Biological activity of Citrus spp. metabolites on Ceratitis capitata (Wiedemann).

The Mediterranean fruit fly (medfly), Ceratitis capitata (Wiedemann) (Diptera: Tephritidae), is one of the most injurious pest at global level. During the last years, several electrophysiological and behavioural studies have been carried out in order to investigate plant volatile compound-insect interactions with the aim to use this knowledge in sustainable control techniques. It has been observed that lemons are not attacked by medfly, probably because of the peel oil, that is toxic to other fruit flies. In the present paper electrophysiological recordings were conducted to evaluate the insect sensitivity to peel extract and peel oil of two Sicilian cultivars (Interdonato and Lunario) of Citrus x limon (L.) Burm.f. on C. capitata females. Behavioural bioassays were also performed to show their possible biological activity (repellent, antioviposition, insecticidal). C. limon peel extracts in different solvents (petroleum ether, dichloromethane and methanol) were investigated at various concentrations using a single cell recording technique (stimulation of tarsal taste chemosensilla). Different tarsal taste cell responses to the two cultivars were recorded. The higher sensitivity was evoked by C. limon Interdonato, particularly to the methanol extract, which elicited significant increases in the spike frequency at increasing concentrations. The peel oil of the same cultivars as well as that ones of other two C. limon varieties (Monachello and Femminello) have been tested by EAG techniques. The EAG data showed a high sensitivity (about -8.0/8.5mV) of the medfly antennae to the oils of Citrus spp. and a clear dose-response relationship. Responses of adult females (virgin and mated) to Citrus spp. peel extract were quantified in a double-choice test using yellow spheres (diameter 7.0cm) housed in field cages. Preliminary tests conducted on three extracts of C. limon Interdonato and Lunario have provided interesting results. It was recorded a general decrease of the oviposition on treated spheres compared to control and in the case of the cultivar Lunario, a mortality of insects

First report of Leptopilina japonica in Europe

5openInternationalItalian coauthor/editorDrosophila suzukii (Matsumura; Diptera: Drosophilidae) is a key pest of sweet cherry and small fruits worldwide. Biological control remains unutilized in the framework of D. suzukii management. Nonetheless, natural enemies may play an important role in regulating this pest. We report for the first time the presence of Leptopilina japonica Novković and Kimura (Hymenoptera: Figitidae) in Europe. Two specimens emerged from ripened fruits and one was collected after direct observation on a cherry tree in June 2019. They showed the distinctive morphological traits already described and shared more than 99% sequence similarity with specimens of L. japonica collected in Asia. This first finding was confirmed by a wider survey carried out in 2020; L. japonica emerged from cherry fruit samples collected in five other sites across the Trentino region, suggesting that L. japonica has already colonized a wide area. Detection of this Asian species is relevant to the future direction in managing D. suzukii, both in Europe and North America. In fact, L. japonica showed similarity with Ganaspis brasiliensis (Ihering) (Hymenoptera: Figitidae), the most promising candidate for the classical biological control, in terms of developmental time, egg maturation, host age preference and lifetime fecundityopenPuppato, S.; Grassi, A.; Pedrazzoli, F.; De Cristofaro, A.; Ioriatti, C.Puppato, S.; Grassi, A.; Pedrazzoli, F.; De Cristofaro, A.; Ioriatti, C

Privacy-Preserving Genetic Relatedness Test

An increasing number of individuals are turning to Direct-To-Consumer (DTC) genetic testing to learn about their predisposition to diseases, traits, and/or ancestry. DTC companies like 23andme and Ancestry.com have started to offer popular and affordable ancestry and genealogy tests, with services allowing users to find unknown relatives and long-distant cousins. Naturally, access and possible dissemination of genetic data prompts serious privacy concerns, thus motivating the need to design efficient primitives supporting private genetic tests. In this paper, we present an effective protocol for privacy-preserving genetic relatedness test (PPGRT), enabling a cloud server to run relatedness tests on input an encrypted genetic database and a test facility's encrypted genetic sample. We reduce the test to a data matching problem and perform it, privately, using searchable encryption. Finally, a performance evaluation of hamming distance based PP-GRT attests to the practicality of our proposals.Comment: A preliminary version of this paper appears in the Proceedings of the 3rd International Workshop on Genome Privacy and Security (GenoPri'16

