Application of PolyPRep tools on HIV protease polyproteins using molecular docking

In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.

Biospeckle Activity of Highbush Blueberry Fruits Infested by Spotted Wing Drosophila (Drosophila suzukii Matsumura)

In this study, the potential of the biospeckle phenomenon for detecting fruit infestation by Drosophila suzukii was examined. We tested both graphical and analytical approaches to evaluate biospeckle activity of healthy and infested fruits. As a result of testing the qualitative approach, a generalized difference method proved to be better at identifying infested areas than Fujii’s method. Biospeckle activity of healthy fruits was low and increased with infestation development. It was found that the biospeckle activity index calculated from spatial-temporal speckle correlation of THSP was the best discriminant of healthy fruits and fruits in two different stages of infestation development irrespective of window size and pixel selection strategy adopted to create the THSP. Other numerical indicators of biospeckle activity (inertia moment, absolute value of differences, average differences) distinguished only fruits in later stage of infestation. Regular values of differences turned out to be of no use in detecting infested fruits. We found that to provide a good representation of activity it was necessary to use a strategy aimed at random selection of pixels gathered around the global maximum of biospeckle activity localized on the graphical outcome. The potential of biospeckle analysis for identification of highbush blueberry fruits infested by D. suzukii was confirmed.

Increase in Fermentable Sugars of Olive Tree Pruning Biomass for Bioethanol Production: Application of an Experimental Design for Optimization of Alkaline Pretreatment

Olive Tree Pruning (OTP) biomass can be considered a suitable source of fermentable sugars for the production of second-generation bioethanol. The present study proposes a remarkable alternative for the valorization of olive tree pruning residues. OTP biomass was processed using a sequential calcium hydroxide pretreatment/enzymatic hydrolysis. A 24–1 half fractional factorial design was adopted for the screening of process variables and a central composite design was used for the optimization stage. Temperature and lime loading resulted statistically significant. The following optimal conditions were obtained: 0.01 g of Ca(OH)2/g of dry material, 20 g of H2O/g of dry material at 160 °C for 2 h. The mathematical model that governs this alkaline pretreatment was obtained with a 76% adjusted determination coefficient, which means that it is a good representation of the process. Under optimal operating conditions, 13% of the cellulose and 88% of the hemicellulose was solubilized. Moreover, the fermentable sugar content increased 1800% compared with the initial conditions, obtaining 240 g of glucose per kg of OTP residue. The fermentable sugars obtained after the calcium hydroxide pretreatment and enzymatic hydrolysis of OTP biomass yielded 2.8 g of ethanol/100 g of raw material.

Modelling and Design of State Estimator for a Pick and Place Robotic Arm

A robust model is essential for the design of system components such as controllers, observers state estimators, and simulators. State estimators are becoming increasingly important in modern systems, especially systems with states that may not be measured with sensors. Therefore, it is imperative to analyze the performance of different modelling and state estimator design techniques. In this research work, a parametric model of a pick and place robotic arm was obtained using system identification technique. Pick and place robotic arms have a lot of industrial applications. The parameters of the obtained model were determined using the general second-order characteristics equation and manual tuning. Furthermore, five state estimators were designed based on the developed model. The accuracy of the model, and the performance of the observers were analyzed. The model was found to provide a good representation of the system. Nonetheless, with very small divergence between the model and the real system. The performance of the observers was found to be dependent on their pole locations; the higher the magnitude of the poles, the higher the state estimators’ gain and the better the estimation provided. It was found out that the state estimators with high gains were more susceptible to measurement noise. Keywords— Modelling, pick and place robots, observers, and state estimators.

Design of single and double acceptance sampling plans based on neutrosophic sets

Although traditional acceptance sampling plans (ASPs) need certain mass quality characteristics, it is not easy to define them as crisp value in some real case problems. The fuzzy set theory (FST) is one of the popular techniques to model uncertainties of the process and therefore fuzzy ASPs have been offered in the literature. Fuzzy set extensions have been proposed recently for better modeling of the uncertainties having different sources and characteristics. One of these extensions named neutrosophic sets (NSs) can be used to increase the sensitiveness and flexibility of ASPs. The ASPs based on NSs can give ability to classify the items as defective, non-defective and indeterminate. Since the operator can become indecisive for slightly defective items, these plans can provide a good representation of human evaluations under uncertainty. In this study, single and double ASPs are designed based on NSs by using binomial and poisson distributions that are also re-analyzed based on NSs. For this aim, some characteristics functions of ASPs such as probability of accepting a lot (Pa), average outgoing quality (AOQ), average total inspection (ATI) and average sample number (ASN) have also been analyzed based on NSs. Numerical examples are presented to analyze the proposed plans.

