Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges of bringing a new sedative to market!

Purpose of review The current review examines the success and failures of the development of new hypnotic compounds for the human market. One of the important aspects is that one of the key present agents, propofol, is considered by many anaesthesiologists as ‘the ideal’. However, all drugs have adverse or side-effects. Recent findings The last 30 years since the introduction of propofol has seen many new compounds evaluated; but as at the present time, only three agents may achieve a pivotal position in the market – fospropofol (a sedative agent which may have a role in endoscopic surgery); remimazolam (a short-acting benzodiazepine) whose development is also being focused on the sedation rather than anaesthesia market; and the pregnane steroid, alfaxalone (an anaesthetic agent first introduced in 1972, but withdrawn in 1984 because of adverse allergic reactions to the solvent, Cremophor EL) now solvented in a cyclodextrin. Summary Studies of these three agents thus far have shown that none of them has any major adverse side-effects; all have properties which warrant further clinical evaluation.
Importance Weighted Transfer of Samples in Reinforcement Learning

We consider the transfer of experience samples (i.e., tuples ) in reinforcement learning (RL), collected from a set of source tasks to improve the learning process in a given target task. Most of the related approaches focus on selecting the most relevant source samples for solving the target task, but then all the transferred samples are used without considering anymore the discrepancies between the task models. In this paper, we propose a model-based technique that automatically estimates the relevance (importance weight) of each source sample for solving the target task. In the proposed approach, all the samples are transferred and used by a batch RL algorithm to solve the target task, but their contribution to the learning process is proportional to their importance weight. By extending the results for importance weighting provided in supervised learning literature, we develop a finite-sample analysis of the proposed batch RL algorithm. Furthermore, we empirically compare the proposed algorithm to state-of-the-art approaches, showing that it achieves better learning performance and is very robust to negative transfer, even when some source tasks are significantly different from the target task.
Simultaneous dual-color and dual-polarization imaging of single molecules

We report the observation of single-molecule colocalization and quantitative fluorescence resonant energy transfer by simultaneously imaging the emission and polarization characteristics of two colocalized fluorophores using a simple optical design. The methodology was tested using the ligand-receptor system streptavidin, fluorescence labeled with the dye Cy5, and biotin labeled with tetramethylrhodamine. Discrimination of the two dyes permitted the observation of single-pair fluorescence resonant energy transfer with an efficiency of 89%. The multidimensional character of our fluorescence microscopy combined with the robustness of our design provides a simple method suitable to study biomolecular interactions on the single molecule level.
High Quality Bidirectional Generative Adversarial Networks

Generative adversarial networks (GANs) have achieved outstanding success in generating the high quality data. Focusing on the generation process, existing GANs investigate unidirectional mapping from the latent vector to the data. Later, various studies point out that the latent space of GANs is semantically meaningful and can be utilized in advanced data analysis and manipulation. In order to analyze the real data in the latent space of GANs, it is necessary to investigate the inverse generation mapping from the data to the latent vector. To tackle this problem, the bidirectional generative models introduce an encoder to enable the inverse path of generation process. Unfortunately, this effort leads to the degradation of generation quality because the imperfect generator rather interferes the encoder training and vice versa. In this paper, we propose a new inference model that estimates the latent vector from the feature of GAN discriminator. While existing bidirectional models learns the image to latent translation, our algorithm formulates this inference mapping by the feature to latent translation. It is important to note that training of our model is independent of the GAN training. Owing to the attractive nature of this independency, the proposed algorithm can generate the high quality samples identical to those of unidirectional GANs and also reconstruct the original data faithfully. Moreover, our algorithm can be employed to any unidirectional GAN, even the pre-traind GANs.
Extraction of Main Event Descriptors from News Articles by Answering the Journalistic Five W and One H Questions

The identification and extraction of the events that news articles report on is a commonly performed task in the analysis workflow of various projects that analyze news articles. However, due to the lack of universally usable and publicly available methods for news articles, many researchers must redundantly implement methods for event extraction to be used within their projects. Answers to the journalistic five W and one H questions (5W1H) describe the main event of a news story, i.e., who did what, when, where, why, and how. We propose Giveme5W1H, an open-source system that uses syntactic and domain-specific rules to extract phrases answering the 5W1H. In our evaluation, we find that the extraction precision of 5W1H phrases is p=0.64, and p=0.79 for the first four W questions, which discretely describe an event.
Systematic Mapping of Process Mining Studies in Healthcare

