Miracle-dz/UniFAR-FTUs huggingface dataset:
Variation in Antioxidant Activity and Antioxidant Constituents of Thymus Serpyllum L Grown in Different Climatic Conditions of Uttarakhand Himalayas

In-vitro antioxidant activity of therapeutically important plant Thymus serpyllum L. grown at different altitudes viz. foothill areas, lower Himalayan and higher Himalayan regions were evaluated against various radicals such as DPPH, ABTS and reducing power assays. The antioxidant constituents like total phenols, flavonoids and total tannins were also evaluated in the present study. The results revealed that the alcoholic, as well as the aqueous extracts of the plant, showed significant antioxidant potential against all the radicals. Extracts obtained from different altitude cultivation showed variation in IC50 values. The alcoholic and aqueous extracts prepared from the plants grown at foothill areas (Haldwani) showed the highest DPPH (IC50: ALC-0.566 mg/ml; AQ0.778 mg/ml), ABTS (IC50: ALC0.484 mg/ml; AQ0.533 mg/ml) and reducing power (EC50: ALC0.29 mg/ml; 0.42 mg/ml) activities, followed by high altitude cultivated plants, (Auli), with moderate antioxidant activity. The extracts from mid-altitude cultivation (Pithoragarh) exhibited the least antioxidant potential. The results showed that the amount of total phenolics and flavonoids were significantly correlated to the antioxidant activity. Higher the value of phenolics (TS3: 12.63mg CE/g> TS1: 11.51 mg CE/g> TS2: 10.70 mg CE/g) and flavonoids (TS3: 9.30 mg QE/g> TS1: 9.07mg QE/g> TS2: 6.59mg QE/g) in the extracts, greater was the antioxidant activity. Therefore, T. serpyllum grown in foothill areas was more beneficial in preparing various herbal formulations.
Effects of mobile phone radiation on buccal mucosal cells based on specific absorption rate: a cross sectional study

Background: The usage of mobile phone had been increased drastically which created a major health concern among the people about the radiation emitted from mobile phones. Hence this study was aimed to evaluate the Micronuclei (MN) frequency in exfoliated oral mucosal cells in high and low mobile users based on Specific absorption rate (SAR) value.Methods: The total of 60 subjects were divided into two major groups: low SAR mobile phone users and high SAR mobile phone users. Further, Subjects who use mobile phone for more than 3 hours a week was considered as high talk time users and less than 3 hours a week was low talk time users. The buccal mucosa cells extracted by slightly scraping the oral cavity with a wooden spatula. For staining, Giemsa stain was used. Micronuclei were evaluated in 1000 cells per individual at the microscope.Results: The result show prolonged talk time may interfere with the development of micronuclei in individuals who use mobile phone for more than 3 hours per week rather than high SAR value showing a significant increase in frequency of micronuclei formation.Conclusions: The study showed mobile phone radiation had adverse effects on buccal mucosal cells.
DOES GUIDED IMAGERY IMPROVE HEALTH-RELATED QUALITY OF LIFE IN CANCER PATIENTS? INTEGRATIVE REVIEW

Objective: to analyze research studies that use Guided Imagery as a strategy to improve healthrelated quality of life in cancer patients. Method: an integrative review with assessment of the level of evidence, conducted in February 2020 with publications from January 2009 to February 2020 in Biblioteca Virtual em Saúde, National Library of Medicine, Scopus and Web of Science, with the following descriptors: Imagery, Psychotherapy; Neoplasms and Quality of Life, in English, Spanish and Portuguese. Results: a total of 16 articles were published between 2013 and 2019; 14 in English and 11 randomized clinical trials, including different types of cancer. Guided Imagery was associated with techniques such as breathing exercises and/or progressive muscle relaxation. Positive results for health-related quality of life were observed in 75% of the studies. Conclusion: Guided Imagery presents benefits when used to improve health-related quality of life in cancer patients. This study contributes to the promotion and dissemination of this practice. DESCRIPTORS: Quality of Life; Imagery; Psychotherapy; Neoplasms; Integrative Oncology; MindBody Therapies. dx.doi. org/10.5380/ce.v26i0. 75334 Cogit. Enferm. 2021, v26:e75334 Luana Aparecida Alves da Silva1 Edenice de Oliveira Santana2 Larissa Marcondes2 Mariana Nunes da Silva3 Andressa Blitzkow Scherer3 Namie Okino Sawada4 Luciana Puchalski Kalinke3 1Complexo Hospital de Clínicas, Universidade Federal do Paraná. Curitiba, PR, Brasil. 2Hospital Erasto Gaertner. Curitiba, PR, Brasil. 3Universidade Federal do Paraná. Curitiba, PR, Brasil. 4Universidade Federal de Alfenas. Alfenas, MG, Brasil. ¿LAS IMÁGENES GUIADAS MEJORAN LA CALIDAD DE VIDA RELACIONADA CON LA SALUD DE PACIENTES COM CÁNCER? UNA REVISIÓN INTEGRADORA
Towards Object-generic 6D Pose Estimation

