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Introduction. In this prospective multicenter analysis, we aimed to investigate the predictive role of neutrophil/lymphocyte ratio (NLR) in permanent pacemaker implantation (PPI) in patients undergoing transcatheter aortic valve replacement (TAVR). Material and methods. 179 consecutive patients without previous PPI underwent TAVR from February 2017 to September 2021. Patients were further divided based on presence (n=48) and absence of conduction abnormalities (CAs) at hospital admission (n=131). Results. In patients with previous CAs, NLR values did not differ significantly between patients requiring PPI (n=16, 33%) and those not requiring it. In contrast, in patients with no CAs at hospital admission, NLR values measured at admission and on TAVR day were significantly higher in patients requiring PPI (n=17, 13%) (4.07±3.22 vs 3.01±1.47, p=0.025, and 10.81±7.81 vs 5.84±3.78, p=0.000, respectively). Multivariable analysis showed that NLR at TAVR day was an independent predictor of PPI in patients without CAs (OR 1.294; 95% CI 1.028-1.630; p=0.028), but not in those with previous CAs. ROC curve analysis showed that the cut point was a NLR value of >7.25. Time to PPI was delayed till 21 days in patients without CAs. Conclusions. In this prospective study, higher NLR values on the day of TAVR day were associated with an increased PPI rate in patients undergoing TAVR with no previous CAs. It is advisable, being inflammation part of the process, to prolong the time of observation for all patients without CAs till at least 21 days not to miss any new CA necessitating PPI.

The Transiting Exoplanet Survey Satellite (TESS) has detected thousands of exoplanet candidates since 2018, most of which have yet to be confirmed. A key step in the confirmation process of these candidates is ruling out false positives through vetting. Vetting also eases the burden on follow-up observations, provides input for demographics studies, and facilitates training machine learning algorithms. Here, we present the TESS Triple-9 (TT9) catalog – a uniformly vetted catalog containing dispositions for 999 exoplanet candidates listed on ExoFOP-TESS, known as TESS Objects of Interest (TOIs). The TT9 was produced using the Discovery And Vetting of Exoplanets pipeline, dave, and utilizing the power of citizen science as a part of the Planet Patrol project. More than 70 per cent of the TOIs listed in the TT9 pass our diagnostic tests, and are thus marked as true planet candidates. We flagged 144 candidates as false positives, and identified 146 as potential false positives. At the time of writing, the TT9 catalog contains $\sim 20{{\ \rm per\ cent}}$ of the entire ExoFOP-TESS TOIs list, demonstrates the synergy between automated tools and citizen science, and represents the first stage of our efforts to vet all TOIs. Our final dispositions and comments are collected in a supplementary table and the dave-generated files are publicly available on ExoFOP TESS.

Platinum complexes are ubiquitous in chemistry and largely used as catalysts or as precursors in drug chemistry, thus a deep knowledge of their electronic properties may help in planning new synthetic strategies or exploring new potential applications. Herein, the electronic structure of many octahedral platinum “IV” complexes is drastically revised especially when the metal is associated with electronegative elements such as halogens and chalcogens. The investigation revealed that in most of the cases the five d platinum orbitals are invariably full, thus the empty antibonding orbitals, usually localized on the metal, are mainly centered on the ligands, suggesting a questionable assignment of oxidation state IV. The analysis supports the occurrence of the Inverted Ligand Field theory in all cases with the only exceptions of the Pt-F and Pt-O bonding. The trends for the molecular complexes are mirrored also by the Density of States plots of extended structures featuring octahedral platinum moieties in association with chalcogens atoms. Based on the gathered information on the electronic structure of complexes and materials, the oxidative addition of a Se-Cl linkage to a square platinum complex to achieve an octahedral moiety has been revised in the framework of the Inverted Ligand Field.

