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Abstract As the world faces growing environmental challenges, understanding the nature of microplastics—such as Low-Density Polyethylene (LDPE) and Polyurethane (PU)—and their transformation in water-based environments is necessary for predicting and mitigating their effects. In this study, we investigated their physicochemical characteristics, presence of impurities, colloidal behavior, and sorption capacity to understand better how microplastics behave and transform in the environment, including their role in transporting heavy metals. The two types of microparticles investigated fall into distinct size ranges, approximately 70 microns for PE particles and around 5 microns for PU particles. Both samples showed a spherical morphology and an evident surface micro-roughness. The elemental and thermal analysis did not show the presence of any significant metal impurities. The zeta-potential measurements as a function of pH provided insights into the dispersion behavior of microplastics (MPs) in freshwaters, suitable for the growth of Zebrafish (Egg water) and Daphnia magna (Elendt M7 Water). Both materials showed in bidistilled water negative zeta potential (ZP) at natural pH (ZP = − 51.0 ± 4.3 mV at pH = 6.6 and ZP = − 29.5 ± 1.4 mV at pH = 5.6 for LDPE and PU, respectively), justified by the presence of surface-active charged impurities. In saline media, ZP vs. pH curves were flatter, with ZP values near 0 mV, confirming the reduced colloidal stability from higher ionic strength and double-layer compression. Finally, we assessed the metal adsorption capacity to establish the role of microplastics in the transport of heavy metals in the environment. We observed selective adsorption for Cu2⁺ ions, which was both medium-dependent (more ions adsorbed in Elendt M7) and plastic-dependent, with PU showing a stronger affinity for Cu2⁺ in MilliQ and Egg water. On the contrary, both plastics showed similar adsorption capacity for Fe3⁺ ions across all media.

The synthesis of silver nanoparticles with controlled physicochemical properties is essential for governing their intended functionalities and safety profiles. However, synthesis process involves multiple parameters that could influence the resulting properties. This challenge could be addressed with the development of predictive models that forecast endpoints based on key synthesis parameters. In this study, we manually extracted synthesis-related data from the literature and leveraged various machine learning algorithms. Data extraction included parameters such as reactant concentrations, experimental conditions, as well as physicochemical properties. The antibacterial efficiencies and toxicological profiles of the synthesized nanoparticles were also extracted. In a second step, based on data completeness, we employed regression algorithms to establish relationships between synthesis parameters and desired endpoints and to build predictive models. The models for core size and antibacterial efficiency were trained and validated using a cross-validation approach. Finally, the features’ impact was evaluated via Shapley values to provide insights into the contribution of features to the predictions. Factors such as synthesis duration, scale of synthesis and the choice of capping agents emerged as the most significant predictors. This study demonstrated the potential of machine learning to aid in the rational design of synthesis process and paves the way for the safe-by-design principles development by providing insights into the optimization of the synthesis process to achieve the desired properties. Finally, this study provides a valuable dataset compiled from literature sources with significant time and effort from multiple researchers. Access to such datasets notably aids computational advances in the field of nanotechnology.

As the world faces growing environmental challenges, understanding the nature of microplastics—such as Low-Density Polyethylene (LDPE) and Polyurethane (PU)—and their transformation in water-based environments is necessary for predicting and mitigating their effects. In this study, we investigated their physicochemical characteristics, presence of impurities, colloidal behavior, and sorption capacity to understand better how microplastics behave and transform in the environment, including their role in transporting heavy metals. The two types of microparticles investigated fall into distinct size ranges, approximately 70 microns for PE particles and around 5 microns for PU particles. Both samples showed a spherical morphology and an evident surface micro-roughness. The elemental and thermal analysis did not show the presence of any significant metal impurities. The zeta-potential measurements as a function of pH provided insights into the dispersion behavior of microplastics (MPs) in freshwaters, suitable for the growth of Zebrafish (Egg water) and Daphnia magna (Elendt M7 Water). Both materials showed in bidistilled water negative zeta potential (ZP) at natural pH (ZP = − 51.0 ± 4.3 mV at pH = 6.6 and ZP = − 29.5 ± 1.4 mV at pH = 5.6 for LDPE and PU, respectively), justified by the presence of surface-active charged impurities. In saline media, ZP vs. pH curves were flatter, with ZP values near 0 mV, confirming the reduced colloidal stability from higher ionic strength and double-layer compression. Finally, we assessed the metal adsorption capacity to establish the role of microplastics in the transport of heavy metals in the environment. We observed selective adsorption for Cu2⁺ ions, which was both medium-dependent (more ions adsorbed in Elendt M7) and plastic-dependent, with PU showing a stronger affinity for Cu2⁺ in MilliQ and Egg water. On the contrary, both plastics showed similar adsorption capacity for Fe3⁺ ions across all media. [ABSTRACT FROM AUTHOR]

