Introduction to Python Dynamic Diffraction Toolkit (PyDDT): structural refinement of single crystals via X-ray phase measurements.

PyDDT is a free Python package of computer codes for exploiting X-ray dynamic multiple diffraction in single crystals. A wide range of tools are available for evaluating the usefulness of the method, planning feasible experiments, extracting phase information from experimental data and further improving model structures of known materials. Graphical tools are also useful in analytical methodologies related to the three-dimensional aspect of multiple diffraction. For general X-ray users, the PyDDT tutorials provide the insight needed to understand the principles of phase measurements and other related methodologies. Key points behind structure refinement using the current approach are presented, and the main features of PyDDT are illustrated for amino acid and filled skutterudite single crystals.

Metal ion content of internal organs in the calorically restricted Wistar rat.

BACKGROUND: Despite the agreed principle that access to food is a human right, undernourishment and metal ion deficiencies are public health problems worldwide, exacerbated in impoverished or war-affected areas. It is known that maternal malnutrition causes growth retardation and affects behavioral and cognitive development of the newborn. Here we ask whether severe caloric restriction leads per se to disrupted metal accumulation in different organs of the Wistar rat. METHODS: Inductively coupled plasma optical emission spectroscopy was used to determine the concentration of multiple elements in the small and large intestine, heart, lung, liver, kidney, pancreas, spleen, brain, spinal cord, and three skeletal muscles from control and calorically restricted Wistar rats. The caloric restriction protocol was initiated from the mothers prior to mating and continued throughout gestation, lactation, and post-weaning up to sixty days of age. RESULTS: Both sexes were analyzed but dimorphism was rare. The pancreas was the most affected organ presenting a higher concentration of all the elements analyzed. Copper concentration decreased in the kidney and increased in the liver. Each skeletal muscle responded to the treatment differentially: Extensor Digitorum Longus accumulated calcium and manganese, gastrocnemius decreased copper and manganese, whereas soleus decreased iron concentrations. Differences were also observed in the concentration of elements between organs independently of treatment: The soleus muscle presents a higher concentration of Zn compared to the other muscles and the rest of the organs. Notably, the spinal cord showed large accumulations of calcium and half the concentration of zinc compared to brain. X-ray fluorescence imaging suggests that the extra calcium is attributable to the presence of ossifications whereas the latter finding is attributable to the low abundance of zinc synapses in the spinal cord. CONCLUSION: Severe caloric restriction did not lead to systemic metal deficiencies but caused instead specific metal responses in few organs.

Is the Corpus Ready for Machine Translation? A Case Study with Python to Pseudo-Code Corpus.

The availability of data is the driving force behind most of the state-of-the-art techniques for machine translation tasks. Understandably, this availability of data motivates researchers to propose new techniques and claim about the superiority of their techniques over the existing ones by using suitable evaluation measures. However, the performance of underlying learning algorithms can be greatly influenced by the correctness and the consistency of the corpus. We present our investigations for the relevance of a publicly available python to pseudo-code parallel corpus for automated documentation task, and the studies performed using this corpus. We found that the corpus had many visible issues like overlapping of instances, inconsistency in translation styles, incompleteness, and misspelled words. We show that these discrepancies can significantly influence the performance of the learning algorithms to the extent that they could have caused previous studies to draw incorrect conclusions. We performed our experimental study using statistical machine translation and neural machine translation models. We have recorded a significant difference ( ∼  10% on BLEU score) in the models' performance after removing the issues from the corpus.

Edges and gradients in lightness illusions: Role of optical veiling glare.