Objective Breast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification. Methods In this retrospective study, four readers labelled four-view mammograms as BAC positive (BAC+) or BAC negative (BAC−) at image level. Starting from a pretrained VGG16 model, we trained a convolutional neural network to discriminate BAC+ and BAC− mammograms. Accuracy, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) were used to assess the diagnostic performance. Predictions of calcified areas were generated using the generalized gradient-weighted class activation mapping (Grad-CAM++) method, and their correlation with manual measurement of BAC length in a subset of cases was assessed using Spearman ρ. Results A total 1493 women (198 BAC+) with a median age of 59 years (interquartile range 52–68) were included and partitioned in a training set of 410 cases (1640 views, 398 BAC+), validation set of 222 cases (888 views, 89 BAC+), and test set of 229 cases (916 views, 94 BAC+). The accuracy, F1 score, and AUC-ROC were 0.94, 0.86, and 0.98 in the training set; 0.96, 0.74, and 0.96 in the validation set; and 0.97, 0.80, and 0.95 in the test set, respectively. In 112 analyzed views, the Grad-CAM++ predictions displayed a strong correlation with BAC measured length (ρ = 0.88, p Conclusion Our model showed promising performances in BAC detection and in quantification of BAC burden, showing a strong correlation with manual measurements. Clinical relevance statement Integrating our model to clinical practice could improve BAC reporting without increasing clinical workload, facilitating large-scale studies on the impact of BAC as a biomarker of cardiovascular risk, raising awareness on women’s cardiovascular health, and leveraging mammographic screening. Key Points • We implemented a deep convolutional neural network (CNN) for BAC detection and quantification. • Our CNN had an area under the receiving operator curve of 0.95 for BAC detection in the test set composed of 916 views, 94 of which were BAC+ . • Furthermore, our CNN showed a strong correlation with manual BAC measurements (ρ = 0.88) in a set of 112 views.

This document report inpictorial directions howstudents can build "ScegliTappi", a simple device capable of selecting the plastic cap based on a defined color.The sequence diagrams allow students, in small groups, to successfully complete this task using the Lego © Education Spike Essential kit. The software diagram is also included.

Welfare assessment of dairy calves is commonly conducted through the observation of their behavior and the analysis of physiological parameters. Despite the large number of studies on this topic, there is a lack of research on the possible correlation between the physiological parameters and behavior at basal level in dairy calves. For this reason, the present study aimed to investigate the possible correlations between serum cortisol, neutrophil-to-lymphocyte ratio (N/L) and locomotor play behavior in 21 Friesian dairy calves within their first month of life. Every week, an arena test after blood collection was performed. A significant positive correlation between serum cortisol levels and N/L (rrm = 0.381; 95% CI = 0.083, 0.617; p = 0.012) and a negative correlation between time spent running and N/L (rrm = −0.351; 95% CI = −0.575, −0.077; p = 0.012) were found. On the contrary, no significant correlation between time spent running and cortisol levels was detected. Cortisol levels and N/L were higher in the newborn and had a constant decrease until reaching a stable value after the 24th day of life. These findings suggest a better predictivity of N/L, compared to serum cortisol, on locomotor play behavior.

This chapter presents an overview of the main time series analysis methods for environment monitoring with earth observation, from classical methods to the deep learning (DL) methods. It summarizes main differences between bi-temporal change detection, annual time series and dense time series analyses, and also presents the three main types of annual time series methods for environment monitoring. The chapter focuses on dense time series methods using all available data, first presenting the main data preprocessing requirements, and provides an overview of the four main types of change detection methods based on dense time series analysis. These include: map classification, trajectory classification, statistical boundary and ensemble approaches. The chapter discusses three kinds of network architectures suited for the analysis of satellite image time series (SITS): recurrent neural networks, convolutional neural networks and hybrid models combining both. It proposes a prospective reflection upon possible convergence at crossroads between SITS analysis, video processing, computer vision and DL.

