Hybrid semiconductor–metal nanoparticles (HNPs) manifest unique combined and often synergetic properties stemming from the materials combination. These structures exhibit spatial charge separation ...across the semiconductor–metal junction upon light absorption, enabling their use as photocatalysts. So far, the main impetus of photocatalysis research in HNPs addresses their functionality in solar fuel generation. Recently, it was discovered that HNPs are functional in efficient photocatalytic generation of reactive oxygen species (ROS). This has opened the path for their implementation in diverse biomedical and industrial applications where high spatially temporally resolved ROS formation is essential. Here, the latest studies on the synergistic characteristics of HNPs are summarized, including their optical, electrical, and chemical properties and their photocatalytic function in the field of solar fuel generation is briefly discussed. Recent studies are then focused concerning photocatalytic ROS formation with HNPs under aerobic conditions. The emergent applications of this capacity are then highlighted, including light‐induced modulation of enzymatic activity, photodynamic therapy, antifouling, wound healing, and as novel photoinitiators for 3D‐printing. The superb photophysical and photocatalytic properties of HNPs offer already clear advantages for their utility in scenarios requiring on‐demand light‐induced radical formation and the full potential of HNPs in this context is yet to be revealed.
Hybrid semiconductor–metal nanoparticles are promising photocatalysts. Recent research on photocatalytic functionality in anaerobic and aerobic conditions toward water splitting and reactive oxygen species formation by these hybrid nanoparticles is highlighted. Novel applications that emerge from the photocatalytic radical formation capacity are described, including in areas of biomedicine and 3D‐printing.
Epidemics and pandemics require an early estimate of the cumulative infection prevalence, sometimes referred to as the infection "Iceberg," whose tip are the known cases. Accurate early estimates ...support better disease monitoring, more accurate estimation of infection fatality rate, and an assessment of the risks from asymptomatic individuals. We find the Pivot group, the population sub-group with the highest probability of being detected and confirmed as positively infected. We differentiate infection susceptibility, assumed to be almost uniform across all population sub-groups at this early stage, from the probability of being confirmed positive. The latter is often related to the likelihood of developing symptoms and complications, which differs between sub-groups (e.g., by age, in the case of the COVID-19 pandemic). A key assumption in our method is the almost-random subgroup infection assumption: The risk of initial infection is either almost uniform across all population sub-groups or not higher in the Pivot sub-group. We then present an algorithm that, using the lift value of the pivot sub-group, finds a lower bound for the cumulative infection prevalence in the population, that is, gives a lower bound on the size of the entire infection "Iceberg." We demonstrate our method by applying it to the case of the COVID-19 pandemic. We use UK and Spain serological surveys of COVID-19 in its first year to demonstrate that the data are consistent with our key assumption, at least for the chosen pivot sub-group. Overall, we applied our methods to nine countries or large regions whose data, mainly during the early COVID-19 pandemic phase, were available: Spain, the UK at two different time points, New York State, New York City, Italy, Norway, Sweden, Belgium, and Israel. We established an estimate of the lower bound of the cumulative infection prevalence for each of them. We have also computed the corresponding upper bounds on the infection fatality rates in each country or region. Using our methodology, we have demonstrated that estimating a lower bound for an epidemic's infection prevalence at its early phase is feasible and that the assumptions underlying that estimate are valid. Our methodology is especially helpful when serological data are not yet available to gain an initial assessment on the prevalence scale, and more so for pandemics with an asymptomatic transmission, as is the case with Covid-19.
Explores the nature of the vast multinational Roman Empire through the identities of ethnic groups and the experiences of single individuals. The chapters range across the many cultures, languages, ...religions and literatures of the Empire, with a special focus on the Jews as a test-case for the larger issues.
