Miracle-dz/UniFAR-FTUs huggingface dataset:
A Formal Analysis of the Bitcoin Protocol

We study Nakamoto's Bitcoin protocol that implements a distributed ledger on peer-to-peer asynchronous networks. In particular, we define a principled formal model of key participants-the miners-as stochastic processes and describe the whole system as a parallel composition of miners. We therefore compute the probability that ledgers turn into a state with more severe inconsistencies, e.g. with longer forks, under the assumptions that messages are not lost and nodes are not hostile. We also study how the presence of hostile nodes mining blocks in wrong positions impacts on the consistency of the ledgers. Our theoretical results agree with the simulations performed on a probabilistic model checker that we extended with dynamic datatypes in order to have a faithful description of miners' behaviour.
Introductory lecture: blazing the trail from metals to nuclei

Emphasis is given to studies of individual clusters. Molecular beam experiments indicate that in isolated metal clusters the stability, shape and several other properties are often dominated by electronic rather than atomic packing effects. Magic numbers arise as in nuclear shell theory. Electron microscopy of supported clusters indicates a preference for simple crystal including icosahedral, though often imperfect, structures and the smallest clusters can be unstable under electron illumination. The possibility of reconciling these results is discussed.
THE RELATIONSHIP OF RAZOR BLADE SHEAR, ALLO‐KRAMER SHEAR, WARNER‐BRATZLER SHEAR AND SENSORY TESTS TO CHANGES IN TENDERNESS OF BROILER BREAST FILLETS

This study evaluated the ability of the razor blade (RB) shearing method and various other instrumental shearing methods as a means for developing models to predict tenderness in broiler breast fillets. Breast fillets were subjected to either shear analysis (razor, Allo-Kramer or Warner-Bratzler) or sensory evaluation (trained descriptive or consumer). The relationships between the instrumental and the descriptive sensory attributes exhibited coefficients of determination of 0.53 < R2 < 0.73 for initial hardness and chewdown hardness, while the relationships between the instrumental and the consumer sensory attributes of tenderness acceptability and intensity had coefficients of determination ranging between 0.71 < R2 < 0.97. For both descriptive and consumer sensory analyses, the instrumental shear tests performed similarly for predicting the tenderness of cooked broiler breast meat. The RB shear test for assessing meat tenderness had advantages, in that no sample cutting or weighing was required to execute the test nor was it excessively destructive, as only a small incision was made in the sample.
Microencapsulation of Fish Oil by Simple Coacervation of Hydroxypropyl Methylcellulose

To improve the oxidative stability and application of fish oil, it was microencapsulated by simple coacervation followed by spray drying. Simple coacervation took place by adding malt dextrin into the emulsion of fish oil and hydroxypropyl methylcellulose (HPMC) solution. Influences of several process parameters on the microencapsulation were evaluated and the oxidative stability and microstructure of microcapsules were analyzed. Results showed that the coacervation could be observed only when dextrose equivalent value (DE value) of malt dextrin, concentration of HPMC solution and fish oil percentage in microcapsules were no more than 20, 5% and 40%, respectively. Moreover, microencapsulation efficiency was higher at HPMC solution concentration of 4% and fish oil percentage of less than 30%. The oxidative stability of fish oil was improved by the microencapsulation and done best in the case of replacing malt dextrin by 40% with acacia. Scanning electronic microscopic photographs showed that the microcapsule obtained was a round, smooth and hollow microcapsule with its wall made up of innumerable small and solid submicrocapsules with the core of fish oil.
Segmentation by Involvement or Nationality for Global Retailing: A Cross-national Comparative Study of Wine Shopping Behaviours

In a study examining wine retail choices of two samples from two different countries (France and Australia), the authors examined the respective contribution of involvement and nationality as segmentation variables. The results suggest that while French wine shoppers differ somewhat from their Australian counterparts, strategies aimed at identifying high-involvement wine consumers may be more successful on a global scale. Whilst there are none to date, this study suggests that there is scope for the development of global wine retailers.
Effect of Clinical Pathway Application on Health Outcomes of Patients Undergoing Colorectal Surgery

