Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling human interindividual variability in metabolism and risk: the example of 4-aminobiphenyl.

We investigate, through modeling, the impact of interindividual heterogeneity in the metabolism of 4-aminobiphenyl (ABP) and in physiological factors on human cancer risk: A physiological pharmacokinetic model was used to quantify the time course of the formation of the proximate carcinogen, N-hydroxy-4-ABP and the DNA-binding of the active species in the bladder. The metabolic and physiologic model parameters were randomly varied, via Monte Carlo simulations, to reproduce interindividual variability. The sampling means for most parameters were scaled from values developed by Kadlubar et al. (Cancer Res., 51: 4371, 1991) for dogs; variances were obtained primarily from published human data (e.g., measurements of ABP N-oxidation, and arylamine N-acetylation in human liver tissue). In 500 simulations, theoretically representing 500 humans, DNA-adduct levels in the bladder of the most susceptible individuals are ten thousand times higher than for the least susceptible, and the 5th and 95th percentiles differ by a factor of 160. DNA binding for the most susceptible individual (with low urine pH, low N-acetylation and high N-oxidation activities) is theoretically one million-fold higher than for the least susceptible (with high urine pH, high N-acetylation and low N-oxidation activities). The simulations also suggest that the four factors contributing most significantly to interindividual differences in DNA-binding of ABP in human bladder are urine pH, ABP N-oxidation, ABP N-acetylation and urination frequency.
Feature based 3D Object Recognition using Artificial Neural Networks

recognition of objects is one of the main goals for computer vision research. This paper formulates and solves the problem of three-dimensional (3D) object recognition for Polyhedral objects. A multiple view of 2D intensity images are taken from multiple cameras and used to model the 3D objects. The proposed methodology is based on extracting set of features from the 2D images which include the Affine, Zernike and Hu moments invariants to be used as inputs to train artificial neural network (ANN). Various architectures of ANN were explored to recognize a shape of Polyhedral objects. The experiments results show that 3D objects can be sufficiently modeled and recognized by set of multiple 2D views. The best ANN architecture was twenty input and single output model.
Dosimetric Comparison and Potential for Improved Clinical Outcomes of Paediatric CNS Patients Treated with Protons or IMRT

Background: We compare clinical outcomes of paediatric patients with CNS tumours treated with protons or IMRT. CNS tumours form the second most common group of cancers in children. Radiotherapy plays a major role in the treatment of many of these patients but also contributes to late side effects in long term survivors. Radiation dose inevitably deposited in healthy tissues outside the clinical target has been linked to detrimental late effects such as neurocognitive, behavioural and vascular effects in addition to endocrine abnormalities and second tumours. Methods: A literature search was performed using keywords: protons, IMRT, CNS and paediatric. Of 189 papers retrieved, 10 were deemed relevant based on title and abstract screening. All papers directly compared outcomes from protons with photons, five papers included medulloblastoma, four papers each included craniopharyngioma and low grade gliomas and three papers included ependymoma. Results: This review found that while proton beam therapy offered similar clinical target coverage, there was a demonstrable reduction in integral dose to normal structures. Conclusions: This in turn suggests the potential for superior long term outcomes for paediatric patients with CNS tumours both in terms of radiogenic second cancers and out-of-field adverse effects.
Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data

Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR‐derived metrics over the unburned area. The selected model estimated AGB with an R2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR‐based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (1012 g), which translate into 12.06 ± 0.06 Tg CO2e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars.
Analisis Sentimen Terhadap Kontroversi Fatwa MUI Nomor 83 Tahun 2023 Tentang Pemboikotan Produk yang Terafiliasi Israel

Abstrak: Kebijakan yang dikeluarkan oleh MUI, khususnya fatwa nomor 83 tahun 2023 yang membahas aspek moralitas dalam mendukung perjuangan palestina, menganjurkan untuk menghindari transaksi dan penggunaan produk yang terkait dengan Israel, terutama negara-negara yang mendukung penjajahan dan Zionisme semaksimal mungkin. Fenomena ini telah memunculkan berbagai tanggapan reaksi dan muncul sebagai subjek wacana yang trending di seluruh platform media sosial termasuk pengguna YouTube. Penelitian ini bertujuan mengembangkan model klasifikasi sentimen menggunakan mengkomparasi lima metode klasifikasi seperti Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), dan K-Nearest Neighbor (KNN) untuk memahami respons terhadap fatwa tersebut. Alat yang digunakan adalah Python Google Collab dengan dataset berasal dari komentar YouTube. Hasil analisis menunjukkan tiga klasifikasi sentimen: setuju, tidak setuju, dan netral, dengan tingkat akurasi Naive Bayes 75%, Decision Tree 65%, Random Forest 67%, SVM 63%, K-NN 53%. Penelitian ini diharapkan memberikan wawasan mendalam tentang distribusi sentimen terkait fatwa tersebut, serta menjadi dasar untuk penelitian lebih lanjut dalam analisis sentimen dan dinamika opini publik.
Atomoxetine Effects on Executive Function as Measured by the BRIEF-A in Young Adults with ADHD: A Randomized, Double-Blind, Placebo-Controlled Study

