FPGA-Microprocessor Based Sensor for Faults Detection in Induction Motors Using Time-Frequency and Machine Learning Methods.

Induction motors (IM) play a fundamental role in the industrial sector because they are robust, efficient, and low-cost machines. Changes in the environment, installation errors, or modifications to working conditions can generate faults in induction motors. The trend on IM fault detection is focused on the design techniques and sensors capable of evaluating multiple faults with various signals using non-invasive analysis. The methodology is based on processing electric current signals by applying the short-time Fourier transform (STFT). Additionally, the computation of the mean and standard deviation of infrared thermograms is proposed as main indicators. The proposed system combines both parameters by means of Support Vector Machine and k-nearest-neighbor classifiers. The development of the diagnostic system was done with digital hardware implementations using a Xilinx PYNQ Z2 card that integrates an FPGA with a microprocessor, thus taking advantage of the acquisition and processing of digital signals and images in hardware. The proposed method has proved to be effective for the classification of healthy (HLT), misalignment (MAMT), unbalance (UNB), damaged bearing (BDF), and broken rotor bar (BRB) faults with an accuracy close to 99%.

Availability of Internet-Based Cognitive-Behavioral Therapies for Depression: A Systematic Review.

We examined the availability and components of internet-based cognitive-behavioral therapies (iCBTs) for depression tested in randomized-controlled trials (RCTs). The objectives of this literature review were to determine the extent to which research-validated iCBTs were available to the public, as well as to determine their therapeutic content. A literature review of RCTs for iCBTs was conducted on July 30, 2021. For each iCBT, interventions were rated by content and compared to commercially available smartphone apps. Our search yielded 80 studies using 41 unique iCBTs. Of these, only 6 (15%) were completely available to the public, more than half were not publicly available (46%), and the remaining 39% were available to the public with some restrictions (e.g., those based on the user's geographical location). When comparing iCBTs evaluated in RCTs to commercially available smartphone apps, we found that iCBTs were more likely to contain psychoeducation, cognitive restructuring, behavioral activation, problem solving, and interpersonal communication components. iCBTs from RCTs contain evidence-based content but few are available to the public. Extending beyond efficacy, attention should be paid to the dissemination of iCBTs.

Measurement of Cutting Temperature in Interrupted Machining Using Optical Spectrometry.

This research presents an experimental study focused on measuring temperature at the tool flank during the up-milling process at high cutting speed. The proposed system deals with emissivity compensation through a two-photodetector system and during calibration. A ratio pyrometer composed of two photodetectors and a multimode fiber-optic coupler is employed to capture the radiation emitted by the cutting insert. The pyrometer is calibrated using an innovative calibration system that addresses theoretical discrepancies arising from various factors affecting the measurement of cutting temperature. This calibration system replicates the milling process to generate a calibration curve. Experimentally, AISI 4140 steel is machined with coated tungsten carbide inserts, using cutting speeds of 300 and 400 m/min, and feed rates of 0.08 and 0.16 mm/tooth. The results reveal a maximum recorded cutting temperature of 518 °C and a minimum of 304 °C. The cutting temperature tends to increase with higher cutting speeds and feed rates, with cutting speed being the more influential factor in this increase. Both the pyrometer calibration and experimental outcomes yield satisfactory results. Finally, the results showed that the process and the device prove to be a convenient, effective, and precise method of measuring cutting temperature in machine processes.

Environmental and biological monitoring of organochlorine pesticides in the city of Salamanca, Mexico.