Sensitivity of lidar metrics to scan angle can affect the robustness of area-based approach (ABA) models, and modelling the interplay of scan geometry and terrain properties can be complex. The study hypothesises that neural networks can manage the interplay of lidar acquisition parameters, terrain properties, and vegetation characteristics to improve ABA models. The study area is in Massif des Bauges Natural Regional Park, eastern France, comprising 291 field plots in a mountainous environment with broadleaf, coniferous, and mixed forest types. Field plots were scanned with a high overlap from multiple flight lines and the corresponding point clouds were considered independently to expand the standard ABA dataset (291 observations) to create a dataset containing 1095 independent observations. Computation of lidar, terrain and scan metrics for each point cloud associated each observation in the expanded dataset with the scan information in addition to the lidar and terrain information. A multilayer perceptron (MLP) was used to model basal area and total volume to compare the predictions resulting from standard and expanded ABA datasets. With expanded datasets containing lidar, terrain and scan information, the R² for the median predictions per plot were higher (R² of 0.83 and 0.85 for BA and Vtot) than predictions with standard datasets(R² of 0.66(BA) and 0.71(Vtot)) containing only lidar metrics. It also outperformed an MLP model for a dataset with lidar and terrain information (R² of 0.77 (BA and Vtot)). The MLP performed better than RF regression, which could not sufficiently exploit additional terrain and scan information.

BackgroundAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia in adults, and it is associated with a high burden of mortality and morbidity worldwide. AF can be managed with rate-control or rhythm-control strategies. The latter is increasingly used to improve symptoms and prognosis in selected patients, especially after the development of catheter ablation. Although this technique is generally considered safe, it is not free from rare but life-threatening procedure-related adverse events. Among these, coronary artery spasm (CAS) is an uncommon but potentially fatal complication that requires immediate diagnosis and treatment.Case summaryWe report a case of severe multivessel CAS triggered by ganglionated plexi stimulation during pulmonary vein isolation with radiofrequency catheter ablation in a patient with persistent AF, promptly resolved after intracoronary nitrate administration.DiscussionAlthough rare, CAS is a serious complication of AF catheter ablation. Immediate invasive coronary angiography is key for both diagnosis confirmation and treatment of such dangerous condition. As the number of invasive procedures increases, it is important that both interventional and general cardiologists are aware of possible procedure-related adverse events.

The Transiting Exoplanet Survey Satellite (TESS) mission is providing the scientific community with millions of light curves of stars spread across the whole sky. Since 2018 the telescope has detected thousands of planet candidates that need to be meticulously scrutinized before being considered amenable targets for follow-up programs. We present the second catalog of the Plant Patrol citizen science project containing 999 uniformly-vetted exoplanet candidates within the TESS ExoFOP archive. The catalog was produced by fully exploiting the power of the Citizen Science Planet Patrol project. We vetted TESS Objects of Interest (TOIs) based on the results of Discovery And Vetting of Exoplanets DAVE pipeline. We also implemented the Automatic Disposition Generator, a custom procedure aimed at generating the final classification for each TOI that was vetted by at least three vetters. The majority of the candidates in our catalog, $752$ TOIs, passed the vetting process and were labelled as planet candidates. We ruled out $142$ candidates as false positives and flagged $105$ as potential false positives. Our final dispositions and comments for all the planet candidates are provided as a publicly available supplementary table., Comment: 17 pages, 11 figures, 5 tables. Accepted for publication on MNRAS

Background Atrial fibrillation is the most common sustained cardiac arrhythmia in adults and it is associated with a high burden of mortality and morbidity worldwide. Atrial fibrillation could be managed with rate-control or rhythm-control strategies. The latter is increasingly used to improve symptoms and prognosis in selected patients, especially after the development of catheter ablation. Although this technique is generally considered safe, it is not free from rare but life-threatening procedure-related adverse events. Among these, coronary artery spasm is an uncommon but potentially fatal complication that requires immediate diagnosis and treatment. Case summary We report a case of severe multivessel coronary artery spasm triggered by ganglionated plexi stimulation during pulmonary vein isolation with radiofrequency catheter ablation in a patient with persistent atrial fibrillation, promptly resolved after intracoronary nitrate administration. Discussion Although rare, coronary artery spasm is a serious complication of atrial fibrillation catheter ablation. Immediate invasive coronary angiography is key for both diagnosis confirmation and treatment of such dangerous condition. As the number of invasive procedures increases, it is important that both interventional and general cardiologists are aware of possible procedure-related adverse events.