Objective To evaluate the effect of atomoxetine treatment on executive functions in young adults with attention-deficit/hyperactivity disorder (ADHD). Methods In this Phase 4, multi-center, double-blind, placebo-controlled trial, young adults (18–30 years) with ADHD were randomized to receive atomoxetine (20–50 mg BID, N = 220) or placebo (N = 225) for 12 weeks. The Behavior Rating Inventory of Executive Function-Adult (BRIEF-A) consists of 75 self-report items within 9 nonoverlapping clinical scales measuring various aspects of executive functioning. Mean changes from baseline to 12-week endpoint on the BRIEF-A were analyzed using an ANCOVA model (terms: baseline score, treatment, and investigator). Results At baseline, there were no significant treatment group differences in the percentage of patients with BRIEF-A composite or index T-scores ≥60 (p>.5), with over 92% of patients having composite scores ≥60 (≥60 deemed clinically meaningful for these analyses). At endpoint, statistically significantly greater mean reductions were seen in the atomoxetine versus placebo group for the BRIEF-A Global Executive Composite (GEC), Behavioral Regulation Index (BRI), and Metacognitive Index (MI) scores, as well as the Inhibit, Self-Monitor, Working Memory, Plan/Organize and Task Monitor subscale scores (p<.05), with decreases in scores signifying improvements in executive functioning. Changes in the BRIEF-A Initiate (p = .051), Organization of Materials (p = .051), Shift (p = .090), and Emotional Control (p = .219) subscale scores were not statistically significant. In addition, the validity scales: Inconsistency (p = .644), Infrequency (p = .097), and Negativity (p = .456) were not statistically significant, showing scale validity. Conclusion Statistically significantly greater improvement in executive function was observed in young adults with ADHD in the atomoxetine versus placebo group as measured by changes in the BRIEF-A scales. Trial Registration ClinicalTrials.gov NCT00510276
Changes in Vegetation Cover of the Arctic National Wildlife Refuge Estimated from MODIS Greenness Trends, 2000–18

Trends and transitions in the growing-season normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in ecosystems of the Arctic National Wildlife Refuge (ANWR) in Alaska. Statistical analysis of changes in the NDVI time series was conducted using the breaks for additive seasonal and trend method (BFAST). This structural change analysis indicated that NDVI breakpoints and negative 18-yr trends in vegetation greenness over the years since 2000 could be explained in large part by the impacts of severe wildfires. At least one NDVI breakpoint was detected in around 20% of the MODIS pixels within both the Porcupine River and Coleen River basins of the study area. The vast majority of vegetation cover in the ANWR Brooks Range and coastal plain ecoregions was detected with no (positive or negative) growing-season NDVI trends since the year 2000. Results suggested that most negative NDVI anomalies in the 18-yr MODIS record have been associated with early spring thawing and elevated levels of surface moisture in low-elevation drainages of the northern ANWR ecoregions.
A service-oriented virtual community overlay network for secure external service orchestration

The Service Oriented Architecture (SOA) is used extensively in ubiquitous computing environments. Using external service orchestration, services can be composed into applications. Since cooperation takes place between services that are scattered over the Internet and belong to different parties, there is a growing need to protect the ownership of service providers and keep the security of communication messages in service composition. This paper shows the details of a service-oriented virtual community overlay network designed for secure external service orchestration. It can also provide contracted QoS guarantees that will definitely affect the overall performance of ubiquitous applications. Further, it highlights the working principle of access control policies as well as a service behavior monitoring mechanism using an example scenario.
Quantifying Model of 3-Echelon Supply Chain Coordination Complexity Information Entropy Based

