Unrestricted Environment Research Articles

Droperidol administration among emergency department patients with abdominal pain, nausea, and vomiting

Study objectiveThe primary objective of this study was to examine the common usage patterns of droperidol in the relatively unrestricted environment of an urban, academic medical center. We focused specifically on the most common use of droperidol in our department: patients with a chief complaint of abdominal pain, nausea, and/or vomiting. MethodsFor this retrospective, observational, single-center study, we extracted records of all administrations of droperidol from August 2019 to August 2020. Patients with a chief complaint of abdominal pain, nausea, or vomiting, or any combination thereof, were included in data analysis. ResultsBetween April 2019 to August 2020, 830 discrete patient visits involving droperidol administration were identified, comprising 706 patients. The average age was 39 years old with a range of 15 to 80. Seven patients (0.08%) were younger than 18, and 35 (4%) were older than 65. Five hundred sixty-five patients (68%) were female. Droperidol doses ranged from 0.625 mg to 5 mg intravenous (IV), with a median dose of 0.625 mg (interquartile range 0.625–1.25 mg), with 590 patients (71%) receiving a dose of 0.625 mg. Only 19 patients (2.3%) had a documented adverse event. Seven had akathisia or restlessness, 7 had anxiety or agitation, 3 had dystonia or stiffness, 1 had fatigue, and 1 had dizziness. For the entire cohort, there were no cardiac dysrhythmias, syncope, seizures, other major adverse events, or fatalities recorded. ConclusionAt one institution, droperidol is being used commonly for the chief complaints of abdominal pain, nausea, and/or vomiting. The preferred dosing is nearly universally below the 2.5 mg IV dose for which the FDA warning applies. Similar to previous studies, identification of adverse events was rare, and no major adverse outcomes such as dysrhythmia or death were identified.

EMOTIONAL INTELLIGENCE AND ACHIEVEMENT MOTIVATION: AN INVESTIGATIONON HIGHER SECONDARY SCHOOL STUDENTS IN PASCHIM MEDINIPUR DISTRICT

Background:According to Behnke (2009), emotional intelligence directly influences motivation.The present study aims to know the significant difference in emotional intelligence and achievement motivation concerning their gender, grade, and stream of education and the significant relationship between emotional intelligence and achievement motivation among higher secondary school students in Paschim Medinipur district. Methods and Materials:This is a cross sectional survey study. 200 (100 boys and 100 girls) higher secondary school students (age mean 17.38 and SD 0.99)from two blocks i.e., Sabang and Pingla in Paschim Medinipur District randomly selected. One information sheet and two scales are used for data collection. The emotional Intelligence Scalewas developed by A. K. Singh and Shruti Narain, and culturally adopted by Ghorai and Mohakud (2016), and the achievement motivation Scale was developed by Prof. Pratibha Deo and Dr. Asha Mohan, and the Bengali version was adopted by Pakira and Mohakud (2017). After the test of Data Normality, Data was analysed through the SPSS 20 version with descriptive statistics viz. Mean and Standard Deviation and inferential statistics testing hypotheses applied t-test and Pearson correlation (r). Results:Results Show that emotional intelligence is not significantly differentamong higher secondary school students concerning their gender, grade, and stream of education. There is no significant difference exists in the achievement motivation concerning their gender and grade buta significant difference exists in the achievement motivation concerning their stream of education among higher secondary school students in Paschim Medinipur District.A positively moderate and significant correlation exists between emotional intelligence and achievement motivationamong higher secondary school students in Paschim Medinipur district. Conclusion:Higher secondary school students should be able to freely express their emotions, opinions, ask questions, and explore their inner needs in a welcoming and unrestricted environment both at home and at school. This will help them become more adept at emotional intelligence and achievement motivation as students.

