bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zingiberaceae Rhizome Essential Oil: A Review of Chemical Composition, Biological Activity, and Application in Food Industry
Authors: Destryana RA , Estiasih T , Sukardi  , Pranowo D 
Published: February 2024

Abstract
Several of Zingiberaceae‘s rhizomes are aromatic and medicinal plants that have been used for thousands of years to enhance food’s taste, color, and aroma. The Zingiberaceae plant is found in various ecosystems in Southeast Asia, including cultivation areas and tropical rainforests. It can be found growing at the edge of the forest or well-rooted on the forest floor. This plant is one of the agroforestry product that usually used for cooking, perfume, dyes, and traditional medicine, especially ethnic medicine. Zingiberaceae products can be consumed in various forms, such as fresh, cooked, or boiled..This rhizome is effective in the treatment of several medical conditions such as digestive, respiratory, nervous, and muscle system problems, as well as other degenerative diseases. Phenolic compounds as secondary metabolites found in Zingiberaceae rhizome plants have been shown to have good biological activity for human health and as antibacterials in their applications in food and pharmaceutical products. The main objective of this review is to provide an overview of essential oils from Zingiberaceae rhizome commodities in terms of chemical components, biological activity, safety, and potential applications in the food industry. A number of literature search methods, in this article the narrative literature observation method is used, by searching for related keywords such as essential oils, zingiberaceae, rhizomes, phytochemicals, ginger, turmeric, ginger, Alpinia, in scientific article search engines such as Google Scholar, Scopus, Web search. of Science, and PubMed implemented. This narrative review will help researchers to describe research developments related to essential oils produced from the rhizome commodity of aromatic plants and medicinal plants from the Zingiberaceae family.The common use of rhizome essential oil in food and traditional medicine has attracted researchers worldwide for its application in the food industry. In this review, this topic is discussed in detail along with the results of scientific research supporting the application of essential oils in food and their functional properties, such as the main functional properties of antioxidant, antibacterial and antifungal.
The Role of Agroforestry to Improve Farming System Sustainability in Upper Brantas Watershed
Authors: Suhartini S , Dwi Cahyono Edi , Maulana Ishaq Riski , Nur Jihad Baroroh , Sandi Lasitya Daffa , Irwandi Putra , Fajar Maulana Muhammad 
Published: February 2024

Abstract
The upper Brantas Watershed area must be conserved, especially for ecological function. On the other hand, the farmers need income to support their livelihoods. So that, the farmers prefer cultivating vegetables in highlands and on land with slopes more than 30 degrees. It will make the agricultural systems tend to be unsustainable in the long run so that it can affect the ecological function of the watershed. This research aimed to analyze the effect of agroforestry techniques on farming sustainability in the upper Brantas Watershed. The location was determined purposively in a farming system with and without an agroforestry system in Batu City. This study uses quantitative and qualitative approaches with survey techniques by field observation and interviews with the farmers and relevant stakeholders. The results showed that the application of conservation farming with the concept of agroforestry will support the farming system‘s sustainability, especially on the ecological aspect.
Complex far fields and optical singularities due to propagation beyond tight focusing: combined effects of wavefront curvature and aperture diffraction
Authors: Kumar Nitish , Debnath Anirban , Viswanathan Nirmal K 
Published: February 2024

Abstract
All optical systems, which involve the collimation of a reflected, transmitted or scattered wave subsequent to tight focusing, are subject to two kinds of deviations. One is the wavefront curvature due to inaccurate focal placement of the interface or scatterer particle under consideration, and the other is the diffraction caused by the finite lens aperture. In the present paper we explore these phenomena in detail by considering a rigorous simulated model and an appropriate experimental setup. We hence demonstrate the complicated intensity profiles and optical singularity characteristics of the observed far field. Then we describe ways to minimize these deviations in a general experiment. But more importantly, our analysis proves that these deviations by themselves are significant optical phenomena of fundamental interest. The observed complex field profiles have similarities to standard diffraction-limited tight focal fields, though our field detection is different from the standard schemes. This indicates the relevance of these complex fields to a larger class of systems involving wavefront curvature and aperture diffraction. The detailed analysis and results of the present paper already serve as core explorations of these optical phenomena; and we also suggest future research directions where these system aspects can be purposefully created and explored further.
A wearable gait-analysis device for idiopathic normal-pressure hydrocephalus (INPH) monitoring
Authors: Atbas Erdem , Gaydecki Patrick , Callaghan Michael J 
Published: February 2024