In the last decade, as an emerging technique for business processes management, process mining (PM) has been applied in many domains, including manufacturing, supply-chain, government, healthcare, and software engineering. Particularly in healthcare, where most processes are complex, variable, dynamic, and multi-disciplinary in nature, the application of this technique is growing yet challenging. Several literature reviews, as secondary studies, reveal the state of PM applications in healthcare from different perspectives, such as clinical pathways, oncology processes, and hospital management. In this article, we present the results of a systematic mapping (SM) study which we conducted to structure the information available in the primary studies. SM is a well-accepted method to identify and categorize research literature, in which the number of primary studies is rapidly growing. We searched for studies between 2005 and 2017 in the electronic digital libraries of scientific literature, and identified 172 studies out of the 2428 initially found on the topic of PM in healthcare. We created a concept map based on the information provided by the primary studies and classified these studies according to a number of attributes including the types of research and contribution, application context, healthcare specialty, mining activity, process modeling type and notation/language, and mining algorithm. We also reported the demographics and bibliometrics trends in this domain; namely, publication volume, top-cited papers, most contributing researchers and countries, and top venues. The results of mapping showed that, despite the healthcare data and technique related challenges, the field is rapidly growing and open for further research and practice. The researchers who are interested in the field could use the results to elicit opportunities for further research. The practitioners who are considering applications of PM, on the other hand, could observe the most common aims and specialties that PM techniques are applied.
The Spreading of Epidemics in Complex Networks

The spreading of epidemics in complex networks has been extensively studied in the last few decades. Depending on the nature of the disease and the network it spreads on, there are different critical behaviors. In this essay I provide a brief introduction to the study of complex networks and the susceptible-infectioussusceptible(SIS) epidemic model. I discuss the different critical behaviors when SIS model is applied to exponential network and scale-free network. The existence of non-zero epidemic threshold in exponential networks and the lack of such threshold in scale-freee networks can help understanding computer virus epidemics.
The fate of neurons after traumatic spinal cord injury in rats: A systematic review

Objective(s): To reach an evidence-based knowledge in the context of the temporal-spatial pattern of neuronal death and find appropriate time of intervention in order to preserve spared neurons and promote regeneration after traumatic spinal cord injury (TSCI). Materials and Methods: The study design was based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)-guided systematic review. PubMed and EMBASE were searched (24 October, 2015) with no temporal or linguistic restrictions. Hand-search was performed in the bibliographies of relevant articles. Non-interventional animal studies evaluating time-dependent neuronal death following acute mechanical trauma to the spinal cord were included. We separately evaluated the fate of various populations of neurons including propriospinal neurons, ventral motor neurons, Clarke’s column neurons, and supraspinal neurons. Results: We found 11,557 non-duplicated studies. Screening through the titles and abstracts led to 549 articles, 49 of which met the inclusion criteria. Both necrotic and apoptotic neuronal deaths occur after TSCI, though necrosis is the prominent mechanism. There are differences in the responses of intrinsic neurons of the spinal cord to the TSCI. Also, the extent of neuronal death in the supraspinal neurons depends on the anatomical location of their axons. Conclusion: In order to develop new therapies, selection of the injury model and time of intervention has a crucial role in the efficacy of therapy. In addition, examining the safety and efficacy of an intervention by reliable methods not confounded by the injury-related changes would promote translation of therapies to the clinical application.
Risk of opportunistic infections in patients treated with alemtuzumab for multiple sclerosis

ABSTRACT Introduction: Alemtuzumab is a monoclonal anti CD-52 antibody recently approved for use in relapsing-remitting multiple sclerosis(MS). Given that the targeted antigen is primarily expressed on B and T lymphocytes, the administration of this biological drug is associated with rapid but protracted peripheral lymphopenia. Areas covered: The impact on infective risk of this immune impairment is still to be fully understood. In this review, we attempt to summarize all the available literature concerning opportunistic infections occurring in patients with MS receiving alemtuzumab. Infective adverse events were observed in more than 70% of patients in phase 2/3 RCTs, mainly of mild-to-moderate severity. Nevertheless, several post-marketing reports documented cases of serious, rare, and unexpected infections. Expert Opinion: Predictive risk factors and prognostic features of opportunistic infections in this setting still need to be exactly assessed. At present, the only recommended preventive measures consist in anti-herpetic prophylaxis, Listeria-free diet, Tuberculosis prophylaxis and annual Papillomavirus screening. Given the non-negligible risk of unpredicted infective events, we advise physicians to take into account patients’ history of infectious diseases and vaccine status and to consider supplementary prophylactic strategies, including screening for Toxoplasma gondii and viral hepatitis serostatus as well as pre-emptive approaches to avert CMV reactivation and Pneumocystosis.
Experimental study on the importance and effectiveness of monkey testing for android applications