The CO2 desorption process from a CO2-saturated nonaqueous sorbent, 2-(2-aminoethoxy)ethanol (DGA) in diethylene glycol monomethyl ether (DEGMME), was investigated in the absence and presence of four different metal oxides, namely, V2O5, TiO2, WO3, and ZnO, aiming at identifying acid catalysts with the potential to reduce the energy demand for sorbent regeneration. The desorption performances of the DGA-DEGMME solutions with and without catalysts were evaluated in terms of CO2 desorption rate, overall CO2 desorbed, and thermal energy consumption. The desorption mechanism was understood by the 13C NMR speciation study of the solutions during the regeneration experiments. As a result, metal oxide catalysts, depending on the number and types of acidic sites on their surface, can accelerate the carbamate breakdown and the subsequent CO2 release. In particular, WO3 and TiO2 can be considered good candidates for implementation in CO2 capture processes with nonaqueous sorbents, as they greatly improved the desorption performance, and their structures remain unchanged before and after use. The combination of nonaqueous sorbents with catalysts, here reported for the first time, provides an effective strategy that could inspire the design of advanced sorbents for energy-efficient CO2 capture.

In Sub-Saharan Africa, smallholder farms play a key role in agriculture, occupying most of the agricultural land. Design policies for increasing smallholder productivity remains a safe way to establish sustainable food systems and boost local economies. However, efforts are still needed in order to achieve accurate and timely monitoring in smallholder farming systems. With the advent of modern Earth Observation programmes such as the Sentinel satellites, which provide quasi-synchronous and high-resolution multi-source information over any area of the continental surfaces, new opportunities are opened up to accurately map crop yields in smallholder farming systems. This study intends to estimate and forecast millet yields in central Senegal, making the use of multi-source (synthetic-aperture radar (SAR) and optical) image time series and state-of-the-art machine learning models. A Random Forest (RF) model explained up to 50% of the millet yield variability, while deep learning models such as Convolutional Neural Network (CNN) showed promise results but performed lower. We also found that the concatenation of SAR polarizations and vegetation indices improved our crop yield modelling, but such improvement was tightly related to the modelling approach, namely RF and CNN. Using RF to forecast millet yields, we achieved stable and satisfactory accuracy 2 weeks before the harvest period.

Background Dobutamine Stress Echo (DSE) is a test widely used in the diagnosis of ischemic heart disease. The purpose of the following work is to describe a clinical case with uncommon behaviour. Case Description: 63–year–old female with dyspnoea on mild exertion, and history of NSTEMI–ACS 5 years prior with Coronary Angiography (CA) finding of 3–vessel coronary artery disease, treated with PCI + stent (DES) of right coronary artery (CDX), untreated disease sub–occlusion of the first marginal obtuse (OM1), and chronic occlusion of the anterior interventricular artery (IVA). We decide for DSE. During 20 mcg/kg/min infusion, the patient reported dyspnoea and paradoxical bradycardia (BP) was documented on the ECG, in the absence of ST changes, with the appearance of akinesia of the basal and mid posterolateral segments and worsening of the inferior hypokinesia, present in basal conditions on Echocardiograms (EC). The BP and the alterations of the ventricular motion (VCA) did not respond to the administration of Atropine (1+1 mg) while the administration of 240 mg of Aminophylline (AM) restored the HR and the VCA to baseline values. The CA demonstrated patency of the CDX with the presence of collateral circulation for IVA and occluded OM1. Discussion This case is characterized by the presence of a double paradox: the BP and the Atropine–Resistance (AR). BP during DEB, as demonstrated in previous studies, occurred in 8% of cases, with signs of significant coronary artery disease in 57% of cases. The BP is an expression of ischemia only in just over half of the patients, in the rest of the cases it appeared referable to the Bezold–Jarish reflex, a vagal reflex determined by the stimulation of the intracardiac mechanoreceptors. In our case, the presence of AR seems to exclude the possibility that bradycardia is due to this reflex. The appearance of paradoxical bradycardia during DSE is a rare complication and can lead to premature termination of the test with inconclusive results. In our case, the BP and the AR confirm the positivity of the test also in consideration of the response to the AM antagonist of Adenosine, which accumulates during ischemia. Conclusions This uncommon response to DSE, where AR and AM response in addition to BP could identify patients with severe coronary artery disease in whom the ischemic response is driven by adenosine accumulation, rather than a vagal reflex responding to atropine administration.