Colorectal cancer is a disease with a major worldwide burden. Care for colorectal cancer patients undergoing surgery tends to be suitable for clinical pathway development because of high-cost of the procedure and the predictable course of events and complications that may occur during hospitalization. Objective: Determine the effect of clinical pathway application on health outcomes of patients undergoing colorectal surgery. Setting: The study was conducted in the Colon and Rectal Surgical Unit at Alexandria Main University Hospital. Subjects: A convenience sample of 50 adult patients with colon or rectal cancer or both undergoing colorectal surgery was included. They were equally and randomly recruited into two groups: a control group and a study 25 each. Tools: Three tools were used for data collection. I: Perioperative Colorectal Surgery Patient Assessment. II: Clinical Pathway Variance Observational Checklist, and III: Colorectal Surgical Patient's Satisfaction tool. Results: There were statistical significant differences between control and study group with whom the (clinical pathway was implemented) as they showed better post colorectal outcomes in relation to wound healing, pain control, achieving criteria for discharge. Conclusion: Patients undergoing colorectal surgery on whom the clinical pathway was applied exhibited improved postoperative outcomes than those on whom it was not. Recommendations: It is recommended that colorectal surgery clinical pathway be used rather than the traditional delivery of care.
Forest Fire reseArch

As a tool of land management and conservation there are a number of applications for which fire is poorly developed. One of those applications is the management of ecosystem services such as pollination and pest control that are provided by mobile organisms. Pollination in particular is an ecosystem service that requires improved management, in response to global declines in pollinators that present a threat to the plants that are dependent on them for reproduction. Much recent attention has been given to the effects of land use and land management generally on pollination, but little to fire as a particular form of land management. Here we develop a conceptual model describing hypothesised causal chains linking fire to pollination, and then report the initial findings of a study investigating fire effects on pollination as informed by this model for an orchid species native to Australia.
What Concerns Consumers about Hypertension? A Comparison between the Online Health Community and the Q&A Forum

In this paper, the Biterm topic modeling method and comparative analysis were employed to identify consumers’ information needs on hypertension and their differences between the Online Health Community and the Q&A Forum. There are common informationneedsonbothplatformsbutconsumersonMedHelpdiscussedmoreaboutpathologyandpharmacology,andmen-talhealthofhypertensionthanthoseonQuora.Theresultscanhelpconsumers,socialmediaplatformdesigners,andmedical professionalsbetterunderstandconsumers’informationneedsonhypertension.
A Scheduler for a Multi-paradigm Grid Environment

Typical Grid environments are characterized by a two-level scheduling: super and local scheduling. While the former regards the selection of proper resources to execute high level tasks, the latter regards the scheduling of tasks to processors for optimizing performance and hardware exploitation. This paper proposes a super scheduler that provides services to domain speciﬁc high-level programming environments, while taking advantage of middleware libraries to handle the complexity of Grid computing. To prove the ﬂexibility of the scheduler, three different programming environments with slightly different programming abstractions have been integrated with it: a problem solving environment (SEGL), a skeleton framework (Calcium) and a workﬂow enactment engine (SAWE). The integration above shows how it is possible to facilitate the adoption of the ProActive middleware for the development of complex Grid applications.
Extending the Veros climate simulator with biochemistry

