Consequences of Violating Conditions of Counting Statistics Are Not Severe When Measuring Radon Progeny Concentrations with the Thomas and Kusnetz Methods.

ABSTRACT: When analyzing samples of radon progeny using the Thomas or Kusnetz methods, we violate one of the conditions of counting statistics because we use counting times that are not short compared with the half-lives of the radionuclides. The result is that we overestimate the uncertainties of the counts if we use counting statistics without correction. In this work, I describe the method by which I adjusted the values of variance of the counts theoretically to values that are more accurate and calculated the amounts by which I overestimate the values of counting uncertainty by using counting statistics without correction. These values are surprisingly small: 4-5% for the Thomas method and 2-3% for the Kusnetz method. Now, I can correct uncertainty values of radon progeny measurements if it is appropriate to do so. The detailed calculations I present here may be used for determining corrections to the counting uncertainty for a method for measuring radon progeny concentration using different sampling and/or counting times than those described here. Further, they may be used for any sample, not necessarily radon progeny, that requires a long counting time to acquire a significant number of observed counts.

The role of trauma services in intentional self-harm at a regional level 1 trauma center.

INTRODUCTION: Suicide claims many lives globally, each year. For every person that dies by suicide, multitudes more attempt it. A national shortage of psychiatrists may prevent many individuals from receiving timely mental health care. For many individuals, the primary entry point into the healthcare system is through the emergency department. The trauma service frequently treats patients with severe self-inflicted injuries and for many this is not the first time. This represents an opportunity for intervention to disrupt the cycle and prevent future death. METHODS: We conducted a retrospective chart review of all patients with self-inflicted injuries, admitted to the trauma surgery service between 2012 and 2021. All patients above 10 years old were included. RESULTS: Four hundred forty-one patients were admitted due to self-injurious behavior in the period under study. The majority of patients (71.9%) had a pre-existing mental health disorder. Fifty six patients suffered fatal injuries; the majority were White (78.6%), males (80.3%), and were inflicted by gunshot (71.4%). Nearly one third of patients with self-inflicted injuries had a history of self-injurious behavior with the average number of attempts being 2.7 (SD: ±3.8). CONCLUSIONS: We need interdisciplinary and innovative solutions for this public health crisis. Perhaps telemedicine can be used to buttress the access to adequate mental health care. More research needs to be done to better identify the barriers individuals encounter in accessing mental health care, both pre- and post-crisis. The goal is that, by identifying the gaps, we can collaboratively bridge them to prevent a preventable death.

High grade leiomyosarcoma of the transverse colon with positive lymph node metastasis: to treat or not to treat with adjuvant radiation therapy?

Intra-abdominal leiomyosarcomas (LMSs) are aggressive malignant tumours arising from smooth muscle cells. These neoplasms are extremely rare and account for 10%-20% of primary soft tissue sarcomas and approximately 0.1% of all colorectal malignancies. Intra-abdominal LMS has a very poor prognosis with an estimated 5-year survival rate between 20% and 50% and the size of the tumour being the main determinant of prognosis. Treatment is further complicated by different anatomic variants with differing clinical behaviours impacting prognosis. Newer techniques in radiation treatment such as intensity-modulated, intraoperative electron and proton beam radiotherapies allow for cases with high probability of local recurrence or likelihood of residual microscopic disease after surgical resection to be treated with precise radiation doses to the targeted tumour volume. We present a case of high grade LMS of the distal transverse colon with positive lymph node metastasis treated by surgical excision followed by adjuvant radiotherapy and discuss the current role of radiotherapy.

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.

LIBS and Raman spectroscopy in tandem with machine learning for interrogating weatherization of lithium hydride.

Lithium compounds such as lithium hydride (L i H) and anhydrous lithium hydroxide (L i O H) have various applications in industry but are highly reactive when exposed to moisture and C O 2. These reactions create new molecular compounds that degrade applications. Environmental conditions such as temperature and moisture are examples of environmental conditions that are of interest for these reactions. To interrogate the effects of such weatherization, experiments were conducted in an environmental chamber (Plas-Labs 890-THC glove box) employing a pulsed laser and an echelle spectrograph in a novel single setup to conduct both Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) in tandem. These measurements in conjunction with data fusion and machine learning techniques are used to develop training and testing of environmental conditioning of Li compounds. Modeling of environmental characterizations involving lithium-based compounds enabled by the presented measurements and analytical techniques has significant implications on industrial technologies, such as batteries, and other nuclear applications.

Optimising aerial military medical evacuation dispatching decisions via operations research techniques.

