Miracle-dz/UniFAR-FTUs huggingface dataset:
Confidence Intervals based on Absolute Deviation for Population Mean of a Positively Skewed Distribution

This paper proposes three alternative confidence intervals namely, AADM-t, MAAD-t and MADM-t, which are simple adjustments to the Student-t confidence interval for estimating the population mean of a positively skewed distribution. The proposed methods are very easy to calculate and are not overly computer-intensive. The performance of these confidence intervals was compared through a simulation study using the following criterion: (a) coverage probability (b) average width and (c) coefficient of variation of width. Simulation studies indicate that for small sample sizes and moderate/highly positively skewed distributions, the proposed AADM-t confidence interval performs the best and it is as good as the Student-t confidence interval. Some real-life data are analyzed which support the findings of this paper to some extent.
Comparative Analysis and Identification of Terpene Synthase Genes in Convallaria keiskei Leaf, Flower and Root Using RNA-Sequencing Profiling

The ‘Lilly of the Valley’ species, Convallaria, is renowned for its fragrant white flowers and distinctive fresh and green floral scent, attributed to a rich composition of volatile organic compounds (VOCs). However, the molecular mechanisms underlying the biosynthesis of this floral scent remain poorly understood due to a lack of transcriptomic data. In this study, we conducted the first comparative transcriptome analysis of C. keiskei, encompassing the leaf, flower, and root tissues. Our aim was to investigate the terpene synthase (TPS) genes and differential gene expression (DEG) patterns associated with essential oil biosynthesis. Through de novo assembly, we generated a substantial number of unigenes, with the highest count in the root (146,550), followed by the flower (116,434) and the leaf (72,044). Among the identified unigenes, we focused on fifteen putative ckTPS genes, which are involved in the synthesis of mono- and sesquiterpenes, the key aromatic compounds responsible for the essential oil biosynthesis in C. keiskei. The expression of these genes was validated using quantitative PCR analysis. Both DEG and qPCR analyses revealed the presence of ckTPS genes in the flower transcriptome, responsible for the synthesis of various compounds such as geraniol, germacrene, kaurene, linalool, nerolidol, trans-ocimene and valencene. The leaf transcriptome exhibited genes related to the biosynthesis of kaurene and trans-ocimene. In the root, the identified unigenes were associated with synthesizing kaurene, trans-ocimene and valencene. Both analyses indicated that the genes involved in mono- and sesquiterpene biosynthesis are more highly expressed in the flower compared to the leaf and root. This comprehensive study provides valuable resources for future investigations aiming to unravel the essential oil-biosynthesis-related genes in the Convallaria genus.
Yellow rust of wheat in Serbia: Control challenges and perspectives

The causal agent of yellow rust (Puccinia striiformis f.sp. tritici) gained special attention in Serbia since the 2013/2014 production year, although its presence in the genetic collection at Rimski šančevi was noted by Jevtić et al. as early as 1997. Considering the mode of transmission of the yellow rust and its high ability to overcome host plant resistance, the aim of this study is to highlight the factors that influence the dynamics of its occurrence and the main challenges in controlling this pathogen in Serbia. The climatic factors in 2023 favored occurrence of wheat yellow rust in Serbia, similar to 2014, 2016, and 2018. However, it should be noted that the race composition of this pathogen can change from year to year, and the susceptibility and/or resistance of wheat genotypes to yellow rust depends on the combined effect of abiotic and biotic stressors. The complexity of factors influencing the level of susceptibility or resistance breakdown in wheat towards yellow rust has also been confirmed in the genetic collection at Rimski šančevi in 2023 when a significantly higher number of genotypes (80%) were infected with yellow rust compared to previous years, with a disease index exceeding 41%. The percentage of genotypes showing susceptibility reaction to yellow rust (DI>41%) was 47.7% in 2016 and 43% in 2018.
SARS-CoV-2 Spike Protein Interaction Space

