Low Probability Research Articles

6641 Observation in Lieu of Surgical Management in Hurthle Cell Neoplasm: Role of Thyroseq V3 Molecular Testing

Abstract Disclosure: R. Kaur: None. L. Kaur: None. T. Chaudhary: None. M. Shrivastava: None. N. Patel: None. The diagnostic utility of fine needle aspiration biopsy with cytology is often confounded in thyroid nodules with predominance of hurthle cells, often interpreted as an oncocytic/hurthle cell lesion with intermediate risk of malignancy, bethesda category (BC) III or IV. With the advent of molecular testing like thyroseq V3, it is helpful in ruling out substantial risk of cancer and considering observation in lieu of surgical management in such difficult cases. We present a case of a 75 year old woman with past medical history significant for type 2 diabetes mellitus and hypothyroidism who was found to have a left lobe complex nodule within a non-toxic multinodular goiter In 2022. Ultrasound of the neck showed a 1.6 x 1.8 x 2 cm intermediate nodule, followed by a fine needle aspiration biopsy which was non-diagnostic and reported as benign, showing only cystic contents and insignificant follicular cells, Bethesda class II. Follow up for the nodule was recommended in one year. Repeat Imaging one year later revealed left nodule without significant changes and repeat fine needle aspiration cytology was advised. The biopsy result was reported as an oncocytic/ Hurthle cell neoplasm, Bethesda class IV. The specimen was also submitted for thyroseq molecular testing and results were awaited. The patient was euthyroid with negative anti thyroid antibodies. There was no family history of thyroid cancer or radiation exposure. The patient denied any active symptoms like shortness of breath, neck pain or pressure, recent voice changes, dysphasia, loss of appetite or weight .On examination the patient was found to have a left thyroid nodule with no signs of tracheal deviation. CT scan of the neck demonstrated a left thyroid nodule with no compression. The patient was followed by both endocrinology and oncology and surgical options were discussed depending upon the biopsy results while awaiting molecular testing report. Molecular testing with thyrosec V3 revealed an absence of gene mutations and reported a low probability of cancer. Depending upon the results observation was considered in lieu of surgical management. Hence It was decided to keep the patient under observation considering the molecular test results in conjunction with all relevant imaging, clinical findings, symptoms, patients family history as well as patients preference. This case report demonstrates the crucial role of molecular Diagnostics specifically thyroseq V3 in the often difficult clinical management of hurthle cell thyroid nodules for ruling out surgical management. Thyroseq V3 shows reliable performance in Hurthle cell cancers with sensitivity of 93% and specificity of 69%. In times of patient guided decision making and ability to narrow down the need of surgery based on pre-operative fine needle aspiration cytology, molecular profiling of thyroid nodules has become increasingly utilized. Presentation: 6/1/2024

The influence of temperature and β-1,3-glucans on the occurrence of white spot syndrome virus and white spot disease in post-larvae of Penaeus vannamei shrimp

Penaeus vannamei is the main species of shrimp farmed worldwide, and for Ecuador it is the first non-oil economic sector. However, various pathogens, including white spot syndrome virus (WSSV), threaten the sustainability of shrimp farming. P. vannamei larvae are susceptible to WSSV infection via vertical or horizontal transmission. To decrease the incidence of WSSV in PLs, a bioassay was performed by exposing P. vannamei shrimp (PL25), which were negative for WSSV and white spot disease (WSD), to two protective factors, water temperature (T = 24 °C and T = 31 °C), and immunestimulation using β-1,3-glucans (BG) (with and without BG added to the food), using a crossed two-factor design, for 20 days. The incidence of WSSV and WSD was modeled using generalized linear model (GLM). The strength of the association between the response and explanatory variables was estimated using the odds ratio [Exp (Beta)] and interpreted as the level of risk for the incidence of WSSV or WSD in one of the categories compared to the baseline category in the GLM. Odds ratios were considered significant if their 95 % confidence interval did not include the value 1. The results showed that BG had a significant negative effect on the number of WSSV-positive animals. In addition, a lower probability of WSSV infection was determined by combining 31 °C and BG. In this treatment, the WSD injuries were almost undetectable. Most larvae shrimps affected by WSD exhibited injuries to the antennal gland and connective tissue. In situ hybridization analysis revealed that 29 % of shrimp, initially negative by histology, were positive for WSSV. The virus was detected mainly in the nervous tissue of the head, epithelium, connective tissue of the head appendages, and the oral region surrounding the integumental glands. Apoptosis analysis showed a weak signal in nerve tissue but was more intense in epithelial cells of the head appendages, in association with cuticular damage. According to the findings, WSSV could disseminate among shrimp populations by infecting them through the TG and epithelium of the head appendage, followed by connective tissue and nervous tissue. However, applying BG at 31 °C may serve as a protective measure to reduce WSD injuries and restrict WSSV dissemination.