Sclera biometrics in restricted and unrestricted environment with cross dataset evaluation

Research on ocular biometric systems in unrestricted environment has grown steadily over the last decade. Though sclera recognition is widely investigated as an alternative or supplementary ocular biometric modality, most of the work has been done in restricted environment. So there are several unanswered questions like, how a model trained in a restricted environment performs in an unrestricted scenario, or whether the performance improves if it is trained in a combined environment. In this work, we aim to study sclera biometrics in multiple environments and answer these questions. In the process, we have worked on all components in the sclera biometric pipeline, viz., sclera segmentation, vessel extraction, gaze detection and sclera recognition. We have trained and tested the deep models proposed for the tasks with high-quality datasets prepared in restricted environment as well as mobile datasets prepared in unrestricted environment. We have also trained the models with images from two or more datasets. This helps us to ascertain how the images captured in diverse environments can be used collectively for the training purpose. We have used two high-quality datasets SBVPI, MASD and two mobile datasets MSD, MASDUM for our work. MASDUM is the proposed mobile dataset prepared in unrestricted environment. It is designed specifically with research of sclera biometrics in mind. It contains a total of 1055 eye images along with 1055 sclera-segmented and 68 sclera-vessel-mark-up images. Since there is a severe lack of vessel-annotated datasets in the field, MASDUM dataset hopefully caters the need of researchers. State-of-the-art results are achieved for sclera segmentation on the datasets SBVPI, MASD, MSD and MASDUM with F1-scores of 96.3, 97.3, 87.9 and 91.2 respectively. State-of-the-art results are also achieved for sclera recognition with respective EERs of 0.132, 0.079, 0.086 and 0.080. We also present in-depth analysis on the novel idea of Dual-output variant of recognition model DeepR. This variant directly produces the matching score between two vessel-extracted binary images and it shows better results by largely reducing FAR.

A deep map transfer learning method for face recognition in an unrestricted smart city environment

Background and objectiveFace images often change in posture, Angle, expression, makeup, aging, lighting, and other aspects. The performance of many models with high accuracy in restricted scenes decreases sharply in unrestricted scenes. Therefore, the study of face recognition in unrestricted scenes is of great significance. In this paper, we proposed a face recognition algorithm based on depth map transfer learning to effectively recognize face images taken in unrestricted environment. MethodsFirstly, the deep network encoding and decoding structure based on dense feature fusion is used to extract depth information from face images. Secondly, depth information for migration learning is fused to improve the feature dimension of small sample data, thereby improving the problem of insufficient feature extraction training due to a small number of samples. Finally, in order to improve the classifier recognition performance in small sample machine learning, central loss is introduced into the traditional Softmax loss to improve the punishment supervision ability of the classification loss function.

IDEOLOGY – ARCHITECTURE RELATIONSHIP: NAZI ARCHITECTURE

Hitler’s Germany witnessed the most influential political power activities in world history before and during the Second World War. Germany’s collapse both politically and economically in the early 1930s enabled Hitler to take action. This structure, which relied on the new political stance behind it, has ensured its legitimacy and ideology with propaganda works. Nazis used the social power of architecture as a tool to support the new order that they were establishing. Aim: This study aims to investigate the effects on the forming and shaping of the city and the designed buildings, planned according to the Nazi ideology fundamentals. Method: In the article, concepts of ideology and propaganda are discussed. The propaganda methods used during the Hitler period are briefly explained. Through the relationship between ideology and architecture, the reflections of ideology on Nazi architecture have been determined. By evaluating the relationship of Hitler's architectural preferences with ideology, it was determined how it was treated as a propaganda tool. Findings: It was determined that the effects of Hitler's ideology on the shaping of Nazi architecture had an independent style of national socialism and classicism established on European typology and morphology. The relationship between the monumental architecture utilized in Nazi Germany and the styles in the history of architecture was detected. Although it is impossible to classify Hitler's architectural preferences under a single title and to say that the Third Reich has an official architectural style, it was determined that Nazi Architecture, founded on the neoclassical basis, was developed and changed around this framework. Conclusion: For architecture to thrive, it needs an innovative, unrestricted and creative environment rather than a repressive one. Politics is expected to be supportive rather than conflicting with architecture. Instead of imitation, supporting historical searches with creativity will develop architecture.

