87value/wos11967 huggingface dataset:
Background: Krokodil or Crocodile is an illegal homemade desomorphine drug obtained from chemical reactions of commercial codeine drugs with several other powerful and highly toxic chemical agents increasing its addiction and hallucinogenic effects when compared with other morphine analogues. Methods: This paper summarizes a complete review about an old drug called desomorphine (Krokodil), presenting its chemistry, pharmacology, metabolism, toxicology and analysis. Results: It is of particular interest and concern because this cheaper injectable semisynthetic opioid drug has been largely used in recent years for recreational purposes in several Eastern European as well as North and South American countries, despite known damage to health that continuous use might induce. These injuries are much stronger and more aggressive than morphine's, infecting and rotting skin and soft tissue to the bone of addicts at the point of injection in less than three years, which, in most cases, evolves to death. On this basis, it is imperative that literature reviews focus on the chemistry, pharmacology, toxicology and analysis of dangerous Krokodil to find strategies for rapid and effective determination to mitigate its adverse effects on addicts and prevent consumption. Conclusions: It is crucial to know the symptoms and consequences of the use of Krokodil, as well as Methods: for identification and quantification of desomorphine, contaminants and metabolites, which can help the forensic work of diagnosis and propose actions to control and eradicate this great danger to public health around the world. (C) 2017 Elsevier B.V. All rights reserved.
Background: The International Classification of Diseases (ICD) has been grouping the allergic and hypersensitivity disorders involving the respiratory tract under topographic distribution, regardless of the underlying mechanisms, triggers or concepts currently in use for allergic and hypersensitivity conditions. In order to strengthen awareness and deliberate the creation of the new Allergic or hypersensitivity disorders involving the respiratory tract section of the ICD-11, we here propose make the building process public. Methods: The new frame has been constructed to cover the gaps previously identified and was based on consensus academic reports and ICD-11 principles. Constant and bilateral discussion was kept with relevant groups representing specialties and resulted in proposals submission into the ICD-11 online platform. Results: The Allergic or hypersensitivity disorders involving the respiratory tract section covers 64 entities distributed across five main categories. All the 79 proposals submitted resulted from an intensive collaboration of the Allergy working group, relevant Expert working groups and the WHO ICD governance. Conclusion: The establishment of the ICD-11 Allergic or hypersensitivity disorders involving the respiratory tract section will allow the dissemination of the updated concepts to be used in clinical practice by many different specialties and health professionals.
An asphalt shear strength tester was developed. It had the advantages of high precision, low cost, and was easy to generalize. Interlayer shear strength testing scheme was designed based on the characteristics of vehicle real driving conditions. Considering different interlayer material types, three typical binding conditions were selected, i.e., with binding oil, without binding oil and geotextile + binding oil. For each kind of binding condition, four specimens were prepared to test the shear strength under different normal stress states. By comparing experimental results, the shear strength formulas for the three conditions were obtained.
Models based on deep convolutional networks have dominated recent image interpretation tasks; we investigate whether models which are also recurrent are effective for tasks involving sequences, visual and otherwise. We describe a class of recurrent convolutional architectures which is end-to-end trainable and suitable for large-scale visual understanding tasks, and demonstrate the value of these models for activity recognition, image captioning, and video description. In contrast to previous models which assume a fixed visual representation or perform simple temporal averaging for sequential processing, recurrent convolutional models are doubly deep in that they learn compositional representations in space and time. Learning long-term dependencies is possible when nonlinearities are incorporated into the network state updates. Differentiable recurrent models are appealing in that they can directly map variable-length inputs (e.g., videos) to variable-length outputs (e.g., natural language text) and can model complex temporal dynamics; yet they can be optimized with backpropagation. Our recurrent sequence models are directly connected to modern visual convolutional network models and can be jointly trained to learn temporal dynamics and convolutional perceptual representations. Our results show that such models have distinct advantages over state-of-the-art models for recognition or generation which are separately defined or optimized.