Joint LPI waveform and passive beamforming design for FDA-MIMO-DFRC systems

Dual-functional Radar-Communication (DFRC) systems have been recognized as one of the most promising technologies in the field of wireless communications. Nevertheless, the low probability of intercept (LPI) performance in the DFRC systems cannot be overlooked. Based on the frequency diverse array multiple-input–multiple output (FDA-MIMO) radar, a DFRC system is proposed to enhance target detection in clutter environment and achieve desirable LPI against an underlying hostile interceptor. The issue can be cast into an optimization problem that maximizes the radar signal-to-interference-plus-noise ratio (SINR) while satisfying the communication quality-of-service (QoS) requirement of each user under one of three metrics, the required LPI performance and the constant-modulus waveform constraint. To solve this challenging problem, we reformulate it into an equivalent but more tractable form by resorting to an auxiliary variable. Subsequently, we employ the alternative direction method of multipliers (ADMM) and majorization-minimization (MM) algorithms to solve the resultant problem. Simulation results validate that the proposed LPI FDA-MIMO-DFRC scheme exhibits superior sensing performance over the conventional scheme with MIMO.

Association between oxidative balance score and chronic obstructive pulmonary disease: A cross-sectional study.

Oxidative stress is an essential contributor to the progression of chronic obstructive pulmonary disease (COPD). A systematic assessment of diet patterns and lifestyle with the oxidative balance score (OBS) to reflect oxidative stress levels will help predict the risk of COPD. This study conducted a cross-sectional analysis to assess the link between OBS and COPD. 5162 participants were collected from 2013 to 2018 from the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression models were applied to assess the relationship between OBS and COPD prevalence. The linearity of the association was explored using smoothed curve fitting. In addition, further subgroup analysis and interaction tests were conducted to ascertain the consistency of the relationship across diverse populations. Results of the multivariate logistic regression models indicated a negative association between OBS and the odds of COPD prevalence. Each incremental unit in OBS correlated with a 3% reduction in the odds of COPD in the fully adjusted model (OR 0.97, 95% CI 0.95-0.99). Further analysis by OBS tertiles indicated that individuals in the highest OBS tertile (T3) had a 17% lower probability of COPD compared to those in the lowest tertile (T1) in the fully adjusted model (OR 0.83, 95% CI 0.64-0.97). The smoothed curve fitting supported the negative association between OBS and COPD. Subgroup analyses revealed that the protective effect of OBS was notably pronounced among the non-hypertensive and non-diabetic populations. These findings suggest a negative link between OBS and COPD, underscoring the importance of antioxidant-rich diets and lifestyles in preventing COPD.

Improving Time to Goals of Care Discussions in Invasively Ventilated Preterm Infants.

The challenge of identifying preterm infants with bronchopulmonary dysplasia (BPD) that need tracheostomy placement may delay goals of care (GOC) discussions. By identifying infants with a low probability of ventilation liberation, timely GOC discussions may reduce the time to tracheostomy. Our SMART aim was to reduce the postmenstrual age (PMA) of GOC discussions by 20% in infants with BPD and prolonged invasive ventilatory requirement by October 2020. Our group conducted a quality improvement initiative at the University of Alabama at Birmingham. Infants were included if born at <32 weeks' gestation and exposed to invasive ventilation for ≥2 weeks beyond 36 weeks' PMA. Interventions included (1) consensus of BPD infants at risk for tracheostomy dependence, (2) monthly multidisciplinary tracheostomy meetings, and (3) development and utilization of tracheostomy educational content for families. Statistical process control charts were used for all analyses. A total of 79 infants were included in analyses, of which 44 infants either received a tracheostomy or died. From X-mR control chart analysis, there was special cause variation in the time to GOC discussions, which decreased from 62 to 51 weeks' PMA related to monthly multidisciplinary conferences. The average PMA at tracheostomy decreased from 80 weeks to 63 weeks with no change in the frequency of tracheostomy placement or discordant GOC discussions in which infants survived to hospital discharge without a tracheostomy. In infants with ventilator-dependent BPD, standardization of GOC discussions reduced the PMA of GOC discussions and tracheostomy.

