Machine learning in analytical spectroscopy for nuclear diagnostics [Invited].

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra.

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of 0.33% and an LoD of 0.015% for quantification of Ga in a Ce matrix. This study concludes that these machine learning methods could yield robust prediction models for rapid quality control analysis of plutonium alloys.

Evaluation of Changes in the Occlusion and Occlusal Vertical Dimension in Children Following the Placement of Preformed Metal Crowns Using the Hall Technique.

Objectives: To evaluate the time taken and the mechanism through which the occlusion settles following the placement of a preformed metal crown (PMC) using the Hall technique. The secondary objective was to assess any temporo mandibular joint dysfunction (TMD) resulting from the Hall technique through a questionnaire. Study Design: 44 children fulfilling the inclusion criteria were evaluated for changes in overbite and occlusal vertical dimension (OVD) following the placement of preformed metal crowns (PMCs) using the Hall technique. The overbite and OVD measurements were taken before treatment, immediately post treatment, then at one, two, three and four weeks post treatment. After four weeks, a questionnaire recorded the occurrence of any signs or symptoms of TMD. Results: At the fourth week, the overbite measurement did not show a statistically significant difference (p value= 0.58) compared to baseline values indicating that the occlusion settled by the fourth week. By the third week the OVD values obtained did not show a significant difference compared to the baseline (p value= 0.42) indicating that the OVD had been restored. The questionnaire provided at the end of four weeks showed negative response for signs and symptoms of TMD in all the children. Conclusion: Any changes in occlusion following the placement of a Hall crown settles in four weeks. The OVD settles three weeks post placement implying that extrusion of teeth do not play a role in settling of the occlusion. The children do not develop any signs or symptoms of TMD post a Hall crown.

Measurement of electron density and temperature from laser-induced nitrogen plasma at elevated pressure (1-6 bar).

Laser-induced plasmas experience Stark broadening and shifts of spectral lines carrying spectral signatures of plasma properties. In this paper, we report time-resolved Stark broadening measurements of a nitrogen triplet emission line at 1-6 bar ambient pressure in a pure nitrogen cell. Electron densities are calculated using the Stark broadening for different pressure conditions, which are shown to linearly increase with pressure. Additionally, using a Boltzmann fit for the triplet, the electron temperature is calculated and shown to decrease with increasing pressure. The rate of plasma cooling is observed to increase with pressure. The reported Stark broadening based plasma diagnostics in nitrogen at high pressure conditions will be significantly useful for future studies on high-pressure combustion and detonation applications.

Machine Learning-Assisted Determination of C6H14 Mole Fraction From Molecular Emissions of Laser-Induced Hexane-Air Plasmas.

Laser-induced plasmas of materials containing hydrocarbons present strong carbon molecular emission features. Using these emissions to build models relating changes in spectral features to a physical parameter of the system, such as hydrocarbon content, can be difficult because of the dynamic complexity of the spectral features and temperature disequilibrium between molecular species. This study presents machine learning models trained to quantify the mole fraction of hexane in hexane-air plasmas from CN Violet and C2 Swan spectral features. Ensemble regression methods provide the most accurate predictions with root mean squared error on the order 10-2. Artificial neural network regressions produce predictions with superlative sensitivity, exhibiting detection limits as low as 0.008. These foundational models can be further refined with more advanced data to quantify the presence of carbon species in complex plasma environments, such as high-speed reacting flows.

Reliability of the electric pulp tester as an indicator of pulpal anesthesia in primary maxillary posterior teeth to assess the need for supplemental injections: An observational clinical study.

