Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of the Reverberations Caused by Predominant Air Pollutants on Urban Vegetation: A Multi-Site Study in Varanasi Located in Indo-Gangetic Plains

Plant responses to air pollution have been extensively studied in urban environments. Nevertheless, detailed and holistic studies assessing their retaliation to air contaminants are still limited. The present study evaluates the effect of criteria pollutants (SO2, NO2, PM10 and O3) on the overall biochemistry and resource allocation strategy of plants in order to categorize the dominant roadside species (Mangifera indica, Psidium guajava, Ficus religiosa, Azadirachta indica, Dalbergia sissoo, Cascabela thevetia and Bougainvillea spectabilis) of the Indo-Gangetic Plains (IGP), with different morphologies and habits, into species that are tolerant and sensitive to the prevailing air pollutants. This study was performed at three different land-use sites (industrial, commercial and reference) in Varanasi for two seasons (summer and winter). It was inferred that NO2 and PM10 consistently violated the air quality standards at all the sites. The fifteen assessed parameters reflected significant variations depending upon the site, season and plant species whereupon the enzymatic antioxidants (superoxide dismutase and catalase) and resource utilization parameters (leaf area and leaf dry matter content) were remarkably affected. Based on the studied parameters, it was entrenched that deciduous tree species with compound leaves (D. sissoo > A. indica) were identified as the less sensitive, followed by a shrub (C. thevetia > B. spectabilis), while evergreen species with simple leaves were the most sensitive. It was also substantiated that the morphology of the foliage contributed more toward the differential response of the plants to air pollutants than its habit.
Model selection and model averaging in the presence of missing values

Model averaging has been proposed as an alternative to model selection which is intended to overcome the underestimation of standard errors that is a consequence of model selection. Model selection and model averaging become more complicated in the presence of missing data. Three different model selection approaches (RR, STACK and M-STACK) and model averaging using three model-building strategies (non-overlapping variable sets, inclusive and restrictive strategies) were explored to combine results from multiply-imputed data sets using a Monte Carlo simulation study on some simple linear and generalized linear models. Imputation was carried out using chained equations (via the "norm" method in the R package MICE). The simulation results showed that the STACK method performs better than RR and M-STACK in terms of model selection and prediction, whereas model averaging performs slightly better than STACK in terms of prediction. The inclusive and restrictive strategies perform better in terms of prediction, but non-overlapping variable sets performs better for model selection. STACK and model averaging using all three model-building strategies were proposed to combine the results from a multiply-imputed data set from the Gateshead Millennium Study (GMS). The performance of STACK and model averaging was compared using mean square error of prediction (MSE(P)) in a 10% cross-validation test. The results showed that STACK using an inclusive strategy provided a better prediction than model averaging. This coincides with the results obtained through a mimic simulation study of GMS data. In addition, the inclusive strategy for building imputation and prediction models was better than the non-overlapping variable sets and restrictive strategy. The presence of highly correlated covariates and response is believed to have led to better prediction in this particular context. Model averaging using non-overlapping variable sets performs better only if an auxiliary variable is available. However, STACK using an inclusive strategy performs well when there is no auxiliary variable available. Therefore, it is advisable to use STACK with an inclusive model-building strategy and highly correlated covariates (where available) to make predictions in the presence of missing data. Alternatively, model averaging with non-overlapping variables sets can be used if an auxiliary variable is available.
Factors Associated with the Non-Exacerbator Phenotype of Chronic Obstructive Pulmonary Disease