Racial and Ethnic Disparities in Hepatitis C Care in Reproductive-Aged Women With Opioid Use Disorder.

In the United States, hepatitis C virus (HCV) diagnoses among reproductive-aged women are increasing amidst the ongoing opioid and drug overdose epidemic. While previous studies document racial and ethnic disparities in HCV testing and treatment in largely male populations, to our knowledge no national studies analyze these outcomes in reproductive-aged women with opioid use disorder (OUD). We analyzed data from a cohort of reproductive-aged women (aged 15-44 years) with diagnosed OUD captured in the TriNetX Research Network, a network of electronic health records from across the United States. Using a log-binomial model, we assessed differences in achieving HCV cascade of care stages (HCV antibody testing, HCV infection [positive HCV RNA test result], linkage to care, and HCV treatment) by race and ethnicity. From 2014 to 2022, 44.6% of the cohort were tested for HCV antibody. Asian and black/African American individuals had a lower probability of having an HCV antibody test than white individuals (risk ratio, 0.77 [95% confidence interval, .62-.96] and 0.76 [.63-.92], respectively). Among those with HCV infection, only 9.1% were treated with direct-acting antivirals. Hispanic/Latinx individuals had a higher probability of treatment than non-Hispanic/Latinx individuals (risk ratio, 1.63 [95% confidence interval, 1.01-2.61]). Few reproductive-aged women with OUD are tested or treated for HCV. Disparities by race and ethnicity in HCV testing further exacerbate the risk of perinatal transmission and disease progression among minoritized communities. Interventions are needed to improve overall rates of and equity in HCV screening and treatment for reproductive-aged women.

Clinical Implications of Pretest Probability of HFpEF on Outcomes in Precapillary Pulmonary Hypertension

BackgroundPatients with group 1 pulmonary hypertension (PH) and risk factors for heart failure with preserved ejection fraction (HFpEF) demonstrate worse response to pulmonary vasodilator therapy. The mechanisms and optimal diagnostic approach to identify such patients remain unclear. ObjectivesThe purpose of this study was to compare exercise capacity, cardiac function, and hemodynamic responses to provocative maneuvers among patients with group 1 PH based upon pretest probability of HFpEF. MethodsPretest probability for HFpEF was determined using the validated HFpEF-ABA algorithm based on age, body mass index, and history of atrial fibrillation among group 1 PH patients recruited to the multicenter PVDOMICS (Redefining Pulmonary Hypertension through Pulmonary Vascular Disease Phenomics) study. Functional capacity, quality of life, and dynamic pulmonary capillary wedge pressure (PCWP) responses were compared between those with low (<25%), intermediate (25%-74%), and high (≥75%) ABA score-based HFpEF probability. ResultsAmong 424 patients with group 1 PH, 54% (n = 228) had intermediate HFpEF probability and 15% (n = 64) had high HFpEF probability. Resting PCWP increased progressively with higher HFpEF probability (P < 0.0001), and patients with group 1 PH and high HFpEF probability had the greatest increases in PCWP with nitric oxide, fluid challenge, and exercise (P < 0.001 for all), changes that were comparable to patients with HFpEF with no pulmonary vascular disease (n = 194), but lower than those with HFpEF and combined precapillary and postcapillary PH. Left ventricular/atrial size, diastolic function, quality of life, 6-minute walk distance, and peak VO2 were most abnormal in patients with group 1 PH and high HFpEF probability compared with those with low or intermediate HFpEF probability (P < 0.0001 for all). Increasing HFpEF probability in group 1 PH was associated with greater risk of death (HR per decile of HFpEF probability 1.09; 95% CI: 1.05-1.13; P < 0.0001). ConclusionsQuantifying pretest probability for HFpEF in patients with group 1 PH identifies a subset of patients with worse dynamic PCWP response indicative of subclinical left heart disease, with poorer functional status, quality of life, and survival. Further study in this group 1 PH subgroup is indicated to determine whether PH therapies are effective and safe, and also whether HFpEF-specific therapies can improve functional status and outcomes.

