Apraxia and motor dysfunction in corticobasal syndrome

Background: Corticobasal syndrome (CBS) is characterized by multifaceted motor system dysfunction and cognitive disturbance; distinctive clinical features include limb apraxia and visuospatial dysfunction. Transcranial magnetic stimulation (TMS) has been used to study motor system dysfunction in CBS, but the relationship of TMS parameters to clinical features has not been studied. The present study explored several hypotheses; firstly, that limb apraxia may be partly due to visuospatial impairment in CBS. Secondly, that motor system dysfunction can be demonstrated in CBS, using threshold-tracking TMS, and is linked to limb apraxia. Finally, that atrophy of the primary motor cortex, studied using voxel-based morphometry analysis (VBM), is associated with motor system dysfunction and limb apraxia in CBS.   Methods: Imitation of meaningful and meaningless hand gestures was graded to assess limb apraxia, while cognitive performance was assessed using the Addenbrooke's Cognitive Examination - Revised (ACE-R), with particular emphasis placed on the visuospatial subtask. Patients underwent TMS, to assess cortical function, and VBM.   Results: In total, 17 patients with CBS (7 male, 10 female; mean age 64.4+/2 6.6 years) were studied and compared to 17 matched control subjects. Of the CBS patients, 23.5% had a relatively inexcitable motor cortex, with evidence of cortical dysfunction in the remaining 76.5% patients. Reduced resting motor threshold, and visuospatial performance, correlated with limb apraxia. Patients with a resting motor threshold <50% performed significantly worse on the visuospatial sub-task of the ACE-R than other CBS patients. Cortical function correlated with atrophy of the primary and pre-motor cortices, and the thalamus, while apraxia correlated with atrophy of the pre-motor and parietal cortices.   Conclusions: Cortical dysfunction appears to underlie the core clinical features of CBS, and is associated with atrophy of the primary motor and pre-motor cortices, as well as the thalamus, while apraxia correlates with pre-motor and parietal atrophy

Institutional difference and outward FDI: Evidence from China

This paper investigates the impact of institutional difference on China’s outward foreign direct investment (OFDI) through a gravity model. Our estimations are based on a large panel of 150 countries over the period 2003-2015. The results show that the institutional differences of government effectiveness and control of corruption between China and a host country have a statistically significant negative effect on China’s OFDI. In addition, our empirical evidence suggests that the ‘One Belt One Road’ policy does not have the expected positive effect on China’s OFDI. Consistent results are obtained from a set of robustness tests. Our findings provide a reasonable guideline for countries aiming to attract Chinese OFDI or seeking factors to boost it

Ontwikkeling emissiemanagementsysteem grondgebonden teelt; de lysimeter en drainmeter

Het hoofddoel van het project ‘Glastuinbouw Waterproof, grondgebonden’ was het ontwikkelen van een aantal middelen voor telers van grondgebonden teelten, waarmee zij emissiedoelstellingen kunnen halen. De leidende gedachte hierbij is dat een gesloten waterkringloop zoals toegepast bij substraatteelten onhaalbaar is. Emissiereductie zal vooral via het waterspoor behaald moeten worden en daarom is een brongerichte aanpak, de irrigatie afgestemd op de evapotranspiratie, het meest effectief. Het project omvatte in de eerste plaats het ontwikkelen en combineren van een aantal technische hulpmiddelen en in de tweede plaats het installeren en testen in de praktijk. In dit rapport worden de lysimeter en de bijbehorende drainmeter besproken

Ontwikkeling emissiemanagementsysteem grondgebonden teelt; bodemvochtsensoren en modulaire opbouw van het systeem

‘Glastuinbouw Waterproof - Grondgebonden’ heeft een modulair emissiemanagementsysteem opgeleverd waarmee telers hun water en meststoffen gebruik kunnen optimaliseren naar een goed teeltresultaat en een minimale emissie. Kern van dit systeem is de lysimeter, waarmee dagelijks de werkelijke drainhoeveelheid gevolgd kan worden. Door bemonstering en analyse van de drain wordt de emissie van meststoffen inzichtelijk. Het systeem bevat naast de lysimeter, een drainmeter, bodemvochtgehalte sensoren en een beslissingsondersteunend systeem met modellen voor gewasverdamping en watertransport in de bodem. Telers kunnen kiezen welke modules ze naast de lysimeter willen toepassen, en ook hoe ze informatie willen inzien, op hun klimaatcomputer of via een externe dienst zoals Letsgrow.com. Bodemvochtgehalte sensoren zijn toegepast en geëvalueerd bij negen praktijktelers. Op basis van de resultaten is een specifi catie opgesteld voor de beste keus, een marktverkenning uitgevoerd, een handleiding geschreven voor het gebruik, en zijn twee typen robuuste sensoren gekozen en in een pilot experiment getest. Met de lysimeter kunnen telers ervaring opdoen, en zo hun strategie op langere termijn aanpassen. Met sensoren kunnen ze trends in bodemvocht volgen en hun dagelijkse gietbeurten daarop aanpassen. Modellen geven de mogelijk om anticiperend te sturen en water te geven naar behoefte van de plant, gericht op voorkomen van emissies

Effects of Treatment of Coronavirus Disease 2019 With Convalescent Plasma in 25 B-Cell-Depleted Patients

Twenty-five B-cell-depleted patients (24 following anti-CD19/20 therapy) diagnosed with coronavirus disease 2019 had been symptomatic for a median of 26 days but remained antibody negative. All were treated with convalescent plasma with high neutralizing antibody titers. Twenty-one (84%) recovered, indicating the potential therapeutic effects of this therapy in this particular population.</p

Endogeneity in Panel Data Models with Time-Varying and Time-Fixed Regressors: To IV or Not IV?

We analyse the problem of parameter inconsistency in panel data econometrics due to the correlation of exogenous variables with the error term. A common solution in this setting is to use Instrumental-Variable (IV) estimation in the spirit of Hausman-Taylor (1981). However, some potential shortcomings of the latter approach recently gave rise to the use of non-IV two-step estimators. Given their growing number of empirical applications, we aim to systematically compare the performance of IV and non-IV approaches in the presence of time-fixed variables and right hand side endogeneity using Monte Carlo simulations, where we explicitly control for the problem of IV selection in the Hausman-Taylor case. The simulation results show that the Hausman- Taylor model with perfect-knowledge about the underlying data structure (instrument orthogonality) has on average the smallest bias. However, compared to the empirically relevant specification with imperfect-knowledge and instruments chosen by statistical criteria, the non-IV rival performs equally well or even better especially in terms of estimating variable coefficients for time- fixed regressors. Moreover, the non-IV method tends to have a smaller root mean square error (rmse) than both Hausman-Taylor models with perfect and imperfect knowledge about the underlying correlation between r.h.s variables and residual term. This indicates that it is generally more efficient. The results are roughly robust for various combinations in the time and cross-section dimension of the data

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants