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Eye gaze analysis is an important research problem in the field of Computer Vision and Human-Computer Interaction. Even with notable progress in the last 10 years, automatic gaze analysis still remains challenging due to the uniqueness of eye appearance, eye-head interplay, occlusion, image quality, and illumination conditions. There are several open questions, including what are the important cues to interpret gaze direction in an unconstrained environment without prior knowledge and how to encode them in real-time. We review the progress across a range of gaze analysis tasks and applications to elucidate these fundamental questions, identify effective methods in gaze analysis, and provide possible future directions. We analyze recent gaze estimation and segmentation methods, especially in the unsupervised and weakly supervised domain, based on their advantages and reported evaluation metrics. Our analysis shows that the development of a robust and generic gaze analysis method still needs to address real-world challenges such as unconstrained setup and learning with less supervision. We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including Computer Vision, Augmented Reality (AR), Virtual Reality (VR), and Human Computer Interaction (HCI).

Fungal Trl1 is an essential trifunctional tRNA splicing enzyme that heals and seals tRNA exons with 2′,3′-cyclic-PO4and 5′-OH ends. Trl1 is composed of C-terminal cyclic phosphodiesterase and central polynucleotide kinase end-healing domains that generate the 3′-OH,2′-PO4and 5′-PO4termini required for sealing by an N-terminal ATP-dependent ligase domain. Trl1 enzymes are present in many human fungal pathogens and are promising targets for antifungal drug discovery because their domain structures and biochemical mechanisms are unique compared to the mammalian RtcB-type tRNA splicing enzyme. Here we report that Mucorales species (deemed high-priority human pathogens by WHO) elaborate a noncanonical tRNA splicing apparatus in which a monofunctional RNA ligase enzyme is encoded separately from any end-healing enzymes. We show that Mucor circinelloidesRNA ligase (MciRNL) is active in tRNA splicing in vivo in budding yeast in lieu of the Trl1 ligase domain. Biochemical and kinetic characterization of recombinant MciRNL underscores its requirement for a 2′-PO4terminus in the end-joining reaction, whereby the 2′-PO4enhances the rates of RNA 5′-adenylylation (step 2) and phosphodiester synthesis (step 3) by ∼125-fold and ∼6200-fold, respectively. In the canonical fungal tRNA splicing pathway, the splice junction 2′-PO4installed by RNA ligase is removed by a dedicated NAD+-dependent RNA 2′-phosphotransferase Tpt1. Here we identify and affirm by genetic complementation in yeast the biological activity of Tpt1 orthologs from three Mucorales species. Recombinant M. circinelloidesTpt1 has vigorous NAD+-dependent RNA 2′-phosphotransferase activity in vitro.

Rapid, sensitive, and selective detection of nucleic acid biomarkers for health diagnostic applications becomes feasible for point of care scenarios when the detection instrument is inexpensive, simple, and robust. Here, we report the design, implementation, and characterization of a point of care instrument for photonic resonator absorption microscopy (PRAM) that takes advantage of resonant optical coupling between plasmonic gold nanoparticle tags and a photonic crystal (PC) surface. Matching the PC resonant wavelength to the gold nanoparticle’s surface plasmon wavelength generates localized and efficient quenching of the PC resonant reflection intensity, resulting in the ability to clearly detect and count individual gold nanoparticles when they are captured on the PC surface. Surface-captured nanoparticles are observed by illuminating the PC at normal incidence with polarized light from a low-intensity red LED, and recording of PC reflected intensity on an inexpensive CMOS image sensor. A contrast limited adaptive histogram equalization (CLAHE) image processing algorithm was applied to derive counts of captured nanoparticles. The instrument is utilized in the context of an activate capture?+?digital counting (AC?+?DC) assay for a specific miRNA sequence, using nucleic acid toehold probes applied to gold nano-urchin (AuNU) nanoparticles to achieve 160 aM detection limits in a 30 min. assay.

Electron paramagnetic resonance (EPR) in combination with the recently developed double-histidine (dHis)-based Cu2+spin labeling has provided valuable insights into protein structure and conformational dynamics. To relate sparse distance constraints measured by EPR to protein fluctuations in solution, modeling techniques are needed. In this work, we have developed force field parameters for Cu2+–nitrilotriacetic and Cu2+–iminodiacetic acid spin labels. We employed molecular dynamics (MD) simulations to capture the atomic-level details of dHis-labeled protein fluctuations. The interspin distances extracted from 200 ns MD trajectories show good agreement with the experimental results. The MD simulations also illustrate the dramatic rigidity of the Cu2+labels compared to the standard nitroxide spin label. Further, the relative orientations between spin-labeled sites were measured to provide insight into the use of double electron–electron resonance (DEER) methods for such labels. The relative mean angles, as well as the standard deviations of the relative angles, agree well in general with the spectral simulations published previously. The fluctuations of relative orientations help rationalize why orientation selectivity effects are minimal at X-band frequencies, but observable at the Q-band for such labels. In summary, the results show that by combining the experimental results with MD simulations precise information about protein conformations as well as flexibility can be obtained.

