Based on the concept of constructive interference (CI), multiuser interference (MUI) has recently been shown to be beneficial for communication secrecy. A few CI-based secure precoding algorithms have been proposed that use both the channel state information (CSI) and knowledge of the instantaneous transmit symbols. In this paper, we examine the CI-based secure precoding problem with a focus on smart eavesdroppers that exploit statistical information gleaned from the precoded data for symbol detection. Moreover, the impact of correlation between the main and eavesdropper channels is taken into account. We first modify an existing CI-based preocding scheme to better utilize the destructive impact of the interference. Then, we point out the drawback of both the existing and the new modified CI-based precoders when faced with a smart eavesdropper. To address this deficiency, we provide a general principle for precoder design and then give two specific design examples. Finally, the scenario where the eavesdropper's CSI is unavailable is studied. Numerical results show that although our modified CI-based precoder can achieve a better energy-secrecy trade-off than the existing approach, both have a limited secrecy benefit. On the contrary, the precoders developed using the new CI-design principle can achieve a much improved trade-off and significantly degrade the eavesdropper's performance.

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

The C-terminal region of cardiac troponin I (cTnI) is known to be important in cardiac function, as removal of the last 17 C-terminal residues of human cTnI has been associated with myocardial stunning. To investigate the C-terminal region of cTnI, three C-terminal deletion mutations in human cTnI were generated: Δ1 (deletion of residue 210), Δ3 (deletion of residues 208-210), and Δ5 (deletion of residues 206-210). Mammalian two-hybrid studies showed that the interactions between cTnI mutants and cardiac troponin C (cTnC) or cardiac troponin T (cTnT) were impaired in Δ3 and Δ5 mutants when compared to wild-type cTnI. Troponin complexes containing 2-[4'-(iodoacetamido) anilino] naphthalene-6-sulfonic acid (IAANS) labeled cTnC showed that the troponin complex containing cTnI Δ5 had a small increase in Ca(2+) affinity (P < 0.05); while the cTnI Δ1- and Δ3 troponin complexes showed no difference in Ca(2+) affinity when compared to wild-type troponin. In vitro motility assays showed that all truncation mutants had increased Ca(2+) dependent motility relative to wild-type cTnI. These results suggest that the last 5 C-terminal residues of cTnI influence the binding of cTnI with cTnC and cTnT and affect the Ca(2+) dependence of filament sliding, and demonstrate the importance of this region of cTnI.

Machine learning has demonstrated great power in materials design, discovery, and property prediction. However, despite the success of machine learning in predicting discrete properties, challenges remain for continuous property prediction. The challenge is aggravated in crystalline solids due to crystallographic symmetry considerations and data scarcity. Here, the direct prediction of phonon density-of-states (DOS) is demonstrated using only atomic species and positions as input. Euclidean neural networks are applied, which by construction are equivariant to 3D rotations, translations, and inversion and thereby capture full crystal symmetry, and achieve high-quality prediction using a small training set of ≈103 examples with over 64 atom types. The predictive model reproduces key features of experimental data and even generalizes to materials with unseen elements, and is naturally suited to efficiently predict alloy systems without additional computational cost. The potential of the network is demonstrated by predicting a broad number of high phononic specific heat capacity materials. The work indicates an efficient approach to explore materials' phonon structure, and can further enable rapid screening for high-performance thermal storage materials and phonon-mediated superconductors.

Background

While the physical and chemical properties of airborne particulate matter (PM) have been extensively studied, their associated microbiome remains largely unexplored. Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM_2.5 and PM₁₀ in Beijing over a period of 6 months in 2012 and 2013, including those from several historically severe smog events.

Results

We observed that the microbiome composition and functional potential were conserved between PM_2.5 and PM₁₀, although considerable temporal variations existed. Among the airborne microorganisms, Propionibacterium acnes, Escherichia coli, Acinetobacter lwoffii, Lactobacillus amylovorus, and Lactobacillus reuteri dominated, along with several viral species. We further identified an extensive repertoire of genes involved in antibiotic resistance and detoxification, including transporters, transpeptidases, and thioredoxins. Sample stratification based on Air Quality Index (AQI) demonstrated that many microbial species, including those associated with human, dog, and mouse feces, exhibit AQI-dependent incidence dynamics. The phylogenetic and functional diversity of air microbiome is comparable to those of soil and water environments, as its composition likely derives from a wide variety of sources.

Conclusions

Airborne particulate matter accommodates rich and dynamic microbial communities, including a range of microbial elements that are associated with potential health consequences.

We aimed to identify the contribution of central nervous system (CNS) viral coinfection to illness in African children with retinopathy-negative or retinopathy-positive cerebral malaria (CM). We collected cerebrospinal fluid (CSF) from 272 children with retinopathy-negative or retinopathy-positive CM and selected CSF from 111 of these children (38 retinopathy positive, 71 retinopathy negative, 2 retinopathy unknown) for analysis by metagenomic next-generation sequencing. We found CSF viral coinfections in 7/38 (18.4%) retinopathy-positive children and in 18/71 (25.4%) retinopathy-negative children. Excluding HIV-1, human herpesviruses (HHV) represented 61% of viruses identified. Excluding HIV-1, CNS viral coinfection was equally likely in children who were retinopathy positive and retinopathy negative (P = 0.1431). Neither mortality nor neurological morbidity was associated with the presence of virus (odds ratio [OR] = 0.276, 95% CI: 0.056-1.363). Retinopathy-negative children with a higher temperature, lower white blood cell count, or being dehydrated were more likely to have viral coinfection. Level of consciousness at admission was not associated with CNS viral coinfection in retinopathy-negative children. Viral CNS coinfection is unlikely to contribute to coma in children with CM. The herpesviruses other than herpes simplex virus may represent incidental bystanders in CM, reactivating during acute malaria infection.

Reactive oxygen species (ROS) are unstable reactive molecules that are toxic to cells. Regulation of ROS homeostasis is crucial to protect cells from dysfunction, senescence, and death. In plant leaves, ROS are mainly generated from chloroplasts and are tightly temporally restricted by the circadian clock. However, little is known about how ROS homeostasis is regulated in nonphotosynthetic organs, such as petals. Here, we showed that hydrogen peroxide (H2O2) levels exhibit typical circadian rhythmicity in rose (Rosa hybrida) petals, consistent with the measured respiratory rate. RNA-seq and functional screening identified a B-box gene, RhBBX28, whose expression was associated with H2O2 rhythms. Silencing RhBBX28 accelerated flower senescence and promoted H2O2 accumulation at night in petals, while overexpression of RhBBX28 had the opposite effects. RhBBX28 influenced the expression of various genes related to respiratory metabolism, including the TCA cycle and glycolysis, and directly repressed the expression of SUCCINATE DEHYDROGENASE 1, which plays a central role in mitochondrial ROS (mtROS) homeostasis. We also found that PHYTOCHROME-INTERACTING FACTOR8 (RhPIF8) could activate RhBBX28 expression to control H2O2 levels in petals and thus flower senescence. Our results indicate that the circadian-controlled RhPIF8-RhBBX28 module is a critical player that controls flower senescence by governing mtROS homeostasis in rose.