The former Tekchem Industrial Unit located in the city of Salamanca, Mexico, constitutes an environmental liability in which the presence of high levels of organochlorine pesticides (OCPs) has been reported. In the present study, levels of OCPs were quantified using gas chromatography-mass spectrometry in 52 soil samples and in 88 blood samples from school-age children in the city of Salamanca. A median concentration of 70.6 ng/g (6.93-3299) was obtained for total OCPs in soil, while for the total sum of dichlorodiphenyltrichloroethane (DDT) the value was 49.6 ng/g (6.93-3276). In children, the median level of the total sum of OCPs was 390 ng/g lipid (7.34-14,895), and for the total sum of DDT was 175 ng/g lipid (< LOD-14,802). The OCPs that resulted in highest concentrations in soil were DDT and its metabolites, as well as aldrin and heptachlor epoxide, while in blood the highest levels corresponded to 4,4'-dichlorodiphenyltrichloroethane (4,4'-DDT) and its metabolites, followed by heptachlor and heptachlor epoxide. The spatial distribution of the concentrations of OCPs in soil shows that the facilities of Tekchem may be a significant potential source for the dispersion of these compounds toward the metropolitan area of Salamanca. The results obtained in the present study demonstrate the presence of OCPs in soil and in child population, providing important bases to study the problem from a broader perspective, while reiterating the importance of continuing efforts to generate resolute and precautionary measures with respect to the environmental liability of Tekchem.

Evolución de los accesos vasculares para hemodiálisis trombosados tras su reparación quirúrgica urgente / Outcomes after surgical thrombectomy in occluded vascular access used for hemodialysis

Resumen: Introducción: un acceso vascular (AV) que funcione bien es esencial para los pacientes en hemodiálisis. La trombosis es la principal causa de fallo de un AV. La trombectomía y la reparación del AV permiten mantenerlo funcional y prolongar su permeabilidad. Por lo tanto, este enfoque sigue siendo el objetivo principal para el rescate del acceso y la prolongación de la tasa de permeabilidad. Objetivo: describir la evolución natural del AV trombosado para HD tras reparación urgente. Métodos: estudio retrospectivo, observacional y unicéntrico. Se incluyeron todos los pacientes sometidos a cirugía urgente por trombosis AV para HD, nativa y protésica, entre 2013 y 2019. Análisis estadístico: en las variables categóricas se obtuvieron proporciones y razones de prevalencia, y en las variables cuantitativas, medias, medianas y desviación estándar. Se realizaron correlaciones de variables, análisis de supervivencia sin falla (SWF) del AV y log rank. Resultados: durante el periodo de estudio rescatamos 54 trombosados e incluimos 48 pacientes. Rescatamos 22 nativos (45,8 %) y 26 protésicos AV (54,2 %) mediante trombectomía urgente. Después de la reparación urgente, el SWF fue del 49 % a los 110 días (ES 0,07), del 25 % a los 478 días (ES 0,07) y del 15 % a los 659 días. Conclusiones: existe un porcentaje nada despreciable de AV que permanece en uso a medio plazo tras ser rescatados, lo que permite una HD eficaz.(AU)

Introduction: a well-functioning vascular access(VA) is essential for patients undergoing hemodialysis. Thrombosis is the leading cause of VA failure. Thrombectomy and the repair of the VA allow maintaining it functional and prolong its permeability. Thus, this approach remains the major goal toward access salvage and prolongation of patency rate. Objective: to describe the natural history of thrombosed VA for HD after urgent repair.Methods: retrospective, observational and single center study. All patients undergoing urgent surgery for VA thrombosis for HD, native and prosthetic, between 2013 and 2019, were included. Statistical analysis: in categorical variables, proportions and prevalence ratios were obtained; and in numerical variables, means, medians and standard deviation. Variable correlations, analysis of survival without failure (SWF) of the VA and log rank were performed. Results: during the study period we rescued 54 thrombosed, we included 48 patients. We rescued 22 native (45.8 %) and 26 prosthetic VA (54.2 %) by urgent thrombectomy. After urgent repair, the SWF was 49 % at 110 days (ES 0.07), 25 % at 478 days (ES 0.07) and 15 % at 659 days. Conclusions: there is a non-negligible percentage of VA that remain in use in the medium term after being rescued, allowing effective HD.(AU)

Infrared Thermography Smart Sensor for the Condition Monitoring of Gearbox and Bearings Faults in Induction Motors.

