Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant Raf-like kinase integrates abscisic acid and hyperosmotic stress signaling upstream of SNF1-related protein kinase2

Significance Plants can sense loss of water caused by drought and stimulate internal mechanisms for protecting cells from damage with the aid of the stress hormone abscisic acid (ABA). Analysis of a mutant of the basal land plant, the moss Physcomitrella patens, revealed that an impairment of a protooncogene Raf-like protein kinase, designated “ARK” (for “ABA and abiotic stress-responsive Raf-like kinase”), causes a loss of both ABA sensitivity and osmotic stress tolerance. We show evidence that ARK has a role in integrating ABA and osmotic signals upstream of the sucrose nonfermenting 1-related protein kinase2, known to be a central regulator of stress signaling in plants. Plant response to drought and hyperosmosis is mediated by the phytohormone abscisic acid (ABA), a sesquiterpene compound widely distributed in various embryophyte groups. Exogenous ABA as well as hyperosmosis activates the sucrose nonfermenting 1 (SNF1)-related protein kinase2 (SnRK2), which plays a central role in cellular responses against drought and dehydration, although the details of the activation mechanism are not understood. Analysis of a mutant of the moss Physcomitrella patens with reduced ABA sensitivity and reduced hyperosmosis tolerance revealed that a protein kinase designated “ARK” (for “ABA and abiotic stress-responsive Raf-like kinase”) plays an essential role in the activation of SnRK2. ARK encoded by a single gene in P. patens belongs to the family of group B3 Raf-like MAP kinase kinase kinases (B3-MAPKKKs) mediating ethylene, disease resistance, and salt and sugar responses in angiosperms. Our findings indicate that ARK, as a novel regulatory component integrating ABA and hyperosmosis signals, represents the ancestral B3-MAPKKKs, which multiplied, diversified, and came to have specific functions in angiosperms.
Lumbar Spine Surgeries and Medication Usage During Hospital Stay: One-Center Perspective

Background: Pain after spine surgery is usually managed with opioid and nonopioids. The rate of lumbar spine surgeries (LSS) is rising, but current practices on LSS are not known. A current trend in LSS and medication usage by age group is needed to gain a better understanding of how LSS and its pain management vary by age. Objective: The aim of this study was to report current practices of LSS of discectomy, laminectomy, and fusion in patients aged 18 and older and to gain an understanding of medication use for management of LSS. Methods: This retrospective study analyzed data of the University of Kansas Medical Center from 2007 to 2014 of patients (>18 years of age) undergoing laminectomy, discectomy, and fusion. Results: A total of 19 463 patients underwent LSS between 2007 and 2014 at Kansas University hospital. For the purpose of this study, 3115 patients’ medical records were observed. A 50% increase in LSS between 2007 and 2014 was noted. Specifically, more than 2-fold increase in LSS was observed in patients aged 65 years and older. Among those aged 65 years and older, laminectomy was the most commonly performed surgery (69.6%) while discectomy was the most common surgery performed among those aged 18 to 34 (82.9%) and those aged 35 to 44 (72%). The medication use also increased with a highest usage in opioids alone (55%), followed by opioids combined with other analgesics (42.7%), regardless of lumbar surgery type or age. Conclusion: The information of increase in both LSS and the medication usage over the 7 years can be used to gain a better understanding of quality, expenditure, and outcomes following LSS. This knowledge may help health care providers plan patient care and rehabilitation services for older adults, as the trajectory of lumbar spine surgery is likely to rise with growing prevalence of older adults. The information regarding increased opioid utilization may also help clinicians to refine opioid usage and consider alternative approaches to manage acute postoperative pain, in light of the current concerns related to overutilization of opioids.
The cinema makers: public life and the exhibition of difference in south-eastern and central Europe since the 1960s

