Despite significant interest and past work to elucidate the phylogeny and photochemistry of species of the Heliobacteriaceae, genomic analyses of heliobacteria to date have been limited to just one published genome, that of the thermophilic species Heliobacterium (Hbt.) modesticaldum str. Ice1T. Here we present an analysis of the complete genome of a second heliobacterium, Heliorestis (Hrs.) convoluta str. HHT, an alkaliphilic, mesophilic, and morphologically distinct heliobacterium isolated from an Egyptian soda lake. The genome of Hrs. convoluta is a single circular chromosome of 3.22 Mb with a GC content of 43.1% and 3263 protein-encoding genes. In addition to culture-based observations and insights gleaned from the Hbt. modesticaldum genome, an analysis of enzyme-encoding genes from key metabolic pathways supports an obligately photoheterotrophic lifestyle for Hrs. convoluta. A complete set of genes encoding enzymes for propionate and butyrate catabolism and the absence of a gene encoding lactate dehydrogenase distinguishes the carbon metabolism of Hrs. convoluta from its close relatives. Comparative analyses of key proteins in Hrs. convoluta, including cytochrome c553 and the Fo alpha subunit of ATP synthase, with those of related species reveal variations in specific amino acid residues that likely contribute to the success of Hrs. convoluta in its highly alkaline environment.About two thirds of the patients affected with lysosomal storage diseases (LSD) experience neurological manifestations, such as developmental delay, seizures, or psychiatric problems. In order to develop efficient therapies, it is crucial to understand the neuropathophysiology underlying these symptoms. How exactly lysosomal storage affects biogenesis and function of neurons is still under investigation however recent research highlights a substantial role played by synaptic defects, such as alterations in synaptic spines, synaptic proteins, postsynaptic densities, and synaptic vesicles that might lead to functional impairments in synaptic transmission and neurodegeneration, finally culminating in massive neuronal death and manifestation of cognitive symptoms. Unveiling how the synaptic components are affected in neurological LSD will thus enable a better understanding of the complexity of disease progression as well as identify crucial targets of therapeutic relevance and optimal time windows for targeted intervention.A recent meta-analysis revealed that cardiac vagal activity (mostly indicated by vagally-mediated heart rate variability; HRV) decreases significantly from the follicular to luteal menstrual cycle phase in naturally-cycling participants. However, the question remains as to whether cyclical changes in estradiol (E2), progesterone (P4), or both are responsible for HRV fluctuations. We present the first studies to use repeated measures of E2, P4, and HRV across the cycle to model both the unique and interactive effects of person-centered E2 and P4 on HRV in multilevel models. In study one, 40 naturally-cycling participants were assessed weekly across four weeks, and were blind to the cycle focus of the study. In study two, 50 naturally-cycling participants were examined in three precisely defined cycle phases via ovulation testing. Both studies revealed that only P4 was correlated with HRV, such that higher-than-usual P4 significantly predicted lower-than-usual HRV within a given participant. In line with this, cycle phase comparisons revealed lower HRV in the mid-luteal phase (characterized by elevated P4) than in other phases. No significant main or interactive effects of E2 on HRV were found. Future female health studies should investigate individual differences in these effects and potential consequences of cyclical HRV changes on daily functioning.A simple and robust analog feedforward and digital feedback compound control system is presented to lock the frequency of a slave continuous wave (CW) laser to an optical frequency comb. The beat frequency between CW laser and the adjacent comb mode was fed to an acousto-optical frequency shifter (AOFS) to compensate the frequency dithering of the CW laser. A digital feedback loop was achieved to expand the operation bandwidth limitation of the AOFS by over an order of magnitude. The signal-to-noise ratio of the interference signal was optimized using a grating-based spectral filtering detection unit. The complete system achieved an ultrastable offset-locking of the slave CW laser to the frequency comb with a relative stability of ±3.62 × 10-14. The Allan deviations of the beat frequency were 8.01 × 10-16 and 2.19 × 10-16 for a gate time of 10 s and 1000 s, respectively. The findings of this study may further improve laser interferometry by providing a simple and robust method for ultrastable frequency control.Preparing for climate change depends on the observation and prediction of decadal trends of the environmental variables, which have a direct impact on the sustainability of resources affecting the quality of life on our planet. The NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is proposed to provide climate quality benchmark spectral radiance