A physics-informed neural network enhanced importance sampling (PINN-IS) for data-free reliability analysis

Reliability analysis of highly sensitive structures is crucial to prevent catastrophic failures and ensure safety. Therefore, these safety-critical systems are to be designed for extremely rare failure events. Accurate statistical quantification of these events associated with a very low probability of occurrence requires millions of evaluations of the limit state function (LSF) involving computationally expensive numerical simulations. Variance reduction techniques like importance sampling (IS) reduce such repetitions to a few thousand. The use of a data-centric metamodel can further cut it down to a few hundred. In data-centric metamodeling approaches, the actual complex numerical analysis is performed at a few points to train the metamodel for approximating the structural response. On the other hand, a physics-informed neural network (PINN) can predict the structural response based on the governing differential equation describing the physics of the problem, without a single evaluation of the complex numerical solver, i.e., data-free. However, the existing PINN models for reliability analysis have been effective only in estimating a large range of failure probabilities (10-1∼10-3). To address this issue, the present study develops a PINN-based data-free reliability analysis for low failure probabilities (<10-5). In doing so, a two-stage PINN integrated with IS (PINN-IS) is proposed. The first stage is employed to approximate the most probable failure point (MPP) appropriately while the second stage enhances the accuracy of LSF predictions at the IS population centred on the approximated MPP. The effectiveness of the proposed approach is numerically illustrated by three structural reliability analysis examples.

Disease disclosure in the workplace in people living with rheumatic diseases: an exploratory study.

Rheumatic musculoskeletal diseases (RMDs) are the causes of frequent absence from work and loss of productivity. As (in)visible diseases, it is up to the individuals to decide if disclosing their diagnosis, with important repercussions also within the workplace. Still little is known about disease disclosure in the workplace (DD-W) in patients with RMDs. This study aimed to investigate socio-demographic, clinical, and psychological predictors of DD-W among working patients with RMDs. A cross-sectional Italian national study captured DD-W in people with RMDs. An online survey was developed using ad-hoc questions and scientific questionnaires to explore demographics and work-related, clinical, and psychological factors. Stepwise logistic regressions were run to identify significant predictors of DD-W. A total of 250 working rheumatic patients completed the survey; 81.2% of the participants enacted DD-W. DD-W behaviors were predicted by perceived visibility of the RMD (p=0.008), work type (p=0.022), general DD behaviors (p<0.001), and perceived family support (p=0.023). Among RMD patients, psoriatic arthritis participants had higher probabilities of DD-W (p=0.02), whereas lower probabilities were detected in fibromyalgia patients (p=0.003). Lower disease duration corresponded in the sample to higher probabilities of DD-W (p=0.036). The majority of RMD patients in this study enacted DD-W. DD-W was associated with medical, occupational, and psychological factors, supporting the multidimensionality of the process. Further research on the subject might help foster better DD-W decision-making processes for RMD patients while promoting intervention strategies in education, policy, and culture.

A robust temporal map of speech monitoring from planning to articulation

Speakers continuously monitor their own speech to optimize fluent production, but the precise timing and underlying variables influencing speech monitoring remain insufficiently understood. Through two EEG experiments, this study aimed to provide a comprehensive temporal map of monitoring processes ranging from speech planning to articulation.In both experiments, participants were primed to switch the consonant onsets of target word pairs read aloud, eliciting speech errors of either lexical or articulatory-phonetic (AP) origin. Experiment I used pairs of the same stimuli words, creating lexical or non-lexical errors when switching initial consonants, with the degree of shared AP features not fully balanced but considered in the analysis. Experiment II followed a similar methodology but used different words in pairs for the lexical and non-lexical conditions, fully orthogonalizing the number of shared AP features.As error probability is higher in trials primed to result in lexical versus non-lexical errors and AP-close compared to AP-distant errors, more monitoring is required for these conditions. Similarly, error trials require more monitoring compared to correct trials. We used high versus low error probability on correct trials and errors versus correct trials as indices of monitoring.Across both experiments, we observed that on correct trials, lexical error probability effects were present during initial stages of speech planning, while AP error probability effects emerged during speech motor preparation. In contrast, error trials showed differences from correct utterances in both early and late speech motor preparation and during articulation. These findings suggest that (a) response conflict on ultimately correct trials does not persist during articulation; (b) the timecourse of response conflict is restricted to the time window during which a given linguistic level is task-relevant (early on for response appropriateness-related variables and later for articulation-relevant variables); and (c) monitoring during the response is primarily triggered by pre-response monitoring failure. These results support that monitoring in language production is temporally distributed and rely on multiple mechanisms.