Background Patients with chronic obstructive pulmonary disease (COPD) and no exacerbations may need less maintenance treatment and follow-up. The aim was to identify factors associated with a non-exacerbator COPD phenotype. Methods Cross-sectional analysis of 1354 patients from primary and secondary care, with a doctor's diagnosis of COPD. In 2014, data on demographics, exacerbation frequency and symptoms using COPD Assessment Test (CAT) were collected using questionnaires and on spirometry and comorbid conditions by record review. The non-exacerbator phenotype was defined as having reported no exacerbations the previous six months. Multivariable logistic regression with the non-exacerbator phenotype as dependent variable was performed, including stratification and interaction analyses by sex. Results The non-exacerbator phenotype was found in 891 (66%) patients and was independently associated with COPD stage 1 (OR [95% CI] 5.72 [3.30–9.92]), stage 2 (3.42 [2.13–5.51]) and stage 3 (2.38 [1.46–3.88]) compared with stage 4, and with CAT score <10 (3.35 [2.34–4.80]). Chronic bronchitis and underweight were inversely associated with the non-exacerbator phenotype (0.47 [0.28–0.79]) and (0.68 [0.48–0.97]), respectively. The proportion of non-exacerbators was higher among patients with no maintenance treatment or a single bronchodilator. The association of COPD stage 1 compared with stage 4 with the non-exacerbator phenotype was stronger in men (p for interaction 0.048). In women, underweight and obesity were both inversely associated with the non-exacerbator phenotype (p for interaction 0.033 and 0.046 respectively), and in men heart failure was inversely associated with the non-exacerbator phenotype (p for interaction 0.030). Conclusion The non-exacerbator phenotype is common, especially in patients with no maintenance treatment or a single bronchodilator, and is characterized by preserved lung function, low symptom burden, and by absence of chronic bronchitis, underweight and obesity and heart failure. We suggest these patients may need less treatment and follow-up, but that management of comorbid conditions is important to avoid exacerbations.
Doxorubicin–Mediated miR–433 Expression on Exosomes Promotes Bystander Senescence in Multiple Myeloma Cells in a DDR–Independent Manner

The success of senescence-based anticancer therapies relies on their anti-proliferative power and on their ability to trigger anti-tumor immune responses. Indeed, genotoxic drug-induced senescence increases the expression of NK cell-activating ligands on multiple myeloma (MM) cells, boosting NK cell recognition and effector functions. Senescent cells undergo morphological change and context-dependent functional diversification, acquiring the ability to secrete a vast pool of molecules termed the senescence-associated secretory phenotype (SASP), which affects neighboring cells. Recently, exosomes have been recognized as SASP factors, contributing to modulating a variety of cell functions. In particular, evidence suggests a key role for exosomal microRNAs in influencing many hallmarks of cancer. Herein, we demonstrate that doxorubicin treatment of MM cells leads to the enrichment of miR-433 into exosomes, which in turn induces bystander senescence. Our analysis reveals that the establishment of the senescent phenotype on neighboring MM cells is p53- and p21-independent and is related to CDK-6 down-regulation. Notably, miR-433-dependent senescence does not induce the up-regulation of activating ligands on MM cells. Altogether, our findings highlight the possibility of miR-433-enriched exosomes to reinforce doxorubicin-mediated cellular senescence.
The Change in Lambda Invariants for Cyclic p-Extensions of Z(p)-Fields

The well-known Riemann-Hurwitz formula for Riemann surfaces (or the corresponding formulas of the same name for curves/function fields) is used in genus computations. In 1979, Yuji Kida proved a strikingly analogous formula in [Kid80] for pextensions of CM-fields (p an odd prime) which is similarly used to compute Iwasawa λ-invariants. However, the relationship between Kida’s formula and the statement for surfaces is not entirely clear since the proofs are of a very different flavor. Also, there were a few hypotheses for Kida’s result which were not fully satisfying; for example, Kida’s formula requires CM-fields rather than more general number fields and excludes the prime p = 2. Around a year after Kida’s result was published, Kenkichi Iwasawa used Galois cohomology in [Iwa81] to establish a more general formula (about representations) that did not exclude the prime p = 2 nor need the CM-field assumption. Moreover, Kida’s formula follows as a corollary from Iwasawa’s formula. We’ll prove a slight generalization of Iwasawa’s formula and use this to give a new proof of a result of Kida in [Kid79] and Ferrero in [Fer80] which computes λ-invariants in imaginary quadratic extensions for the prime p = 2. We go on to produce special generalizations of Iwasawa’s formula in the case of cyclic p-extensions; these formulas can be realized as statements about Qp-representations, and, in the cases of degree p or p, about p-adic integral representations. One upshot of these formulas is a vanishing criterion for λ-invariants which generalizes a result of Takashi Fukuda et al. in [FKOT97]. Other applications include new congruences and inequalities for λ-invariants that cannot be gleaned from Iwasawa’s formula. Lastly, we give a scheme theoretic approach to produce a general formula for finite, separable morphisms of Dedekind schemes which simultaneously encompasses the classical Riemann-Hurwitz formula and Iwasawa’s formula.
Financial Transparency and Financial Performance of Listed Manufacturing Firms in Nigeria

