Intertwining ROP Gadgets and Opaque Predicates for Robust Obfuscation

Software obfuscation plays a crucial role in protecting intellectual property in software from reverse engineering attempts. While some obfuscation techniques originate from the obfuscation-reverse engineering arms race, others stem from different research areas, such as binary software exploitation. Return-oriented programming (ROP) gained popularity as one of the most effective exploitation techniques for memory error vulnerabilities. ROP interferes with our natural perception of a process control flow, which naturally inspires us to repurpose ROP as a robust and effective form of software obfuscation. Although previous work already explores ROP's effectiveness as an obfuscation technique, evolving reverse engineering research raises the need for principled reasoning to understand the strengths and limitations of ROP-based mechanisms against man-at-the-end (MATE) attacks. To this end, we propose ROPFuscator, a fine-grained obfuscation framework for C/C++ programs using ROP. We incorporate opaque predicates and constants and a novel instruction hiding technique to withstand sophisticated MATE attacks. More importantly, we introduce a realistic and unified threat model to thoroughly evaluate ROPFuscator and provide principled reasoning on ROP-based obfuscation techniques that answer to code coverage, incurred overhead, correctness, robustness, and practicality challenges

A modified technique of orthotopic transplant of the kidney in rabbits

In this study kidneys were harvested from bred-for-research cats weighing 4 to 5 kg. General principles of donor bilateral nephrectomy en bloc with aorta, vena cava, renal vessels, and ureters were followed. After the harvest the grafts were placed in lactated Ringer slush. A cuff was prepared on the renal vein over a 10 French plastic tube. The aorta was divided and left in connection with the renal artery at each side. Twenty female checkered Flemish giant rabbits weighing 4.0-6.0 kg served as recipients. After premedication with 40 mg/kg of ketamine, anesthesia was maintained with repeated doses (every 10-15 min) of a 0.1-mL mixture of 5 parts ketamine and 1 part acepromazine diluted 50% in a normal saline. Arterial pressure, CVP, blood gases, and temperature were monitored. Through a limited midline incision a native left nephrectomy was performed. The venous anastomosis was performed with a cuff technique without clamping the vena cava (which causes severe hemodynamic instability); the anastomotic time was 2-3 min. The arterial anastomosis was performed with an end-to-side aorta-to-aorta anastomosis; the anastomotic time was 5 to 7 min. There were no episodes of venous or arterial thrombosis. The donor procedure took approximately 40 min, and the backtable preparation of the graft an additional 45 to 60 min. Preparation of the recipient for the anastomosis took 15 min and the anastomotic time (warm ischemia) was 13 +/- 5 min. In this model suitable for xenograft research the duration of the surgery in the recipient has been greatly reduced because of (1) the previous backtable preparation of the graft, and (2) the cuff technique used for venous anastomosis. The present anesthesia regimen and careful hemodynamic monitoring were also important in the success of this model

Failure analysis of fiberglass cover used for photovoltaic plants

Cover boxes with inspection glass are generally used outdoors for photovoltaic systems.Sometimes these boxes break, during normal use. Hightemperature, thermal stress, cyclic stress, and cracking contribute to weakening the polymeric inspection “glass”. The study presents an interdisciplinary analysis to discover the mode of occurrence and causes of the failure. First, the material is accurately characterized. Then its mechanical behavior is characterized in a virtual scenario that reconstructs the real external environment. The goal is to build a new cover with inspection boxes that exhibits superior life cycle behavior when exposed to harsh weather conditions and atmospheric agents. The breaking phenomena of solar panels covering boxes in PMMA (Poly Methyl Methacrylate) are examined. Environmental stress is the main responsible for cracking. Styrene is employed in the polymerization process of Sheet Molding Compound (SMC); the diffusion of this material is the main responsible for cracking. Comprehensive engineering analysis shows how the thermoplastic component fails after being exposed to atmospheric agents. The PMMA “glass” is one of the polymers most sensible to the crazing phenomena

Modelling approach to the assessment of biogenic fluxes at a selected Ross Sea site, Antarctica

