Tragic Victims of Mania a Potu (“Madness from Drink”): A Study of Literary Nineteenth-Century Female Drunkards

Temperance literature, though widely popular in America and Britain between 1830–80, lost its allure in the decades that followed. In spite of its didactic and moralistic nature, the public eagerly consumed temperance novels, thus reciprocating contemporaneous writers’ efforts to promote social ideals and mend social ills. The main aim of this paper is to redress the critical neglect that the temperance prose written by women about women has endured by looking at three literary works—two novellas and one confessional novelette—written by mid-nineteenth-century American female writers. These works serve as a prism through which the authors present generally “tabooed” afflictions such as inebriation among high-class women and society’s role in perpetuating such behaviors. The essay examines the conflicting forces underlying such representations and offers an inquiry into the restrictive and hostile social climate in mid-nineteenth-century America and the lack of medical attention given to alcohol addicts as the possible causes that might have prompted women’s dangerous behaviors, including inebriation. This paper also demonstrates the cautious approach that nineteenth-century female writers had to take when dealing with prevalent social ills, such as bigotry, hypocrisy and disdain directed at female drunkards. It shows how these writers, often sneered at or belittled by critics and editors, had to maneuver very carefully between the contending forces of openly critiquing social mores, on the one hand, and not being censored, on the other.

Results of Behavioral Evaluations Predict Length of Stay for Shelter Dogs

Most animal shelters conduct behavioral evaluations before making dogs available for adoption. However, little information exists on whether behaviors displayed during these assessments predict a dog’s length of stay at the shelter. We reviewed nearly 5 years of records from 975 dogs released for adoption at a New York shelter to see whether behaviors shown during their evaluation predicted length of stay. For most tests and subtests, the prevalence of concerning and especially dangerous behaviors was low. Nevertheless, dogs’ scores on some tests or subtests—food guarding and meeting another dog—predicted length of stay at the shelter. Dogs evaluated as showing dangerous behavior had longer lengths of stay than dogs evaluated as showing either concerning behavior or no concerning behavior; the latter two groups did not differ from one another in length of stay. The most likely explanation for the relationships found between behavior during the evaluation and length of stay at the shelter is that dogs with challenging behaviors had smaller pools of potential adopters. Understanding the relationships between performance on behavioral evaluations and length of stay may inform shelter management of canine populations and also help identify dogs requiring special adoption efforts to avoid long shelter stays.

UAV Behavior-Intention Estimation Method Based on 4-D Flight-Trajectory Prediction

Aiming at the limitation of the traditional four-dimensional (4-D) trajectory-prediction model of unmanned aerial vehicles (UAV), a 4-D trajectory combined prediction model based on a genetic algorithm is proposed. Based on historical flight data and the UAV motion equation, the model is weighted dynamically by a genetic algorithm, which can predict UAV trajectory and the time of entering the protection zone instantly and accurately. Then, according to the number of areas where the tangent line of the current trajectory point intersects with the collision area, alarm area, alert area, and the time of entering the protection zone, the UAV’s behavior intention can be estimated. The simulation experiments verify the dangerous behaviors of UAV under different danger levels, which provides reference for the subsequent maneuvering strategies.

Nonlinear Analysis and Bifurcation Characteristics of Whirl Flutter in Unmanned Aerial Systems

Aerial drones have improved significantly over the recent decades with stronger and smaller motors, more powerful propellers, and overall optimization of systems. These improvements have consequently increased top speeds and improved a variety of performance aspects, along with introducing new structural challenges, such as whirl flutter. Whirl flutter is an aeroelastic instability that can be affected by structural or aerodynamic nonlinearities. This instability may affect the prediction of potentially dangerous behaviors. In this work, a nonlinear reduced-order model for a nacelle-rotor system, considering quasi-steady aerodynamics, is implemented. First, a parametric study for the linear system is performed to determine the main aerodynamic and structural characteristics that affect the onset of instability. Multiple polynomial nonlinearities in the two degrees of freedom nacelle-rotor model are tested to simulate possible structural nonlinear effects including symmetric cubic hardening nonlinearities for the pitch and yaw degrees of freedom; purely yaw nonlinearity; purely pitch nonlinearity; and a combination of quadratic, cubic, and fifth-order nonlinearities for both degrees of freedom. Results show that the presence of hardening structural nonlinearities introduces limit cycle oscillations to the system in the post-flutter regime. Moreover, it is demonstrated that the inclusion of quadratic nonlinearity introduces asymmetric oscillations and subcritical behavior, where large and potentially dangerous deformations can be reached before the predicted linear flutter speed.

Infections of scleroderma digital ulcers: a single center cohort retrospective study

BACKGROUNDS: Systemic Sclerosis (SSc) is a complex autoimmune and up to fifty percent of patients develop digital ulcers. AIMS: Understand how much infections influence scleroderma digital ulcers’ healing. METHODS: We revised fifty consecutive patients with SSc-related DUs who referred to our Scleroderma Unit. Thirty-five of them who showed clear signs of DUs infection underwent to cutaneous swab and microbiological data collection. We performed 87 cutaneous swabs overall. RESULTS: DUs were recurrent in 58% of the patients and multiple in 60% of patients. Fourty-four swabs (53%) were positive for Staphylococcus Aureus (13% Methicillin-Resistant), 9 were positive for Pseudomonas Aeruginosa (Pseudomonas A.) (10%), and then the others less frequently isolated. Twenty-fifth percent of patients needed hospitalization. CONCLUSIONS: Our data support a patient-tailored approached to DUs, particularly those infected. Self-hygiene and asepsis during dressing procedures are mandatory. Patient must be trained to avoid dangerous behaviors and reduce the risk of infection.