The study examined the effect of financial transparency on the performance of listed manufacturing firms in Nigeria. To achieve the objective of the study, descriptive research design was adopted. The data were collected through primary source with the aid of wellstructured questionnaire. The sample of the study was 250 respondents purposively selected from five listed manufacturing firms located in South East Nigeria. The data collected from these respondents were analyzed using multiple regression analysis and the following findings were revealed; (i) Ownership structure, board of directors and timeliness of information have positive and significant effect on profitability of listed manufacturing firms in Nigeria, (ii) Ownership structure, board of directors and timeliness of information have positive and significant effect on accountability of listed manufacturing firms in Nigeria and (iii) Ownership structure, board of directors and timeliness of information have positive and significant effect on sales growth of listed manufacturing firms in Nigeria. Based on the findings, the study recommends Since the result showed that financial transparency has positive and significant effect on firm’s profitability, it’s prudent for listed companies to disclose as much information as possible and also ensure that the information disclosed are transparent so as to minimize the level of information asymmetry and consequently stimulate financial performance. The companies can also take the control of financial performance of the company through using high proficiency, experienced and independent managers with the necessary legal power as a potentially powerful mechanism and to be a cause of improvement in the accountability of the company. Keywords: Financial, Transparency, Ownership Structure, Board of Directors and Information.
The effect of the pretreatment systemic immune-inflammatory index and C-reactive protein-to-albumin ratio on prognosis in pediatric patients with IgA vasculitis

Aim: Indices related to blood parameters that indicate inflammation have recently started to be used in determining prognosis for many diseases. Visceral involvement is the most important factor affecting prognosis in immunoglobulin A vasculitis (IgAV). In this study, we sought to explore the value of the systemic immune-inflammation index (SII) and the C-reactive protein-to-albumin ratio (CAR) in predicting visceral involvement in IgAV. Material and Method: Patients diagnosed with IgAV who had gastrointestinal, renal, testicular, or central nervous system involvement were considered patients with visceral involvement. All patients with IgAV were divided into two groups, those with and without visceral involvement. The effect of SII and CAR in predicting visceral involvement was evaluated by logistic regression analysis. Results: We found that in the summertime, the percentage of patients with visceral involvement was significantly higher than those without visceral involvement (p=0.010). The rates of the recurrence of the disease, arthralgia, arthritis, and fever were significantly greater in those with visceral involvement (p=0.032, p
Neuroinflammation, Oxidative Stress, Apoptosis, Microgliosis and Astrogliosis in the Cerebellum of Mice Chronically Exposed to Waterpipe Smoke

Waterpipe smoking (WPS) is prevalent in Asian and Middle Eastern countries and has recently gained worldwide popularity, especially among youth. WPS has potentially harmful chemicals and is associated with a wide range of adverse effects on different organs. However, little is known regarding the impact of WPS inhalation on the brain and especially on the cerebellum. Presently, we aimed at investigating inflammation, oxidative stress and apoptosis as well as microgliosis and astrogliosis in the cerebellum of BALB/C mice chronically (6 months) exposed to WPS compared with air-exposed mice (control). WPS inhalation augmented the concentrations of proinflammatory cytokines tumor necrosis factor, interleukin (IL)-6 and IL-1β in cerebellar homogenates. Likewise, WPS increased oxidative stress markers including 8-isoprostane, thiobarbituric acid reactive substances and superoxide dismutase. In addition, compared with the air-exposed group, WPS caused an increase in the oxidative DNA damage marker, 8-hydroxy-2′-deoxyguanosine, in cerebellar homogenates. Similarly, in comparison with the air group, WPS inhalation elevated the cerebellar homogenate levels of cytochrome C, cleaved caspase-3 and nuclear factor-κB (NF-κB). Immunofluorescence analysis of the cerebellum showed that WPS exposure significantly augmented the number of ionized calcium-binding adaptor molecule 1 and glial fibrillary acidic protein-positive microglia and astroglia, respectively. Taken together, our data show that chronic exposure to WPS is associated with cerebellar inflammation, oxidative stress, apoptosis, microgliosis and astrogliosis. These actions were associated with a mechanism involving NF-κB activation.
Optimal generalized case–cohort sampling design under the additive hazard model