Several biogeochemical data have been collected in the last 10 years of Italian activity in Antarctica (ABIOCLEAR, ROSSMIZE, BIOSESO-I/II). A comprehensive 1-D biogeochemical model was implemented as a tool to link observations with processes and to investigate the mechanisms that regulate the flux of biogenic material through the water column. The model is ideally located at station B (175° E–74° S) and was set up to reproduce the seasonal cycle of phytoplankton and organic matter fluxes as forced by the dominant water column physics over the period 1990–2001. Austral spring-summer bloom conditions are assessed by comparing simulated nutrient drawdown, primary production rates, bacterial respiration and biomass with the available observations. The simulated biogenic fluxes of carbon, nitrogen and silica have been compared with the fluxes derived from sediment traps data. The model reproduces the observed magnitude of the biogenic fluxes, especially those found in the bottom sediment trap, but the peaks are markedly delayed in time. Sensitivity experiments have shown that the characterization of detritus, the choice of the sinking velocity and the degradation rates are crucial for the timing and magnitude of the vertical fluxes. An increase of velocity leads to a shift towards observation but also to an overestimation of the deposition flux which can be counteracted by higher bacterial remineralization rates. Model results suggest that the timing of the observed fluxes depends first and foremost on the timing of surface production and on a combination of size-distribution and quality of the autochtonous biogenic material. It is hypothesized that the bottom sediment trap collects material originated from the rapid sinking of freshly-produced particles and also from the previous year's production period

Artificial intelligence weights the importance of factors predicting complete cytoreduction at secondary cytoreductive surgery for recurrent ovarian cancer

Objective: Accumulating evidence support that complete cytoreduction (CC) at the time of secondary cytoreductive surgery (SCS) improves survival in patients affected by recurrent ovarian cancer (ROC). Here, we aimed to determine whether artificial intelligence (AI) might be useful in weighting the importance of clinical variables predicting CC and survival. Methods: This is a retrospective study evaluating 194 patients having SCS for ROC. Using artificial neuronal network (ANN) analysis was estimated the importance of different variables, used in predicting CC and survival. ANN simulates a biological neuronal system. Like neurons, ANN acquires knowledge through a learning-phase process and allows weighting the importance of covariates, thus establishing how much a variable influences a multifactor phenomenon. Results: Overall, 82.9% of patients had CC at the time of SCS. Using ANN, we observed that the 3 main factors driving the ability of achieve CC included: disease-free interval (DFI) (importance: 0.231), retroperitoneal recurrence (importance: 0.178), residual disease at primary surgical treatment (importance: 0.138), and International Federation of Gynecology and Obstetrics (FIGO) stage at presentation (importance: 0.088). Looking at connections between different covariates and overall survival (OS), we observed that DFI is the most important variable influencing OS (importance: 0.306). Other important variables included: CC (importance: 0.217), and FIGO stage at presentation (importance: 0.100). Conclusion: According to our results, DFI should be considered as the most important factor predicting both CC and OS. Further studies are needed to estimate the clinical utility of AI in providing help in decision making process

Modelling approach to the assessment of biogenic fluxes at a selected Ross Sea site, Antarctica

Abstract Several biogeochemical data have been collected in the last 10 years of Italian activity in Antarctica (ABIOCLEAR, ROSSMIZE, BIOSESO-I/II). A comprehensive 1-D biogeochemical model was implemented as a tool to link observations with processes and to investigate the mechanisms that regulate the flux of biogenic material through the water column. The model is ideally located at station B (175^{o}E - 74^{o}S) and was set up to reproduce the seasonal cycle of phytoplankton and organic matter fluxes as forced by the dominant water column physics over the period 1990-2001. Austral spring-summer bloom conditions are assessed by comparing simulated nutrient drawdown, primary production rates, bacterial respiration and biomass with the available observations. The simulated biogenic fluxes of carbon, nitrogen and silica have been compared with the fluxes derived from sediment traps data. The model reproduces quite well the magnitude of the biogenic fluxes, expecially those observed in the bottom sediment trap, but the peaks are delayed in time. Sensitivity experiments have shown that the characterization of detritus, the choice of the sinking velocity and the degradation rates are crucial for the timing and magnitude of the vertical fluxes. An increase of velocity leads to a shift towards observation but also to an overestimation of the deposition flux which can be counteracted by higher bacterial remineralization rates. Model results suggest that observed fluxes could be explained by the size-distribution and quality of the locally-produced biogenic material. It is hypothesized that the bottom sediment trap collects material originated from rapid sinking of particles and also from previous years production periods, likely modulated by advective and aggregation mechanisms which are still not resolved by the model