In this Account, we showcase site-directed Cu2+labeling in proteins and DNA, which has opened new avenues for the measurement of the structure and dynamics of biomolecules using electron paramagnetic resonance (EPR) spectroscopy. In proteins, the spin label is assembled in situfrom natural amino acid residues and a metal complex and requires no post-expression synthetic modification or purification procedures. The labeling scheme exploits a double histidine (dHis) motif, which utilizes endogenous or site-specifically mutated histidine residues to coordinate a Cu2+complex. Pulsed EPR measurements on such Cu2+-labeled proteins potentially yield distance distributions that are up to 5 times narrowerthan the common protein spin label—the approach, thus, overcomes the inherent limitation of the current technology, which relies on a spin label with a highly flexible side chain. This labeling scheme provides a straightforward method that elucidates biophysical information that is costly, complicated, or simply inaccessible by traditional EPR labels. Examples include the direct measurement of protein backbone dynamics at β-sheet sites, which are largely inaccessible through traditional spin labels, and rigid Cu2+–Cu2+distance measurements that enable higher precision in the analysis of protein conformations, conformational changes, interactions with other biomolecules, and the relative orientations of two labeled protein subunits. Likewise, a Cu2+label has been developed for use in DNA, which is small, is nucleotide independent, and is positioned within the DNA helix. The placement of the Cu2+label directly reports on the biologically relevant backbone distance. Additionally, for both of these labeling techniques, we have developed models for interpretation of the EPR distance information, primarily utilizing molecular dynamics (MD) simulations. Initial results using force fields developed for both protein and DNA labels have agreed with experimental results, which has been a major bottleneck for traditional spin labels. Looking ahead, we anticipate new combinations of MD and EPR to further our understanding of protein and DNA conformational changes, as well as working synergistically to investigate protein–DNA interactions.

Polynucleotide phosphorylase (PNPase) catalyzes stepwise phosphorolysis of the 3′-terminal phosphodiesters of RNA chains to yield nucleoside diphosphate products. In the reverse reaction, PNPase acts as a polymerase, using NDPs as substrates to add NMPs to the 3′-OH terminus of RNA chains while expelling inorganic phosphate. The apparent essentiality of PNPase for growth of M. tuberculosismilitates for mycobacterial PNPase as a potential drug target. A cryo-EM structure of Mycobacterium smegmatisPNPase (MsmPNPase) reveals a characteristic ring-shaped homotrimer in which each protomer consists of two RNase PH-like domains and an intervening α-helical module on the inferior surface of the ring. The carboxy-terminal KH and S1 domains, which impart RNA specificity to MsmPNPase, are on the opposite face of the core ring and are conformationally mobile. Single particle reconstructions of MsmPNPase in the act of poly(A) synthesis highlight a 3′-terminal (rA)4oligonucleotide and two magnesium ions in the active site and an adenine nucleobase in the central tunnel. We identify amino acids that engage the 3′ segment of the RNA chain (Phe68, Arg105, Arg112, Arg430, Arg431) and the two metal ions (Asp526, Asp532, Gln546, Asp548), and we infer those that bind inorganic phosphate (Thr470, Ser471, His435, Lys534). Alanine mutagenesis pinpointed RNA and phosphate contacts as essential (Arg105, Arg431, Lys534, Thr470 + Ser471), important (Arg112, Arg430), or unimportant (Phe68) for PNPase activity. Severe phosphorolysis and polymerase defects accompanying alanine mutations of the enzymic metal ligands suggest a two-metal mechanism of catalysis by MsmPNPase.

Electron spin resonance (ESR) or electron paramagnetic resonance (EPR) spectroscopy is an incisive technique for the characterization of paramagnetic centers in inorganic, bioinorganic, and organic molecules and materials. These measurements are enabled with the help of paramagnetic species, such as organic free radicals and ions, electronically excited states, and metal–ligand compounds, some of which with biological importance. In this experiment, analogues of histidine–copper coordination compounds are investigated to show students how ESR line shapes depend on the complexed copper ion electronic structure as well as how the spectral features elucidate the coordination environment of copper. These coordinated compounds play an important role in metal ion coordination in proteins and peptides. The experiment has two parts. First, three copper–imidazole complexes that mimic copper–histidine compounds in the human body are synthesized. Second, the ESR spectrum of each complex is obtained at 77 K from frozen chloroform/methanol and acetonitrile/methanol matrixes and used to elucidate the ligand arrangement of the Cu2+ion and the effect on the unpaired electron density.