ABSTRACT Generalized case–cohort designs have been proved to be a cost-effective way to enhance effectiveness in large epidemiological cohort. In generalized case–cohort design, we first select a subcohort from the underlying cohort by simple random sampling, and then sample a subset of the failures in the remaining subjects. In this article, we propose the inference procedure for the unknown regression parameters in the additive hazards model and develop an optimal sample size allocations to achieve maximum power at a given budget in generalized case–cohort design. The finite sample performance of the proposed method is evaluated through simulation studies. The proposed method is applied to a real data set from the National Wilm's Tumor Study Group.
Optical fibre pressure sensing using a frequency modulated laser-based signal processing technique

Range resolved interferometry (RRI) applied to the interrogation of an extrinsic Fabry–Perot based pressure sensor in laboratory and wind tunnel environments is presented. A simple, compact sensor head design was fabricated and subsequently characterised using RRI, which was shown to have a sensitivity of 1.627 ×10−3 rad Pa−1 with a noise standard deviation of 9 Pa over a data rate of 1.5 kHz. When installed in a high-lift wing for surface pressure evaluation during wind tunnel testing, the approach outlined here was able to perform as well as a conventionally employed commercial device for relative static pressure measurements.
Benchmarking Neural Network Compression Techniques for Ocular-Based User Authentication on Smartphones

With the unprecedented mobile technology revolution, mobile devices have transcended from being the primary means of communication to an all-in-one platform. Consequently, an increasing number of individuals are accessing online services for e-commerce and banking via smartphones instead of traditional desktop computers. However, smartphones can be easily misplaced, lost, or stolen more often than other computing devices, thereby demanding effective user authentication mechanisms for device unlocking and secured transactions. Ocular biometrics has obtained significant attention from academia and industry because of its accuracy, security, and ease of use in mobile devices. Several studies have demonstrated the efficacy of deep learning models for ocular-based user authentication on smartphones. However, these high-performing models require enormous space and computational complexity due to the millions of parameters and computations involved. These requirements make their deployment on resource-constrained smartphones challenging. To this end, a handful of studies have been proposed for compact-size ocular-based deep-learning models to facilitate on-device deployment. In this paper, we conduct a thorough analysis of the existing neural network compression techniques applied as a standalone and in combination for ocular-based user authentication. Extensive experimental validation is performed on the two latest large-scale ocular biometric datasets collected using smartphones, namely, UFPR and VISOB 2.0 datasets. This study benchmarks the results of advanced compression techniques for further research and development in lightweight models for ocular-based user authentication on smartphones.
Generation and manipulation of entangled photons on silicon chips

Abstract Integrated quantum photonics is now seen as one of the promising approaches to realize scalable quantum information systems. With optical waveguides based on silicon photonics technologies, we can realize quantum optical circuits with a higher degree of integration than with silica waveguides. In addition, thanks to the large nonlinearity observed in silicon nanophotonic waveguides, we can implement active components such as entangled photon sources on a chip. In this paper, we report recent progress in integrated quantum photonic circuits based on silicon photonics. We review our work on correlated and entangled photon-pair sources on silicon chips, using nanoscale silicon waveguides and silicon photonic crystal waveguides. We also describe an on-chip quantum buffer realized using the slow-light effect in a silicon photonic crystal waveguide. As an approach to combine the merits of different waveguide platforms, a hybrid quantum circuit that integrates a silicon-based photon-pair source and a silica-based arrayed waveguide grating is also presented.
Quasi-stationary distributions in semi-Markov processes