An Efficient Molecular Dynamics Scheme for the Calculation of Dopant Profiles due to Ion Implantation

We present a highly efficient molecular dynamics scheme for calculating the concentration depth profile of dopants in ion irradiated materials. The scheme incorporates several methods for reducing the computational overhead, plus a rare event algorithm that allows statistically reliable results to be obtained over a range of several orders of magnitude in the dopant concentration. We give examples of using this scheme for calculating concentration profiles of dopants in crystalline silicon. Here we can predict the experimental profile over five orders of magnitude for both channeling and non-channeling implants at energies up to 100s of keV. The scheme has advantages over binary collision approximation (BCA) simulations, in that it does not rely on a large set of empirically fitted parameters. Although our scheme has a greater computational overhead than the BCA, it is far superior in the low ion energy regime, where the BCA scheme becomes invalid.Comment: 17 pages, 21 figures, 2 tables. See: http://bifrost.lanl.gov/~reed

Produção de morangos no sistema semihidropônico.

bitstream/CNPUV/8140/1/cir062.pdf2. ed

Detection and Classification of Hysteroscopic Images Using Deep Learning

Background: Although hysteroscopy with endometrial biopsy is the gold standard in the diagnosis of endometrial pathology, the gynecologist experience is crucial for a correct diagnosis. Deep learning (DL), as an artificial intelligence method, might help to overcome this limitation. Unfortunately, only preliminary findings are available, with the absence of studies evaluating the performance of DL models in identifying intrauterine lesions and the possible aid related to the inclusion of clinical factors in the model. Aim: To develop a DL model as an automated tool for detecting and classifying endometrial pathologies from hysteroscopic images. Methods: A monocentric observational retrospective cohort study was performed by reviewing clinical records, electronic databases, and stored videos of hysteroscopies from consecutive patients with pathologically confirmed intrauterine lesions at our Center from January 2021 to May 2021. Retrieved hysteroscopic images were used to build a DL model for the classification and identification of intracavitary uterine lesions with or without the aid of clinical factors. Study outcomes were DL model diagnostic metrics in the classification and identification of intracavitary uterine lesions with and without the aid of clinical factors. Results: We reviewed 1500 images from 266 patients: 186 patients had benign focal lesions, 25 benign diffuse lesions, and 55 preneoplastic/neoplastic lesions. For both the classification and identification tasks, the best performance was achieved with the aid of clinical factors, with an overall precision of 80.11%, recall of 80.11%, specificity of 90.06%, F1 score of 80.11%, and accuracy of 86.74 for the classification task, and overall detection of 85.82%, precision of 93.12%, recall of 91.63%, and an F1 score of 92.37% for the identification task. Conclusion: Our DL model achieved a low diagnostic performance in the detection and classification of intracavitary uterine lesions from hysteroscopic images. Although the best diagnostic performance was obtained with the aid of clinical data, such an improvement was slight

Molecular analysis of TP53, Ki-Ras and P16 methylation status in tissue and plasma of subjects affected by gastrointestinal cancer (GIC)

BACKGROUND: Despite the improvement in detection and surgical therapy in the last years, the outcome of patients affected by colorectal carcinoma (CRC) remains limited by metastatic relapse. The aim of this study was to investigate the presence of free tumor DNA in the plasma of CRC patients in order to understand its possible prognostic role. PATIENTS AND METHODS: Ki-Ras, TP53 mutations and p16(INK4A) methylation status were prospectively evaluated in tumor tissues and plasma of 66 CRC patients. RESULTS: In 50 of the 66 primitive tumor cases (76%) at least one significant alteration was identified in Ki-Ras and/or TP53 and/or p16(INK4A) genes. Eighteen of the 50 patients presented the same alteration both in the plasma and in the tumor tissue. At univariate analysis, Ki-Ras mutations proved to be significantly related to quicker relapse (P <0.01), whereas only a trend towards statistical significance (P = 0.083) was observed for the TP53 mutations CONCLUSIONS: Detection of Ki-Ras and TP53 mutation in plasma should be significantly related to disease recurrence. These data suggest that patients with a high risk of recurrence can be identified by means of the analysis of tumor-derived plasma DNA with the use of fairly non-invasive techniques