Model-independent measurements of the sodium magneto-optical trap's excited-state population

We present model-independent measurements of the excited-state population of atoms in a sodium (Na) magneto-optical trap (MOT) using a hybrid ion-neutral trap composed of a MOT and a linear Paul trap (LPT). We photoionize excited Na atoms trapped in the MOT and use two independent methods to measure the resulting ions: directly by trapping them in our LPT, and indirectly by monitoring changes in MOT fluorescence. By measuring the ionization rate via these two independent methods, we have enough information to directly determine the population of MOT atoms in the excited-state. The resulting measurement reveals that there is a range of trapping-laser intensities where the excited-state population of atoms in our MOT follows the standard two-level model intensity-dependence. However, an experimentally determined effective saturation intensity must be used instead of the theoretically predicted value from the two-level model. We measured the effective saturation intensity to be $I_\mathrm{se}=22.9(3)\:\textrm{mW}/\textrm{cm}^2$ for the type-I Na MOT and $I_\mathrm{se}=48.9(7)\;\textrm{mW}/\textrm{cm}^2$ for the type-II Na MOT, approximately 1.7 and 3.6 times the theoretical estimate, respectively. Lastly, at large trapping-laser intensities, our experiment reveals a clear departure from the two-level model at a critical intensity that we believe is due to a state-mixing effect, whose critical intensity can be determined by a simple power broadening model.Comment: 10 pages, 8 figure

A general aspect-term-extraction model for multi-criteria recommendations

In recent years, increasingly large quantities of user reviews have been made available by several e-commerce platforms. This content is very useful for recommender systems (RSs), since it reflects the users' opinion of the items regarding several aspects. In fact, they are especially valuable for RSs that are able to exploit multi-faceted user ratings. However, extracting aspect-based ratings from unstructured text is not a trivial task. Deep Learning models for aspect extraction have proven to be effective, but they need to be trained on large quantities of domain-specific data, which are not always available. In this paper, we explore the possibility of transferring knowledge across domains for automatically extracting aspects from user reviews, and its implications in terms of recommendation accuracy. We performed different experiments with several Deep Learning-based Aspect Term Extraction (ATE) techniques and Multi-Criteria recommendation algorithms. Results show that our framework is able to improve recommendation accuracy compared to several baselines based on single-criteria recommendation, despite the fact that no labeled data in the target domain was used when training the ATE model

An investigation on the impact of natural language on conversational recommendations

In this paper, we investigate the combination of Virtual Assistants and Conversational Recommender Systems (CoRSs) by designing and implementing a framework named ConveRSE, for building chatbots that can recommend items from different domains and interact with the user through natural language. An user experiment was carried out to understand how natural language influences both the cost of interaction and recommendation accuracy of a CoRS. Experimental results show that natural language can indeed improve user experience, but some critical aspects of the interaction should be mitigated appropriately

Evidence of sympathetic cooling of Na+ ions by a Na MOT in a hybrid trap

A hybrid ion-neutral trap provides an ideal system to study collisional dynamics between ions and neutrals. This system provides a general cooling method that can be applied to optically inaccessible species and can also potentially cool internal degrees of freedom. The long range polarization potentials ($V\propto-\alpha/r^4$) between ions and neutrals result in large scattering cross sections at cold temperatures, making the hybrid trap a favorable system for efficient sympathetic cooling of ions by collisions with neutral atoms. We present experimental evidence of sympathetic cooling in a hybrid trap of \ce{Na+} ions, which are closed shell and therefore do not have a laser induced atomic transition, by equal mass cold Na atoms in a magneto-optical trap (MOT).Comment: 7 figure

Safety and commercial issues in fresh mushrooms and mushroom-based products sold at retail in Tuscany region