the dictatorial and democratising periods in Portugal (Chapters 3–5) and Spain (Chapters 6–8). In comparing the context of civil–military relations Chapters 3 and 6 illustrate the situation faced by the respective leaders and begin to give some indication regarding how models of governance developed. A particularly salient point that underpins the analysis is the standing of the leader in relation to the military as a corporate body, with Franco in Spain possessing an advantage over Salazar and Caetano in Portugal due to his military career and standing. The end of the dictatorial regimes and the move towards democracy presented a different set of challenges, as the military came to play important roles in directing the initial process (Portugal) or acting as a potential spoiler (Spain). The control tools that were used to manage civil–military relations (Chapters 4, 5, 7 and 8) were based on the elite’s perception of the military during these periods, seeking to minimise the disruption and uncertainty with the resources available. Although the focus of these chapters is necessarily on the relationship between the regime and the military, the role of wider society in shaping their respective actions could have been brought out more fully as a factor shaping the context. In the concluding section (Chapters 9 and 10), the book returns to a comparison of the two countries in order to assess their management of civil–military relations. Drawing on the detailed case study analysis Olivas Osuna argues that while macro-historical events created ‘critical junctures’ enabling change, these opportunities needed to be recognised and acted on by ‘individuals and institutions within the system’ (205). This leads to the point that while change was likely at certain points, the direction was not predetermined or immediately apparent. During the transitional period there was a greater degree of convergence between the two regimes, as decisions moved from the ruler’s preferences to more institutionalised patterns of operation. Concluding the book, it is argued that although past experience is a useful guide to potential decisions there is no single style that can be discerned between the cases, pointing to the need for detailed consideration of the way in which specific critical junctures are interpreted and translated through to forms of governance. The analysis of forms of control of the military in these two regimes is novel and makes a useful contribution to the existing literature. This book will be of interest to researchers concerned with the nature of civil–military relations in non-democratic and democratising regimes. The framework developed also has potential applications in the consideration of longer term change in other policy areas.
Towards an Infrastructure to Support Big Data for a Smart City Project

The spread of projects focused on smart cities have grown in recent years. With this, the massive amount of data generated in these initiatives, creates a degree of complexity in how to manage all this information. In this paper we propose an infrastructure model for big data for a smart city projet. The goal of this model is to present the stages for the processing of data in the step of extraction, storage, processing and visualization, as well as the types of tools needed for each phase. To implement our proposed model, we used the Particip ACT Brazil a project based in smart cities. This project uses different databases to compose its big data and uses this data to seek solutions to urban problems. We observe that our model provides a structured vision of the software to be used in big data server of ParticipACT Brazil. In addition, we can also note that our model can be used in other big data servers.
Regression kernel for prognostics with support vector machines

Estimating the remaining useful life (RUL) of systems and/or equpipments has been an important goal for reliable, safe, and profitable operation of industrial plants. However, traditional mathematical and statistical modeling based approaches are difficult to design and they adapt poorly to the ever changing operating and environmental conditions in real-world industries. With recent developments in computational technologies, data storage, and industrial automation recording and storage of large amounts of historical plant data from embedded sensors and maintenance records have become easy. Availability of large data sets together with advancements in data driven machine learning algorithms has been the key driver for prognostic and diagnostic research in the industry as well as by academia. Nevertheless, developing generalized machine learning algorithms for the prognostic domain has been challenging due to the very nature of the problem. This paper describes some of these challenges and proposes a modified regression kernel that can be used by support vector regression (SVR) for prognostic problems. The method is tested on a simplified simulated time-series data set that is modeled to represent the challenges presented.
Premedication with fentanyl-midazolam improves sevoflurane anesthesia for surgical intervention in laboratory mice

