A few dark matter substructures have recently been detected in strong gravitational lenses through their perturbations of highly magnified images. We derive a characteristic scale for lensing perturbations and show that they are significantly larger than the perturber's Einstein radius. We show that the perturber's projected mass enclosed within this radius, scaled by the log-slope of the host galaxy's density profile, can be robustly inferred even if the inferred density profile and tidal radius of the perturber are biased. We demonstrate the validity of our analytic derivation using several gravitational lens simulations where the tidal radii and the inner log-slopes of the density profile of the perturbing subhalo are allowed to vary. By modeling these simulated data, we find that our mass estimator, which we call the effective subhalo lensing mass, is accurate to within about 10% or smaller in each case, whereas the inferred total subhalo mass can potentially be biased by nearly an order of magnitude. We therefore recommend that the effective subhalo lensing mass be reported in future lensing reconstructions, as this will allow for a more accurate comparison with the results of dark matter simulations.

In developed countries, mortality decline is decelerating at younger ages and accelerating at old ages, a phenomenon we call "rotation." We expect that this rotation will also occur in developing countries as they attain high life expectancies. But the rotation is subtle and has proved difficult to handle in mortality models that include all age groups. Without taking it into account, however, long-term mortality projections will produce questionable results. We simplify the problem by focusing on the relative magnitude of death rates at two ages (0 and 15-19) while making assumptions about changes in rates of decline at other ages. We extend the Lee-Carter method to incorporate this subtle rotation in projection. We suggest that the extended Lee-Carter method could provide plausible projections of the age pattern of mortality for populations, including those that currently have very high life expectancies. Detailed examples are given using data from Japan and the United States.

Through the high affinity of the β-cyclodextrin (β-CD) cavity for adamantane moieties, novel polysaccharide-gold nanocluster supramolecular conjugates (HACD-AuNPs) were successfully constructed from gold nanoparticles (AuNPs) bearing adamantane moieties and cyclodextrin-grafted hyaluronic acid (HACD). Due to their porous structure, the supramolecular conjugates could serve as a versatile and biocompatible platform for the loading and delivery of various anticancer drugs, such as doxorubicin hydrochloride (DOX), paclitaxel (PTX), camptothecin (CPT), irinotecan hydrochloride (CPT-11), and topotecan hydrochloride (TPT), by taking advantage of the controlled association/dissociation of drug molecules from the cavities formed by the HACD skeletons and AuNPs cores as well as by harnessing the efficient targeting of cancer cells by hyaluronic acid. Significantly, the release of anticancer drugs from the drug@HACD-AuNPs system was pH-responsive, with more efficient release occurring under a mildly acidic environment, such as that in a cancer cell. Taking the anticancer drug DOX as an example, cell viability experiments revealed that the DOX@HACD-AuNPs system exhibited similar tumor cell inhibition abilities but lower toxicity than free DOX due to the hyaluronic acid reporter-mediated endocytosis. Therefore, the HACD-AuNPs supramolecular conjugates may possess great potential for the targeted delivery of anticancer drugs.

DNA damage response mediator protein 53BP1 is a key regulator of non-homologous end-joining (NHEJ) repair. 53BP1 protects DNA broken ends from resection by recruiting two downstream factors, RIF1 (RAP1-interacting factor 1) and PTIP (Pax transactivation domain-interacting protein), to double-stranded breaks (DSBs) via ATM (ataxia telangiectasia mutated)-mediated 53BP1 phosphorylation, and competes with BRCA1-mediated homologous recombination (HR) repair in G1 phase. In contrast, BRCA1 antagonizes 53BP1-direct NHEJ repair in S/G2 phases. We and others have found that BRCA1 prevents the translocation of RIF1 to DSBs in S/G2 phases; however, the underlying mechanism remains unclear. Here we show that efficient ATM-dependent 53BP1 phosphorylation is restricted to the G1 phase of the cell cycle, as a consequence RIF1 and PTIP accumulation at DSB sites only occur in G1 phase. Mechanistically, both BRCT and RING domains of BRCA1 are required for the inhibition of 53BP1 phosphorylation in S and G2 phases. Thus, our findings reveal how BRCA1 antagonizes 53BP1 signaling to ensure that HR repair is the dominant repair pathway in S/G2 phases.

With the rapid advances in sensing and digital technologies, cyber-physical systems are regarded as the most viable platforms for improving building design and management. Researchers investigated the possibility of integrating energy management systems with cyber-physical systems to form energy-cyber-physical systems in order to promote building energy management. However, minimizing energy consumption while fulfilling building functions for energy-cyber-physical systems is challenging due to the dynamics of building occupants. As occupant behavior is a major source of uncertainty for energy management, ignoring it often results in both energy waste caused by overheating and overcooling as well as discomfort due to insufficient thermal and ventilation services. To mitigate such uncertainties, this study proposes an occupancy-linked energy-cyber-physical system that incorporates WiFi probe-based occupancy detection. The proposed framework utilizes ensemble classification algorithms to extract three forms of occupancy information. It creates a data interface to link energy management systems and cyber-physical systems and allows for automated occupancy detection and interpretation by assembling multiple weak classifiers for WiFi signals. A validation experiment in a large office room was conducted to examine the performance of the proposed occupancy-linked energy-cyber-physical systems. The experiment and simulation results suggest that, with a proper classifier and occupancy data type, the proposed model can potentially save about 26.4% of energy consumption in cooling and ventilation demands.