Miracle-dz/UniFAR-FTUs huggingface dataset:
Lower Extremity Stiffness: Considerations for Testing, Performance Enhancement and Injury Risk

Force-deformation characteristics of the lower limb have been associated with athletic performance and may modulate the risk of injury. In-spite of these known associations, measurements of lower extremity stiffness are not commonly administered by strength and conditioning coaches. This review provides an overview of the available literature pertaining to the effects of lower extremity stiffness on physical performance and injury risk. Practical methods of monitoring and training stiffness are also discussed. The cumulative body of evidence indicates that increases in lower extremity stiffness are associated with heightened performance in athletic tasks such as hopping, jumping, throwing, endurance running, sprinting and changing direction. Relationships with injury are less conclusive as both excessive and insufficient limb stiffness have been postulated to increase risk. Thus, the ‘optimal’ level of stiffness appears to be dependent on the anthropometry, and physical capabilities of the athlete, in addition to sport-specific activity demands. Training interventions can positively enhance lower extremity stiffness, including isometric, eccentric and isotonic strength training and plyometrics. Complex training also appears to provide a potent stimulus and may be more effective than the use of singular training modes. For plyometric activities, it is recommended that coaches use a developmental sequence of exercises with increasing eccentric demand to provide an appropriate stimulus based on the training age and technical competency of the athlete.
PARAMETERS USED IN MODELING SEDIMENT- LADEN FLOW IN OPEN CHANNELS

A new method for predicting the suspended sediment concentration and transport rate for turbulent flows in open channels is developed based on the Rouse Equation and the traditional power law velocity profile. The work is based on basic hydraulic principles pmsliand theory analysis of open channel flows, and the extensive investigations by others on the origins of the relevant studies. This study focuses on improving the accuracy of pre-existing parameters and their application. In the study, the accuracy of prediction of the Rouse equation has been improved by an optimized Rouse number and the choice of the reference level. The sediment diffusion coefficient, es, and momentum diffusion coefficient, em, have been estimated, by using the relevant study results to divide water depth into the upper region (y/d > 0.1) and the lower region (yld < 0.1), in which a supplemental A-value is assumed to exist in the upper flow in order to correct the ideal distribution of momentum diffusion coefficient. By analyzing the observed data, a linear regression relationship between A and the product of water depth and shear velocity may be obtained. The depth-averaged integration is employed to compute /3-value, i.e. the ratio of the sediment diffusion coefficient to the momentum diffusion coefficient. A dimensionless parameter V2/gd has been introduced, which means that thefi-value predicted by this new method is applicable to a wide range of water depths, from lab flumes to rivers. The sediment concentration profiles predicted by the proposed method agree well with measured data when compared with other formulas developed for certain areas. Fine suspended load transport rate may be estimated effectively by a new formula. Further investigation will be focused on the improvement and extension of this model. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. [jMsq
Ref: BRLN_2018_116 Title: Written sentence context effects on acoustic-phonetic perception: fMRI reveals cross-modal semantic-perceptual interactions Journal: Brain and Language

This study examines cross-modality effects of a semantically-biased written sentence context on the perception of an acoustically-ambiguous word target identifying neural areas sensitive to interactions between sentential bias and phonetic ambiguity. Of interest is whether the locus or nature of the interactions resembles those previously demonstrated for auditory-only effects. FMRI results show significant interaction effects in right mid-middle temporal gyrus (RmMTG) and bilateral anterior superior temporal gyri (aSTG), regions along the ventral language comprehension stream that map sound onto meaning. These regions are more anterior than those previously identified for auditory-only effects; however, the same cross-over interaction pattern emerged implying similar underlying computations at play. The findings suggest that the mechanisms that integrate information across modality and across sentence and phonetic levels of processing recruit amodal areas where reading and spoken lexical and semantic access converge. Taken together, results support interactive accounts of speech and language processing.
Effect of tectonic structure on the occurrence of ground water in the basalt of the Columbia River Group of The Dalles area, Oregon and Washington