Balanced anesthesia allows for a reduced dosage of each component, while inducing general anesthesia of sufficient depth with potentially fewer side effects. Here, we compare two anesthetic protocols combining sevoflurane anesthesia with pre-medication (ketamine [K] or fentanyl-midazolam [FM]) to a sevoflurane monoanesthesia (S) concerning their ability to provide reliable anesthesia suitable for moderate surgery in laboratory mice. Twenty-one female C57BL/6J mice assigned randomly to one of three protocols underwent a 50-min anesthesia and a sham embryo transfer. Heart rate and core body temperature were continuously recorded by telemetry intra-operatively and for three days pre- and three days post-surgery. Intra-operative respiratory rate was determined by counting thorax movements. Body weight, food, and water intake were measured daily for three days pre- and three days post-surgery. The heart rate in the KS group remained at baseline level throughout the 50-min of anesthesia and surgery. FMS caused a lower heart rate and S alone caused a higher heart rate compared to baseline values. Intra-operative body temperature was at baseline levels in all groups. A decreased respiratory rate was observed in all groups compared to baseline values obtained from resting mice of the same strain, sex and age-distribution. Surgical stimuli induced no significant changes in heart rate and respiratory rate in the KS or FMS group but significant respiratory alteration in the S group compared to baseline values obtained 10 s before applying the stimulus. Post-operative heart rate was above baseline values in all groups; with a significant deviation in the S group. There were no changes in body weight, food, and water intake. In summary, FMS was superior to KS and S for moderate surgery in laboratory mice resulting in less inter-individual variability in response to painful stimuli. Fentanyl and midazolam reduced the depressant effect of sevoflurane on the respiratory rate and the negative post-anesthetic effects on the heart rate. Impact statement With approximately 65 million animals used per year mice are still the most prevalent laboratory mammal species worldwide. In course of biomedical research projects approximately 40% of mice will undergo one or more short or long-term anesthesia. Sufficient anesthetic depth, cardiovascular stability, adequate analgesia, and short recovery times are essential requirements of anesthetic protocols to meet animal welfare. Anesthesia in mice and rats are only to be performed by personnel with appropriate basic training and experience. However, more and more adapted and advanced anesthetic protocols, required to answer very specific scientific questions, often exceed the skills acquired through basic training and present a major challenge to researchers. It is therefore of great importance to further develop and evaluate safe and reliable anesthetic protocols as presented in this study to provide new perspectives on this challenging problem.
Plasma CC‐chemokine ligand 28 level is correlated with hematopoietic stem cells in human cord blood

CC‐chemokine ligand 28 (CCL28) was previously identified as a novel growth factor in vitro for hematopoietic stem cells (HSCs) from cord blood (CB). However, there is no report on the relationship between CCL28 and HSCs in a human body.
The Sport Concussion Assessment Tool 5th Edition (SCAT5): Background and rationale

This paper presents the Sport Concussion Assessment Tool 5th Edition (SCAT5), which is the most recent revision of a sport concussion evaluation tool for use by healthcare professionals in the acute evaluation of suspected concussion. The revision of the SCAT3 (first published in 2013) culminated in the SCAT5. The revision was based on a systematic review and synthesis of current research, public input and expert panel review as part of the 5th International Consensus Conference on Concussion in Sport held in Berlin in 2016. The SCAT5 is intended for use in those who are 13 years of age or older. The Child SCAT5 is a tool for those aged 5–12 years, which is discussed elsewhere.
Multiobjective optimization: Redundant and informative objectives

In multiobjective optimization there is often the problem of the existence of a large number of objectives. For more than two objectives there is a difficulty with the representation and visualization of the solutions in the objective space. Therefore, it is not clear for the decision maker the trade-off between the different alternative solutions. Thus, this creates enormous difficulties when choosing a solution from the Pareto-optimal set and constitutes a central question in the process of decision making. Based on a statistical method, Principal Component Analysis, the problem of reduction of the number of objectives is addressed. Several test examples with different number of objectives have been studied in order to evaluate the process of decision making through these methods. Preliminary results indicate that this statistical approach can be a valuable tool on decision making in multiobjective optimization.
Examining prescribed rest as treatment for adolescents who are slow to recover from concussion

