Miracle-dz/UniFAR-FTUs huggingface dataset:
Respiration in Macaca mulatta (Rhesus Monkey)

Summary 1. The average respiratory rate, tidal air, and minute volume were measured in 39 unanesthetized, untrained, young monkeys (Macaca mulatto,) with an average weight of 2.63 kg (a- = ± 0.41 kg, e= ± 0.07 kg). 2. Expressing the tidal air or minute volume in terms of body weight in kilograms, body surface area in square meters, or body weight in kilograms raised to the 0.73 power resulted in practically identical coefficients of variation. 3. The mean values observed were as follows: a. Respiratory rate: 37 per minute (a=± 6.6; e= ± 1.1). b. Tidal air: 10.1 cc per kg (<r = ± 2.8 cc; e = ±0.5 cc) or 119.6 cc per square meter (a = ± 33.4 cc; ε = ± 5.3 cc). c. Minute Volume: 383 cc per kg (o- = ± 129 cc; ε = ± 21 cc) or 4532 cc per square meter (o- = ± 1554 cc: e = ± 248.8 cc) or 498.7 cc per kg body weight raised to the 0.73 power (a- = ± 173.2 cc; ε = ±27.7 cc). 4. No correlation was found between the animals' pulse rate (mean = 215 per minute) (a = ±27; t = ±4.5), which was intended as an index of excitability, and any of the respiratory data. 5. The respiratory rate, tidal air. and minute volume were significantly inhibited in monkeys exposed to a phosgene concentration of 1.38 mg/1. 6.a. The mean heat production determined by the indirect method in 4 unanesthetized, untrained, tracheotomized macaques with an average weight of 3.49 kg was 85.76 Cals/ kg/24 hrs and 1137.29 Cals/sq.M/24 hrs— approximately 180% of the basal values reported in the literature. b. The mean heat production of the same macaques sedated with 10 mg/kg of nembutal intraperitoneally was 92.77 Cals/ kg/24 hrs and 1202.08 Cals/sq.M/24 hrs. 7. The average coefficient of oxygen utilization in these 4 monkeys was 2.10% for the non-sedated and 2.40% for the nembutalized macaques.
Online density estimates: a probabilistic condensed representation of data for knowledge discovery

The Internet of Things (IoT) and the data that is generated from its sensors are making new demands on data mining methods. These demands stem from the desire to benefit from the knowledge contained in this data and the increasing number of devices that are equipped with these sensors. According to companies like Intel or HP, the number of sensors worldwide is likely to reach more than one trillion by 2022. All of them will produce streams of measurements and leveraging knowledge from these streams requires infrastructure to analyze them in real-time. From a data mining perspective, this involves challenging tasks such as cleaning the data, handling large amounts of data, and preserving their privacy, to name a few. The state of the art in data mining already addressed some of these challenges, but the proposed methods are typically designed for a specific task (e.g., predicting a certain variable or finding frequent patterns) and perform this task while scanning the data stream. However, at the time of collecting the data, it is often not known what kind of analysis needs to be performed or there are several – possibly even dependent – analysis tasks. This means that whenever storing the original data is either not feasible due to the sheer volume or impossible due to privacy concerns, the user has to wait for more data to initiate another analysis task, which impedes the use of conventional data mining algorithms. Therefore, we present a framework in this thesis, called MiDEO (Mining Density Estimates inferred Online), which decouples the process of collecting the data from the actual analysis. It uses density estimates to maintain a compact representation of the data stream and provides inference capabilities to perform queries on them. The queries can be combined to complex data mining tasks and allow to adapt the estimates to the current needs of the user or the algorithm. Compared to current methods that typically focus on one task at a time, this enables a more interactive analysis of the data stream, where the task selection is part of the analysis. In the course of designing such a framework, we develop several methods to improve the state of the art. This includes online density estimators for conditional joint densities with mixed types of variables, an online density estimator for high-dimensional data, algorithms to perform pattern mining on online density estimates, an online density estimator that is able to represent recurrences in the data stream, and algorithms that enforce well-known privacy-preserving properties to protect the entities described by the data. To show the effectiveness of these methods, we prove some of their theoretical properties and perform an extensive set of experiments.
"Pokémon Go!" May Promote Walking, Discourage Sedentary Behavior in College Students.

