Miracle-dz/UniFAR-FTUs huggingface dataset:
Ethnopharmacological and Biotechnological Significance of Vitex

Vitex (Verbenaceae) is a large genus that has a plethora of ethnopharmacological uses. The various species of Vitex have been used to treat a range of human ailments, particularly related to insects, fungi, bacteria, snakes and poisonous spiders and diseases associated with menstruation and gynaecological problems. Several secondary metabolites like flavonoids, iridoid glycosides, terpenoids and labdane diterpenes have been reported in different species of Vitex. Vitex trifolia and Vitex negundo can be propagated vegetatively for cultivation on desecrated lands to produce huge biomass for commercial applications. This review emphasizes the phytochemical and ethnobotanical knowledge on some species of Vitex to highlight their traditional and modern usage.
A confirmatory factor analytic study of an authentic leadership measure in Nigeria

Orientation: Authentic leadership has been identified as one of the competencies for effective leaders. Research purpose: The primary goal of the present study was to test, on a Nigerian sample, the psychometric properties of the Authentic Leadership Inventory (ALI) developed by Neider and Schriesheim. Motivation for the study: Various instruments have been developed to measure authentic leadership, with the ALI being one of the widely used questionnaires. There is a need to assess the reliability and construct validity of the ALI on a Nigerian sample owing to paucity of studies on its psychometric properties in this setting. Research approach/design and method: A non-probability sample consisting of 213 bank employees working in Nigeria was studied. The ALI was used to measure authentic leadership, and its reliability was evaluated using SPSS, while construct validity was assessed through confirmatory factory analyses in the Linear Structural Relations (LISREL) programme. Main findings: Moderate levels of reliability were found for the subscales of the ALI. Reasonable model fit with the data was found for the first- and second-order as well as the bi-factor and single-factor measurement models through confirmatory factor analyses (CFA). Practical/managerial implications: Although the ALI demonstrated reasonable model fit for the CFA models tested in this study, the reliability coefficients of the relational transparency and internalised moral perspective subscales were below the 0.70 threshold. In addition, the discriminant validity of the self-awareness and the internalised moral perspective subscales was not achieved. Contribution/value-add: The study promotes the use of reliable and valid instruments in Nigeria by confirming the psychometric properties of the ALI.
Deep Learning Based Twitter Users Classification Using Sentiment Analysis

: - Sentiment analysis is essential for social alignment, especially when there are many Twitter users nowadays. In every rational sense, each of the previous works is dependent on old classification systems, for example SVM, Naïve Bayes, etc. Starting from late, fundamental learning techniques have shown promising accuracy in this space about the body of tweets in English. In this article we propose the fundamental assessment that enormous learning structures apply to gather the sense of Twitter information. There are two colossal learning methods with regard to our evaluation: short-term memory (LSTM) and dynamic convolution neural network (DCNN). A preprocessing of certifiable information has been promoted. We also investigate the impact of word management on tweets. The results show that critical learning strategies classified old style structures in all aspects: Naïve Bayes and SVM, with the exception of Maximum entropy.
Mating interactions of the harmful dinoflagellate alexandrium tamarense from UK coastal waters

