Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictors of Acute Poststroke Seizures

Background: In this study, we tried to identify predictors of acute poststroke seizures (aPSS) in stroke patients. Methods:We analyzed a large prospective hospital-based stroke registry in Germany. 58,874 patients with the diagnosis of transient ischemic attack (TIA), ischemic stroke (IS) or intracerebral hemorrhage (ICH) were admitted within 24 h after symptom onset. Predictors for aPSS were identified using multivariate regression analysis adjusted for age, gender, stroke severity, vascular risk factors, acute nonneurologic infection, history of TIA and length of hospital stay. Results: aPSS occurred in 0.7% of patients with TIA (mean duration of hospitalization 8 days), in 2.2% of patients with IS (12 days) and in 5.1% of patients with ICH (13 days). A lower age, a higher stroke severity, acute nonneurologic infection, a history of diabetes mellitus and a history of preceding TIA were identified to be independent predictors of aPSS in IS, whereas younger age, acute infection and a history of TIA were found predictive for aPSS in ICH. Conclusions: This study characterized so far unknown predictors of aPSS and may help to improve the identification of patients with a high risk of aPSS.
Why Spanish Discard information is still not available to be used for some Stocks of Southern Shelf WGHMM

The 2006 ICES WGHMM Report (ICES, 2006) in point 1.5 about “Recommendations” suggests, that discard data should be ready available to the assessment group. However report mentioned in the same paragraph the discard data has to be studied before incorporating them to the analysis. The WG recommends the analysis and development of methods for discard data estimation, and an overall reconstruction of discard data series for their inclusion in the assessment”. In Recommendations for Recovery Plan (WGHMM report point 3.6.8) the Group considers that a complete evaluation of the management plan requires more information and/or more explicit modelling regarding also to discard data. The Group recommends that a further work have to be carried out to obtain information in these areas together with a deep analysis, aimed to evaluate the potential effects on assessment and management. Also in Annex I of WGHMM Report for Recommendations and Action the 6th section recommend the “Analysis and development of methods for discard data estimation andreconstruction of discard data series for inclusion in the assessment”
Self-reported pain and utilization of pain treatment between minorities and nonminorities in the United States.

OBJECTIVES To investigate differences in reported pain and pain treatment utilization (use of over-the-counter and prescription pain medications, seeing a pain specialist, and use of complementary and alternative medicine) among minorities and nonminorities in the general population. DESIGN Secondary analysis of a national probability survey conducted by the CBS News/New York Times in January 2003. SAMPLE Adult population in the United States, 18 years or older, having a telephone line at home. MEASUREMENTS The survey asked respondents a series of questions about demographics, pain characteristics, and utilization of pain treatment; logistic regression was used to identify variables predicting reported utilization of pain treatment. RESULTS Of the 902 respondents completing the survey, 676 (75%) reported experiencing "any type of pain. " Of these, 17% reported being diagnosed with chronic pain. Minorities reported a higher average daily pain than Whites (4.75 vs. 3.72; p<.001). However, race/ethnicity did not explain utilization of pain treatment; income, education, age, gender, and pain levels explained more variability in different pain treatment utilization variables than race/ethnicity. CONCLUSIONS Although minorities report higher pain levels than Whites, race/ethnicity does not explain utilization of treatment for pain. Future studies should consider more nuanced examination of interactions among race/ethnicity, pain, and socioeconomic variables.
Genitofemoral Nerve Block: A Transpsoas Technique

The end concentration of a solution is dependent on the mass (dose) of the solute and the volume of the solvent. Thus. if an unduly large dose of LA is used, regardless of its volume or concentration. a high or even total spinal anesthesia will eventually be produced because the end concentration in CSF is still pharmacologically active after full dilution. Conversely. administering a LA in a neurotoxic concentration, even in a small dose or volume. unless adequately diluted by CSF. may cause neural damage such as cauda equina syndrome. In clinical doses. dilution into much larger volumes will not produce the lower levels of block that smaller volumes may. due to simple bulk displacement or area contact. · Funher dilution into volumes of non pharmacologically active concentrations may even give no clinical analgesia/ anesthesia. The spread of LA in the subarachnoid space is multifactorial.s-10 Therefore. it can be seen that drug dosage is only one of the determinants that governs the spread. It is the product of concentration and volume. Those basic principles state that concentration determines the effectiveness or quality of the block and that volume determines the quantity (spread) still hold in SAB. All four drug factors (dose. volume, concentration. and baricity) should be taken imo consideration.
Addressing Domestic Violence Against Women: An Unfinished Agenda

