Exploring data and model poisoning attacks to deep learning-based NLP systems

Natural Language Processing (NLP) is being recently explored also to its application in supporting malicious activities and objects detection. Furthermore, NLP and Deep Learning have become targets of malicious attacks too. Very recent researches evidenced that adversarial attacks are able to affect also NLP tasks, in addition to the more popular adversarial attacks on deep learning systems for image processing tasks. More precisely, while small perturbations applied to the data set adopted for training typical NLP tasks (e.g., Part-of-Speech Tagging, Named Entity Recognition, etc..) could be easily recognized, models poisoning, performed by the means of altered data models, typically provided in the transfer learning phase to a deep neural networks (e.g., poisoning attacks by word embeddings), are harder to be detected. In this work, we preliminary explore the effectiveness of a poisoned word embeddings attack aimed at a deep neural network trained to accomplish a Named Entity Recognition (NER) task. By adopting the NER case study, we aimed to analyze the severity of such a kind of attack to accuracy in recognizing the right classes for the given entities. Finally, this study represents a preliminary step to assess the impact and the vulnerabilities of some NLP systems we adopt in our research activities, and further investigating some potential mitigation strategies, in order to make these systems more resilient to data and models poisoning attacks

Titanium versus absorbable tacks comparative study (TACS): a multicenter, non-inferiority prospective evaluation during laparoscopic repair of ventral and incisional hernia: study protocol for randomized controlled trial

BACKGROUND: Laparoscopic repair of ventral and incisional hernias has gained popularity since many studies have reported encouraging results in terms of outcomee and recurrence. Choice of mesh and fixation methods are considered crucial issues in preventing recurrences and complications. Lightweight meshes are considered the first choice due to their biomechanical properties and the ability to integrate into the abdominal wall. Titanium helicoidal tacks still represent the "gold standard" for mesh fixation, even if they have been suggested to be involved in the genesis of post-operative pain and complications. Recently, absorbable tacks have been introduced, under the hypothesis that there will be no need to maintain a permanent fixation device after mesh integration. Nevertheless, there is no evidence that absorbable tacks may guarantee the same results as titanium tacks in terms of strength of fixation and recurrence rates. The primary end point of the present trial is to test the hypothesis that absorbable tacks are non-inferior to titanium tacks in laparoscopic incisional and ventral hernia repair (LIVHR) by lightweight polypropylene mesh, in terms of recurrence rates at 3-year follow-up. Surgical complications, post-operative stay, comfort and pain are secondary end points to be assessed. METHODS/DESIGN: Two hundred and twenty patients with ventral hernia will be randomized into 2 groups: Group A (110) patients will be submitted to LIVHR by lightweight polypropylene mesh fixed by titanium tacks; Group B (110) patients will be submitted to LIVHR by lightweight polypropylene mesh fixed by absorbable tacks. DISCUSSION: A few retrospective studies have reported similar results when comparing absorbable versus non-absorbable tacks in terms of intraoperative and early post-operative outcomes. These studies have the pitfalls to be retrospective evaluation of small series of patients, and the reported results still need to be validated by larger series and prospective studies. The aim of the present trial is to investigate and test the non-inferiority of absorbable versus non-absorbable tacks in terms of hernia recurrence rates, in order to assess whether the use of absorbable tacks may achieve the same results as non-absorbable tacks in mid-term and long-term settings

An AI-Assisted Design Method for Topology Optimization Without Pre-Optimized Training Data

Topology optimization is widely used by engineers during the initial product development process to get a first possible geometry design. The state-of-the-art is the iterative calculation, which requires both time and computational power. Some newly developed methods use artificial intelligence to accelerate the topology optimization. These require conventionally pre-optimized data and therefore are dependent on the quality and number of available data. This paper proposes an AI-assisted design method for topology optimization, which does not require pre-optimized data. The designs are provided by an artificial neural network, the predictor, on the basis of boundary conditions and degree of filling (the volume percentage filled by material) as input data. In the training phase, geometries generated on the basis of random input data are evaluated with respect to given criteria. The results of those evaluations flow into an objective function which is minimized by adapting the predictor's parameters. After the training is completed, the presented AI-assisted design procedure supplies geometries which are similar to the ones generated by conventional topology optimizers, but requires a small fraction of the computational effort required by those algorithms. We anticipate our paper to be a starting point for AI-based methods that requires data, that is hard to compute or not available

Sirt3 and metabolic reprogramming mediate the antiproliferative effects of whey in human colon cancer cells

Emerging strategies to improve healthy aging include dietary interventions as a tool to promote health benefits and reduce the incidence of aging-related comorbidities. The health benefits of milk are also linked to its richness in betaines and short-chain acylcarnitines, which act synergisti-cally in conferring anticancer, anti-inflammatory, and antioxidant properties. Whey, despite being a dairy by-product, still has a considerable content of bioactive betaines and acylcarnitines. Here, we investigated the anticancer properties of whey from Mediterranean water buffalo (Bubalus bubalis) milk by testing its antiproliferative effects in colorectal cancer (CRC) cells HT-29, HCT 116, LoVo and SW480. Results indicated that treatment with whey for 72 h inhibited cell proliferation (p < 0.001), induced cell cycle arrest, and apoptosis via caspase-3 activation, and modulated cell metabolism by limiting glucose uptake and interfering with mitochondrial energy metabolism with the highest effects observed in HT-29 and HCT 116 cells. At molecular level, these effects were accompanied by upregulation of sirtuin 3 (SIRT3) (p < 0.01) and peroxisome proliferator-activated receptor (PPAR)-γ expression (p < 0.001), and downregulation of lactate dehydrogenase A (LDHA) (p < 0.01), sterol regulatory-element binding protein 1 (SREBP1) (p < 0.05), and PPAR-α (p < 0.01). Transient SIRT3 gene silencing blocked the effects of whey on the LDHA, PPAR-γ, and PPAR-α protein expressions (p < 0.01) suggesting that the whey capacity of perturbating the metabolic homeostasis in CRC cell lines is mediated by SIRT3