Race estimation with deep networks

Identifying race, which is a major physical feature in humans, is still a challenging task owing much to the lack of a concrete definition of race and the diversity of population across the globe. In this paper, we try to address the problem of race identification of four broad racial groups namely Caucasian, African, Asian and Indian. The newly developed BUPT Equalised Face dataset bearing about 1.3 M images in unrestricted environment is used to train our deep convolution network (R-Net) which achieves a state-of-the-art accuracy of 97%. To test the validity of this model it is evaluated on other datasets namely UTK and CFD. R-Net is also compared with fine-tuned VGG16 model for race estimation. Experimental results prove the robustness of this model for use in unconstrained environments. And finally, Gradient-weighted Class Activation Mapping (Grad-CAM) is applied to get a visual explanation of the deep learning model.

Psychiatrists' agency and their distance from the authoritarian state in post-World War II Taiwan.

By the end of World War II and in the shadow of the Cold War, many Asia-Pacific nations developed their psychiatric disciplines and strengthened their mental health care provision. This article examines the activities of the first generation of psychiatrists in Taiwan during the postwar period, focusing on their self-fashioning during the transition of a medical discipline. At this time, psychiatry was imagined by the state and by professionals as a science serving different clinical and political objectives. Psychiatrists, however, enjoyed a relatively unrestricted environment that allowed them to gradually form a professional identity. At the height of the Cold War, the state attempted to use psychiatry for political ends. Because of its initially malleable nature and undeveloped content, psychiatry could be employed by various authorities for diverse purposes, including patient care, scientific inquiry, psychological warfare, and even political probes to obtain crucial information. Nevertheless, psychiatrists sought to create spaces where they could develop their professional autonomy and prevent exploitation amid complicated political polemics. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Recognition of Pashto Handwritten Characters Based on Deep Learning.

Handwritten character recognition is increasingly important in a variety of automation fields, for example, authentication of bank signatures, identification of ZIP codes on letter addresses, and forensic evidence. Despite improved object recognition technologies, Pashto’s hand-written character recognition (PHCR) remains largely unsolved due to the presence of many enigmatic hand-written characters, enormously cursive Pashto characters, and lack of research attention. We propose a convolutional neural network (CNN) model for recognition of Pashto hand-written characters for the first time in an unrestricted environment. Firstly, a novel Pashto handwritten character data set, “Poha”, for 44 characters is constructed. For preprocessing, deep fusion image processing techniques and noise reduction for text optimization are applied. A CNN model optimized in the number of convolutional layers and their parameters outperformed common deep models in terms of accuracy. Moreover, a set of benchmark popular CNN models applied to Poha is evaluated and compared with the proposed model. The obtained experimental results show that the proposed model is superior to other models with test accuracy of 99.64 percent for PHCR. The results indicate that our model may be a strong candidate for handwritten character recognition and automated PHCR applications.

Hate begets Hate

With the ongoing debate on 'freedom of speech' vs. 'hate speech,' there is an urgent need to carefully understand the consequences of the inevitable culmination of the two, i.e., 'freedom of hate speech' over time. An ideal scenario to understand this would be to observe the effects of hate speech in an (almost) unrestricted environment. Hence, we perform the first temporal analysis of hate speech on Gab.com, a social media site with very loose moderation policy. We first generate temporal snapshots of Gab from millions of posts and users. Using these temporal snapshots, we compute an activity vector based on DeGroot model to identify hateful users. The amount of hate speech in Gab is steadily increasing and the new users are becoming hateful at an increased and faster rate. Further, our analysis analysis reveals that the hate users are occupying the prominent positions in the Gab network. Also, the language used by the community as a whole seem to correlate more with that of the hateful users as compared to the non-hateful ones. We discuss how, many crucial design questions in CSCW open up from our work.

Positioning and determining pupils being open and closed and its role in accident reduction

Despite wide spread advances in the car manufacturing industries around the world, the death toll from car accidents is worrying. This concern is heightened when reports of a road accident website reports that the main reason in 25% of road accidents in particular and 60% to road accidents resulting in death or injury. Therefore, there has been a great deal of researches and functions for the automatic and machine detection of drowsiness that of them have reached the production stage. The present study is a method for positioning the pupil of the eye, determining the opening and closing of the pupil in real time and in unlimited environments, using the color feature in the first step, in Ybcbr color space and with the help of Gaussian function and Euclidean distance detection and then the area of the eye is positioned using the Viola jones algorithm. Finally, in order to locate the pupil and detect its openness, we have used two parallel Kalman filters. If the pupils are closed, they follow the Harris Eye Detection algorithm to identify the drowsiness of the driver and use this system to minimize the deaths caused by fatigue (tiredness) while driving. Detection is performed more precisely in the case of face rotation, different lighting conditions, and the eyes being closed or missing one of the eyes, the presence of glasses, beards, makeup, hijab, or obstruction of the eyes. The low computational complexity and maximum stability, real-time and unrestricted environment are other advantages of this method, all because the filters operate in parallel and do not even require high-resolution images.

