Miracle-dz/UniFAR-FTUs huggingface dataset:
Playing the Game of Universal Adversarial Perturbations

We study the problem of learning classifiers robust to universal adversarial perturbations. While prior work approaches this problem via robust optimization, adversarial training, or input transformation, we instead phrase it as a two-player zero-sum game. In this new formulation, both players simultaneously play the same game, where one player chooses a classifier that minimizes a classification loss whilst the other player creates an adversarial perturbation that increases the same loss when applied to every sample in the training set. By observing that performing a classification (respectively creating adversarial samples) is the best response to the other player, we propose a novel extension of a game-theoretic algorithm, namely fictitious play, to the domain of training robust classifiers. Finally, we empirically show the robustness and versatility of our approach in two defence scenarios where universal attacks are performed on several image classification datasets -- CIFAR10, CIFAR100 and ImageNet.
Flyway structure in the circumpolar greater white‐fronted goose

Abstract Dispersal and migratory behavior are influential factors in determining how genetic diversity is distributed across the landscape. In migratory species, genetic structure can be promoted via several mechanisms including fidelity to distinct migratory routes. Particularly within North America, waterfowl management units have been delineated according to distinct longitudinal migratory flyways supported by banding data and other direct evidence. The greater white‐fronted goose (Anser albifrons) is a migratory waterfowl species with a largely circumpolar distribution consisting of up to six subspecies roughly corresponding to phenotypic variation. We examined the rangewide population genetic structure of greater white‐fronted geese using mtDNA control region sequence data and microsatellite loci from 23 locales across North America and Eurasia. We found significant differentiation in mtDNA between sampling locales with flyway delineation explaining a significant portion of the observed genetic variation (~12%). This is concordant with band recovery data which shows little interflyway or intercontinental movements. However, microsatellite loci revealed little genetic structure suggesting a panmictic population across most of the Arctic. As with many high‐latitude species, Beringia appears to have played a role in the diversification of this species. A common Beringian origin of North America and Asian populations and a recent divergence could at least partly explain the general lack of structure at nuclear markers. Further, our results do not provide strong support for the various taxonomic proposals for this species except for supporting the distinctness of two isolated breeding populations within Cook Inlet, Alaska (A. a. elgasi) and Greenland (A. a. flavirostris), consistent with their subspecies status.
S-palmitoylation Is Required for the Control of Growth Cone Morphology of DRG Neurons by CNP-Induced cGMP Signaling

Genetic investigations have demonstrated that a specific form of axonal branching - the bifurcation of afferents from dorsal root ganglia (DRG), cranial sensory ganglia (CSG) and mesencephalic trigeminal neurons (MTN) – is regulated by a cGMP-dependent signaling pathway. This cascade is composed of the ligand C-type natriuretic peptide (CNP), the receptor guanylyl cyclase Npr2, and the cGMP-dependent protein kinase Iα (cGKIα). In the absence of any one of these components, axons no longer bifurcate, instead they turn in either an ascending or a descending direction. To gain further mechanistic insights into the process of axon bifurcation we applied different cell culture approaches to decipher downstream activities of cGKI in somatosensory growth cones. We demonstrate that CNP induces an enlargement of DRG growth cones via cGKI which is considered as the priming step of axon bifurcation in the spinal cord. This growth cone remodeling was both blocked by pharmacological inhibitors of S-palmitoylation and potentiated by blocking de-palmitoylation. cGKI colocalizes with the palmitoylome and vesicular structures including the endoplasmic reticulum, early endosomes, lysosomes primarily in the central domain of the growth cone as well as with the Golgi apparatus at the level of the soma. Interestingly, an acyl-biotin-exchange chemistry-based screen indicated that 8pCPT-cGMP-induced signaling induces S-palmitoylation of a restricted pool of proteins in the DRG-derived cell line F11. Overall, our data indicate that CNP-induced cGMP signaling via cGKI affects growth cone morphology of somatosensory afferents. Moreover, it also suggests that S-palmitoylation might play a role in this process.
Inhibition of Ca2+‐activated chloride channel ANO1 suppresses ovarian cancer through inactivating PI3K/Akt signaling