Abstract
Idiopathic Normal Pressure Hydrocephalus (iNPH) is a progressive neurologic disorder (fluid build-up in the brain) that affects 0.2%–5% of the UK population aged over 65. Mobility problems, dementia and urinary incontinence are symptoms of iNPH but often these are not properly evaluated, and patients receive the wrong diagnosis. Here, we describe the development and testing of firmware embedded in a wearable device in conjunction with a user-based software system that records and analyses a patient’s gait. The movement patterns, expressed as quantitative data, allow clinicians to improve the non-invasive assessment of iNPH as well as monitor the management of patients undergoing treatment. The wearable sensor system comprises a miniature electronic unit that attaches to one ankle of the patient via a simple Velcro strap which was designed for this application. The unit monitors acceleration along three axes with a sample rate of 60 Hz and transmits the data via a Bluetooth communication link to a tablet or smart phone running the Android and the iOS operating systems. The software package extracts statistics based on stride length, stride height, distance walked and speed. Analysis confirmed that the system achieved an average accuracy of at least 98% for gait tests conducted over distances 9 m. This device has been developed to assist in the management and treatment of older adults diagnosed with iNPH.
Stereotactic Optimized Automated Radiotherapy (SOAR): a novel automated planning solution for multi-metastatic SRS compared to HyperArc™
Authors: Mann Thomas , Ploquin Nicolas , Faruqi Salman , Loewen Shaun , Thind Kundan 
Published: February 2024

Abstract

Objective. Automated Stereotactic Radiosurgery (SRS) planning solutions improve clinical efficiency and reduce treatment plan variability. Available commercial solutions employ a template-based strategy that may not be optimal for all SRS patients. This study compares a novel beam angle optimized Volumetric Modulated Arc Therapy (VMAT) planning solution for multi-metastatic SRS to the commercial solution HyperArc. Approach. Stereotactic Optimized Automated Radiotherapy (SOAR) performs automated plan creation by combining collision prediction, beam angle optimization, and dose optimization to produce individualized high-quality SRS plans using Eclipse Scripting. In this retrospective study 50 patients were planned using SOAR and HyperArc. Assessed dose metrics included the Conformity Index (CI), Gradient Index (GI), and doses to organs-at-risk. Complexity metrics evaluated the modulation, gantry speed, and dose rate complexity. Plan dosimetric quality, and complexity were compared using double-sided Wilcoxon signed rank tests (α = 0.05) adjusted for multiple comparisons. Main Results. The median target CI was 0.82 with SOAR and 0.79 with HyperArc (p < .001). Median GI was 1.85 for SOAR and 1.68 for HyperArc (p < .001). The median V12Gy normal brain volume for SOAR and HyperArc were 7.76 cm3 and 7.47 cm3 respectively. Median doses to the eyes, lens, optic nerves, and optic chiasm were statistically significant favoring SOAR. The SOAR algorithm scored lower for all complexity metrics assessed. Significance. In-house developed automated planning solutions are a viable alternative to commercial solutions. SOAR designs high-quality patient-specific SRS plans with a greater degree of versatility than template-based methods.
Enhancing oil pressure dynamics in a high-performance racing engine with innovative lubrication system tuning
Authors: Pai Anand , Singh Virk Sharanpreet , Pai K Dayananda , Shenoy B Satish , Nayak Suhas Yeshwant 
Published: February 2024