_______----_--_---______________________ Introduction. _____________________________________ Purpose. ___--_---__--_---_--_-_-_______-______ Physiographic setting. __________________________ Preceding work and schedule for this report. _______ Well-numbering system________________________ General geologic setting. ____-_-_--___-__--______ Consolidated rocks. _-_-___-_--_____-________ Principal bedrock units____-____--_-_____ Deformation and early erosion__-_-_____ Later lavas, deformation, and erosion. ____ Unconsolidated rocks______________________ Geohydrology of the basalt of the Columbia River GroupPhysical and hydrologic characteristics of the rock_ _ Petrologic features. _________________________ Texture _______________________________ Layering____---____-_-_-___-___-_____ Joints produced by cooling of the lava____ Regional joints. ________________________ Autobrecciation. _______________________ Interflow sediments. ________-___---_____ Weathering. ___________________________ Folds and faults. ___________________________ Major folds______. __-__-_-______--_____ Minor folds____________________________ Faults________________________ Page Cl 1 1 2 3 3 3 3 3 6 6 6 10 10 10 10 10 13 13 14 14 15 15 15 17 18 Geohydrology of the basalt Con. Page Ground-water occurrences. ___---____--____-_____ C20 Tectonic controls on the ground water_______ 20 Ease of water entry into the basalt____. ___ 20 Downdip, a preferential direction of groundwater movement_______--__-___---___ 20 Obstruction of percolation in aquifers ______ 20 Major occurrence, beneath the main water table__________-_ __ _ 21 Minor occurrences. _________________________ 22 High-perched ground water____-_________ 22 Intermediate-perched ground water. ______ 22 Local examples of structural control of ground water. ______-_-_____-----__-----__--__-23 Mosier Creek basin______--___--_-____-_ 23 Chenoweth Creek basin. _____--___-___-_ 25 Mill Creek valley__-----________ 25 "The Dalles Ground Water Reservoir"__ 27 The uplands west of the canyon of the Deschutes River______________ 28 Plateau east of the Deschutes River. _____ 29 Localities north of the Columbia River___ 30 Summary___ __--_--_-----_-----------__-----------32 References cited-----------------------------------33
MINDS: A Multi-label Emotion and Sentiment Classification Dataset Related to COVID-19

During times of crisis, such as the COVID-19 pandemic, there has been a sudden increase in information exchanges on social media. People gathered to share their feelings, experiences, knowledge, and ideas with one another. Twitter has emerged as the most authentic, admired, and widely used social media platform for users to express their sentiments, opinions or emotions. Understanding the emotions expressed in text facilitates the development of empathetic machines. In this paper, we intend to collect and annotate a large corpus of textual data that can be used to train classification models for detecting emotions and sentiments in user-generated content. We analyze user sentiments and emotions expressed in tweets during the third wave of the omicron sub-variant pandemic. Our curated dataset, MINDS, consists of 227, 229 tweet instances that were annotated using a multi-model setup in order to quantify all aspects of model uncertainty. Each instance in the dataset is classified according to three sentiment classes (positive, negative, and neutral) and five emotion classes (sadness, joy, fear, disgust, and anger). We have used a well-performing benchmark dataset related to SemEval-2018’s E-c subtask for determining the classification threshold. The MINDS datasets is publicly available at http://www.abulaish. com/ldsa/dataset for research purposes.
WITH PAROXYSMAL ATRIO-VENTRICULAR HEART BLOCK, A MULTI-DISCIPLINARY TEAM APPROACH