Hybrid vehicular access protocol and message prioritization for real-time safety messaging

Real-time safety services rely on the exchange of messages to enhance the operations of connected and automated vehicles (CAVs). These safety messages convey vital information about traffic conditions, enabling drivers to take necessary measures to prevent accidents. The timely and reliable delivery of these messages is essential, necessitating efficient channel access. Vehicular Deterministic Access (VDA) is employed as a channel access scheme with distinct priorities and stringent timing guidelines, particularly for urgent safety warnings. In this paper, we propose a hybrid approach that combines VDA and Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocols, along with a message prioritization algorithm, to ensure efficient and reliable communication of safety messages in vehicular networks. Our approach leverages the strengths of both VDA and CSMA/CA to avoid message collisions; VDA is more efficient under high traffic loads, while CSMA/CA is better suited for low traffic loads. Additionally, the incorporation of the message prioritization algorithm ensures strict deadline guarantees for high-priority messages, such as Decentralized Environmental Notification Messages (DENMs). We evaluate our proposed solution using the Artery simulation framework. Our results show over a 93% delivery rate for DENM exchanges while maintaining low collision probability across various traffic loads. This research provides practical guidance for the development of efficient and reliable communication systems for CAVs. It also offers a detailed analysis of the trade-offs among different access protocols and message prioritization strategies in vehicular networks.

Privacy-preserving and verifiable convolution neural network inference and training in cloud computing

With the rapid development of cloud computing, outsourcing massive data and complex deep learning model to cloud servers (CSs) has become a popular trend, which also brings some security problems. One is that the model stored in the CSs may be corrupted, leading to incorrect inference and training results. The other is that the privacy of outsourced data and model may be compromised. However, existing privacy-preserving and verifiable inference schemes suffer from low detection probability, high communication overhead and substantial computational time. To solve the above problems, we propose a privacy-preserving and verifiable scheme for convolutional neural network inference and training in cloud computing. In our scheme, the model owner generates the authenticators for model parameters before uploading the model to CSs. In the phase of model integrity verification, model owner and user can utilize these authenticators to check model integrity with high detection probability. Furthermore, we design a set of privacy-preserving protocols based on replicated secret sharing for both the inference and training phases, significantly reducing communication overhead and computational time. Through security analysis, we demonstrate that our scheme is secure. Experimental evaluations show that the proposed scheme outperforms existing schemes in privacy-preserving inference and model integrity verification.

In-situ passivating surface defects of ultra-thin MAPbBr3 perovskite single crystal films for high performance photodetectors

Ultra-thin single crystal film (SCF) without grain boundary, inherits low charge recombination probability as bulk single crystals. However, its low depth brings a high surface defects ratio and hinders carrier transport and extraction, which affects the performance and stability of optoelectronic devices such as photodetectors, and thus surface defect passivation is of great practical significance. In this paper, we used the space confined method to grow MAPbBr3 SCF and selected BA2PbI4 for surface defect passivation. The results reveal that BA cation passivates MA vacancy surface defects, reduces carrier recombination, and enhances carrier lifetime. The carrier mobility is as high as 33.6 cm2V−1s−1, and the surface defect density is reduced to 3.4 ​× ​1012 ​cm−3. Thus, the self-driven vertical MAPbBr3 SCF photodetector after surface passivation exhibits more excellent optoelectronic performance.