The monitoring of machine conditions is very important from the viewpoints of productivity, economic benefits, and maintenance. Several techniques have been proposed in which sensors are the key to providing relevant information to verify the system. Recently, the smart sensor concept is common, in which the sensors are integrated with a data processing unit executing dedicated algorithms used to generate meaningful information about the system in situ. Additionally, infrared thermography has gained relevance in monitoring processes, since the new infrared cameras have more resolution, smaller dimensions, reliability, functionality, and lower costs. These units were firstly used as secondary elements in the condition monitoring of machines, but thanks to modern techniques for data processing, the infrared sensors can be used to give a first, or even a direct, diagnosis in a nonintrusive way in industrial applications. Therefore, in this manuscript, the structure and development of an infrared-thermography-based smart sensor for diagnosing faults in the elements associated with induction motors, such as rolling bearings and the gearbox, is described. The smart sensor structure includes five main parts: an infrared primary sensor, a preprocessing module, an image processing module, classification of faults, and a user interface. The infrared primary sensor considers a low-cost micro thermal camera for acquiring the thermal images. The processing modules and the classification module implement the data processing algorithms into digital development boards, enabling smart system characteristics. Finally, the interface module allows the final users to require the smart sensor to perform processing actions and data visualization, with the additional feature that the diagnosis report can be provided by the system. The smart sensor is validated in a real experimental test bench, demonstrating its capabilities in different case studies.

Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals.

Due to their robustness, versatility and performance, induction motors (IMs) have been widely used in many industrial applications. Despite their characteristics, these machines are not immune to failures. In this sense, breakage of the rotor bars (BRB) is a common fault, which is mainly related to the high currents flowing along those bars during start-up. In order to reduce the stresses that could lead to the appearance of these faults, the use of soft starters is becoming usual. However, these devices introduce additional components in the current and flux signals, affecting the evolution of the fault-related patterns and so making the fault diagnosis process more difficult. This paper proposes a new method to automatically classify the rotor health state in IMs driven by soft starters. The proposed method relies on obtaining the Persistence Spectrum (PS) of the start-up stray-flux signals. To obtain a proper dataset, Data Augmentation Techniques (DAT) are applied, adding Gaussian noise to the original signals. Then, these PS images are used to train a Convolutional Neural Network (CNN), in order to automatically classify the rotor health state, depending on the severity of the fault, namely: healthy motor, one broken bar and two broken bars. This method has been validated by means of a test bench consisting of a 1.1 kW IM driven by four different soft starters coupled to a DC motor. The results confirm the reliability of the proposed method, obtaining a classification rate of 100.00% when analyzing each model separately and 99.89% when all the models are analyzed at a time.

System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing.

The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is essential for the economic development of many countries. Current high quality production standards, along with the requirement for maximum economic benefits, demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wear. Current TCM methodologies mainly rely on vibration signals, cutting force signals, and acoustic emission (AE) signals, which have the common drawback of requiring the installation of sensors near the working area, a factor that limits their application in practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variety of cutting parameters. This paper proposes a novel non-invasive method capable of automatically diagnosing cutting tool wear in CNC machines under the variation of cutting speed and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA); a feed-forward neural network is then used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wear levels and different cutting speed and feed rate values.

La Facultad de Tecnología-Enfermería de Villa Clara ante la mitigación de la COVID-19 / Technology and Nursing Faculty of Villa Clara facing the COVID 19 challenge

