A precise CNOT gate in the presence of large fabrication induced variations of the exchange interaction strength

We demonstrate how using two-qubit composite rotations a high fidelity controlled-NOT (CNOT) gate can be constructed, even when the strength of the interaction between qubits is not accurately known. We focus on the exchange interaction oscillation in silicon based solid-state architectures with a Heisenberg Hamiltonian. This method easily applies to a general two-qubit Hamiltonian. We show how the robust CNOT gate can achieve a very high fidelity when a single application of the composite rotations is combined with a modest level of Hamiltonian characterisation. Operating the robust CNOT gate in a suitably characterised system means concatenation of the composite pulse is unnecessary, hence reducing operation time, and ensuring the gate operates below the threshold required for fault-tolerant quantum computation.Comment: 9 pages, 8 figure

Optically induced spin to charge transduction in donor spin read-out

The proposed read-out configuration D+D- for the Kane Si:P architecture[Nature 393, 133 (1998)] depends on spin-dependent electron tunneling between donors, induced adiabatically by surface gates. However, previous work has shown that since the doubly occupied donor state is so shallow the dwell-time of the read-out state is less than the required time for measurement using a single electron transistor (SET). We propose and analyse single-spin read-out using optically induced spin to charge transduction, and show that the top gate biases, required for qubit selection, are significantly less than those demanded by the Kane scheme, thereby increasing the D+D- lifetime. Implications for singlet-triplet discrimination for electron spin qubits are also discussed.Comment: 8 pages, 10 figures; added reference, corrected typ

Comparative analysis of methods for estimating genetic parameters of fruit-quality traits in apple breeding program

Apples, originating from Central Asia, are widely cultivated worldwide, with China producing 47.6 million tonnes annually. Despite their global importance, breeding programs often focus on a limited number of high-quality cultivars, potentially threatening genetic diversity. To mitigate this risk, advanced statistical methods could be employed to improve selection strategies. For example, the multi-trait BLUP method, which accounts for genetic correlations among traits, can reduce selection bias but increases computational complexity due to the model’s intricacy and slow convergence of the REML process. Bayesian methods, like Markov Chain Monte Carlo (MCMC), offer a solution to these challenges. This study compares single-trait and multi-trait approaches using REML/BLUP and MCMC/BLUP to estimate variance components and predict genetic values. Over two seasons, phenotypic data from 304 seedlings and 16 parents were analyzed using an animal model to predict their genetic values related to fruit quality traits. Significant progress was made in estimating genetic parameters and selecting parents for traits such as fruit weight, flesh firmness, and soluble solids content in the University of Udine’s apple breeding program. The multi-trait BLUP method improved the accuracy of predicted breeding values, particularly for fruit weight, polar diameter, flesh firmness, and soluble solids content. The multivariate repeated measures model, despite low correlations between some trait pairs, was recommended for integrating multi-season results and accounting for trait correlations. The Bayesian MCMC approach proved superior in genetic evaluations, offering higher heritabilities and genetic gains compared to Fisherian methods (REML). It effectively handles small sample sizes, captures more genetic variance, and enhances breeding value predictions, recommending traits like fruit size, firmness, and sweetness for selecting superior parents

Effect of biostimulants on apple quality at harvest and after storage

Nutritional unbalances, such as calcium deficiency at the fruit level, are generally the causative agent of post-harvest disorders in apples. Foliar application of Ca as calcium chloride is the current solution to increase Ca concentration in apples, even though the effectiveness of this approach is often not satisfactory. In this research, we tested the efficacy of a combined application of Ca with selected biostimulants to improve apple quality and to reduce the incidence of storage disorders. The experiment was conducted in two \u201cJonathan\u201d apple orchards that differed in management systems and characteristics. Tree canopies were sprayed with calcium chloride alone and in combination with a commercial product containing zinc and silicon or a seaweed extract. The seaweed extract increased apple quality by boosting the reddish coloration (+32% of color index) and by enhancing final anthocyanin concentration of fruit skin. Both biostimulants significantly reduced (by 20%) the incidence of the physiological disorder, known as \u201cJonathan spot\u201d, after 160 days of storage. Increased concentration of nutrients (Ca, Zn, and Mn) in the skin of apples after biostimulant applications, together with changes of the phenolic profile during the storage, are discussed as the possible causes of the reduced fruit susceptibility to post-harvest disorders

Floristic changes of vascular flora in the city of Rome through grid-cell census over 23 years

Cities are considered important areas for biodiversity and host a high plant species richness. However, many factors, such as urbanisation or changes in land use, can affect the presence of spontaneous flora and, consequently, represent a threat for biodiversity. How species respond to these factors of change in cities over time is a relevant and current issue and spatiotemporal analyses represent an essential step forward to better understand these dynamic systems and to fill gaps of knowledge. In this paper we present a comparison between a floristic survey carried out in 1995 on a grid-cell for the city of Rome and a new survey, performed between 2015 and 2018, in order to verify if the species composition significantly changed over time and to which drivers this change was related to. For 76 grid-cells of the raster, each of which of 1.6 km(2), we recorded all spontaneous vascular species. We analysed the differences between the two surveys by means of statistical tests on species richness, by species turnover, by generalised linear models (GLMs) and by Ellenberg indicator values. The patterns of species richness are similar between the two surveys, although an increase in the number of species per grid-cell, on average, was observed. This increase regarded both native and alien richness, with significant differences only for aliens. Many species significantly reduced or increased their frequencies, comparing the two surveys. A set of environmental variables, among which the presence of protected areas, are relevant for explaining the pattern of species' frequencies and its change over time. Our results suggest that the flora of the city, notwithstanding the steady human pressure and the increase in alien species, maintained a high level of heterogeneity

