Integrated Support for Handoff Management and Context-Awareness in Heterogeneous Wireless Networks

The overwhelming success of mobile devices and wireless communications is stressing the need for the development of mobility-aware services. Device mobility requires services adapting their behavior to sudden context changes and being aware of handoffs, which introduce unpredictable delays and intermittent discontinuities. Heterogeneity of wireless technologies (Wi-Fi, Bluetooth, 3G) complicates the situation, since a different treatment of context-awareness and handoffs is required for each solution. This paper presents a middleware architecture designed to ease mobility-aware service development. The architecture hides technology-specific mechanisms and offers a set of facilities for context awareness and handoff management. The architecture prototype works with Bluetooth and Wi-Fi, which today represent two of the most widespread wireless technologies. In addition, the paper discusses motivations and design details in the challenging context of mobile multimedia streaming applications

Contraceptive use and sexual function: a comparison of Italian female medical students and women attending family planning services

Objectives: The aims of the study were to understand how education relates to contraceptive choice and how sexual function can vary in relation to the use of a contraceptive method. Methods: We surveyed female medical students and women attending a family planning service (FPS) in Italy. Participants completed an online questionnaire which asked for information on sociodemographics, lifestyle, sexuality and contraceptive use and also included items of the Female Sexual Function Index (FSFI). Results: The questionnaire was completed by 413 women (362 students and 51 women attending the FPS) between the ages of 18 and 30 years. FSFI scores revealed a lower risk of sexual dysfunction among women in the control group who did not use oral hormonal contraception. The differences in FSFI total scores between the two study groups, when subdivided by the primary contraceptive method used, was statistically significant (p < 0.005). Women using the vaginal ring had the lowest risk of sexual dysfunction, compared with all other women, and had a positive sexual function profile. In particular, the highest FSFI domain scores were lubrication, orgasm and satisfaction, also among the control group. Expensive contraception, such as long-acting reversible contraception, was not preferred by this young population, even though such methods are more contemporary and manageable. Compared with controls, students had lower compliance with contraception and a negative attitude towards voluntary termination of pregnancy. Conclusion: Despite their scientific knowledge, Italian female medical students were found to need sexual and contraceptive assistance. A woman's sexual function responds to her awareness of her body and varies in relation to how she is guided in her contraceptive choice. Contraceptive counselling is an excellent means to improve female sexuality

Big Data in Critical Infrastructures Security Monitoring: Challenges and Opportunities

Critical Infrastructures (CIs), such as smart power grids, transport systems, and financial infrastructures, are more and more vulnerable to cyber threats, due to the adoption of commodity computing facilities. Despite the use of several monitoring tools, recent attacks have proven that current defensive mechanisms for CIs are not effective enough against most advanced threats. In this paper we explore the idea of a framework leveraging multiple data sources to improve protection capabilities of CIs. Challenges and opportunities are discussed along three main research directions: i) use of distinct and heterogeneous data sources, ii) monitoring with adaptive granularity, and iii) attack modeling and runtime combination of multiple data analysis techniques.Comment: EDCC-2014, BIG4CIP-201

Role of poly [adp-ribose] polymerase 1 in activating the kirsten ras (Kras) gene in response to oxidative stress

In pancreatic Panc-1 cancer cells, an increase of oxidative stress enhances the level of 7,8-dihydro-8-oxoguanine (8OG) more in the KRAS promoter region containing G4 motifs than in non-G4 motif G-rich genomic regions. We found that H2O2 stimulates the recruitment to the KRAS promoter of poly [ADP-ribose] polymerase 1 (PARP-1), which efficiently binds to local G4 structures. Upon binding to G4 DNA, PARP-1 undergoes auto PARylation and thus becomes negatively charged. In our view this should favor the recruitment to the KRAS promoter of MAZ and hnRNP A1, as these two nuclear factors, because of their isoelectric points >7, are cationic in nature under physiological conditions. This is indeed supported by pulldown assays which showed that PARP-1, MAZ, and hnRNP A1 form a multiprotein complex with an oligonucleotide mimicking the KRAS G4 structure. Our data suggest that an increase of oxidative stress in Panc-1 cells activates a ROS-G4-PARP-1 axis that stimulates the transcription of KRAS. This mechanism is confirmed by the finding that when PARP-1 is silenced by siRNA or auto PARylation is inhibited by Veliparib, the expression of KRAS is downregulated. When Panc-1 cells are treated with H2O2 instead, a strong up-regulation of KRAS transcription is observed