Background On December 2017 the Italian Parliament approved law n. 219/2017 “Provisions for informed consent and advance directives” regarding challenging legal and bioethical issues related to healthcare decisions and end-of-life choices. The law does not contain an explicit reference to Ethics Committees (ECs), but they could still play a role in implementing the law. Methods A questionnaire-based survey was performed among the ECs of the Italian Institute for Research and Care belonging to the Network of neuroscience and neurorehabilitation, with the aim of (1) knowing whether the ECs participated and, if so, how in the process of implementation of law n. 219/2017 in the referring institutes; (2) investigating the point of view of the ECs regarding their possible involvement in the process; (3) exploring the contribution ECs can provide to give effective implementation to the law principles and provisions. Results Seventeen ECs out of thirty took part in the survey; the characteristics of the responding and non-responding committees are similar, so the responding ECs can be regarded as representative of all ECs in the Network. Nine ECs did not discuss the law in anyway: the main reason for this is that the referring institutions (6) and the health care professionals (3) did not ask for an EC intervention. Nevertheless, the large majority of the ECs believe that their involvement in the implementation of the law as a whole is appropriate (8) or absolutely appropriate (6), while 3 of them are neutral. No EC believes that the involvement is inappropriate. The aspect of the law on which the 14 ECs converge in considering the EC involvement appropriate/absolutely appropriate is the one related to the health facilities obligation to guarantee the full and proper implementation of the principles of the law. Conclusions Our survey confirms that ECs believe they can play a role in the implementation of law n. 219/2017, although this does not entirely correspond to what the committees have actually done in reality. This role could be better exercised by ECs specifically established for clinical practice, which would have a composition, functioning and a mandate better suited to the purpose. This supports the call for a national regulation of ECs for clinical practice.

Essential oils (EOs) and oleoresins are complex mixtures mainly made up of terpenes, synthesized by a wide variety of plants. Individual terpenes may show broad-spectrum activity against different plant pathogens, and their combination into EO and oleoresin mixtures enhances plant chemical defense. The interest in EOs has significantly increased due to the trend of using natural products as herbicides, insecticidal and antimicrobial agents. In addition, the use of plant mixtures is an emerging approach to face the problem of antimicrobial resistance in agriculture. This chapter reports guidelines about plant sample collection for the production of EOs and provides protocols to test their activity as antimicrobial agents against bacteria and fungi. It also describes a solvent-free method for the inclusion of EOs into β-cyclodextrins. This type of formulate is prepared to turn liquid EOs into easily manageable water-soluble powders, and to control the release of volatile compounds, aiming to increase EOs' applications in agriculture.

International audience; This letter proposes a deep learning model to deal with the spatial transfer challenge for the mapping of irrigated areas through the analysis of Sentinel-1 data. First, a convolutional neural network (CNN) model called "Teacher Model" is trained on a source geographical area characterized by a huge volume of samples. Then, this model is transferred from the source area to a target area characterized by a limited number of samples. The transfer learning framework is based on a distill and refine strategy in which the teacher model is firstly distilled into a student model and, successively, refined by data samples coming from the target geographical area. The proposed strategy is compared to different approaches including a random forest (RF) classifier trained on the target dataset, a CNN trained on the source dataset and directly applied on the target area as well as several CNN classifiers trained on the target dataset. The evaluation of the performed transfer strategy shows that the "distill and refine" framework obtains the best performance compared to other competing approaches. The obtained findings represent a first step towards the understanding of the spatial transferability of deep learning models in the Earth Observation domain.