were identical to the ones used in 2014. The data was analysed using Microsoft Excel. Results The number of respondents totalled 107 (Response rate: 19%). The respondents consisted of 84 individuals who were pharmacists or pharmacy technicians, and the remaining 23 were non-pharmacy staff such as doctors or nurses. The majority of the pharmacy team reviewed palliative care patients on a monthly basis, and this trend had increased since 2014. Overall, an increase in patient contact was observed. The clinical involvement of the pharmacy team in PP care had increased, especially in medicines optimisation and prescribing. Since 2014, the number of pharmacists prescribing for children with palliative care needs appeared to have doubled. Other roles where pharmacy involvement appeared to have increased included advising on storage of medicines, investigating medication errors and formulary development. Conducting research/audits, writing guidelines and financial reports were not popular tasks. In 2020, only 25% of the pharmacy team were involved with writing patient information leaflets for children with palliative care needs. Lack of staffing, time and funding were the most frequently reported impediments to the pharmacy team taking on more clinical roles. In 2014 and 2020, the British National Formulary for Children (BNF-C) was the most popular reference source routinely used by all staff groups. The Palliative Care Formulary, syringe driver compatibility charts and Handbook of Drug Administration via Enteral Feeding Tubes were also popular references amongst the pharmacy team. Doctors and nurses utilised the Alder Hey Book of Children’s Doses and the APPM Master Formulary more than pharmacy staff. In 2020, doctors and nurses gave a median of 10/10 regarding their satisfaction of the pharmacy team’s contributions. The minimum score given was 6. Khan’s study reported a median rating of 9, but the difference observed was not considered to be statistically significant (p value >0.05). Conclusions This study inferred that the involvement of the pharmacy team in paediatric palliative care has increased since 2014. More of the pharmacy team are handling clinical issues and the paediatric palliative healthcare team would like this growth to continue. The increase in prescribing by pharmacists was an interesting finding and it would be well-worth observing how this trend progresses. Consistent with Khan’s observations in 2014, non-pharmacy staff highly valued the pharmacy team’s contributions.
An Ex-post Analysis of the Phenomenon of Wash Trading on NFTs

In recent years, many researchers have studied the phenomenon of wash trading on NFTs (Non Fungible Tokens) from an “ex-ante” perspective. The latter aims to identify and classify wash trading activities before or as they occur. In this paper, we propose an “ex-post” analysis of wash trading on NFTs. This perspective aims to analyze wash trading activities carried out in the past to see whether such illicit and risky activities brought significant profit to those who did them. To the best of our knowledge, this is the first paper in the literature to analyze wash trading on NFTs from an “ex-post”, instead of an “ex-ante”, perspective.
Exploring the Drivers of Tropospheric Hydroxyl Radical Trends in the GFDL AM4.1 Atmospheric Chemistry-Climate Model

We explore the sensitivity of modelled tropospheric hydroxyl (OH) concentration trends to meteorology and near-term climate forcers (NTCFs), namely methane (CH 4 ); nitrogen oxides (NO x = NO 2 + NO); carbon monoxide (CO); non-methane volatile organic compounds (NMVOCs); and ozone-depleting substances (ODS) using the Geophysical Fluid Dynamics Laboratory (GFDL)’s atmospheric chemistry-climate model, Atmospheric Model version 4.1 (AM4.1) driven by emissions invento-5 ries developed for the Sixth Coupled Model Intercomparison Project (CMIP6) and forced by observed sea surface temperatures and sea ice prepared in support of the CMIP6 Atmospheric Model Intercomparison Project (AMIP) simulations. We ﬁnd that the modelled tropospheric airmass-weighted mean [OH] has increased by ∼ 5% globally from 1980 to 2014. We ﬁnd that NO x emissions and CH 4 concentrations dominate the modelled global trend, while CO emissions and meteorology were also important in driving regional trends. Modelled tropospheric NO 2 column trends are largely consistent with those retrieved from the 10 Ozone Monitoring Instrument (OMI) satellite, but simulated CO column trends generally overestimate those retrieved from the Measurements of Pollution in The Troposphere (MOPITT) satellite, possibly reﬂecting biases in input anthropogenic emission inventories, especially over China and South Asia.
A general approach to Supervised Meta-Blocking