Analysing the mobility traces of moving agents (mobile users, GPS-equipped vehicles, CDRs, etc.) may help in interpreting the “human interests and intentions” behind the movements and thus facilitates diverse range of location-based applications. The trajectory analysis uncovers the connections, correlations and differences among individuals and their activities by exploring their mobility attributes. This paper focuses on how mobilityinformation (GPS traces) of a student exhibits correlation with her academic performance. The proposed framework analyses the GPS trajectories of students in an academic campus, models the mobility patterns of students using context-aware traj-graph (CTG), clusters signature mobility patterns and uncovers the correlation of mobility attributes with the academic performance of the students. A mobility knowledge graph has been constructed considering the entities, namely students, places of visits, movement behaviours, subjects, academic performances and the relationships among the entities. Using real-life dataset of an academic campus, we demonstrate that the mobility attributes are associated with students’ academic performances and students’ academic performance can be predicted from their movement behaviours.

In this work, we explore the potential of a rigid Cu2+spin-labeling technique, the double histidine (dHis) motif, along with Q-band electron paramagnetic resonance to report on the relative orientations of the spin labels. We show that the precision of the dHis motif, coupled with the sensitivity and resolution of Q-band frequencies, may allow for the straightforward determination of the relative orientation of the dHis-Cu2+labels using double electron–electron resonance (DEER). We performed Q-band DEER measurements at different magnetic fields on a protein containing two dHis Cu2+sites. These measurements exhibited orientational selectivity such that each discrete magnetic field yielded a unique DEER signal. We determined the relative orientation of the two metal centers by simulating the orientationally selective DEER data. These relative orientations were validated by visual analysis of the protein crystal structure modified with dHis sites. The simple visual analysis was shown to agree well with the angular values determined via simulation of the experimental data. The combination of the dHis-Cu2+motif along with the advantages of the Q-band can aid in the accurate measurement of protein structural and conformational dynamics.

Resource management in computing is a very challenging problem that involves making sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse nature of workload, and the unpredictability of fog/edge computing environments have made resource management even more challenging to be considered in the fog landscape. Recently Artificial Intelligence (AI) and Machine Learning (ML) based solutions are adopted to solve this problem. AI/ML methods with the capability to make sequential decisions like reinforcement learning seem most promising for these type of problems. But these algorithms come with their own challenges such as high variance, explainability, and online training. The continuously changing fog/edge environment dynamics require solutions that learn online, adopting changing computing environment. In this paper, we used standard review methodology to conduct this Systematic Literature Review (SLR) to analyze the role of AI/ML algorithms and the challenges in the applicability of these algorithms for resource management in fog/edge computing environments. Further, various machine learning, deep learning and reinforcement learning techniques for edge AI management have been discussed. Furthermore, we have presented the background and current status of AI/ML-based Fog/Edge Computing. Moreover, a taxonomy of AI/ML-based resource management techniques for fog/edge computing has been proposed and compared the existing techniques based on the proposed taxonomy. Finally, open challenges and promising future research directions have been identified and discussed in the area of AI/ML-based fog/edge computing.

As recommended by the World Health Organization, testing, isolation, and physical distancing are the keys to combat the pandemic due to COVID-19. However, physical distance monitoring and management is not straightforward, specifically in regions with high population density. Crowdsensing is one of the most feasible solutions where a large group of volunteers with mobile devices collectively share data and analysis on such data is carried out for extracting insights of common interest. This article proposes a novel mobile crowdsensing-based geospatial physical distance monitoring model capable of efficient pandemic monitoring and management. The work consists of two major contributions: analysis of human mobility information to find probable hot-spot regions and monitoring of the physical distance mandate. Another objective of this paper is to devise mobile crowdsourcing analytics model to find out the quality of the crowdsensing information and infer any implicit knowledge without affecting the quality of the output. Furthermore, we have also designed an Android application to implement the mobile crowdsensing system, named SocialSense, and provide effective pandemic management. The proposed model is supported by a theoretical analysis of latency calculation. We observe from the experimental results that the accuracy in hot-spot identification and physical distance monitoring are better in the case of the proposed model than the existing approaches. The trustworthiness of the crowdsourcing data is also improved in terms of accuracy than the existing approaches.