Background Tako Tsubo syndrome (TTS) is characterized by transient alterations of ventricular kinetics (ATC) in the absence of obstructive epicardial coronary artery disease. Materials 39 cases of TTS that came to our observation from 2005 to 2019 are described, the diagnosis was made on the basis of evidence of ATC, ECG alterations, increase necrosis markers in the absence of obstructive coronary disease, excluding myocarditis. Results 39 patients (PZ) (35 females and 4 males) diagnosed with TTS had an average age of 61 ± 13.21 years and symptoms at onset were mainly angina in 28 PZs (72%), dyspnea was present in 8 (20%) and syncope in 3 (8%). ECG changes were characterized by ST depression and/or negative T waves in 30 patients (77%), in 9 (23%) the ST segment was elevated. ATV involved apical segments (SAP) in 27 PZ (69%), 4 (10%) the basal segments (SBA), 2 (5%) the middle segments (SME) and 6 (15%) had focal points abnormalities (FOC). The average Ejection Fraction (FE) on admission was 36.85%, in PZ with ATV of SAP 33.96%, when involved SBA 41%, SME 43.5% and FOC 44.83%. Haemodynamic conditions were stable in 33 pts (84%), 3 pts (8%) presented cardiogenic shock, 3 (8%) pulmonary edema. Arrhythmias were present in 1/3 of the cases. Atrial fibrillation in 38%, extrasystolic arrhythmia in 30%, one patient with sustained ventricular tachycardia, and three patients with total BAV (23%) of which one in shock. In 10% of cases (4 PZ) there was a subvalvular aortic gradient at discharge disappeared. In 8% (3 PZ) was a recurrent TTS. 92% of the PZ reported a psychophysical stress in the 24 hours preceding the event, and a psychiatric pathology was present in 90%. However, only in 60% of cases the psychiatric diagnosis was known on admission, in the remaining 40% the diagnosis was made subsequently, and among the PZ being treated only in ¼ of the cases was it judged adequate. Conclusions In our series, SAP involvement was associated with lower EF values and greater hemodynamic compromise. Involvement of SME, SBA or FOC was associated with higher EF values and less hemodynamic compromise. A psychiatric pathology was present in over 90% of the PZ even if in 40% of the cases it was not ascertained at the time of admission, and in 75% of the PZ in which the diagnosis was known, the treatment was not adequate.

The selective recognition of caffeine in water among structurally related xanthines and purine or pyrimidine bases was achieved by a simple tweezer-shaped receptor featuring sulfonate hydrosolubilizing groups. The remarkable affinity for caffeine, among the highest reported thus far in the literature and larger than that shown by adenosine receptors of all subtypes, stems from a synergistic combination of hydrogen bonding, CH-pi, and pi-stacking interactions.

Additional file 1. Questionnaire (Italian version and English transaltion).

Exceptional Preferences Mining (EPM) combines the research fields of Preference Learning and Exceptional Model Mining. It is a local pattern mining task, where we try to find coherent subgroups of the dataset featuring unusual preferences between a fixed set of labels. We introduce a new quality measure for Exceptional Preferences Mining, inspired by concepts from Clustering. On top of that, we draw conclusions on two design choices that must necessarily be made whenever one defines a quality measure for any version of Exceptional Model Mining: on the one hand, exceptional behavior is easily (spuriously) found in tiny subgroups, so what is the best way to compensate for that; on the other hand, when gauging exceptionality of a subgroup’s behavior, what does one use as reference for the normal behavior? We find that the choice of correction factor not only influences the subgroup size but it also effects the presumed exceptionality of found subgroups. The entropy function allows for detecting exceptional subgroups of a meaningful size, both when a candidate subgroup is evaluated against its complement and against the entire dataset.

A mitochondrial stroke-like event is an evolving subacute neurological syndrome linked to seizure activity and focal metabolic brain derangement in a genetically determined mitochondrial disorder. The acronym "MELAS" (mitochondrial encephalopathy associated with lactic acidosis and stroke-like lesions) identifies subjects with molecular, biochemical and/or histological evidence of mitochondrial disorder who experience stroke-like lesions. MELAS is a rare inherited mitochondrial disease linked to severe multiorgan involvement and stress-induced episodes of metabolic decompensation and lactic acidosis. Unfortunately, there are no etiopathogenetic therapies for stroke-like episodes to date, and the treatment is mainly based on anti-epileptic drugs and supportive therapies. This perspective opinion article discusses the current care standards for MELAS patients and revises current and innovative emerging therapies for mitochondrial stroke-like episodes.