Entity Resolution is a core data integration task that relies on Blocking to scale to large datasets. Schema-agnostic blocking achieves very high recall, requires no domain knowledge, and works on data with any structure. The main drawback of this approach is the number of generated superfluous comparisons (i.e. non-matching), which can be reduced by Meta-blocking techniques that aim to discard most of them. Unsupervised Meta-blocking performs this process by scoring each comparison with a single metric and then applying a pruning algorithm, so choosing the right metric among the existing ones is fundamental to achieving good results. Supervised Meta-blocking improves this approach by combining multiple scores per comparison into a feature vector that is fed to a binary classifier used to decide if a comparison is a match or not. In this work, we generalize the Supervised Meta-blocking approach by using a probabilistic classifier that pairs each comparison with a score that represents its likelihood to be a match, allowing to use of any pruning algorithm.
Energy management strategies for HEVs: introduction and positioning

: Hybrid Electric Vehicles are effective solutions to reduce energy consumption and pollution emission in the transport sector. They however present multiple energy sources and complex drivetrain structures involving numerous energy transformers. Their control is therefore complex and represents a key point to achieve the expected performance. The energy management is a part of this control and should be properly developed so that the efficiency of the HEV is enhanced. This topic has been of great concern in the two last decades and still mobilizes number of researchers. Energy management strategies (EMS) ensuring the power sharing between the different components, sources as well as transformers, adapted to different cases have been therefore developed and optimized. This chapter presents the definition and principle of the EMSs for HEV. Different families of EMSs are then introduced and illustrated by examples in order to provide a better understanding of the methods principles. Some of these methods are based on the expertise and the intuition of developer. Others use optimization theories in order to operate near the maximum expected efficiency. In most of the cases today, offline simulation using global vehicle models are used to develop and compare the performance of these different methods.
CoreKB: A Web-based Platform for Searching Reliable Facts over a Medical Knowledge Base

CoreKB is a web-based platform enabling users to search for reliable scientific facts concerning gene expression-cancer associations over a medical Knowledge Base (KB). CoreKB provides a streamlined interface for searching either using natural language queries or by exploiting structured facets providing autocomplete facilities. It is designed to simplify information access and search of scientific facts targeting healthcare stakeholders (i.e., clinicians, physicians, and researchers). CoreKB aims at presenting the user a comprehensive overview of the scientific evidence supporting a medical fact, fully connected with ontology-based entities and well-defined literature resources. In addition, CoreKB provides the user a quantitative comparison of the possible gene-cancer associations related to a specific fact, thus enabling users to assess the degree of agreement among the evidence support.
Discourse cohesion in Xenophon's On Horsemanship through Sketch Engine

We build a Sketch Engine corpus for Xenophon’s classical Greek scientific treatise On Horsemanship . Sketch Engine is a web-based corpus-analysis tool that allows the user to inspect the lexical makeup of a text (cf. keyword lists), explore the surroundings of select items (cf. concordances) and identify fixed expressions in a text (cf. n-grams). We make available our corpus-preparation tool and our corpus configuration file for Sketch Engine. We use the Sketch Engine corpus to detect discontinuous verbal multi-word expressions, specifically support-verb constructions (e.g. to take a decision ). We examine how support-verb constructions – through their structural and lexical properties – aid discourse coherence and cohesion throughout Xenophon’s treatise. We furthermore examine how the recurring support-verb constructions in the treatise reflect the scientific register of the text. The article shows how an understudied category of lexico-syntactic device (support-verb constructions) in classical Greek majorly aids discourse cohesion, structurally and contextually speaking. It also shows how an understudied text in the form of a technical treatise ( On Horsemanship ) majorly furthers insight into scientific literacy of the classical period. Finally, by making available our corpus-preparation tool and code, we hope to further collaboration and adaptation and thus improvement of existing tools and counteract the multiplication of tools.
A modified common set of weights method to complete ranking DMUs