New technical approach to the diabetes therapy.

Optimal glycemic control remains challenging in individuals with type 1 diabetes. With the comprehensive clinical evidence on safety and efficiency, the adoption of continuous glucose monitoring (CGM), insulin pumps, and control algorithms merging the two into closed-loop systems is rapidly increasing. Particularly the CGM and intermittently scanned CGM improved diabetes management outcomes in large populations. A meaningful translation from clinical trials in highly controlled settings to numerous evaluations of closed-loop technology in the unrestricted home environment ended with its commercialization and use in routine clinical practice. Although it is still not a cure, the closed-loop currently seems to be the most promising advancement in the treatment of diabetes, with promising results also reported from routine clinical practice in children and adults with type 1 diabetes. We summarize different aspects of a technological approach to diabetes care, list currently available devices and systems in the pipeline, and the key supporting clinical evidence for their use. We consider human factors associated with technology use and the importance of health economics to support implementation and reimbursement.

Evaluating Mental Load During Realistic Driving Simulations by Means of Round the Ear Electrodes.

Film based round the ear electrodes (cEEGrids) provide both, the accessibility of unobtrusive mobile EEG as well as a rapid EEG application in stationary settings when extended measurements are not possible. In a large-scale evaluation of driving abilities of older adults (N > 350) in a realistic driving simulation, we evaluated to what extent mental demands can be measured using cEEGrids in a completely unrestricted environment. For a first frequency-based analysis, the driving scenario was subdivided into different street segments with respect to their task loads (low, medium, high) that was a priori rated by an expert. Theta activity increased with task load but no change in Alpha power was found. Effects gained clarity after removing pink noise effects, that were potentially high in this data set due to motion artifacts. Theta fraction increased with task load and Alpha fraction decreased. We mapped this effect to specific street segments by applying a track-frequency analysis. Whilst participants drove with constant speed and without high steering wheel activity, Alpha was high and theta low. The reverse was the case in sections that required either high activity or increased attentional allocation to the driving context. When calculating mental demands for different street segments based on EEG, this measure is highly significant correlated with the experts’ rating of task load. Deviances can be explained by specific features within the segments. Thus, modulations in spectral power of the EEG were validly reflected in the cEEGrids data. All findings were in line with the prominent literature in the field. The results clearly demonstrate the usability of this low-density EEG method for application in real-world settings where an increase in ecological validity might outweigh the loss of certain aspects of internal validity.

Context-Aware Implicit Authentication of Smartphone Users Based on Multi-Sensor Behavior

Implicit authentication is a new research direction to enhance the privacy protection of smartphones. However, implicit authentication has low robustness due to its vulnerability to environment. Motivated by this, this paper proposes a context-aware implicit authentication, which is a scheme to improve the robustness of authentication by introducing context awareness module. In the scheme, multi-sensor data (including accelerometer, gyroscope, magnetometer, timestamp, pressure, touch size) is first captured in a fine-grained manner to characterize one's touch action. Then, based on various sensors data, gesture features and touch features are extracted by employing both statistical method and distance measurement method. Particularly, one's body posture when touch action happens can be used as context. In each context, we present a weighted sum fusion rule to fuse the results of different features obtained by One-Class SVM (OC-SVM). We have collected 10000+ sensor data from 87 participants for experimental evaluation. The results show that the authentication in an unrestricted environment can achieve a best equal error rate (EER) of 0.0071%, which is more than one percent lower than the non-context-aware authentication. The proposed method can effectively improve the reliability and practicability of implicit authentication.

