Key Parameters for Strength Control of Artificially Cemented Soils

Often, the use of traditional techniques in geotechnical engineering faces obstacles of economical and environmental nature. The addition of cement becomes an attractive technique when the project requires improvement of the local soil. The treatment of soils with cement finds application, for instance, in the construction of pavement base layers, in slope protection of earth dams, and as a support layer for shallow foundations. However, there are no dosage methodologies based on rational criteria as exist in the case of the concrete technology, where the water/cement ratio plays a fundamental role in the assessment of the target strength. This study therefore aims to quantify the influence of the amount of cement, the porosity and the moisture content on the strength of a sandy soil artificially cemented, as well as to evaluate the use of a water/cement ratio and a voids/cement ratio to assess its unconfined compression strength. A number of unconfined compression tests, triaxial compression tests, and measurements of matric suction were carried out. The results show that the unconfined compression strength increased linearly with the increase in the cement content and exponentially with the reduction in porosity of the compacted mixture. The change in moisture content also has a marked effect on the unconfined compression strength of mixtures compacted at the same dry density. It was shown that, for the soil-cement mixture in an unsaturated state (which is usual for compacted fills), the water/cement ratio is not a good parameter for the assessment of unconfined compression strength. In contrast, the voids/cement ratio, defined as the ratio between the porosity of the compacted mixture and the volumetric cement content, is demonstrated to be the most appropriate parameter to assess the unconfined compression strength of the soil-cement mixture studied.     

Modeling the Direct Synthesis of Dimethyl Ether using Artificial Neural Networks

Artificial neural networks (ANNs) are designed and implemented to model the direct synthesis of dimethyl ether (DME) from syngas over a commercial catalyst system. The predictive power of the ANNs is assessed by comparison with the predictions of a lumped model parameterized to fit the same data used for ANN training. The ANN training converges much faster than the parameter estimation of the lumped model, and the predictions show a higher degree of accuracy under all conditions. Furthermore, the simulations show that the ANN predictions are also accurate even at some conditions beyond the validity range.     

A Microfluidic 3D Endothelium-on-a-Chip Model to Study Transendothelial Migration of T Cells in Health and Disease

The recruitment of T cells is a crucial component in the inflammatory cascade of the body. The process involves the transport of T cells through the vascular system and their stable arrest to vessel walls at the site of inflammation, followed by extravasation and subsequent infiltration into tissue. Here, we describe an assay to study 3D T cell dynamics under flow in real time using a high-throughput, artificial membrane-free microfluidic platform that allows unimpeded extravasation of T cells. We show that primary human T cells adhere to endothelial vessel walls upon perfusion of microvessels and can be stimulated to undergo transendothelial migration (TEM) by TNFα-mediated vascular inflammation and the presence of CXCL12 gradients or ECM-embedded melanoma cells. Notably, migratory behavior was found to differ depending on T cell activation states. The assay is unique in its comprehensiveness for modelling T cell trafficking, arrest, extravasation and migration, all in one system, combined with its throughput, quality of imaging and ease of use. We envision routine use of this assay to study immunological processes and expect it to spur research in the fields of immunological disorders, immuno-oncology and the development of novel immunotherapeutics.     

A new correlation for the coefficient of restitution of particles with low mechanical resistance for modeling wastewater treatment biofilm reactors

Clean Technologies and Environmental Policy - Fluidized bed bioreactors are widely used in wastewater treatment applications. Such reactors employ gel beads or hard particles covered with a biofilm...     

Assessing and interpreting personality change and continuity in patients treated for major depression.

Structural, mean- and individual-level, differential, and ipsative personality continuity were examined in 599 patients treated for major depression assigned to 1 of 6 forms of a 6-month pharmaco-psychotherapy program. Covariation among traits from the Five Factor model remained invariant across treatment, and patients described themselves as slightly more extraverted, open to experience, agreeable and conscientious, and substantially more emotional stable after treatment. Trait changes were only to a small extent explained by changes in depression severity. There was evidence for differential, individual-level, and ipsative stability, with stable personality profiles in terms of shape and to a lesser extent in terms of scatter and elevation. Traits remain relatively stable, except for emotional stability, despite the depressive state and the psychopharmacological interventions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Radiomics and Machine Learning in Oral Healthcare