Most common ovarian cancers are epithelial carcinoma in which the etiology for carcinogenesis remains elusive. ANO1/TMEM16A, a member of Ca2+‐activated Cl− channels (CaCCs), has been demonstrated to promote epithelium‐originated cancers and whether it plays a role in the pathogenesis of ovarian cancer is unknown. In our study we found that ANO1 proteins were overexpressed in human epithelial ovarian cancer cells and tissue samples. ANO1 protein upregulation was correlated with the clinical FIGO (International Federation of Gynecology and Obstetrics) staging and poor grade in ovarian cancer tissues. Interestingly, the upregulation of ANO1 gene expression was also detected in the peripheral blood mononuclear cells (PBMCs) from preoperative patients with ovarian tumors, and the down‐regulation of ANO1 in the PBMCs from postoperative patients. Silencing of ANO1 inhibited proliferation and invasion of ovarian cancer cells. Mechanistically, ANO1 knockdown attenuated phosphorylation of PI3K/Akt, and inhibition of PI3K/Akt signaling by specific inhibitor LY294002 resulted in suppression of ovarian cancer cells growth promoted by ANO1 expression. Furthermore, intratumoral injection of ANO1 siRNA suppressed subcutaneous xenograft tumor growth in nude mice implanted with ovarian cancer SKOV3 cells. Taken together, our findings demonstrate that ANO1 overexpression is involved in the pathogenesis of human epithelial ovarian cancer. Inhibition of ANO1 upregulation or inactivating PI3K/Akt signaling may have therapeutic potential for epithelial ovarian cancer, and the detection of ANO1 expression level in PBMCs from patients may also serve as a biomarker for diagnosis and prognosis of epithelial ovarian cancers.
Personal Virtual Traffic Light Systems

Traffic control management at intersections, a challenging and complex field of study, aims to attain a balance between safety and efficient traffic control. Nowadays, traffic control at intersections is typically done by traffic light systems which are not optimal and exhibit several drawbacks, e.g. poor efficiency and real-time adaptability. With the advent of Intelligent Transportation Systems (ITS), vehicles are being equipped with state-of-the-art technology, enabling cooperative decision-making which will certainly overwhelm the available traffic control systems. This solution strongly penalizes users without such capabilities, namely pedestrians, cyclists and other legacy vehicles. Therefore, in this work, a prototype based on an alternative technology to the standard vehicular communications, BLE, is presented. The proposed framework aims to integrate legacy and modern vehicular communication systems into a cohesive management system. In this framework, the movements of users at intersections are managed by a centralized controller which, through the use of networked retransmitters deployed at intersections, broadcasts alerts and virtual light signalization orders. Users receive the aforementioned information on their own smart devices, discarding the need for dedicated light signalization infrastructures. Field tests, carried-out with a real-world implementation, validate the correct operation of the proposed framework.
High levels of multiple paternity in a spermcast mating freshwater mussel

Abstract Multiple paternity is an important characteristic of the genetic mating system and common across a wide range of taxa. Multiple paternity can increase within‐population genotypic diversity, allowing selection to act on a wider spectre of genotypes, and potentially increasing effective population size. While the genetic mating system has been studied in many species with active mating behavior, little is known about multiple paternity in sessile species releasing gametes into the water. In freshwater mussels, males release sperm into the water, while eggs are retained and fertilized inside the female (spermcast mating). Mature parasitic glochidia are released into the water and attach to the gills of fish where they are encapsulated until settling in the bottom substrate. We used 15 microsatellite markers to detect multiple paternity in a wild population of the freshwater pearl mussel (Margaritifera margaritifera). We found multiple paternity in all clutches for which more than two offspring were genotyped, and numbers of sires were extremely high. Thirty‐two sires had contributed to the largest clutch (43 offspring sampled). This study provides the first evidence of multiple paternity in the freshwater pearl mussel, a species that has experienced dramatic declines across Europe. Previous studies on other species of freshwater mussels have detected much lower numbers of sires. Multiple paternity in freshwater pearl mussels may be central for maintaining genetic variability in small and fragmented populations and for their potential to recover after habitat restoration and may also be important in the evolutionary arms race with their fish host with a much shorter generation time.
In utero exposure to cigarette smoke and effects across generations: A conference of animals on asthma