Lightness Illusions (Contrast, Assimilation, and Natural Scenes with Edges and Gradients) show that appearances do not correlate with the light sent from the scene to the eye. Lightness Illusions begin with a control experiment that includes two identical Gray Regions-Of-Interest(GrayROI) that have equal appearances in uniform surrounds. The Illusion experiment modifies "the-rest-of-the-scene" to make these GrayROIs appear different from each other. Our visual system performs complex-spatial transformations of scene-luminance patterns using two independent spatial mechanisms: optical and neural. First, optical veiling glare transforms scene luminances into a different light pattern on receptors, called retinal contrasts. This article provides a new Python program that calculates retinal contrast. Equal scene luminances become unequal retinal contrasts. Uniform scene segments become nonuniform retinal gradients; darker regions acquire substantial scattered light; and the retinal range-of-light changes. The glare on each receptor is the sum of the individual contributions from every other scene segment. Glare responds to the content of the entire scene. Glare is a scene-dependent optical transformation. Lightness Illusions are intended to demonstrate how our "brain sees" using simple-uniform patterns. However, the after-glare pattern of light on receptors is a morass of high-and low-slope gradients. Quantitative measurements, and pseudocolor renderings are needed to appreciate the magnitude, and spatial patterns of glare. Glare's gradients are invisible when you inspect them. Illusions are generated by neural responses from "the-rest-of-the-scene." The neural network input is the simultaneous array of all receptors' responses. Neural processing performs vision's second scene-dependent spatial transformation. Neural processing generates appearances in Illusions and Natural Scenes. "Glare's Paradox" is that glare adds more re-distributed light to GrayROIs that appear darker, and less light to those that appear lighter. This article describes nine experiments in which neural-spatial-image processing overcompensates the effects of glare. This article studies the first-step in imaging: scene-dependent glare. Despite near invisibility, glare modifies all quantitative measurements of images. This article reveals glare's modification of input data used in quantitative image analysis and models of vision, as well as visual image-quality metrics. Glare redefines the challenges in modeling Lightness Illusions. Neural spatial processing is more powerful than we realized.

Genetic and Bioinformatic Strategies to Improve Diagnosis in Three Inherited Bleeding Disorders in Bogotá, Colombia.

Inherited bleeding disorders (IBDs) are the most frequent congenital diseases in the Colombian population; three of them are hemophilia A (HA), hemophilia B (HB), and von Willebrand Disease (VWD). Currently, diagnosis relies on multiple clinical laboratory assays to assign a phenotype. Due to the lack of accessibility to these tests, patients can receive an incomplete diagnosis. In these cases, genetic studies reinforce the clinical diagnosis. The present study characterized the molecular genetic basis of 11 HA, three HB, and five VWD patients by sequencing the F8, F9, or the VWF gene. Twelve variations were found in HA patients, four in HB patients, and 19 in WVD patients. From these variations a total of 25 novel variations were found. Disease-causing variations were used as positive controls for validation of the high-resolution melting (HRM) variant-scanning technique. This approach is a low-cost genetic diagnostic method proposed to be incorporated in developing countries. For the data analysis, we developed an accessible open-source code in Python that improves HRM data analysis with better sensitivity of 95% and without bias when using different HRM equipment and software. Analysis of amplicons with a length greater than 300 bp can be performed by implementing an analysis by denaturation domains.

An Algorithm to Optimize the Micro-Geometrical Dimensions of Scaffolds with Spherical Pores.

Despite the wide use of scaffolds with spherical pores in the clinical context, no studies are reported in the literature that optimize the micro-architecture dimensions of such scaffolds to maximize the amounts of neo-formed bone. In this study, a mechanobiology-based optimization algorithm was implemented to determine the optimal geometry of scaffolds with spherical pores subjected to both compression and shear loading. We found that these scaffolds are particularly suited to bear shear loads; the amounts of bone predicted to form for this load type are, in fact, larger than those predicted in other scaffold geometries. Knowing the anthropometric characteristics of the patient, one can hypothesize the possible value of load acting on the scaffold that will be implanted and, through the proposed algorithm, determine the optimal dimensions of the scaffold that favor the formation of the largest amounts of bone. The proposed algorithm can guide and support the surgeon in the choice of a "personalized" scaffold that better suits the anthropometric characteristics of the patient, thus allowing to achieve a successful follow-up in the shortest possible time.

A method for estimation of fundamental frequency for tonal sounds inspired on bird song studies.

In this work a simple implementation of fundamental frequency estimation is presented. The algorithm is based on a frequency-domain approach. It was mainly developed for tonal sounds and it was used in Canary birdsong analysis. The method was implemented but not restricted for this kind of data. It could be easily adapted for other sounds. Python libraries were used to develop a code with a simple algorithm to obtain fundamental frequency. An open source code is provided in the local university repository and Github. •The algorithm and the implementation are very simple and cover a set of potential applications for signal analysis.•Code implementation is written in python, very easy to use and modify.•Present method is proposed to analyze data from sounds of Serinus canaria.