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Rapid growth in the popularity of cloud computing has been largely caused by increasing demand for scalable IT solutions, which could provide a cost-effective way to manage the software development process and meet business objectives. Optimization of cloud resource usage remains a key issue given its potential to significantly increase efficiency and flexibility, minimize costs, ensure security, and maintain high availability of services. This paper presents a novel concept of a Cloud Computing Resource Prediction and Optimization System, which is based on exploratory data analysis that acknowledges, among others, the information value of outliers and dynamic feature selection. The optimization of cloud resource usage relies on long-term forecasting, which is considered a dynamic and proactive optimization category. The analysis presented here focuses on the applicability of classical statistical models, XGBoost, neural networks and Transformer. Experimental results reveal that machine learning methods are highly effective in long-term forecasting. Particularly promising results – in the context of potential prediction-based dynamic resource reservations – have been yielded by prediction methods based on the BiGRU neural network and the Temporal Fusion Transformer.

Although the selective and effective clearance of senescent cancer cells can improve cancer treatment, their development is confronted by many challenges. As part of efforts designed to overcome these problems, prodrugs, whose design is based on senescence-associated ß-galactosidase (SA-ß-gal), have been developed to selectively eliminate senescent cells. However, chemotherapies relying on targeted molecular inhibitors as senolytic drugs can induce drug resistance. In the current investigation, we devised a new strategy for selective degradation of target proteins in senescent cancer cells that utilizes a prodrug composed of the SA-ß-gal substrate galactose (galacto) and the proteolysis-targeting chimeras (PROTACs) as senolytic agents. Prodrugs Gal-ARV-771 and Gal-MS99 were found to display senolytic indexes higher than those of ARV-771 and MS99. Significantly, results of in vivostudies utilizing a human lung A549 xenograft mouse model demonstrated that concomitant treatment with etoposide and Gal-ARV-771 leads to a significant inhibition of tumor growth without eliciting significant toxicity.

The air medical transport industry places a high value on developing and maintaining a culture of safety due to the higher risk nature of its operations. The dynamic nature of response and transport, inherent risks involved with flight, lack of supporting resources, weather conditions, and austere nature of the transport environment are all factors that highlight the need for enhanced safety. As such, the air medical transport industry has developed a robust and unique approach to provider and patient safety involving many tactics not otherwise used in other areas of health care. This article describes some of the unique safety features and approaches that are commonplace in the air medical transport industry and proposes a means for these initiatives to other areas of the health care system.

It was proved that the presence of epiretinal membranes is a negative prognostic factor of macular hole closure when inverted ILM flap technique is used.

We incorporate nuclear quantum effects (NQE) in condensed matter simulations by introducing short-range neural network (NN) corrections to the ab initio fitted molecular force field ARROW. Force field NN corrections are fitted to average interaction energies and forces of molecular dimers, which are simulated using the Path Integral Molecular Dynamics (PIMD) technique with restrained centroid positions. The NN-corrected force field allows reproduction of the NQE for computed liquid water and methane properties such as density, radial distribution function (RDF), heat of evaporation (HVAP), and solvation free energy. Accounting for NQE through molecular force field corrections circumvents the need for explicit computationally expensive PIMD simulations in accurate calculations of the properties of chemical and biological systems. The accuracy and locality of pairwise NN NQE corrections indicate that this approach could be applicable to complex heterogeneous systems, such as proteins.

We present a formalism of a neural network encoding bonded interactions in molecules. This intramolecular encoding is consistent with the models of intermolecular interactions previously designed by this group. Variants of the encoding fed into a corresponding neural network may be used to economically improve the representation of torsional degrees of freedom in any force field. We test the accuracy of the reproduction of the ab initio potential energy surface on a set of conformations of two dipeptides, methyl-capped ALA and ASP, in several scenarios. The encoding, either alone or in conjunction with an analytical potential, improves agreement with ab initio energies that are on par with those of other neural network-based potentials. Using the encoding and neural nets in tandem with an analytical model places the agreements firmly within “chemical accuracy” of ±0.5 kcal/mol.

