Cortical cholinergic impairment and behavioral deficits produced by kainic acid lesions of rat magnocellular basal forebrain.

The rat magnocellular basal forebrain (MNBF) is homologous to the human nucleus basalis of Meynert, a structure implicated in the cholinergic hypothesis of cognitive impairment in Alzheimer's disease (AD). In the present study, 18 male Sprague-Dawley rats with kainic acid lesions in the MNBF were compared with 6 unoperated controls, 10 sham-operated controls, and 6 controls injected with kainic acid in the cortical area directly above the MNBF. MNBF lesions depleted choline acetyltransferase in cortex but not in striatum or hippocampus. Cortical dopamine levels were unchanged; serotonin levels were unchanged in hippocampus and parietal cortex but decreased in frontal cortex. Compared with controls, MNBF-lesioned Ss were impaired in 24-hr retention, but not acquisition, of a passive avoidance task with escapable footshock. The groups did not differ in mean number of daily avoidances on a barpress active avoidance task, although learning was slower in MNBF-lesioned Ss. In a serial spatial discrimination reversal test, MNBF-lesioned Ss performed significantly worse than controls. This model may be useful for studying the role of the cholinergic system in memory and possibly for developing treatment strategies to alleviate the cognitive dysfunction of AD. (63 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance.

Addresses issues related to partial measurement invariance using a tutorial approach based on the {lisrel} confirmatory factor analytic model. Specifically, we demonstrate procedures for (a) using "sensitivity analyses" to establish stable and substantively well-fitting baseline models, (b) determining partially invariant measurement parameters, and (c) testing for the invariance of factor covariance and mean structures, given partial measurement invariance. We also show, explicitly, the transformation of parameters from an all-X to an all-Y model specification, for purposes of testing mean structures. These procedures are illustrated with multidimensional self-concept data from low (n?=?248) and high (n?=?582) academically tracked high school adolescents. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

The impact of risk and protective factors on online teaching experience in high school Italian teachers during the COVID-19 pandemic

The lockdown due to COVID-19 in Italy resulted in the sudden closure of schools, with a shift from traditional teaching to the online one. Through an online questionnaire, this survey explores teachers' experience of online teaching, the level of risk factors (e.g., stress) and protective factors (e.g., locus of control) and their impact on satisfaction levels during the social distancing. One hundred seven high school teachers from Lombardy, an Italian region very affected by the COVID-19 outbreak, participated. Results show that depression and stress are the main predictors of satisfaction levels for online teaching. In addition, coping, locus of control and self-efficacy emerge as important protective factors. Finally, although there is great satisfaction with the online teaching experience, critical elements emerged. This study is relevant because it describes the critical elements of the online teaching experience, and identifies some protective factors and the main risk factors in teachers operating in an area strongly marked by social restrictions imposed by the pandemic. High school teachers emerge as a sub-group of the general population with specific psychological reactions. Considering the results, it is possible to suggest providing high-quality educational support and crisis-psychological oriented services to teachers, and help to maintain the psychological well-being.     

Loveparade 2010: Automatic video analysis of a crowd disaster

On July 24, 2010, 21 people died and more than 500 were injured in a stampede at the Loveparade, a music festival, in Duisburg, Germany. Although this tragic incident is but one among many terrible crowd disasters that occur during pilgrimage, sports events, or other mass gatherings, it stands out for it has been well documented: there were a total of seven security cameras monitoring the Loveparade and the chain of events that led to disaster was meticulously reconstructed.In this paper, we present an automatic, video-based analysis of the events in Duisburg. While physical models and simulations of human crowd behavior have been reported before, to the best of our knowledge, automatic vision systems that detect congestions and dangerous crowd turbulences in real world settings were not reported yet. Derived from lessons learned from the video footage of the Loveparade, our system is able to detect motion patterns that characterize crowd behavior in stampedes. Based on our analysis, we propose methods for the detection and early warning of dangerous situations during mass events. Since our approach mainly relies on optical flow computations, it runs in real-time and preserves privacy of the people being monitored.     

Interactive Genetic Algorithm with Mixed Initiative Interaction for multi-criteria ground water monitoring design