Pose estimation is a basic module in many robot manipulation pipelines. Estimating the pose of objects in the environment can be useful for grasping, motion planning, or manipulation. However, current state-of-the-art methods for pose estimation either rely on large annotated training sets or simulated data. Further, the long training times for these methods prohibit quick interaction with novel objects. To address these issues, we introduce a novel method for zero-shot object pose estimation in clutter. Our approach uses a hypothesis generation and scoring framework, with a focus on learning a scoring function that generalizes to objects not used for training. We achieve zero-shot generalization by rating hypotheses as a function of unordered point diﬀerences. We evaluate our method on challenging datasets with both textured and untextured objects in cluttered scenes and demonstrate that our method signiﬁcantly outperforms previous methods on this task. We also demonstrate how our system can be used by quickly scanning and building a model of a novel object, which can immediately be used by our method for pose estimation. Our work allows users to estimate the pose of novel objects without requiring any retraining.
Survey of gravitational wave memory in intermediate mass ratio binaries

The non-linear gravitational wave (GW) memory effect is a distinct prediction in general relativity. While the effect has been well studied for comparable mass binaries, it has mostly been overlooked for intermediate mass ratio inspirals (IMRIs). We offer a comprehensive analysis of the phenomenology and detectability of memory effects, including contributions from subdominant harmonic modes, in heavy IMRIs consisting of a stellar mass black hole and an intermediate mass black hole. When formed through hierarchical mergers, for example when a GW190521-like remnant captures a stellar mass black hole, IMRI systems have a large total mass, large spin on the primary, and possibly residual eccentricity; features that potentially raise the prospect for memory detection. We compute both the displacement and spin non-linear GW memory from the $m \neq 0$ gravitational waveforms computed within a black hole perturbation theory framework that is partially calibrated to numerical relativity waveforms. We probe the dependence of memory effects on mass ratio, spin, and eccentricity and consider the detectability of a memory signal from IMRIs using current and future GW detectors. We find that (i) while eccentricity introduces additional features in both displacement and spin memory, it does not appreciatively change the prospects of detectability, (ii) including higher modes into the memory computation can increase singal-to-noise (SNR) values by about 7\% in some cases, (iii) the SNR from displacement memory dramatically increases as the spin approaches large, positive values, (iv) spin memory from heavy IMRIs would, however, be difficult to detect with future generation detectors even from highly spinning systems. Our results suggest that hierarchical binary black hole mergers may be a promising source for detecting memory and could favorably impact memory forecasts.
Searching for Efficient Multi-Stage Vision Transformers

Vision Transformer (ViT) demonstrates that Transformer for natural language processing can be applied to computer vision tasks and result in comparable performance to convolutional neural networks (CNN), which have been studied and adopted in computer vision for years. This naturally raises the question of how the performance of ViT can be advanced with design techniques of CNN. To this end, we propose to incorporate two techniques and present ViT-ResNAS, an efficient multi-stage ViT architecture designed with neural architecture search (NAS). First, we propose residual spatial reduction to decrease sequence lengths for deeper layers and utilize a multi-stage architecture. When reducing lengths, we add skip connections to improve performance and stabilize training deeper networks. Second, we propose weight-sharing NAS with multi-architectural sampling. We enlarge a network and utilize its sub-networks to define a search space. A super-network covering all sub-networks is then trained for fast evaluation of their performance. To efficiently train the super-network, we propose to sample and train multiple sub-networks with one forward-backward pass. After that, evolutionary search is performed to discover high-performance network architectures. Experiments on ImageNet demonstrate that ViT-ResNAS achieves better accuracy-MACs and accuracy-throughput trade-offs than the original DeiT and other strong baselines of ViT. Code is available at https://github.com/yilunliao/vit-search.
Growth-enhanced Performance by Pleurotus ostreatus Cultivated on Salon Effluent and Spent Calcium-carbide Amended Substrates