Marine biogeochemistry poses a set of nonlinear coupled problems. Biogeochemistry covers a large variety of components, each with varying importance in different regions. This raises an issue for the models of providing functionality for many possible combinations of actively tracked components and the dynamical systems between them with as little overhead as possible. When models provide multiple configuration options, they must maintain each combination of possible options, which in many models has lead to complex, difficult to maintain code structures. This limits the availability of the model for new users and may require significant introduction times. I propose a different model design, which is able to accommodate configuration options without the combinatorial problems of other designs, and allows for easy addition of new features without the risk of breaking existing functionality. The design is implemented as a module to the ”Versatile Ocean Simulation in Pure Python”, Veros. I discuss the design choices and requirements for a modern, approachable biogeochemistry simulation model, and present results produced by the implemented design. Finally I simulate a weakening of the Atlantic meridional overturning circulation and analyze the results on global biogeochemistry.
ONLINE JOURNAL OF ANIMAL AND FEED RESEARCH

In present study, brine shrimp (Artemia salina L.) was used to determine the toxicity of auto-detoxified Jatropha kernel cake (JKC) mixed with bovine blood (ADMJKC/bb). The powdered-JKC was mixed with bovine blood (bb) at three ratios (1:1=X, 2:1=Y and 3:1=Z of JKC: bb) and the resultant mixtures processed using four protocols: Heated, Spread Dry = 1, Unheated Spread Dry = 2, Heated Spread Remoisten to 66% dry matter (DM) = 3 and Unheated Spread Remoistened to 66% DM = 4). The resultant 12 treatment combinations (X1, X2, X3, X4, Y1, Y2, Y3, Y4, Z1, Z2, Z3 and Z4) were placed in a Solar J. curcas auto-detoxification apparatus from where samples were retrieved periodically and evaluated for detoxification using the brine shrimp lethality test. There were no significant differences within the same ratio of mixes among the four protocols. However, there was a tendency for mean LC50 values to increase between the ratios. Specifically, Protocol 2 recorded a significant difference between X2 and Z2 treatments, having 1:1 and 3:1 JKC: bb mixes respectively. Upon ranking the level of auto-detoxification, the most detoxified treatments (Z2 with LC50=4674 and Z4 with LC50 =3692) differed significantly from the least two (X1 with LC50=1383 and X2 with LC50=1459). Addition of bovine blood to JKC increased the dynamics of JKC auto-detoxification, probably due to the presence of some innate autodetoxifying microbial inoculum and bovine blood which boost the rapid growth, development and succession of these microbes. Thus combining JKC with bovine blood is complementary for JKC auto-detoxification, with the most detoxified ingredients (Z2, Z4 and Y3) appearing most suitable for further development and testing as feed ingredient for farm animals.
A Case for Hydrothermal Systems in Firsoff Crater

Life on Earth is thought to possibly have originated from ancient hydrothermal systems, some of which are associated with impact craters. This analogue was used to investigate the potential circumstances for past hydrothermal systems on Mars. Candidate craters are those with diameters >50km and evidence of phyllosilicates. All dust-covered and eroded craters were eliminated to avoid spectral data errors. Features found using HiRISE were found to be morphologically similar to hydrothermal systems on Earth. An analysis of the intersection of the crater depth profile with the Martian steady-state ground ice shows the intersection of the two, further supporting the existence of impact-induced hydrothermal phenomena. Firsoff Crater was imaged by THEMIS after comparing spectral and morphological data and analysed with respect to these criteria.
Propane/Propylene Separation by Simulated Moving Bed II. Measurement and Prediction of Binary Adsorption Equilibria of Propane, Propylene, Isobutane, and 1-Butene on 13X Zeolite

Abstract The design of a simulated moving bed (SMB) process relies on valid thermodynamic predictions of multicomponent adsorption built up from accurate binary adsorption equilibrium data. Experimental adsorption equilibria of binary mixtures constituted by propane, propylene, isobutane and 1-butene on 13X zeolite were determined using breakthrough experiments at 373 K and 150 kPa. In addition, these binary adsorption experiments allow to confirm the choice of isobutane as an interesting desorbent for the separation of propane-propylene by SMB, since it has an intermediate selectivity between the two species to separate. Various prediction models are available in the literature but only a few of them have both physical and thermodynamical consistency. The ideal adsorbed solution theory (IAST), the thermodynamically consistent extended Toth model (TCET), and the physically-consistent extended Toth isotherm (PCET) were used to predict binary adsorption equilibria from pure component adsorption isotherms parameters. The PCET model was found suitable for representing the adsorption equilibrium of the different hydrocarbon mixtures with a reasonably good accuracy.
Effect of Salinity and Nitrogen Form in Irrigation Water on Growth, Antioxidants and Fatty Acids Profiles in Halophytes Salsola australis, Suaeda maritima, and Enchylaena tomentosa for a Perspective of Biosaline Agriculture