Design of optimal plans for environmental planning and management applications should ideally consider the multiple quantitative and qualitative criteria relevant to the problem. For example, in ground water monitoring design problems, qualitative criteria such as acceptable spatial extent and shape of the contaminant plume predicted from the monitored locations can be equally important as the typical quantitative criteria such as economic costs and contaminant prediction accuracy. Incorporation of qualitative criteria in the problem-solving process is typically done in one of two ways: (a) quantifying approximate representations of the qualitative criteria, which are then used as additional criteria during the optimization process, or (b) post-optimization analysis of designs by experts to evaluate the overall performance of the optimized designs with respect to the qualitative criteria. These approaches, however, may not adequately represent all of the relevant qualitative information that affect a human expert involved in design (e.g. engineers, stakeholders, regulators, etc.), and do not necessarily incorporate the effect of the expert's own learning process on the suitability of the final design. The Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) is a novel approach that addresses these limitations by using a collaborative human-computer search strategy to assist users in designing optimized solutions to their applications, while also learning about their problem. The algorithm adaptively learns from the expert's feedback, and explores multiple designs that meet her/his criteria using both the human expert and a simulated model of the expert's responses in a collaborative fashion. The algorithm provides an introspection-based learning framework for the human expert and uses the human's subjective confidence measures to adjust the optimization search process to the transient learning process of the user. This paper presents the design and testing of this computational framework, and the benefits of using this approach for solving groundwater monitoring design problems.     

Steel-to-concrete bond after concrete splitting: test results

The definite trend towards the use of large-diameter rebars and the introduction of high-strength steels (f _y=500 to 600 MPa) make it necessary to study the effects of longitudinal splitting on the steel-to-concrete bond. The study of splitting effects requires firstly basic tests to be performed in order to gather experimental information on bond and confinement stresses acting at the bar-to-concrete interface. For this purpose, three series of tests were recently carried out at the Politecnico di Milano. The results make it possible to ascertain a few basic properties of the bond after concrete splitting, and to formulate empirical constitutive laws regarding the stresses and the displacements (bar slip and opening of the splitting crack). All specimens consisted of a short deformed bar embedded in a concrete block, which had a preformed splitting crack in the plane passing through the bar axis: twelve specimens (Tests A and C) were fitted up with a round deformed bar having crescent-shaped lugs (D_b=18 mm); seven specimens (Tests B) were fitted up with a specially machined deformed bar having a rectangular cross-section and straigth, lugs, so that concrete deterioration close to the bar could be investigated at the surface of the specimen, by means of the moiré technique. The tests were carried out at constant slip rate, up to very large slip values ( ); both the ascending and the descending branches of the stress-slip curves were measured, for four different values of the opening of the splitting crack. The agreement among the results of the three series is generally satisfactory and often very good: consequently, constitutive laws regarding the four main variables (crack opening and bar slip, shear and confinement stresses) can be worked out, as will be shown in a companion paper on constitutive relationships and on concrete deterioration at the bar-to-concrete interface.     

The Effect of Hypoxia on the Expression of CXC Chemokines and CXC Chemokine Receptors—A Review of Literature

Hypoxia is an integral component of the tumor microenvironment. Either as chronic or cycling hypoxia, it exerts a similar effect on cancer processes by activating hypoxia-inducible factor-1 (HIF-1) and nuclear factor (NF-κB), with cycling hypoxia showing a stronger proinflammatory influence. One of the systems affected by hypoxia is the CXC chemokine system. This paper reviews all available information on hypoxia-induced changes in the expression of all CXC chemokines (CXCL1, CXCL2, CXCL3, CXCL4, CXCL5, CXCL6, CXCL7, CXCL8 (IL-8), CXCL9, CXCL10, CXCL11, CXCL12 (SDF-1), CXCL13, CXCL14, CXCL15, CXCL16, CXCL17) as well as CXC chemokine receptors—CXCR1, CXCR2, CXCR3, CXCR4, CXCR5, CXCR6, CXCR7 and CXCR8. First, we present basic information on the effect of these chemoattractant cytokines on cancer processes. We then discuss the effect of hypoxia-induced changes on CXC chemokine expression on the angiogenesis, lymphangiogenesis and recruitment of various cells to the tumor niche, including myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), tumor-associated neutrophils (TANs), regulatory T cells (T_regs) and tumor-infiltrating lymphocytes (TILs). Finally, the review summarizes data on the use of drugs targeting the CXC chemokine system in cancer therapies.     

Auxin and Root Gravitropism: Addressing Basic Cellular Processes by Exploiting a Defined Growth Response

Root architecture and growth are decisive for crop performance and yield, and thus a highly topical research field in plant sciences. The root system of the model plant Arabidopsis thaliana is the ideal system to obtain insights into fundamental key parameters and molecular players involved in underlying regulatory circuits of root growth, particularly in responses to environmental stimuli. Root gravitropism, directional growth along the gravity, in particular represents a highly sensitive readout, suitable to study adjustments in polar auxin transport and to identify molecular determinants involved. This review strives to summarize and give an overview into the function of PIN-FORMED auxin transport proteins, emphasizing on their sorting and polarity control. As there already is an abundance of information, the focus lies in integrating this wealth of information on mechanisms and pathways. This overview of a highly dynamic and complex field highlights recent developments in understanding the role of auxin in higher plants. Specifically, it exemplifies, how analysis of a single, defined growth response contributes to our understanding of basic cellular processes in general.