OBJECTIVE To assess self-reported walking and sedentary behavior in young adults before and after downloading "Pokémon Go! ". MATERIALS AND METHODS In September 2016, a sample of 358 (19.8 ± 2.1 years old, n = 187 females) college students who had downloaded "Pokémon Go! " on their cellular telephones (i.e., cell phones) were surveyed for weekly walking and sedentary behavior via the International Physical Activity Questionnaire. A single interview was administered to participants who estimated their walking and sedentary behavior at three time points: the week immediately preceding their download of "Pokémon Go! " (Baseline), the first week after downloading the game (Time 1), and the week the survey was completed (Time 2). Differences in self-reported physical activity and sedentary behavior across the three time points and across the two genders were compared via analyses of variance. RESULTS There was a significant main effect of time (F ≥ 49.3, P ≤ 0.001) for walking and sedentary behavior. Participants reported greater (t ≥ 9.5, P < 0.001) daily walking during Time 1 (218.6 ± 156.3 minutes) and Time 2 (182.7 ± 172.1 minutes) versus the baseline (108.5 ± 110.8 minutes). Walking behavior was also significantly greater (t = 4.1, P < 0.001) at Time 1 versus Time 2. Participants reported greater (t ≥ 6.5, P < 0.001) daily sedentary behavior during baseline (346.6 ± 201.3 minutes) versus both Time 1 (261.7 ± 172.4 minutes) and Time 2 (284.3 ± 175.4 minutes). Sedentary behavior was also significantly greater (t = 2.6, P = 0.03) at Time 2 versus Time 1. There were no effects of gender (F ≤ 1.8, P ≥ 0.17). CONCLUSION Playing "Pokémon Go! " was associated with increased self-reported walking and decreased sedentary behavior. Such games hold promise as technology that may promote physical activity and discourage sedentary behavior.
Diving bradycardia in man.

It has been known for many years that aquatic animals show a marked fall in heart rate on immersion in water. Paul Bert (1870) observed that in the duck 'the heart, which was beating before immersion about 100 times per minute, does not give more than fourteen regular and deep beats'. Diving bradycardia has since been described in the seal, duck, water snake, porpoise and musk rat, and Irving, Scholander & Grinnell (1941) have reported its occurrence in man. The mechanism of the phenomenon does not appear to have been elucidated. That slowing is produced by increased vagal activity is illustrated by the finding that it is abolished by atropine (Murdaugh, Seabury & Mitchell, 1961), but the afferent side of the reflex remains obscure. Irving, Scholander & Grinnell (1942) postulate a conditioned response due to higher centre activity inducing bradyeardia and peripheral vasoconstriction in order to conserve oxygen stores; Johansen (1959) finds in the snake that the apnoea and wetting of the nostrils play a part. In the present investigation of diving bradycardia in the human subject, the cardiovascular responses to breath-holding have been examined both in air and in water at various depths of immersion. The results provide an explanation of the mechanism of the response. A preliminary account of this work has been presented to the Australian Physiological Society (Harding & Roman, 1961).
A Comparison of the Activity of Soil Fungal Isolates Against Three Insect Pests