The prevalence of asthma and chronic obstructive pulmonary disease (COPD) has risen markedly over the last decades and is reaching epidemic proportions. However, underlying molecular mechanisms are not fully understood, hampering the urgently needed development of approaches to prevent these diseases. It is well established from epidemiological studies that prenatal exposure to cigarette smoke is one of the main risk factors for aberrant lung function development or reduced fetal growth, but also for the development of asthma and possibly COPD later in life. Of note, recent evidence suggests that the disease risk can be transferred across generations, that is, from grandparents to their grandchildren. While initial studies in mouse models on in utero smoke exposure have provided important mechanistic insights, there are still knowledge gaps that need to be filled.
Solving Large Extensive-Form Games with Strategy Constraints

Extensive-form games are a common model for multiagent interactions with imperfect information. In two-player zerosum games, the typical solution concept is a Nash equilibrium over the unconstrained strategy set for each player. In many situations, however, we would like to constrain the set of possible strategies. For example, constraints are a natural way to model limited resources, risk mitigation, safety, consistency with past observations of behavior, or other secondary objectives for an agent. In small games, optimal strategies under linear constraints can be found by solving a linear program; however, state-of-the-art algorithms for solving large games cannot handle general constraints. In this work we introduce a generalized form of Counterfactual Regret Minimization that provably finds optimal strategies under any feasible set of convex constraints. We demonstrate the effectiveness of our algorithm for finding strategies that mitigate risk in security games, and for opponent modeling in poker games when given only partial observations of private information.
Arianna+: Scalable Human Activity Recognition by Reasoning with a Network of Ontologies

Aging population ratios are rising significantly. Meanwhile, smart home based health monitoring services are evolving rapidly to become a viable alternative to traditional healthcare solutions. Such services can augment qualitative analyses done by gerontologists with quantitative data. Hence, the recognition of Activities of Daily Living (ADL) has become an active domain of research in recent times. For a system to perform human activity recognition in a real-world environment, multiple requirements exist, such as scalability, robustness, ability to deal with uncertainty (e.g., missing sensor data), to operate with multi-occupants and to take into account their privacy and security. This paper attempts to address the requirements of scalability and robustness, by describing a reasoning mechanism based on modular spatial and/or temporal context models as a network of ontologies. The reasoning mechanism has been implemented in a smart home system referred to as Arianna+. The paper presents and discusses a use case, and experiments are performed on a simulated dataset, to showcase Arianna+'s modularity features, internal working, and computational performance. Results indicate scalability and robustness for human activity recognition processes.
Learning Recommender Systems from Multi-Behavior Data

Most existing recommender systems leverage user behavior data of one type only, such as the purchase behavior in E-commerce that is directly related to the business KPI (Key Performance Indicator) of conversion rate. Besides the key behavioral data, we argue that other forms of user behaviors also provide valuable signal, such as views, clicks, adding a product to shop carts and so on. They should be taken into account properly to provide quality recommendation for users. In this work, we contribute a new solution named NMTR (short for Neural Multi-Task Recommendation) for learning recommender systems from user multi-behavior data. We develop a neural network model to capture the complicated and multi-type interactions between users and items. In particular, our model accounts for the cascading relationship among different types of behaviors (e.g., a user must click on a product before purchasing it). To fully exploit the signal in the data of multiple types of behaviors, we perform a joint optimization based on the multi-task learning framework, where the optimization on a behavior is treated as a task. Extensive experiments on two real-world datasets demonstrate that NMTR significantly outperforms state-of-the-art recommender systems that are designed to learn from both single-behavior data and multi-behavior data. Further analysis shows that modeling multiple behaviors is particularly useful for providing recommendation for sparse users that have very few interactions.
Impact of fatigue and insufficient sleep on physician and patient outcomes: a systematic review

