Roads and loans

Does financing respond to changes in productive opportunities, even for the world’s poor? We answer this question by examining the response of private bank financing to an infrastructure program that brought road access to unconnected Indian villages. This program prioritized roads for villages above specific population thresholds, allowing us to exploit the resultant discontinuities for identification. Using detailed data from a large bank, we find that 75% more villagers get loans, and the average amount lent to them is 30%–35% higher, in villages just above these thresholds. District-level analyses further suggest that roads and loans are complements in the growth process

Stress detection using machine learning and deep learning

Stress is a normal phenomenon in today's world, and it causes people to respond to a variety of factors, resulting in physiological and behavioural changes. If we keep stress in our minds for too long, it will have an effect on our bodies. Many health conditions associated with stress can be avoided if stress is detected sooner. When a person is stressed, a pattern can be detected using various bio-signals such as thermal, electrical, impedance, acoustic, optical, and so on, and stress levels can be identified using these bio-signals. This paper uses a dataset that was obtained using an Internet of Things (IOT) sensor, which led to the collection of information about a real-life situation involving a person's mental health. To obtain a pattern for stress detection, data from sensors such as the Galvanic Skin Response Sensor (GSR) and the Electrocardiogram (ECG) were collected. The dataset will then be categorised using Multilayer Perceptron (MLP), Decision Tree (DT), K-Nearest Neighbour (KNN), Support Vector Machine (SVM), and Deep Learning algorithms (DL). Accuracy, precision, recall, and F1-Score are used to assess the data's performance. Finally, Decision Tree (DT) had the best performance where DT have accuracy 95%, precision 96%, recall 96% and F1-score 96% among all machine learning classifiers

Bio-inspired fabrication of DNA-inorganic hybrid composites using synthetic DNA

Nucleic acid nanostructures have attracted significant interest as potential therapeutic and diagnostic platforms due to their intrinsic biocompatibility and biodegradability, structural and functional diversity, and compatibility with various chemistries for modification and stabilization. Among the fabrication approaches for such structures, the rolling circle techniques have emerged as particularly promising, producing morphologically round, flower-shaped nucleic acid particles: typically hybrid composites of long nucleic acid strands and inorganic magnesium pyrophosphate (Mg2PPi). These constructs are known to form via anisotropic nucleic acid-driven crystallization in a sequence-independent manner, rendering monodisperse and densely packed RNA or DNA–inorganic composites. However, it still remains to fully explore how flexible polymer-like RNA or DNA strands (acting as biomolecular additives) mediate the crystallization process of Mg2PPi and affect the structure and properties of the product crystals. To address this, we closely examined nanoscale details to mesoscopic features of Mg2PPi/DNA hybrid composites fabricated by two approaches, namely rolling circle amplification (RCA)-based in situ synthesis and long synthetic DNA-mediated crystallization. Similar to the DNA constructs fabricated by RCA, the rapid crystallization of Mg2PPi was retarded on a short-range order when we precipitated the crystals in the presence of presynthesized long DNA, which resulted in effective incorporation of biomolecular additives such as DNA and enzymes. These findings further provide a more feasible way to encapsulate bioactive enzymes within DNA constructs compared to in situ RCA-mediated synthesis, i.e., by not only protecting them from possible denaturation under the reaction conditions but also preventing nonselective association of proteins arising from the RCA reaction mixtures

A finite model of two-dimensional ideal hydrodynamics

A finite-dimensional su($N$) Lie algebra equation is discussed that in the infinite $N$ limit (giving the area preserving diffeomorphism group) tends to the two-dimensional, inviscid vorticity equation on the torus. The equation is numerically integrated, for various values of $N$, and the time evolution of an (interpolated) stream function is compared with that obtained from a simple mode truncation of the continuum equation. The time averaged vorticity moments and correlation functions are compared with canonical ensemble averages.Comment: (25 p., 7 figures, not included. MUTP/92/1

Cup products on polyhedral approximations of 3D digital images

Let I be a 3D digital image, and let Q(I) be the associated cubical complex. In this paper we show how to simplify the combinatorial structure of Q(I) and obtain a homeomorphic cellular complex P(I) with fewer cells. We introduce formulas for a diagonal approximation on a general polygon and use it to compute cup products on the cohomology H *(P(I)). The cup product encodes important geometrical information not captured by the cohomology groups. Consequently, the ring structure of H *(P(I)) is a finer topological invariant. The algorithm proposed here can be applied to compute cup products on any polyhedral approximation of an object embedded in 3-space

Image cytometric analysis of p53 and mdm-2 expression in primary and recurrent mucoepidermoid carcinoma of parotid gland: immunohistochemical study

<p>Abstract</p> <p>Aims and Objectives</p> <p>This study aims to analyze immunocytochemically p53 aberrant expression and mdm-2 expression in primary and recurrent mucoepidermoid carcinoma (MEC) of parotid gland and to ascertain if expression of these markers correlates with tumor behavior, clinical outcome, histological grade and local recurrence.</p> <p>Methods</p> <p>20 cases histologically diagnosed as primary MEC with different grades were included in the study. Out of 20 cases, 7 were classified as grade I, 8 as grade II and 5 as grade III. Immunohistochemical staining of these 20 primary cases as well as 6 recurrent cases with anti-p53 and anti-mdm-2 antibodies was carried out. Area fraction of immunopositivity was estimated by image analysis software.</p> <p>Results</p> <p>16/20 primary cases were p53 +ve (80%). The p53 positive cases included 3 cases classified as grade (I), 8 cases as grade (II) and 5 cases as grade (III). All 6 recurrent cases were p53 +ve. On the other hand, 14/20 primary and only 2/6 recurrent cases were mdm-2 +ve. The mdm-2 +ve primary cases included 2 classified as grade (I), 7 as grade (II) and 5 as grade (III). 12 primary MEC showed co-expression of both p53 and mdm-2 of which 2 cases showed local recurrence.</p> <p>Conclusions</p> <p>these data suggested that expression of p53 and mdm-2 in primary and recurrent MEC correlates with the high histological grade. P53 aberrant expression is not only considered as an early event in MEC carcinogenesis but also correlates to tumor behavior and local recurrence. Mdm-2 overexpression is correlated to pathogenesis of MEC. However, no strong evidence was found between mdm-2 expression and MEC local recurrence.</p

On wavenumber spectra for sound within subsonic jets

This paper explores the nature of sound spectra within subsonic jets. Three problems of increasing complexity are presented. First, a point source is placed in a two-dimensional plug flow and the sound field is obtained analytically. Second, a point source is embedded in a diverging axisymmetric jet and the sound field is obtained by solving the linearized Euler equations. Finally, an analysis of the acoustic waves propagating through a turbulent jet obtained by direct numerical simulation is presented. In each problem, the pressure or density field is analyzed in the frequency-wavenumber domain. It is found that acoustic waves can be classified into three main frequency-dependent groups. A physical justification is provided for this classification. The main conclusion is that, at low Strouhal numbers, acoustic waves satisfy the d'Alembertian dispersion relation