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a +sense single-strand RNA virus. The virus has four major surface proteins: spike (S), envelope (E), membrane (M), and nucleocapsid (N), respectively. The constitutive proteins present a high grade of symmetry. Identifying a binding site is difficult. The virion is approximately 50–200 nm in diameter. Angiotensin-converting enzyme 2 (ACE2) acts as the cell receptor for the virus. SARS-CoV-2 has an increased affinity to human ACE2 compared with the original SAR strain. Topological space, and its symmetry, is a critical component in molecular interactions. By exploring this space, a suitable ligand space can be characterized accordingly. A spike protein (S) computational model in a complex with ACE 2 was generated using silica methods. Topological spaces were probed using high computational throughput screening techniques to identify and characterize the topological space of both SARS and SARS-CoV-2 spike protein and its ligand space. In order to identify the symmetry clusters, computational analysis techniques, together with statistical analysis, were utilized. The computations are based on crystallographic protein data bank PDB-based models of constitutive proteins. Cartesian coordinates of component atoms and some cluster maps were generated and analyzed. Dihedral angles were used in order to compute a topological receptor space. This computational study uses a multimodal representation of spike protein interactions with some fragment proteins. The chemical space of the receptors (a dimensional volume) suggests the relevance of the receptor as a drug target. The spike protein S of SARS and SARS-CoV-2 is analyzed and compared. The results suggest a mirror symmetry of SARS and SARS-CoV-2 spike proteins. The results show thatSARS-CoV-2 space is variable and has a distinct topology. In conclusion, surface proteins grant virion variability and symmetry in interactions with a potential complementary target (protein, antibody, ligand). The mirror symmetry of dihedral angle clusters determines a high specificity of the receptor space.
Well-M$^3$N: A Maximum-Margin Approach to Unsupervised Structured Prediction

Unsupervised structured prediction is of fundamental importance for the clustering and classification of unannotated structured data. To date, its most common approach still relies on the use of structural probabilistic models and the expectation-maximization (EM) algorithm. Conversely, structural maximum-margin approaches, despite their extensive success in supervised and semi-supervised classification, have not raised equivalent attention in the unsupervised case. For this reason, in this paper, we propose a novel approach that extends the maximum-margin Markov networks (M<inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula>N) to an unsupervised training framework. The main contributions of our extension are new formulations for the feature map and loss function of M<inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula>N that decouple the labels from the measurements and support multiple ground-truth training. Experiments on two challenging segmentation datasets have achieved competitive accuracy and generalization compared to other unsupervised algorithms such as <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-means, EM and unsupervised structural SVM, and comparable performance to a contemporary deep learning-based approach.
BAT6026, a novel anti-OX40 antibody with enhanced antibody dependent cellular cytotoxicity effect for cancer immunotherapy

OX40 (CD134), a member of the TNF receptor superfamily, is a widely studied costimulatory immune checkpoint. Several OX40 agonistic antibodies are in the clinical stage for cancer treatment, among which PF-04518600 is the leader and currently in phase II trial. It has been recognized that one potential mode of action for anti-OX40 antibodies is the deletion of intratumoral Tregs. Thus, a novel human anti-OX40 antibody, BAT6026, was generated with enhanced antibody dependent cellular cytotoxicity (ADCC) via fucose deletion to strengthen its Treg depletion activity. This characteristic of BAT6026 differentiates it from other previously reported anti-OX40 antibodies in the field of tumor therapy. The affinity of BT6026 to OX40 was 0.28nM, approximately 8 times stronger than that of PF-04518600. BAT6026 effectively competed for the binding of ligand OX40L to OX40, whereas PF-04518600 only partially competed. Moreover, compared to PF-04518600, BAT6026 activated T cells more effectively when clustered by FcγRs engagement and stimulated SEB-pretreated PBMCs to secrete IL-2 cytokines in vitro. In addition, BAT6026 demonstrated stronger anti-tumor activity than PF-04518600 in an OX40-humanized mouse MC38 tumor model. BAT6026 also showed a significantly synergistic effect on tumor inhibition when combined treatment with PD-1 antibody. Analysis of tumor-infiltrating T cells revealed that BAT6026 treatment significantly reduced Treg cells and increased CD8+ T cells in tumor. Preclinical safety assessment in non-human primates demonstrated a good safety profile for BAT6026. Together these data warrant further development of BAT6026 into clinical trials for patients with cancer.
Ground-Based Hyperspectral Image Surveillance System for Explosive Detection: Methods, Experiments, and Comparisons

Explosive detection is crucial for public safety and confidence. Among various solutions for this purpose, hyperspectral imaging differs from its alternatives with its detection capability from standoff distances. However, the state-of-the-art for such a technology is still significantly missing a complete technical and experimental framework for surveillance applications. In this article, an end-to-end technical framework, which involves capturing, preprocessing, reflectance conversion, target detection, and performance evaluation stages, is proposed to reveal the potential of a ground-based hyperspectral image (HSI) surveillance system for the detection of explosive traces. The proposed framework utilizes a short-wave infrared region (0.9–1.7 μm), which covers the distinctive absorption characteristics of different explosives. Three classes of detection methods, namely index, signature, and learning-based methods are adapted to the proposed surveillance system. Their performances are compared over various experiments, which are specifically designed for granular and sprayed residues, fingerprint residues, and explosive traces on vehicles. The experiments reveal that the best method in terms of precision and recall performances is hybrid structure detector, which effectively combines signature-based detection with unmixing. While deep-learning-based methods have also achieved satisfactory precision values, their low recall values for the moment have comparatively limited their usage for the high-risk cases. Although one of the main reasons for the current performances of deep-learning methods is less data for learning, these performances for HSIs can be increased with more data in the future as in other image applications.
Surface heat loads on the ITER divertor vertical targets