Objectives For physicians in independent practice, we synthesised evidence on the (1) impacts of insufficient sleep and fatigue on health and performance, and patient safety and (2) effectiveness of interventions targeting insufficient sleep and fatigue. Design We systematically reviewed online literature. After piloting, one reviewer selected studies by title and abstract; full texts were then reviewed in duplicate. One reviewer extracted data; another verified a random 10% sample. Two reviewers assessed risk of bias. We pooled findings via meta-analysis when appropriate or narratively. Data sources We searched Medline, Embase, PsycINFO, CINAHL and PubMed for published studies in April 2016; Medline was updated in November 2017. We searched Embase for conference proceedings, and hand-searched meeting abstracts, association and foundation websites. Eligibility criteria for selecting studies English or French language primary research studies published from 2000 to 2017 examining the effect of fatigue-related or sleep-related exposures or interventions on any outcome among physicians in independent practice and their patients. Results Of 16 154 records identified, we included 47 quantitative studies of variable quality. 28 studies showed associations between fatigue or insufficient sleep and physician health and well-being outcomes. 21 studies showed no association with surgical performance, and mixed findings for psychomotor performance, work performance and medical errors. We pooled data from six cohort studies for patient outcomes. For sleep deprived versus non-sleep deprived surgeons, we found no difference in patient mortality (n=60 436, relative risk (RR) 0.98, 95% CI 0.84 to 1.15, I2=0% (p=0.87)) nor postoperative complications (n=60 201, RR 0.99, 95% CI 0.95 to 1.03, I2=0% (p=0.45)). The findings for intraoperative complications and length of stay were considerably heterogeneous. Conclusions Fatigue and insufficient sleep may be associated with negative physician health outcomes. Current evidence is inadequate to inform practice recommendations.
Changes in Types of Dietary Fats Influence Long-term Weight Change in US Women and Men.

Background The relation between dietary fat intake and body weight remains controversial. Few studies have examined long-term changes in types of dietary fat and weight change in longitudinal studies. Objective The objective of this study was to examine associations between intake of different types of fat and long-term weight change in US women and men. Methods The association between changes in consumption of varying types of fat and weight change was examined every 4 y through the use of multivariate models adjusted for age, baseline body mass index, and change in percentage energy from protein, intake of cereal fiber, fruits, and vegetables, alcohol use, and other lifestyle covariates in 3 prospective US cohorts, including 121,335 men and women free of diabetes, cardiovascular disease, cancer, or obesity over a 20- to 24-y follow-up. Dietary intakes and body weight were assessed via validated questionnaires. Cohort-specific results were pooled with the use of a random-effect meta-analysis. Results Compared with equivalent changes in carbohydrate intake, a 5% increase in energy from saturated fatty acid (SFA) and a 1% increase in energy from trans-fat were associated with 0.61 kg (95% CI: 0.54, 0.68 kg) and 0.69 kg (95% CI: 0.56, 0.84 kg) greater weight gain per 4-y period, respectively. A 5% increase in energy from polyunsaturated fatty acid (PUFA) was associated with less weight gain (-0.55 kg; 95% CI: -0.81, -0.29 kg). Increased intake of monounsaturated fatty acid (MUFA) from animal sources by 1% was associated with weight gain of 0.29 kg (95% CI: 0.25, 0.33 kg), whereas MUFA from plant sources was not associated with weight gain. Conclusions Different dietary fats have divergent associations with long-term weight change in US men and women. Replacing saturated and trans-fats with unsaturated fats, especially PUFAs, contributes to the prevention of age-related weight gain. These trials were registered at clinicaltrials.gov as NCT00005152 and NCT00005182.
Individual Development and Adaptation (IDA): A Life-Span Longitudinal Program Suited for Person-Oriented Research