We test an information theory of prosocial behavior whereby ego utility and self-signaling crowd out the effect of consumption utility on choice. The data come from two field experiments involving purchases of a consumer good bundled with a charitable donation. Across experimental cells, we randomize the price level and the donation level. A model-free analysis of the data reveals nonmonotonic regions of demand when the good is bundled with relatively large charitable donations. Subjects also self-report lower ratings of feeling good about themselves when offered bundles with large donations and price discounts. The evidence suggests that price discounts crowd out consumer self-inference of altruism. Alternative motivation-crowding theories are rejected due to their inability to explain the nonmonotonic data moments. The standard use of interaction effects and other falsification checks to explore the underlying choice mechanism in an experimental setting is complicated in our self-signaling context. Instead, a novel feature of our analysis consists of using the experimental data to estimate the structural form of a model of consumer demand with self-signaling. We specify a model in which consumers obtain both consumption and ego utility from their choices. Ego utility derives from a consumer's posterior self-beliefs after making her choice. An estimator is proposed that handles the potential multiplicity of equilibria that can arise in the self-signaling model. The model estimates allowus to quantify the economic role of ego utility and to explore the underlying signaling mechanism. Nested tests reject the hypothesis of no self-signaling. Alternative model specifications that potentially allow for nonmontonic demand without the self-signaling structure exhibit an inferior fit to the data. The model estimates imply that consumer response to the donations are mainly driven by ego utility and not by consumption utility (i.e., not by altruistic motives). The findings from the combination of a field experiment and a structural model contribute to a growing literature on self-signaling and consumer behavior by quantifying the magnitude of self-signaling on preferences and choices. The results also have implications for the design of a cause marketing campaign and the potential negative synergies between price and nonprice promotions.
Background: Extended-spectrum beta-lactamase (ESBL)-producing bacteria are resistant to several types of antibiotics excluding carbapenems. A transmissibility of ESBL-producing Enterobacteriaceae would be depending on each bacterial property, however, that has not been elucidated in clinical setting. In this study, we attempted to identify the source of an outbreak of ESBL-producing bacteria in a medical oncology and immunology care unit. Methods: An ESBL-producing Enterobacteriaceae (ESBL-E) outbreak observed between July 2012 and August 2012 in Kagawa University Hospital was surveyed using various molecular microbiology techniques. We used Pulsed-field gel electrophoresis (PFGE), PCR-based ESBL gene typing, and direct sequence of ESBL gene as molecular microbiology typing method to distinguish each strain. Results: The typical prevalence of ESBL-E isolation in the unit was 7.0 per month (1.7 per week). The prevalence of ESBL-E isolation during the target research period was 20.0 per month (5.0 per week). In total, 19 isolates (11 K. pneumoniae and 8 E. coli) were obtained from clinical samples, including four control strains (two each of both bacteria), that were physically different from those obtained from other inpatient units in our hospital. Pulsed-field gel electrophoresis (PFGE) for K. pneumoniae (digested by XbaI) produced similar patterns excluding one control strain. PCR classification of the ESBL gene for K. pneumoniae revealed that all strains other than the control strain carried SHV and CTX-M-9. This result was reconfirmed by direct DNA sequencing. Although the outbreak of K. pneumoniae was considered to be clonal, PFGE and PCR classification of the ESBL genes for E. coli uncovered at least six different non-clonal strains possessing individual ESBL gene patterns. According to the result of an antibiogram, the pattern of antimicrobial susceptibility was more variable for K. pneumoniae than for E. coli. Conclusions: Typing by PFGE and ESBL gene PCR analysis is practical for discriminating various organisms. In our cohort, two outbreaks were concomitantly spread with different transmission strategies, namely clonal and non-clonal, in the same unit. This might represent clinical evidence that transmissibility differs according to the type of strain. We speculated that patient-to-patient transmission of ESBL-E occurred according to the properties of each individual strain.
Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder characterized by repetitive episodes of complete or partial obstruction of the upper airway. The prevalence of this disorder is strictly dependent on its gravity. At >= 15 events/h apnea-hypopnea index (AHI), it ranges from 6 to 17% in the general population, with higher rates in men and increasing with age. The hypoxia induced by OSA severely affects the structure and function of blood vessels, culminating in mortality and morbidity. Its negative impact influences also cognitive functioning. Recent papers showed the relationship between OSA and some neurological disorders, such as neurodegenerative diseases, stroke, epilepsy, and headache. OSA may accelerate the onset of mild cognitive impairment and Alzheimer's disease (AD) and might also represent an independent risk factor for Parkinson's disease (PD). OSA is also frequent in multisystem atrophy. In the early stages of AD, continuous positive airway pressure (CPAP) treatment might slow down the progression of the disease, thus highlighting the potential importance of OSA screening and a timely intervention in these patients. Moreover, CPAP is effective in reducing daytime sleepiness in PD. OSA may induce seizures by means of sleep disruption and deprivation, as well as cerebral hypoxemia with consequent oxidative stress. It has been demonstrated that CPAP treatment is efficacious in controlling epileptic seizures. OSA can represent a risk factor for stroke and death, mainly related to the endothelial dysfunction, with the formation of atherosclerosis caused by hypoxia through oxidative stress. CPAP treatment in patients with OSA and stroke, if delivered in the early stages, is able to increase the magnitude of neurologic improvement after the vascular accident. There is a strong association between OSA and headache. In particular, there is a sleep apnea headache described as a recurrent morning headache, with resolution after effective treatment of sleep apnea. This review clearly shows the importance of taking asleep history in neurological patients and considering the diagnosis and specific treatment of OSA in these patients.