The compliance to European and National safety and labelling requirements relating to the sale of spontaneous and cultivated mushrooms and mushroom-based products in Tuscany was assessed. The evidence was collected by the Mycological Inspectorate of North-West Tuscany Local Health Authority during 90 inspections (from 2016 to 2020) at large-scale distribution stores, wholesalers, and restaurants in 10 cities belonging to 3 provinces, and on the labelling analysis of 98 commercial products collected at retail in 2021. Despite a substantial compliance of the inspected activities and products with the regulatory requirements, critical issues were highlighted: 1) EU legislative gap in the definition of specific measures for the safe sale of spontaneous mushrooms; 2) improper shelf storage temperatures of fresh-cut products; 3) incorrect condition of use on the labels of pre-packaged products; 4) lack of countryof-origin declaration in pre-packaged products. Furthermore, the labelling analysis highlighted that 18.4% and 15.3% of the products presented issues in the validity and correctness of the scientific names respect to national requirements in. A revision of the current EU legislation is needed to guarantee consumers safety, also considering the relevant number of poisoning cases related to false mycetisms (ingestion of edible mushrooms unproperly stored or used). Also, a specific revision and harmonization of the EU labelling of mushrooms would be desirable to protect consumers

Heisenberg scaling precision in multi-mode distributed quantum metrology

We consider the estimation of an arbitrary parameter φ, such as the temperature or a magnetic field, affecting in a distributed manner the components of an arbitrary linear optical passive network, such as an integrated chip. We demonstrate that Heisenberg scaling precision (i.e. of the order of 1/N, where N is the number of probe photons) can be achieved without any iterative adaptation of the interferometer hardware and by using only a simple, single, squeezed light source and well-established homodyne measurements techniques. Furthermore, no constraint on the possible values of the parameter is needed but only a preliminary shot-noise estimation (i.e. with a precision of) easily achievable without any quantum resources. Indeed, such a classical knowledge of the parameter is enough to prepare a single, suitable optical stage either at the input or the output of the network to monitor with Heisenberg-limited precision any variation of the parameter to the order of without the need to iteratively modify such a stage

Ion-neutral sympathetic cooling in a hybrid linear rf Paul and magneto-optical trap

Long range polarization forces between ions and neutral atoms result in large elastic scattering cross sections, e.g., 10^6 a.u. for Na+ on Na or Ca+ on Na at cold and ultracold temperatures. This suggests that a hybrid ion-neutral trap should offer a general means for significant sympathetic cooling of atomic or molecular ions. We present SIMION 7.0 simulation results concerning the advantages and limitations of sympathetic cooling within a hybrid trap apparatus, consisting of a linear rf Paul trap concentric with a Na magneto-optical trap (MOT). This paper explores the impact of various heating mechanisms on the hybrid system and how parameters related to the MOT, Paul trap, number of ions, and ion species affect the efficiency of the sympathetic cooling

Clinical characteristics, neuroimaging findings, and neuropsychological functioning in attention-deficit hyperactivity disorder: Sex differences

Recent clinical studies, in both children/adolescents and adults, have shown the extreme neuropsychological heterogeneity of attention-deficit hyperactivity disorder (ADHD): specific neuropsychological deficits have been found only in a minority of individuals, with no direct correlation between discrete cognitive performances and the trajectory of clinical symptoms. Deficits in specific neuropsychological functions may be common in ADHD, but nevertheless no cognitive or neuropsychological profile may fully explain the disorder. Sex differences in the ADHD presentation, both at a neuropsychological and clinical level, also contribute to this clinical and neuropsychological heterogeneity. At a neuropsychological level, females with ADHD may show greater working memory problems, poorer vocabulary skills and worse visual spatial reasoning. Structural and functional imaging study also show discrete differences across sex; however, the great majority of clinical studies mainly or exclusively include male participants with insufficient data to draw firm conclusions on sex differences within the disorder. Here, we report the recent literature data, discussing still open research questions about the clinical presentation, neuroimaging findings, and neuropsychological functioning in ADHD with a focus on the impact of sex differences—a deeper insight in these unresolved issues may have relevant clinical and therapeutic implications for tailored, effective, and long-lasting interventions

A comparison of services for intent and entity recognition for conversational recommender systems

Conversational Recommender Systems (CoRSs) are becoming increasingly popular. However, designing and developing a CoRS is a challenging task since it requires multi-disciplinary skills. Even though several third-party services are available for supporting the creation of a CoRS, a comparative study of these platforms for the specific recommendation task is not available yet. In this work, we focus our attention on two crucial steps of the Conversational Recommendation (CoR) process, namely Intent and Entity Recognition. We compared four of the most popular services, both commercial and open source. Furthermore, we proposed two custom-made solutions for Entity Recognition, whose aim is to overcome the limitations of the other services. Results are very interesting and give a clear picture of the strengths and weaknesses of each solution