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The phenomenon of underscreening in concentrated electrolyte solutions leads to a larger decay length of the charge–charge correlation than the prediction of Debye–Hückel (DH) theory and has found a resurgence of both theoretical and experimental interest in the chemical physics community. To systematically understand and investigate this phenomenon in electrolytes requires a theory of concentrated electrolytes to describe charge–charge correlations beyond the DH theory. We review the theories of electrolytes that can transition from the DH limit to concentrations where charge correlations dominate, giving rise to underscreening and the associated Kirkwood Transitions (KTs). In this perspective, we provide a conceptual approach to a theoretical formulation of electrolyte solutions that exploits the competition between molecular-informed short-range (SR) and long-range interactions. We demonstrate that all deviations from the DH limit for real electrolyte solutions can be expressed through a single function Σ Q that can be determined both theoretically and numerically. Importantly, Σ Q can be directly related to the details of SR interactions and, therefore, can be used as a tool to understand how differences in representations of interaction can influence collective effects. The precise function form of Σ Q can be inferred through a Gaussian field theory of both the number and charge densities. The resulting formulation is validated by experiment and can accurately describe the collective phenomenon of screening in concentrated bulk electrolytes. Importantly, the Gaussian field theory predictions of the screening lengths appear to be less than ∼1 nm at concentrations above KTs. [ABSTRACT FROM AUTHOR]

We establish the connection between the measured small angle x-ray scattering signal and the charge–charge correlations underlying Kirkwood transitions (KTs) in 1:1, 2:1, and 3:1 aqueous electrolytes. These measurements allow us to obtain underscreening lengths for bulk electrolytes independently verified by theory and simulations. Furthermore, we generalize the concept of KTs beyond those theoretically predicted for 1:1 electrolytes, which involves the inverse screening length, a0, and the inverse periodicity length, Q0. Above the KTs, we find a universal scaling of a 0 ∝ c − ζ / 3 and Q0 ∝ c1/3 for the studied electrolyte solutions, where ζ is the ionic strength factor. [ABSTRACT FROM AUTHOR]

Mechanisms of CaCO3 nucleation from solutions that depend on multistage pathways and the existence of species far more complex than simple ions or ion pairs have recently been proposed. Herein, we provide a tightly coupled theoretical and experimental study on the pathways that precede the initial stages of CaCO3 nucleation. Starting from molecular simulations, we succeed in correctly predicting bulk thermodynamic quantities and experimental data, including equilibrium constants, titration curves, and detailed x-ray absorption spectra taken from the supersaturated CaCO3 solutions. The picture that emerges is in complete agreement with classical views of cluster populations in which ions and ion pairs dominate, with the concomitant free energy landscapes following classical nucleation theory.

Background Human immunodeficiency virus type 1 (HIV-1) acquired drug resistance (ADR) compromises antiretroviral therapy (ART). Methods We aggregated all HIV-1 protease–reverse transcriptase–integrase sequences over 2004–2021 at the largest HIV center in Rhode Island and evaluated ADR extent, trends, and impact using Stanford Database tools. Trends were measured with Mann-Kendall statistic, and multivariable regressions evaluated resistance predictors. Results Sequences were available for 914 ART-experienced persons. Overall ADR to any drug decreased from 77% to 49% (−0.66 Mann-Kendall statistic); nucleoside reverse transcriptase inhibitors 65% to 32%, nonnucleoside reverse transcriptase inhibitors 53% to 43%, and protease inhibitors 28% to 7% (2004–2021), and integrase strand transfer inhibitors 16% to 13% (2017–2021). Multiclass resistance decreased from 44% to 12% (2-class) and 12% to 6% (3-class). In 2021, 94% had at least one 3-drug or 2-drug one-pill-once-daily (OPOD) option. Males and those exposed to more ART regimens were more likely to have ≥2-class resistance, and higher regimen exposure was also associated with fewer OPOD options. Conclusions Comprehensive analyses within a densely-sampled HIV epidemic over 2004–2021 demonstrated decreasing ADR. Continued ADR monitoring is important to maintain ART success, particularly with rising INSTI use in all lines of therapy and 2-drug and long-acting formulations. [ABSTRACT FROM AUTHOR]