Aims: To investigate the growth response of Pleurotus ostreatus, a wood-rotting fungus, to different growth substrates [Sawdust (SD), dry banana leaves (BL) and a combination of both BL and SD (BLSD)] amended with waste [salon effluent (SE) and spent calcium-carbide (SC)]. Place and duration of study: Department of Plant and Ecological Studies, University of Calabar, Cross River State, Nigeria, between May 2015 and August 2015. Methodology: Amendments were applied to growth substrates at different levels of concentration as follows: 0 ml and 0 g, 5 ml and 5 g, 10 ml and 10 g, 15 ml and 15 g per kg substrate. Mature mushrooms were harvested and assessed on the following parameters; number of fruit bodies, fresh weight, dry weight, length of stipe, girth of stipe, pileus area using conventional method. Results: Number of fruitbodies, fresh weight, dry weight and stipe length increased with increase in concentration of additives. Best performances of these growth parameters were obtained at 15 g/kg and 15 ml/kg concentration. The highest number of fruitbodies (with a peak mean value of 28.42 fruitbodies at 15 g/kg concentration), highest value of fresh weight and dry weight were observed in Original Research Article Oni et al.; AJOB, 12(2): 1-11, 2021; Article no.AJOB. 69868 2 SD. The longest stipe length, largest stipe girth and pileus area were observed in BLSD, though it exhibited least performances in other growth parameters. BLSD amended with salon effluent produced mushrooms with the largest pileus area (with a peak mean value of 53.8 cm 2 at 15ml concentration) compared to the other substrates. Conclusion: This study reveals that all growth parameters of P. ostreatus assessed were positively influenced by all the levels of amendments on the substrates used in this study. Therefore, these wastes could be used to increase the yield of P. ostreatus and possibly remediate sites polluted by these wastes.
Financial Constraints across Pakistani Listed Firms

Using Q investment model to scrutinize investment-cash flow sensitivity, a measure of financial constraint, has been a subject of controversy in literature. By using an alternative model called Error Correction model, this study aims to check the sensitivity between firm’s internal finance and investment level for the case of lower middle income country. Literature has shown that firms’ specific characteristics affect the relation between investment and cash flow of the firms. By considering the unique characteristics of Pakistani corporate sector, this study further target to check whether the investment-cash flow sensitivity differs across size of the firms, group affiliation of the firms and dividend policy of the firms. Our findings indicate that Pakistani listed firms are financially constrained. We find a strong relationship between investment and cash flow for small and non-dividend-paying firms; whereas group-affiliation does not affect investmentcash flow sensitivity of firms.
Anxiety and personality as indicators of academic performance in university foreign language classrooms

The main purpose of this study is to test whether students’ performance in official language tests in the university context is influenced, apart from anxiety, by certain personality traits. A sample of 394 university students in Spain were assessed in language academic performance using the Test of English for International Communication: Listening and Reading (TOEIC L&R), Foreign Language Anxiety using the Spanish version of the Foreign Language Classroom Anxiety Scale (FLCAS), Test Anxiety, by means of the Spanish version of the Test Anxiety Inventory and Personality Traits through the Five Factor Inventory (NEO-FFI). Frequency analyses for the categorical variables, and means and standard deviations for continuous variables were calculated, and a forward stepwise regression model was used to assess the independent variables that contributed significantly to the variance in the score on the academic performance. Foreign Language Classroom Anxiety (FLCA) correlated most significantly with student foreign language academic performance, followed by the Neuroticism dimension, Test Anxiety and Extraversion. These results show that anxiety can still be considered the best indicator to predict language academic performance and that personality traits do play a relevant part in the foreign language learning process in the university context.
Python Crypto Misuses in the Wild

Background: Previous studies have shown that up to 99.59 % of the Java apps using crypto APIs misuse the API at least once. However, these studies have been conducted on Java and C, while empirical studies for other languages are missing. For example, a controlled user study with crypto tasks in Python has shown that 68.5 % of the professional developers write a secure solution for a crypto task. Aims: To understand if this observation holds for real-world code, we conducted a study of crypto misuses in Python. Method: We developed a static analysis tool that covers common misuses of 5 different Python crypto APIs. With this analysis, we analyzed 895 popular Python projects from GitHub and 51 MicroPython projects for embedded devices. Further, we compared our results with the findings of previous studies. Results: Our analysis reveals that 52.26 % of the Python projects have at least one misuse. Further, some Python crypto libraries' API design helps developers from misusing crypto functions, which were much more common in studies conducted with Java and C code. Conclusion: We conclude that we can see a positive impact of the good API design on crypto misuses for Python applications. Further, our analysis of MicroPython projects reveals the importance of hybrid analyses.
Blowup algebras of determinantal ideals in prime characteristic

We study when blowup algebras are $F$-split or strongly $F$-regular. Our main focus is on algebras given by symbolic and ordinary powers of ideals of minors of a generic matrix, a symmetric matrix, and a Hankel matrix. We also study ideals of Pfaffians of a skew-symmetric matrix. We use these results to obtain bounds on the degrees of the defining equations for these algebras. We also prove that the limit of the normalized regularity of the symbolic powers of these ideals exists and that their depth stabilizes. Finally, we show that, for determinantal ideals, there exists a monomial order for which taking initial ideals commutes with taking symbolic powers. To obtain these results we develop the notion of $F$-split filtrations and symbolic $F$-split ideals.
On the Chromatic Number in the Stochastic Block Model

