Miracle-dz/UniFAR-FTUs huggingface dataset:
Is risk of fast bowling injury in cricketers greatest in those who bowl most? A cohort of young English fast bowlers

Objectives: To determine whether young fast bowlers are exceeding directives limiting bowling and how incidence of fast bowling injury varies with amount of bowling. Methods: A prospective cohort study of injuries sustained by 70 fast bowlers (mean (SD) age 15.3 (2.4) years) was undertaken. Bowlers were recruited from the Centres of Excellence of three “First Class” counties in England in January 1998. Details of injuries were collected by telephone questionnaire every six weeks for six months from each bowler. The number of balls bowled in matches and practices by each bowler was recorded. The cohort was divided into groups according to the number of balls bowled in the study period, and bowling injury incidences were calculated for each group. Main outcome measures: All injuries caused by bowling and interfering with bowling. Results: Telephone follow up was achieved when planned on 97.9% of occasions. There were 23 bowling injuries reported in the study period that met the inclusion criteria. The overall incidence of bowling injury in the study period was 32.8 per 100 fast bowlers. The incidence of bowling injury for the 15 bowlers who bowled less than 1000 balls in the study period was 20.0 per 100 fast bowlers. The incidence for the 32 who bowled 1000–2000 balls was 37.5 per 100 fast bowlers. The incidence for the 14 who bowled 2000–3000 balls was 35.7 per 100. The incidence for the nine who bowled more than 3000 balls was 33.3 per 100. Conclusions: The expected increased incidence of bowling injury in young fast bowlers who bowl most was not observed, although more than 12% exceeded the recommended limit.
A trainable system for object detection in images and video sequences

This thesis presents a general, trainable system for object detection in static images and video sequences. The core system finds a certain class of objects in static images of completely unconstrained, cluttered scenes without using motion, tracking, or handcrafted models and without making any assumptions on the scene structure or the number of objects in the scene. The system uses a set of training data of positive and negative example images as input, transforms the pixel images to a Haar wavelet representation, and uses a support vector machine classifier to learn the difference between in-class and out-of-class patterns. To detect objects in out-of-sample images, we do a brute force search over all the subwindows in the image. This system is applied to face, people, and car detection with excellent results. For our extensions to video sequences, we augment the core static detection system in several ways (1) extending the representation to five frames, (2) implementing an approximation to a Kalman filter, and (3) modeling detections in an image as a density and propagating this density through time according to measured features. In addition, we present a real-time version of the system that is currently running in a DaimlerChrysler experimental vehicle. As part of this thesis, we also present a system that, instead of detecting full patterns, uses a component-based approach. We find it to be more robust to occlusions, rotations in depth, and severe lighting conditions for people detection than the full body version. We also experiment with various other representations including pixels and principal components and show results that quantify how the number of features, color, and gray-level affect performance. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
A novel approach to measuring class cohesion based on dependence analysis

Classes are the basic modules in object-oriented (OO) software, which consist of attributes and methods. Thus, in an OO environment, cohesion mainly concerns how tight the attributes and methods of classes are. This paper discusses the relationships between attributes and attributes, attributes and methods, and methods and methods of a class based on dependence analysis. Then we discuss the properties of these relationships. According to these properties, this paper proposes a novel approach to measuring class cohesion. Our approach overcomes the limitations of previous class cohesion measures, which consider only one or two of the three relationships in a class. We also prove that this measure satisfies the properties that a good measurement should have.
Model‐Informed Development and Registration of a Once‐Daily Regimen of Extended‐Release Tofacitinib

Extended‐release (XR) formulations enable less frequent dosing vs. conventional (e.g., immediate release (IR)) formulations. Regulatory registration of such formulations typically requires pharmacokinetic (PK) and clinical efficacy data. Here we illustrate a model‐informed, exposure–response (E‐R) approach to translate controlled trial data from one formulation to another without a phase III trial, using a tofacitinib case study. Tofacitinib is an oral Janus kinase (JAK) inhibitor for the treatment of rheumatoid arthritis (RA). E‐R analyses were conducted using validated clinical endpoints from phase II dose–response and nonclinical dose fractionation studies of the IR formulation. Consistent with the delay in clinical response dynamics relative to PK, average concentration was established as the relevant PK parameter for tofacitinib efficacy and supported pharmacodynamic similarity. These evaluations, alongside demonstrated equivalence in total systemic exposure between IR and XR formulations, provided the basis for the regulatory approval of tofacitinib XR once daily by the US Food and Drug Administration.
A Compact Blast-Induced Traumatic Brain Injury Model in Mice