Hydractiniais a colonial marine hydroid that shows remarkable biological properties, including the capacity to regenerate its entire body throughout its lifetime, a process made possible by its adult migratory stem cells, known as i-cells. Here, we provide an in-depth characterization of the genomic structure and gene content of two Hydractiniaspecies, Hydractinia symbiolongicarpusand Hydractinia echinata, placing them in a comparative evolutionary framework with other cnidarian genomes. We also generated and annotated a single-cell transcriptomic atlas for adult male H. symbiolongicarpusand identified cell-type markers for all major cell types, including key i-cell markers. Orthology analyses based on the markers revealed that Hydractinia’s i-cells are highly enriched in genes that are widely shared amongst animals, a striking finding given that Hydractiniahas a higher proportion of phylum-specific genes than any of the other 41 animals in our orthology analysis. These results indicate that Hydractinia’s stem cells and early progenitor cells may use a toolkit shared with all animals, making it a promising model organism for future exploration of stem cell biology and regenerative medicine. The genomic and transcriptomic resources for Hydractiniapresented here will enable further studies of their regenerative capacity, colonial morphology, and ability to distinguish self from nonself.

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

The rational molecular design of fullerene-based molecules with exceptional physical and electrical properties is in high demand to ensure efficient charge transport at the perovskite/electron transport layer interface. In this work, novel azahomofullerene (AHF) is designed, synthesized, and introduced as the interlayer between the SnO2/perovskite interface in planar n–i–p heterojunction perovskite solar cells (PSCs). The AHF molecule (denoted as AHF-4) is proven to enhance charge transfer capability compared to the commonly used fullerene derivative [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) due to its superior coordination interaction and electronic coupling with the SnO2surface. In addition, the AHF-4 interlayer concurrently improves the quality of the perovskite film and reduces charge recombination in PSCs. The resultant AHF-4-based device exhibits a maximum efficiency of 21.43% with lower hysteresis compared to the PCBM device (18.56%). Benefiting from the enhanced stability of the AHF-4 film toward light soaking and elevated temperature, the AHF-4-based devices show improved stability under continuous 1 sun illumination at the maximum power point and 45 °C. Our work opens a new direction to the design of AHF derivatives with favorable physical and electrical properties as an interlayer material to improve both the performance and stability of PSCs.

AbstractIn 1982, Raymond Smullyan published an article, “The Asylum of Doctor Tarr and Professor Fether,” that consists of a series of puzzles. These were later reprinted in the anthology The Lady or The Tiger? and Other Logic Puzzles. The last puzzle, which describes the asylum alluded to in the title, was designed to be especially difficult. With the help of automated reasoning, we show that the puzzle’s hypotheses are, in fact, inconsistent, which is to say, no such asylum can possibly exist.

Solution chemistry of the lanthanide(III) ions is unexplored and relevant: extraction and recycling processes exclusively operate in solution, MRI is a solution-phase method, and bioassays are done in solution. However, the molecular structure of the lanthanide(III) ions in solution is poorly described, especially for the near-IR (NIR)-emitting lanthanides, as these are difficult to investigate using optical tools, which has limited the availability of experimental data. Here we report a custom-built spectrometer dedicated to investigation of lanthanide(III) luminescence in the NIR region. Absorption, luminescence excitation, and luminescence spectra of five complexes of europium(III) and neodymium(III) were acquired. The obtained spectra display high spectral resolution and high signal-to-noise ratios. Using the high-quality data, a method for determining the electronic structure for the thermal ground states and emitting states is proposed. It combines Boltzmann distributions with population analysis and uses the experimentally determined relative transition probabilities from both excitation and emission data. The method was tested on the five europium(III) complexes and was used to resolve the electronic structures of the ground state and the emitting state of neodymium(III) in five different solution complexes. This is the first step toward correlating optical spectra with chemical structure in solution for NIR-emitting lanthanide complexes.

Photosynthetic reaction centers catalyze the majority of solar energy conversion on the Earth. Under low-intensity illumination, this is achieved with a near-unity quantum efficiency, almost every absorbed photon producing a photochemical charge separation. Biohybrid technologies seek to capture the high efficiency of natural photoproteins by combining them with man-made electrodes. However, the transfer of photoproteins from their membrane environment into an abiotic architecture invariably results in efficiency losses. Here, we combined spectroscopy and analytical electrochemistry to identify the loss processes in a reaction-center-based biophotoelectrode. While over 90% efficient under low-intensity illumination, the biophotoelectrode efficiency dropped to ∼11% under high-intensity illumination. This loss stemmed from bottlenecks in electron transfer that rendered 60% of reaction centers inactive, as well as a short-circuiting of 73% of the separated charge from active reaction centers. The quantitative insights into loss processes presented in this work will be instrumental in shaping future rational design of biophotoelectrode devices.