“Domestic violence is a burden on numerous sectors of the social system and quietly, yet dramatically, affects the development of a nation… batterers cost nations fortunes in terms of law enforcement, health care, lost labor and general progress in development. These costs do not only affect the present generation; what begins as an assault by one person on another, reverberates through the family and the community into the future”. (Zimmerman)(1) Domestic violence is a global issue reaching across national boundaries as well as socio-economic, cultural, racial and class distinctions. This problem is not only widely dispersed geographically, but its incidence is also extensive, making it a typical and accepted behavior. Domestic violence is wide spread, deeply ingrained and has serious impacts on women's health and well-being. Its continued existence is morally indefensible. Its cost to individuals, to health systems and to society is enormous. Yet no other major problem of public health has been so widely ignored and so little understood. (2)
Position Drift Compensation in Time Domain Passivity based Teleoperation

The Time Domain Passivity Control Approach is gathering interest in the robotics field. Simplicity and flexibility and the fact that system design emerges from ideal cases make it a powerful stability tool for teleoperation systems. Communication time delay is an inherent attribute of nearly every realistic teleoperation system. Unless the communication channel guarantees transmission delays of less than the system sampling time, the delay must be considered in the design in order to guarantee stability and satisfy a desired degree of performance. In previous work it has been shown how passivity can be considered in the time domain and how control rules are derived from it in order to dissipate the energy produced by the delayed communication. However, a weakness of these approaches is the impossibility of observing the exact amount of energy stored in the communication channel due to its delayed nature. A passive estimation is therefore needed which outcomes in an over-dissipation and in turn impacts on transparency. In constrained communications over-dissipation may become apparent in the form of a non-neglectful position drift between master and slave. This paper tackles the overdissipative behavior of the Passivity Controller by resembling the energetic behavior of an ideal communication, i.e. where no delay is present and the transmission is lossless. Thus, the communication channel is not just controlled to be passive, as has been the case up to now, but also lossless. Energy can be dissipated to prevent activity, but activity can be also produced to prevent dissipative behaviors. The approach is sustained with experimental results.
Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise—Basics and Options for Wearable Devices

The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.
METRICS FOR QUANTIFYING SURFACE WETTING EFFECTS ON BOILING AND EVAPORATION AT NANOSTRUCTURED HYDROPHILIC SURFACES

Static contact angle is most often used as a means of quantifying the wetting characteristics of the liquid phase in vaporization processes. This metric is often convenient to measure and it is intuitive in its interpretation, but its usefulness is questionable in some cases. For highly wetting, nanostructured surfaces, the use of a static contact angle to quantify wetting has two key disadvantages. One is that it can be difficult to measure from photographs of sessile droplet profiles or contact line regions when the contact angle is very small. A second disadvantage is that the relationship of the macroscopic contact angle to the nanoscale interaction of the liquid and vapor contact line with the nanostructured surface is unclear. In this study, the advantages and disadvantages of different wetting metrics were explored and evaluated for hydrophilic surfaces. Alternate choices of wetting metric suggested in earlier studies such as dynamic advancing and receding contact angles, and spreading coefficients, are explored here as alternatives to static contact angle. A new wetting metric based on spreading characteristics of sessile droplets is also proposed that has the advantage of being easily measured for hydrophilic surfaces. Use of this new metric is then explored for evaporation and boiling applications with superhydrophilic surfaces. The results of our study indicate that this new metric can be particularly useful for characterizing the effects of variable wetting on vaporization processes at highly wetted surfaces.
Imaging of Colloidal Gold Nanoparticle Using Atomic Force Microscope

Colloidal gold or also known as gold nanoparticle (AuNP) is a suspension of sub-nanometer-sized particle of gold in a fluid usually water. The synthesized AuNP have particle sizes ranging from, e.g. 10 nm to 100 nm with color changing from an intense red color (for particle less than 100 nm) to a dirty yellowish color (for larger particle). The size of AuNP determines their unique optic, electronic and magnetic properties. AuNP nowadays has widely used in material science [ and biomedical [2,. For many of this application, the AuNP need to be monodispersed and have a specific size. Generally, colloidal AuNP can be synthesis as monodispersed nanoparticles with core sizes ranging from 1nm to 250nm. The synthesis of AuNP can be controlled in different size and shapes due to their ability to react and agglomerate with other nanoparticles in their ambient condition [. Furthermore, AuNP can also becomes more prone to flocculation and aggregation [. As the size of colloidal AuNP increase so do their sensitivity to salt and environment. AuNP have increasingly gain interest due to their unique properties ofcontrolable morphology [ and size dispersion [6,, less toxicity and ease in synthesis and detection.
Advances in Organic Solvent Nanofiltration Rely on Physical Chemistry and Polymer Chemistry

