De bedwants: a bad bug?

The bed bug: a bad bug? The common bed bug, Cimex lectularius, is a bloodsucking ectoparasite which attacks mammals and is on the rise since the beginning of the early 21st century. They are brown and flat. Skin lesions appear after the painless bite, often during the predawn hours. Small, purpuric macules develop into erythematous, indurated papules on exposed areas of skin of the face, neck and extremities, and resolve over the course of 2 weeks. Often, a linear or cluster configuration of 3 to 4 lesions (‘breakfast, lunch and dinner’) appears. Pruritic wheal reactions represent a type 1 hypersensitivity reaction elicited by the parasite’s saliva antigens. The clinical differential diagnosis is broad and may include other insect and arthropod bites and stings, scabies infestation, dermatitis herpetiformis, ecthyma, etc. There is no evidence that bed bugs are vectors and transmit human pathogens. They are responsible for considerable physical irritation and significant psychological distress. Very rarely, the patient could develop anemia or anaphylaxis. Control involves treating both the patient’s symptoms and the cause by the eradication of the infestation, a challenge that may require a professional exterminator for an integrated pest management strategy. “Good night, sleep tight, don’t let the bed bugs bite!”

Electronic Couplings and Electrostatic Interactions Behind the Light Absorption of Retinal Proteins

The photo-functional chromophore retinal exhibits a wide variety of optical absorption properties depending on its intermolecular interactions with surrounding proteins and other chromophores. By utilizing these properties, microbial and animal rhodopsins express biological functions such as ion-transport and signal transduction. In this review, we present the molecular mechanisms underlying light absorption in rhodopsins, as revealed by quantum chemical calculations. Here, symmetry-adapted cluster-configuration interaction (SAC-CI), combined quantum mechanical and molecular mechanical (QM/MM), and transition-density-fragment interaction (TDFI) methods are used to describe the electronic structure of the retinal, the surrounding protein environment, and the electronic coupling between chromophores, respectively. These computational approaches provide successful reproductions of experimentally observed absorption and circular dichroism (CD) spectra, as well as insights into the mechanisms of unique optical properties in terms of chromophore-protein electrostatic interactions and chromophore-chromophore electronic couplings. On the basis of the molecular mechanisms revealed in these studies, we also discuss strategies for artificial design of the optical absorption properties of rhodopsins.

RNA Identification and Detection of Nucleic Acids as Aerosols in Air Samples by Means of Photon and Electron Interactions

This study presents a methodology to reveal traces of viral particles, as aerosol with known chemical and molecular structure, in a sample by means of photon and electron interactions. The method is based on Monte Carlo simulations and on the analysis of photon-electron fluxes-spectra through energy channels counts as a function of different aerosol viral concentrations in the air sample and looking at the peculiar photon/electron interactions with the potential abnormal atomic hydrogen (H), oxygen (O), carbon (C), and phosphorus (P) compositions present in the air sample as a function of living and nonliving matter with PO4 group RNA/DNA strands in a cluster configuration.

Deep-Framework: A Distributed, Scalable, and Edge-Oriented Framework for Real-Time Analysis of Video Streams

Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on computation heavy deep learning algorithms, there is a growing need for solutions that allow the deployment and use of new models on scalable and flexible edge architectures. In this work, we present Deep-Framework, a novel open source framework for developing edge-oriented real-time video analytics applications based on deep learning. Deep-Framework has a scalable multi-stream architecture based on Docker and abstracts away from the user the complexity of cluster configuration, orchestration of services, and GPU resources allocation. It provides Python interfaces for integrating deep learning models developed with the most popular frameworks and also provides high-level APIs based on standard HTTP and WebRTC interfaces for consuming the extracted video data on clients running on browsers or any other web-based platform.

Notes on cluster algebras and some all-loop Feynman integrals

We study cluster algebras for some all-loop Feynman integrals, including box-ladder, penta-box-ladder, and double-penta-ladder integrals. In addition to the well-known box ladder whose symbol alphabet is $$ {D}_2\simeq {A}_1^2 $$ D 2 ≃ A 1 2 , we show that penta-box ladder has an alphabet of D3 ≃ A3 and provide strong evidence that the alphabet of seven-point double-penta ladders can be identified with a D4 cluster algebra. We relate the symbol letters to the u variables of cluster configuration space, which provide a gauge-invariant description of the cluster algebra, and we find various sub-algebras associated with limits of the integrals. We comment on constraints similar to extended-Steinmann relations or cluster adjacency conditions on cluster function spaces. Our study of the symbol and alphabet is based on the recently proposed Wilson-loop d log representation, which allows us to predict higher-loop alphabet recursively; by applying it to certain eight-point and nine-point double-penta ladders, we also find D5 and D6 cluster functions respectively.

RNA Identification and Detection of Nucleic Acids as Aerosols in Air Samples by Means of Photon and Electron Interactions

This study presents a methodology to reveal traces of viral particles, as aerosol with known chemical and molecular structure, in a sample by means of photon and electron interactions. The method is based on Monte Carlo simulations and on the analysis of photon-electron fluxes-spectra through energy channels counts as a function of different aerosol viral concentrations in the air sample and looking at the peculiar photon/electron interactions with the potential abnormal atomic hydrogen (H), oxygen (O), carbon (C), and phosphorus (P) compositions present in the air sample as a function of living and nonliving matter with PO4 group RNA/DNA strands in a cluster configuration.

Designing plots for precise estimation of forest attributes in landscapes and forests of varying heterogeneity

Models of relationships among forest inventory sampling efficiency and cluster plot configuration variables inform decisions by inventory planners. However, relationships vary under different spatial heterogeneity scenarios. In order to improve understanding of how spatial patterns of forests affects these relationships, we implemented a factorial experiment by simulating forest pattern at both the landscape and stand scales. We sampled these simulated forests with a variety of cluster plot configurations, calculated coefficient of variation (CV) of trees per hectare (TPH) for each replicate, and tested the relationships among CV and the heterogeneity and cluster plot configuration factors within a linear mixed model framework. Both landscape and stand-scale pattern aggregation had a significant relationship with CV. Changing cluster plot configuration factors did little to change the overall CV when using larger subplots but had some important effects when using smaller subplots. These impacts were stronger in the more uniform landscapes. Results were opposite for stand-scale heterogeneity; changing plot configuration in areas with aggregated patterns had a stronger impact than it did in areas with more uniform patterns. Results of this study reveal the importance of accounting for spatial pattern at multiple scales when making cluster configuration choices if the goal is statistical efficiency.