Background: The primary maxillary molars occasionally remain sensitive during operative procedures even post the buccal supraperiosteal injection. This could be due to the widely flared palatal roots receiving accessory innervation from the palatal nerves. Identifying inadequate anesthesia upfront using the electric pulp test (EPT) would give vital information to the clinician on the need of a supplemental palatal injection. Aim: The aim of this study was to assess and evaluate the reliability of the EPT as an indicator of pulpal anesthesia in primary maxillary molars. Methodology: Fifty one primary maxillary molars were subjected to the EPT following a buccal supraperiosteal injection. During the operative procedure, the " Face Legs Activity Cry Consolability" (FLACC) scores were recorded. The outcome of the EPT was correlated with the results of the FLACC score using Pearson's Chi-square test.Results: The EPT results were correlated to the FLACC scores. Five out of the 10 primary maxillary second molars which responded to the EPT scored 0 on the FLACC scale. The remaining 5 teeth scored 1 on the FLACC scale. The P value was 0.056 which was not statistically significant. This infers that the EPT is not a reliable tool to assess the adequacy of pulpal anesthesia in primary maxillary second molars. Conclusion: From the results of the present study, it can be concluded that the EPT is not a reliable tool to be used as an indicator of pulpal anesthesia in primary maxillary molars.

Screening for Microbial Contamination of Multi-dose Lignocaine Vials in a Dental Hospital: A Prospective Study.

Aim: Multidose vials (MDVs) for local anesthetic injections are routinely used in dental practice. MDVs contain multiple doses of a parenteral drug intended for administration to the same or multiple patients. Potentially harmful microbes have been shown to be able to live and occasionally multiply in MDVs if not handled aseptically. The goal of this study thus was to evaluate the bacterial and fungal contamination (FC) of lignocaine MDVs after use in a dental hospital. Materials and methods: A total of 27 MDVs of lignocaine free of any microbial contamination were distributed to different departments of the dental hospital and they were asked to use them on patients routinely. The samples were recollected from the departments either at the end of the 28th day or as and when the contents in the MDVs reached a predetermined level marked on the bottle during its usage, whichever was earlier. These leftover samples were subjected to a microbiological investigation by inoculation into thioglycolate broth and subsequent subculturing onto agar plates. Results: None of the inoculated broths showed turbidity. Subcultured agar plates, even on the 7th day of incubation, did not show any bacterial or fungal growth. The lignocaine MDVs tested after use were thus found to be sterile. Conclusion: There was no bacterial or FC detected in MDVs of lignocaine subjected to testing after use in the dental hospital. Clinical significance: Multidose vials (MDVs) continue to be used in clinics for economic reasons. But the clinician opting for MDVs should be conscious of their potential for microbial contamination and should meticulously follow the protocol for their aseptic use. How to cite this article: Renu SM, Rao AP, Biranthabail D, et al. Screening for Microbial Contamination of Multi-dose Lignocaine Vials in a Dental Hospital: A Prospective Study. Int J Clin Pediatr Dent 2023;16(5):678-680.

Rapid quantitative analysis of trace elements in plutonium alloys using a handheld laser-induced breakdown spectroscopy (LIBS) device coupled with chemometrics and machine learning.

We present the first reported quantification of trace elements in plutonium via a portable laser-induced breakdown spectroscopy (LIBS) device and demonstrate the use of chemometric analysis to enhance the handheld device's sensitivity and precision. Quantification of trace elements such as iron and nickel in plutonium metal via LIBS is a challenging problem due to the complex nature of the plutonium optical emission spectra. While rapid analysis of plutonium alloys has been demonstrated using portable LIBS devices, such as the SciAps Z300, their detection limits for trace elements are severely constrained by their achievable pulse power and length, light collection optics, and detectors. In this paper, analytical methods are evaluated as a means to circumvent the detection constraints. Three chemometric methods often used in analytical spectroscopy are evaluated; principal component regression, partial least-squares regression, and artificial neural networks. These models are evaluated based on goodness-of-fit metrics, root mean-squared error, and their achievable limits of detection (LoDs). Partial least squares proved superior for determining content of iron and nickel in plutonium metal, yielding LoDs of 15 and 20 ppm, respectively. These results of identifying the undesirable trace elements in plutonium components are critical for applications such as fabricating radioisotope thermoelectric generators or nuclear fuel.