RESUMEN Fundamento: la situación epidemiológica provocada por la COVID-19 transformó el proceso docente educativo en la Facultad de Tecnología-Enfermería. Objetivo: describir las acciones educativas que realizan directivos, profesores y estudiantes de la Facultad de Tecnología-Enfermería para el enfrentamiento a la COVID-19 en la Universidad de Ciencias Médicas de Villa Clara. Métodos: se realizó un estudio descriptivo con enfoque cualitativo entre marzo-mayo de 2020. Se utilizaron métodos teóricos: análisis-síntesis e inducción-deducción; empíricos: revisión documental y encuesta en forma de entrevista a directivos, profesores y estudiantes. Resultados: en las acciones educativas predominaron la capacitación sobre la nueva enfermedad, la evaluación y acreditación de todo el personal que trabajaría en la facultad como centro de aislamiento, y se determinaron otras para aplicarlas desde el área de la docencia donde se tuvieron en cuenta su proceso de formación de perfil amplio compuesto por nueve carreras universitarias, formación técnica profesional y de educación superior de ciclo corto en diferentes especialidades técnicas de la salud. Conclusiones: el estudio permitió describir las acciones realizadas en correspondencia con las resoluciones y normativas vigentes para el proceso docente educativo de las ciencias médicas en tiempos de contingencia epidemiológica, en las que se pone de manifiesto la labor extensionista de la universidad como una de sus funciones fundamentales.

ABSTRACT Background: the epidemiological setting caused by COVID-19 changed the educational teaching process in the Technology and Nursing Faculty. Objective: to describe the educational actions carried out by executives, professors and students from the Technology and Nursing Faculty to deal with COVID-19 at the University of Medical Sciences in Villa Clara. Methods: from March to May 2020, a descriptive study with a qualitative approach, was conducted. Theoretical methods were used: analysis-synthesis and induction-deduction; empirical methods: documentary review and interview survey that involves directors, teachers and students. Results: among the educational actions, training related to the new disease, evaluation and accreditation of all staff who would work in the faculty as an isolation facility, prevailed. Others were determined to be put into practice by teachers in the teaching area where the broad-based training process consisting of nine university degrees, technical professional training and short cycle higher education in different technical health specialties, was taken into account. Conclusions: the actions carried out in accordance with resolutions and regulations in force for the teaching learning process in medical sciences in times of epidemiological contingency, in which the extension university service is highlighted as one of its fundamental functions, were possible through this study.

Assessment of CFH and HTRA1 polymorphisms in age-related macular degeneration using classic and machine-learning approaches.

BACKGROUND: CFH and HTRA1 are pivotal genes driving increased risk for age-related macular degeneration (AMD) among several populations. Here, we performed a hospital-based case-control study to evaluate the effects of three single nucleotide polymorphisms (SNPs) among Hispanics from Mexico. MATERIALS AND METHODS: 122 cases and 249 controls were genotyped using Taqman probes. Experienced ophthalmologists diagnosed AMD following the American Association of Ophthalmology guidelines. We studied CFH (rs1329428, rs203687) and HTRA1 (rs11200638) SNPs thoroughly by logistic regression models (assuming different modes of inheritance) and machine learning-based methods (ML). RESULTS: HTRA1 rs11200638 is the most significant polymorphism associated with AMD in our studied population. In a multivariate regression model adjusted for clinically and statistically meaningful covariates, the A/G and A/A genotypes increased the odds of disease by a factor of 2.32 and 7.81, respectively (P < .05) suggesting a multiplicative effect of the polymorphic A allele. Furthermore, this observation remains statistically meaningful in the allelic, dominant, and recessive models, and ML algorithms. When stratifying by phenotype, this polymorphism was significantly associated with increased odds for geographic atrophy (GA) in a recessive mode of inheritance (12.4, p < .05). CONCLUSIONS: In sum, this work supports a strong association between HTRA1 genetic variants and AMD in Hispanics from Mexico, especially with GA. Moreover, ML was able to replicate the results of conventional biostatistics methods unbiasedly.

Smart-Sensor for the Automatic Detection of Electromechanical Faults in Induction Motors Based on the Transient Stray Flux Analysis.