Abstract
This work focuses on fine-tuning the oil pressure dynamics of a single-seater formula car, a participant in international engineering competition organized by the Society of Automotive Engineers (SAE). Adhering to competition guidelines, the Honda CBR600RR 05-06® motorcycle engine, renowned for its 600 c.c. displacement and exceptional power-to-weight ratio, emerges as a popular choice. However, as this engine is originally equipped with a wet sump lubrication system (featuring deep wet sumps to prevent oil starvation during turns), this presents challenges when adapted to Formula Society of Automotive Engineers (FSAE) cars. Cornering leads to significant pressure drops, as sloshing exposes the pickup port, causing consequential engine issues. To tackle sloshing-related challenges and pressure loss during lateral and longitudinal g-forces, a dry sump lubrication system was introduced in the Formula car. The dry sump system also lowers the engine’s center of gravity, by reducing sump height. However, transitioning to the dry sump system and integrating it with the existing engine demanded extensive design modifications to various components, including the oil reservoir, lubrication lines, scavenging pump, and oil ports. These adjustments were essential to achieve the targeted elevation in oil pressures at higher engine RPMs. A relationship between the engine oil pressure and the engine RPM was developed as part of the study.
Topic evolution before fall incidents in new fallers through natural language processing of general practitioners’ clinical notes
Authors: Dormosh Noman , Abu-Hanna Ameen , Calixto Iacer , Schut Martijn C , Heymans Martijn W , van der Velde Nathalie 
Published: February 2024

Abstract

Background
Falls involve dynamic risk factors that change over time, but most studies on fall-risk factors are cross-sectional and do not capture this temporal aspect. The longitudinal clinical notes within electronic health records (EHR) provide an opportunity to analyse fall risk factor trajectories through Natural Language Processing techniques, specifically dynamic topic modelling (DTM). This study aims to uncover fall-related topics for new fallers and track their evolving trends leading up to falls.

Methods
This case–cohort study utilised primary care EHR data covering information on older adults between 2016 and 2019. Cases were individuals who fell in 2019 but had no falls in the preceding three years (2016–18). The control group was randomly sampled individuals, with similar size to the cases group, who did not endure falls during the whole study follow-up period. We applied DTM on the clinical notes collected between 2016 and 2018. We compared the trend lines of the case and control groups using the slopes, which indicate direction and steepness of the change over time.

Results
A total of 2,384 fallers (cases) and an equal number of controls were included. We identified 25 topics that showed significant differences in trends between the case and control groups. Topics such as medications, renal care, family caregivers, hospital admission/discharge and referral/streamlining diagnostic pathways exhibited a consistent increase in steepness over time within the cases group before the occurrence of falls.

Conclusions
Early recognition of health conditions demanding care is crucial for applying proactive and comprehensive multifactorial assessments that address underlying causes, ultimately reducing falls and fall-related injuries.
Personalized treatment selection via product partition models with covariates
Authors: Pedone Matteo , Argiento Raffaele , Stingo Francesco C 
Published: February 2024

ABSTRACTPrecision medicine is an approach for disease treatment that defines treatment strategies based on the individual characteristics of the patients. Motivated by an open problem in cancer genomics, we develop a novel model that flexibly clusters patients with similar predictive characteristics and similar treatment responses; this approach identifies, via predictive inference, which one among a set of treatments is better suited for a new patient. The proposed method is fully model based, avoiding uncertainty underestimation attained when treatment assignment is performed by adopting heuristic clustering procedures, and belongs to the class of product partition models with covariates, here extended to include the cohesion induced by the normalized generalized gamma process. The method performs particularly well in scenarios characterized by considerable heterogeneity of the predictive covariates in simulation studies. A cancer genomics case study illustrates the potential benefits in terms of treatment response yielded by the proposed approach. Finally, being model based, the approach allows estimating clusters’ specific response probabilities and then identifying patients more likely to benefit from personalized treatment.
Longitudinal varying coefficient single-index model with censored covariates
Authors: Wang Shikun , Ning Jing , Xu Ying , Shih Ya-Chen Tina , Shen Yu , Li Liang 
Published: February 2024