Abstract Entomopathogenic fungi (e.f.) are important agents of biological control of insects. Two aspects, among others, are important for the use of e.f. against insect pests: the logistics of e.f. strain acquisition, and the activity of individual strains against multiple insects. Soil is the natural reservoir for many e.f. , but only few strains used against insect pests originate from soil; most have been isolated from insects. Also, there are few reports that simultaneously compare the activity of individual strains of e.f. (of insect or soil origin) against more than one insect species. This is important for the deployment of e.f. in agroecosystems, where simultaneous control of several insect pests is very often desirable. In this work we determined and compared the simultaneous activity of local strains of e.f. (isolated from soil or insects at Saltillo, Mexico) against important regional pests: fall armyworm, Spodoptera frugiperda, greenhouse whitefly, Trialeurodes vaporariorum, and potato psyllid, Bactericera cockerelli. Against all three insects, one Beauveria bassiana strain from soil was as active as or more active than other B. bassiana and Metarhizium anisopliae strains from insect or soil origin. In some localities, native individual strains of e.f. from soil might have good activity against multiple local insect pests. We recommend the isolation and testing of local soil strains of e.f. for use in local biocontrol projects.
The Role of t(11;14) in Tailoring Treatment Decisions in Multiple Myeloma

Simple Summary The presence of t(11;14) in MM is a significant genetic abnormality and plays an essential role in tailoring treatment decisions. t(11;14) is present in 15% to 20% of MM and is associated with an upregulation of cyclin D1, leading to tumor cell proliferation. Patients harboring t(11;14) often exhibit clinical characteristics that position them between standard- and high-risk categories. Moreover, t(11;14) is associated with higher levels of BCL2, and published data demonstrate that t(11;14) is predictive of the BCL2 dependency. A better understanding of this genetic abnormality influences the choice of therapeutic approaches. In recent studies, the impact of t(11;14) on treatment responses was evident, which emphasize its role in shaping therapeutic strategies. In this review, we highlight the association of t(11;14) with other molecular abnormalities, raise questions about the predictive and prognostic value of t(11;14) in MM and summarize current clinical studies of BCL2 inhibitors in terms of efficacy and safety. Abstract Multiple myeloma (MM) represents a hematological neoplasia with an uncontrolled proliferation of malignant plasma cells and complex cytogenetic abnormalities. t(11;14) has emerged as a crucial genetic aberration and is one of the most common primary translocations in MM. Patients harboring t(11;14) represent a distinctive subgroup with a clinical profile that differs from t(11;14)-negative MM risk categories. One of the key features linked with t(11;14) is the BCL2 dependency, indicating vulnerability to BCL2 inhibition. BCL2 inhibitors, such as venetoclax, demonstrated impressive efficacy alone or in combination with other anti-myeloma drugs in patients with RRMM accompanied by t(11;14) and BCL2 overexpression. Therefore, t(11;14) plays a key role in both risk stratification and informed decision making towards a tailored therapy. In this review, we highlight the biology of t(11;14) in MM cells, summarize the current evolving role of t(11;14) in the era of novel agents and novel targeted therapies, illuminate current efficacy and safety data of BCL2-based treatment options and explore the future prospects of individualized precision medicine for this special subgroup of patients with MM.
Modeling of human heart rate variability enhanced using stochastic sleep architecture properties

Human sleep consists of four characteristic phases: light (L), deep (D), REM sleep and almost-awake state (W) with additional arousal episodes (Exc). All of these elements create a nontrivial, complex structure, the statistical properties of which were studied here carefully. We observed a different behavior of heart rate variability for each phase. Thus, we should take these specific properties of sleep architecture into consideration while modeling heart rate variability.We analyzed 34 simultaneous heart rate variability and 30 EEG nighttime recordings from healthy adults. EEG provides accurate information about sleep phases. The main idea behind our sleep architecture reconstruction is to consider two properties: probabilities of transitions between all possible pairs of phases and probability distribution of phase durations. We calculated the probabilities of transition between each pair of phases and we aggregated them into two probability matrices (separately for each half of the sleep period because the character of the inter-phase transitions is diferent in early and late sleep). We found also that the probability distribution of L, D and REM sleep duration are described by a gamma distribution and that of the W phase - by a Pareto distribution. To generate the RR intervals for every sleep phase, we use the model described in [1j. We consider three variants: (a) periodic sleep cycles with the sequences of phases: L, D, REM, W in each cycle, (b) a randomized distribution of phases, (c) the architecture based on our model. The results show that variant (c) gives 50% of the time series indistinguishable from real data using all standard linear and nonlinear HRV assessment methods while for variants (a) and (b) we obtain 41% and 3% accordingly.
International Journal of Biological & Medical Research Branching Pattern of the Colic Branches of Superior Mesenteric Artery-a Cadaveric Study A* B C D