Development and Feasibility of a Patient-Derived Training Simulator for Image-Guided Adaptive Brachytherapy of Locally Advanced Cervical Cancers

Background Image-guided adaptive brachytherapy (IGABT) plays a pivotal role in definitive radiotherapy of cervical cancer. Although the combination of a tandem and ovoid applicator with interstitial needles (IC/IS brachytherapy) is an efficient IGABT technique for bulky irregular-shaped tumors, training opportunities for IC/IS brachytherapy remain limited. Thus, we developed a training simulator for IC/IS brachytherapy for locally advanced cervical cancer and tested its feasibility. Methods The training simulator combined a patient-derived soft silicone tumor phantom with an acrylic tube mimicking the vagina. The tumor phantom was modeled on a cervical cancer patient treated with IGABT at our institute between 2012–2020, through detailed inspection of their three-dimensional (3D) high-risk clinical target volume (HR-CTV) at the first brachytherapy session. A true-scale tumor phantom was created from the HR-CTV data using 3D-printing. The feasibility of the training simulator was investigated by comparing treatment plans between the following six sessions (sessions #1–#3, with a Fletcher-Suit Asian Pacific applicator; #4–#6, with a Venezia applicator): in sessions #1 and #4, an expert inserted a tandem and ovoids (T&O); in sessions #2 and #5, a resident inserted a T&O plus four needles; and in sessions #3 and #6, an expert inserted a T&O plus four needles. At each session, the highest possible dose was prescribed to the HR-CTV while keeping the D2cc of the rectum and bladder (derived from the model case) below 6 and 7.6 Gy, respectively. Results The training simulator was developed using the HR-CTV data of a FIGO stage IIIB tumor (68 ⋅ 49 ⋅ 45 mm) selected from one of 495 candidates. The feasibility tests with a Fletcher-Suit Asian Pacific applicator resulted in HR-CTV D90 of 4.23, 5.69, and 6.70 Gy for sessions #1, #2, and #3, respectively. With a Venezia applicator, HR-CTV D90 was 4.16, 6.20, and 6.45 Gy for sessions #4, #5, and #6, respectively. Conclusions The tumor phantom was a good representation that resulted in various HR-CTV D90 doses depending on the physician’s experience and applicator type. Further evaluation of the training simulator is warranted to confirm its educational value for IC/IS brachytherapy for locally advanced cervical cancer.

A plea for teaching writing as an integrative process meant to serve a functional purpose

In the Romanian context, writing is in a paradoxical situation: it is claimed to be important though it is one of the skills that is little invested in and moreover it undergoes strong opposition from the parents who would opt for digitalization as a preventive opportunity for their children in the future. Mistreated by both school and society, writing is given meagre chances of proving its determining role in the intellectual formation of the young generation. In this line of thought this paper aims at mapping writing as a school-taught skill by first outlining the Romanian approach to school writing (as product or process) and secondly by carrying out an analysis of the writing tasks regularly assigned, with a view to emphasizing their ups and downs and to suggesting changes that might improve not only the perception on writing in the Romanian curriculum, but also the quality of the educational output. In order to obtain a good representation of how writing is viewed by the Romanian educational system, it is deemed as appropriate to analyse the school curriculum issued and approved by the Ministry of National Education and to evaluate the implementation of the official guidelines into school textbooks. The justification for the interest of the authors in writing is related to the high rates of functional illiteracy, to the preponderant evaluation type of the pupils (a written one) and to the largely acknowledged inability of pupils to successfully manage their written tasks.

