Completely Normal Research Articles

Neutrosophic Generalized Regular Star Compact, Connected, Regular and Normal Topological Spaces

Neutrosophic Generalized Regular Star Compact, Connected, Regular and Normal Topological Spaces

Thermodynamic geometry of STU black holes

This work investigates the phase structure of STU black holes with uniform charges by utilizing the New Thermodynamic Geometry (NTG) approach. The study explores the intriguing relationship between heat capacity phase transitions and curvature singularities, employing the NTG formalism. The analysis encompasses an examination of phase transitions along the T − S and Q − Φ planes, a study of critical exponents, and an assessment of black hole stability. The NTG geometry is applied in both the normal and extended phase spaces, revealing valuable insights into the thermodynamic behavior and stability of STU black holes. Meanwhile, a closer examination of NTG geometry shows a positive correlation in the sign between the extrinsic curvature and the heat capacity, which is incompatible with the curvature singularity. Overall, this study contributes to our understanding of the phase transitions and thermodynamic properties of STU black holes, shedding light on the intricate interplay between curvature singularities and the stability of black holes in diverse thermodynamic scenarios.

A whole-body diffusion MRI normal atlas: development, evaluation and initial use

BackgroundStatistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task.MethodsMulti-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture.ResultsSex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4–48% at 1.5T, 6–70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision.ConclusionsWhole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.

Regular and normal spaces for certain generalized open sets in ideal topological spaces

In this paper, we study four types of generalized open sets: Pre-I-open sets, Semi-I-open sets, α-I-open sets, and b-I-open sets, in ideal topological spaces and define the regular and normal spaces for these generalized open sets. We establish some of their properties and compare these regular and normal spaces.

Cartesian constraints in QM/MM optimizations.

With the rise of quantum mechanical/molecular mechanical (QM/MM) methods, the interest in the calculation of molecular assemblies has increased considerably. The structures and dynamics of such assemblies are usually governed to a large extend by intermolecular interactions. As a result, the corresponding potential energy surfaces are topological rich and possess many shallow minima. Therefore, local structure optimizations of QM/MM molecular assemblies can be challenging, in particular if optimization constraints are imposed. To overcome this problem, structure optimization in normal coordinate space is advocated. To do so, the external degrees of freedom of a molecule are separated from the internal ones by a projector matrix in the space of the Cartesian coordinates. Here we extend this approach to Cartesian constraints. To this end, we devise an algorithm that adds the Cartesian constraints directly to the projector matrix and in this way eliminates them from the reduced coordinate space in which the molecule is optimized. To analyze the performance and stability of the constrained optimization algorithm in normal coordinate space, we present constrained minimizations of small molecular systems and amino acids in gas phase as well as water employing QM/MM constrained optimizations. All calculations are performed in the framework of auxiliary density functional theory as implemented in the program deMon2k.

APPLICATION OF STATISTICAL PROCESS CONTROL IN MECHANIZED CORN SEEDING

Several factors alter the quality of the mechanized sowing process of corn, and the use of the statistical process control (SPC) technique not only allows the identification of process limitation points but also ensures the correct functioning and conduction of the mechanized process, determining critical factors. that may decrease their performance. In view of the above, the present study aims to qualitatively evaluate, through this technique, the longitudinal distribution of corn seeds as a function of different stands and operational speeds during the sowing process. The experiment was carried out in a randomized block design (CBD) with three replications and in a split-plot design. Data were submitted to analysis of variance and when significant, analyzed using Tukey's test, with 5% significance. To carry out the statistical process control, mean and amplitude control charts were used to evaluate the effect of operational speed, seed distribution, deposition depth and plant germination. The results indicate that the use of statistical process control is an efficient tool to identify the behavior of the corn sowing process. Based on the results, speeds close to 4.5 km/h allowed an efficient sowing process, as it presented a higher percentage of normal spaces in the distribution of maize seeds.