The heating of tungsten monoblocks at the ITER divertor vertical targets is calculated using the heat flux predicted by three-dimensional ion orbit modelling. The monoblocks are beveled to a depth of 0.5 mm in the toroidal direction to provide magnetic shadowing of the poloidal leading edges within the range of specified assembly tolerances, but this increases the magnetic field incidence angle resulting in a reduction of toroidal wetted fraction and concentration of the local heat flux to the unshadowed surfaces. This shaping solution successfully protects the leading edges from inter-ELM heat loads, but at the expense of (1) temperatures on the main loaded surface that could exceed the tungsten recrystallization temperature in the nominal partially detached regime, and (2) melting and loss of margin against critical heat flux during transient loss of detachment control. During ELMs, the risk of monoblock edge melting is found to be greater than the risk of full surface melting on the plasma-wetted zone. Full surface and edge melting will be triggered by uncontrolled ELMs in the burning plasma phase of ITER operation if current models of the likely ELM ion impact energies at the divertor targets are correct. During uncontrolled ELMs in pre-nuclear deuterium or helium plasmas at half the nominal plasma current and magnetic field, full surface melting should be avoided, but edge melting is predicted.
Insight into the melt processed Polylimonene oxide/Polylactic acid blends

In this work, the polymerization of Limonene Oxide (LO) has been optimized at room temperature with two different aluminium-based catalysts [AlMeX{2,6-(CHPh2)2-4-tBu-C6H2O}] (X = Me (1), Cl (2) ). A fully.
The amplitude of low-frequency fluctuation characteristics in depressed adolescents with suicide attempts: a resting-state fMRI study

Background The amplitude of low-frequency fluctuation (ALFF) is a measure of spontaneous brain activity derived from resting-state functional magnetic resonance imaging (rs-fMRI). Previous research has suggested that abnormal ALFF values may be associated with major depressive disorder (MDD) and suicide attempts in adolescents. In this study, our aim was to investigate the differences in ALFF values between adolescent MDD patients with and without a history of suicide attempts, and to explore the potential utility of ALFF as a neuroimaging biomarker for aiding in the diagnosis and prediction of suicide attempts in this population. Methods The study included 34 adolescent depression patients with suicide attempts (SU group), 43 depression patients without suicide attempts (NSU group), and 36 healthy controls (HC group). Depression was diagnosed using a threshold score greater than 17 on the Hamilton Depression Rating Scale (HDRS). The rs-fMRI was employed to calculate zALFF values and compare differences among the groups. Associations between zALFF values in specific brain regions and clinical variables such as emotion regulation difficulties were explored using Pearson partial correlation analysis. Receiver-Operating Characteristics (ROC) analysis assessed the ability of mean zALFF values to differentiate between SU and NSU groups. Results Significant differences in zALFF values were observed in the left and right inferior temporal gyrus (l-ITG, r-ITG) and right fusiform gyrus (r-FG) among the three groups (GRF corrected). Both SU and NSU groups exhibited increased zALFF values in the inferior temporal gyrus compared to the HC group. Furthermore, the SU group showed significantly higher zALFF values in the l-ITG and r-FG compared to both the NSU group and the HC group. Partial correlation analysis revealed a negative correlation between zALFF values in the left superior and middle frontal gyrus (l-SFG, l-MFG) and the degree of emotional dysregulation in the SU group (R = −0.496, p = 0.003; R = −0.484, p = 0.005). Combining zALFF values from the l-ITG and r-FG achieved successful discrimination between depressed adolescents with and without suicide attempts (AUC = 0.855) with high sensitivity (86%) and specificity (71%). Conclusion Depressed adolescents with suicidal behavior exhibit unique neural activity patterns in the inferior temporal gyrus and fusiform gyrus. These findings highlight the potential utility of these specific brain regions as biomarkers for identifying suicide risk in depressed adolescents. Furthermore, associations between emotion dysregulation and activity in their frontal gyrus regions were observed. These findings provide preliminary yet pertinent insights into the pathophysiology of suicide in depressed adolescents.
Household Contact Tuberculosis Screening Adherence and Associated Factors Among Pulmonary Tuberculosis Patients on Follow-Up at Health Facilities in Shashamane Town, Southeast Ethiopia