The increasing storage of information, data, and forms of knowledge has led to the development of new technologies that can help to accomplish complex tasks in different areas, such as in dentistry. In this context, the role of computational methods, such as radiomics and Artificial Intelligence (AI) applications, has been progressing remarkably for dentomaxillofacial radiology (DMFR). These tools bring new perspectives for diagnosis, classification, and prediction of oral diseases, treatment planning, and for the evaluation and prediction of outcomes, minimizing the possibilities of human errors. A comprehensive review of the state‐of‐the‐art of using radiomics and machine learning (ML) for imaging in oral healthcare is presented in this paper. Although the number of published studies is still relatively low, the preliminary results are very promising and in a near future, an augmented dentomaxillofacial radiology (ADMFR) will combine the use of radiomics‐based and AI‐based analyses with the radiologist's evaluation. In addition to the opportunities and possibilities, some challenges and limitations have also been discussed for further investigations.     

Effects of repeated practice and contextual-writing experiences on college students' writing skills.

The authors examined the effects of both general and task-specific writing experiences on college students' writing-skill development. On the basis of theories of expertise development and a cognitive process theory of writing-skill development, the authors predicted that repeated practice would be associated with superior writing skills and that after controlling for repeated practice, writing within a specific task domain would be associated with superior writing skills. Undergraduate students participated in a field experiment in which 279 students practiced their writing skills in a professionally relevant task domain, whereas another group of 385 students practiced their writing skills in a more general domain. The results were consistent with the predictions. The authors discuss implications for teaching writing skills and for general theories of expertise development in writing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fungal Effectoromics: A World in Constant Evolution

Effectors are small, secreted molecules that mediate the establishment of interactions in nature. While some concepts of effector biology have stood the test of time, this area of study is ever-evolving as new effectors and associated characteristics are being revealed. In the present review, the different characteristics that underly effector classifications are discussed, contrasting past and present knowledge regarding these molecules to foster a more comprehensive understanding of effectors for the reader. Research gaps in effector identification and perspectives for effector application in plant disease management are also presented, with a focus on fungal effectors in the plant-microbe interaction and interactions beyond the plant host. In summary, the review provides an amenable yet thorough introduction to fungal effector biology, presenting noteworthy examples of effectors and effector studies that have shaped our present understanding of the field.     

Advances of Epigenetic Biomarkers and Epigenome Editing for Early Diagnosis in Breast Cancer

Epigenetic modifications are known to regulate cell phenotype during cancer progression, including breast cancer. Unlike genetic alterations, changes in the epigenome are reversible, thus potentially reversed by epi-drugs. Breast cancer, the most common cause of cancer death worldwide in women, encompasses multiple histopathological and molecular subtypes. Several lines of evidence demonstrated distortion of the epigenetic landscape in breast cancer. Interestingly, mammary cells isolated from breast cancer patients and cultured ex vivo maintained the tumorigenic phenotype and exhibited aberrant epigenetic modifications. Recent studies indicated that the therapeutic efficiency for breast cancer regimens has increased over time, resulting in reduced mortality. Future medical treatment for breast cancer patients, however, will likely depend upon a better understanding of epigenetic modifications. The present review aims to outline different epigenetic mechanisms including DNA methylation, histone modifications, and ncRNAs with their impact on breast cancer, as well as to discuss studies highlighting the central role of epigenetic mechanisms in breast cancer pathogenesis. We propose new research areas that may facilitate locus-specific epigenome editing as breast cancer therapeutics.     

Effects of a Corneal Anesthetic on Extinction of the Classically Conditioned Nictitating Membrane Response in the Rabbit (Oryctolagus cuniculus).

Rabbits (Oryctolagus cuniculus) were presented with 7 daily sessions of tone-alone training after conditioning. Before the beginning of each of the first 4 extinction sessions, an artificial tear solution or tetracaine hydrochloride was administered to the cornea of rabbits in the control group (n=6) and experimental group (n=1), respectively. There were no between-group differences in the percentage of conditioned responses between both groups. However, the amplitude of the conditioned response was notably reduced in the tetracaine group (M=0.40, SEM±0.216) relative to the control group (M=1.32, SEM ±0.639) early in extinction. Results seem to suggest that although motor output has been found to play an important role in extinction, corneal sensory feedback is not necessary. (PsycINFO Database Record (c) 2010 APA, all rights reserved)