Flame height of axisymmetric gaseous fuel jets restricted by parallel sidewalls: Experiments and theoretical analysis

This study reports experimental results and correlations for axisymmetric gaseous fuel jets restricted by parallel sidewalls at various separation distances. Although many investigations have been conducted to elucidate the flame height evolution of diffusion flames in an unrestricted environment; the restriction effect of sidewalls on diffusion flames, which occasionally occurs in accidental leakages of city natural gas pipelines, has received little attention. The underlying interaction dynamics of axisymmetric gaseous fuel jets with two parallel sidewalls at various separation distances has not been fully elucidated. In this work, a series of experiments on this issue were carried out with 3-, 6- and 10-mm nozzles. The sidewall separation distances were varied from 10 to 50cm with a corresponding free condition. A series of new results and their interpretation are presented in this work. The results show that the flame height changes little when the sidewall separation distance reduces from +∞ to a critical value (Scri). Further reductions on the sidewall separation distance from Scri disturbed the evolution process of uprising vortexes and hindered air entrainment, leading to significant changes to the jet-flame shape by enlarging the flame height. The maximum flame heights had a linear relation with the critical separation distance of the sidewalls at the critical conditions, being consistent with the scaling analysis of the flow field. The dimensionless critical separation distance was found to be well correlated with the dimensionless heat release rate, Q̇D∗, with a 2/5 power law. A global model, characterizing the variation of the flame height with the dimensionless heat release rate, was proposed, showing good agreement with the experimental results. The results and the expressions obtained in this study contribute to a better understanding of jet fires, allowing a better prediction of flame height, relevant to the design of gas fuel storage systems and transportation systems in the city.

Characterization of the binding of shikonin to human immunoglobulin using scanning electron microscope, molecular modeling and multi-spectroscopic methods

Shikonin, one of the active components isolated from the root of Arnebia euchroma (Royle) Johnst, have anti-tumor, anti-bacterial and anti-inflammatory activities and has been used clinically in phlebitis and vascular purpura. In the present work, the interaction of human immunoglobulin (HIg) with shikonin has been investigated by using scanning electron microscope (SEM), Fourier transform infrared (FT-IR) spectroscopy, fluorescence polarization, synchronous and 3D fluorescence spectroscopy in combination with molecular modeling techniques under physiological conditions with drug concentrations of 3.33–36.67μM. The results of SEM exhibited visually the special effect on aggregation behavior of the complex formed between HIg and shikonin. The fluorescence polarization values indicated that shikonin molecules were found in a motionally unrestricted environment introduced by HIg. Molecular docking showed the shikonin moiety bound to the hydrophobic cavity of HIg, and there are four hydrogen-bonding interactions between shikonin and the residues of protein. The synchronous and 3D fluorescence spectra confirmed that shikonin could quench the intrinsic fluorescence of HIg and has an effect on the microenvironment around HIg in aqueous solution. The changes in the secondary structure of HIg were estimated by qualitative and quantitative FT-IR spectroscopic analysis. The binding constants and thermodynamic parameters for shikonin–HIg systems were obtained under different temperatures (300K, 310K and 320K). The above results revealed the binding mechanism of shikonin and HIg at the ultrastructure and molecular level.

Confined mobility in biomembranes modeled by early stage Brownian motion

An equation of motion, derived from the fractal analysis of the Brownian particle trajectory, makes it possible to calculate the time dependence of the mean square displacement for early times, before the Einstein formula becomes valid. The diffusion coefficient increases with the distance travelled which can be restricted by the geometrical conditions. The corresponding diffusion coefficient cannot increase further to achieve a value characteristic for unrestricted environment. Explicit formula is derived for confined diffusivity related to the unrestricted one as dependent on the maximum particle mean square displacement possible normalized by the square of its mean free path. The model describes the lipid and protein diffusion in tubular membranes with different radii, originally fitted by the modified Saffman–Delbrück equation, and the lateral mobility of synthetic model peptides for which the diffusion coefficient is inversely proportional to the radius of the diffusing object and to the thickness of the membrane.

Willow Garage Retrospective [ROS Topics

During its seven-year history, Willow Garage assembled a remarkable community of scientists and engineers to address some of the most pressing challenges in realizing the effective use of robotics in society. Cognizant of the need to accelerate robotics research in the United States, the Willow Garage team made substantial contributions to the global robotics community by conducting fundamental research, training the next generation of robotics researchers, developing open software and hardware platforms for the research community, and creating both for profit and nonprofit organizations. These contributions allowed researchers, developers, and commercial organizations to advance their robotics initiatives both in the United States and across the globe. Because of its philanthropic culture and fairly unrestricted research environment, the Willow Garage community was able to address fundamental research issues and enable a broader range of universities, research organizations, and commercial firms to accelerate their own research and development agenda.

