Superradiant Emission from Coherent Excitons in van Der Waals Heterostructures

Recent advancements in isolation and stacking of layered van der Waals materials have created an unprecedented paradigm for demonstrating varieties of 2D quantum materials. Rationally designed van der Waals heterostructures composed of monolayer transition-metal dichalcogenides (TMDs) and few-layer hBN show several unique optoelectronic features driven by correlations. However, entangled superradiant excitonic species in such systems have not been observed before. In this report, it is demonstrated that strong suppression of phonon population at low temperature results in a formation of a coherent excitonic-dipoles ensemble in the heterostructure, and the collective oscillation of those dipoles stimulates a robust phase synchronized ultra-narrow band superradiant emission even at extremely low pumping intensity. Such emitters are in high demand for a multitude of applications, including fundamental research on many-body correlations and other state-of-the-art technologies. This timely demonstration paves the way for further exploration of ultralow-threshold quantum-emitting devices with unmatched design freedom and spectral tunability.     

Statistical hierarchical clustering algorithm for outlier detection in evolving data streams

Machine Learning - Anomaly detection is a hard data analysis process that requires constant creation and improvement of data analysis algorithms. Using traditional clustering algorithms to analyse...     

Emissions Production from Small Heat Sources Depending on Various Aspects

Mobile Networks and Applications - Solid fuels combustion is rather complicated because there is always environment pollution by emissions, mainly by particulate matter. The efforts of heat sources...     

Detection and analysis of triterpenic compounds in apple extracts

A new technique for the rapid detection and analysis of triterpenic compounds in apple extracts using HPLC was developed and validated. The main advantage of this technique is the short duration of the analysis – this makes this technique superior to others currently applied for the routine HPLC analysis of triterpenic compounds. The developed, optimized, and validated technique was used for the evaluation of triterpenic compounds in samples of different cultivars of apples, their peels, and flesh. In total, four triterpenic compounds were isolated and identified. Ursolic acid was the dominant compound in all the tested apple samples. The highest amounts of triterpenic compounds were detected in the peels of the ‘Lodel’ apple cultivar, and thus apples of this cultivar may be potentially useful for the isolation of individual compounds and the production of functional food and dietary supplements.     

Synthesis of ZnS nanoparticles of required size by precipitation in aerosol microdroplets

Zinc sulphide (ZnS) nanoparticles were prepared by an aerosol method from zinc acetate and sodium sulphide (Na₂S) aqueous solutions. Aqueous solution of zinc acetate was dispersed into the form of microdroplets, which were introduced by airflow to vigorously stirred aqueous solution of Na₂S, which was in excess. Microdroplets served as microreactors, so the reaction took place only in limited volume. Particle size distribution was studied by transmission electron microscopy and by dynamic light scattering measurements. In this work, the equation that allows us to predict the final size distribution of ZnS nanoparticles using exact concentration of zinc acetate was derived and ZnS nanoparticles with predicted mean particle diameter around 50 and 70?nm were successfully synthetised.     

Depassivation and repassivation of stainless steels by stepwise pH change

Immersion tests with different stainless steels have been performed, while the pH was stepwise decreased and then increased again. During 8.5-day exposure, the depassivation and repassivation pH values as a function of pitting resistance equivalent number were determined. There is always a gap between both pH values (depassivation and repassivation), indicating that for every steel, there are conditions where an existing passive layer can be maintained but cannot be rebuilt after depassivation. In such environments, the passive layer is thicker, consisting mainly of molybdenum and iron rich oxides, while chromium is dissolved. Usually, depending on conditions, the passive layer is more chromium-rich, especially the inner layer. This is relevant, for example, for acidizing jobs in oil and gas industry, proving that repassivation after acidizing will happen promptly, when the pH is increased again.     

Hybridizing adaptive large neighborhood search with kernel search: a new solution approach for the nurse routing problem with incompatible services and minimum demand

The average age of the population has grown steadily in recent decades along with the number of people suffering from chronic diseases and asking for treatments. Hospital care is expensive and often unsafe, especially for older individuals. This is particularly true during pandemics as the recent SARS-CoV-2. Hospitalization at home has become a valuable alternative to face efficiently a huge increase in treatment requests while guaranteeing a high quality of service and lower risk to fragile patients. This new model of care requires the redefinition of health services organization and the optimization of scarce resources (e.g., available nurses). In this paper, we study a Nurse Routing Problem that tries to find a good balance between hospital costs reduction and the well-being of patients, also considering realistic operational restrictions like maximum working times for the nurses and possible incompatibilities between services jointly provided to the same patient. We first propose a Mixed Integer Linear Programming formulation for the problem and use some valid inequalities to strengthen it. A simple branch-and-cut algorithm is proposed and validated to derive ground benchmarks. In addition, to efficiently solve the problem, we develop an Adaptive Large Neighborhood Search hybridized with a Kernel Search and validate its performance over a large set of different realistic working scenarios. Computational tests show how our matheuristic approach manages to find good solutions in a reasonable amount of time even in the most difficult settings. Finally, some interesting managerial insights are discussed through an economic analysis of the operating context.