ABSTRACT
It is of interest to health policy research to estimate the population-averaged longitudinal medical cost trajectory from initial cancer diagnosis to death, and understand how the trajectory curve is affected by patient characteristics. This research question leads to a number of statistical challenges because the longitudinal cost data are often non-normally distributed with skewness, zero-inflation, and heteroscedasticity. The trajectory is nonlinear, and its length and shape depend on survival, which are subject to censoring. Modeling the association between multiple patient characteristics and nonlinear cost trajectory curves of varying lengths should take into consideration parsimony, flexibility, and interpretation. We propose a novel longitudinal varying coefficient single-index model. Multiple patient characteristics are summarized in a single-index, representing a patient's overall propensity for healthcare use. The effects of this index on various segments of the cost trajectory depend on both time and survival, which is flexibly modeled by a bivariate varying coefficient function. The model is estimated by generalized estimating equations with an extended marginal mean structure to accommodate censored survival time as a covariate. We established the pointwise confidence interval of the varying coefficient and a test for the covariate effect. The numerical performance was extensively studied in simulations. We applied the proposed methodology to medical cost data of prostate cancer patients from the Surveillance, Epidemiology, and End Results-Medicare-Linked Database.
Efficient designs and analysis of two-phase studies with longitudinal binary data
Authors: Di Gravio Chiara , Schildcrout Jonathan S , Tao Ran 
Published: February 2024

AbstractResearchers interested in understanding the relationship between a readily available longitudinal binary outcome and a novel biomarker exposure can be confronted with ascertainment costs that limit sample size. In such settings, two-phase studies can be cost-effective solutions that allow researchers to target informative individuals for exposure ascertainment and increase estimation precision for time-varying and/or time-fixed exposure coefficients. In this paper, we introduce a novel class of residual-dependent sampling (RDS) designs that select informative individuals using data available on the longitudinal outcome and inexpensive covariates. Together with the RDS designs, we propose a semiparametric analysis approach that efficiently uses all data to estimate the parameters. We describe a numerically stable and computationally efficient EM algorithm to maximize the semiparametric likelihood. We examine the finite sample operating characteristics of the proposed approaches through extensive simulation studies, and compare the efficiency of our designs and analysis approach with existing ones. We illustrate the usefulness of the proposed RDS designs and analysis method in practice by studying the association between a genetic marker and poor lung function among patients enrolled in the Lung Health Study (Connett et al, 1993).
That’s not the Mona Lisa! How to interpret spatial capture-recapture density surface estimates
Authors: Durbach Ian , Chopara Rishika , Borchers David L , Phillip Rachel , Sharma Koustubh , Stevenson Ben C 
Published: February 2024

ABSTRACT
Spatial capture-recapture methods are often used to produce density surfaces, and these surfaces are often misinterpreted. In particular, spatial change in density is confused with spatial change in uncertainty about density. We illustrate correct and incorrect inference visually by treating a grayscale image of the Mona Lisa as an activity center intensity or density surface and simulating spatial capture-recapture survey data from it. Inferences can be drawn about the intensity of the point process generating activity centers, and about the likely locations of activity centers associated with the capture histories obtained from a single survey of a single realization of this process. We show that treating probabilistic predictions of activity center locations as estimates of the intensity of the process results in invalid and misleading ecological inferences, and that predictions are highly dependent on where the detectors are placed and how much survey effort is used. Estimates of the activity center density surface should be obtained by estimating the intensity of a point process model for activity centers. Practitioners should state explicitly whether they are estimating the intensity or making predictions of activity center location, and predictions of activity center locations should not be confused with estimates of the intensity.
Mitochondrial myopathies diagnosed in adulthood: clinico-genetic spectrum and long-term outcomes
Authors: Beecher Grayson , Gavrilova Ralitza H , Mandrekar Jay , Naddaf Elie 
Published: February 2024