Adhesion molecules in gamete transport, fertilization, early embryonic development, and implantation—role in establishing a pregnancy in cattle: A review

Cell–cell adhesion molecules have critically important roles in the early events of reproduction including gamete transport, sperm–oocyte interaction, embryonic development, and implantation. Major adhesion molecules involved in reproduction include cadherins, integrins, and disintegrin and metalloprotease domain-containing (ADAM) proteins. ADAMs on the surface of sperm adhere to integrins on the oocyte in the initial stages of sperm–oocyte interaction and fusion. Cadherins act in early embryos to organize the inner cell mass and trophectoderm. The trophoblast and uterine endometrial epithelium variously express cadherins, integrins, trophinin, and selectin, which achieve apposition and attachment between the elongating conceptus and uterine epithelium before implantation. An overview of the major cell–cell adhesion molecules is presented and this is followed by examples of how adhesion molecules help shape early reproductive events. The argument is made that a deeper understanding of adhesion molecules and reproduction will inform new strategies that improve embryo survival and increase the efficiency of natural mating and assisted breeding in cattle

Strategies to reduce embryonic mortality in buffalo cows

The aim of the present study was to examine whether treatment with a GnRH agonist, hCG or P4 on Day 25 after AI increased P4 concentrations and reduced the incidence of embryonic mortality (EM) in pregnant buffaloes mated in mid-winter in a Mediterranean environment. The trial was carried out in two farms characterized, in previous years, by low (LEM Group), 153 buffaloes (DIM=150±7 days), and high (HEM Group), 284 buffaloes (DIM=163±5 days), incidence of embryo mortality. Animals were synchronized by Ovsynch-TAI Program and artificially inseminated. On day 25, pregnant buffaloes were randomly assigned to four groups: Control (no treatment), GnRH agonist (buserelin acetate, 12.6 μg), hCG (1500 IU) and P4 (341 mg of P4 i.m. every 4 days for three times). Progesterone (pg/ml) was determined in milk whey on Days 10, 20 and 25 after AI in all buffaloes and in Days 30 and 45 only in buffaloes pregnant on day 25 and assigned to four groups of treatment. Pregnancy diagnosis was undertaken on Day 45 by ultrasound. All treatments increased P4 milk whey and reduced embryonic mortality in buffalo cows bred in the farm characterized by high EM

embryonic mortality in buffalo naturally mated

The aim of this work was to evaluate the incidence of embryonic mortality in three different period of year in buffaloes naturally mated. The trial was carried out in a buffalo farm located in Caserta province between 2000-2006. In this period were registered natural insemination on 200 buffaloes. Pregnancy diagnosis was carried out on Day 30, confirmed on Day 45 and every 15th days until 90 days after natural mating. Buffaloes that were pregnant on Day 30 but not on Day 45 or Day 90 were considered to have undergone embryonic (EM) or fetal mortality (FM) respectively. EM and FM were 8.8% and 13.4% respectively throughout the experimental period. A high incidence (P<0.01) of FM was found in the transitional period (December-March) than in other months of the year. The incidence of embryonic mortality was significantly (P<0.01) higher between 28-60 days of gestation and lower after 71 day of gestation. The higher fetal mortality found in this study could be due the lower serum levels of progesterone normally found in transitional period in buffalo cows

Relationship of body condition score and blood urea and ammonia to pregnancy in Italian Mediterranean buffaloes

The relationship of body condition score ( BCS) and blood urea and ammonia to pregnancy outcome was examined in Italian Mediterranean Buffalo cows mated by AI. The study was conducted on 150 buffaloes at 145 +/- 83 days in milk that were fed a diet comprising 14.8% crude protein, 0.9 milk forage units . kg(-1) dry matter and a non- structural carbohydrate/ crude protein ratio of 2.14. The stage of the oestrous cycle was synchronised by the Ovsynch- TAI programme and blood urea and ammonia levels were assessed on the day of AI. Energy corrected milk ( ECM) production and BCS were recorded bi- weekly. The pregnancy risk was 46.7% and was slightly lower in buffaloes with BCS 7.5. There were no significant differences in ECM, urea and ammonia between pregnant and non- pregnant buffaloes. However, pregnancy outcome was higher ( P = 0.02) in buffaloes with blood urea < 6.83 mmol . L-1. The likelihood of pregnancy for buffaloes with low urea blood level was 2.6 greater than for high urea level and exposure to a high urea level lowered the probability of pregnancy by about 0.25. The findings indicate that buffaloes are similar to cattle and increased blood levels of urea are associated with reduced fertility when animals are mated by AI