The Alexandrium tamarense species complex is a group of economically and ecologically important marine dinoflagellates. The complex is comprised of three morphospecies A. tamarense, A. fundyense and A. catenella grouped according to ribosomal DNA or ‘ribotype’. There are five ribotype type groups (I-V) each consisting entirely of toxic or non-toxic isolates. Toxic isolates are associated with harmful algal blooms (HAB’s) due to their ability to produce powerful neurotoxins, which are responsible for outbreaks of paralytic shellfish poisoning in areas of shellfish production. Sexual reproduction in A. tamarense has important implications for the initiation and termination of HAB’s associated with these species. Resistant, long-lived hypnozygotes are formed during blooms through gamete fusion and deposited in sediments. These hypnozygotes provide the source of inoculum of motile vegetative A. tamarense cells in temperate zones during subsequent spring/summer blooms. This study provides further insight into the mating interactions between toxic Group I and non-toxic Group III isolates primarily from UK coastal waters. Study of the effect of temperature on the mating interactions of A. tamarense Group I and Group III in culture showed that temperature had a significant effect on both groups. Co-cultures of compatible Group III isolates showed a significant decrease (p<0.05) in hypnozygote yield at 15°C, compared to 20°C. In contrast the mating compatibility of co-cultures of Group I isolates showed significant increase (p<0.05) at 15°C, compared to 20°C. Similar to other studies, compatible Group I and Group III isolates formed non-viable hybrid hypnozygotes in co-culture. Comparison of the average vigour of inbred Group I crosses and outbred Group I/III crosses suggest that Group I isolates are more likely to out-breed with a compatible Group III isolate. A finding that may have significance in areas where the two groups co-occur. Preliminary data suggesting the presence of both Group I and Group III ribotypes in some isolates has been generated from a nested single cell PCR/qPCR protocol using group specific primers. These data were compared to a dual probe whole cell fluorescent in situ hybridisation (whole cell FISH) assay of isolates. Whole cell FISH showed no dual expression of ribosomal RNA. This suggests that some A. tamarense Group I and Group III isolates may have rDNA pseudogenes corresponding to different ribotypes. If correct this could have implications for the overestimation of A. tamarense group diversity in natural populations when using rDNA sequences for identification.
Hybrid Beamforming in MU-MIMO Using Partial Interfering Beam Feedback

We propose a hybrid beamforming scheme with partial interfering beam feedback for a codebook-based multi-user multiple-input multiple-output (MU-MIMO) system, where users feed back information only about the top-<inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> transmit beams. For the analog part of the precoding, we consider two codebooks, the conventional Discrete Fourier Transform (DFT) codebook with uniform amplitude beamforming vectors and the Taylor codebook with non-uniform amplitude beamforming vectors. For the digital precoding part, the effective channel matrix is approximated and used for zero-forcing (ZF). We also propose a beam pairing algorithm that results in reduced inter-beam interference and simplifies beam and user selection in MU-MIMO. When <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> is equal to the number of beams in the transmit codebook, the proposed scheme includes an existing scheme with full effective channel matrix feedback as a special case. Numerical results show that the proposed hybrid beamforming performs better than an existing hybrid precoding scheme based on channel reconstruction.
Hydration of red cells in α and β thalassemias differs : a useful approach to distinguish between these red cell phenotypes

Differences in the pathobiologic features of alpha and beta thalassemic red cells include differing derangements in the ability of these cells to regulate their volume. To explore differences in cell hydration in these two red cell phenotypes, heterogeneity in hemoglobin concentration of individual red cells was quantitated. Red cells from 91 patients with alpha thalassemia (hemoglobin H disease) and 69 patients with beta thalassemia of the genotype beta-thal zero/Hb E were analyzed. Marked differences between these thalassemias were noted in the heterogeneity of hemoglobin concentration among individual cells. Decreased cell hemoglobin concentration and increased cell hydration were features of alpha-thalassemic blood samples, whereas both decreased and increased cell hemoglobin concentration as a result of cell hydration and dehydration, respectively, were features of beta-thalassemic blood samples. The documented differences in the hemoglobin concentration distributions should prove useful in distinguishing between the two thalassemic phenotypes.
Myocardial Infarction Severity Stages Classification From ECG Signals Using Attentional Recurrent Neural Network