Cultivation of salt-tolerant crops help to face to irreversible global salinization of freshwater and soils. In New-Caledonia, three halophytes are candidates for saline crops, Salsola australis R.Br. , Suaeda maritima (L.) Dumort and Enchylaena tomentosa R.Br. Their success and quality depend yet on availabilities of salinity and essential nutrients in agrosystems. So, we investigated effects of three salinities, i.e., control moderate and high, and five nitrogen ratios, i.e., 100:0, 75:25, 50:50, 25:75 or 0:100 NO3−-N:NH4+-N ratio on their growth and functional value for fatty acids and antioxidants. Results show that the leaf fatty acid and antioxidant profiles of species, emphasize their good potential to become functional crop products, based on comparison with other functional plants, dietetic recommendation, or functional indices. However, their total phenolic compounds (TPC) content can be influenced by N-ratio (Suaeda maritima and Enchylaena tomentosa) and their antioxidant activity index (AAI) can be influenced by salinity (Suaeda maritima), N-ratio (Salsola australis) or both (Enchylaenatomentosa). Their quantitative and/or qualitative fatty acid profiles can also be influenced by salinity (Enchylaena tomentosa), N-ratio (Suaeda maritima), or both (Salsola australis). Regarding these variations, involving salt tolerance and nitrogen nutrition mechanisms, we recommend suitable treatments to maintain or optimize the growth and the functional quality of leaves in the three species.
Atmospheric Pressure Spray and Electrospray Mass Spectra of Glycine and Its Oligopeptides

Mass spectra of glycine, glycyl-glycine and glycyl-glycyl-glyrine obtained by atmospheric pressure spray mass spectrometry (APS-MS) are compared with those obtained by electrospray mass spectrometry (ESP-MS). Intense cationized molecules of (M+Na)^+ and (M+K)^+ are observed in addition to protonated molecules of (M+H)^+ in the atmospheric pressure spray mass spectra, while only protonated molecules are observed in the electrospray mass spectra. This result clearly indicates that the two methods differ greatly as regards ionization process, although sample solutions are sprayed to produce ions under atmospheric pressure in both methods.
International Journal of Current Research in

Date of Publication: 06 April 2019 The study investigated the hormonal activities of Sida rhombifolia ethanolic leaf extract on micronor induced infertility in female rats. Sida rhombifolia is a shrub from the family Malvaceae. Forty eight (48) female albino rats were randomly placed into six (6) study groups of eight (8) rats each. Positive control group (PC) was given clean water and food, micronor control group (MC) induced with micronor but not treated with Sida rhombifolia, Sida rhombifolia control groups; SRC, SRM1, SRM2, SRM3 were induced with micronor and treated with ethanolic leaf extract of Sida rhombifolia at varying concentrations of 100mg/kg, 200mg/kg, and 400mg/kg body weight respectively for 14 days. Phytochemical screening, estrogen, luteinizing hormone, cholesterol and body weight indices were monitored in this research. Animals treated with Sida rhombifolia showed significant increase in estrogen and luteinizing hormone level (P<0.05) compared to the micronor control at varying concentrations. All treatment groups showed no significant difference (P<0.05) in cholesterol level compared positive control and micronor control. Keywords
Phishing Email Detection Method: Leveraging Data Across Diﬀerent Organizations