Induction motors are essential and widely used components in many industrial processes. Although these machines are very robust, they are prone to fail. Nowadays, it is a paramount task to obtain a reliable and accurate diagnosis of the electric motor health, so that a subsequent reduction of the required time and repairing costs can be achieved. The most common approaches to accomplish this task are based on the analysis of currents, which has some well-known drawbacks that may lead to false diagnosis. With the new developments in the technology of the sensors and signal processing field, the possibility of combining the information obtained from the analysis of different magnitudes should be explored, in order to achieve more reliable diagnostic conclusions, before the fault can develop into an irreversible damage. This paper proposes a smart-sensor that explores the weighted analysis of the axial, radial, and combination of both stray fluxes captured by a low-cost, easy setup, non-invasive, and compact triaxial stray flux sensor during the start-up transient through the short time Fourier transform (STFT) and characterizes specific patterns appearing on them using statistical parameters that feed a feature reduction linear discriminant analysis (LDA) and then a feed-forward neural network (FFNN) for classification purposes, opening the possibility of offering an on-site automatic fault diagnosis scheme. The obtained results show that the proposed smart-sensor is efficient for monitoring and diagnosing early induction motor electromechanical faults. This is validated with a laboratory induction motor test bench for individual and combined broken rotor bars and misalignment faults.

Significant Association Between Variant in SGCD and Age-Related Macular Degeneration.

CFH and HTRA1 genes are traditional markers of increased risk of age-related macular degeneration (AMD) across populations. Recent findings suggest that additional genes-for instance, in the dystrophin-associated protein complex-might be promising markers for AMD. Here, we performed a case-control study to assess the effect of SGCD single nucleotide polymorphisms (SNPs), a member of this protein family, on AMD diagnosis and phenotype. We performed a case-control study of an under-studied population from Hispanics in Mexico City, with 134 cases with 134 unpaired controls. Cases were 60 years or older (Clinical Age-Related Maculopathy Staging (CARMS) grade 4⁻5, as assessed by experienced ophthalmologists following the American Association of Ophthalmology (AAO) guidelines), without other retinal disease or history of vitreous-retinal surgery. Controls were outpatients aged 60 years or older, with no drusen or retinal pigment epithelium (RPE) changes on a fundus exam and a negative family history of AMD. We examined SNPs in the SGCD gene (rs931798, rs140617, rs140616, and rs970476) by sequencing and real-time PCR. Genotyping quality checks and univariate analyses were performed with PLINK v1.90b3.42. Furthermore, logistic regression models were done in SAS v.9.4 and haplotype configurations in R v.3.3.1. After adjusting for clinical covariates, the G/A genotype of the SGCD gene (rs931798) significantly increases the odds of being diagnosed with AMD in 81% of cases (1.81; 95% CI 1.06⁻3.14; p = 0.031), especially the geographic atrophy phenotype (1.82; 95% CI 1.03⁻3.21; p = 0.038) compared to the G/G homozygous genotype. Moreover, the GATT haplotype in this gene (rs931798, rs140617, rs140616, and rs970476) is associated with lower odds of AMD (adjusted odds ratio (OR) 0.13; 95% CI 0.02⁻0.91; p = 0.041). SGCD is a promising gene for AMD research. Further corroboration in other populations is warranted, especially among other Hispanic ethnicities.

Embryonary Mouse Cardiac Fibroblast Isolation.

Mouse cardiac fibroblasts have been widely used as an in vitro model for studying fundamental biological processes and mechanisms underlying cardiac pathologies, as well as identifying potential therapeutic targets. Cardiac FBs are relatively easy to culture in a dish and can be manipulated using molecular and pharmacological tools. Because FBs rapidly decrease cell cycle division and proliferative rate after birth, they are prone to phenotypic changes and senescence in cell culture soon after a few passages. Therefore, primary cultures of differentiated fibroblasts from embryos are more desirable. Below we will describe a method that provides good cell yield and viability of E16 CD-1 mouse embryonic cardiac fibroblasts in primary cultures.