Considering research progress of complexity study and characteristic of supply chain coordination, from the relation between the complexity of a system and the amount of information which is needed to describe the state of a system, this paper proposes a quantifying model of 3-echelon supply chain coordination complexity information entropy based. The model includes two parts: supplier-manufacturer interface entropy model and manufacturer-retailer interface entropy model. Finally, through an example, gives the value of supply chain coordinating complexity and analyzes the results. Keywords3-echelon Supply Chain; Coordination; Complexity; Information Entropy
Failure correlation in software reliability models

Perhaps the most stringent restriction that is present in most software reliability models is the assumption of independence among successive software failures. Our research was motivated by the fact that although there are practical situations in which this assumption could be easily violated, much of the published literature on software reliability modeling does not seriously address this issue. In this paper we present a software reliability modeling framework based on Markov renewal processes which naturally introduces dependence among successive software runs. The presented approach enables the phenomena of failure clustering to be precisely characterized and its effects on software reliability to be analyzed. Furthermore, it also provides bases for a more flexible and consistent model formulation and solution. The Markov renewal model presented in this paper can be related to the existing software reliability growth models, that is, a number of them can be derived as special cases under the assumption of failure independence. Our future research is focused on developing more specific and detailed models within this framework, as well as statistical inference procedures for performing estimations and predictions based on the experimental data.
Transcription Factor Map Alignment of Promoter Regions

We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels—to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human–mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments.
Formal Analysis of Selective Disclosure Attribute-Based Credential System in Applied Pi Calculus

We propose a general framework of formally verifying selective disclosure attribute-based credential system. The framework includes two modules: the first module allows user to receive a credential, which contains a list of attributes, from a trusted party, the second module allows user to convince a service provider with the credential. Particularly, the user can selectively disclose parts of the attributes according to the requirement of the service provider, while not revealing the rest of the attributes. We formalize the framework with applied Pi calculus. It can be used to check attribute-based credential system on security properties. In our experiments, we apply the framework to a concrete security protocol and successfully provetheauthenticitypropertiesintheprotocolusingProVerif.
Essential Oils from Ugandan Aromatic Medicinal Plants: Chemical Composition and Growth Inhibitory Effects on Oral Pathogens

The study assessed the growth inhibitory effects of essential oils extracted from ten Ugandan medicinal plants (Bidens pilosa, Helichrysum odoratissimum, Vernonia amygdalina, Hoslundia opposita, Ocimum gratissimum, Cymbopogon citratus, Cymbopogon nardus, Teclea nobilis, Zanthoxylum chalybeum, and Lantana trifolia) used traditionally in the management of oral diseases against oral pathogens. Chemical compositions of the oils were explored by GC-MS. Inhibitory effects of the oils were assessed on periodontopathic Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans and cariogenic Streptococcus mutans and Lactobacillus acidophilus using broth dilution methods at concentrations of 1%, 0.1%, and 0.01%. The most sensitive organism was A. actinomycetemcomitans. Its growth was markedly inhibited by six of the oils at all the concentrations tested. Essential oil from C. nardus exhibited the highest activity with complete growth inhibition of A. actinomycetemcomitans and P. gingivalis at all the three concentrations tested, the major constituents in the oil being mainly oxygenated sesquiterpenes. Most of the oils exhibited limited effects on L. acidophilus. We conclude that essential oils from the studied plants show marked growth inhibitory effects on periodontopathic A. actinomycetemcomitans and P. gingivalis, moderate effects on cariogenic S. mutans, and the least effect on L. acidophilus. The present study constitutes a basis for further investigations and development of certain oils into alternative antiplaque agents.
Presence of Spontaneous Nystagmus, Benign Paroxysmal Positional Vertigo, and Tumarkin Fall in Patients With Primary Headache and Their Responses to Caloric and Video Head Impulse Tests