BREAST CONSERVING SURGERY AWARENESS AND ACCEPTANCE AMONG FEMALE NURSES IN IRRUA SPECIALIST TEACHING HOSPITAL

Introduction: Breast Conserving Surgery (BCS) is oncologically safe for eligible patients with breast cancer and has enormous physical and psychological benefits. Despite this, the mastectomy rate in many centres is still very high. Nurses are frontline staff in healthcare settings and have great contact with the patients. The level of their awareness would have a great impact on patients eligible for breast conservation seeking expert opinion. This study explored the awareness, perception and acceptance of BCS among female nurses in a rural Nigeria tertiary hospital. Methodology: A quasi-structured self-questionnaire was distributed to 235 nurses using a convenient sampling method. The responses on 219 adequately filled questionnaires were entered into an IBM SPSS Statistics Data Document (version 21.0) for analysis. Categorical variables were presented in counts and percentages. Association between the acceptance of BCS versus its awareness, equivalence to TM and years of nursing practice were tested using Chi-square probability test and a p-value of <0.05 was considered statistically significant. Result: The 219 participants had a good representation of junior and senior nurses among whom 80.4% were at least 45 years old and 82.2% were married. The nurses were mostly general nursing practitioners (76.7%) and 49.3% of the nurses had practised for a duration not less than 10 years of age. The 126 (57.5%) nurses, who described BCS as the surgical removal of a cancerous breast lump short of mastectomy, were considered to be aware of BCS irrespective of their understanding of complementary treatment modalities, eligibilities, comparative advantages to TM and certainty of its oncologic safety. The lack of ready access to radiotherapy centres (54.3%) and delay/overcrowding of these facilities (42.5%) were recognised respectively as major local challenges to BCS practices. The equivalence of BCS to TM was affirmed in 44.3% of the nurses and 35.6% had participated in managing breast cancer patients using the conservative surgical approach. 57.1% were willing to accept BCS or recommend it for an eligible friend or relative and no statistically significant association was observed among those who accepted BCS when matched with the level of awareness or the duration of nursing practice. A higher and significant level of acceptance of BCS was noted among those aware of its oncologic equivalence to TM (p-value = 0.000) Conclusion: This study demonstrated gaps in knowledge of BCS among nurses who are stakeholders in assisting patients make the right decision. This knowledge gap in the perception of BCS will interfere with the ability of the nurse to adequately counsel patients in need of their expert opinion. The awareness of the oncologic equivalence of BCS to TM increased its acceptance significantly. An increase in public awareness and education of nurses is required to improve the acceptance rate of BCS in our practice. Caregivers should also devise effective means of communication to encourage eligible patients for breast conservation

Quantifying Fluctuations of Average Environments for Embedding Calculations

In the context of employing embedding methods to study spectroscopic properties, the viability and effectiveness of replacing an ensemble of calculations by a single calculation using an average description of the system of study are evaluated. This work aims to provide a baseline of the expected fluctuations in the average description of the system obtained in the two cases: from calculations of an ensemble of geometries, and from an average environment constructed with the same ensemble. To this end, the classical molecular dynamics simulation of a very simple system was used: a rigid molecule of acetone in a solution of rigid water. We perform a careful numerical analysis of the fluctuations of the electrostatic potential felt by the solute, as well as the fluctuations in the effect on its electronic density, measure through the dipole moment and the atomic charges derived from the corresponding potential. At the same time, we inspect the accuracy of the methods used to construct average environments. Finally, the proposed approach to generate the embedding potential from an average environment density is applied to estimate the solvatochromic shift of the first excitation of acetone. In order to account for quantum-confinement effects that may be important in certain cases, the fluctuations on the shift due to the interaction with the solvent are evaluated using Frozen-Density Embedding Theory. Our results demonstrate that, for normally-behaved environments, the constructed average environment is a reasonably good representation of a discrete solvent environment.

Evaluation of Deep Learning Methods in a Dual Prediction Scheme to Reduce Transmission Data in a WSN

One of the most important challenges in Wireless Sensor Networks (WSN) is the extension of the sensors lifetime, which are battery-powered devices, through a reduction in energy consumption. Using data prediction to decrease the amount of transmitted data is one of the approaches to solve this problem. This paper provides a comparison of deep learning methods in a dual prediction scheme to reduce transmission. The structures of the models are presented along with their parameters. A comparison of the models is provided using different performance metrics, together with the percent of points transmitted per threshold, and the errors between the final data received by Base Station (BS) and the measured values. The results show that the model with better performance in the dataset was the model with Attention, saving a considerable amount of data in transmission and still maintaining a good representation of the measured data.