Au Nanoparticles Decorated Graphene-Based Hybrid Nanocomposite for As(III) Electroanalytical Detection

Electrochemical sensors integrating hybrid nanostructured platforms are a promising alternative to conventional detection techniques for addressing highly relevant challenges of heavy metal determination in the environment. Hybrid nanocomposites based on graphene derivatives and inorganic nanoparticles (NPs) are ideal candidates as active materials for detecting heavy metals, as they merge the relevant physico-chemical properties of both the components, finally leading to a rapid and sensitive current response. In this work, a hybrid nanocomposite formed of reduced graphene oxide (RGO) sheets, surface functionalized by π-π interactions with 1-pyrene carboxylic acid (PCA), and decorated in situ by Au NPs, was synthesized by using a colloidal route. The hybrid nanocomposite was characterized by cyclic voltammetry and electrochemical impedance spectroscopy with respect to the corresponding single components, both bare and deposited as a layer-by-layer junction onto the electrode. The results demonstrated the high electrochemical activity of the hybrid nanocomposite with respect to the single components, highlighting the crucial role of the nanostructured surface morphology of the electrode and the PCA coupling agent at the NPs-RGO interphase in enhancing the nanocomposite electroactivity. Finally, the Au NP-decorated PCA-RGO sheets were tested by anodic stripping voltammetry of As(III) ion—a particularly relevant analyte among heavy metal ions—in order to assess the sensing ability of the nanocomposite material with respect to its single components. The nanocomposite has been found to present a sensitivity higher than that characterizing the bare components, with LODs complying with the directives established by the U.S. EPA and in line with those reported for state-of-the-art electrochemical sensors based on other Au-graphene nanocomposites

Investigating the effect of selective logging on tree biodiversity and structure of the tropical forests of Papua New Guinea

Abstract: Unsustainable exploitation of tropical forest resources is raising worldwide concern. In Papua New Guinea (PNG) timber harvesting has been identified as a major contributor to deforestation and forest degradation but its impact on biodiversity is still poorly understood. In this study we investigated the effect of selective logging on tree taxonomic composition, structure and diversity of PNG forests. We used data from 101 one-hectare permanent sample plots (PSPs) belonging to two vegetation types: low altitude forests on plains and fans (type P) and low altitude forests on uplands (type H). We used multivariate techniques to test for significant differences in species composition between plots of different vegetation types and disturbance regimes, identifying the tree taxa to which these differences could be ascribed. ANOVA was used to test for differences between logged-over and unlogged forest PSPs with respect to biodiversity (richness, Shannon's diversity, Pielou's evenness) and stand structure (stem density, basal area - BA). Temporal trends of forest features were analyzed using linear regression. Significant differences in taxonomic composition were found between logged-over and unlogged plots of the H type (p = 0.04). No differences were found in richness, diversity and evenness between logged-over and unlogged forest plots, while stem density was higher in the latter (421 ± 153 stems ha-1). Greater BA was found in unlogged forests (30.28 ± 4.45 m2 ha-1) of the H type when compared to the logged-over stands (15.52 ± 4.04 m2 ha-1). We detected positive trends in richness (0.55 ± 0.19 taxa ha-1 yr-1) and diversity after logging. Furthermore, H type forest exhibited positive trends in stem density (9 ± 1 stems ha-1 yr-1) and BA (0.42 ± 0.06 m2 ha-1 yr-1) with elapsed time since harvesting. Our analysis highlights some significant effects of logging activities on biodiversity and structure of PNG forests. Additionally, forests exhibited a significant recovery with respect to richness, diversity and stand structure. These preliminary results will be compared with data collected by the forthcoming National Forest Inventory in order to assess and monitor the effects of human activities and ecological factors on PNG forest biodiversity and develop appropriate conservation measures and sustainable management strategies

Genetic analysis for physical nut traits in almond

Peer ReviewedPublishe

Enhanced performances of RGO-AuNPs hybrids towards electroanalytical applications

In recent years, lot of attention has been devoted to understanding the properties of hybrid nanocomposites, \u201cbrave new materials\u201d made of two or more organic and inorganic components. These systems show enhanced or novel physico-chemical properties with respect to the single components, resulting not only from the sum of the precursors\u2019 ones, but also from interactions occurring at their interface, the so-called \u201cheterojunction\u201d. However, a remaining challenge is to understand in depth the phenomena here originating. In the present work, to start fulfilling this gap, a deep electrochemical study of hybrids made of Reduced Graphene Oxide (RGO) and Au nanoparticles (NPs) is performed, analysing carefully the role played by each single component of the material on the electrochemical properties. In more details, RGO platforms are surface functionalized with 1-aminopyrene or 1-pyrene carboxylic acid that act as heteronucleation and growing sites of the amine- or thiol-coated Au NPs of different dimensions (from 3 to 20 nm). At first, Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) measurements are carried out in order to characterize the different hybrids. Then, the materials are applied as electroanalytical sensors for both organic and inorganic molecules (dopamine and As, respectively) with very promising results, comparable or even better than analogous systems reported in literature. Moreover, preliminary tests on H2O2 detection open the venue to the application of these materials in biosensor applications. The properties of the hybrid nanocomposite, enhanced with respect to those of the single components, are ascribed to charge transfer occurring at the heterojunction from the Au NPs to the RGO, assisted and channelled by the pyrene linker