presented a method for obtaining a common set of weights in data envelopment analysis (DEA) and they also provided a system for ranking decision making units (DMUs) using common set of weights. Their method has two main problems. At first, their presented model may have alternative optimal solutions (alternative common set of weights). Alternative optimal solutions may lead to different ranks for each DMU. Second, all criteria for ranking, by their suggested system, may be identical for at least two DMUs and so these DMUs will have the same rank. Therefore, there is no full ranking for DMUs using the suggested method. The aim of this paper is surveying these shortcomings and presenting methods to overcome them. This paper suggests a method to obtain unique common set of weights which can be applied for all methods used linear programs for acquiring common set of weights. Moreover, by definition bad benchmark against benchmark defined by Liu and Peng, a system for full ranking DMUs is proposed. Numerical examples are used to illustrate the proposed method.
Understanding flow-induced crystallization in polymers: A perspective on the role of molecular simulations

Flow-induced crystallization in polymers is an important problem in both fundamental polymer science and industrial polymer processing. The key process of flow-induced nucleation occurs on a very rapid time scale and on a highly localized lengthscale and so is extremely difficult to observe directly in experiments. However, recent advances in molecular dynamics (MD) simulations mean that flow-induced nucleation can be simulated at an achievable computational cost. Such studies offer unrivalled time and lengthscale resolution of the nucleation process. Nevertheless, the computational cost of MD places considerable constraints on the range of molecular weights, temperature, and polydispersity that can be studied. In this review, I will discuss recent progress, describe how future work might resolve or work around the constraints of molecular simulation, and examine how multiscale modeling could translate molecular insight into improved polymer processing.Flow-induced crystallization in polymers is an important problem in both fundamental polymer science and industrial polymer processing. The key process of flow-induced nucleation occurs on a very rapid time scale and on a highly localized lengthscale and so is extremely difficult to observe directly in experiments. However, recent advances in molecular dynamics (MD) simulations mean that flow-induced nucleation can be simulated at an achievable computational cost. Such studies offer unrivalled time and lengthscale resolution of the nucleation process. Nevertheless, the computational cost of MD places considerable constraints on the range of molecular weights, temperature, and polydispersity that can be studied. In this review, I will discuss recent progress, describe how future work might resolve or work around the constraints of molecular simulation, and examine how multiscale modeling could translate molecular insight into improved polymer processing.
Comparative Evaluation on Iris Recognition Performance

recognition software between the open source (Libor Masek) and the commercially available (VeriEye by Neurotechnology). There are five processes to evaluate the performance: 1) resize the images' resolution from 1280 x 960 to 640 x 480; 2) convert the images from JPEG2000 to JPEG format; 3) convert the images into grayscales; 4) run the images with both Libor Masek's and VeriEye software; 5) measure the performance of the two software using Receiver Operating Characteristic (ROC) plot and the operational time framework. The ROC plots show that VeriEye software performs better than Libor Masek's. There is significant difference in the processing time between the two software.
ICARE: An Intuitive Context-Aware Recommender with Explanations

The Intuitive Context-Aware Recommender with Explanations (ICARE) framework leverages data mining algorithms to provide contextual recommendations, together with their explanations, useful to achieve a specific and predefined goal. We apply ICARE in the healthcare scenario to infer personalized recommendations related to the activities (fitness and rest periods) a specific user should pursue or avoid in order to obtain a high value for the sleep quality score, while also considering their current context and the physical activities performed during the previous days.
Network‐based distributed direct load control guaranteeing fair welfare maximisation

This study examines a distributed direct load control (DLC) problem for maximising customer welfare in a power system for the network communication of energy management controllers (EMCs). A model is first built to describe the dynamics and communication intervals of the EMCs with a distributed and uniform controller. The controller conditions are then derived to stabilise the system and to converge the power imbalance to zero at an assigned rate. The control condition that maximises customer welfare is then found. Furthermore, an optimal controller that maximises customer welfare over a given network communication is proposed, and the performance degradation caused by distributed management is evaluated. This study reveals that even though moving from a centralised to a distributed DLC can degrade customer welfare, this degradation can be reduced by considering consumer properties and network topologies of the EMCs. Numerical examples with real consumption data are also presented to demonstrate the effectiveness of the proposed method.