Hybrid semiconductor–metal nanoparticles are interesting materials for use as photocatalysts due to their tunable properties and chemical processibility. Their function in the evolution of hydrogen ...in photocatalytic water splitting is the subject of intense current investigation. Here, the effects of the surface coatings on the photocatalytic function are studied, with Au‐tipped CdS nanorods as a model hybrid nanoparticle system. Kinetic measurements of the hydrogen evolution rate following photocatalytic water reduction are performed on similar nanoparticles but with different surface coatings, including various types of thiolated alkyl ligands and different polymer coatings. The apparent hydrogen evolution quantum yields are found to strongly depend on the surface coating. The lowest yields are observed for thiolated alkyl ligands. Intermediate values are obtained with L‐glutathione and poly(styrene‐co‐maleic anhydride) polymer coatings. The highest efficiency is obtained for polyethylenimine (PEI) polymer coating. These pronounced differences in the photocatalytic efficiencies are correlated with ultrafast transient absorption spectroscopy measurements, which show a faster bleach recovery for the PEI‐coated hybrid nanoparticles, consistent with faster and more efficient charge separation. These differences are primarily attributed to the effects of surface passivation by the different coatings affecting the surface trapping of charge carriers that compete with effective charge separation required for the photocatalysis. Further support of this assignment is provided from steady‐state emission and time‐resolved spectral measurements, performed on related strongly fluorescing CdSe/CdS nanorods. The control and understanding of the effect of the surface coating of the hybrid nanosystems on the photocatalytic processes is of importance for the potential application of hybrid nanoparticles as photocatalysts.
Surface coating effects on the photocatalytic properties of hybrid CdS‐Au nanorods are studied by comparing the hydrogen evolution rate and efficiencies in the water splitting reaction. Thiolated‐alkyl ligands show low yields, while polymer coatings with polyethyleneimine provide a significant increase in the apparent quantum yield due to the improved surface passivation reducing the competing surface trapping of charge carriers.
Interaction-driven modeling of diseases over real-world contact data has been shown to promote the understanding of the spread of diseases in communities. This temporal modeling follows the ...path-preserving order and timing of the contacts, which are essential for accurate modeling. Yet, other important aspects were overlooked. Various airborne pathogens differ in the duration of exposure needed for infection. Also, from the individual perspective, Covid-19 progression differs between individuals, and its severity is statistically correlated with age. Here, we enrich an interaction-driven model of Covid-19 and similar airborne viral diseases with (a) meetings duration and (b) personal disease progression. The enriched model enables predicting outcomes at both the population and the individual levels. It further allows predicting individual risk of engaging in social interactions as a function of the virus characteristics and its prevalence in the population. We further showed that the enigmatic nature of asymptomatic transmission stems from the latent effect of the network density on this transmission and that asymptomatic transmission has a substantial impact only in sparse communities.
The temporal dynamics of social interactions were shown to influence the spread of disease. Here, we model the conditions of progression and competition for several viral strains, exploring various ...levels of cross-immunity over temporal networks. We use our interaction-driven contagion model and characterize, using it, several viral variants. Our results, obtained on temporal random networks and on real-world interaction data, demonstrate that temporal dynamics are crucial to determining the competition results. We consider two and three competing pathogens and show the conditions under which a slower pathogen will remain active and create a second wave infecting most of the population. We then show that when the duration of the encounters is considered, the spreading dynamics change significantly. Our results indicate that when considering airborne diseases, it might be crucial to consider the duration of temporal meetings to model the spread of pathogens in a population.