Blast-induced traumatic brain injury (bTBI) is a common injury on the battlefield and often results in permanent cognitive and neurological abnormalities. We report a novel compact device that creates graded bTBI in mice. The injury severity can be controlled by precise pressures that mimic Friedlander shockwave curves. The mouse head was stabilized with a head fixator, and the body was protected with a metal shield; shockwave durations were 3 to 4 milliseconds. Reflective shockwave peak readings at the position of the mouse head were 12 ± 2.6 psi, 50 ± 20.3 psi, and 100 ± 33.1 psi at 100, 200, and 250 psi predetermined driver chamber pressures, respectively. The bTBIs of 250 psi caused 80% mortality, which decreased to 27% with the metal shield. Brain and lung damage depended on the shockwave duration and amplitude. Cognitive deficits were assessed using the Morris water maze, Y-maze, and open-field tests. Pathological changes in the brain included disruption of the blood-brain barrier, multifocal neuronal and axonal degeneration, and reactive gliosis assessed by Evans Blue dye extravasation, silver and Fluoro-Jade B staining, and glial fibrillary acidic protein immunohistochemistry, respectively. Behavioral and pathological changes were injury severity-dependent. This mouse bTBI model may be useful for investigating injury mechanisms and therapeutic strategies associated with bTBI.
Conclusions of 5-year investigations in sliding mode control of manipulators

Sliding mode control is applied in point-to-point motions of robot manipulators. The sliding manifold is defined by nonlinear saturated functions, one for each manipulator joint, taking into account constraints on velocities. To avoid chattering, a continuous PID-like control law is used inside a boundary-layer along the sliding manifold. The stability has been investigated via passivity arguments, and the performance has been shown by experiments on an industrial robot with a 3-DOF anthropoid arm, and on a servomechanism with compliant joint.
Herding, social influence and economic decision-making: socio-psychological and neuroscientific analyses

Typically, modern economics has steered away from the analysis of sociological and psychological factors and has focused on narrow behavioural assumptions in which expectations are formed on the basis of mathematical algorithms. Blending together ideas from the social and behavioural sciences, this paper argues that the behavioural approach adopted in most economic analysis, in its neglect of sociological and psychological forces and its simplistically dichotomous categorization of behaviour as either rational or not rational, is too narrow and stark. Behaviour may reflect an interaction of cognitive and emotional factors and this can be captured more effectively using an approach that focuses on the interplay of different decision-making systems. In understanding the mechanisms affecting economic and financial decision-making, an interdisciplinary approach is needed which incorporates ideas from a range of disciplines including sociology, economic psychology, evolutionary biology and neuroeconomics.
Impact of Ramadan focused education program on hypoglycemic risk and metabolic control for patients with type 2 diabetes

Background Fasting during the month of Ramadan could lead to acute complications and increased hypoglycemic risk of patients with type 2 diabetes. Therefore, diabetes is one of the diseases that need careful observation and special considerations during Ramadan including patients’ education and counseling. Objectives To evaluate the impact of Ramadan focused education program on acute complications and biomedical parameters. Methods A prospective nonrandomized interventional controlled design was run on three phases: before, during, and after Ramadan on 262 type 2 diabetes patients. The intervention group (n=140) received focused individualized diabetic education sessions and antidiabetic medications adjustment before and after Ramadan, while the control group (n=122) received standard diabetic care. A validated hypoglycemia questionnaire was used in both groups to assess the change of the risk. Patients were advised to adjust the dosage and timing of antidiabetic agents according to the recommendations for management of diabetes during Ramadan. Primary outcomes were postintervention change of hypoglycemia score and HbA1c over 6-month follow-up. Data were presented as mean ± standard deviation. HbA1c was expressed in percentage. Results The hypoglycemic scores before, during, and after Ramadan were 14.21±8.50, 6.36±6.17, and 5.44±5.55 in the intervention group, respectively (P<0.001) and 14.01±5.10, 13.46±5.30, and 9.27±4.65 in the control group, respectively (P<0.001). HbA1c levels were 9.79±1.89, 8.26±1.54, and 8.52±1.61 before, during, and after Ramadan in the intervention group, respectively (P<0.001), and 10.04±1.47, 9.54±1.38, and 9.59±1.79 in the control group, respectively (P<0.001). Post-Ramadan reductions of HbA1c and hypoglycemic scores were significantly higher in the intervention group (−13.0% vs −4.5%, P=0.004 for HbA1c and −61.7% vs −33.8%, P<0.001 for hypoglycemic score). Low-density lipoprotein cholesterol improved in the intervention group from 2.41±0.91 mmol/L before Ramadan to 2.28±0.68 mmol/L after Ramadan (P<0.001). No statistically significant effects were observed on blood pressure or body weight in the intervention group. Also, no change was observed in the control group. Conclusion Ramadan educational program had a positive impact with reduction of hypoglycemic risk, HbA1c, and low-density lipoprotein cholesterol. Therefore, it could be recommended for patients with increased risk of hypoglycemia during Ramadan fasting.
A Research to Identify the Relationship between Consumers' Attitude and Mobile Advertising