Yield monitoring technology (YM) is a valuable tool to evaluate crop performance in on‐farm research (OFR). However, limited information exists on utilizing this technology to accurately inform OFR. The objectives of this study were to evaluate the ability of grain yield monitor mass flow sensors to detect changes in corn (Zea mays L.) yield for different plot lengths, provide a recommended minimum plot length to utilize YM in OFR, and determine if differences in estimating yield existed between YMs. Six treatment lengths that varied in distance of intentional yield differences (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were created by alternating high‐yield (202 kg N/ha application) and low‐yield (0 kg N/ha application) plots. A total of four grain YMs with impact‐style mass flow sensors were used within two commercially available combines. Yield comparisons were made between the plot combine and YMs to evaluate the accuracy of each technology for detecting the magnitude of yield change across lengths using analysis of variance and exponential regression curves. Results indicated that the mass flow sensors were not sensitive enough to detect quickly changing flow rates for alternating yield changes in small plot lengths. Minimum plot lengths ranged from 43 to 107 m depending on YM. Significant differences were observed between grain YMs from different manufacturers. Future work could evaluate the influence additional crops or smaller yield differences have on the optimum OFR plot length. Core Ideas: The mass flow sensors tested were unable to detect yield variations over small plot lengths (7.6 m).Minimum plot length for detecting treatment yield differences ranged from 43 to 107 m depending on the technology.Technologies varied in their ability to quantify the true magnitude of yield changes compared to the plot combine.Proper calibration and understanding limitations of yield monitoring systems are key for use in on‐farm research. [ABSTRACT FROM AUTHOR]

Background Human immunodeficiency virus (HIV) remains a global challenge and novel measures for transmission disruption are needed. Contact tracing is limited by reluctance or inability of newly diagnosed individuals to name at-risk contacts. Molecular cluster analysis is mostly used for outbreak investigations, and its role in routine public health activities remains uncertain. Methods We conducted a 2-year prospective statewide study in Rhode Island to evaluate integration of HIV cluster analyses into routine contact tracing, by attempting to reinterview all new diagnoses who clustered, notifying them of clustering, and evaluating benefits of this strategy. Clustering was compared between a phylogenetic ensemble versus distance-based HIV-TRACE. Results Of 100 new diagnoses during 2021–2022, 52 individuals clustered, of whom only 31% were reinterviewed. Reinterviewing did not improve contact tracing beyond initial interviews, and the study was stopped early for futility. Clustering concordance within the phylogenetic ensemble was high (88%–89%), but lower (74%) for HIV-TRACE. Despite hypothesis rejection, we established a public health–academic partnership, developed a bioinformatics pipeline enabling near real-time cluster analysis, and identified gaps and unique opportunities for intervention. Conclusions Attempting to reinterview all statewide new HIV diagnoses in molecular clusters showed no evidence of improving contact tracing. However, a strong academic–public health partnership enabled near real-time, longitudinal integration of molecular cluster analysis into routine public health activities, and identified barriers and opportunities tailoring data-driven approaches to unique individual and community characteristics, guiding future work on optimal use of molecular epidemiology to disrupt HIV transmission. [ABSTRACT FROM AUTHOR]

The digitalization of agriculture is rapidly changing the way farmers do business. With the integration of advanced technology, farmers are now able to increase efficiency, productivity, and precision in their operations. Digitalization allows for real-time monitoring and management of crops, leading to improved yields and reduced waste. This paper presents a review of some of the use cases that digitalization has made an impact in the automation of open-field and closedfield cultivations by means of collecting data about soils, crop growth, and microclimate, or by contributing to more accurate decisions about water usage and fertilizer application. The objective was to address some of the most recent technological advances that are leading to increased efficiency and sustainability of crop production, reduction in the use of inputs and environmental impacts, and releasing manual workforces from repetitive field tasks. The short discussions included at the end of each case study attempt to highlight the limitations and technological challenges toward successful implementations, as well as to introduce alternative solutions and methods that are rapidly evolving to offer a vast array of benefits for farmers by influencing cost-saving measures. This review concludes that despite the many benefits of digitalization, there are still a number of challenges that need to be overcome, including high costs, reliability, and scalability. Most of the available setups that are currently used for this purpose have been custom designed for specific tasks and are still too expensive to be implemented on commercial scales, while others are still in their early stages of development, making them not reliable or scalable for widespread acceptance and adoption by farmers. By providing a comprehensive understanding of the current state of digitalization in agriculture and its impact on sustainable crop production and food security, this review provides insights for policy-makers, industry stakeholders, and researchers working in this field. [ABSTRACT FROM AUTHOR]