Data mining for detecting Bitcoin Ponzi schemes

Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives

Novel contrast-enhanced ultrasound imaging in prostate cancer

The purposes of this paper were to present the current status of contrast-enhanced transrectal ultrasound imaging and to discuss the latest achievements and techniques now under preclinical testing. Although grayscale transrectal ultrasound is the standard method for prostate imaging, it lacks accuracy in the detection and localization of prostate cancer. With the introduction of contrast-enhanced ultrasound (CEUS), perfusion imaging of the microvascularization became available. By this, cancer-induced neovascularisation can be visualized with the potential to improve ultrasound imaging for prostate cancer detection and localization significantly. For example, several studies have shown that CEUS-guided biopsies have the same or higher PCa detection rate compared with systematic biopsies with less biopsies needed. This paper describes the current status of CEUS and discusses novel quantification techniques that can improve the accuracy even further. Furthermore, quantification might decrease the user-dependency, opening the door to use in the routine clinical environment. A new generation of targeted microbubbles is now under pre-clinical testing and showed avidly binding to VEGFR-2, a receptor up-regulated in prostate cancer due to angiogenesis. The first publications regarding a targeted microbubble ready for human use will be discussed. Ultrasound-assisted drug delivery gives rise to a whole new set of therapeutic options, also for prostate cancer. A major breakthrough in the future can be expected from the clinical use of targeted microbubbles for drug delivery for prostate cancer diagnosis as well as treatmen

Molecular biomarkers in the context of focal therapy for prostate cancer: Recommendations of a delphi consensus from the focal therapy society

BACKGROUND: Focal therapy (FT) for prostate cancer (PCa) is promising. However, long-term oncological results are awaited and there is no consensus on follow-up strategies. Molecular biomarkers (MB) may be useful in selecting, treating and following up men undergoing FT, though there is limited evidence in this field to guide practice. We aimed to conduct a consensus meeting, endorsed by the Focal Therapy Society, amongst a large group of experts, to understand the potential utility of MB in FT for localized PCa. METHODS: A 38-item questionnaire was built following a literature search. The authors then performed three rounds of a Delphi Consensus using DelphiManager, using the GRADE grid scoring system, followed by a face-to-face expert meeting. Three areas of interest were identified and covered concerning MB for FT, 1) the current/present role; 2) the potential/future role; 3) the recommended features for future studies. Consensus was defined using a 70% agreement threshold. RESULTS: Of 95 invited experts, 42 (44.2%) completed the three Delphi rounds. Twenty-four items reached a consensus and they were then approved at the meeting involving (N.=15) experts. Fourteen items reached a consensus on uncertainty, or they did not reach a consensus. They were re-discussed, resulting in a consensus (N.=3), a consensus on a partial agreement (N.=1), and a consensus on uncertainty (N.=10). A final list of statements were derived from the approved and discussed items, with the addition of three generated statements, to provide guidance regarding MB in the context of FT for localized PCa. Research efforts in this field should be considered a priority. CONCLUSIONS: The present study detailed an initial consensus on the use of MB in FT for PCa. This is until evidence becomes available on the subject

Data mining for detecting Bitcoin Ponzi schemes

Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives

A Cluster Project Approach to Develop New Functional Dairy Products from Sheep and Goat Milk

The growing scientific interest in the role of food in promoting human health and wellbeing has profoundly influenced consumers’ perceptions and attitudes towards nutrition, leading to the advent of a new class of foods, called functional foods, which are currently one of the fastest growing food-producing sectors, particularly in the dairy industry. The cluster project “Diversification in sheep & goat Sardinian dairy production” was built and carried out, based on requests from ten Sardinian dairy companies, to plan and implement experimental protocols directed to develop new production processes, according to the latest health and nutritional guidelines. Consequently, the following different interconnected research lines were developed: lactose-free dairy products; low-fat dairy products; dairy products enriched with added functional ingredients. The studied processes were based on the modification of cheese milk or whey, through the elimination of or reduction in one or more components with negative health effects or by adding functional ingredients. Therefore, a total of six different dairy products were developed: two from sheep milk and whey and four from goat milk. The technological processes adopted were typically those of Ricotta, fresh and soft cheeses. Contextually, their adaptability to the industrial equipment available in the cluster dairy companies was verified, and most of them were successfully transferred. These novel dairy products meet the current market demand, which shows a greater interest in fresh and short-ripened dairy products, with a low energy intake and high nutritional value. Moreover, can represent an example of the diversification in the sheep and goat dairy sector

Replacement of fat with long-chain inulin in a fresh cheese made from caprine milk

The aim of this study was to evaluate the effect of the replacement of fat with long-chain inulin on textural and microstructural properties of a fresh caprine milk cheese. All the samples contained the same level of total solids (about 22%, w/w) and substitution of fat with inulin at levels from 2% to 7%. Penetrometry parameters were affected by the levels of replacement of fat with inulin; samples containing inulin were characterised by lower values of compressive force, stiffness, viscosity and adhesiveness (except for the sample with 2% fat substitution). Scanning electron microscopy (SEM) images showed that the positioning of inulin within the gel interrupted the casein/fat network. In conclusion, the rheological results were dependent on the arrangement of inulin within the protein/fat network and, in particular, as shown by SEM images, on the aggregation of inulin during cheese-making