Myocardial infarction (MI) is a lethal heart condition that occurs due to the lack of blood flow to the heart tissues. Based on the time from symptoms onset, it is categorized into three severity stages: early MI (EMI), acute MI (AMI), and chronic MI (CMI). Electrocardiogram (ECG) signals are often used to diagnose MI with pathological changes in its characteristics. In clinical practice, accurate diagnosis and risk-stratification are essential to optimize various treatment strategies, hence clinical outcome. However, most automated methods focus only on identifying MI patients from healthy controls (HC). Therefore, in this paper, we propose a novel multi-lead diagnostic attention-based recurrent neural network (MLDA-RNN) for automated diagnosis of the three MI severity stages from HC subjects. The method systematically processes the 12-lead ECGs to capture the multi-scale temporal dependencies from each ECG leads for improved classification. Specifically, we first employ the RNNs to encode the temporal variations in the 12-lead ECG signals. These encoded vectors are fed to the intra-lead attention module to summarize the within-lead discriminative vectors to obtain lead-attentive representations. Then, the inter-lead attention module aggregates these representative vectors based on their clinical relevance to obtain a high-level feature representation for a reliable diagnosis. Using 12-lead ECGs from the PTBDB and STAFF III datasets, we achieved an overall accuracy of 97.79% without compromising on the class-wise detection rates. With improved performance, the MLDA-RNN also shows promising results for model interpretability as the learned attention weights often correlate with clinicians’ way of diagnosing MI severity stages.
Scattering of waves at the interface of two distinct anisotropic media

The present paper aims to study the reflection/transmission of two-dimensional plane elastic waves (quasi-longitudinal displacement waves) at the interface between a self-reinforced half-space and an orthotropic micropolar elastic solid half-space. Three kinds of coupled elastic waves are reflected in the orthotropic micropolar half-space, and two types of waves are transmitted in the self-reinforced medium. The phase velocities obtained in closed form depend upon the angle of propagation and material parameters. The boundary conditions at the interface of the two media are solved, and reflection/transmission coefficients are obtained using Cramer’s rule. Numerical examples are given, and dependence of the reflection/transmission coefficients on the incident angle has been shown graphically. Also, the comparisons between anisotropic and isotropic cases have been marked distinctly. The obtained results may be utilised for the interpretation and analysis of geophysical data.
Robust Size Estimation of Online Social Networks via Subgraph Sampling

Estimating the number of nodes in a large-scale online social network is a fundamental problem in the field of network science. However, it is observed that the performance of traditional RW (Random Walk)-based network size estimators is not stable enough. The relative error of estimated network size can be extremely high for social networks with high skewness of degree distribution, even when the sampling rate is over 50%. In this paper, we propose a robust network size estimation algorithm called Graser, which significantly improves the robustness of size estimation on different types of online social networks. To understand the problem, we first conduct an in-depth study to examine influential factors that lead to inaccuracy of traditional RW-based estimators. Our study identifies a few key factors (e.g., degree distribution) closely related to the inaccuracy of size estimation. Next, we design an efficient network size estimator called Graser, which can iteratively reduce the estimation error by subgraph sampling. We also perform theoretical analysis on the performance of Graser, and prove that our algorithm can guarantee to achieve a relative error that is much smaller than that of traditional RW-based estimators. Finally, we conduct extensive experiments using real datasets to evaluate the performance of our proposed algorithm and the results show that Graser performs much better than traditional RW-based estimators on different types of social networks, and can reduce the relative error of size estimation significantly even with an extremely low sampling rate.
Selection for growth and maternal ability impacts simulation on the reproductive efficiency in a Nellore herd.

Universidade do Estado de Mato Grosso, Departamento d Z otecnia, Pontes e Lacerda, Mato Grosso, Brasi l. Embrapa Cerrados, Departamento de Zootecnia, Planal tina, Distrito Federal, Brasil. Universidade Federal de Goiás, Departamento de Zoot ecnia, Jataí, Goiás, Brasil. Universidade Federal de Goiás, Departamento de Zoot ecnia, Goiânia, Goiás, Brasil. Universidade da California, Departamento de Zootecn ia, Davis, California, EUA. Meat Animal Research Center, Departamento de Zootec nia, Clay Center, Nebrasca, EUA. * Endereço para correspondência: edsonjr@unemat.br
ANTIOXIDANT ACTIVITY TEST OF FRACTIONS FROM STAR FRUIT LEAVES (AVERRHOA CARAMBOLA L.) FROM THREE REGIONS IN WEST JAVA