This present study aims to investigate the relationships between mobile advertising characteristics and consumers’ attitude towards mobile advertising (ATMA). Based on prior literature, a conceptual model was developed to identify factors affecting consumers’ ATMA. 364 samples from Korea, India, and China were collected through online and offline questionnaire and five hypotheses were tested, using hierarchical regression analysis (HRA). Among the key findings, informativeness and credibility had significant impacts on ATMA where as other factors such as entertainment, irritation, and interactivity were not statistically significant.
Surface Rainfall Cold Cloud Fractional Coverage Relationship in TOGA COARE: A Function of Vertical Wind Shear

Abstract Shipboard radar-derived rain rates and satellite-observed IR brightness temperatures have been used to examine the relationship between cold cloud fractional coverage for brightness temperatures <235 K and areally averaged surface rainfall during the Tropical Ocean–Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). A nearly linear relationship was observed with a ratio of mean rain rate to fraction cold cloud coverage of approximately 1 mm h−1. This is in contrast to the GOES precipitation index (GPI) methodology, which assumes a proportionality (GPI slope coefficient) of 3 mm h−1. It was also observed that when considering 5-day timescales, the relationship between the cold cloud fractional coverage and surface rainfall exhibited considerable variability. This variability was in phase with the interseasonal oscillations (ISOs). During the convectively active phase of the ISOs, the deep vertical wind shear (700–150 mb) was strong and the convective organization was domin.
Social media and sales : determining the predictive power of sentiment analysis towards car sales

This paper aims at exploring the use of sentiment analysis on social media as a tool for sales forecasting in the automotive industry. Previous research on this topic has presented significant results although current literature still lacks investigation on the usefulness of this technique when it comes to more expensive items. In particular, about 500,000 social media posts and eleven car models from the Dutch market are analyzed using linear models. Furthermore, the research compares these outcomes to the predictive power of search volume by using Google Trends as an indicator. Based on variables that are assessed as strong predictors of sales a prediction model using decision tree regression is built that can potentially be used by car manufacturers as an addition to traditional forecasting methods if tested and developed further. The results suggest that social media sentiments have little to no predictive power towards car sales. While search volume as well as the rate of attention a model receives on social media show significant results and can be incorporated into the prediction model, the sentiments itself only obtain weak correlations with car sales and clearly show a limitation to the technique of sentiment analysis. Although the findings cannot be generalized for other car models and markets, this research contributes to further understanding the field of sentiment analysis and explores its boundaries. It also presents a prediction model that allows to approximate car sales. It therefore has both practical and academic value.
Outcome of chronic idiopathic thrombocytopenic purpura in children

There is paucity of data on long‐term probability of remission in chronic idiopathic thrombocytopenic purpura (ITP). Aim was to study the course and factors influencing remission of chronic ITP. Chronic ITP was defined as thrombocytopenia persisting >6 months following initial diagnosis.
On distributed concern delivery in user interface design

Increasing demands on user interface (UI) usability, adaptability, and dynamic behavior drives ever-growing development and maintenance complexity. Traditional UI design techniques result in complex descriptions for data presentations with significant information restatement. In addition, multiple concerns in UI development leads to descriptions that exhibit concern tangling, which results in high fragment replication. Concern-separating approaches address these issues; however, they fail to maintain the separation of concerns for execution tasks like rendering or UI delivery to clients. During the rendering process at the server side, the separation collapses into entangled concerns that are provided to clients. Such client-side entanglement may seem inconsequential since the clients are simply displaying what is sent to them; however, such entanglement compromises client performance as it results in problems such as replication, fragment granularity ill-suited for effective caching, etc. This paper considers advantages brought by concern-separation from both perspectives. It proposes extension to the aspect-oriented UI design with distributed concern delivery (DCD) for client-server applications. Such an extension lessens the serverside involvement in UI assembly and reduces the fragment replication in provided UI descriptions. The server provides clients with individual UI concerns, and they become partially responsible for the UI assembly. This change increases client-side concern reuse and extends caching opportunities, reducing the volume of transmitted information between client and server to improve UI responsiveness and performance. The underlying aspect-oriented UI design automates the server-side derivation of concerns related to data presentations adapted to runtime context, security, conditions, etc. Evaluation of the approach is considered in a case study applying DCD to an existing, production web application. Our results demonstrate decreased volumes of UI descriptions assembled by the server-side and extended client-side caching abilities, reducing required data/fragment transmission, which improves UI responsiveness. Furthermore, we evaluate the potential benefits of DCD integration implications in selected UI frameworks.
Dynamics of distribution and performance of ramets constructing genets: a demographic-genetic study in a clonal plant, Convallaria keiskei.