ABSTRACTIntroductionPhysiological processes at the molecular level take place at precise spatiotemporal scales, which vary from tissue to tissue and from one patient to another, implying the need for carriers that enable tunable release of therapeutics.AreascoveredClassification of all drug release to intrinsic and extrinsic is proposed, followed by the etymological clarification of the term ‘tunable’ and its distinction from the term ‘tailorable’. Tunability is defined as analogous to tuning a guitar string or a radio receiver to the right frequency using a single knob. It implies changing a structural parameter along a continuous quantitative scale and correlating it numerically with the release kinetics. Examples of tunable, tailorable and environmentally responsive carriers are given, along with the parameters used to achieve these levels of control.Expert opinionInterdependence of multiple variables defining the carrier microstructure obstructs the attempts to elucidate parameters that allow for the independent tuning of release kinetics. Learning from the tunability of nanostructured materials and superstructured metamaterials can be a fruitful source of inspiration in the quest for the new generation of tunable release carriers. The greater intersection of traditional materials sciences and pharmacokinetic perspectives could foster the development of more sophisticated mechanisms for tunable release.

Osteomyelitis, an infectious disease predominantly tied to poor sanitary conditions in underdeveloped regions of the world, is in need of inexpensive, easily in situ synthesizable and administrable materials for its treatment. The results of this study stem from the attempt to create one such affordable and minimally invasive therapeutic platform in the form of a self-setting, injectable cement with a tunable drug release profile, composed of only nanoparticulate hydroxyapatite, the synthetic version of the bone mineral. Cements comprised two separately synthesized hydroxyapatite powders, one of which, HAP2, was precipitated abruptly, retaining the amorphous nature longer, and the other one of which, HAP1, was precipitated at a slower rate, more rapidly transitioning to the crystalline structure. Cements were made with four different weight ratios of the two hydroxyapatite components: 100/0, 85/15, 50/50, and 0/100 with respect to HAP1 and HAP2. Both the setting and the release rates measured on two different antibiotics, vancomycin and ciprofloxacin, were controlled using the weight ratio of the two hydroxyapatite components. Various inorganic powder properties were formerly used to control drug release, but here we demonstrate for the first time that the kinetics of the mechanism of formation of a solid compound can be controlled to produce tunable drug release profiles. Specifically, it was found that the longer the precursor calcium phosphate component of the cement retains the amorphous nature of the primary precipitate, the more active it was in terms of speeding up the diffusional release of the adsorbed drug. The setting rate was, in contrast, inversely proportional to the release rate and to the content of this active hydroxyapatite component, HAP2. The empirical release profiles were fitted to a set of equations that could be used to tune the release rate to the therapeutic occasion. All of the cements loaded with vancomycin or ciprofloxacin inhibited the growth of Gram-positive Staphylococcus aureusand Gram-negative Escherichia coliand Pseudomonas aeruginosain both agar diffusion assays and broth dilution tests with intensities either comparable to the antibiotic per se, as in the case of ciprofloxacin, or even larger than the antibiotic alone, as in the case of vancomycin. Interestingly, even the pure cements exhibited an antibacterial effect ranging from moderate to strong, while demonstrating high levels of biocompatibility with osteoclastic RAW264.7 cells and only slightly affecting the viability of the osteoblastic MC3T3-E1 cells, in direct proportion with the amount of the more active hydroxyapatite component in the cements. This antibacterial effect was especially noticeable against Gram-negative bacteria, where the growth inhibition by the cements was comparable to or even stronger than that of the pure antibiotics. The antibiofilm assay against P. aeruginosabiofilms reiterated the antibiotic effectiveness of pure, antibiotic-free cements. That the carrier per se, composed of a nontoxic, easily prepared, bone mineral composite, can exhibit a strong antibacterial effect even in the absence of an antibiotic drug is an insight highly relevant in view of the rising resistance of an array of pathogens to traditional antibiotic therapies and the demands for the timely development of suitable alternatives.

In the recent times, the IoT (Internet of Things) enabled devices and applications have seen a rapid growth in various sectors including healthcare. The ability of low-cost connected sensors to cover large areas makes it a potential tool in the fight against pandemics, like COVID-19. The COVID-19 has posed a formidable challenge for the developing countries, like India, which need to cater to large population base with limited health infrastructure. In this paper, we proposed a  Cloud-fog-dew based mOnitoriNg Framework foR cOvid-19 maNagemenT, called CONFRONT. This cloud-fog-dew based healthcare model may help in preliminary diagnosis and also in monitoring patients while they are in quarantine facilities or home based treatments. The fog architecture ensures that the model is suited for real-time scenarios while keeping the bandwidth requirements low. To analyse large scale COVID-19 statistics data for extracting aggregate information of the disease spread, the cloud servers are leveraged due to its scalable computational and storage capabilities. The dew architecture ensures that the application is available at a limited scale even when cloud connectivity is lost, leading to a faster uptime for the application. A low cost wearable device consisting of heterogeneous sensors has also been designed and fabricated to realize the proposed framework.

This publisher’s notes amends the funding of [Biomed. Opt. Express12, 4637 (2021)10.1364/BOE.427475].