This work proposes a novel modeling approach for analog organic circuits using very simple to customize circuit topology and parameters of individual p- and n-type organic field effect transistors (OFETs). Aided with the combination of primitive elements (OFETs, capacitors, resistors), the convoluted behavior of analog organic neuromorphic circuits (ONCs) and even other general analog organic circuits, can be predicted. The organic log-domain integrator (oLDI) synaptic circuit, the organic differential-pair integrator (oDPI) synaptic circuit, and the organic Axon-Hillock (oAH) somatic circuit are designed and serve as the modular circuit primitives of more complicated ONCs. We first validate our modeling approach by comparing the simulated oDPI and oAH circuit responses to their experimental measurements. Thereafter, the summation effects of the excitatory and inhibitory oDPI circuits in prototyped ONCs are investigated. We also predict the dynamic power dissipation of modular ONCs and show an average power consumption of $2.1 \mu \text {J}$ per spike for the oAH soma at a ~1 Hz spiking frequency. Furthermore, we compare our modeling approach with other two representative organic circuit models and prove that our approach outperforms the other two in terms of accuracy and convergence speed.

Protein–ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)─a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein–ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ∼0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

Lanthanide luminescence fascinates with a complicated electronic structure and “forbidden” transitions. By studying the photophysics of lanthanide(III) solvates, a close to ideal average coordination geometry can be used to map both electronic energy levels and transition probabilities. Some lanthanide(III) ions are simpler to study than others, and samarium(III) belongs to the more difficult ones. The 4f5system has numerous absorption and emission lines in the visible and infrared parts of the spectrum and in this work, the energy levels giving rise to these transitions were mapped, the transition probability between them was calculated, and it was shown that the electronic structures of the samarium(III) solvates in DMSO, MeOH, and water are different.

Safranal, as an aroma in saffron, is one of the cytotoxic compounds in saffron that causes cell death in triple-negative breast cancer cells. Our recent research reported the anti-cancer effects of safranal, which further demonstrated its impact on protein translation, mitochondrial dysfunction, and DNA fragmentation. To better understand the underlying mechanisms, we identified acetylated and phosphorylated peptides in safranal-treated cancer cells. We conducted a comprehensive phosphoproteomics and acetylomics analysis of safranal-treated MDA-MB-231 cells by using a combination of TMT labeling and enrichment methods including titanium dioxide and immunoprecipitation. We provide a wide range of phosphoproteome regulation in different signaling pathways that are disrupted by safranal treatment. Safranal influences the phosphorylation level on proteins involved in DNA replication and repair, translation, and EGFR activation/accumulation, which can lead the cells into apoptosis. Safranal causes DNA damage which is followed by the activation of cell cycle checkpoints for DNA repair. Over time, checkpoints and DNA repair are inhibited and cells are under a mitotic catastrophe. Moreover, safranal prevents repair by the hypo-acetylation of H4 and facilitates the transcription of proapoptotic genes by hyper-acetylation of H3, which push the cells to the brink of death.

Purpose: To report a case of treatment of a full-thickness macular hole, which appeared after 10 months of anti-VEGF treatment in neovascular age related macular degeneration (nAMD).Methods: The patient was diagnosed as type 1 nAMD. The coexisting vitreomacular traction caused a full thickness macular hole after 10 months of treatment.Patients: A 68-year-old woman treated with anti VEGF.Results: Vitrectomy with the temporal inverted ILM flap technique succeeded in closing the hole. Further anti-VEGF treatment followed.Conclusion: FTMH is a rare complication or coexistence in nAMD. Vitrectomy and continuous anti-VEGF treatment might result in satisfactory anatomical and functional results.

Purpose:To report vitrectomy with the inverted internal limiting membrane (ILM) flap technique in a patient with a full-thickness macular hole (FTMH) and Coats disease. Methods:A case and its long-term findings were analyzed. Results:A 27-year-old patient with Coats disease who was treated 5 years earlier with laser photocoagulation presented with an FTMH. Vitrectomy with the temporal inverted ILM flap technique was performed. The macular hole decreased in size on serial OCT scans but did completely close until 18 months postoperatively. The final visual acuity was 20/40 (0.3 logMAR). The patient’s vision remained stable for the next 5 years. Conclusions:Although the healing process after vitrectomy with ILM peeling and the inverted flap technique in an FTMH coexisting with Coats disease is prolonged compared with an idiopathic FTMH, it is still possible to obtain satisfactory anatomic and functional results.

