PCP Characterizations of NP: Toward a Polynomially-Small Error-Probability

This paper strengthens the low-error PCP characterization of NP, coming closer to the upper limit of the BGLR conjecture. Consider the task of verifying a written proof for the membership of a given input in an NP language. In this paper, this is achieved by making a constant number of accesses to the proof, obtaining error probability that is exponentially small in the total number of bits that are read.     

Why and how can human-related measures support software development processes?

In this paper we discuss why and how measures related to human aspects should be incorporated into software development processes. This perspective is based on the vast evidence that human aspects are the source of the majority of problems associated with software development projects. Having said that, we do not blame the humans involved in software development processes; rather, we suggest that human-related measures might be one means by which human aspects of software development processes can be supported.     

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population''s infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease''s specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (R_e) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age–class structure, and a maximum likelihood methodology allows us to estimate the model''s next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of ‘who-infected-who’. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias.     

miRNAs as Biomarkers in Diabetes: Moving towards Precision Medicine

Diabetes mellitus (DM) is a complex metabolic disease with many specifically related complications. Early diagnosis of this disease could prevent the progression to overt disease and its related complications. There are several limitations to using existing biomarkers, and between 24% and 62% of people with diabetes remain undiagnosed and untreated, suggesting a large gap in current diagnostic practices. Early detection of the percentage of insulin-producing cells preceding loss of function would allow for effective therapeutic interventions that could delay or slow down the onset of diabetes. MicroRNAs (miRNAs) could be used for early diagnosis, as well as for following the progression and the severity of the disease, due to the fact of their pancreatic specific expression and stability in various body fluids. Thus, many studies have focused on the identification and validation of such groups or “signatures of miRNAs” that may prove useful in diagnosing or treating patients. Here, we summarize the findings on miRNAs as biomarkers in diabetes and those associated with direct cellular reprogramming strategies, as well as the relevance of miRNAs that act as a bidirectional switch for cell therapy of damaged pancreatic tissue and the studies that have measured and tracked miRNAs as biomarkers in insulin resistance are addressed.     

Nanomechanics of Biomaterials – from Cells to Shells

Biological organisms are inherently complex. Although investigations of the function and design of living organisms have existed since the dawn of science, only in recent years have the tools existed to extend such studies to the nanoscale. Progress in nanomechanics of biological systems has enabled our understanding of intricate mechanical designs which nature has optimized for specific functions. This review provides an overview of the field of bionanomechanics, emphasizing the manner in which fundamental mechanical concepts are expressed in the design of a wide spectrum of biological specimens. We show that diverse species exploit common concepts to achieve desired function; a principle that extends over large scales of size and mechanical properties. The powerful techniques that enable such studies, particularly atomic force microscopy and instrumented nanoindentation, as well as common analytical approaches are given special attention.     

Buffer gas effect on ground and metastable populations in a pulsed CuBr laser

We have measured the time dependence of the concentration of copper atoms in the ground and metastable states in a pulsed CuBr laser by monitoring the absorption of the atomic copper lines 244.2 and 510.6 nm. In agreement with previous measurements in a CuCl laser, we found the populations to grow after the dissociation pulse, peaking many tens of microseconds later. Temperature and buffer gas species and pressure have a considerable influence on the details of the temporal evolution. The results are interpreted in terms of a schematic mechanism involving parallel dissociation processes. Qualitative agreement with the experimental results is quite good, but no attempt was made to elucidate the physical processes which actually occur during and after the dissociation pulse. In the course of the experiment the radiative transition probability of the 244.2 nm line was measured and found to be0.26 times 10^{-7}s^-1.     

RNA labeling and immobilization for nano-displacement measurement: probing three-dimensional RNA structure

RNA molecules play essential roles in many biological processes, including the storage and transfer of information in the cell. These events are mediated via RNA-protein interactions or by catalytic RNA molecules. It is now recognized that unique RNA folds are associated with biological functions. Therefore, to study the intrinsic structural changes and dynamics which regulate the various functions of RNA, it is necessary to probe its three-dimensional structure in solution. In this respect, using single-molecule methodologies may allow study of native RNA molecules independent of their size and in real time. However, this may require the immobilization of RNA on a surface. Here, we report a novel approach to immobilize RNA on a glass. The procedures involve both chemical and enzymatic modifications of long RNA molecules. In addition, we demonstrate the application of an optical tweezers apparatus to measure the length and, hence, the dynamics of immobilized intact ribosomal RNA molecules as a function of different solution conditions.