BACKGROUND AND AIMS In clonal plants producing vegetative offspring, performance at the genet level as well as at the ramet level should be investigated in order to understand the entire picture of the population dynamics and the life history characteristics. In this study, demography, including reproduction and survival, the growth patterns and the spatial distributions of ramets within genets of the clonal herb Convallaria keiskei were explored. METHODS Vegetative growth, flowering and survival of shoots whose genets were identified using microsatellite markers were monitored in four study plots for 3 years (2003-2005). The size structures of ramets in genets and their temporal shifts were then analysed. Their spatial distributions were also examined. KEY RESULTS During the census, 274 and 149 ramets were mapped in two 1 x 2 m plots, and 83 and 94 ramets in two 2 x 2 m quadrats. Thirty-eight genotypes were identified from 580 samples. Each plot included 5-18 genets, and most ramets belonged to the predominant genet(s) in each plot. Shoots foliated yearly for several years, but flowering ramets did not have an inflorescence the next year. A considerable number of new clonal offspring persistently appeared, forming a bell-shaped curve of the size structure of ramets in each genet. Comparing the structures modelled by the normal distributions suggested variation among ramets belonging to a single genet and variation among genets. Furthermore, spatial analyses revealed clumped and distant distributions of ramet pairs in a genet, in which the distant patterns corresponded to the linearly elongating clonal growth pattern of this species. CONCLUSION Characteristics of ramet performances such as flowering and recruitment of clonal offspring, in addition to growth, played a large part in the regulation of genet dynamics and distribution, which were different among the studied genets. These might be characteristics particularly relevant to clonal life histories.
Social evolution in micro-organisms and a Trojan horse approach to medical intervention strategies

Medical science is typically pitted against the evolutionary forces acting upon infective populations of bacteria. As an alternative strategy, we could exploit our growing understanding of population dynamics of social traits in bacteria to help treat bacterial disease. In particular, population dynamics of social traits could be exploited to introduce less virulent strains of bacteria, or medically beneficial alleles into infective populations. We discuss how bacterial strains adopting different social strategies can invade a population of cooperative wild-type, considering public good cheats, cheats carrying medically beneficial alleles (Trojan horses) and cheats carrying allelopathic traits (anti-competitor chemical bacteriocins or temperate bacteriophage viruses). We suggest that exploitation of the ability of cheats to invade cooperative, wild-type populations is a potential new strategy for treating bacterial disease.
The early build-up of dust in galaxies: A study of damped Ly α systems

We present a study of the early build-up of dust in high redshift galaxies. The study is based on the analysis of 38 Damped Lyα systems (DLAs) for which we derive the fraction of iron atoms in dust form, f Fe . The sample is representative of metal-poor galaxies in the redshift range 0.6 < z < 3.4 selected on the basis of their absorption HI column density (N(HI) ≥ 2 x 10 20 atoms cm -2 ). We find that the dust fraction increases with metallicity, from f Fe ≃ 0 at [Fe/H] ∼ -2 dex, up to f Fe ≃ 0.9 at solar metallicity; the increase is fast below [Fe/H] ≃ -1 dex and mild at higher metallicities. We also find some evidence for an increase of f Fe with cosmic time; a large fraction of the systems younger than 3 Gyr has f Fe ≤ 0.5. These results indicate that the dust-to-metal ratio increases in the course of chemical evolution, at variance with the hypothesis of an approximately constant dust-to-metal ratio, commonly adopted in models of galactic evolution. This hypothesis is consistent with local and high-redshift data only when the metallicity is relatively high ([Fe/H] ≥ -1 dex). The results of this work suggest that the main mechanisms of dust formation may be rather sensitive to the level of metallicity attained by a galaxy in the course of its chemical evolution. A metallicity-dependent dust production by SNe II seems to be the most promising mechanism to explain the rise of f Fe at [Fe/H] ≤ -1 dex.
Imaging of Fluoride Ion in Living Cells and Tissues with a Two-Photon Ratiometric Fluorescence Probe

A reaction-based two-photon (TP) ratiometric fluorescence probe Z2 has been developed and successfully applied to detect and image fluoride ion in living cells and tissues. The Z2 probe was designed designed to utilize an ICT mechanism between n-butylnaphthalimide as a fluorophore and tert-butyldiphenylsilane (TBDPS) as a response group. Upon addition of fluoride ion, the Si-O bond in the Z2 would be cleaved, and then a stronger electron-donating group was released. The fluorescent changes at 450 and 540 nm, respectively, made it possible to achieve ratiometric fluorescence detection. The results indicated that the Z2 could ratiometrically detect and image fluoride ion in living cells and tissues in a depth of 250 μm by two-photon microscopy (TPM).