Phishing attacks are a common tool used by malicious actors to gain access to systems or exploit individuals. Much of the phishing detection schemes focuses on awareness training programs and detection models. While these methods, detection models utilizing machine learning techniques, blacklists, and other email characteristics such as domain names, email addresses, and URLs are helpful in combating the problem, more research is needed in order to detect phishing scams more accurately and precisely where phishing email data can play an important role. Nowadays phishing attacks exploit human vulnerabilities by targeting speciﬁc human emotions, such as fear, to trick users into giving up their personal information. Consideration of the emotional exploitation present in phishing emails data combined with current detection schemes could lead to better detection. The goal of this paper is to analyze the emotional related content of a phishing email dataset to see if there is any relation between the emotion exploited and the sender’s email domain. In addition, this research demonstrates the need for the collection and analysis of the various types of phishing emails and its related emotional content that can be beneﬁcial in developing better detection methods.
Behaviour Detection of Vehicles Using Graph Convolutional Networks with Attention

Autonomous driving has evolved with the advent of deep learning and increased computational capacity in the past two decades. While many tasks have evolved that help autonomous navigation, understanding on-road vehicle behaviour from a continuous sequence of sensor data (camera or radar) is an important and useful task. Determining state of other vehicles and their motion helps in decision making for the ego-vehicle (Self/Our Vehicle). Such systems can be a part of driver assistance systems or even path planners for vehicles to avoid obstacles. Instances of such decision making could be, deciding to apply brakes incase an external agent is moving into our lane or coming opposite to us. Another instance would be keeping distance from an aggressive driver who is changing lanes and overtaking frequently could be helpful and safer. Specifically, our proposed methods classify the behaviours of on-road vehicles into one of the following categories-{Moving Away, Moving Towards Us, Parked/stationary, Lane Change, Overtake}. Many current methods leverage 3D depth information using expensive equipment, such as Lidar and complex algorithms. In this thesis, we propose a simpler pipeline for understanding vehicle behaviour from a monocular (single camera) image sequence or video. This will help in easier installation of the equipment and helps in Driver Assistance systems. A simple video along with Camera parameters, scene semantics (Detected Objects in the images) are used to get information about the objects of interest (vehicles) and other static objects like lanes/poles in the scene. We consider detecting objects across frames as the pre-processing pipe-line and propose two main methods, 1.Spatio-temporal MRGCN (Chapter:3) and 2.Relational-Attentive GCN (Chapter:4) for behaviour detection of vehicles. We divide our process of identifying behaviours into learning positional information of vehicles first, and then observing them across time to make a prediction. The positional information is encoded by a Multi-Relational Graph Convolutional Network (MR-GCN) in both the methods. Temporal information is encoded by recurrent networks in Method 1, while it is formulated inside the graph in Method 2. We also showcase how Attention is an important aspect in both our methods through our experiments. The proposed frameworks can classify a variety of vehicle behaviours to high fidelity on datasets that are diverse and include European, Chinese and Indian on-road scenes. The framework also provides for seamless transfer of models across datasets without entailing re-annotation, retraining and even fine-tuning. We provide comparative performance gain over baselines and detail a variety of ablations to showcase the efficacy of the framework.
ATTENTION REGIONS IN TERRAIN ROUGHNESS CLASSIFICATION FOR OFF-ROAD AUTONOMOUS VEHICLES

This research examines the use of attention regions in terrain roughness prediction for off-road autonomous vehicles. We approach terrain roughness prediction as an image classiﬁcation problem, labeling images of upcoming drivable terrain with a measure of roughness derived from the z-axis acceleration readings taken by a vehicle’s inertial measurement unit. We used deep learning models to learn two roughness labeling schemas and examined whether an attention region surrounding the upcoming drivable terrain could improve the ability of our classiﬁers to predict terrain roughness. The results of our experiments demonstrate that in all cases, models utilizing images with no attention region show increased performance compared to those utilizing images with an attention region. These results indicate there is important contextual information in the non-path pixels of the images that assists models in predicting upcoming terrain roughness.