Smart Learning to Find Dumb Contracts

We introduce Deep Learning Vulnerability Analyzer (DLVA), a vulnerability detection tool for Ethereum smart contracts based on powerful deep learning techniques for sequential data adapted for bytecode. We train DLVA to judge bytecode even though the supervising oracle, Slither, can only judge source code. DLVA's training algorithm is general: we "extend" a source code analysis to bytecode without any manual feature engineering, predefined patterns, or expert rules. DLVA's training algorithm is also robust: it overcame a 1.25% error rate mislabeled contracts, and the student surpassing the teacher; found vulnerable contracts that Slither mislabeled. In addition to extending a source code analyzer to bytecode, DLVA is much faster than conventional tools for smart contract vulnerability detection based on formal methods: DLVA checks contracts for 29 vulnerabilities in 0.2 seconds, a speedup of 10-500x+ compared to traditional tools. DLVA has three key components. Smart Contract to Vector (SC2V) uses neural networks to map arbitrary smart contract bytecode to an high-dimensional floating-point vector. Sibling Detector (SD) classifies contracts when a target contract's vector is Euclidian-close to a labeled contract's vector in a training set; although only able to judge 55.7% of the contracts in our test set, it has an average accuracy of 97.4% with a false positive rate of only 0.1%. Lastly, Core Classifier (CC) uses neural networks to infer vulnerable contracts regardless of vector distance. DLVA has an overall accuracy of 96.6% with an associated false positive rate of only 3.7%

Schooling to Exploit Foolish Contracts

We introduce SCooLS, our Smart Contract Learning (Semi-supervised) engine. SCooLS uses neural networks to analyze Ethereum contract bytecode and identifies specific vulnerable functions. SCooLS incorporates two key elements: semi-supervised learning and graph neural networks (GNNs). Semi-supervised learning produces more accurate models than unsupervised learning, while not requiring the large oracle-labeled training set that supervised learning requires. GNNs enable direct analysis of smart contract bytecode without any manual feature engineering, predefined patterns, or expert rules. SCooLS is the first application of semi-supervised learning to smart contract vulnerability analysis, as well as the first deep learning-based vulnerability analyzer to identify specific vulnerable functions. SCooLS's performance is better than existing tools, with an accuracy level of 98.4%, an F1 score of 90.5%, and an exceptionally low false positive rate of only 0.8%. Furthermore, SCooLS is fast, analyzing a typical function in 0.05 seconds. We leverage SCooLS's ability to identify specific vulnerable functions to build an exploit generator, which was successful in stealing Ether from 76.9% of the true positives

Ecotoxicity effects of oil Water Accommodated Fractions and oil Water Accommodated Fractions + Dispersant on cold environments: Acarita tonsa based bioassays and microbial community dynamics as monitoring tools

224 p.La contaminación por petróleo es un problema importante en los océanos y mares, especialmente en ambientes fríos y regiones polares, donde los procesos de remediación son más complejos y los ecosistemas son muy vulnerables. Durante un vertido de petróleo diversos factores meteorológicos y el movimiento de las olas favorecen la integración de los hidrocarburos hidrofílicos en la columna de agua, siendo el producto resultante la conocida como fracción acomodada del petróleo en el agua (WAF), que suele estar compuesta principalmente, aunque no solo, por hidrocarburos aromáticos policíclicos (HAPs). Históricamente como forma de remediación ante los vertidos de petróleo se ha utilizado la incorporación de dispersantes químicos que favorecen la degradación del petróleo. Sin embargo, diversos estudios han demostrado que los dispersantes químicos pueden tener efectos adversos sobre los organismos marinos. El objetivo de este proyecto de Tesis doctoral ha sido estimar el posible impacto del WAF de un petróleo nafténico del Atlántico Norte (NNA), con o sin la adición del dispersante químico Finasol OSR52, mediante bioensayos in vivo con copépodos y el estudio de alteraciones en comunidades microbianas. Los bioensayos con el organismo modelo Acartia tonsa demostraron que el NNA WAF fue menos tóxico que los WAFs obtenidos a partir de destilados de fuel oil (IFO 180 y Gasóleo de uso marítimo), que mostraron una alta toxicidad a distintos niveles de organización biológica (transcripción génica, reproducción y supervivencia) en los copépodos. Al añadir el dispersante químico el NNA WAF fue más tóxico para los copépodos en términos de alteración de la transcripción génica, la reproducción y la mortalidad. En el caso de las comunidades microbianas, al examinar en condiciones de microcosmos los efectos del NNA WAF en solitario y NNA WAF con dispersante, se pudo observar que el dispersante no favoreció la biodegradación bacteriana de los compuestos procedentes del NNA WAF. Sin embargo, sí alteró las dinámicas de las comunidades microbianas, tanto en la columna de agua como en el sedimento, favoreciendo ciertos taxones. Se observó que las comunidades microbianas que poseían desde el inicio bacterias degradadoras de hidrocarburos, debido a un historial de exposición crónico a estos compuestos (legacy effects), fueron el principal impulsor de la degradación de los HAPs en la columna de agua y en los sedimentos. En conclusión, la integración de bioensayos de toxicidad in vivo con copépodos y el estudio de la dinámica de las comunidades microbianas ofrecen una visión amplia de los efectos y respuestas en ecosistemas sensibles que puede causar un escenario de vertido de petróleo y la adición de dispersantes químicos