The vast majority of industrial chemical synthesis occurs in organic solution. Solute concentration and solvent recovery consume ~50% of the energy required to produce chemicals and pose problems that are as relevant as the synthesis process itself. Separation and purification processes often involve a phase change and, as such, they are highly energy-intensive. However, novel, energy-efficient technologies based on polymer membranes are emerging as a viable alternative to thermal processes. Despite organic solvent nanofiltration (OSN) could revolutionize the chemical, petrochemical, food and pharmaceutical industry, its development is still in its infancy for two reasons: (i) the lack of fundamental knowledge of elemental transport phenomena in OSN membranes, and (ii) the instability of traditional polymer materials in chemically challenging environments. While the latter issue has been partially solved, the former was not addressed at all. Moreover, the few data available about solute and solvent transport in OSN membranes are often interpreted using inappropriate theoretical tools, which contributes to the spread of misleading conclusions in the literature. In this review we provide the state of the art of organic solvent nanofiltration using polymeric membranes. First, theoretical models useful to interpret experimental data are discussed and some misleading conclusions commonly reported in the literature are highlighted. Then, currently available materials are reviewed. Finally, materials that could revolutionize OSN in the future are identified. Among the possible applications of OSN, isomers separation could open a new era in chemical engineering and polymer science in the years to come.
Unified state-space modeling method for dual-active-bridge converters considering bidirectional phase shift

In this paper, unified modeling method for dual-active-bridge (DAB) bidirectional converters (BDCs) considering bidirectional phase shift is proposed. There is only one model, and it is shared by both positive and negative phase shift. DAB and its extended converters are widely used in energy storage systems. These converters are regulated by duty cycle plus phase shift. The existing modeling methods model these converters in positive and negative phase shift directions respectively. Though the two models are built in similar ways, they are not the same. Hence they are hard to be utilized in applications where phase shift direction changes. Therefore, a modeling method to build only one model for both phase shift directions is desired. In this paper, a conjugate shifted phase based superposition technique is proposed to facilitate the proposed bidirectional unified modeling method. By this technique, voltage on the shifted side of the transformer is expressed in a superposition form, which represents both situations of positive and negative phase shift simultaneously. This superposition form will collapse to actual form, once the shift direction is given. Hence situations in both directions are unified. Besides, a newly proposed current division technique is integrated into this method for high model accuracy. A buck-boost coupled dual-active-half-bridge (DAHB) converter is selected to describe the method. The only one large-signal model for both phase shift directions is established, so as a small-signal model. Simulations and experiments have validated the proposed modeling method and its high accuracy
Mutual information derived functional connectivity of the electroencephalogram (EEG)

Monitoring the functional connectivity between brain networks is becoming increasingly important in elucidating brain functionality in normal and disease states. Current methods of detecting networks in the recorded EEG such as correlation and coherence are limited by the fact that they assume stationarity of the relationship between channels, and rely on linear dependencies. Here we utilize mutual information (MI) as the metric for determining nonlinear statistical dependencies between electroencephalographic (EEG) channels. Previous work investigating MI between EEG channels in subjects with widespread diseases of the cerebral cortex had subjects simply rest quietly with their eyes closed. In motor disorders such as Parkinson’s disease (PD), abnormalities are only expected during performance of motor tasks, but this makes the assumption of stationarity of relationships between EEG channels untenable. We therefore propose a novel EEG segmentation method based on the temporal dynamics of the cross-spectrogram of the computed Independent Components (ICs). After suitable thresholding of the MI values between channels in the temporally segmented EEG, graphical theoretical analysis approaches are applied to the derived networks. The method was applied to EEG data recorded from six normal subjects and seven PD subjects on and off medication performing a motor task involving either their right hand only or both hands simultaneously. One-way analysis of variance (ANOVA) tests demonstrated statistically significant difference between subject groups. This proposed segmentation/MI network method appears to be a promising approach for EEG analysis.
Fit for work? Health, employability and challenges for the UK welfare reform agenda