The Transiting Exoplanet Survey Satellite (TESS) has detected thousands of exoplanet candidates since 2018, most of which have yet to be confirmed. A key step in the confirmation process of these candidates is ruling out false positives through vetting. Vetting also eases the burden on follow-up observations, provides input for demographics studies, and facilitates training machine learning algorithms. Here we present the TESS Triple-9 (TT9) catalog -- a uniformly-vetted catalog containing dispositions for 999 exoplanet candidates listed on ExoFOP-TESS, known as TESS Objects of Interest (TOIs). The TT9 was produced using the Discovery And Vetting of Exoplanets pipeline, DAVE, and utilizing the power of citizen science as part of the Planet Patrol project. More than 70% of the TOIs listed in the TT9 pass our diagnostic tests, and are thus marked as true planetary candidates. We flagged 144 candidates as false positives, and identified 146 as potential false positives. At the time of writing, the TT9 catalog contains ~20% of the entire ExoFOP-TESS TOIs list, demonstrates the synergy between automated tools and citizen science, and represents the first stage of our efforts to vet all TOIs. The DAVE generated results are publicly available on ExoFOP-TESS., Comment: 15 pages, 11 figures. Accepted on MNRAS

The presence and infestation level of Bactrocera oleae was monitored in an organic olive orchard divided into differently treated parcels with kaolin (K), spinosad (S) and with kaolin and spinosad (K + S) in alternate rows. The treatments did not seem to affect olive fruit fly population dynamics, while statistically significant protective effects were recorded against total and harmful infestation, but not against the active one. Eventually, neither kaolin nor spinosad were shown to have a particular detrimental effect against naturally occurring B. oleae parasitoids.

We report the Transiting Exoplanet Survey Satellite (TESS) discovery of a three-planet system around the bright Sun-like star HD~22946(V=8.3 mag),also known as TIC~100990000, located 63 parsecs away.The system was observed by TESS in Sectors 3, 4, 30 and 31 and two planet candidates, labelled TESS Objects of Interest (TOIs) 411.01 (planet $c$) and 411.02 (planet $b$), were identified on orbits of 9.57 and 4.04 days, respectively. In this work, we validate the two planets and recover an additional single transit-like signal in the light curve, which suggests the presence of a third transiting planet with a longer period of about 46 days.We assess the veracity of the TESS transit signals and use follow-up imaging and time series photometry to rule out false positive scenarios, including unresolved binary systems, nearby eclipsing binaries or background/foreground stars contaminating the light curves. Parallax measurements from Gaia EDR3, together with broad-band photometry and spectroscopic follow-up by TFOP allowed us to constrain the stellar parameters of TOI-411, including its radius of$1.157\pm0.025R_\odot$. Adopting this value, we determined the radii for the three exoplanet candidates and found that planet $b$ is a super-Earth, with a radius of $1.72\pm0.10R_\oplus$, while planet $c$ and $d$ are sub-Neptunian planets, with radii of$2.74\pm0.14R_\oplus$ and $3.23\pm0.19R_\oplus$ respectively. By using dynamical simulations, we assessed the stability of the system and evaluated the possibility of the presence of other undetected, non-transiting planets by investigating its dynamical packing. We find that the system is dynamically stable and potentially unpacked, with enough space to host at least one more planet between $c$ and $d$.(Abridged), 21 pages, 12 figures. Accepted for publication on A&A

Oxygenic photosynthesis is the most important biochemical process in Earth biosphere and likely very common on other habitable terrestrial planets, given the general availability of its input chemical ingredients and of light as source of energy. It is therefore important to evaluate the effective possibility of oxygenic photosynthesis on planets around stars as a function of their spectral type and the planet-star separation. We aim at estimating the photon flux, the exergy and the exergetic efficiency of the radiation in the wavelength range useful for the oxygenic photosynthesis as a function of the host star effective temperature and planet-star separation. We compute analytically these quantities and compare our results with the estimates for the small sample of known Earth-like planets. We find that exergy is an increasing function of the star effective temperature, within the range 2600-7200 K. It depends both on the star-planet separation and the star effective temperature. Biospheres on exoplanets around cool stars might be generally light-limited. So far, we have not observed terrestrial planets comparable to Earth in terms of useful photon flux, exergy and exergetic efficiency., Comment: Accepted for publication on MNRAS