Android application development has attracted attention of many software developers as a mainstream software platform. Despite its interesting characteristics, there are a number of issues that result in developing applications with poor performance. Hence, it is very crucial to evaluate quality of Android applications, specially their robustness and responsiveness. Monkey testing is a traditional technique used for testing these aspects, and Google’s Android Studio, as the official Android IDE, is equipped with monkey testing facilities. In this paper, two experimental studies are performed to investigate the necessity of monkey testing on Android applications and also to evaluate the effectiveness of the default Android Studio monkey for revealing application failures. The results demonstrate that there is a strong negative correlation between the number of crashes detected by the monkey and the rating that users have assigned to the application. So, monkey testing for Android applications is indeed a requirement. Further, the results show that the default monkey is weak in terms of focusing on the target application, and hence, there is much room for improving monkey testing techniques for Android applications.
A QoE Estimation Model Considering Video Popularity for Video Streaming Services

With the increasing demand of keeping competitive force for video streaming service provider, the user-oriented QoE evaluation is significant to be optimized. In previous work, those user-centric QoE evaluation methods depend on user perception collection which are generally based on subjective feedbacks which causes the impracticality of evaluation model. In this paper, a QoE estimated model considering video popularity is proposed. The model substitutes the user preference by the mapping relationship between video popularity and user preference so that the service provider can estimate user perceived QoE with objective video information. The mapping relationship between video popularity and user preference is explored by analysis of uncertainty of user prefenrece for different popularity degree. Then, a crowdsourcing-based experiment is conducted to collect data for QoE model regression and verification. With data analysis, a QoE model based on video popularity is developed and the correlation coefficient shows the well estimation on QoE.
Context-Aware Mobile Recommendation By A Novel Post-Filtering Approach

Recommender system has been demonstrated as a successful solution to assist decision makings. Context-awareness becomes necessity in recommendations, especially in mobile computing, since a user’s decision may vary from contexts to contexts. Context-aware recommender systems, therefore, emerged to adapt the personalizations to different contextual situations. Context ﬁltering is one of the popular ways to develop the context-aware recommendation models. Contextual pre-ﬁltering techniques have been well developed, but the post-ﬁltering methods are still under investigated. In this paper, we propose a simple but effective post-ﬁltering recommendation approach. We demonstrate the effectiveness of this algorithm in comparison with other context-aware recommendation approaches based on the real-world rating data from mobile applications. Our experimental results reveal that the proposed algorithm is the best post-ﬁltering approach, and it is even able to outperform the popular pre-ﬁltering and contextual modeling recommendation models.
Impact of Rye Kernel-Based Evening Meal on Microbiota Composition of Young Healthy Lean Volunteers With an Emphasis on Their Hormonal and Appetite Regulations, and Blood Levels of Brain-Derived Neurotrophic Factor

Rye kernel bread (RKB) evening meals improve glucose tolerance, enhance appetite regulation and increase satiety in healthy volunteers. These beneficial effects on metabolic responses have been shown to be associated with increased gut fermentation. The present study aimed to elucidate if RKB evening meals may cause rapid alterations in microbiota composition that might be linked to metabolic-, immune-, and appetite- parameters. Gut-brain axis interaction was also studied by relating microbiota composition to amount of brain-derived neurotrophic factor (BDNF) in blood plasma. Nineteen healthy volunteers, ten women and nine men aged 22–29 years, BMI < 25 (NCT02093481) participated in the study performed in a crossover design. Each person was assigned to either white wheat bread (WWB) or RKB intake as a single evening meal or three consecutive evenings. Stool and blood samples as well as subjective appetite ratings were obtained the subsequent morning after each test occasion, resulting in four independent collections per participant (n = 76). DNA was extracted from the fecal samples and V4 hypervariable region of the bacterial 16S rRNA genes was sequenced using next generation sequencing technology. Higher abundance of Prevotella and Faecalibacterium with simultaneous reduction of Bacteroides spp. were observed after RKB meals compared to WWB. The associations between metabolic test variables and microbiota composition showed a positive correlation between Bacteroides and adiponectin levels, whereas only Prevotella genus was found to have positive association with plasma levels of BDNF. These novel findings in gut-brain interactions might be of importance, since decreased levels of BDNF, that plays an essential role in brain function, contribute to the pathogenesis of several major neurodisorders, including Alzheimer's. Thus, daily consumption of Faecalibacterium- and/or Prevotella-favoring meals should be investigated further for their potential to prevent neurodegenerative processes in the brain.
Differing psychological vulnerabilities among behaviourally and perinatally HIV infected adolescents in South Africa – implications for targeted health service provision*

