\u27Parental Track\u27 is Solution for Today\u27s Corporations, Says Men\u27s Activist; The New Entrepreneur: Student Operates Own Business, Attends Class Full Time

Feature leads for the media: Men\u27s studies specialist Eugene August suggests that corporations adopt policies to support a growing commitment to family life among couples with young children. University of Dayton student Marty Grunder is running a landscaping business while earning his degree in finance

Comparative study of some cardiovascular diseases risk factors in type D personality and non- type D personality

زمینه و هدف: ریخت شخصیتی D (Distressed personality) حدود 21 جامعه سالم را تشکیل داده است و به عنوان یک ریسک فاکتور در بروزبیماری های قلبی-عروقی شناخته می شود. این تحقیق به منظوربررسی برخی ریسک فاکتورهای بروز بیماری های قلبی در افراد بزرگسال سالم دارای ویژگی ریخت شناسی D انجام شده است. روش بررسی: در این مطالعه توصیفی-تحلیلی 54 نفر (زن و مرد) از بین مراجعه کنندگان به مرکز آزمایشگاهی المهدی شهرکرد به روش نمونه گیری در دسترس انتخاب شدند. افراد تحت مطالعه بر اساس مقیاس DS14 به دو گروه تقسیم شدند. 27 نفر آنها که دارای تیپ شخصیتی D بودند در گروه مورد و 27 نفر دیگر که فاقد تیپ شخصیتی Dبودند در گروه شاهد قرار گرفتند. داده های پژوهش از طریق آزمون افسردگی بِک (Beck)، مقیاس های اضطراب و خشم اسپیلبرگر و نتایج آزمایشگاهی کلسترول، تری گلیسیرید،LDL و HDL جمع آوری شدند. برای تجزیه و تحلیل داده ها ازآزمون t مستقل استفاده شد. یافته ها: میزان اضطراب، افسردگی، خشم و LDL در گروه مورد به طور معنی داری بیشتر از گروه شاهد بود بود (05/0>P). میزان HDL بصورت جزئی در گروه مورد کمتر از گروه شاهد بود (052/0= P) و ارتباط معنی داری بین شخصیت D وکلسترول و تری گلیسیرید دیده نشد (05/

Synchronizing Linear Heterogeneous Networks by Output Homogenization

This article deals with the synchronization of heterogeneous multi-agent systems. A simple distributed control law is provided to solve the problem. The presented approach is based on the idea to ascribe the heterogeneous case to a homogeneous synchronization task, for which the solution is well known. The presented method is applicable to networks of completely different agents, even with different dimensions. Additionally, the communication effort is minimized because only the states which are to be synchronized need to be exchanged through the network. An example illustrates the efficiency of the concept

Inference of single-cell phylogenies from lineage tracing data using Cassiopeia.

The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. First, we introduce Cassiopeia-a suite of scalable maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date, 34,557 human cells continuously traced over 15 generations, and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together, these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia

Building typological classification in Switzerland using deep learning methods for seismic assessment

Natural disasters, such as earthquakes, have always represented a danger to human life. Seismic risk assessment consists of the evaluation of existing buildings and their expected response in case of an earthquake; the exposure model of buildings plays a key role in risk calculations. With this respect, in recent years, advanced techniques have been developed to speed up and automatize the processes of data acquisition to data interpretation, although it is worth mentioning that the visual survey is essential to train and validate Machine Learning (ML) methods. In the present study, the identification of building types is conducted by exploiting the traditional visual survey to implement a Deep Learning (DL) classification model. As a first step, city mapping schemes are obtained by classifying buildings according to the main features (i.e., construction period and height classes). Then, Random Forest (RF), a supervised learning algorithm, is applied to classify different building types by exploiting all their attributes. The RF model is trained and tested on the cities of Neuchatel and Yverdon-Les-Bains. The decent accuracy of the results encourages the application of the method to different cities, with proper adjustments in datasets, features and algorithms

Robust observer-based fault detection and isolation in the standard control problem framework

This paper deals with the design of robust fault detection and isolation observers where only a single observer is employed to isolate different faults. To this end, the problem of parameterizing such observers is shown to be equivalent to designing a structurally constrained controller in the standard control problem framework. Thereby, the problem is reformulated as a well known classical control problem, which enables the use of existing tools to optimize robustness with respect to arbitrary exogenous disturbances. To account for parametric uncertainties, an approximate model matching approach is used

Root Locus Design for the Synchronization of Multi-Agent Systems in General Directed Networks

This paper considers the synchronization problem of multi-agent SISO systems with general unidirectional communication structures. A distributed control strategy is presented which relies on relative output differences of neighboring agents and, thus, does not need relative state information. We propose a root locus design method to determine the synchronization gain. Since in directed networks the characteristic equation for synchronization might be complex valued, we use tools from the complex root locus technique to solve the synchronization task

Molecular recording of mammalian embryogenesis.