Background Migraine, vestibular migraine (VM) and tension-type headache (TTH) are the most common disorders in dizziness and headache clinics, associated with dizziness or vertigo and postural imbalance, causing a substantial burden on the individual and the society. The objective of this research was to examine the presence of spontaneous nystagmus, comorbidity of benign paroxysmal positional vertigo (BPPV), and Tumarkin fall in patients; additionally, the study focused on assessing the patients’ responses to bithermal caloric irrigation and video head impulse test (vHIT). Methods Consecutive patients diagnosed with migraine, VM, and TTH according to the International Classification of Headache Disorders, third edition (beta version (ICHD-3β)), who were referred to Dizziness and Headache Clinic were enrolled. BPPV and Tumarkin fall were assessed by questionnaires. The presence of BPPV was further evaluated through Dix-Hallpike or head roll maneuver, while spontaneous nystagmus was monitored using video-oculography during interictal period. Lastly, patients’ responses to bithermal caloric irrigation and vHIT were analyzed. Results There was a significantly higher incidence of spontaneous nystagmus in VM compared to both migraine and TTH. The drop attack episodes were slightly more frequent in VM than in TTH and migraine, though not statistically significant. The prevalence of BPPV was significantly higher in VM than in migraine and TTH. Unilateral vestibular paresis was more common in the VM group than in migraine and TTH. There was profound unilateral weakness (UW) in VM patients than in migraine, but no significant difference was found between VM and TTH. In VM, the percentage of saccades along with reduced vHIT gain was significantly higher than in migraine. Lastly, the percentage of abnormal response in vHIT was significantly lower than the percentage of abnormal UW in caloric irrigation across all groups. Conclusions In VM patients, the prevalences of decompensated peripheral damage and BPPV were higher than in migraine and TTH patients as disclosed by the presence of peripheral spontaneous nystagmus and abnormal vHIT during the interictal period. Our findings suggest that the peripheral vestibular system acts as a significant mechanism in the pathogenesis of VM, and it might also be involved in migraine and TTH cases without vertigo symptoms.
The vitamin D receptor gene variant and physical activity predicts fasting glucose levels in healthy young men.

AIMS Vitamin D can influence lipolysis and insulin secretion. A common genetic polymorphism of the vitamin D receptor (VDR), which has been found to be associated with bone mineral density, has been reported to be also associated with Type 2 diabetes mellitus (DM). To test the influence of the VDR polymorphism on fasting glucose in healthy young men before the onset of Type 2 DM, we studied a homogeneous population of aircrew members. METHODS A total of 1539 individuals were recruited during routine medical qualification for flying duty. Physical activity was assessed in all individuals and categorized into low physical activity (<or= 3 h per week) and high physical activity (> 3 h per week). The BsmI VDR polymorphism was analysed by polymerase chain reaction. On the day of blood testing the individuals were fasting for at least 8 h overnight. Serum glucose was measured within 60 min after sampling venous blood. RESULTS In young males with low physical activity (n = 752) gene carriers with the VDR genotype BB (n = 137) have significantly (P < 0.001) higher levels of fasting glucose (5.61 +/- 0.49 mmol/l) than gene carriers with the genotype Bb (n = 370; 5.44 +/- 0.44 mmol/l) or bb (n = 245; 5.38 +/- 0.44 mmol/l). Of BB gene carriers, 47% had fasting glucose levels > 5.55 mmol/l compared with 36% of Bb gene carriers and 34% of bb gene carriers (P = 0.018). This effect is absent in gene carriers with high physical activity (n = 787). CONCLUSIONS The VDR genotype is associated with altered fasting glucose levels in young men with low physical activity. If this association is confirmed in other populations it might be worthwhile studying the particular benefits of an exercise programme in dependents of the VDR genotype.
The occipital lateral plate mesoderm is a novel source for vertebrate neck musculature

In vertebrates, body musculature originates from somites, whereas head muscles originate from the cranial mesoderm. Neck muscles are located in the transition between these regions. We show that the chick occipital lateral plate mesoderm has myogenic capacity and gives rise to large muscles located in the neck and thorax. We present molecular and genetic evidence to show that these muscles not only have a unique origin, but additionally display a distinct temporal development, forming later than any other muscle group described to date. We further report that these muscles, found in the body of the animal, develop like head musculature rather than deploying the programme used by the trunk muscles. Using mouse genetics we reveal that these muscles are formed in trunk muscle mutants but are absent in head muscle mutants. In concordance with this conclusion, their connective tissue is neural crest in origin. Finally, we provide evidence that the mechanism by which these neck muscles develop is conserved in vertebrates.
Generative modelling for unsupervised score calibration

Score calibration enables automatic speaker recognizers to make cost-effective accept / reject decisions. Traditional calibration requires supervised data, which is an expensive resource. We propose a 2-component GMM for unsupervised calibration and demonstrate good performance relative to a supervised baseline on NIST SRE'10 and SRE'12. A Bayesian analysis demonstrates that the uncertainty associated with the unsupervised calibration parameter estimates is surprisingly small.