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Nevin Manimala Statistics

Quantum mechanics once baffled scientists. Now it’s changing the world

Quantum mechanics has journeyed from a strange and controversial idea to the foundation of some of humanity’s most advanced technologies. Now researchers are pushing its boundaries even further, with potential breakthroughs in energy, medicine, computing, and our understanding of the universe.
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Nevin Manimala Statistics

Efficacy of adjunctive Yoga Nidra in patients with functional dissociative seizures receiving structured psychoeducation (YOGA-FDS): a pilot randomised controlled trial

Epilepsy Behav. 2026 Jul 5;183:111180. doi: 10.1016/j.yebeh.2026.111180. Online ahead of print.

ABSTRACT

BACKGROUND: Functional dissociative seizures (FDS) are paroxysmal seizure-like events with no electrographic abnormalities. Structured psychoeducation is considered a standard component of FDS management. Yoga Nidra (YN) is a guided meditative relaxation technique that has shown benefit in other neuropsychiatric conditions, but its adjunctive role in FDS has not been studied.

OBJECTIVE: To evaluate whether adjunctive YN provides additional benefit over structured brief psychoeducation alone in reducing monthly FDS frequency.

METHODS: This open-label, randomised controlled pilot trial enrolled 50 FDS patients aged ≥13 years, randomised 1:1 to receive brief psychoeducation plus YN (n = 25) or brief psychoeducation plus sham YN (n = 25). All participants received structured psychoeducation; the intervention group additionally practised standardised audio-guided YN. The primary outcome was the change in monthly FDS frequency. Secondary outcomes included 6-month FDS episode count, seizure freedom duration, HAM-A, HAM-D, WSAS, and QOLIE-31 scores. Outcomes were assessed at 6 months by a blinded evaluator.

RESULTS: Between January 2021 and February 2022, 72 patients were screened, and 22 were excluded. Fifty patients were randomly assigned to receive brief psychoeducation plus YN (n = 25) or brief psychoeducation plus sham YN (n = 25), of whom primary outcome data were available for 48 patients at 6 months (23 patients in the brief psychoeducation plus YN group and 25 in the brief psychoeducation plus sham YN group). Median monthly FDS frequency reduced from 6 (IQR 2.5-45) to 0.5 (0-1) in the brief psychoeducation plus YN group and from 7 (3.5-45) to 0.5 (01.7) in the sham group; between-group difference was not statistically significant (p = 0.88).

CONCLUSION: Both groups demonstrated substantial clinical improvement during follow-up in seizure frequency, mood symptoms, functioning and quality of life; however, adjunctive YN did not provide measurable additional benefit over the control condition. Larger studies are needed to clarify the role of adjunctive YN in the management of functional dissociative seizures.

PMID:42402245 | DOI:10.1016/j.yebeh.2026.111180

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Nevin Manimala Statistics

ECG arrhythmia classification via wavelet-driven feature extraction and swarm-optimised gradient boosting

Comput Biol Med. 2026 Jul 5;213:111839. doi: 10.1016/j.compbiomed.2026.111839. Online ahead of print.

ABSTRACT

Cardiovascular diseases have been the primary contributor to deaths worldwide, and hence, the need to detect arrhythmia from Electrocardiogram signals in a precise and efficient manner is a critical problem in the medical community. This work presents a lightweight and computationally efficient framework that integrates Discrete Wavelet Transform (DWT)-based statistical features, ECG morphological descriptors, and Artificial Bee Colony (ABC)-optimized eXtreme Gradient Boosting Machine (XGBM) classification for ECG beat analysis. This work has been implemented using the popular MIT-BIH Arrhythmia Database, which has 100,674 instances of ECG beats, divided into five AAMI classes, with a severe level of class imbalance, where 89.4% instances belong to the Normal class. ECG signals have been pre-processed using a seven-stage algorithm, including Butterworth high-pass filtering, notch filtering, Pan-Tompkins R-peak detection, beat segmentation, and normalisation. Then, a three-level Haar transform is implemented, and 32 statistical features have been extracted from the DWT decomposition, along with 32 morphological features, forming a 64-dimensional vector. The proposed ABC algorithm with 8 bees and 8 iterations optimizes the six XGBM model hyperparameters using a balanced fitness function of accuracy and macro F1-score and converges at the optimal fitness value of 0.8211. The proposed ABC-XGBM model has a classification accuracy of 95.14%, a macro F1-score of 0.948, a macro AUC of 0.983, Matthews Correlation Coefficient of 0.925, and G-Mean of 0.932 with class-wise AUC values > 0.94. An ablation study has shown that the proposed DWT adds +3.7% and the proposed ABC optimization adds +1.14% in accuracy improvement. Five-fold cross-validation has shown a stable performance with a mean accuracy of 0.952 ± 0.001 at a time complexity of 1.0 ms per sample without the dependency of the GPU. The proposed framework is better than the other deep learning models such as CardioAttentionNet with a classification accuracy of 91.20% and the proposed transformer-based classifier with a classification accuracy of 90.50%.