Original Article PURPOSE: A thorough knowledge of the anatomy of colonic mesenteric arteries is necessary to accomplish successful uncomplicated abdominal operations, especially laparoscopic colonic resections in which the mesenteric vessels can't be palpated. Such knowledge is also important when performing a colonic resection for cancer using proximal vascular ligation and wide en bloc resection. Most surgical textbooks depict a "normal pattern" of arterial supply to the ascending and right 2/3 of transvesre colon consists of three arterial branches the ileocolic artery(ICA), right colic artery(RCA) and the middle colic artery(MCA) arising independently from the superior mesenteric artery (SMA). Based on the literature, there are only two colonic arteries arising independently from the SMA in many cases. METHOD: In this study we mainly observed the branching pattern of colic branches of superior mesenteric arteries in 50 embalmed cadavers. RESULTS: In 90% cases the middle colic artery and in 66% the ileocolic artery arose directly from the SMA, the most variable artery was the RCA. In 46% cases, the RCA arose as a direct branch from SMA where as in 10% cases it formed a common stem with MCA and in 34% with ICA. The RCA was absent in 10% of cases. CONCLUSION: Knowledge of the colic vascular territories of the mesenteric arteries has a special interest in surgical practice because of the difficult post-operatory revitalization of the colon. Therefore these findings will be of great help for surgeons and radiologists
A Circle of Learning

‘ow do students learn what they are supposed to do in a . game situation? How do coaches and teachers structure practice sessions to make sure that everything is covered? How do they get their players to learn the skills and tactics they need in order to be successful? How do they ensure that they are providing information in a way that makes learning possible for all players? For anyone who teaches physical education, coaches a sport, or plans to do either in the future, these are just some of the major questions that, when answered, can determine the difference between winning and losing, satisfaction and frustration. This article describes a way of creating a comprehensive physical education program based on current research on learning styles and current sportinstruction strategies. For the purposes of this discussion, the term “instructor” will indicate both teachers and coaches, and students and athletes will be referred to as “players. ”
Monitoring asthma in children: what does BATMAN tell us?

The importance of monitoring asthma and adjusting treatment according to control is a fundamental part of asthma management and many studies have demonstrated the benefits of achieving good control. Numerous tools can be used, including spirometry, inflammometry, airway hyper-responsiveness and validated questionnaires of asthma control and asthma-related quality of life. In practice, the clinician uses a combination of some (or none! ) of these. However, the evidence of the utility of most of these is lacking, particularly in children. Studies that have been carried out are hampered by a number of constraints: first, there is no gold standard for asthma control. The Global Initiative for Asthma (GINA) definition of controlled, partially controlled or uncontrolled is often used.1 This is a composite measure, including symptoms, exacerbations and lung function, which was developed for adults and has not been validated in children. It is not universally used to assess the usefulness of monitoring strategies and a variety of end points, including exacerbations, symptom-free days (SFD), inhaled corticosteroid (ICS) dose and FEV1, have been reported. Second, studies tend to evaluate each measure in isolation: lung function or measurement of exhaled nitric oxide (FeNO) versus standard care and so on and there is limited evidence as to how the various components of control should be integrated. Third, the term ‘standard care’ is also open to much interpretation. The BATMAN …
A Comparative Analysis on the Evaluation of Classification Algorithms in the Prediction of Students Performance