International audience; Nowadays, huge volume of satellite images, via the different Earth Observation missions, are constantly acquired and they constitute a valuable source of information for the analysis of spatio-temporal phenomena. However, it can be challenging to obtain reference data associated to such images to deal with land use or land cover changes as often the nature of the phenomena under study is not known a priori. With the aim to deal with satellite image analysis, considering a real-world scenario where reference data cannot be available, in this paper, we present a novel end-to-end unsupervised approach for change detection and clustering for satellite image time series (SITS). In the proposed framework, we firstly create bi-temporal change masks for every couple of consecutive images using neural network autoencoders. Then, we associate the extracted changes to different spatial objects. The objects sharing the same geographical location are combined in spatio-temporal evolution graphs that are finally clustered accordingly to the type of change process with gated recurrent unit (GRU) autoencoder-based model. The proposed approach was assessed on two real-world SITS data supplying promising results.

The three different solid forms of dexktoprofen trometamol (DK-T_A, DK-T_B, and DK-T_2H2O) have been studied by using X-ray diffraction and calorimetric methods. In the molecular and crystal structure of DK-T_A, the thermodynamically stable form used in the tablets production process, all the potential H-bond donors and acceptors of each trometamol cation are involved in strong H-bonds which hold together the cations as well as the dexketoprofen/trometamol ionic pairs. The dihydrate species is quickly formed starting from DK-T_A apparently without the formation of an amorphous phase, and the process is fully reversible. In addition, the two solids have comparable crystal density (cell parameters and space group of the resulting hydrate were determined by X-ray powder diffraction). We speculate that the anhydrous and hydrate crystal architectures did not suffer upon the hydration/dehydration process and that the hydrate form belongs to the class of the channel hydrates and most probably is a planar hydrate. Finally, the unit cell parameters and space group were determined also for the metastable DK-T_B solid form.

Heterostructures of single- and few-layer black phosphorus (2D bP) functionalized with gold nanoparticles (Au NPs) have been recently reported in the literature, exploiting their intriguing properties and biocompatibility for catalytic, therapeutical and diagnostic applications. However, a deeper insight on the structural and electronic properties at the interface of the 2D bP/Au NP heterostructure is still lacking. In this work, 2D bP is functionalized with Au nanoparticles (NPs) through in situ deposition–precipitation heterogeneous reaction. The smallest realized Au NPs have a diameter around 10 nm as revealed by atomic-force and scanning electron microscopy, and are partially positively charged as revealed by X-ray Photoelectron Spectroscopy (XPS). XPS, UV-vis and Raman spectroscopy, supported by density functional theory (DFT) calculations, confirmed that while the structural and electronic properties of 2D bP are overall preserved, a soft-pairing between P atoms at the surface of 2D bP and Au atoms at the surface of Au NPs occurs, leading to a partial charge transfer at the 2D bP/Au interface, with a positive charge being localized on the Au atoms directly bonded to 2D bP. DFT calculations also predicted a band gap lowering, by 0.8 eV, for phosphorene functionalized with a tetranuclear Au cluster. Larger effects are expected as the Au cluster nuclearity (and coverage) increases., Computational analysis and electronic, structural and morphological properties of a heterostructure of 2D bP with Au nanoparticles formed in situ.

The need for reliable and exhaustive data on land use is a major issue in planning policies and monitoring of land take. In this work, we evaluate urban building classification resulting from deep learning based approaches using as input SPOT 6/7 satellite images (at a spatial resolution of 1.5m) and national databases. In addition to assessing the classifier behaviour on urban land cover, the objective here is to compare the deep learning results at both pixel-based and object-based scale to qualify the overall results. Standard evaluation metrics (such as F-score) have shown better scores at the object-based assessment level (median F-score = 0.78) than the pixel ones (median F-score = 0.68). Identifying the impact of object characteristics using the object-based level of analysis has also revealed that beyond a surface area of 100 m2, objects are much better detected (median F-score > 0.91). It is the same with a high urban density (median F-score > 0.97). The accuracy of the intersections evaluated from the Intersection over Union also follows these trends as the entities area increases.