Objectives: Previous in vitro research showed that ethyl acetate fractions of star fruit leaves exhibit strong antioxidant activities toward 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical (IC50 = 90 μg/ml). This study’s aim was to evaluate antioxidant activity of fractions from leaf extracts from star fruitsourced from three different regions in Indonesia (Depok, Sukabumi, and Subang) and, for the most active fraction (that with the highest antioxidantactivity), determine whether there was any correlation with phenolic and flavonoid content.Methods: Liquid–liquid partitioning, fractions were evaluated for in vitro antioxidant activity using DPPH radical scavenging and ferric reducingability of plasma (FRAP) assay.Results: The ethyl acetate fraction from the Subang region exhibited the strongest radical scavenging activity with both the DPPH assay (IC50 = 96 μg/ml)and the FRAP assay (FeEAC value = 1405 μmol/g). Conclusion: Ethyl acetate fractions from star fruit leaves could be used as natural antioxidants. No correlation was found between antioxidant activityand phenolic or flavonoid content.
The human papillomavirus type 16 E7 (HPV-16 E7) oncoprotein and the host cell DNA damage response

High-risk human papillomaviruses (HPVs), such as HPV-16, are the etiological agents of squamous cell carcinomas (SCCs) of the anogenital tract and a subset of oropharyngeal cancers. High-risk HPVs encode two oncoproteins, E6 and E7, which promote unscheduled host cell proliferation by targeting the p53 and pRB tumor suppressor proteins, respectively. HPV-16 E7 has been shown to stimulate structural chromosomal instability and DNA breakage. These findings raise several important questions. First, how does HPV-16 E7 induce DNA damage? Second, what are the precise consequences of HPV-16 E7-induced DNA damage for host cell genomic integrity, and lastly, how do HPV-16 E7-expressing cells maintain proliferation despite activated DNA damage checkpoints? Here, we show that HPV-16 E7 activates the Fanconi Anemia (FA) pathway, a branch of the host cell DNA damage response that primarily responds to stalled DNA replication forks. Importantly, we show that HPV-16 E7 expression in FA-deficient cells accelerates the formation of structural chromosomal alterations, which may help to explain the heightened susceptibility of FA patients to HPV-associated tumors. However, we also provide evidence that HPV-16 E7-induced FA pathway activation in FA-proficient cells may contribute to evasion of anti-proliferative host cell barriers by promoting alternative lengthening of telomeres (ALT). Finally, we demonstrate that HPV-16 E7 circumvents DNA damage checkpoint control and promotes aberrant mitotic entry by increasing the proteolytic turnover of claspin, which plays a role in the ATR/CHK1-mediated replication stress response. Collectively, our results underscore that HPV-16 E7 interferes with host cell genome integrity by inducing DNA replication stress. The detrimental effects of HPV-16 E7 on the genomic integrity of host cells with a deficient FA pathway support the notion that this DNA damage response pathway is crucial to prevent HPV-16 E7-induced genomic instability and malignant progression. However, we also provide evidence that HPV-16 E7 can exploit the FA pathway to promote cellular immortalization. Future experiments to explore these events for cancer therapy and/or prevention are warranted.
Effect of an Enzyme Blend on the Performance, Diet Metabolizability, Phosphorous Retention, and Bone Mineralization of Broilers Fed Diets Containing Defatted Rice Bran

An experiment was conducted to evaluate the effect of an enzyme blend (EB) on the performance, diet metabolizability, phosphorus (P) retention, and bone mineralization of broilers fed diets containing 10% defatted rice bran (DRB). In total, 432 one- to 38-d-old male Cobb broilers were evaluated according to a completely randomized experimental design in 3 x 2 factorial arrangement. Three diets were tested with two nutrient reductions (NR) in the matrix (standard diet; NR I of 75 kcal/kg ME, 0.1% Ca and 0.1% available P; and NR II of 100 kcal/kg ME, 0.1% Ca and 0.1% available P) with or without the addition of an EB (200 g/t). The coefficients of total tract apparent retention (CTTAR) of the diets and P retention were determined by collecting excreta during two periods (14 to 17 and 28 to 31 d). As expected, birds fed the standard diet had higher BW, BW gain, and G:F compared to birds on the NR diets. The EB did not show any positive effects on CTTAR or on performance; however, birds fed the EB retained 6.58% more P from d 14 to 17 (p ≤ 0.07) and 8.55% from d 28 to 31 (p < 0.05). Tibiotarsus ash percentage also increased by 2.45% (p ≤ 0.06) on d 38. In diets containing 10% DRB, the enzyme blend showed biological activity improving P retention and tibiotarsus mineralization.
Blind Hyperspectral Unmixing using Dual Branch Deep Autoencoder with Orthogonal Sparse Prior