Senior military leaders and medical practitioners continuously seek new ways to improve the performance and organisation of deployed medical evacuation (MEDEVAC) systems to minimise mortality rates of combat casualties. The objective of this paper is to highlight how recent research in the fields of operations research and machine learning can be leveraged to better inform the implementation and modification of current and future MEDEVAC tactics, techniques and procedures for combat operations in a deployed environment. More specifically, this paper discusses state-of-the-art techniques that optimise the management of MEDEVAC assets prior to and during combat operations. These recent research efforts emphasise that military healthcare administrators should contribute to and extend the evolving portfolio of research that seeks to design and develop decision support systems leveraging artificial intelligence and operations research to improve MEDEVAC system performance.

Use of an Electronic Referral Application to Address Post-Injury Needs of Victims of Firearm Injury in a Hospital-Based Violence Intervention Program.

BACKGROUND: Wraparound referrals are a cornerstone of hospital-based violence intervention programs, which have proven to be an effective public health approach for mitigating violence and recidivism. We hypothesized that replacing a manual referral process with an electronic referral application would increase the number of generated referrals and improve compliance with follow-up visits. STUDY DESIGN: The population for this single center quantitative study was a convenience sample of firearm-injured patients. Data from 74 patients were collected using the electronic health record, the electronic referral application, and the trauma registry before and after the intervention. RESULTS: Post-implementation of the electronic referral application showed an increased number of generated referrals, increased emergency department and inpatient utilization of trauma recovery center services, and an increase in second follow-up visit compliance. CONCLUSION: This study demonstrated an increase in the number of referrals and greater likelihood of completion of post-injury follow-up visits after implementing the electronic referral system.

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.

Preoperative computed tomography for acutely incarcerated ventral or inguinal hernia.

BACKGROUND: The utility of preoperative computed tomography for urgent abdominal wall hernia repair is unclear. This study tests the hypothesis that there is no difference in patient outcomes for acutely incarcerated ventral or inguinal hernias diagnosed by preoperative computed tomography versus clinical assessment alone. METHODS: This retrospective cohort analysis included 270 adult patients undergoing urgent repair of ventral or inguinal hernia. Demographics, risk factors for complications, operative management strategies, and 1-year outcomes were compared between patients with (n = 179) versus without (n = 91) preoperative computed tomography. RESULTS: Among 179 preoperative computed tomography scans, 15 (8.4%) were ordered by surgeons, and all others were ordered by referring providers. The computed tomography and no computed tomography groups had similar age (58 vs 58 years, P = .77), body mass index (30.7 vs 30.6 kg/m2, P = .30), American Society of Anesthesiologists class (3.0 vs 3.0, P = .39), incidence of the systemic inflammatory response syndrome (19.0% vs 20.9%, P = .75), and incidence of recurrent hernia (16.8% vs 19.8%, P = .61). The interval between admission and incision was longer in the computed tomography group (11.2 hours vs 6.6 hours, P < .001). The computed tomography and no computed tomography groups had similar duration of surgery (125 minutes in both groups, P = .88), proportions of patients with biologic mesh (21.2% vs 17.6%, P = .52) and synthetic mesh (35.2% vs 46.2%, P = .09) placement, and 1-year outcomes including incidence of superficial (8.4% vs 6.6%, P = .81) and deep or organ/space surgical site infection (5.0% vs 6.6%, P = .59), mesh explant for infection (2.2% vs 3.3%, P = .69), reoperation for recurrent hernia (3.9% vs 1.1%, P = .27), and mortality (7.8% vs 4.4%, P = .44). CONCLUSION: The performance of preoperative computed tomography was associated with a longer interval between admission and incision and no differences in mesh placement, mesh type, or 1-year patient outcomes. These results support the safety of performing urgent repair of acutely incarcerated ventral or inguinal hernias based on clinical assessment alone.

An in-depth look at ventilator-associated pneumonia in trauma patients and efforts to increase bundle compliance, education and documentation in a surgical trauma critical care unit.

BACKGROUND: Ventilator-associated pneumonia (VAP) is considered the most common hospital acquired infection seen in critical care settings and leading cause of death in Intensive Care Units (ICU). The objective of this study was to assess whether specimen collection impacted diagnosis and if implementation of a VAP bundle would decrease rates at our center. METHODS: This single center study design is a retrospective chart review from 2017 to 2020 utilizing the electronic medical record. A pre-/postintervention comparison was performed following implementation of a unit wide VAP bundle and nursing education. Descriptive statistics and continuous variables were analyzed with independent group t -tests, and categorical variables were analyzed with chi-squared tests. RESULTS: Ventilator-associated pneumonia rates decreased in the postimplementation time (20.8%, n = 74 vs 12.2%, n = 15; P = .03). There were no significant differences in the patient profile of those who acquired VAP (ie, males 79.7% vs 86.7%, blunt injuries 63.5% vs 86.7% and severity scores 24.8 vs 25.1, pre vs postimplementation, respectively, all P-values greater than .05). DISCUSSION/CONCLUSIONS: Reduction in VAP rates were achieved by implementing a standardized, evidence based, prevention protocol. Further research is warranted as studies have noted that patients requiring mechanical ventilation are at greater risk for VAP than other ICU patients due to the nature of their injuries and increased risk of prolonged mechanical ventilation ≥ 21 days.