Book Review

Les fouilles menées entre 1963 et 1967 dans la cathédrale de Saint-Gall, ancienne abbatiale du monastère bien connu pour sa fameuse bibliothèque baroque, ont mis au jour 266 fragments sculptés de différentes périodes. 82 pièces sont attribuables au haut Moyen Âge : des fragments de chancel, ainsi que des bases, chapiteaux de colonne, chapiteaux de pilier et tailloirs monumentaux. Sur ces sculptures est récemment parue une publication exhaustive qui rend accessible à tout le monde ce trésor exceptionnel et précieux. La documentation réalisée se compose non seulement de descriptions, photographies et dessins, mais également de scans 3D et restitutions virtuelles – pour les objets comme pour l’architecture. En ce qui concerne le contexte archéologique, il reste à remarquer que la documentation des fouilles de l’époque n’est pas encore suffisamment élaborée. Mais, à l’aide des quelques rapports préliminaires, on peut restituer l’emplacement des œuvres et proposer ainsi leur datation, surtout pour les sculptures monumentales.

The incidence of colorectal cancer (CRC) after liver transplantation is 0.5%–4%. Laparoscopic surgery is the standard-of-care treatment, however it is rarely performed in patients who had previously undergone liver transplantation. Few reports exist regarding minimally invasive surgery in such context and none about laparoscopic right colectomy. We present the case of a 64-year-old female with a history of liver transplantation in 2001 and who developed a right-sided CRC. A laparoscopic right colectomy was successfully performed, and the post-operative course was uneventful. Given the known benefits, we believe that laparoscopic approach should be considered in such patients.

Acute calculus cholecystitis (ACC) is increasing in frequency within an ageing population, in which biliary tract infection, including cholecystitis and cholangitis, is the second most common cause of sepsis, with higher morbidity and mortality rates. Patient’s critical conditions, such as septic shock or anaesthesiology contraindication, may be reasons to avoid laparoscopic cholecystectomy—the first-line treatment of ACC—preferring gallbladder drainage. It can aid in patient’s stabilization with also the benefit of identifying the causative organism to establish a targeted antibiotic therapy, especially in patients at high risk for antimicrobial resistance such as healthcare-associated infection. Nevertheless, a recent randomized clinical trial showed that laparoscopic cholecystectomy can reduce the rate of major complications compared with percutaneous catheter drainage in critically ill patients too. On the other hand, among the possibilities to control biliary sepsis in non-operative management of ACC, according to recent meta-analysis, endoscopic gallbladder drainage showed better clinical success rate, and it is gaining popularity because of the potential advantage of allowing gallstones clearance to reduce recurrences of ACC. However, complications that may arise, although rare, can worsen an already weak clinical condition, as happened to the high surgical-risk elderly patient taken into account in our case report.

The aim of this study is to investigate the role of the assimilation of Doppler weather radar (DWR) data in a mesoscale model for the forecast of a heavy rainfall event that occurred in Italy in the urban area of Rome from 19 to 22 May 2008. For this purpose, radar reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model, version 3.4.1. The general goal is to improve the quantitative precipitation forecasts (QPF): with this aim, several experiments are performed using the three-dimensional variational (3DVAR) technique. Moreover, sensitivity tests to outer loops are performed to include non-linearity in the observation operators. In order to identify the best initial conditions (ICs), statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a large impact on both the position of convective cells and on the rainfall forecast of the analyzed event. A positive impact is also found if they are ingested together with conventional observations. Sensitivity to the use of two or three outer loops is also found if DWR data are assimilated together with conventional data.

Die cluniazensische Prioratskirche von Payerne VD/CH, die sog. Abbatiale, steht über einem römischen Gebäudekomplex. Ein für das Jahr 587 in Payerne genanntes templum sancte Marie kann nur vage und auf einer Indizienkette aufbauend lokalisiert werden – im Bereich des Gebäudekomplexes zwar, aber unter der heutigen Pfarrkirche. Archäologisch erforscht ist diese nicht. Fast 400 Jahre später, 961, 973 und 983 erscheinen die nächsten Erwähnungen einer Kirche und eines Klosters in Payerne. Diese aecclesiae entsprechen einer Stifts- und Klosterkirche. Das Monasterium kann mit der Cluniazenserpriorat identifiziert werden. Doch das Aussehen der im 10. Jahrhundert schriftlich belegten Bauten kann wegen fehlender, exakter archäologischer Datierungen nicht weiter konkretisiert werden.

Objectives. This prospective, observational, multicentre study aims to identify electrodiagnostic (EDX) markers of clinical recovery in patients with traumatic neuropathy (TN) receiving surgical (S) and nonsurgical (NS) treatments. Methods. Subjects referred to the Italian Traumatic Neuropathy Network between 2010 and 2011 (307 patients, for a total of 444 TN) were evaluated with serial clinical/EDX evaluations at 6, 12, 24, and 36 months of follow-up. Results. Primary surgery was performed in 21 subjects with open lesions and evidence of neurotmesis, while closed lesions were treated with either conservative medical approach (216 patients) or secondary surgery (70 patients), according to the clinical spontaneous recovery at 4–6 months. Clinical improvement correlated with the increase of the compound muscle action potential amplitude (OR 3.76; CI 1.61–8.76), particularly in the S group (OR 7.25; CI 1.2–43.87), and with sensory nerve action potential amplitude in the NS group (OR 4.35; CI 1.14–16.69). No correlations were found with needle electromyography qualitative evaluations, changes in maximal voluntary recruitment, age, and gender. Conclusions. Nerve conduction studies (NCS) represent the more accurate neurophysiological markers of clinical outcome in patients with TN. Significance. Serial NCS assessments predict the functional recovery in TN, increasing the accuracy of peripheral nerves surgical decision-making process.