PMID:42402238 | DOI:10.1016/j.compbiomed.2026.111839

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Nevin Manimala Statistics

Decoupling clinker technology from cement product emissions: A macroeconomic ML-LCA framework for global embodied carbon policy screening

J Environ Manage. 2026 Jul 5;413:130402. doi: 10.1016/j.jenvman.2026.130402. Online ahead of print.

ABSTRACT

The cement industry contributes approximately 7-8% of global anthropogenic CO2 emissions, yet accurate cradle-to-gate embodied carbon estimation requires plant-level inventory data that are largely unavailable across developing and emerging economies. This data scarcity constrains global benchmarking and the implementation of emerging embodied carbon regulations. This study proposes a STIRPAT-grounded hybrid machine learning-life cycle assessment (ML-LCA) framework for estimating national-scale cement embodied carbon using exclusively publicly available macroeconomic data. GDP per capita, population, and temporal indicators are used to predict the clinker-to-cement ratio (CCR), which is subsequently propagated through a technology-stratified, process-based LCA model enforcing stoichiometric and thermodynamic constraints across A1-A3 stages. Among seven candidate algorithms, Gradient Boosting was selected for its smooth non-linear approximation and LCA integration suitability. SHAP analysis confirms GDP per capita as the dominant CCR driver, with contributions directionally consistent with established technology diffusion theory, ensuring model transparency. Validation across 18 economies through statistical metrics, residual diagnostics, country-level diagnostic benchmarking, Leave-One-Country-Out (LOCO) cross-validation, and three independent literature-benchmarking countries (Pakistan, Mexico, Spain) confirms physically plausible and externally consistent outputs ranging from 0.53 to 0.97 kg CO2/kg cement. A central methodological contribution is the ability to estimate the clinker-substitution decoupling effect at the country scale using only macroeconomic inputs, in contexts where plant-level LCA inventory data are unavailable. Conventional LCA already separates process, energy, and material composition contributions when inventory data are present; the present framework extends this separation to data-scarce national contexts. At the system level, an Environmental Kuznets Curve-type pattern is qualitatively reproduced when model outputs are aggregated across countries, providing a coherence check on the framework as a whole. Out-of-country generalisation is assessed using Leave-One-Country-Out (LOCO) cross-validation as the primary protocol (mean fold RMSE 0.077; 12 of 18 folds below RMSE 0.10), with a forward-chaining temporal split as a complementary diagnostic. The framework is operationalised through an interactive decision-support interface, offering a scalable, transparent baseline for embodied carbon benchmarking, policy screening, and net-zero pathway evaluation in the global cement sector. The framework is positioned as a screening-level reference for data-scarce contexts, complementary to plant-level LCA and Environmental Product Declarations where these are available.

PMID:42402234 | DOI:10.1016/j.jenvman.2026.130402

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Nevin Manimala Statistics

Cyanobacterial resilience and productivity decoupling from declining phosphorus during a four-year whole-lake aeration

J Environ Manage. 2026 Jul 5;413:130432. doi: 10.1016/j.jenvman.2026.130432. Online ahead of print.

ABSTRACT

Urban eutrophic lakes in subtropical regions represent a persistent management challenge due to their strong internal feedbacks that resist rehabilitation. We report a four-year whole-lake intervention evaluating the effectiveness of artificial aeration in a 10 m-deep, eutrophic urban lake in Uruguay, using a Before-After Control-Impact (BACI) design with a comparable reference lake. Despite continuous operation, aeration did not alter the seasonal warm-monomictic regime nor eliminate summer deep-layer anoxia. However, it partially weakened thermal stratification and drove a sustained, statistically significant decline in surface total phosphorus (∼18 μg P L-1 yr-1), shifting the TP-based trophic state index from hypereutrophic to eutrophic. In contrast, chlorophyll-a remained hypereutrophic throughout, revealing a marked decoupling between nutrient availability and phytoplankton productivity. Persistent cyanobacterial dominance, rising phosphorus-use efficiency, and cycles of intense bloom growth, collapse, and rapid recovery indicate physiological adjustment to declining phosphorus rather than a proportional loss of biomass. The reference lake showed no equivalent directional changes, supporting the attribution of these trends to aeration. The intervention altered specific processes-thermal stability and internal phosphorus release-without shifting the dominant feedbacks sustaining eutrophy, consistent with “pathological resilience”, wherein internal mechanisms perpetuate a degraded state despite external perturbation. Aeration alone proved insufficient to trigger structural reorganization within four years, underscoring the need for integrated, adaptive rehabilitation strategies in urban lakes with strong self-sustaining eutrophic feedbacks.