In this article, we give a presentation of the longitudinal research program Individual Development and Adaptation (IDA) that can be helpful as a template for researchers considering to launch their own longitudinal studies, and that opens the door to IDA for researchers looking for suitable data to be analyzed within their own project or in collaboration with IDA. We also introduce the holistic-interactionistic theoretical framework of IDA and the associated person-oriented approach – an approach that is especially suited for analyzing the rich IDA data set with its broad coverage of different areas of adjustment and related factors. The paper provides an overview of the essential features of the IDA database, as well as of ongoing and planned IDA research.
Molecular regulation of miR-378 on the development of mouse follicle and the maturation of oocyte in vivo

ABSTRACT MicroRNAs (miRNAs) are small, endogenous, non-coding RNAs which can bind to completely or partially complementary sequences in the 3’UTR of target mRNAs, therefore degrading the mRNA or repressing translation. We previously reported that miR-378 played a role in estradiol production via suppression of aromatase translation in porcine granulosa cells and could affect oocyte maturation in vitro by inhibiting cumulus cell expansion. However, the role of miR-378 on ovary development in vivo is unknown. The current study aimed to uncover the molecular mechanism of miR-378 in regulating mouse follicular development via micro-injection of CMV-miR-378 lentivirus into the bursa of mouse ovary. The results showed that CMV-miR-378 lentivirus transduction in the mouse ovaries resulted in reduced ovary size, extended oestrous cycle (6-7 d in miR-378 overexpression group and 4–5 dyas in GFP control group) due to continuous oestrum, decreased percentage of oocytes in vitro maturation rate (IVM 60.8% vs. 89.4% in GFP control), increased apoptosis rate (Bax/Bcl2 in mRNA and protein level), decreased expression of genes associated with gap junction, such as connexin 43 (Cx-43) and connexin (Cx-37) and decreased expression of genes associated with follicular development, such as BMP15 and GDF9. Moreover, the number of pups/litter was consistently lower in the miR-378 group in each batch of the paired breeding. Our data suggest that miR-378 alters gene expression in cumulus cells and indirectly influences oocyte maturation competency, possibly via inhibition of oocyte-cumulus interaction or induction of apoptosis.
Interventions to improve diagnostic decision making: A systematic review and meta-analysis on reflective strategies

Abstract Aims: To identify, appraise and describe studies of cognitive interventions to improve diagnostic decision making (DDM) amongst medical professionals, assess their effectiveness and identify methodological limitations in existing studies. Methods: We systematically searched for studies (publication date 2000–2016) in multiple databases including Cochrane Controlled Trials, EMBASE, ERIC, Medline, PubMed and PsycINFO, and used additional strategies such as hand searching and snowballing. Included studies evaluated cognitive interventions to enhance DDM amongst medical professionals, using defined outcomes such as diagnostic accuracy. A meta-analysis assessed the impact of “reflection”. Results: Forty-four studies out of 10,114 screened citations, involving 4380 medical professionals, were included. Studies evaluated reasoning workshops/curricula, de-biasing workshops, checklists, reflection, feedback, and instructions to induce analytical thinking. Guided reflection was demonstrated to improve DDM [effect size 0.38(95%CI 0.23–0.52), p < 0.001]. Immediate feedback and modeling reflection using contrasting examples also appeared to improve diagnostic accuracy, however underlying methodological issues prevented a quantitative assessment of any strategies other than reflection. Conclusions: Educational interventions incorporating practising deliberate reflection on a formulated diagnosis, modeled reflection on contrasting examples and immediate feedback are promising strategies for improving DDM. The effectiveness of other strategies is unknown, with more methodological refinements required in future research.
Validation of a European Cross‐Cultural Neuropsychological Test Battery (CNTB) for evaluation of dementia

The aims of this study were to establish the diagnostic accuracy of the European Cross‐Cultural Neuropsychological Test Battery (CNTB) for dementia in different ethnic populations in Western Europe, to examine its ability to differentiate cognitive impairment profiles for dementia subtypes, and to assess the impact of demographic variables on diagnostic properties.