More Kindness, Less Prejudice against Immigrants? A Preliminary Study with Adolescents

Prejudice against immigrants is a relevant research topic within social psychology. Researchers identified several individual variables affecting anti-immigrant prejudice, such as morality and personality. However, until now, prejudice has never been studied in relation to kindness, which might be a significant protective factor against prejudice. Based on Kohlberg's theory of moral judgement, four stage dimensions of kindness were identified, from egocentric to authentic kindness (i.e., a means for social progress and improvement). This study aims to explore the relationship between the four kindness dimensions and blatant and subtle prejudice against immigrants in adolescence, by also considering the moderating role of adolescents' sex. It involved 215 Italian participants (77% girls), who were asked to fill in a self-report questionnaire. Results showed that boys scored higher on egocentric kindness than girls, but no sex differences emerged for prejudice. Egocentric and extrinsically motivated kindness appeared to be risk factors for prejudice, whereas the most authentic form of kindness was a protective factor. In addition, adolescents' sex moderated the relationship between egocentric kindness and blatant prejudice, whereby this association was stronger for boys. The implications of these findings, the study's limitations, and suggestions for future research are discussed

MV-MS-FETE: Multi-view multi-scale feature extractor and transformer encoder for stenosis recognition in echocardiograms

Background: aortic stenosis is a common heart valve disease that mainly affects older people in developed countries. Its early detection is crucial to prevent the irreversible disease progression and, eventually, death. A typical screening technique to detect stenosis uses echocardiograms; however, variations introduced by other tissues, camera movements, and uneven lighting can hamper the visual inspection, leading to misdiagnosis. To address these issues, effective solutions involve employing deep learning algorithms to assist clinicians in detecting and classifying stenosis by developing models that can predict this pathology from single heart views. Although promising, the visual information conveyed by a single image may not be sufficient for an accurate diagnosis, especially when using an automatic system; thus, this indicates that different solutions should be explored. Methodology: following this rationale, this paper proposes a novel deep learning architecture, composed of a multi-view, multi-scale feature extractor, and a transformer encoder (MV-MS-FETE) to predict stenosis from parasternal long and short-axis views. In particular, starting from the latter, the designed model extracts relevant features at multiple scales along its feature extractor component and takes advantage of a transformer encoder to perform the final classification. Results: experiments were performed on the recently released Tufts medical echocardiogram public dataset, which comprises 27,788 images split into training, validation, and test sets. Due to the recent release of this collection, tests were also conducted on several state-of-the-art models to create multi-view and single-view benchmarks. For all models, standard classification metrics were computed (e.g., precision, F1-score). The obtained results show that the proposed approach outperforms other multi-view methods in terms of accuracy and F1-score and has more stable performance throughout the training procedure. Furthermore, the experiments also highlight that multi-view methods generally perform better than their single-view counterparts. Conclusion: this paper introduces a novel multi-view and multi-scale model for aortic stenosis recognition, as well as three benchmarks to evaluate it, effectively providing multi-view and single-view comparisons that fully highlight the model's effectiveness in aiding clinicians in performing diagnoses while also producing several baselines for the aortic stenosis recognition task

Signal enhancement and efficient DTW-based comparison for wearable gait recognition