Multifractality of Pseudo-Velocities and Seismic Quiescence Associated with the Tehuantepec M8.2 EQ.

By using earthquake catalogs, previous studies have reported evidence that some changes in the spatial and temporal organization of earthquake activity are observed before and after of a main shock. These previous studies have used different approaches for detecting clustering behavior and distance-events density in order to point out the asymmetric behavior of foreshocks and aftershocks. Here, we present a statistical analysis of the seismic activity related to the M w = 8.2 earthquake that occurred on 7 September 2017 in Mexico. First, we calculated the inter-event time and distance between successive events for the period 1 January 1998 until 20 October 2017 in a circular region centered at the epicenter of the M w = 8.2 EQ. Next, we introduced the concept of pseudo-velocity as the ratio between the inter-event distance and inter-event time. A sliding window is considered to estimate some statistical features of the pseudo-velocity sequence before the main shock. Specifically, we applied the multifractal method to detect changes in the spectrum of singularities for the period before the main event on 7 September. Our results point out that the multifractality associated with the pseudo-velocities exhibits noticeable changes in the characteristics of the spectra (more narrower) for approximately three years, from 2013 until 2016, which is preceded and followed by periods with wider spectra. On the other hand, we present an analysis of patterns of seismic quiescence before the M w = 8.2 earthquake based on the Schreider algorithm over a period of 27 years. We report the existence of an important period of seismic quietude, for six to seven years, from 2008 to 2015 approximately, known as the alpha stage, and a beta stage of resumption of seismic activity, with a duration of approximately three years until the occurrence of the great earthquake of magnitude M w = 8.2 . Our results are in general concordance with previous results reported for statistics based on magnitude temporal sequences.

Pharmacogenetics of response to neoadjuvant paclitaxel treatment for locally advanced breast cancer.

Locally advanced breast cancer (LABC) cases have a varying five-year survival rate, mainly influenced by the tumor response to chemotherapy. Paclitaxel activity (response rate) varies across populations from 21.5% to 84%. There are some reports on genetic traits and paclitaxel; however, there is still considerable residual unexplained variability. In this study, we aimed to test the association between eleven novel markers and tumor response to paclitaxel and to explore if any of them influenced tumor protein expression. We studied a cohort of 140 women with LABC. At baseline, we collected a blood sample (for genotyping), fine needle aspirates (for Western blot), and tumor measurements by imaging. After follow-up, we ascertained the response to paclitaxel monotherapy by comparing the percent change in the pre-, post- tumor measurements after treatment. To allocate exposure, we genotyped eleven SNPs with TaqMan probes on RT-PCR and regressed them to tumor response using linear modeling. In addition, we compared protein expression, between breast tumors and healthy controls, of those genes whose genetic markers were significantly associated with tumor response. After adjusting for multiple clinical covariates, SNPs on the LPHN2, ROBO1, SNTG1, and GRIK1 genes were significant independent predictors of poor tumor response (tumor growth) despite paclitaxel treatment. Moreover, proteins encoded by those genes are significantly downregulated in breast tumor samples.

Necesidades de aprendizaje sobre informática educativa en los docentes de Tecnología de la Salud / Learning needs about educational informatics in teachers from Health Technology

Fundamento: la incorporación de las Tecnologías de la Información y la Comunicación (TIC) se convierte en nuevos desafíos educativos que exigen la formación de profesionales preparados en el área del saber de la informática educativa. Objetivo: identificar las necesidades de aprendizaje en informática educativa de los docentes para el perfeccionamiento del proceso enseñanza aprendizaje en las carreras de Tecnología de la Salud en Villa Clara. Métodos: se realizó un estudio descriptivo con enfoque cuantitativo. Se utilizaron métodos teóricos: analítico-sintético e inductivo-deductivo, empíricos: el cuestionario, y matemáticos: de la estadística descriptiva, el análisis porcentual. Resultados: se constataron dificultades en el conocimiento sobre los fundamentos psicopedagógicos para la aplicación de la informática educativa relacionado con las habilidades prácticas que deben mostrar los profesores para la utilización de herramientas y recursos informáticos en función del perfeccionamiento del proceso enseñanza aprendizaje, teniendo en cuenta los retos que enfrenta como docente universitario. Conclusiones: los resultados del diagnóstico permitieron identificar la necesidad que poseen los docentes de una preparación sistemática en informática educativa de acuerdo con las exigencias de la actual sociedad de la información y la gestión del conocimiento en las carreras de Tecnología de la Salud.