Abstract Objective: Rest is a widely recommended treatment for concussion, but its utility is unclear following the acute stage of recovery. This study examined the effects of 1-week of prescribed rest in concussed adolescent athletes. Method: Participants were 13 adolescent athletes with persistent symptoms following a concussion. More than three-quarters (77%) had self-reported ADHD, learning disability or two prior concussions. All completed ImPACT® at another facility, but none completed a period of comprehensive rest prior to examination at a specialty practice. Three time points of test data were compared, to control for possible spontaneous recovery: Test 1 (external facility), Test 2 (before prescribed rest) and Test 3 (following prescribed rest). Results: Repeated measures ANOVAs revealed a significant effect of prescribed rest on all ImPACT® composite scores and the total symptom score. Post-hoc analyses revealed no significant differences between Time 1 and Time 2, whereas significant differences were present after prescribed rest. Following prescribed rest, having two or more reliably improved cognitive test scores or having improved symptoms was present in eight of the 13 patients (61.5%). Conclusions: A substantial percentage of adolescents with persistent symptoms following concussion showed improvement in symptoms and cognitive functioning following education, reassurance and 1-week of prescribed rest.
Stable, high-Q fabry-perot resonators with long cavity based on curved, all-silicon, high reflectance mirrors

For the first time, we demonstrate experimentally high optical quality factor Q ∼9000 in MEMS-compatible silicon Fabry-Pérot (FP) resonators based on free space propagation of light and direct coupling to optical fiber. This result is obtained on long cavity resonators (L > 250 µm), a usually difficult case in terms of power loss. The resonator design includes two multilayered silicon-air Bragg mirrors of cylindrical shape, combined with a Fiber Rod Lens (FRL). Dimensions are chosen according to stability criteria imposed on the optical resonator. The core of the presented device is entirely made of single-crystal silicon. It is obtained by DRIE using an optimized single step process.
Evaluating Business Models: Evidence on User Understanding and Impact to BPM Correspondence

Representation and formalization of value models and constellations do not only affect companies' strategies. Even within the process level, the contribution of activities to the value chain has to be obvious to enhance understanding. One important aspect to reach correspondence between the strategic value-oriented business model level and business process level is consistency in modeling. Therefore, the quality of value models to users' perception and perceived impact to business processes has become obvious. Therefore, the paper's contribution is to evaluate the perceived quality of two value models, i.e. e^3 value and the Resource Event Agent (REA) model to a consistent modeling. Based on an experiment, it is shown that both models show a high user understanding. Understanding is not only limited to business models, but also on business processes. In conclusion, the results contribute to an integration of value models in current enterprise models.
Regression Analysis When Covariates Are Regression Parameters of a Random Effects Model for Observed Longitudinal Measurements

Summary. We consider regression analysis when covariate variables are the underlying regression coefficients of another linear mixed model. A naive approach is t o use each subject's repeated measurements, which are assumed to follow a linear mixed model, and obtain subject‐specific estimated coefficients to replace the covariate variables. However, directly replacing the unobserved covariates in the primary regression by these estimated coefficients may result in a significantly biased estimator. The aforementioned problem can be evaluated as a generalization of the classical additive error model where repeated measures are considered as replicates. To correct for these biases, we investigate a pseudo‐expected estimating equation (EEE) estimator, a regression calibration (RC) estimator, and a refined version of the RC estimator. For linear regression, the first two estimators are identical under certain conditions. However, when the primary regression model is a nonlinear model, the RC estimator is usually biased. We thus consider a refined regression calibration estimator whose performance is close to that of the pseudo‐EEE estimator but does not require numerical integration. The RC estimator is also extended to the proportional hazards regression model. In addition to the distribution theory, we evaluate the methods through simulation studies. The methods are applied to analyze a real dataset from a child growth study.
On mobile instant video clip sharing with screen scrolling