The global industry is currently facing a growing increase in the competitiveness that forces companies to adopt and develop new strategies and methods of production. Therefore, one of the most relevant challenges in manufacturing engineering is innovatively integrating Product, Process and Factory dimensions and life cycles, in a holistic approach, from design to recycling/disposal and reuse. The challenge faced here is the synchronization and simultaneous generation of all three-domain models by integrating manufacturing engineering knowledge into the early stage of the modelling and planning processes. The next generation of factories has to be modular, scalable, flexible, open, agile and knowledge-based in order to be able to adapt, in real time, to the continuously changing market demands, technology options and regulations. Therefore, integration, flexibility and efficiency requirements and the ability to simulate the production life cycle of a factory play a crucial role in decreasing ramp-up and design times. Furthermore they play a crucial role in improving the performance in the evaluation and reconfiguration of new or existing facilities, in supporting management decisions and providing tools that can guarantee real-time performance monitoring. Therefore, it is necessary to research and implement the underlying models and ideas during the foundation stage of a new conceptual framework, which is designed to be implemented in the next generation of factories. This will be supported by suitable Information and Communication Technologies (ICT) and digital infrastructures and should lay down the foundations for future applications in this research area the industrial paradigm of Factory as a Product. In line with the context presented here, we propose the development of factory templates to address the design and operation practices throughout the entire life cycle of the factory. Different dimensions of the factory templates are presented in this paper; they cover the design and creation of the factory, its remodelling and even the disassembly and recycling stages. This entire study takes into account relevant factors such as costs, quality, time, flexibility, environmental and social issues and energy efficiency. Throughout the article, different kinds of models are presented, which describe and adjust the structure of the analysis, design and development of a factory integration project that helps provide a formal analysis of the system. Furthermore, templates integrating the factory's response to internal and external disturbances will also be developed. (C) 2011 Elsevier Ltd. All rights reserved.
Climate change is an unprecedented global threat to fundamental life-supporting systems and people's livelihoods and is expected to aggravate development challenges. Subsistence-oriented smallholder farmers of developing regions, such as those in sub-Saharan Africa, are highly vulnerable to these changes given their lower adaptive capacity. In this context, building a climate-resilient agricultural society is an essential requirement to protect livelihoods. Hence, there is a need for spreading the climate-resilient sustainable agricultural (CRSA) practices by replicating the proven ones to larger areas (scaling-up). Fostering widespread adoption of such practices needs consideration of their social, ecological, economic, and institutional appropriateness in target areas. This article reports the application of a tool ScalA that generates information on a multitude of aspects and assesses the local suitability of CRSA practices among sub-Saharan smallholders. It also briefly presents other state-of-the-art tools that can be used for similar purposes. In the first case study, the tool is used to assess appropriateness of agroforestry, biochar application, and rainwater harvesting in Fulwe village of Morogoro, Tanzania, for enhancing resilience capacity. In another case study, the potential of fertilizer management is assessed for two different villages, i.e., Fulwe and Mlali. Analytically, appropriateness of interventions is assessed by the deviation of the actual factor constellation of the scaling-up process with an optimal constellation that will foster the wider adoption of the given practice.
This research details the development of the comfort with interpersonal touch (CIT) scale designed to measure individual differences in interpersonal touch tendencies and preferences. The CIT construct is defined as the degree to which an individual is comfortable with intentional interpersonal touch from or to another person. The scale incorporates the distinction between initiating touch, which is the act of touching someone else, and receiving touch, which is the act of being touched by someone else. Investigation of this construct includes scale development, measure purification, and validation. We situate CIT-initiating and CIT-receiving within an approach avoidance framework and demonstrate that comfort with initiating touch is more related to approach tendencies such as assertiveness while comfort with receiving touch is more related to avoidant tendencies such as avoiding crowded spaces. While previous research generally finds positive effects of interpersonal touch, we find that these effects, at least in part, depend on an individual's comfort with interpersonal touch. We discuss theoretical and managerial implications as well as future research opportunities using the CIT scale. (C) 2014 Society for Consumer Psychology. Published by Elsevier Inc. All rights reserved.