Hydrogenolysis of Glycerol over γ-Al2O3-Supported Iridium Catalyst

In recent years, much attention has been focused on the hydrogenolysis of biodiesel derived glycerol to other high value products for the sustainable development and efficient valorization strategies. In the present work, alumina-supported Ir catalyst was prepared by the incipient wetness impregnation method and tested in the glycerol hydrogenolysis reaction. The synthesized catalyst was characterized by neutron activation analysis, N2 physisorption, and H2 chemisorption techniques. The experiments standard conditions were 150 mL feed volume, 0.3 g catalyst, 1500 rpm stirring speed, and 5 wt% glycerol aqueous solution for 4 h. The effects of catalyst amount, temperature, hydrogen pressure, stirring speed, and solution pH on glycerol conversion and selectivity of the principal products obtained were also investigated. The glycerol conversion and the 1,2-propanediol selectivity varied from 4.9% to 22% and from 23.8% to 70.3%, respectively. It was found that the selectivity of 1,2-propanediol increased significantly with the increased alkalinity of the reaction medium

Patient Optimization is the Key in Surgical Repair of Ruptured Umblical Hernia in Cirrhotic Patients and Tense Ascitis

Background: Ulceration, leakage, and rupture are considered as the most common complications of umbilical hernias in patients with refractory ascites due to advanced cirrhosis. We aim to determine optimal management and outcome after umbilical herniorrhaphy or hernioplasty in those patients

A trust evaluation scheme of service providers in mobile edge computing

Mobile edge computing (MEC) is a new computing paradigm that brings cloud services to the network edge. Despite its great need in terms of computational services in daily life, service users may have several concerns while selecting a suitable service provider to fulfil their computational requirements. Such concerns are: with whom they are dealing with, where will their private data migrate to, service provider processing performance quality. Therefore, this paper presents a trust evaluation scheme that evaluates the processing performance of a service provider in the MEC environment. Processing performance of service providers is evaluated in terms of average processing success rate and processing throughput, thus allocating a service provider in a relevant trust status. Service provider processing incompliance and user termination ratio are also computed during provider’s interactions with users. This is in an attempt to help future service users to be acknowledged of service provider’s past interactions prior dealing with it. Thus, eliminating the probability of existing compromised service providers and raising the security and success of future interactions between service providers and users. Simulations results show service providers processing performance degree, processing incompliance and user termination ratio. A service provider is allocated to a trust status according to the evaluated processing performance trust degree

Tumescent Local Infiltration Anesthesia for Mini Abdominoplasty with Liposuction

AIM: To evaluate the feasibility and safety of mini abdominoplasty with liposuction under local tumescent anaesthesia (LA) as the sole anaesthetic modality. METHODS: The study included 60 female patients with a mean age of 33.3 ± 5.6 years. Local infiltration using a mixture of 1:1000 epinephrine (1 ml), 2% lidocaine (100 ml) and 0.5% Levobupivacaine (50 ml) in 2500 ml saline was started with Local infiltration started with the abdomen, outer thigh, hips, back, inner thighs and knees. After Mini Abdominoplasty with supplemental liposuction was conducted and application of suction drains wound closure was performed, and the tight bandage was applied. Pain during injection, incision and surgical manipulations was determined. Duration of postoperative analgesia, till oral intake and return home, patients and surgeon satisfaction scores were determined. RESULTS: All surgeries were conducted completely without conversion to general anaesthesia. Injection pain was mild in 46 patients, moderate in 10 and hardly tolerated in 4 patients. Incision pain was mild in 16 patients, while 44 patients reported no sensation. During the surgical procedure, 6 patients required an additional dose of LA. Meantime till resumption of oral intake was 1.6 ± 0.9 hours. Meantime till home return was 5.6 ± 2.4 hours. Twelve patients were highly satisfied, 18 patients were satisfied, and these 42 patients were willing to repeat the trial if required. Eight patients found the trial is good and only one patient refused to repeat the trial and was dissatisfied, for a mean total satisfaction score of 3.1 ± 0.9. CONCLUSION: Mini Abdominoplasty with liposuction could be conducted safely under tumescent LA with mostly pain-free intraoperative and PO courses and allowed such surgical procedure to be managed as an office procedure. The applied anaesthetic procedure provided patients’ satisfaction with varying degrees in about 97% of studied patients

The intraperitoneal ondansetron for postoperative pain management following laparoscopic cholecystectomy: A proof-of-concept, double-blind, placebo-controlled trial

Background Pain after laparoscopic cholecystectomy remains a major challenge. Ondansetron blocks sodium channels and may have local anesthetic properties. Aims To investigate the effect of intraperitoneal administration of ondansetron for postoperative pain management as an adjuvant to intravenous acetaminophen in patients undergoing laparoscopic cholecystectomy. Methods Patients scheduled for elective laparoscopic cholecystectomy were randomized into two groups (n = 25 each) to receive either intraperitoneal ondansetron or saline injected in the gall bladder bed at the end of the procedure. The primary outcome was the difference in pain from baseline to 24-h post-operative assessed by comparing the area under the curve of visual analog score between the two groups. Results The derived area under response curve of visual analog scores in the ondansetron group (735.8 ± 418.3) was 33.97% lower than (p = 0.005) that calculated for the control group (1114.4 ± 423.9). The need for rescue analgesia was significantly lower in the ondansetron (16%) versus in the control group (54.17%) (p = 0.005), indicating better pain control. The correlation between the time for unassisted mobilization and the area under response curve of visual analog scores signified the positive analgesic influence of ondansetron (rs = 0.315, p = 0.028). The frequency of nausea and vomiting was significantly lower in patients who received ondansetron than that reported in the control group (p = 0.023 (8 h), and 0.016 (24 h) respectively). Conclusions The added positive impact of ondansetron on postoperative pain control alongside its anti-emetic effect made it a unique novel option for patients undergoing laparoscopic cholecystectomy