We prove a generalisation of Bollobás' classical result on the asymptotics of the chromatic number of the binomial random graph to the stochastic block model. In addition, by allowing the number of blocks to grow, we determine the chromatic number in the Chung-Lu model. Our approach is based on the estimates for the weighted independence number, where weights are specifically designed to encapsulate inhomogeneities of the random graph.
Point-of-Interest Type Prediction using Text and Images

Point-of-interest (POI) type prediction is the task of inferring the type of a place from where a social media post was shared. Inferring a POI’s type is useful for studies in computational social science including sociolinguistics, geosemiotics, and cultural geography, and has applications in geosocial networking technologies such as recommendation and visualization systems. Prior efforts in POI type prediction focus solely on text, without taking visual information into account. However in reality, the variety of modalities, as well as their semiotic relationships with one another, shape communication and interactions in social media. This paper presents a study on POI type prediction using multimodal information from text and images available at posting time. For that purpose, we enrich a currently available data set for POI type prediction with the images that accompany the text messages. Our proposed method extracts relevant information from each modality to effectively capture interactions between text and image achieving a macro F1 of 47.21 across 8 categories significantly outperforming the state-of-the-art method for POI type prediction based on text-only methods. Finally, we provide a detailed analysis to shed light on cross-modal interactions and the limitations of our best performing model.
Body Mass Index and HbA1c Are Associated with Renal and Hepatic Function

Hypertension and diabetes may have implications for damage to other organs such as the kidneys and liver which are evaluated by serum creatinine and ALT, respectively. This study aims to delineate the association between body mass index and hbA1c with renal and hepatic function, respectively. This is a cross-sectional study involving 32 subjects. The research subjects consisted of diabetics and hypertension who were registered in the Muhammadiyah Primary Health Care, Kebanaran, Purwokerto. It was found that in diabetics, there were significant results between serum creatinine and HbA1c values (p <0.01, r = 0.855). Systolic blood pressure was correlated with body mass index (BMI) (p <0.01, r = 0.649). In patients with hypertension, serum creatinine was correlated with the length of time a person has hypertension (p <0.01, r = 0.475). Meanwhile, the ALT value was correlated with body mass index (p <0.05, r = 0.422) and waist circumference (p <0.001, r = 0.528). We found that a decreased HbA1c levels significantly reduces serum creatinine levels so it may also reduce kidney damage. A decrease in the value of BMI and waist circumference significantly reduces ALT enzyme levels which may have the potential for reducing liver damage.
TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks

With the increasing reliance on automated decision making, the issue of algorithmic fairness has gained increasing importance. In this paper, we propose a Generative Adversarial Network for tabular data generation. The model includes two phases of training. In the first phase, the model is trained to accurately generate synthetic data similar to the reference dataset. In the second phase we modify the value function to add fairness constraint, and continue training the network to generate data that is both accurate and fair. We test our results in both cases of unconstrained, and constrained fair data generation. We show that using a fairly simple architecture and applying quantile transformation of numerical attributes the model achieves promising performance. In the unconstrained case, i.e., when the model is only trained in the first phase and is only meant to generate accurate data following the same joint probability distribution of the real data, the results show that the model beats the state-of-the-art GANs proposed in the literature to produce synthetic tabular data. Furthermore, in the constrained case in which the first phase of training is followed by the second phase, we train the network and test it on four datasets studied in the fairness literature and compare our results with another state-of-the-art pre-processing method, and present the promising results that it achieves. Comparing to other studies utilizing GANs for fair data generation, our model is comparably more stable by using only one critic, and also by avoiding major problems of original GAN model, such as mode-dropping and non-convergence.
Influence of an external electric field on the energy dissipation at the initial stage of laser ablation

Abstract. A density-dependent two-temperature model is applied to describe laser excitation and the following relaxation processes of silicon in an external electric field. Two approaches on how to describe the effects of the external electric field are presented. The first approach avoids the buildup of internal electric fields due to charge separation by assuming ambipolar diffusion and adds an additional carrier-pair current. In the second approach, electrons and holes are treated separately to account for charge separation and the resulting shielding of the external electric field inside the material. The two approaches are compared to experimental results. Both the first approach and the experimental results show similar tendencies for optimization of laser ablation in the external electric field.
ALUMINUM BASED COMPOSITES OBTAINED BY FSP (REVIEW)

The composites based on aluminum alloys obtained by friction stir processing (FSP) combine the advantages of lightweight aluminum composites with the well-refined structure obtained by deformation in plastic state. When reinforcing elements in the form of powders or nanoplates are introduced in the process, of mixing they are evenly distributed in the processes zone, which acquires a fine-grained structure. The study examines specific results in the use of various tools and materials, as well as some basic parameters of the process in terms of surface smoothness, defects and some performance characteristics of the tested samples, such as strength, ductility, hardness and corrosion resistance.