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.

The Presence of Nucleated Red Blood Cells as an Indicator for Increased Mortality and Morbidity in Burn Patients.

Nucleated red blood cells (NRBCs) have been studied in critically ill and injured patients as a predictor of increased in-hospital mortality and poor clinical outcomes. While prior studies have demonstrated the prognostic power of NRBCs in the critical patient, there has been a paucity of literature available describing their value as a prognostic indicator in the severely burned patient. This retrospective observational study was conducted from 2012 to 2017. Inclusion criteria for this study included all burn patients with total body surface area > 10% who were aged ≥ 15 years. Demographic and clinical data were collected from the electronic medical record system. Data analysis consisted of descriptive and comparative analysis using SPSS. Two hundred and nineteen patients (17.5%) met inclusion criteria with 51 (23.3%) patients positive for NRBCs. The presence of NRBCs had an increased mortality rate with an odds ratio of 6.0 (P = .001; 2.5, 14.5); was more likely to appear in older patients (P < .001); and was associated with increased hospital length of stay (P < .001), injury severity scores (P < .001), and complications. The presence of NRBCs even at the low concentrations reported in our study showed a 6-fold increase in the rate of mortality. With the current improvements in burn care leading to higher survival rates, the need to improve upon the numerous models that have been developed to predict mortality in severe burn patients is clear given the significantly increased risk of death that the presence of NRBCs portends.

A complex genitourinary injury following gunshot in a 12 Year old and systematic review.

We highlight the case of a 12 year old male who presented after sustaining a gunshot injury to the scrotum resulting in testicular, prostatic, and urethral transection in addition to pelvic fracture, extra peritoneal bladder injury, and transmural injury to recto sigmoid and ileum. The patient underwent a left orchiectomy, primary repair of the bladder and urethra, placement of universal plate on superior pubic rami, and segmental rectosigmoid and ileum resection. These findings illustrate the collaborative efforts of trauma surgery and urology to treat complex lower genitourinary (GU) injuries and how the direct prioritization of surgical efforts provides acceptable outcomes.

Optimal Semiconductors for 3H and 63Ni Betavoltaics.

Betavoltaic power sources based on the conversion of radioisotope energy to electrical power are considered an appealing option for remote applications due to extended period of operation and high energy densities. However, to be competitive with other power sources, their efficiency must be increased. This can be done through optimization of the beta source and selection of the semiconductor absorber. This paper evaluates available on the market and developing wideband gap semiconductors as prospective absorbers with 3H and 63Ni sources. Simulation results indicate that among wide band gap materials 4H-SiC and diamond are two optimal semiconductors due to the combination of good coupling efficiencies with isotope sources and good electronic transport properties. Additionally, having good coupling efficiency, an ultra-wide bandgap, and the capability for both n- and p-type doping, c-BN is a promising material for betavoltaic applications.

A nerve guidance conduit with topographical and biochemical cues: potential application using human neural stem cells.

Despite major advances in the pathophysiological understanding of peripheral nerve damage, the treatment of nerve injuries still remains an unmet medical need. Nerve guidance conduits present a promising treatment option by providing a growth-permissive environment that 1) promotes neuronal cell survival and axon growth and 2) directs axonal extension. To this end, we designed an electrospun nerve guidance conduit using a blend of polyurea and poly-caprolactone with both biochemical and topographical cues. Biochemical cues were integrated into the conduit by functionalizing the polyurea with RGD to improve cell attachment. Topographical cues that resemble natural nerve tissue were incorporated by introducing intraluminal microchannels aligned with nanofibers. We determined that electrospinning the polymer solution across a two electrode system with dissolvable sucrose fibers produced a polymer conduit with the appropriate biomimetic properties. Human neural stem cells were cultured on the conduit to evaluate its ability to promote neuronal growth and axonal extension. The nerve guidance conduit was shown to enhance cell survival, migration, and guide neurite extension.