The popularity of biometrics-based user identification has significantly increased over the last few years. User identification based on the face, fingerprints, and iris, usually achieves very high accuracy only in controlled setups and can be vulnerable to presentation attacks, spoofing, and forgeries. To overcome these issues, this work proposes a novel strategy based on a relatively less explored biometric trait, i.e., gait, collected by a smartphone accelerometer, which can be more robust to the attacks mentioned above. According to the wearable sensor-based gait recognition state-of-the-art, two main classes of approaches exist: 1) those based on machine and deep learning; 2) those exploiting hand-crafted features. While the former approaches can reach a higher accuracy, they suffer from problems like, e.g., performing poorly outside the training data, i.e., lack of generalizability. This paper proposes an algorithm based on hand-crafted features for gait recognition that can outperform the existing machine and deep learning approaches. It leverages a modified Majority Voting scheme applied to Fast Window Dynamic Time Warping, a modified version of the Dynamic Time Warping (DTW) algorithm with relaxed constraints and majority voting, to recognize gait patterns. We tested our approach named MV-FWDTW on the ZJU-gaitacc, one of the most extensive datasets for the number of subjects, but especially for the number of walks per subject and walk lengths. Results set a new state-of-the-art gait recognition rate of 98.82% in a cross-session experimental setup. We also confirm the quality of the proposed method using a subset of the OU-ISIR dataset, another large state-of-the-art benchmark with more subjects but much shorter walk signals

A Novel Transformer-Based IMU Self-Calibration Approach through On-Board RGB Camera for UAV Flight Stabilization

During flight, unmanned aerial vehicles (UAVs) need several sensors to follow a predefined path and reach a specific destination. To this aim, they generally exploit an inertial measurement unit (IMU) for pose estimation. Usually, in the UAV context, an IMU entails a three-axis accelerometer and a three-axis gyroscope. However, as happens for many physical devices, they can present some misalignment between the real value and the registered one. These systematic or occasional errors can derive from different sources and could be related to the sensor itself or to external noise due to the place where it is located. Hardware calibration requires special equipment, which is not always available. In any case, even if possible, it can be used to solve the physical problem and sometimes requires removing the sensor from its location, which is not always feasible. At the same time, solving the problem of external noise usually requires software procedures. Moreover, as reported in the literature, even two IMUs from the same brand and the same production chain could produce different measurements under identical conditions. This paper proposes a soft calibration procedure to reduce the misalignment created by systematic errors and noise based on the grayscale or RGB camera built-in on the drone. Based on the transformer neural network architecture trained in a supervised learning fashion on pairs of short videos shot by the UAV’s camera and the correspondent UAV measurements, the strategy does not require any special equipment. It is easily reproducible and could be used to increase the trajectory accuracy of the UAV during the flight

Gonosomal mosaicism for a novel col5a1 pathogenic variant in classic ehlers-danlos syndrome

(1) Background: Classic Ehlers-Danlos syndrome (cEDS) is a heritable connective tissue disorder characterized by joint hypermobility and skin hyperextensibility with atrophic scarring. Many cEDS individuals carry variants in either the COL5A1 or COL5A2 genes. Mosaicism is relatively common in heritable connective tissue disorders but is rare in EDS. In cEDS, a single example of presumed gonosomal mosaicism for a COL5A1 variant has been published to date. (2) Methods: An 8-year-old girl with cEDS was analyzed by next-generation sequencing (NGS). Segregation was performed by Sanger sequencing in her unaffected parents. In the father, the mosaicism of the variant was further analyzed by targeted NGS and droplet digital PCR (ddPCR) in the blood and by Sanger sequencing in other tissues. (3) Results: The NGS analysis revealed the novel germline heterozygous COL5A1 c.1369G&gt;T, p.(Glu457*) variant in the proband. Sanger chromatogram of the father’s blood specimen suggested the presence of a low-level mosaicism for the COL5A1 variant, which was confirmed by NGS and estimated to be 4.8% by ddPCR. The mosaicism was also confirmed by Sanger sequencing in the father’s saliva, hair bulbs and nails. (4) Conclusions: We described the second case of cEDS caused by paternal gonosomal mosaicism in COL5A1. Parental mosaicism could be an issue in cEDS and, therefore, considered for appropriate genetic counseling