Electric drive system for seed metering and its effects on the distribution and development of the corn crop

The present study aimed to evaluate the efficiency of the electric transmission drive of the seed metering mechanism of a precision seeder, in relation to the mechanical drive, in the distribution of corn seeds, and its effects on the development of the crop. The experiment was carried out using precision agriculture techniques - geostatistics - in a plot of 4.19 ha managed under no-tillage system. The area was divided into a grid with 35 points for each treatment (electrical transmission of the seed metering mechanism and mechanical transmission of the seed metering mechanism). To carry out the experiment, a precision seeder consisting of 7 lines was used, configured with 0.45m line spacing, being: 4 consecutive lines by electrical transmission and 3 consecutive lines driven by mechanical transmission. The electrical transmission of the seed dosing mechanism provided, in relation to mechanical transmission, a lower coefficient of variation of the linear distribution of seeds, a lower spacing index with failure, a higher normal spacing index, and a smaller difference in seeding density. As a consequence, the electrical transmission of the seed metering mechanism increased the productivity of the corn crop by 1.33% (87.96 kg ha-1) when compared to mechanical transmission.

Some Properties of Generalized (Λ, α)-Closed Sets

The aim of this paper is to introduce the concept of generalized (Λ, α)-closed sets. Moreover, we investigate some characterizations of Λα-T1/2 -spaces, (Λ, α)-normal spaces and (Λ, α)-regular spaces by utilizing generalized (Λ, α)-closed sets.

Fuzzy Fixed Point Theorems in Normal Cone Metric Space

In this paper, we proved a few fuzzy fixed point theorems in whole regular cone metric spaces, which can be the generalization of a few current consequences within side the literature.

Exploring Normal Covering Spaces: A Bridge between Algebraic Topology and Abstract Algebra

Exploring Normal Covering Spaces: A Bridge between Algebraic Topology and Abstract Algebra

Integral Estimates and Multiplier Operators from Normal Weight General Function Spaces to Bloch Type Spaces

Integral Estimates and Multiplier Operators from Normal Weight General Function Spaces to Bloch Type Spaces

Characterizations of Some Topological Spaces

This paper is concerned with the concepts of some topological spaces. Firstly, we introduce the notions of δs(Λ, p)-open sets. Some properties concerning δs(Λ, p)-open sets are discussed. Secondly, the concept of s(Λ, p)-connected spaces is introduced. Moreover, we give several characterizations of s(Λ, p)-connected spaces by utilizing δs(Λ, p)-open sets. Thirdly, we apply the notion of s(Λ, p)-open sets to present and study new classes of spaces called s(Λ, p)-regular spaces and s(Λ, p)-normal spaces. Especially, some characterizations of s(Λ, p)-regular spaces and s(Λ, p)-normal spaces are established. Fourthly, we introduce and investigate the concepts of s(Λ, p)-T2 spaces and s(Λ, p)-Urysohn spaces. Finally, the notion of S(Λ, p)-closed spaces is studied. Basic properties and characterizations of S(Λ, p)-closed spaces are considered.

Generalized integral type Hilbert operator acting between weighted Bloch spaces

Let be a finite Borel measure on . In this paper, we consider the generalized integral type Hilbert operator The operator has been extensively studied recently. The aim of this paper is to study the boundedness (resp. compactness) of acting from the normal weight Bloch space into another of the same kind. As consequences of our study, we get completely results for the boundedness of acting between Bloch type spaces, and between logarithmic Bloch spaces.