Errors in measurements of 222Rn in methane and carbon dioxide using scintillation cells calibrated for 222Rn in air.

Scintillation cells are used typically for measuring the concentration of (222)Rn in air and are calibrated for that purpose. However, scintillation cells are sometimes used for measuring (222)Rn in natural gas or carbon dioxide. The counting efficiencies of scintillation cells for measurements of (222)Rn in these gases should be different from those for measuring (222)Rn in air because the ranges of alpha particles emitted by (222)Rn and its progeny are greater in methane and smaller in carbon dioxide than in air. If these effects are not taken into consideration, measurements of (222)Rn in natural gas will be biased high and in carbon dioxide will be biased low. The authors previously investigated the effects of barometric pressure on measurements of (222)Rn in air using scintillation cells. A modeling technique was used in a previous study to calculate theoretical errors that would result if atmospheric pressure were not considered. In the current study, the same modeling technique was used to calculate theoretical errors that would be made for measurements of (222)Rn in methane and carbon dioxide if the calibration for (222)Rn in air were used. Results are presented for four types of scintillation cells of varying geometries and for barometric pressures representative of four elevations ranging from sea level to 1,963 m (6,440 feet). These results indicate that the errors introduced by the ranges of the alpha particles in gases different from air can be significant. Depending on the type of cell and the local pressure, a measurement of (222)Rn in methane may be biased high by 2-7%, while a measurement of (222)Rn in CO2 may be biased low by 15-20% if the calibration for (222)Rn in air is used.

Biomimetic poly(serinol hexamethylene urea) for promotion of neurite outgrowth and guidance.

Nerve function recovery is a major technical challenge in the rehabilitation of patients suffering from severe neuropathies. Facilitating functional recovery requires the creation of a growth-permissive environment that directs the extension and myelination of surviving neurons. To this end, an electrospun nanofiber scaffold composed of arginine-glycine-aspartate-modified poly(serinol hexamethylene urea)-blend-poly-ε-caprolactone (PSHU-RGD/PCL) has been employed. Initially, we investigated the cytotoxicity of PSHU in PC12 cell culture. This was followed by functional examinations of PSHU-RGD for cell viability, proliferation, differentiation, and neurite outgrowth, and finally we examined electrospun scaffolds for guided neurite sprouting. MTT proliferation assays indicated no cytotoxic effects of polymer as compared to laminin-coated surfaces. Functional testing revealed PSHU-RGD surfaces to be comparable to the positive control, laminin-coated surface, in neurite outgrowth studies with average neurite lengths of 84.6 µm (laminin), 218.2 µm (PSHU-RGD), 570.2 µm (laminin + NGF), and 958.2 µm (PSHU-RGD + NGF) after two weeks on homogeneously modified surfaces, and 554.8 µm (nonwoven mats) and 1512.3 µm (uniaxially aligned mats) for PSHU-RGD/PCL + NGF scaffolds after one week. We created PSHU functionalized with the tripeptide, RGD, which provided chemical and physical cues to PC12 cell proliferation and differentiation. We expect that PSHU-RGD will be capable of directing and promoting neurite outgrowth in many neuropathy models.

CIB: an improved communication architecture for real-time monitoring of aerospace materials, instruments, and sensors on the ISS.

The Communications Interface Board (CIB) is an improved communications architecture that was demonstrated on the International Space Station (ISS). ISS communication interfaces allowing for real-time telemetry and health monitoring require a significant amount of development. The CIB simplifies the communications interface to the ISS for real-time health monitoring, telemetry, and control of resident sensors or experiments. With a simpler interface available to the telemetry bus, more sensors or experiments may be flown. The CIB accomplishes this by acting as a bridge between the ISS MIL-STD-1553 low-rate telemetry (LRT) bus and the sensors allowing for two-way command and telemetry data transfer. The CIB was designed to be highly reliable and radiation hard for an extended flight in low Earth orbit (LEO) and has been proven with over 40 months of flight operation on the outside of ISS supporting two sets of flight experiments. Since the CIB is currently operating in flight on the ISS, recent results of operations will be provided. Additionally, as a vehicle health monitoring enabling technology, an overview and results from two experiments enabled by the CIB will be provided. Future applications for vehicle health monitoring utilizing the CIB architecture will also be discussed.

Equations for modeling of grab samples of radon decay products.

A mathematical model of the process of collecting and analyzing a grab sample of radon decay products in air can be useful for a number ofpurposes. Among them is predicting the observed counts of alpha particles and/or beta particles (1) under various conditions of radon decay product equilibrium; (2) for various sampling, delay and counting times; and (3) for various counting efficiencies for the particles emitted by the collected decay products.