Survival of Selected Pathogenic Bacteria during PDO Pecorino Romano Cheese Ripening

This study was conducted to assess, for the first time, the survival of the pathogenic bacteria Listeria monocytogenes, Salmonella spp., Escherichia coli O157:H7, and Staphylococcus aureus during the ripening of protected designation of origin (PDO) Pecorino Romano cheese. A total of twenty-four cheese-making trials (twelve from raw milk and twelve from thermized milk) were performed under the protocol specified by PDO requirements. Sheep cheese milk was first inoculated before processing with approximately 106 colony-forming unit (CFU) mL−1 of each considered pathogen and the experiment was repeated six times for each selected pathogen. Cheese composition and pathogens count were then evaluated in inoculated raw milk, thermized milk, and cheese after 1, 90, and 150 days of ripening. pH, moisture, water activity, and salt content of cheese were within the range of the commercial PDO Pecorino Romano cheese. All the cheeses made from raw and thermized milk were microbiologically safe after 90 days and 1 day from their production, respectively. In conclusion, when Pecorino Romano cheese is produced under PDO specifications, from raw or thermized milk, a combination of factors including the speed and extent of curd acidification in the first phase of the production, together with an intense salting and a long ripening time, preclude the possibility of growth and survival of L. monocytogenes, Salmonella spp., and E. coli O157:H7. Only S. aureus can be still detectable at such low levels that it does not pose a risk to consumers

Development and Chemico-Physical Characterization of Ovine Milk-Based Ingredients for Infant Formulae

The great majority of infant formula (FM) for neonate’s nutrition are produced using ingredients from cow milk. Recently, some countries, such as China and New Zealand, are turning their attention to the use of ovine milk ingredients for FM production. In this study, a pilot plant process has been set up to produce infant formula ingredients from Sarda sheep milk. To meet the nutritional needs of neonates (0–6 and 6–12 months of age) two different liquid milk-derived formulations (IF1 and IF2, respectively) obtained mixing whole milk, skimmed milk, and whey milk ultrafiltration concentrate (retentate) were produced. Compositional analysis of milk, retentate, and the final IFs showed that the two formulations contain elements of nutritional interest, such as well-balanced content of high biological value proteins (casein:whey proteins ratio of 30:70 and 60:40 for IF1 and IF2, respectively), vitamin A, E and B5, cholesterol, minerals, nucleotides, free amino acids and essential fatty acids (n–6:n–3 ~1), compatible with the growth and development needs of neonates. Therefore, the obtained IF1 and IF2 can be proposed as valuable ovine dairy ingredients for FM manufacturing. Further studies will be necessary to verify the adaptability of the developed process from laboratory to industrial scale application

Development and Chemico-Physical Characterization of Ovine Milk-Based Ingredients for Infant Formulae

The great majority of infant formula (FM) for neonate’s nutrition are produced using ingredients from cow milk. Recently, some countries, such as China and New Zealand, are turning their attention to the use of ovine milk ingredients for FM production. In this study, a pilot plant process has been set up to produce infant formula ingredients from Sarda sheep milk. To meet the nutritional needs of neonates (0–6 and 6–12 months of age) two different liquid milk-derived formulations (IF1 and IF2, respectively) obtained mixing whole milk, skimmed milk, and whey milk ultrafiltration concentrate (retentate) were produced. Compositional analysis of milk, retentate, and the final IFs showed that the two formulations contain elements of nutritional interest, such as well-balanced content of high biological value proteins (casein:whey proteins ratio of 30:70 and 60:40 for IF1 and IF2, respectively), vitamin A, E and B5, cholesterol, minerals, nucleotides, free amino acids and essential fatty acids (n–6:n–3 ~1), compatible with the growth and development needs of neonates. Therefore, the obtained IF1 and IF2 can be proposed as valuable ovine dairy ingredients for FM manufacturing. Further studies will be necessary to verify the adaptability of the developed process from laboratory to industrial scale application

Metabolomic profiling of Fiore Sardo cheese: Investigation of the influence of thermal treatment and ripening time using univariate and multivariate classification techniques

The effect of different sub-pasteurization heat treatments and different ripening times was investigated in this work. The metabolite profiles of 95 cheese samples were analyzed using GC–MS in order to determine the effects of thermal treatment (raw milk, 57 °C and 68 °C milk thermization) and ripening time (105 and 180 days). ANOVA test on GC–MS peaks complemented with false discovery rate correction was employed to identify the compounds whose levels significantly varied over different ripening times and thermal treatments. The univariate t-test classifier and Partial Least Square Discriminant Analysis (PLS-DA) provided acceptable classification results, with an overall accuracy in cross-validation of 76% for the univariate model and 72% from the PLS-DA. The metabolites that mostly changed with ripening time were amino acids and one endocannabinoid (i.e., arachidonoyl amide), while compounds belonging to the classes of biogenic amines and saccharides resulted in being strongly affected by the thermization process