We introduce a new approach for automated guideline-based-care quality assessment, the bidirectional knowledge-based assessment of compliance (BiKBAC) method, and the DiscovErr system, which ...implements it. Our methodology compares the guideline's Asbru-based formal representation, including its intentions, with the longitudinal medical record, using a top-down and bottom-up approach. Partial matches are resolved using fuzzy temporal logic. The system was evaluated in the type 2 Diabetes management domain, comparing it to three expert clinicians, including two diabetes experts. The system and the experts commented on the management of 10 patients, randomly selected from 2,000 diabetes patients. On average, each record spanned 5.23 years; the data included 1,584 medical transactions. The system provided 279 comments. The experts made 181 different unique comments. The completeness (recall) of the system was 91% when the gold standard was comments made by at least two of the three experts, and 98%, compared to comments made by all three experts. The experts also assessed all of the 114 medication-therapy-related comments, and a random 35% of the 165 tests-and-monitoring-related comments. The system's correctness (precision) was 81%, compared to comments judged as correct by both diabetes experts, and 91%, compared to comments judged as correct by one diabetes expert and at least as partially correct by the other. 89% of the comments were judged as important by both diabetes experts, 8% were judged as important by one expert, and 3% were judged as less important by both experts. Adding the validated system comments to the experts' comments, the completeness scores of the experts were 75%, 60%, and 55%; the expert correctness scores were respectively 99%, 91%, and 88%. Thus, the system could be ranked first in completeness and second in correctness. We conclude that systems such as DiscovErr can effectively assess the quality of continuous guideline-based care.
Demonstrability-the extent to which group members can recognize a correct solution to a problem-has a significant effect on group performance. However, the interplay between group size, ...demonstrability and performance is not well understood. This paper addresses these gaps by studying the joint effect of two factors-the difficulty of solving a problem and the difficulty of verifying the correctness of a solution-on the ability of groups of varying sizes to converge to correct solutions. Our empirical investigations use problem instances from different computational complexity classes, NP-Complete (NPC) and PSPACE-complete (PSC), that exhibit similar solution difficulty but differ in verification difficulty. Our study focuses on nominal groups to isolate the effect of problem complexity on performance. We show that NPC problems have higher demonstrability than PSC problems: participants were significantly more likely to recognize correct and incorrect solutions for NPC problems than for PSC problems. We further show that increasing the group size can actually decrease group performance for some problems of low demonstrability. We analytically derive the boundary that distinguishes these problems from others for which group performance monotonically improves with group size. These findings increase our understanding of the mechanisms that underlie group problem-solving processes, and can inform the design of systems and processes that would better facilitate collective decision-making.
Semiconductor‐metal hybrid nanoparticles (HNPs) are promising photocatalysts for redox reactions, including water reduction for hydrogen generation and reactive oxygen species (ROS) formation. Herein ...we study the effect of the metal co‐catalyst type on the light‐induced ROS formation using a combination of spectrophotometric and fluorescence assays, as well as electron paramagnetic resonance spectroscopy. We find that although Pt tips are more efficient for H2 generation, hydrogen peroxide and hydroxyl radicals are formed more effectively by Au tipped HNPs. These variations are attributed to the different surface reactivity and selectivity related to the metal tip composition. The obtained understanding contributes to the optimal design of these hybrid nanosystems as photocatalysts in various ROS‐driven applications such as photopolymerization, and environmental and biomedical scenarios.
Just the tip of the iceberg: The metal tip effect on the light‐induced redox reactions by semiconductor‐metal hybrid nanoparticles was investigated. It is demonstrated that hydrogen peroxide and hydroxyl radicals are formed more effectively by Au tipped HNPs, whereas Pt tips are more efficient for H2 generation. These variations are attributed to the specificity of the metal surface reactivity.
Semiconductor-metal hybrid nanostructures offer a highly controllable platform for light-induced charge separation, with direct relevance for their implementation in photocatalysis. Advances in the ...synthesis allow for control over the size, shape and morphology, providing tunability of the optical and electronic properties. A critical determining factor of the photocatalytic cycle is the metal domain characteristics and in particular its size, a subject that lacks deep understanding. Here, using a well-defined model system of cadmium sulfide-gold nanorods, we address the effect of the gold tip size on the photocatalytic function, including the charge transfer dynamics and hydrogen production efficiency. A combination of transient absorption, hydrogen evolution kinetics and theoretical modelling reveal a non-monotonic behaviour with size of the gold tip, leading to an optimal metal domain size for the most efficient photocatalysis. We show that this results from the size-dependent interplay of the metal domain charging, the relative band-alignments, and the resulting kinetics.
PDF