/Evel Gasparini. From Russian Literature to Slavic Ethnology./ A quarter of a century has passed since the death of Evel Gasparini (1900–1982), a prominent Italian Slavicist and anthropologist. Presenting his life and work, this article focuses on his interest in art and in ideas of Fyodor Mikhailovich Dostoevsky and, on the other hand, on his passionate research of cultural history and Slavic ethnology, of their development, and of their mature stages. Gasparini had obtained considerable helpful assistance from South Slavic ethnographers such as Milko Matičetov and others.

The assimilation of Special Sensor Microwave Imager (SSM/I) data into the Mesoscale Model 5 (MM5) allows for improving the weather forecast. However the results suggested an update the Radiative Transfer Equation (RTE) within the three-dimensional variational (3DVAR) algorithm which is tailored for non rainy conditions only. To this purpose, a new RTE algorithm is tested, in order to account for radiometric response in rainy regions. The new brightness temperatures (TB) are estimated by using hydrometeor profiles from the MM5 mesoscale model, running with two different microphysical parameterizations. The goodness of the results is assessed by comparing the new TB with those of the original RTE algorithm in the 3DVAR code and the SSM/I observed data. The results confirm a better reliability of the new RTE compared to the old one.

Data assimilation by 3DVAR of data from the Special Sensor Microwave/Imager (SSM/I) has been performed to study the IOP2b case (19-21 September 1999) of the Mesoscale Alpine Programme (MAP). Only data over the sea surface are used to avoid the contamination of the surface emissivity. Moreover, the rainy data are filtered out because the assimilation algorithm of 3DVAR does not take into account the scattering processes. SSM/I data are assimilated in two different ways: as Brightness Temperature directly, or as Precipitable Water and surface wind speed retrieved from the Brightness Temperature. The effect of the thinning of the observations has been studied and a set of sensitivity test cases has been carried out; the one by one removal of the SSM/I frequencies from the initial dataset allows to evaluate their impact on the Initial Conditions. A few experiments are performed using these new Initial Conditions to initialize the MM5 (PSU/NCAR) model. The results show that the assimilation of the retrieved quantities, i.e. Precipitable Water and surface wind speed, does not produces large improvement in the Initial Conditions. Vice versa, the assimilation of the Brightness temperatures produces a large variability of the Initial Conditions. The forecast experiments show that the model is very sensitive to the 22GHz and 37GHz frequencies.

Global Positioning System Zenith Total Delay (GPS ZTD) can provide information about the water vapour in atmosphere. Its assimilation into the analysis used to initialize a model can then improve the weather forecast, giving the right amount of moisture and reducing the model spinup. In the last year, an high density GPS network has been created on the Basilicata region (south of Italy) by the Italian Space Agency in the framework of a national project named MAGIC2. MAGIC2 is the Italian follow on of the EC project MAGIC has. Daily operational data assimilation experiments are performed since December 2003. The results show that the assimilation of GPS ZTD improves the forecast especially during the transition from winter to spring even if a no very high model resolution (9km) is used.

In autumn deep convection in the Mediterranean region is a common phenomenon. The local events characterized by deep convection are still a difficult task even for high resolution numerical weather prediction. Three flood cases, produced by convection either embedded in a large scale system or locally developed, occurring in Italy, are presented. All these case were not correctly forecasted: Sardinia (Cagliari, 13 November 1999); Calabria (Soverato, 7 September 2000) and Sicily (Catania, 16 September 2003). The first case occurred during the Mesoscale Alpine Programme (MAP) campaign, therefore a lot of data are available; for the second one only data from SSM/I and local rain-gauge are available; the third one occurred during the operational experimentation of the TOUGH project. The last one was not well predicted even using the operational assimilation of ground based GPS. To improve the forecast of these cases the assimilation of several data is tested. The variational assimilation performed using 3DVAR of GPS, SSM/I and surface and upper air data is applied to improve the Initial Conditions of the Sicily case. The Sardinia case is improved using either GPS and surface data, whereas for the Soverato case only ZTD is assimilated. The experiments are performed using the MM5 model from Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR); the model is initialized using the new Initial Conditions produced by the variational assimilation of conventional and non conventional data. The results show that the assimilation of the retrieved quantities does produces large improvement in the precipitation forecast. Large sensitivity to the assimilation of surface data and brightness temperature from SSM/I is found.