HMGA2 regulates GPX4 expression and ferroptosis in prostate cancer cells

Prostate cancer (PCa) remains a significant global health burden and an increase in oxidative stress is associated with cancer progression. High Mobility Group A2 (HMGA2), a chromatin architectural protein, increases oxidative stress and promotes sensitivity to ferroptosis inducers, however, the mechanism is unknown. We investigated the role of HMGA2 in GPX4 regulation and the impact on cellular responses to oxidative stress and ferroptosis sensitivity. We conducted UALCAN database analysis, western blot analysis, and lipid peroxidation assays to determine the relationship between HMGA2 and GPX4 and the levels of lipid reactive oxygen species in a panel of PCa cell lines, including an enzalutamide-resistant cancer cell line (C4–2B MDVR). Our results show an inverse relationship between HMGA2 and GPX4 expression with high HMGA2 and low GPX4 expression associated with higher Gleason score and lower survival probability in prostate adenocarcinoma (PRAD) patients, while low/moderate HMGA2 expression is positively associated with increased GPX4 expression and higher survival probability. Cell lines showed a moderately negative but not statistically significant correlation between HMGA2 and GPX4 expression, however, PC3 and DU145 PCa cells display higher lipid peroxides concomitant with higher endogenous levels of HMGA2 and low GPX4. Overexpression of wild-type HMGA2 in LNCaP and 22Rv1 cells leads to higher HMGA2 expression compared to Neo control and is associated with higher SLC7A11 and GPX4 expression, while interestingly truncated HMGA2 overexpression in LNCaP and 22Rv1 cells coincides with higher HMGA2 and reduced GPX4 expression, leading to increased lipid peroxides and susceptibility to ferroptosis. Overexpression of wild-type and truncated HMGA2 in 22Rv1 cells increases SLC7A11 mRNA yet differing GPX4 protein expression suggests posttranslational regulation of GPX4. Moreover, enzalutamide-resistant C4–2B MDVR cells display higher HMGA2 levels compared to C4–2B cells, as well as sensitivity to RSL3 ferroptosis inducer, which is partially reversed by ferroptosis inhibitor, ferrostatin-1. Interestingly, GPX4 expression is higher in C4–2B MDVR cells compared to C4–2B, and HMGA2 knockdown further increases its expression but does not significantly alter its susceptibility to ferroptosis. In conclusion, our study shows that HMGA2 regulation of GPX4 expression is complex and truncated HMGA2 downregulates GPX4 and increases lipid peroxides. Moreover, HMGA2-expressing cells including enzalutamide-resistant cells are susceptible to RSL-3-induced ferroptosis. Thus, ferroptosis sensitivity offers promising insights for the development of targeted therapeutic interventions for aggressive PCa.

Research and Practice of Sand Control Completion Technology Optimization in Western H Oilfield

Abstract In view of the problems of poor reservoir physical properties, high clay content, loose cementation, shallow burial, low compaction degree, low temperature in the middle and deep oil layers during the development process of unconsolidated sandstone reservoirs in the western H oilfield, the original sand control technology has poor adaptability and short sand control validity period., this paper carried out research on the optimization of sand control completion technology. In the study, a series of optimization studies were conducted, including analysis of acoustic time difference in sand producing layers, simulation of sand control formation compaction, optimization of gravel filling particle size, and sand control tools. A high-strength artificial wellbore and cyclic gravel filling sand control completion process suitable for different sand producing well conditions were developed and applied in practice. The research results and on-site practice indicate that the high-strength artificial wellbore sand control completion technology has good adaptability in low-temperature and long wellbore sand production wells; The cyclic gravel filling sand control completion technology has the advantages of simple construction, low cost, and low probability of major repairs in conventional shallow sand producing wells; The complementary advantages of the two processes effectively solve the problem of sand damage in H oilfield. Since 2021, the optimized sand control completion technology has been applied 46 times in H oilfield, with an average recovery oil production of 3.4t per well and an average effective period of over 500 days for sand control. The overall input-output ratio is 1:2.8, achieving good benefits and having high promotion and application value.

A multi-layer constrained spectral k-embedded clustering methodology approach for intelligent partitioning of power grid to enhance resiliency in transmission networks