ABSTRACT HIV infections are growing the fastest amongst adolescents, especially in sub Saharan Africa. On reaching adolescence, perinatally-infected youth may have different needs to those who acquired infection behaviourally. Yet both have sub-optimal adherence with implications for their own health as well as onward transmission. This study uses the world's largest community-based study of HIV-positive adolescents from the Eastern Cape, South Africa. Clinic records at N = 53 district health facilities generated a log of all ART-initiated adolescents who were then interviewed in the community: N = 1058 (90%) were tracked and participated. Ethical approval, informed consent and data collector training preceded data gathering. Inventories comprised validated measures of mental health (depression, anxiety, suicidality and internalised stigma), substance use, ART adherence, and clinic attendance. Analyses were conducted using SPSS25 and STATA15. Perinatally-infected adolescents (n = 792, 77.3%) were significantly more likely to be ART adherent (OR = 1.54 95%CI: 1.14–2.07 p = 0.005), retained in healthcare (OR = 1.59 95%CI1.18–2.14 p = 0.002), and treated well by clinic staff (OR = 2.12 95%CI1.59–3.07 p ≤ 0.001). Behaviourally-infected adolescents were more likely to be depressed (B = 0.81 p ≤ 0.001), anxious (B = 1.36 p ≤ 0.001), report internalised stigma (B = 0.91 p ≤ 0.001), express suicidal ideation (OR = 3.65 95%CI: 1.96–6.82 p ≤ 0.001) and report excessive substance use in the past year (OR = 9.37 95%CI5.73–15.35 p ≤ 0.001). Being older explained most of these differences, with female adolescents living with HIV more likely to report suicidal ideation. However, behaviourally-infected adolescents were more likely to report substance use (OR = 2.69 95%CI: 1.48–4.91 p = 0.001), depression (B = 0.406, p = 0.022), anxiety (B = 1.359, p ≤ 0.001), and internalised stigma (B = 0.403, p = 0.007) in multivariate regression analyses, controlling for covariates. Moderation analyses (adjusting for multiple testing) suggest that behaviourally-infected HIV-positive adolescents who are also maternal orphans are more likely to report higher rates of depression (B = 1.075, p < 0.001). These notable differences by mode of infection suggest that studies which conflate HIV-positive adolescents may blur the clinical and psychological experiences of these two different sub-populations. Drivers of non-adherence, poor retention in care, and mental health problems may differ by mode of infection, requiring tailored interventions. Health and social service provision, if it is to be effective, needs to address these different youth profiles to ensure optimal adherence, development and wellbeing throughout the life course.
Prolonged low-dose cyclophosphamide treatment after pulse therapy attenuates lung injury in rats with paraquat intoxication

Background/Aims This study tested the hypothesis that prolonged low-dose cyclophosphamide (CTX) treatment after pulse therapy attenuate paraquat (PQ)-induced lung injury in rats. Methods PQ (25 mg/kg) was administered intraperitoneally to induce PQ-intoxicated rat model. The rats were randomly divided into four groups: control group (1 mL/day saline solution for 14 days), PQ group (1 mL/day saline solution for 14 days after PQ exposure), pulse group (15 mg/kg/day CTX in 1 mL of saline solution for 2 days and subsequent 1 mL/day saline solution for 12 days), and prolonged low-dose group (15 mg/kg/day CTX in 1 mL of saline solution for 2 days and subsequent 1.5 mg/kg/day CTX in 1 mL of saline solution for 12 days). A 14-day follow-up was conducted to determine the survival rat, and lung hydroxyproline (HYP), wet-to-dry weight ratios (W/Dc) and histopathological changes were evaluated. Results Results showed similar survival rate (55% vs. 50%, p > 0.05) between prolonged low-dose and pulse groups. Lung W/Dc (4.94 ± 0.38 vs. 5.47 ± 0.28, p < 0.01), HYP (3.34 ± 0.29 µg/mg vs. 3.65 ± 0.19 µg/mg, p < 0.001), and fibrosis score (2.69 ± 0.84 vs. 3.13 ± 0.63, p < 0.05) were lower in prolonged low-dose group than those in the pulse group. Conclusions These findings suggested prolonged low-dose CTX treatment after pulse therapy could attenuate PQ-induced lung injury in rats.
Computerized test for oral language perception: TIPLO

A computerized test for oral language perception (TIPLO) has been developed to evaluate the abilities of young children (from age 2) and of children with language disorders (including a lack of language production) to perceive and discriminate phonetic information. The test has a computer game presentation that makes it easy to use with very young children. An experiment with normally developing children aged 18-33 months and with children with severe language disorders showed that all children had no problems with the test. Children had to point out one of the two or four images displayed simultaneously on the screen after hearing oral instructions given through the computer loudspeakers. There were two versions of the test: one tested phonetic discrimination and semantic knowledge, the other semantic knowledge only. Each test consisted of 20 items and lasted about 15 minutes.