This article introduces a special issue of Policy Studies entitled “Fit for work? Health, employability and challenges for the UK welfare reform agenda”. Growing from a shared concern over the need to expand the evidence base around the processes that led to large numbers of people claiming disability benefits in the UK, it brings together contributions from leading labour market and social policy researchers providing evidence and commentary on major reforms to Incapacity Benefit (IB) in the UK. This special issue address three key questions: what are the main causes of the long-term rise in the number of people claiming IBs; what will reduce the number of claimants; and what is likely to deliver policy effectively and efficiently? This introduction first explains and examines the challenges to reforms to IB in the UK, and then, in conclusion, highlights the answers to the previous three questions – first, labour market restructuring and marginalisation have driven the rise in numbers claiming IBs. Second, economic regeneration in the Britain’s less prosperous areas coupled with intensive and sustained supply-side support measures will bring numbers down. Third, delivery need to be flexible and tailored to individual needs and needs to be able to access local and expert knowledge in a range of organisations, including Job Centre Plus, the NHS as well as the private and voluntary sectors.
SHELL DISEASE IN BLUE CRABS, CALLINECTES SAPIDUS, FROM THE ALBEMARLE-PAMLICO ESTUARY

• . •••••• • ••••••••••••••••••••••••••••••••• . •• • LIST OF FIGURES •••••••••••••••••••••. •••••••••• • ••••••• LIST OF TABLES •••••••••••••••••••••••••••• • ••••••••••• • SUMMARY AND CONCLUSIONS •••••••••••••••••••••• • ••••••••• RECOMMEN DATI ONS ••••••••. ••••••••••••••••••••••••••••••• INTRODUCTION •••••••••. •. ••••••••••••••••••••••••••••••• PURPOSE AND OBJECT I VES ••••••••••••••••••••••••••••••••• PROCEDURES . ••••••. •••••••••••••••••••••• . •••••••••••• A. Tissues s ampled for antibacterial activity . B. Bacterial cultures . c. Assay for enzymatic activity in crab bacterial isolates . D. Assays for antibacterial activity . E. Identification of bactericidal activity in samples. F. Biochemical characterization of antibacterial activity . •. G. Trace metal measurements . · . H. Determinati on of hemocyanin concentrations I. Experimental reproduction o f shell disease in blue crabs: Preliminary study . RESULTS •••••. •••••••••••••••••••••••. •••••••• • ••••••••• A. Clinical features of shell disease . B. Pathogens associated with s he ll disease lesions . • C. Identification of antimicrobial activity in blue crabs: Bacterial susceptibility and anatomical Page
Geospatial Technique for Rapid Delineation of Potential Hurricane Damage

Rapid delineation of potential damage from hurricanes to the natural and human-modified landscape is critical for disaster management and for assessment of ecological and economic impacts. Geospatial technologies including Remote Sensing (RS), Geographic Information Systems/Science (GIS), and Global Positioning Systems (GPS) provide new tools for delineating damage potential and for assessing destruction after natural disasters. Historically, airborne and space RS missions have been used for post-hurricane impact assessment, but these data are limited in a variety of ways. Space-based RS data have limitations including differing specifications for spatial, spectral, and temporal resolution. As an example, predicting damage or assessing damage from land-falling hurricanes via satellite data is often hampered by temporal resolution (re-visit frequency) that can result in unavailability of cloudfree images over impacted areas. Airborne RS data are not temporally limited to a specific window of ground coverage and can even acquire data during cloudy conditions. Airborne RS instruments may provide data of higher spectral and spatial resolution than space-borne instruments; however complete ‘wall-to-wall’ coverage of landscapes impacted by tropical systems as large as hurricane Katrina can be impractical and prohibitively expensive. Consequently, many geospatial analysts first use space-borne data and geospatial modeling at a relatively coarse-resolution to provide an overview of hurricane impacted areas, and then they use this information to pinpoint locations where they need to acquire airborne RS data for higher-resolution subsets of damaged areas. Therefore, there is a need to develop more accurate geospatial models that incorporate readily available data at a regional scale to assist emergency and disaster management agencies with their decision-support. According to Hodgson et al., (2010), agencies with first responder responsibilities have expressed the critical need for image acquisitions over disaster impacted areas within 24 hours, or within three days of the event at a minimum. Given the limitations for rapid acquisition of RS imagery over hurricane-impacted areas, researchers at Mississippi State University in coordination with Mississippi Emergency Management Agency (MEMA) advisors have developed a geospatial modeling-based tool that enables rapid depiction (within 24 – 48 hours after landfall) of a damage probability statistical grid which incorporates readily available data sources such as storm surge predictions and precipitation and wind forecasts. This grid can be overlain on a variety of image and GIS base layers to help plan for evacuation procedures prior to landfall and to help orient and manage the effective allocation of resources to impacted areas.