Background The greatest risk of getting tuberculosis (TB) infection is contact with patients who have pulmonary tuberculosis (PTB). The World Health Organization (WHO) strongly recommends tuberculosis screening for all household contacts of PTB patients. However, there is no information on household contact screening adherence among PTB patients in Shashamane town. Methods A facility-based mixed-method cross-sectional study was conducted from July 1 to November 30, 2021 among consecutively selected 392 PTB patients and 23 purposely selected key informants. Data were collected using a pre-tested interviewer administered questionnaire and leading questions. Data analysis was made using SPSS version 25 and in-depth interview information was analyzed based on thematic areas. Bivariable followed by multivariable logistic regression with 95% CI were conducted. P-value<0.05 was considered to identify statistically significant factors. Results The overall adherence to household contact screening (HHCS) was 44.4% (95% CI: 39.3, 49.1). Having under fifteen years of contact (AOR=2.386, 95% CI: 1.44, 3.96), diploma and above education status (AOR=3.43, 95% CI: 1.286, 9.15), good knowledge (AOR=2.999, 95% CI: 1.79, 5.03), favorable attitude (AOR=2.409, 95% CI: 1.45, 4.02), getting health education (AOR=3.287, 95% CI: 1.92, 5.63) and smear positive type of PTB (AOR=2.156, 95% CI: 1.28, 3.62) were factors significantly associated with HHCS adherence. Workload, facility readiness and care provide commitments were also identified from qualitative data. Conclusion and Recommendation HHCS adherence in our study was sub-optimal referenced to WHO and national recommendations that all household contact should be screened. Having age less than fifteen years contact, education status, knowledge, attitude, receiving health education and type of pulmonary tuberculosis were factors associated with adherence. We recommend increasing community awareness of TB, providing health education TB patients and their families, strengthening positive attitudes toward HHC screening and strengthening the commitment of health professionals to screen for HHCs.
Sustainable Consumption and the Comprehensive Economic Well-Being of American Households

Abstract: This paper develops a comprehensive measure of household economic well-being. The “sustainable consumption” concept accounts for income, assets, debt, transfer payments, and asset returns to estimate a consumption path that balances resources with expenditure over a household’s lifetime. Calculating sustainable consumption using Panel Study of Income Dynamics data demonstrates that it acts as an anchor for actual household spending. Results show that following a period of rapid growth from the mid-1980s to the early 2000s, sustainable consumption stagnated on average. In the aftermath of the Great Recession, the decline in sustainable consumption exceeded the fall in actual consumption due in part to a decline in real asset returns. Decomposing sustainable consumption reveals the relative importance of different household resources in determining well-being and how these factors evolve over time— insights that would be missed when resources such as income or wealth are considered separately. Taxable income supports the majority of sustainable consumption; however, as a share of households’ lifetime resources, taxable income has decreased on average while the Social Security share has grown.
On positivity and boundedness of solutions of nonlinearstochastic difference equations

Consider nonlinear stochastic difference equations $X(n+1) = X(n)+hf(X(n))+\sqrthg(X(n))\xi_{n+1},$ $n \in \N,$ $X(0) =$ ς $\in \mathbb{R},$ (1) where $\{\xi_n\}_{n\in \N}$ are independent $fr{N} (0,1)$-distributed random variables, $h>0$, can be viewed as a discretization of Ito stochastic differential equations (SDEs). We discuss the following. If, for all $t\ge 0$, the solution $Y(t)$ of the corresponding SDE is positive, or $Y(t) \in [0,K]$ for some $K>0$, does the solution $X(n)$ of related discretization (1) possess the same properties with large probability? In general, the answer is no. However in many cases we are able to discretize the SDE related to (1) over a compact interval $[0,T]$ in such a way that an adequate qualitative behavior is observed with an arbitrarily high probability.
On solutions arising from radial spatial dynamics of some semilinear elliptic equations

We consider the semilinear elliptic equation $$\Delta u+f(x,u)=0, $$ where \(x\in\mathbb{R}^N\setminus\{0\}\), \(N\geq 2,\) and \(f \) satisfies certain smoothness and structural assumptions. We construct solutions of the form \(u(r,\phi)=r^{(2-N)/2} \tilde{u}(\log r,\phi)\), where \(r=|x|>0|0\), \(\phi\in\mathbb{S}^{N-1}\), and \(\tilde{u}\) is quasiperiodic in its first argument with two nonresonant frequencies. These solutions are found using some recent developments in the theory of spatial dynamics, in which the radial variable r takes the role of time, combined with classical results from dynamical systems and the KAM theory. For more information see https://ejde.math.txstate.edu/conf-proc/26/v1/abstr.html