observations for the purpose of determining the decadal trends of climate variables, and validating and improving the long-range climate model forecasts needed to prepare for the changing climate of the Earth. The CLARREO will serve as an in-orbit, absolute, radiometric standard for the cross-calibration of hyperspectral radiance spectra observed by the international system of polar operational satellite sounding sensors. Here, we demonstrate that the resulting accurately cross-calibrated polar satellite global infrared spectral radiance trends (e.g., from the Metop IASI instrument considered here) can be interpreted in terms of temperature and water vapor profile trends. This demonstration is performed using atmospheric state data generated for a 100-year period from 2000-2099, produced by a numerical climate model prediction that was forced by the doubling of the global average atmospheric CO2 over the 100-year period. The vertical profiles and spatial distribution of temperature decadal trends were successfully diagnosed by applying a linear regression profile retrieval algorithm to the simulated hyperspectral radiance spectra for the 100-year period. These results indicate that it is possible to detect decadal trends in atmospheric climate variables from high accuracy all-sky satellite infrared radiance spectra using the linear regression retrieval technique.The purpose of this study was to determine the minimum separation distance between aquaculture farms and ship traffic to prevent damage to either the farms or the vessels. A high-risk area in South Korea was selected for the study by overlapping shipping routes with fisheries using satellite and aerial photographs. The annual frequency of damage was calculated based on a probability distribution applied to the sea area, and a safe distance between the aquaculture farms and the traffic was derived. The Kolmogorov-Smirnov (KS) test was conducted to determine whether the Gaussian mixture model (GMM) follows the data of this study. It was found that a safe distance of at least 1000 m is needed to avoid farm or vessel damage. Then, it is possible to prevent damage to vessel propellers and fisheries locating aquaculture farms at the minimum safe distance from the traffic routes. For protection and security of these structures, the installation of a set of wirelessly Internet of Underwater Things (IoUT) sensors that can transmit the farm location to the ship’s navigator were suggested.In this work, microelectromechanical systems (MEMS)-based directional acoustic sensors operating in an underwater environment are explored. The studied sensors consist of a free-standing single wing or two wings pivoted to a substrate. The sensors operate in a narrow frequency band determined by the resonant frequency of the mechanical structure. The electronic readout of the mechanical response is obtained using interdigitated comb finger capacitors attached to the wings. The characteristics of MEMS sensors immersed in silicone oil are simulated using finite element modeling. The performance of the sensors is evaluated both in air and underwater. For underwater testing and operation, the sensors are packaged in a housing containing silicone oil, which was specially developed to present near unity acoustic transmission. The measurements show that the resonant frequency of the sensors obtained in air shifts to a lower frequency when immersed in silicone oil, which is primarily due to the mass loading of the liquid. The peak sensitivity of the MEMS sensors is approximately 6 mV/Pa or -165 dB re 1 V/mPa, and the directional response shows a dipole pattern. The signal-to-noise ratio was found to be about 200 or 23 dB at 1 Pa incident sound pressure. The results show the potential of MEMS sensors to be used in underwater applications for sound source localization.With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAFRNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAFRNA estimation from current scRNA-seq datasets and shows that the 3′-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.Virtual Reality has already been proven as a useful supplementary treatment tool for anxiety disorders. However, no specific technological importance has been given so far on how to apply Virtual Reality with a way that properly stimulates the phobic stimulus and provide the necessary means for lifelike experience. Thanks to technological advancements, there is now a variety of hardware that can help enhance stronger emotions generated by Virtual Reality systems. This study aims to evaluate the feeling of presence during different hardware setups of Virtual Reality Exposure Therapy, and, particularly how the user’s interaction with those setups can affects their sense of presence during the virtual simulation. An acrophobic virtual scenario is used as a case study by 20 phobic individuals and the Witmer-Singer presence questionnaire was used for presence evaluation by the users of the system. Statistical analysis on their answers revealed that the proposed full body Motion Recognition Cameras system generates a better feeling of presence compared to the Hand Controllers system.