Biological performance of a bioabsorbable Poly (L-Lactic Acid) produced in polymerization unit: in vivo studies

Background: The biomaterials engineering goal is to manufacture a biocompatible scaffold that adequately supports or improves tissue regeneration after implantation of the biomaterial in the injured area. Many requirements are demanded for a biomaterial, such as biocompatibility, elasticity, degradation time, and a very important factor is its cost of importation or synthesis, making its application inaccessible to some countries. Studies about biomaterials market show that Polylactic acid (PLLA) is one of the most used polymers, but expensive to produce. It becomes important to prove the biocompatibility of the new PLLA and to find strategies to produce biocompatible biopolymers at an acceptable production cost. Methods: In this work, the polylactic acid biomaterial was synthesized by ring-opening polymerization. The polymer was submitted to initial in vivo biocompatibility studies in 12 New Zealand female rabbits, assigned to two groups: (1) Lesion and PLLA group (n = 6), (2) Lesion No PLLA group (n = 6). Each group was divided into two subgroups at six and nine months post-surgical time. Before euthanasia clinical and biochemical studies were performed and after that tomographic (CT), histological (Hematoxylin and Eosin and Masson's trichrome) and histomorphometric analyses were performed to evaluate the injury site and prove biocompatibility. The final cost of this polymer was analyzed. Results: The statistical studies of hemogram and hepatocyte enzymes, showed that there were no significant differences between the groups for any of the times studied, in any of the variables considered and the results of CT and histology showed that there was an important process of neoregeneration. The cost analysis showed the biopolymer synthesis is between R$3,06 - R$5,49 cheaper than the import cost. Conclusions: It was possible to synthesize the PLLA biopolymer by cyclic ring opening, which proved to be biocompatible, potential osteoregenerative and cheaper than other imported biopolymers.

A Prediction Study about the Pandemic Era based on Machine Learning Methods

Coronavirus pandemic has been going on since late 2019, millions of people died worldwide, vaccination has recently started in many countries and new strategies are sought by countries since they are still struggling to defeat the virus. So, this research is made to predict the possible ending time of the coronavirus pandemic in Turkey using data mining and statistical studies. Data mining is a computer science study that processes large amounts of data and produces new useful information. It is especially used to support decision making in companies today. So, this project could support the decision making of authorities in developing an effective strategy against the on-going pandemic. During the research we have practiced on Turkey’s coronavirus and vaccination data between 13 January 2021 and 28 May 2021. We used Rapidminer and the Random Forest method for data mining. After all the simulations we have applied and observed during our research, it was clearly seen that vaccination parameters were decreasing the new cases. Also, the stringency index did not affect the new cases. As a conclusion of our research and observations, we think that the government should vaccinate as many people as it can in order to relax restrictions for the last time.

Lived and perceived space during lock-down in a sensitive map approach

The first lock-down in France due to the Covid-19 pandemic happened during spring 2020. It meant restrictions for everyone regarding reachable space and possible time length outside home. The seminar of sensitive mapping taking place in École des hautes études en sciences sociales (EHESS) went online and proposed an exercise to investigate the consequences of these statutory restrictions on individual lived and perceived space. The defined protocol of the exercise was based on the framework of the sensitive map approach. This approach adapts the principles of conventional cartography so that to favour personal information selection and design. Each participant of the seminar had the task to map their space. Displayed information should concern meaningful elements from their spatial environment. Other targeted information was sensitive information including emotions, feelings, and opinions as well as perceived elements from the five senses. The resulted map corpus offers diverse mapping creations. Each map contains several graphic items. Items are mainly cartographical displays enriched with non-cartographical drawings, pictures, photos, records, charts. Techniques were mixed: pen, fabrics, computer-based. The themes of displayed elements are about spatially-stable features like the dwelling, buildings remained open, green spaces, and about ephemeral and sensitive information like social interactions, people, perceived sounds, smells and feelings about the lock-down situation and the pandemic. Some maps have used or were inspired by topographic maps. Though in most maps, distances and topology are subjective. Sensitive mapping appeared as an interesting approach to collect individual testimonies and might be complementary to statistical studies.

