days longer than corals from the stable environment. Despite being separated by \u3c5 \u3ekm, there was significant genetic differentiation among coral colonies (FST=0.206, PCladocopium sp. (ITS type C15). Our study demonstrates consistent signatures of adaptation in growth and stress resistance in corals from naturally thermally variable habitats, suggesting that differences in the amount of thermal variability may be an important contributor to adaptive differentiation in reef-building corals

Inhibition of CDK activity and PCNA-dependent DNA replication by p21 is blocked by interaction with the HPV-16 E7 oncoprotein

p21 inhibits cyclin-dependent kinase (CDK) activity and proliferating cell nuclear antigen (PCNA)-dependent DNA replication by binding to CDK/cyclin complexes and to PCNA through distinct domains. The human papillomavirus (HPV)-16 E7 oncoprotein (16E7) abrogated a DNA damage-induced cell cycle arrest in vivo, despite high levels of p21. Using cell lysates and purified proteins we show that 16E7 prevented p21 both from inhibiting CDK2/cyclin E activity and PCNA-dependent DNA replication, whereas the nononcogenic HPV-6 E7 had reduced effects. Inactivation of both inhibitory functions of p21 was attained through binding between 16E7 and sequences in the carboxy-terminal end of p21 that overlap with the PCNA-binding site and the second p21 cyclin-binding motif. These data imply that the carboxyl terminus of p21 simultaneously modulates both CDK activity and PCNA-dependent DNA replication and that a single protein, 16E7, can override this modulation to disrupt normal cell cycle control

Excess noise in GaAs and AlGaAs avalanche photodiodes with GaSb absorption regions—composite structures grown using interfacial misfit arrays

Interfacial misfit arrays were embedded within two avalanche photodiode (APD) structures. This allowed GaSb absorption layers to be combined with wide-bandgap multiplication regions, consisting of GaAs and Al0.8Ga0.2As, respectively. The GaAs APD represents the simplest case. The Al0.8Ga0.2As APD shows reduced dark currents of 5.07 μAcm−2 at 90% of the breakdown voltage, and values for effective below 0.2. Random-path-length modeled excess noise is compared with experimental data, for both samples. The designs could be developed further, allowing operation to be extended to longer wavelengths, using other established absorber materials which are lattice matched to GaSb

Epigenetic Chromatin Silencing: Bistability and Front Propagation

The role of post-translational modification of histones in eukaryotic gene regulation is well recognized. Epigenetic silencing of genes via heritable chromatin modifications plays a major role in cell fate specification in higher organisms. We formulate a coarse-grained model of chromatin silencing in yeast and study the conditions under which the system becomes bistable, allowing for different epigenetic states. We also study the dynamics of the boundary between the two locally stable states of chromatin: silenced and unsilenced. The model could be of use in guiding the discussion on chromatin silencing in general. In the context of silencing in budding yeast, it helps us understand the phenotype of various mutants, some of which may be non-trivial to see without the help of a mathematical model. One such example is a mutation that reduces the rate of background acetylation of particular histone side-chains that competes with the deacetylation by Sir2p. The resulting negative feedback due to a Sir protein depletion effect gives rise to interesting counter-intuitive consequences. Our mathematical analysis brings forth the different dynamical behaviors possible within the same molecular model and guides the formulation of more refined hypotheses that could be addressed experimentally.Comment: 19 pages, 5 figure

Kleptoparasitic melees--modelling food stealing featuring contests with multiple individuals

Kleptoparasitism is the stealing of food by one animal from another. This has been modelled in various ways before, but all previous models have only allowed contests between two individuals. We investigate a model of kleptoparasitism where individuals are allowed to fight in groups of more than two, as often occurs in real populations. We find the equilibrium distribution of the population amongst various behavioural states, conditional upon the strategies played and environmental parameters, and then find evolutionarily stable challenging strategies. We find that there is always at least one ESS, but sometimes there are two or more, and discuss the circumstances when particular ESSs occur, and when there are likely to be multiple ESSs

Statistical Modeling of the Default Mode Brain Network Reveals a Segregated Highway Structure

We investigate the functional organization of the Default Mode Network (DMN) – an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational principles, subnetwork structure is less well understood. Current statistical tools, however, are not suited to quantifying the operating characteristics of functional networks as they often require threshold censoring of information and do not allow for inferential testing of the role that local processes play in determining network structure. Here, we develop the correlation Generalized Exponential Random Graph Model (cGERGM) – a statistical network model that uses local processes to capture the emergent structural properties of correlation networks without loss of information. Examining the DMN with the cGERGM, we show that, rather than demonstrating small-world properties, the DMN appears to be organized according to principles of a segregated highway – suggesting it is optimized for function-specific coordination between brain regions as opposed to information integration across the DMN. We further validate our findings through assessing the power and accuracy of the cGERGM on a testbed of simulated networks representing various commonly observed brain architectures

Statistical Modeling of the Default Mode Brain Network Reveals a Segregated Highway Structure

We investigate the functional organization of the Default Mode Network (DMN) - an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational principles, subnetwork structure is less well understood. Current statistical tools, however, are not suited to quantifying the operating characteristics of functional networks as they often require threshold censoring of information and do not allow for inferential testing of the role that local processes play in determining network structure. Here, we develop the correlation Generalized Exponential Random Graph Model (cGERGM) - a statistical network model that uses local processes to capture the emergent structural properties of correlation networks without loss of information. Examining the DMN with the cGERGM, we show that, rather than demonstrating small-world properties, the DMN appears to be organized according to principles of a segregated highway - suggesting it is optimized for function-specific coordination between brain regions as opposed to information integration across the DMN. We further validate our findings through assessing the power and accuracy of the cGERGM on a testbed of simulated networks representing various commonly observed brain architectures

Mining Disaggregase Sequence Space to Safely Counter TDP-43, FUS, and α-Synuclein Proteotoxicity.

Hsp104 is an AAA+ protein disaggregase, which can be potentiated via diverse mutations in its autoregulatory middle domain (MD) to mitigate toxic misfolding of TDP-43, FUS, and α-synuclein implicated in fatal neurodegenerative disorders. Problematically, potentiated MD variants can exhibit off-target toxicity. Here, we mine disaggregase sequence space to safely enhance Hsp104 activity via single mutations in nucleotide-binding domain 1 (NBD1) or NBD2. Like MD variants, NBD variants counter TDP-43, FUS, and α-synuclein toxicity and exhibit elevated ATPase and disaggregase activity. Unlike MD variants, non-toxic NBD1 and NBD2 variants emerge that rescue TDP-43, FUS, and α-synuclein toxicity. Potentiating substitutions alter NBD1 residues that contact ATP, ATP-binding residues, or the MD. Mutating the NBD2 protomer interface can also safely ameliorate Hsp104. Thus, we disambiguate allosteric regulation of Hsp104 by several tunable structural contacts, which can be engineered to spawn enhanced therapeutic disaggregases with minimal off-target toxicity