Background: the incorporation of the Information and Communication Technologies brings new educational challenges that demand the training of qualified professionals in the field of knowledge in educational informatics. Objective: to identify the learning needs in educational informatics among the teachers, for the perfection of the teaching-learning process in the Health Technology studies in Villa Clara. Methods: a descriptive study with quantitative approach was done. Theoretical methods were used: analytic-synthetic and inductive-deductive; empirical: the questionnaire; and mathematical: descriptive statistics and percentage analysis. Results: difficulties were verified in the knowledge about the psycho-pedagogical foundations for the application of educational informatics, related to the practical skills that teachers must show for the utilization of the informatics tools and resources for the improvement of the teaching-learning process, taking into account the challenges that the teacher faces as university teacher. Conclusions: the results of the diagnosis made possible to identify the need that teachers have of a systematic training in educational informatics, according with the demands of the present-day informatics society, and the management of knowledge in the Health Technology studies.

On the N1-H and N3-H Bond Dissociation in Uracil by Low Energy Electrons: A CASSCF/CASPT2 Study.

The dissociative electron-attachment (DEA) phenomena at the N1-H and N3-H bonds observed experimentally at low energies (<3 eV) in uracil are studied with the CASSCF/CASPT2 methodology. Two valence-bound π(-) and two dissociative σ(-) states of the uracil anionic species, together with the ground state of the neutral molecule, are proven to contribute to the shapes appearing in the experimental DEA cross sections. Conical intersections (CI) between the π(-) and σ(-) are established as the structures which activate the DEA processes. The N1-H and N3-H DEA mechanisms in uracil are described, and experimental observations are interpreted on the basis of two factors: (1) the relative energy of the (U-H)(-) + H fragments obtained after DEA with respect to the ground-state equilibrium structure (S0) of the neutral molecule (threshold for DEA) and (2) the relative energy of the CIs also with respect to S0 (band maxima). The π1(-) state is found to be mainly responsible for the N1-H bond breaking, whereas the π2(-) state is proved to be involved in the cleavage of the N3-H bond.

Singlet-Triplet States Interaction Regions in DNA/RNA Nucleobase Hypersurfaces.

The present study provides new insight into the intrinsic mechanisms for the population of the triplet manifold in DNA nucleobases by determining, at the multiconfigurational CASSCF/CASPT2 level, the singlet-triplet states crossing regions and the main decay paths for their lowest singlet and triplet states after near-UV irradiation. The studied singlet-triplet interacting regions are accessible along the minimum energy path of the initially populated singlet bright (1)ππ* state. In particular, all five natural DNA/RNA nucleobases have, at the end of the main minimum energy path and near a conical intersection of the ground and (1)ππ* states, a low-energy, easily accessible, singlet-triplet crossing region directly connecting the lowest singlet and triplet ππ* excited states. Adenine, thymine, and uracil display additional higher-energy crossing regions related to the presence of low-lying singlet and a triplet nπ* state. These funnels are absent in guanine and cytosine, which have the bright (1)ππ* state lower in energy and less accessible nπ* states. Knowledge of the location and accessibility of these regions, in which the singlet-triplet interaction is related to large spin-orbit coupling elements, may help to understand experimental evidence such as the wavelength dependence measured for the triplet formation quantum yield in nucleobases and the prevalence of adenine and thymine components in the phosphorescence spectra of DNA.