The intentional controlled islanding by intelligent partitioning of the power grid is considered as essential to protect the grid from cascading events, faults, and High Impact Low Probability (HILP) events. To enhance the resilience, stability, and security of the power grid, the proposed model in this paper intentionally divides the affected power network into islands. This paper presents an intelligent partitioning approach to create an islanding solution through multilayer graphs using spectral clustering. The controlled islanding algorithm uses a multi-criteria objective function that considers the correlation coefficients among the frequency of the buses and minimal disturbances in the real and reactive power. The proposed control technique is implemented in two phases. The first phase employs correlation coefficients between frequency of the buses and modularity clustering to identify clusters of coherent buses. During the second stage, all nodes are categorised into groups using Multi-level constrained Spectral Clustering (ML-CSC) to determine the solution for Intentional controlled Islanding that satisfies bus coherency with the minimum level of disruptions to real and reactive power flows across the boundaries. The proposed algorithm for resolving the generator coherency issue and an intelligent islanding solution is demonstrated by simulation experiments conducted on an IEEE 39-bus transmission test system developed in DIGSILENT Powerfactory version 2023. The MATLAB version R2023a is used to construct the ML-CSC control method. The results demonstrated that the proposed ML-CSC algorithm substantially impacts the functioning of the power system, enabling the formation of intelligent islanding during abnormal conditions. Also, the results clearly show that instead of using single-layer spectral clustering, the multi-layer spectral clustering yields a better intentional islanding solution with minimum power flow mismatch which enhances the transient stability of the islands.

It is, uh, very likely? The impact of prosodic uncertainty cues on the perception and interpretation of spoken verbal probability phrases.

People typically use verbal probability phrases when discussing risks ("It is likely that this treatment will work"), both in written and spoken communication. When speakers are uncertain about risks, they can nonverbally signal this uncertainty by using prosodic cues, such as a rising, question-like intonation or a filled pause ("uh"). We experimentally studied the effects of these two prosodic cues on the listener's perceived speaker certainty and numerical interpretation of spoken verbal probability phrases. Participants (N=115) listened to various verbal probability phrases that were uttered with a rising or falling global intonation and with or without a filled pause before the probability phrase. For each phrase, they gave a point estimate of their numerical interpretation in percentages and indicated how certain they thought the speaker was about the correctness of the probability phrase. Speakers were perceived as least certain when the verbal probability phrases were spoken with both prosodic uncertainty cues. Interpretation of verbal probability phrases varied widely across participants, especially when rising intonation was produced by the speaker. Overall, high probability phrases (e.g., "very likely") were estimated as lower (and low probability phrases, such as "unlikely," as higher) when they were uttered with a rising intonation. The effects of filled pauses were less pronounced, as were the uncertainty effects for medium probability phrases (e.g., "probable"). These results stress the importance of nonverbal communication when verbally communicating risks and probabilities to people, for example, in the context of doctor-patient communication.

Design and Synthesis of a Novel Pyrazole-Based Molecule with Potential Anticancer and Antimicrobial effects: A Multifaceted in silico Approach

Although cancer remains the largest cause of morbidity and mortality globally, there is growing concern about the usage of cancer drugs due to their serious side effects. Therefore, a compound, 3,5-di(1H-indol-6-yl)-4,5-dihydro-1H-pyrazole-1-carboxamide, was synthesized using a mixture of (E)-1, 3-Di(1H-indol-3-yl) prop-2-en-1-one, semicarbazide hydrochloride, and sodium acetate. It was then examined for its anticancer and antimicrobial properties using molecular docking, molecular dynamic simulations and molecular mechanics, and generalised born surface area (MM/GBSA). The molecular docking was performed by targeting the cancer and antimicrobial associated proteins, namely protein tyrosine phosphatase L1 (1WCH), tankyrase-1 (5ETY), and phosphotransferase enzyme family protein (6SUI). Eventually, 3,5-di(1H-indol-6-yl)-4,5-dihydro-1H-pyrazole-1-carboxamide was found to be the most promising drug candidate for fighting both cancer and microbial infections. With docking scores of -9.730 Kcal/mol for 1WCH, -9.142 Kcal/mol for 5ETY, and -7.026 Kcal/mol for 6SUI, it showed strong interactions with all the target proteins. To investigate the binding stability of 3,5-di(1H-indol-6-yl)-4,5-dihydro-1H-pyrazole-1-carboxamide with the target molecules, molecular dynamics simulations were performed for 100 ns on the docked complexes. With an RMSD of less than 2.8Å, the synthesized compound was highly stable with all of the targets for 100 ns. Furthermore, the evaluation of the binding free energies (MM/GBSA) of these complexes revealed that the simulated environment had no significant influence on the binding energies, implying the synthesized molecule has strong binding affinities with the target proteins. Furthermore, in the toxicity assessment, the active probability ratio for 3,5-di(1H-indol-6-yl)-4,5-dihydro-1H-pyrazole-1-carboxamide was less than 0.60, indicating a low probability of organ toxicity and endpoint toxicity. Based on the results, the research concludes that the synthesized novel pyrazole-based compound could be a promising candidate for the development of new therapeutic drugs for the treatment of cancer and microbial infections.