Objectives: To develop and validate a noninvasive mobility sensor to automatically and continuously detect and measure patient mobility in the ICU. Design: Prospective, observational study. Setting: Surgical ICU at an academic hospital. Patients: Three hundred sixty-two hours of sensor color and depth image data were recorded and curated into 109 segments, each containing 1,000 images, from eight patients. Interventions: None. Measurements and Main Results: Three Microsoft Kinect sensors (Microsoft, Beijing, China) were deployed in one ICU room to collect continuous patient mobility data. We developed software that automatically analyzes the sensor data to measure mobility and assign the highest level within a time period. To characterize the highest mobility level, a validated 11-point mobility scale was collapsed into four categories: nothing in bed, in-bed activity, out-of-bed activity, and walking. Of the 109 sensor segments, the noninvasive mobility sensor was developed using 26 of these from three ICU patients and validated on 83 remaining segments from five different patients. Three physicians annotated each segment for the highest mobility level. The weighted Kappa (kappa) statistic for agreement between automated noninvasive mobility sensor output versus manual physician annotation was 0.86 (95% CI, 0.72-1.00). Disagreement primarily occurred in the nothing in bed versus in-bed activity categories because the sensor assessed movement continuously, which was significantly more sensitive to motion than physician annotations using a discrete manual scale. Conclusions: Noninvasive mobility sensor is a novel and feasible method for automating evaluation of ICU patient mobility. (Crit Care Med 2017; 45:630-636)
If there is a 'platonic world' of mathematical facts, what does contain precisely? I observe that if is too large, it is uninteresting, because the value is in the selection, not in the totality; if it is smaller and interesting, it is not independent of us. Both alternatives challenge mathematical platonism. I suggest that the universality of our mathematics may be a prejudice and illustrate contingent aspects of classical geometry, arithmetic and linear algebra, making the case that what we call mathematics is always contingent.
Imidazo[1,2-a]pyridine is one of the most potential bicyclic 5-6 heterocyclic rings that is recognized as a drug prejudice scaffold due to its broad range of applications in medicinal chemistry such as anticancer, antimycobacterial, antileishmanial, anticonvulsant, antimicrobial, antiviral, antidiabetic, proton pump inhibitor, insecticidal activities. This scaffold has also been represented in various marketed preparations such as zolimidine, zolpidem, alpidem. Therefore, several attempts were made to carry out the structural modifications of this scaffold to discover and develop novel therapeutic agents. This review provides a valuable insight into the research findings of wide range of derivatives of imidazo[1,2-a]pyridine scaffold leading to promising heterocyclic compounds which could be explored further for the synthesis of new derivatives as well as construction of potential drug-like chemical libraries for biological screening in search of new therapeutic agents.
Designing lightweight security protocols for cloud-based Internet-of-Things (IoT) applications for battery-limited mobile devices, such as smart phones and laptops, is a topic of recent focus. Ciphertext-policy attribute-based encryption (CP-ABE) is a viable solution, particularly for cloud deployment, as an encryptor can write the access policy so that only authorized users can decrypt and have access to the data. However, most existing CP-ABE schemes are based on the costly bilinear maps, and require long decryption keys, ciphertexts and incur significant computation costs in the encryption and decryption (e.g. costs is at least linear to the number of attributes involved in the access policy). These design drawbacks prevent the deployment of CP-ABE schemes on battery-limited mobile devices. In this paper, we propose a new RSA-based CP-ABE scheme with constant size secret keys and ciphertexts (CSKC) and has O(1) time complexity for each decryption and encryption. Our scheme is then shown to be secure against a chosen-ciphertext adversary, as well as been an efficient solution with the expressive AND gate access structures (in comparison to other related existing schemes). Thus, the proposed scheme is suitable for deployment on battery-limited mobile devices.
Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omits made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers. Given the assumption that the cell population is in a steady state, we derive transformation rules which transform the number density on the manifold to the steady state number density of age structured population models. Our theory facilitates the study of cell cycle dependent processes including local molecular events, cell death and cell division from high dimensional snapshot data. Ergodic analysis can in general be applied to every process that exhibits a steady state distribution. By combining ergodic analysis with age structured population models we furthermore provide the theoretic basis for extensions of ergodic principles to distribution that deviate from their steady state.