Objectives: Data mining techniques are implemented in many organizations as a standard procedure for analyzing the large volume of available data, extracting useful information and knowledge to support the major decision-making processes. Data mining can be applied to wide variety of applications in the educational sector for the purpose of improving the performance of students as well as the status of the educational institutions. Educational data mining is rapidly developing as a key technique in the analysis of data generated in the educational domain. Methods: The aim of this study presents an analysis of final year results of UG degree students using data mining technique, which carried out in three of the private colleges in Tamil Nadu state of India. The primary objective of this research work is to apply the classification techniques to the prediction of the performance of students in end semester university examinations. Particularly, the decision tree algorithm C4.5 (J48), Bayesian classifiers, k Nearest Neighbor algorithm and two rule learner’s algorithms namely OneR and JRip are used for classifying the performance of students as well as to develop a model of student performance predictors. Results: The result of this study reveals that overall accuracy of the tested classifiers is above 60%. In addition classification accuracy for the different classes reveals that the predictions are worst for distinction class and fairly good for the first class. The JRip produces highest classification accuracy for the Distinction. Classification of the students based on the attributes reveals that prediction rates are not uniform among the classification algorithms. Also shows that selected data attributes have found to be influenced the classification process. The results showed to be satisfactory. Improvements: The study can be extended to draw the performance of other classification techniques on an expanded data set with more distinct attributes to get more accurate results.
Low-intensity farming systems in the conservation of the countryside

The historical role of agriculture in creating semi-natural vegetation is still not fully appreciated by many ecologists, conservationists, policy-makers or the general public. Nor is the fact that for many European landscapes and biotopes of high nature conservation value, the only practicable, socially acceptable and sustainable management involves the continuation of low-intensity farming. Consequently, too much emphasis is placed on attempting to ameliorate damaging effects of agricultural management rather than supporting ecologically sustainable low-intensity farming practices. More than 50% of Europe's most highly valued biotopes occur on low-intensity farmland. However, most of this farmland has no environmental policy directly affecting it; most management decisions are taken by farm businesses and determined primarily by European and national agricultural officials. As a result, there continues to be intensification or abandonment of traditional practices, changes which are equally damaging to the nature conservation value. However, the nature conservation importance of low-intensity farming systems is gradually being recognized. Reforms and reviews of agriculture policy are providing a variety of potential opportunities for maintaining such systems. Unfortunately, initiating change through policy is a slow process. There is therefore also a pressing need to look for other opportunities to maintain surviving systems and, where poss-. ible, to reinstate those recently lost. Although these systems may be considered low-intensity in terms of chemical inputs and productivity, they are usually high-intensity in terms of human labour. Therefore, the processes that make the low-intensity farmed countryside biologically rich and diverse must be understood, but at the same time mechanisms to make life easier and more rewarding for the people who work such farmland must be found. Ecologists and conservationists should think less of'remnants of habitat being left amongst farmland' and more of a farmland biotope for which optimum management practices need to be developed. At the same time the current emphasis on site-based conservation should be complemented by strategic initiatives that promote wise management of the wider countryside.
Learning to Handle Exceptions

Exception handling is an important built-in feature of many modern programming languages such as Java. It allows developers to deal with abnormal or unexpected conditions that may occur at runtime in advance by using try-catch blocks. Missing or improper implementation of exception handling can cause catastrophic consequences such as system crash. However, previous studies reveal that developers are unwilling or feel it hard to adopt exception handling mechanism, and tend to ignore it until a system failure forces them to do so. To help developers with exception handling, existing work produces recommendations such as code examples and exception types, which still requires developers to localize the try blocks and modify the catch block code to fit the context. In this paper, we propose a novel neural approach to automated exception handling, which can predict locations of try blocks and automatically generate the complete catch blocks. We collect a large number of Java methods from GitHub and conduct experiments to evaluate our approach. The evaluation results, including quantitative measurement and human evaluation, show that our approach is highly effective and outperforms all baselines. Our work makes one step further towards automated exception handling.