Addressing large scale patterns of no-flow events in rivers: An in-depth analysis with Achelous software

Establishment of hydrological criteria that could serve as guidelines for addressing intermittency is not an easy task. However, efforts in the last years are yielding promising advancements in this direction. Scientists have been working to unravel the complexities of intermittency dynamics. In this study, we aimed to investigate the characteristics of naturally intermittent water systems by exploring the occurrence of no-flow events. A hydrological model was employed to generate streamflow data. Our analysis encompassed a thorough examination of nineteen flow regime metrics, estimated across 2064 subbasins, with 190 of these meeting the criterion for intermittency. A custom Python library was deployed to automate the quantification of no-flow events, aligning with the concept of critical thresholds. Using the probabilistic t-distributed Stochastic Neighbor Embedding technique to capture complex patterns, three clusters were emerged. The first one was characterized by a low probability of no-flow events and a small number of no-flow events per year, the second cluster was abundant in no-flow events and demonstrated a tendency towards longer annual recession time scales. The third cluster stands out due to the significant variance in the duration of no-flow events. Concerning the time variability of the no-flow events, we concluded that they predominantly occurred during August. Both long- and short-term quantification of no-flow events should be under consideration so as to harmonize the naturally intermittent waterways with the water use requirements and the potential consequences of not meeting them. Future research should prioritize the investigation of hydroecology and ecohydrology in relation to streamflow dynamics and ecosystem interactions. By doing so, we can elevate our comprehension of how intermittent water systems function and their significance within the broader ecological context.

Creating and validating a neurosurgical intervention rule-out tool for patients with mild traumatic brain injury and isolated subdural hematoma: a 5-year, six-center retrospective cohort study.

Because there is no reliable method on admission to predict whether a patient will require neurosurgical intervention in the future, the general approach remains to treat each patient with mild traumatic brain injury (mTBI) and subdural hematoma (SDH) as if they will require such an intervention. Consequently, there is a growing population of patients with mTBI and SDH that is overtriaged despite having a low probability of needing neurosurgical intervention. This study aimed to train and validate a predictive rule-out tool for neurosurgical intervention in patients with mTBI and SDH. This was a retrospective cohort study of all trauma patients admitted to six level I trauma centers in three states. Patients were included if they met the following criteria: admitted between 2016 and 2020, ≥ 18 years of age, ICD-10 diagnosis of isolated SDH, initial head imaging available, initial Glasgow Coma Scale score of 13-15, and arrived within 48 hours of injury. Exclusion criteria included skull fracture, intracranial hemorrhage other than an SDH, and no neurosurgical consultation. Prediction variables included 34 demographic, clinical, and radiographic variables. The study outcome was neurosurgical intervention within 48 hours of hospital admission. Seventy-five percent of the data were used for training, and 25% for testing. Multivariable logistic regression with fivefold cross-validation was used on the training set to identify covariates with the highest specificity while holding sensitivity at 100%. Results were validated on the testing set. In total, 1000 patients were in the training set and 333 in the testing set. The overall neurosurgical intervention rate was 8.8%. For the fivefold cross-validation process, three variables were selected that maximized specificity while holding sensitivity at 100%: maximum hematoma thickness, initial Glasgow Coma Scale score, and preinjury antithrombotic use (sensitivity 100%, specificity 56%, area under the receiver operating characteristic curve 0.94). With a cutoff probability of neurosurgical intervention set at 1.88%, the final model was validated to predict neurosurgical intervention with a sensitivity of 100% (95% CI 88.4%-100%) and specificity of 55.1% (95% CI 49.3%-60.8%). In this study, the largest of its kind to date, the authors successfully developed and validated a new tool for ruling out the necessity of neurosurgical intervention in patients with mTBI and isolated SDH. By successfully identifying more than half of patients who are unlikely to require neurosurgery within the first 2 days of admission, this tool can be used to improve treatment efficiency and provide patients and clinicians with valuable prognostic information.