A Research Using Private Cloud with IP Camera and Smartphone Video Retrieval

In this thesis, A video information system uses IP camera, which transmits video information to HOST via Streaming Server or ftp server. But there’s problem that HOST cannot retrieve video information without video information transmitted from IP camera. So in this thesis, host-active application program is developed, which can retrieve video information from HOST with only IP camera’s IP address. By installing cloud server in the HOST, which smartphone can send videos to it regardless of network realms such as Wi-Fi, LTE or AP and transfer smartphone’s video information to cloud server anytime using wired or wireless networks. So by installing a Private Cloud server in HOST, which provides unrestricted environment where user can develop and launch application programs and sync smartphone to it. Smartphone’s video information is synced with Private Cloud ubiquitously using wired or wireless networks such as AP, LTE or WIFI and stored to Private Cloud so smartphone or IP Camera’s video information is always stored in Private Cloud server which can be used as evidence when there’s crime. Also employees can save materials of meeting which is saved to corporation’s Private Cloud server in real-time and enables remote monitoring for employee in office to cooperate with employee in remote locations.

Searching to maximize revenue in unrestricted and less-restricted competitive fare environments: Combining hybrid forecasting and fare adjustment with various unconstraining methods

In their competitive environment, airlines are always searching for ways to maximize revenues. This article considers both less-restricted and fully unrestricted fare environments. We use the sophisticated Passenger Origin–Destination Simulator (PODS) to examine the revenue impact of four implementations of hybrid forecasting (HF) and fare adjustment (FA) in combination with three different methods of unconstraining – Expectation Maximization (EM), Projection Detruncation (PD) and Booking Curve (BC). Owing to the competitive nature of PODS (two airlines competing head-to-head for customers) and its allowance for customer choice, we are able to assess all the implications of these HF and FA implementations in combination with unconstraining, including the impact of spill, upgrades and recapture. We find that in the less-restricted fare environment, under either EM or PD, the optimal combination is HF with FA equal to 0.5, and that under BC unconstraining the optimal combination is HF with FA equal to 1.0, independent of optimization technique (leg or network) or demand level (medium or high). For the unrestricted fare environment, we find that under leg optimization, generally it is best to use HF with FA equal to 0.5 combined with willingness-to-pay estimate curves of either Frat5c (EM/PD) or Frat5a (BC). Under network optimization, it is best to use HF with FA equal to 1.0, combined with WTP estimate curve Frat5c for all three unconstraining methods. When using realistic booking data from major global airlines to calibrate the PODS D6 network, we show that becoming more aggressive with HF and FA can lead to significant revenue gains of 1.6–5.8 per cent (less-restricted environment) or 3–15.9 per cent (fully unrestricted environment).

Uterine environment and early embryonic development in sheep

Uterine restriction during gestation can result in the birth of lambs that are smaller than those born from an unrestricted environment. The objective of this study was to examine whether this effect is present during the early embryonic period. Pure-breed embryos were transferred within and reciprocally between genotypically large (Suffolk: S) and small (Cheviot: C) sheep to establish four groups; SinS (Suffolk embryos in Suffolk dams), SinC (Suffolk embryos in Cheviot dams), CinS (Cheviot embryos in Suffolk dams) and CinC (Cheviot embryos in Cheviot dams). At Day 19, SinS embryos were longer (13.4±0.53mm) than SinC embryos (11.0±0.57mm; p<0.05), whereas CinS embryos were longer (15.2±0.68mm) than CinC embryos (12.9±0.53mm; p<0.05). There were fewer (p<0.05) binucleate cells in SinC trophoblasts than SinS, and binucleate cells were larger (p<0.05) in CinS than CinC trophoblasts. This study suggests that uterine environment regulates the development of embryos very early in gestation, when the physical capacity of uterus is not a developmental constraint, possibly via alteration in trophoblast binucleate cell number and structure.