Nowadays technology advances of wireless networking and mobile devices have made anytime anywhere data access become readily available. This also enables crowdsourced content capturing and sharing, especially for such multimedia data as video. One example is Twitter's Vine, which mainly target mobile devices, allowing users to create ultra-short video clips and instantly share with their followers. In this paper, we take an initial study on this new generation of mobile instant video clip sharing service and explore the potentials towards its further enhancement. We closely investigate its unique mobile interface, featured user behaviors with screen scrolling, revealing the key differences between Vine-enabled anytime anywhere data access patterns and that of traditional counterparts. We then examine the scheduling policy to maximize the user watching experience as well as the cost efficiency. We show that the generic scheduling problem involves two subproblems, namely, pre-fetching scheduling and watch-time download scheduling, and develop effective solutions towards both of them. The superiority of our solution is demonstrated by extensive trace-driven simulations. To the best of our knowledge, this is the first work on modeling and optimizing the view experience of the instant video clip sharing service on mobile devices.
Characterization of infectious bursal disease virus isolates from Indonesia indicates the existence ofvery virulent strains with unique genetic changes

Sequencing of the hypervariable region of viral protein VP2 of infectious bursal disease virus (IBDV) isolates obtained from non-vaccinated chickens in Indonesia showed that the majority (16/17) were closely related topublished very virulent (vv)IBDV strains. Four isolates contained identical amino acid sequences to Asian andEuropean wIBDVs, sharing w-specific amino acid residues 222(Ala), 256(Πe), and 294(Πe). Eight isolatesdiffered by one amino acid at position 222(Ala->Ser); however, this change did not alter the pathogenicity orantigenicity of these strains. Two isolates, with amino acid substitutions at positions 272(Π→Thr) and279(Asp→Asn), did not cause clinical disease or mortality, and were therefore considered to be naturallyoccurring, attenuated mutants of vvIBDV. The results illustrate variability that might occur among vvIBDVstrains.
PREDICTION EQUATIONS FOR SINGLE BREATH DIFFUSING CAPACITY D L CO (T L CO) IN A MIDDLE AGED CAUCASIAN POPULATION

Rationale : There are many reference equations for the measurement of D L CO. However the testing methodologies vary and there are no well-documented studies that develop reference equations for D L CO and alveolar volume (V A ) in middle aged and older populations. Objectives : 1. Develop reference equations for D L CO in a middle aged population using the current ATS/ERS guidelines; 2. Compare the equations with those commonly used in laboratories around the world. Methods : Healthy subjects (498 male and 474 female) aged 45 to 71 years were recruited as part of a larger epidemiological study. All participants completed a respiratory questionnaire and had spirometry and single breath D L CO (corrected for haemoglobin) measurements following ATS/ERS guidelines. Results : The mean age was 58 years for males and 57 years for females. For males, factors that predicted D L CO were: Height, Age and Age * Height interaction and being an ex-smoker. For females, factors that predicted D L CO were: Height, Age, Weight and an Age * Height interaction. Conclusion : We have described new prediction equations for D L CO in a middle-aged population that require validation in other populations.
Mining Frequent 3D Sequential Patterns

We propose a mining approach, MSP, to find the maximal sequential 3D patterns with the constraints of minimum support and minimum confidence. Each pattern is a group of similar sequential 3D objects appearing in a given dataset. Mining sequential patterns in terms of 3D coordinates is important and meaningful in many real-life applications. MSP finds out the maximal patterns in terms of both length and frequency without loss. MSP involves three stages: generating seeds with pairwise pattern mining, vertical extension to detect all hits with a depth-first search and horizontal extension to extend the pattern length without loss of hits. Furthermore, we propose a method to automatically detect proper settings in order to adapt MSP to various datasets. The experiments on protein chains and synthetic data show MSP significantly outperforms the alternative methods. We apply MSP to protein family classification and pattern mining in spatial moving objects. The obtained patterns correctly classify the protein families on all the tested binary-class datasets. Sample patterns in protein structures and spatial moving objects are presented