The cult structure of the American anti

The online-based group known as antis, which originated around 2016 in the United States, exhibit morality-based, cult-like behavior and perpetuate hate speech and censorship in online spaces. Anti ideology has encouraged harmful, obsessive, and dangerous behaviors among its members, specifically minors and young adults. An analysis of the antifandom movement through political, sociological, and behavioral lenses reveals its damaging effects on women, people of color, minors, and members of the LGBTQIA+ community.

Technology-Mediated Dangerous Behaviors as Foraging for Social-Hedonic Rewards: The Role of Implied Inequality

Technology-mediated dangerous behaviors (TMDBs), such as posting selfies while driving or posting private information, are prevalent and potentially require interventions. Knowledge about the drivers of these, and specifically the role of information in stimulating such behaviors, is limited. To address this gap, this paper turns to foraging and risk-sensitivity theories. These theories suggest that animals engage in more dangerous behaviors when their perceived need for calories is high. Similarly, humans increase financial risk-taking when they perceive dissatisfaction with what they have. Importantly, inequality information can increase such perceptions and change people’s risk-taking propensity. Adapting these ideas, the paper postulates that TMDBs resemble food-seeking in animals in that they are goal oriented, can be dangerous, and yield unknown (probabilistic) rewards. Therefore, TMDBs are explained using foraging and risk-sensitivity theory angles. Focusing on social media users (Studies 1-4; four experiments; total n = 2,504), I argue that (1) it is reasonable to view users as foraging the “fields of social media” for social-hedonic rewards, (2) it is possible to alter their risk appetite and TMDBs through inequality information and upward comparison mechanisms, (3) this process can be mediated not only through cognitions, but also emotions, and (4) perceived scarcity of rewards and social comparison orientation affect this process. With Study 5, the paper extends the core aspects of this theoretical perspective to the U.S. state level and argues that objective financial inequality can explain differences between states in terms of TMDBs such as texting while driving and relative interest in TMDBs such as prank videos. The findings largely support these assertions. They illuminate the role of information, notably inequality, in driving TMDBs, extend prior research focused on basic needs (e.g., physiological needs in the case of food intake decisions) to an evaluation of higher-order human needs (e.g., needs for belongingness, esteem, and self-actualization) catered to by nonphysiological, social-hedonic rewards, and point to important mechanisms that translate inequality into TMDBs.

Ambient Intelligence Based on IoT for Assisting People with Alzheimer’s Disease Through Context Histories

New Internet of Things (IoT) applications are enabling the development of projects that help with monitoring people with different diseases in their daily lives. Alzheimer’s is a disease that affects neurological functions and needs support to maintain maximum independence and security of patients during this stage of life, as the cure and reversal of symptoms have not yet been discovered. The IoT-based monitoring system provides the caregivers’ support in monitoring people with Alzheimer’s disease (AD). This paper presents an ontology-based computational model that receives physiological data from external IoT applications, allowing identification of potentially dangerous behaviors for patients with AD. The main scientific contribution of this work is the specification of a model focusing on Alzheimer’s disease using the analysis of context histories and context prediction, which, considering the state of the art, is the only one that uses analysis of context histories to perform predictions. In this research, we also propose a simulator to generate activities of the daily life of patients, allowing the creation of data sets. These data sets were used to evaluate the contributions of the model and were generated according to the standardization of the ontology. The simulator generated 1026 scenarios applied to guide the predictions, which achieved average accurary of 97.44%. The experiments also allowed the learning of 20 relevant lessons on technological, medical, and methodological aspects that are recorded in this article.

A novel Siamese Attention Network for visual object tracking of autonomous vehicles

In the environment perception stage of autonomous driving, vehicles need to track its surrounding objects quickly and accurately to avoid dangerous behaviors. Therefore, visual object tracking has important practical application value in autonomous driving system. However, the performance of most hierarchical convolutional feature trackers are limited by ignoring the complex environment of autonomous driving. In this paper, a novel Siamese Attention Network to explore the rich spatial and channel information of objects was proposed. Because of the lack of important information between the channel and the spatial position, the tracking performance is reduced by the challenges of illumination change and deformation. The spatial attention block and channel attention block focus on the importance of different spatial positions and channels, respectively. The effective fusion of the two makes our tracker achieve the state-of-the art performance of 0.300 in the EAO criterion of 2017, which exceeds the baseline by 5.7%.

Saudi Youth and Risky Behaviours

The study examined the problem of risky behavior, its prevalence among Saudi youth, and the degree of their awareness of it. These behaviors were determined on the basis of academic scientific studies and reports of the relevant international organizations. They consisted of: dangerous driving, smoking, drug addiction, violence, Unsafe healthy behavior, food, and physical activity. The researchers adopted the quantitative and qualitative approaches using the electronic questionnaire and the SPSS 21 statistical system at the quantitative level, and the Focus Groups tool at the qualitative level, on a sample of 625 individuals in Hail. The study concluded that Saudi youth are exposed to risks like other youth in the world. The dangerous behavior that stares at them with one another and leads to each other are interconnected, and they arise in the school environment and grow in peer groups, and they start with bullying and pass to smoking so that the teenager becomes more ready for more dangerous behaviors such as drugs, violence and various deviations . The study confirmed that exposure to danger, risk and challenge is one of the most prominent dimensions of the transitional phase from childhood to adulthood, and that the multiplicity of modes of upbringing and the many temptations make youth an easy target in light of the decline in family social control and the abundance of leisure time. The researchers recommended the necessity to continuously monitor the situation of young people and adopt integrated education, education and awareness strategies with the participation of all concerned parties.