Cloud computing is gaining popularity in high-performance computing applications. Its utilization enables advanced simulations when local computing resources are limited. However, cloud usage may increase costs and entail resource unavailability risks. This article presents an original approach that employs machine learning to predict long-term cloud resource usage. This enables optimizing resource utilization through appropriate reservation plans, reducing the associated costs. The solution developed utilizes statistical models, XGBoost, neural networks and the Temporal Fusion Transformer. Long-term prediction of cloud resource consumption, especially the Cloud Resource Usage Optimization System that is critical for prolonged simulations, involves using prediction results to dynamically create resource reservation plans across various virtual machine types for HPC on the Google Cloud Platform. Experiments using real-life production data demonstrate that the TFT prediction model improved prediction quality (by 31.4%) compared to the best baseline method, particularly in adapting to chaotic changes in resource consumption. However, it should be noted that the best prediction model in terms of error magnitude might not be the most suitable for resource reservation planning. This was validated by the neural network-based method, introducing an FR metric for forecast evaluation. Resource reservation plans were assessed both qualitatively and quantitatively, focusing on various aspects like a service-level agreement compliance and potential downtime. This paper is an extension of work originally presented during the International Conference on Computational Science — ICCS 2023, entitled "Long-Term Prediction of Cloud Resource Usage in High-Performance Computing". • Novel approach that employs machine learning to provide resource usage predictions. • A Reservation Module which serves as a central point in the FinOps-driven approach. • The evaluation of diverse time series forecasting methods using a real-life dataset. • Qualitative and quantitative assessment of resource reservation plans. [ABSTRACT FROM AUTHOR]

Blacklegged ticks, Ixodes scapularisSay, transmit Lyme disease spirochetes and other human pathogens in the eastern United States. White-tailed deer (Odocoileus virginianus) are key reproductive hosts for I. scapularisadults, and therefore control methods targeting deer have the potential for landscape-wide tick suppression. A topical acaricide product, containing 10% permethrin, is self-applied by deer to kill parasitizing ticks when they visit 4-Poster Tick Control Deer Feeders (hereafter, 4-Posters) Previous 4-Poster intervention studies, including in residential settings, demonstrated suppression of I. scapularispopulations but did not include human-based outcomes. To prepare for a proposed 4-Poster intervention trial in residential areas of Connecticut and New York that would include human-tick encounters and tick-borne diseases as outcomes, we sought to identify areas (study clusters) in the 80–100 ha size range and specific locations within these areas where 4-Poster devices could be deployed at adequate density (1 device per 20–25 ha) and in accordance with regulatory requirements. Geographic Information System-based data were used to identify prospective study clusters, based on minimum thresholds for Lyme disease incidence, population density, and forest cover. Ground truthing of potential 4-Poster placement locations was done to confirm the suitability of selected clusters. Based on these efforts, we failed to identify more than a few residential areas fulfilling all criteria for a treatment cluster. We, therefore, reconsidered pursuing the intervention trial, which required inclusion of >30 treatment clusters to achieve adequate statistical power. The 4-Poster methodology may be more readily evaluated in natural or public areas than in residential settings in NY or CT.

Ixodes pacificusCooley & Kohls is the primary vector of Lyme disease spirochetes to humans in the western United States. Although not native to Alaska, this tick species has recently been found on domestic animals in the state. Ixodes pacificushas a known native range within the western contiguous United States and southwest Canada; therefore, it is not clear if introduced individuals can successfully survive and reproduce in the high-latitude climate of Alaska. To identify areas of suitable habitat within Alaska for I. pacificus, we used model parameters from two existing sets of ensemble habitat distribution models calibrated in the contiguous United States. To match the model input covariates, we calculated climatic and land cover covariates for the present (1980–2014) and future (2070–2100) climatologies in Alaska. The present-day habitat suitability maps suggest that the climate and land cover in Southeast Alaska and portions of Southcentral Alaska could support the establishment of I. pacificuspopulations. Future forecasts suggest an increase in suitable habitat with considerable uncertainty for many areas of the state. Repeated introductions of this non-native tick to Alaska increase the likelihood that resident populations could become established.