Prime spectrums of EQ-algebras

Abstract The main purpose of this paper is to study prime spectrums of EQ-algebras and to solve two open problems about $\wedge $-prime spectrums of involutive and prelinear EQ-algebras, which were proposed by N. Akhlaghinia, R.A. Borzooei and M. A. Kologani. In order to do so, we first give some characterizations of preideals, prime preideals and maximal preideals on (good) EQ-algebras, respectively. Then we introduce the notion of quasi De Morgan EQ-algebras (MEQ-algebras for short) and obtain that $\wedge $-prime preideals coincide with prime preideals for MEQ-algebras, and each involutive EQ-algebra is an MEQ-algebra. Following, we show that the prime spectrum space of a good EQ-algebra is a compact topological space and obtain that for any involutive EQ-algebra the prime spectrum space is connected if and only if its Boolean center is indeed 2-element. Also, we prove that the maximal spectrum space of a good and prelinear EQ-algebra (or an involutive and prelinear EQ-algebra) is a normal Hausdorff space. These results totally answer the above two open problems. Finally, we give some characterizations of the spectrum space of an MEQ-algebra by its reticulation.

Superposition operators between normal weight bloch spaces

Superposition operators between normal weight bloch spaces

Normal paracontact metric space form on $W_0$-curvature tensor

In this article, normal paracontact metric space forms are investigated on $W_0$-curvature tensor. Characterizations of normal paracontact space forms are obtained on $W_0$-curvature tensor. Special curvature conditions established with the help of Riemann, Ricci, and concircular curvature tensors are discussed on $W_0$-curvature tensor. Through these curvature conditions, some important characterizations of normal paracontact metric space forms are obtained. Finally, the need for further research is discussed.

A unified framework for multi-lead ECG characterization using Laplacian Eigenmaps

Background. The analysis of multi-lead electrocardiographic (ECG) signals requires integrating the information derived from each lead to reach clinically relevant conclusions. This analysis could benefit from data-driven methods compacting the information in those leads into lower-dimensional representations (i.e. 2 or 3 dimensions instead of 12). Objective. We propose Laplacian Eigenmaps (LE) to create a unified framework where ECGs from different subjects can be compared and their abnormalities are enhanced. Approach. We conceive a normal reference ECG space based on LE, calculated using signals of healthy subjects in sinus rhythm. Signals from new subjects can be mapped onto this reference space creating a loop per heartbeat that captures ECG abnormalities. A set of parameters, based on distance metrics and on the shape of loops, are proposed to quantify the differences between subjects. Main results. This methodology was applied to find structural and arrhythmogenic changes in the ECG. The LE framework consistently captured the characteristics of healthy ECGs, confirming that normal signals behaved similarly in the LE space. Significant differences between normal signals, and those from patients with ischemic heart disease or dilated cardiomyopathy were detected. In contrast, LE biomarkers did not identify differences between patients with cardiomyopathy and a history of ventricular arrhythmia and their matched controls. Significance. This LE unified framework offers a new representation of multi-lead signals, reducing dimensionality while enhancing imperceptible abnormalities and enabling the comparison of signals of different subjects.

Risk Control of Energy Performance Fluctuation in Multi-Unit Housing for Weather Uncertainty

With the acceleration of urban development, the population density of urban cities has increased. As the spatial characteristics of multi-unit housing (MUH) perfectly fit this developmental trend and, simultaneously, have high energy efficiency, the number of MUHs has increased rapidly in recent decades. Although many studies have proposed high energy efficiency strategies, weather uncertainty leads to errors between the operational performance of building energy and simulated values. This study introduces a robust optimization framework that incorporates uncertainty considerations into the optimization process to suppress energy consumption fluctuations and improve the average building energy consumption performance. Neural networks are used to model the uncertainty of multiple weather elements as normal distributions for each hour, and the accuracy of the uncertainty model is validated by calculating the mean absolute percentage error (MAPE) between the mean values of the distribution and the measurement values, which ranges from 3% to 13%. The clustering algorithm is proposed to replace the sampling method to complete the sampling work from the normal distribution space of the weather elements to serve the subsequent optimization process. Compared with the traditional method, the sampling results of the clustering algorithm show better representativeness in the sample space. The robust optimization results show that the average energy consumption of the optimal scheme decreases by 13.4%, and the standard deviation decreases by approximately 17.2%, which means that the optimal scheme, generated by the robust optimization framework proposed in this study, has lower average energy consumption results and a more stable energy consumption performance in the face of weather uncertainty.

Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection

Learning discriminative features for effectively separating abnormal events from normality is crucial for weakly supervised video anomaly detection (WS-VAD) tasks. Existing approaches, both video and segment level label oriented, mainly focus on extracting representations for anomaly data while neglecting the implication of normal data. We observe that such a scheme is sub-optimal, i.e., for better distinguishing anomaly one needs to understand what is a normal state, and may yield a higher false alarm rate. To address this issue, we propose an Uncertainty Regulated Dual Memory Units (UR-DMU) model to learn both the representations of normal data and discriminative features of abnormal data. To be specific, inspired by the traditional global and local structure on graph convolutional networks, we introduce a Global and Local Multi-Head Self Attention (GL-MHSA) module for the Transformer network to obtain more expressive embeddings for capturing associations in videos. Then, we use two memory banks, one additional abnormal memory for tackling hard samples, to store and separate abnormal and normal prototypes and maximize the margins between the two representations. Finally, we propose an uncertainty learning scheme to learn the normal data latent space, that is robust to noise from camera switching, object changing, scene transforming, etc. Extensive experiments on XD-Violence and UCF-Crime datasets demonstrate that our method outperforms the state-of-the-art methods by a sizable margin.

BH05 Successful treatment of acrodermatitis continua of Hallopeau with methotrexate

Abstract A 39-year-old woman was referred with a 3-month history of brittle nails, painful fingertips and psoriasiform plaques affecting her torso and limbs. She had a past medical history of macrocytic anaemia secondary to dietary B12 and folate deficiencies, which required inpatient transfusions. She had no previous dermatological concerns, and there was no history of infection or trauma to the affected sites. On examination of her hands and feet, there was evidence of nailbed pustulation, subungual hyperkeratosis, onychodystrophy, anonychia of multiple nails and dactylitis, consistent with acrodermatitis continua of Hallopeau (ACH) with associated psoriasis. At diagnosis, the patient’s Dermatology Life Quality Index (DLQI) was 16, she had a Psoriasis Area and Severity Index (PASI) score of 18 and a Psoriasis Epidemiology Screening Tool (PEST) score of 4. Nail fungal culture was negative. Plain radiographs of the hands and feet demonstrated a flexion deformity of the left fifth finger distal interphalangeal joint, with otherwise normal bone texture, alignment and joint spaces. The patient was initially treated with potent topical corticosteroids and vitamin D analogues, with little improvement. The patient was commenced on 15 mg subcutaneous methotrexate (MTX), with close monitoring of serum and red cell folate given her background of folate deficiency, which was being actively replaced. Within 3 months of starting MTX monotherapy, the patient’s hands had dramatically improved with skin and fingernail changes largely resolved, and an improvement in manual dexterity (DLQI 11, PASI 3, PEST 5). MTX was increased to 20 mg once weekly and the patient was also started on sulfasalazine 500 mg twice daily by her rheumatologist for psoriatic arthritis. ACH is a chronic pustular eruption initially affecting distal phalanges with gradual proximal progression and the potential development of generalized pustular psoriasis. ACH is considered a variant of palmoplantar pustulosis, commonly affecting adult females with localized trauma and infection as possible triggers. Given the rarity of ACH, the evidence base for therapy is limited to case reports and series, with no standardized treatment guidelines. Topical therapies include corticosteroids, calcineurin inhibitors and vitamin D analogues. Local phototherapy and systemic therapy with acitretin, MTX and ciclosporin have been described, with wide-ranging results. In severe cases such as this, patients typically receive biologic therapy, with variable responses reported with tumour necrosis factor-α inhibitors, anti-interleukin (IL)-6 therapy, and anti-IL-12/IL-23 and anti-IL-17 therapy. We present a rare case of severe ACH and psoriasis, treated with MTX monotherapy, which was not only clinically effective but also cost-effective.