Stem cells and fluid flow drive cyst formation in an invertebrate excretory organ.

Cystic kidney diseases (CKDs) affect millions of people worldwide. The defining pathological features are fluid-filled cysts developing from nephric tubules due to defective flow sensing, cell proliferation and differentiation. The underlying molecular mechanisms, however, remain poorly understood, and the derived excretory systems of established invertebrate models (Caenorhabditis elegans and Drosophila melanogaster) are unsuitable to model CKDs. Systematic structure/function comparisons revealed that the combination of ultrafiltration and flow-associated filtrate modification that is central to CKD etiology is remarkably conserved between the planarian excretory system and the vertebrate nephron. Consistently, both RNA-mediated genetic interference (RNAi) of planarian orthologues of human CKD genes and inhibition of tubule flow led to tubular cystogenesis that share many features with vertebrate CKDs, suggesting deep mechanistic conservation. Our results demonstrate a common evolutionary origin of animal excretory systems and establish planarians as a novel and experimentally accessible invertebrate model for the study of human kidney pathologies

Spin dependent photoelectron tunnelling from GaAs into magnetic Cobalt

The spin dependence of the photoelectron tunnel current from free standing GaAs films into out-of- plane magnetized Cobalt films is demonstrated. The measured spin asymmetry (A) resulting from a change in light helicity, reaches +/- 6% around zero applied tunnel bias and drops to +/- 2% at a bias of -1.6 V applied to the GaAs. This decrease is a result of the drop in the photoelectron spin polarization that results from a reduction in the GaAs surface recombination velocity. The sign of A changes with that of the Cobalt magnetization direction. In contrast, on a (nonmagnetic) Gold film A ~ 0%

Epstein-Barr Virus–induced Molecule 1 Ligand Chemokine Is Expressed by Dendritic Cells in Lymphoid Tissues and Strongly Attracts Naive T Cells and Activated B Cells

Movement of T and B lymphocytes through secondary lymphoid tissues is likely to involve multiple cues that help the cells navigate to appropriate compartments. Epstein-Barr virus– induced molecule 1 (EBI-1) ligand chemokine (ELC/MIP3β) is expressed constitutively within lymphoid tissues and may act as such a guidance cue. Here, we have isolated mouse ELC and characterized its expression pattern and chemotactic properties. ELC is expressed constitutively in dendritic cells within the T cell zone of secondary lymphoid tissues. Recombinant ELC was strongly chemotactic for naive (L-selectinhi) CD4 T cells and for CD8 T cells and weakly attractive for resting B cells and memory (L-selectinlo) CD4 T cells. After activation through the B cell receptor, the chemotactic response of B cells was enhanced. Like its human counterpart, murine ELC stimulated cells transfected with EBI-1/CC chemokine receptor 7 (CCR7). Our findings suggest a central role for ELC in promoting encounters between recirculating T cells and dendritic cells and in the migration of activated B cells into the T zone of secondary lymphoid tissues

ADDMC: Weighted Model Counting with Algebraic Decision Diagrams

We present an algorithm to compute exact literal-weighted model counts of Boolean formulas in Conjunctive Normal Form. Our algorithm employs dynamic programming and uses Algebraic Decision Diagrams as the primary data structure. We implement this technique in ADDMC, a new model counter. We empirically evaluate various heuristics that can be used with ADDMC. We then compare ADDMC to state-of-the-art exact weighted model counters (Cachet, c2d, d4, and miniC2D) on 1914 standard model counting benchmarks and show that ADDMC significantly improves the virtual best solver.Comment: Presented at AAAI 202

System Energy-Efficient Hybrid Beamforming for mmWave Multi-user Systems

This paper develops energy-efficient hybrid beamforming designs for mmWave multi-user systems where analog precoding is realized by switches and phase shifters such that radio frequency (RF) chain to transmit antenna connections can be switched off for energy saving. By explicitly considering the effect of each connection on the required power for baseband and RF signal processing, we describe the total power consumption in a sparsity form of the analog precoding matrix. However, these sparsity terms and sparsity-modulus constraints of the analog precoding make the system energy-efficiency maximization problem non-convex and challenging to solve. To tackle this problem, we first transform it into a subtractive-form weighted sum rate and power problem. A compressed sensing-based re-weighted quadratic-form relaxation method is employed to deal with the sparsity parts and the sparsity-modulus constraints. We then exploit alternating minimization of the mean-squared error to solve the equivalent problem where the digital precoding vectors and the analog precoding matrix are updated sequentially. The energy efficiency upper bound and a heuristic algorithm are also examined for comparison purposes. Numerical results confirm the superior performances of the proposed algorithm over benchmark energy-efficiency hybrid precoding algorithms and heuristic ones.Comment: submitted to TGC

Estimation of Travel Times for Minor Roads in Urban Areas Using Sparse Travel Time Data

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link

n-Gram-based text compression

We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.Web of Scienceart. no. 948364