PMID:42402233 | DOI:10.1016/j.jenvman.2026.130432

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Nevin Manimala Statistics

Postoperative complications after injection laryngoplasty for minor laryngeal clefts

Int J Pediatr Otorhinolaryngol. 2026 Jul 2;207:112922. doi: 10.1016/j.ijporl.2026.112922. Online ahead of print.

ABSTRACT

OBJECTIVE: To describe the incidence, clinical presentation, and management of postoperative complications following injection laryngoplasty for minor laryngeal clefts and to assess their impact on postoperative dysphagia evolution.

METHODS: A unicentric retrospective case-control study of pediatric patients who underwent injection laryngoplasty for minor laryngeal clefts (hyaluronic acid-based injectable or sodium carboxymethylcellulose) between January 2018 and October 2025 in a tertiary pediatric center was conducted. Demographics, comorbidities, intraoperative variables, postoperative dysphagia outcomes, and Penetration-Aspiration Scale scores were analyzed. Ordinal logistic regression was used to evaluate the overall dysphagia trajectory.

RESULTS: Among 48 patients, 10 (20.8%) developed postoperative complications. Case and control groups were comparable in age, sex, weight percentiles, gestational age and most comorbidities. Operative duration, injected volume, and intraoperative antibiotic use were similar (all p > 0.2). Swallowing outcomes (resolution, improvement, persistence, or worsening) did not differ between groups. Ordinal logistic regression showed no association between complications and the dysphagia trajectory (Odds ratio, OR 5.1, p = 0.2). PAS severity categories were also similar (p = 0.8). Patients with hyaluronic acid appeared to have more complications (26.5%) compared to methylcellulose (7.1%), despite not reaching statistical significance.

CONCLUSION: Despite a higher-than-expected complication rate, postoperative inflammatory or infectious complications were not linked to worse swallowing function or higher PAS scores. These findings inform risk-benefit discussions and support informed shared decision-making with families regarding minor cleft treatment options.

PMID:42402231 | DOI:10.1016/j.ijporl.2026.112922

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Nevin Manimala Statistics

Bullying and sexual harassment of medical and nursing students, in relation to stress, burnout and intention to dropout

Int J Med Educ. 2026 Jul 2;17:90-96. doi: 10.5116/ijme.6a31.6bd0.

ABSTRACT

OBJECTIVES: This study examines the prevalence and impact of bullying and sexual harassment among students in nursing and medical education programmes in Sweden.

METHODS: This cross-sectional survey targeted students from 38 universities. A total of 18,582 individuals responded to the questionnaire, yielding a 25% response rate. The sample included students enrolled in nursing (N = 1,083) and medical (N = 431) programmes. Data were analysed using descriptive statistics and two-sample t-tests.

RESULTS: Among female students who experienced bullying, higher levels of stress ( t (1188) = 4.91, p < .001), burnout (t(1188) = 5.83, p < .001), and intention to quit studies ( t (1186) = 4.30, p < .001) were reported. Bullied male students showed elevated stress ( t (317) = 3.15, p = .002), burnout ( t (317) = 3.49, p < .001), and intention to quit ( t (316) = 3.67, p < .001). Female students who experienced sexual harassment reported increased stress ( t (1185) = 4.02, p < .001), burnout ( t (1185) = 4.10, p < .001), and intention to quit ( t (1184) = 2.73, p = .006). In contrast, sexually harassed male students reported higher stress ( t (314) = 2.04, p = .042), but no significant differences in burnout ( t (314) = 0.80, p = .425) or intention to quit ( t (314) = 1.86, p = .064). Students from the nursing- and medical programme reported a higher prevalence of bullying and sexual harassment than other students.

CONCLUSIONS: Given the high prevalence and detrimental effects of bullying and sexual harassment in nursing and medical education, targeted interventions are needed to prevent and address these behaviours.

PMID:42402223 | DOI:10.5116/ijme.6a31.6bd0

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Nevin Manimala Statistics

Association of Valvular Disease Progression Using Echocardiographic Findings in a Large U.S. Cohort

Echocardiography. 2026 Jul;43(7):e70546. doi: 10.1111/echo.70546.

ABSTRACT

BACKGROUND: The prevalence of valvular disease in the US is approximately 2.5%. Given that over 5 million Americans are affected, it is crucial to find those at higher risk of progression. The goal of this paper is to uncover which patients are more likely to have valvular disease progression using demographic factors, EKG and echocardiogram (ECHO) findings.