Ontogeny describes the emergence of complex multicellular organisms from single totipotent cells. This field is particularly challenging in mammals, owing to the indeterminate relationship between self-renewal and differentiation, variation in progenitor field sizes, and internal gestation in these animals. Here we present a flexible, high-information, multi-channel molecular recorder with a single-cell readout and apply it as an evolving lineage tracer to assemble mouse cell-fate maps from fertilization through gastrulation. By combining lineage information with single-cell RNA sequencing profiles, we recapitulate canonical developmental relationships between different tissue types and reveal the nearly complete transcriptional convergence of endodermal cells of extra-embryonic and embryonic origins. Finally, we apply our cell-fate maps to estimate the number of embryonic progenitor cells and their degree of asymmetric partitioning during specification. Our approach enables massively parallel, high-resolution recording of lineage and other information in mammalian systems, which will facilitate the construction of a quantitative framework for understanding developmental processes

Discovery of antivirulence agents against methicillin-resistant staphylococcus aureus

Antivirulence agents inhibit the production of disease-causing virulence factors but are neither bacteriostatic nor bactericidal. Antivirulence agents against methicillin-resistant Staphylococcus aureus (MRSA) strain USA300, the most widespread community-associated MRSA strain in the United States, were discovered by virtual screening against the response regulator AgrA, which acts as a transcription factor for the expression of several of the most prominent S. aureus toxins and virulence factors involved in pathogenesis. Virtual screening was followed by similarity searches in the databases of commercial vendors. The small-molecule compounds discovered inhibit the production of the toxins alpha-hemolysin and phenol-soluble modulin α in a dose-dependent manner without inhibiting bacterial growth. These antivirulence agents are small-molecule biaryl compounds in which the aromatic rings either are fused or are separated by a short linker. One of these compounds is the FDA-approved nonsteroidal anti-inflammatory drug diflunisal. This represents a new use for an old drug. Antivirulence agents might be useful in prophylaxis and as adjuvants in antibiotic therapy for MRSA infections

Deferiprone: Pan-selective Histone Lysine Demethylase Inhibition Activity and Structure Activity Relationship Study

Deferiprone (DFP) is a hydroxypyridinone-derived iron chelator currently in clinical use for iron chelation therapy. DFP has also been known to elicit antiproliferative activities, yet the mechanism of this effect has remained elusive. We herein report that DFP chelates the Fe 2+ ion at the active sites of selected iron-dependent histone lysine demethylases (KDMs), resulting in pan inhibition of a subfamily of KDMs. Specifically, DFP inhibits the demethylase activities of six KDMs - 2A, 2B, 5C, 6A, 7A and 7B - with low micromolar IC 50 s while considerably less active or inactive against eleven KDMs - 1A, 3A, 3B, 4A-E, 5A, 5B and 6B. The KDM that is most sensitive to DFP, KDM6A, has an IC 50 that is between 7- and 70-fold lower than the iron binding equivalence concentrations at which DFP inhibits ribonucleotide reductase (RNR) activities and/or reduces the labile intracellular zinc ion pool. In breast cancer cell lines, DFP potently inhibits the demethylation of H3K4me3 and H3K27me3, two chromatin posttranslational marks that are subject to removal by several KDM subfamilies which are inhibited by DFP in cell-free assay. These data strongly suggest that DFP derives its anti-proliferative activity largely from the inhibition of a sub-set of KDMs. The docked poses adopted by DFP at the KDM active sites enabled identification of new DFP-based KDM inhibitors which are more cytotoxic to cancer cell lines. We also found that a cohort of these agents inhibited HP1-mediated gene silencing and one lead compound potently inhibited breast tumor growth in murine xenograft models. Overall, this study identified a new chemical scaffold capable of inhibiting KDM enzymes, globally changing histone modification profiles, and with specific anti-tumor activities