Assessing the behavior management problems during the first dental visit of preschool children using a doll placement test.

CONTEXT: Assessing dental anxiety as a predictor of the likely behavior of the child in the dental operatory is of paramount importance for a clinician to render quality care. AIM: This study aims to correlate the dental anxiety of preschool children as shown during the doll placement test with that of their behavioral patterns during the first dental visit. SETTINGS AND DESIGN: This cross-sectional study was conducted between the ages of 3-7 years. MATERIALS AND METHODS: During their first dental visit, the background variables were elicited from parent/guardian at the reception desk. Later at the play area, the child was given a set of dolls representing dentist, child, and mother to place them in a model dental office having a dental chair. The child was then taken for the initial oral examination, during which the behavior of the child was rated using Frankl's Behavior Rating Scale. The data collected were analyzed using Chi-square test and binary regression analysis. RESULTS: The observed association between the doll placement pattern and the behavior of the patient during dental treatment was statistically significant (P < 0.001). The binary regression analysis showed that the child's unpleasant previous medical and parent's unpleasant dental experiences had higher odds favoring uncooperative behavior (46.63 and 41.93, respectively). CONCLUSIONS: The child's behavior on the dental chair is associated with the doll placement pattern, which is also influenced by experiences of the child during his/her encounter with the medical doctor and previous dental experiences of their parents.

Comparison of Patient Comfort During the First Stage of Conventional Versus Modified Two-Stage Inferior Alveolar Nerve Blocks in Pediatric Patients.

Our aim was to compare the comfort of pediatric patients during the first stage of the conventional 2-stage inferior alveolar nerve block (IANB) versus the modified 2-stage IANB. This was a parallel group, single-blinded, randomized controlled trial. Pediatric patients meeting the inclusion criteria were randomly allocated to 1 of the 2 groups receiving IANB, group 1 (31 subjects) utilized a conventional 2-stage technique, and group 2 (33 subjects) utilized a modified 2-stage approach. Patient comfort was assessed indirectly by 2 observers using the Face, Legs, Activity, Cry, Consolability (FLACC) scale during the first stage of the injections. FLACC score data between the 2 groups were analyzed using the chi-square test, and interobserver reliability was measured using kappa statistics. During the first stage of the injections, lower FLACC scores of 0 indicating a relaxed/comfortable patient experience were found in 57.6% of group 2 subjects compared with only 25.8% group 1 subjects, which was a statistically significant difference (p-value .013). Interobserver reliability assessed using kappa coefficients (κ = 0.812) indicated excellent agreement. FLACC scores for the pediatric patients during the first stage of the modified 2-stage IANB technique were significantly lower than during the first stage of the conventional 2-stage IANB technique.

Differential effects of leptin on the invasive potential of androgen-dependent and -independent prostate carcinoma cells.

Obesity has been linked with an increased risk of prostate cancer. The formation of toxic free oxygen radicals has been implicated in obesity mediated disease processes. Leptin is one of the major cytokines produced by adipocytes and controls body weight homeostasis through food intake and energy expenditure. The rationale of the study was to determine the impact of leptin on the metastatic potential of androgen-sensitive (LNCaP) cells as well as androgen-insensitive (PC-3 and DU-145) cells. At a concentration of 200 nm, LNCaP cells showed a significant increase (20% above control; P < .0001) in cellular proliferation without any effect on androgen-insensitive cells. Furthermore, exposure to leptin caused a significant (P < .01 to P < .0001) dose-dependent decrease in migration and invasion of PC3 and Du-145 prostate carcinoma cell lines. At the molecular level, exposure of androgen-independent prostate cancer cells to leptin stimulates the phosphorylation of MAPK at early time point as well as the transcription factor STAT3, suggesting the activation of the intracellular signaling cascade upon leptin binding to its cognate receptor. Taken together, these results suggest that leptin mediates the invasive potential of prostate carcinoma cells, and that this effect is dependent on their androgen sensitivity.