Active IR location as the roadway profilometry method

This article observe a using of active infrared beam location as roadway surface quality control. Changes in the spatial structure of the emitted IR radiation by surfaces within the capture scene allow creating a depth map of this scene. An optical camera makes it possible to use classical computer vision methods for stitching a depth map. For testing the possibility of using this approach, we made statistical studies on a multiple sample of distance measurements. Here we explain two experimental schemes with a programmable mechanical scanning system. The first one, we had determined the distance, which the image is capture accurately. The second, we measure the planar resolution, a minimum size of the defect that recognize by the infrared beam location system.

Radio imaging using Doppler sensors

The article shows the multi-angle single-frequency probing of the object with the tactical antenna array, which we install and moves on a two-coordinate scanner. For testing the possibility of using this approach, we made statistical studies. Presented radio images show that using the scanner makes possible to detect metal and dielectric objects. Achieved resolution sufficient to identify forbidden items

The Effects of Some Physical and Chemical Factors on Apparent Resistivity of Surface Soil in the University of Mosul, Mosul City, Northern Iraq

Soil resistivity depends on many overlapping factors, which influence it in various ways. The aim of this study was to determine the effects of some physical and chemical factors on soil apparent resistivity. The results of field, laboratory, and statistical studies revealed a complex relationship between water content, pH, and salinity with soil apparent resistivity. The results showed that water content had a clear effect on apparent resistivity, as it increased significantly when water content value decreased to less than about 5%. The results also showed that increasing the salinity ratio at the expense of water content led to an increase in the apparent resistivity values. The apparent resistivity values also increased significantly when pH values ​​fell below about 7.7. The increase in air temperature caused an increase in water evaporation from the soil, which led to increasing the apparent resistivity. The rise in air temperature also caused an increase in the concentration of salts at the expense of water content; since salts are considered to be insulators, unless they are dissolved in water, they cause an increase in the value of apparent resistivity.

Machine learning approach for multidimensional poverty estimation

In the social sciences, a theoretical analysis has predominated in its research. The scarcity of data and its difficulty in collecting and storing it, has been the main limitation for the social sciences to adopt quantitative approaches. However, the large amount of information generated in recent years, mainly through the use of the Internet, has allowed the social sciences to include more and more quantitative analysis. This study proposes the use of technologies such as Machine Learning (ML) are the answers to solving this data scarcity. The objective is to estimate the multidimensional poverty index at the personal level in a particular territory of Ecuador by using Machine Learning (ML) regression models based on a limited amount of data for training. Ten ML models are compared, such as linear, regularized, and assembled models and Random Forest performs outstandingly against the other models. An error of 7.5% was obtained in the cross-validation and 7.48% with the test data set. The estimates are compared with statistical approximations of the MPI in a geographical area and it is obtained that the average MPI estimated by the model compared to the average reported by the statistical studies differs by 1%.

Designing of Fabric Reinforced Polymer in the Assessment of Sorption Capacity of Mussel Shell Powder for Divalent Ion: GIS Mapping and Statistical Studies

This paper discusses the efficiency of acid modified mollusc shell powder in adsorbing Zn(II) ions from synthetic wastewater and actual wastewater samples discharged from electroplating industries. The chemically treated adsorbent was characterized in terms of structure and surface properties. The parameters such as, size of the sorbent particles, dosage, initial Zn(II) concentration, temperature, contact time pH and temperature were varied for optimization using batch studies. The adsorbate-adsorbent system was studied by Langmuir, Freundlich, Tempkin and DKR isotherms. The adsorption experiments were conducted in a column packed with the acid modified mollusc shell powder. Further, real wastewater samples having Zn(II) concentration higher than the permissible levels were collected from the industrial belt in Coimbatore, to assess the potential of the bio adsorbent. A fiber reinforced polymer fabricated with the adsorbent material installed at the effluent discharge plants achieved 100% Zn(II) removal from electroplating wastewaters. Statistical analysis performed using SPSS software showed significant correlation among the input parameters and the analytical results post-adsorption.