On Collaborative Predictive Blacklisting

Collaborative predictive blacklisting (CPB) allows to forecast future attack sources based on logs and alerts contributed by multiple organizations. Unfortunately, however, research on CPB has only focused on increasing the number of predicted attacks but has not considered the impact on false positives and false negatives. Moreover, sharing alerts is often hindered by confidentiality, trust, and liability issues, which motivates the need for privacy-preserving approaches to the problem. In this paper, we present a measurement study of state-of-the-art CPB techniques, aiming to shed light on the actual impact of collaboration. To this end, we reproduce and measure two systems: a non privacy-friendly one that uses a trusted coordinating party with access to all alerts (Soldo et al., 2010) and a peer-to-peer one using privacy-preserving data sharing (Freudiger et al., 2015). We show that, while collaboration boosts the number of predicted attacks, it also yields high false positives, ultimately leading to poor accuracy. This motivates us to present a hybrid approach, using a semi-trusted central entity, aiming to increase utility from collaboration while, at the same time, limiting information disclosure and false positives. This leads to a better trade-off of true and false positive rates, while at the same time addressing privacy concerns.Comment: A preliminary version of this paper appears in ACM SIGCOMM's Computer Communication Review (Volume 48 Issue 5, October 2018). This is the full versio

Integrative IRT for documentation and interpretation of archaeological structures

The documentation of built heritage involves tangible and intangible features. Several morphological and metric aspects of architectural structures are acquired throughout a massive data capture system, such as the Terrestrial Laser Scanner (TLS) and the Structure from Motion (SfM) technique. They produce models that give information about the skin of architectural organism. Infrared Thermography (IRT) is one of the techniques used to investigate what is beyond the external layer. This technology is particularly significant in the diagnostics and conservation of the built heritage. In archaeology, the integration of data acquired through different sensors improves the analysis and the interpretation of findings that are incomplete or transformed. Starting from a topographic and photogrammetric survey, the procedure here proposed aims to combine the bidimensional IRT data together with the 3D point cloud. This system helps to overcome the Field of View (FoV) of each IRT image and provides a three-dimensional reading of the thermal behaviour of the object. This approach is based on the geometric constraints of the pair of RGB-IR images coming from two different sensors mounted inside a bi-camera commercial device. Knowing the approximate distance between the two sensors, and making the necessary simplifications allowed by the low resolution of the thermal sensor, we projected the colour of the IR images to the RGB point cloud. The procedure was applied is the so-called Nymphaeum of Egeria, an archaeological structure in the Caffarella Park (Rome, Italy), which is currently part of the Appia Antica Regional Park

Last-male sperm precedence in Rhynchophorus ferrugineus (Olivier): observations in laboratory mating experiments with irradiated males

The Red PalmWeevil (RPW)Rhynchophorus ferrugineus(Olivier 1790) is an invasive pest from southeastern Asia and Melanesia that in the last 30 years has spread widely in the Middle East and Mediterranean Basin. Its stem-boring larvae cause great damage to several palm species of the Arecaceae family, many of which are economically important for agricultural and ornamental purposes. Therefore, great attention has recently been focused in studying this species to identify sustainable and effective eradication strategies, such as sterile insect technique (SIT). The rapid spread of RPW is associated with its high reproductive success. To evaluate the suitability of a SIT strategy, particular physiological and behavioral aspects of RPW reproduction, such as the presence of polyandry and post-copulatory sperm selection mechanisms, were investigated. To determine paternity of progeny from multiply mated females, double-crossing experiments were carried out confining individual females with either a wild-type male or a γ-irradiated male (Co-60). Fecundity and fertility of females were scored to evaluate post-copulatory sperm selection. Results showed that progeny were almost exclusively produced by the sperm of the second male, suggesting that a last-male sperm precedence is expressed at high levels in this species, and providing interesting insights for an area-wide RPW management strategy such as the SIT

Controlled Data Sharing for Collaborative Predictive Blacklisting

Although sharing data across organizations is often advocated as a promising way to enhance cybersecurity, collaborative initiatives are rarely put into practice owing to confidentiality, trust, and liability challenges. In this paper, we investigate whether collaborative threat mitigation can be realized via a controlled data sharing approach, whereby organizations make informed decisions as to whether or not, and how much, to share. Using appropriate cryptographic tools, entities can estimate the benefits of collaboration and agree on what to share in a privacy-preserving way, without having to disclose their datasets. We focus on collaborative predictive blacklisting, i.e., forecasting attack sources based on one's logs and those contributed by other organizations. We study the impact of different sharing strategies by experimenting on a real-world dataset of two billion suspicious IP addresses collected from Dshield over two months. We find that controlled data sharing yields up to 105% accuracy improvement on average, while also reducing the false positive rate.Comment: A preliminary version of this paper appears in DIMVA 2015. This is the full version. arXiv admin note: substantial text overlap with arXiv:1403.212