Abstract
Mitochondrial myopathies are frequently recognized in childhood as part of a broader multisystem disorder and often overlooked in adulthood. Herein, we describe the phenotypic and genotypic spectrum and long-term outcomes of mitochondrial myopathies diagnosed in adulthood, focusing on neuromuscular features, electrodiagnostic and myopathological findings and survival. We performed a retrospective chart review of adult patients diagnosed with mitochondrial myopathy at Mayo Clinic (2005–21). We identified 94 patients. Median time from symptom onset to diagnosis was 11 years (interquartile range 4–21 years). Median age at diagnosis was 48 years (32–63 years). Primary genetic defects were identified in mitochondrial DNA in 48 patients (10 with single large deletion, 38 with point mutations) and nuclear DNA in 29. Five patients had multiple mitochondrial DNA deletions or depletion without nuclear DNA variants. Twelve patients had histopathological features of mitochondrial myopathy without molecular diagnosis. The most common phenotypes included multisystem disorder (n = 30); mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes (14); limb myopathy (13); chronic progressive external ophthalmoplegia (12); and chronic progressive external ophthalmoplegia-plus (12). Isolated skeletal muscle manifestations occurred in 27%. Sixty-nine per cent had CNS and 21% had cardiac involvement. Mutations most frequently involved MT-TL1 (27) and POLG (17); however, a wide spectrum of established and novel molecular defects, with overlapping phenotypes, was identified. Electrodiagnostic studies identified myopathy (77%), fibrillation potentials (27%) and axonal peripheral neuropathy (42%, most common with nuclear DNA variants). Among 42 muscle biopsies available, median percentage counts were highest for cytochrome C oxidase negative fibres (5.1%) then ragged blue (1.4%) and ragged red fibres (0.5%). Skeletal muscle weakness was mild and slowly progressive (decline in strength summated score of 0.01/year). Median time to gait assistance was 5.5 years from diagnosis and 17 years from symptom onset. Thirty patients died, with median survival of 33.4 years from symptom onset and 10.9 years from diagnosis. Median age at death was 55 years. Cardiac involvement was associated with increased mortality [hazard ratio 2.36 (1.05, 5.29)]. There was no difference in survival based on genotype or phenotype. Despite the wide phenotypic and genotypic spectrum, mitochondrial myopathies in adults share similar features with slowly progressive limb weakness, contrasting with common multiorgan involvement and high mortality.
Traumatic brain injury disrupts state-dependent functional cortical connectivity in a mouse model
Authors: Bottom-Tanzer Samantha , Corella Sofia , Meyer Jochen , Sommer Mary , Bolaños Luis , Murphy Timothy , Quiñones Sadi , Heiney Shane , Shtrahman Matthew , Whalen Michael , Oren Rachel , Higley Michael J , Cardin Jessica A , Noubary Farzad , Armbruster Moritz , Dulla Chris 
Published: February 2024

Abstract
Traumatic brain injury (TBI) is the leading cause of death in young people and can cause cognitive and motor dysfunction and disruptions in functional connectivity between brain regions. In human TBI patients and rodent models of TBI, functional connectivity is decreased after injury. Recovery of connectivity after TBI is associated with improved cognition and memory, suggesting an important link between connectivity and functional outcome. We examined widespread alterations in functional connectivity following TBI using simultaneous widefield mesoscale GCaMP7c calcium imaging and electrocorticography (ECoG) in mice injured using the controlled cortical impact (CCI) model of TBI. Combining CCI with widefield cortical imaging provides us with unprecedented access to characterize network connectivity changes throughout the entire injured cortex over time. Our data demonstrate that CCI profoundly disrupts functional connectivity immediately after injury, followed by partial recovery over 3 weeks. Examining discrete periods of locomotion and stillness reveals that CCI alters functional connectivity and reduces theta power only during periods of behavioral stillness. Together, these findings demonstrate that TBI causes dynamic, behavioral state-dependent changes in functional connectivity and ECoG activity across the cortex.