METHODS: This paper utilized the EchoNext Database, which pairs 100,000 electrocardiograms and echocardiograms based on specific structural heart disease labels. Univariate and multivariate logistic regression were used to find risk factors for progression for aortic stenosis (AS), aortic regurgitation (AR), mitral regurgitation (MR), tricuspid regurgitation (TR) and pulmonary insufficiency (PI). Progression was defined as worsened valvular disease on follow up ECHOs.

RESULTS: There were 100,000 encounters of EKGs/ECHOs included in the study, and 36,286 individual patients. Independent risk factors of AS progression were age and QRS duration. Age, QRS duration, AS, AR, MR and pericardial effusion were independent risk factors for AR progression. MR progression was independently associated with PR, QRS and QTc durations, MR and left ventricular ejection fraction. QRS duration, MR, TR and right ventricular function were independent factors for TR progression. Lastly, for PI progression, male sex and AS were found to be independent risk factors.

CONCLUSIONS: The combination of demographic, electrocardiographic and echocardiographic findings can help better assess the progression of valvular disease.

PMID:42402188 | DOI:10.1111/echo.70546

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Nevin Manimala Statistics

Niacinamide/ Co-enzyme Q10 loaded transferosomal gel for anti-aging and enhanced biophysical skin outcome: a split-face clinical study

J Cosmet Laser Ther. 2026 Jul 5:1-10. doi: 10.1080/14764172.2026.2698114. Online ahead of print.

ABSTRACT

This study investigated the dermatological outcomes of a transferosomal gel encapsulating Niacinamide and Co-enzyme Q10 compared with a conventional base gel in healthy female volunteers over a 12-week period, with a particular focus on key biophysical and aesthetic skin parameters. Before human use, both formulations underwent primary skin irritation testing on rabbit skin, followed by a patch test on healthy volunteers to establish safety. A randomized split-face study design was implemented. Skin hydration, elasticity, melanin, erythema, sebum content, pore size, spots, and wrinkle indices were systematically assessed. Sensory evaluation and appropriate statistical analyses complemented the biophysical measurements. Irritation and patch-test assessments confirmed the nonirritant, well-tolerated nature of both formulations. The transferosomal gel demonstrated significantly higher efficacy (p < .05) across multiple parameters, including hydration, elasticity, melanin, erythema reduction, and sebum regulation. Improvements in pore size, spot reduction, and wrinkle were also more substantial and became evident as early as week 2, with continual enhancement observed throughout the 12-week study. Transferosomal delivery of Niacinamide and Co-enzyme Q10 demonstrates improved topical efficacy compared with conventional formulation, as evidenced by the performance outcomes. It offers a safe, noninvasive delivery strategy for improving skin-related parameters within the study conditions.

PMID:42402180 | DOI:10.1080/14764172.2026.2698114

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Nevin Manimala Statistics

Effectiveness of polycaprolactone-based dermal fillers for full-face rejuvenation

J Cosmet Laser Ther. 2026 Jul 5:1-6. doi: 10.1080/14764172.2026.2697503. Online ahead of print.

ABSTRACT

Aging impacts all facial layers, leading to aesthetic concerns such as lines, folds, and furrows. Injectable dermal fillers are commonly employed to address these changes, with polycaprolactone (PCL) emerging as a widely used and innovative option. Images from before and after PCL injection were analyzed from 31 medical records (n = 31). The treatment points were 11. Images were processed in GIMP, and the selection of the facial area was in Adobe Photoshop, and the selected area was calculated in ImageJ. Associations between measurement variations before and after the procedure were tested concerning the increase and decrease in projections and shadows in the places where PCL was injected. The margin of error was 5% (p = .05) in the Bootstrap test (n = 300), Tukey’s post hoc test, and ANOVA. There was no statistically significant difference in the zygomatic (p = .093), angle and ramus of the mandible (p = .07), and labiomental sulcus (p = .3559). In all other areas, there was a reduction in the shadow area, which was associated with an increase in the projection/prominence of the regions adjacent to the injection. PCL proved effective in full-face use in most areas tested (eight out of 11): Mean percentage reductions were: infraorbital margin (-8.3%, p = .021), palpebromalar groove (-7.4%, p = .006), piriformis fossa (-11.9%, p = .000), nasolabial fold (-9.5%, p = .002), oral commissure (-5.5%, p = .002), mentolabial groove (-9.0%, p = .001), pre-jowl area (-6.9%, p = .001), and chin (-6.9%, p = .001).

PMID:42402150 | DOI:10.1080/14764172.2026.2697503