Our main concern in this paper is the convergence, as t → ∞, of the quantities i, j ∈ E; where Pij (t) is the transition probability of a semi-Markov process whose state space E is irreducible but not closed (i.e., escape from E is possible), and rj is the probability of eventual escape from E conditional on the initial state being i. The theorems proved here generalize some results of Seneta and Vere-Jones ([8] and [11]) for Markov processes.
Malaria and HIV Co-Infection among Pregnant Women in Africa: Prevalence, Effect on Immunity and Clinical Management: Review

Malaria and HIV are geographically in the tropics and subtropics of the world, including sub-Saharan Africa. Understanding the overlapping effect of both infections, especially among pregnant women, is crucial in managing pregnant women during antenatal care visits, and postpartum babies. It was realized that the prevalence of malaria among HIV-positive pregnant women ranges between 31–61%, while for non-HIV infected pregnant women the prevalence still stands between 10 and 36%. Co-infection is between 0.52 and 56.3%. Even though the rate of mother-to-child transmission of HIV has dropped, MTCT of malaria still remains a problem. MTCT is associated with low birth-weight, anemia, and even immune dysregulation. The adoption of the Option B+ plan has proven to be effective in the fight against the MTCT of HIV. However, malaria in pregnancy still remains a problem. Concurrent administration of both antimalarial drugs and Cotrimozaxole to pregnant women is not recommended, because of the toxic effect of the interaction of both drugs. Nevertheless, studies looking at the effect of the current ART regimens on mothers and their children need to be carried out. Studies looking at exposed children over a longer period of time, to determine their susceptibility to malaria infection and also to monitor their immune response to malaria over time, are needed.
Diagnosing sentinel lymph node metastasis of T1/T2 breast cancer with conventional ultrasound combined with double contrast-enhanced ultrasound: a preliminary study

Background In patients with T1/T2 breast cancer (BC), sentinel lymph node (SLN) status is essential for prognosis and treatment. This study investigated the value of conventional ultrasound combined with double contrast-enhanced ultrasound in diagnosing the metastasis of SLNs in patients with T1/T2 BC. Methods This study employed a prospective design (this diagnostic study was not registered on a clinical trial platform), and the participants formed a convenience series. Based on the inclusion and exclusion criteria, 163 patients with BC who received treatment in the First Affiliated Hospital of Soochow University from July 2017 to December 2021 were included in this study. A total of 165 SLNs from 163 patients with T1/T2 BC were analyzed. All patients underwent percutaneous contrast-enhanced ultrasound (PCEUS) to trace SLNs before the operation. Subsequently, all patients underwent conventional ultrasound and intravenous contrast-enhanced ultrasound (ICEUS) examinations to observe the SLNs. The results of the conventional ultrasound, ICEUS, and PCEUS of the SLNs were analyzed. The associations between the risk of SLN metastasis and imaging features were evaluated via a nomogram based on the pathological results. Results Overall, 54 metastatic SLNs and 111 nonmetastatic SLNs were evaluated. Metastatic SLNs displayed a greater cortical thickness, area ratio, eccentric fatty hilum, and hybrid blood flow on conventional ultrasound compared with nonmetastatic SLNs (P<0.001). According to PCEUS, 75.93% of metastatic SLNs showed heterogeneous enhancement (type II and III), and 73.88% of nonmetastatic SLNs showed homogeneous enhancement (type I; P<0.001). According to ICEUS, heterogeneous enhancement (type B/C, 20.37% vs. 11.71%) and overall enhancement (55.56% vs. 23.42%) were more common in metastatic SLNs than in nonmetastatic SLNs (P<0.001). Logistic regression analysis showed that the cortical thickness and enhancement type of PCEUS were independent predictors of SLN metastasis. Moreover, a nomogram combining these factors showed a high diagnostic ability for SLN metastasis (unadjusted concordance index 0.860, 95% CI: 0.730–0.990; bootstrap-corrected concordance index 0.853). Conclusions The nomogram of cortical thickness and enhancement type of PCEUS could effectively diagnose SLN metastasis in patients with T1/T2 BC.