Blind hyperspectral unmixing has become an important task for hyperspectral applications. In this paper, we propose a dual branch autoencoder with a novel sparse prior to simultaneously extract endmembers and abundances from the raw HSI. The dual branch structure extends the linear mixing model by only modeling linear mixtures of the endmembers and treating the bilinear interactions as error. In this way, the proposed model doesn’t require the assumptions of explicit forms of bilinear interactions. The proposed sparse prior, named as orthogonal sparse prior, is based on the key observation that the abundance vector of one pixel is very sparse, there are often no more than two non-zero elements. Different from the conventional norm-based sparse prior which assumes the abundance maps are independent, the orthogonal sparse prior explores the orthogonality between the abundance maps. Extensive experiments on two real datasets show that the proposed method significantly and consistently outperforms the compared state-of-the-art methods, with up to 50% improvements.
Characterization of Salmonellae isolated from different animal and human sources by PCR and resistance trends

Summary Salmonella is one of the most important zoonotic pathogens with many virulence factors playing a major role in its pathogenesis. The aims of this study were to detect spvA, int2 and invC virulence genes of different Salmonella serotypes isolated from various clinical animal and human sources, and to investigate antibiotic resistance patterns among these serotypes. Using a PCR assay, a total of 64 Salmonella isolates were evaluated for the presence of virulence genes. Results revealed that spvA, int2 and invC genes were found in 65.6%, 39.1%, and 76.6% of the Salmonella isolates, respectively. Seven different serotypes were differentiated according to the specific antisera. Antibiotic susceptibility results showed that isolates were susceptible to all tested antibiotics (31.25%), Amikacin (84.4%), Co-Amoxiclav (81.2%), Cefepime (73.4%), Ceftizoxime (76.6%), Ceftriaxone (60.9%), Meropenem (50%), Norfloxacin (82.8%), and Piperacillin (75%). SpvA is a plasmid gene and the int2 gene has been identified on mobile elements. In addition, the chromosomal invC gene is associated with type III secretion systems (TTSS; not present in all Salmonellae). Hence, the detection of these genes could be used to identify the Salmonella genus. High prevalence of int2 and spvA genes was also observed in multidrug resistance Salmonella isolates which might play an important role in the dissemination of antimicrobial resistance in multidrug resistance (MDR) Salmonella isolates.
Analysis of Transit Users’ Response Behavior in Case of Unplanned Service Disruptions

Public transit disruption is becoming more common across different transit services, and can have a destructive influence on the resiliency of the transportation system. Even though transit agencies have various strategies to mitigate the probability of failure in the transit system by conducting preventative actions, some disruptions cannot be avoided because of their either unpredictable or uncontrollable nature. Utilizing recently collected data of transit users in the Chicago Metropolitan Area, the current study aims to analyze how transit users respond to an unplanned service disruption and disclose the factors that affect their behavior. In this study, a random parameter multinomial logit model is employed to consider heterogeneity across observations as well as panel effects. The results of the analysis reveal that a wide range of factors including socio-demographic attributes, personal attitudes, trip-related information, and built environment are significant in passengers’ behavior in case of unplanned transit disruptions. Moreover, the effect of service recovery time on passengers is not the same among all types of disrupted services; rail users are more sensitive to the recovery time as compared with bus users. The findings of this study provide insights for transportation authorities to improve the transit service quality in relation to user satisfaction and transportation resilience. These insights help transit agencies to implement effective recovery strategies.