Miracle-dz/UniFAR-FTUs huggingface dataset:
Original article Effect of antimicrobial agents and dough conditioners on the shelf-life extension and quality of flat bread, as determined by near-infrared spectroscopy

Summary Middle Eastern Countries are experiencing the emergence of high volume production and retail marketing over traditional unit baking and retailing. This phenomenon has revealed a shortcoming in quality issues in Arabic flat bread (AFB) manufacture. Therefore, shelf-life extension and quality improvement are in demand to limit economic loss. Five improvers and a control (without any improver) were selected for improving shelf-life and quality of AFB. The improver treatments included: (1) sodium 9 stearoyl-2-lactylate (SSL), (2) monoglycreides (MG), (3) hydroxy propyl methyl cellulose gum (HPMC), (4) high-fructose corn syrup (HFCS), and (5) a combination of all the aforementioned improvers. The texture analysis data indicated that the presence of HFCS may act as a plasticizer through contributing to the longer tearing time. The other treatments exhibited a significant decline in tearing time throughout storage. The NIRS data indicated that after 3 days, the control was less fresh than AFB formulated with HFCS or improver combinations. The sensory evaluation of AFB exhibited that the improver combination significantly improved the quality attributes.
Bioactive potential of endophytic fungi isolated from Phyllanthus niruri L.

Present work describes the isolation and morphological identification of endophytic fungi from Phyllanthus niruri L. including their chemical and bioactivity screening. Two isolated and purified endophytic fungi with the internal strain numbers PNRE and PNLE were taxonomically identified as Colletotrichum sp. and Fusarium sp. , respectively. Preliminary chemical screening of the fungal extracts through thin layer chromatography (TLC) revealed the presence of various components. PNLE showed significant antifungal activity against the fungi Aspergillus niger (24 mm) and Aspergillus flavus (20 mm). Extracts of PNRE and PNLE gave significant cytotoxic activity with LC50 values of 1.08 μg mL -1 and 1.05 μg mL-1, respectively in the brine shrimp lethality bioassay. PNRE extract showed mild scavenging of DPPH with IC50 value of 96.06 μg mL -1 during antioxidant activity screening. Crystal formation was observed in the crude PNRE fungal extract which was purified using methanol/dichloromethane (0-20%) to obtain pure white crystal and the structure was elucidated by NMR (1H NMR and 13C NMR) spectroscopic analysis to be confirmed as ergosterol. Since isolated fungi showed promising antifungal and cytotoxic activities, the crude extract of endophytic fungi of P. niruri could be considered as a promising source for isolation of potential bioactive compounds.
Bioenergetic Controls on Anaerobic Oxidation of Methane (AOM) in Coastal Marine Sediments: A Theoretical Analysis

A kinetic-bioenergetic reaction model for the anaerobic oxidation of methane (AOM) in coastal marine sediments is presented. The model considers a fixed depth interval of sediments below the zone of bioturbation (the window-of-observation), subject to seasonal variations of temperature and inputs of organic substrates and sulfate. It includes (1) nine microbially-mediated reaction pathways involved in CH 4 production/consumption; (2) an explicit representation of five functional microbial groups; and (3) bioenergetic limitations of the microbial metabolic pathways. Fermentation of organic substrates is assumed to produce hydrogen (H 2 ) and acetate (Ac) as key reactive intermediates. Competition among the metabolic pathways is controlled by the relative kinetic efficiencies of the various microbial processes and by bioenergetic constraints. Model results imply that the functional microbial biomasses within the window-of-observation undergo little variation over the year, as a result of kinetic and thermodynamic buffering of the seasonal forcings. Furthermore, the microbial processes proceed at only small fractions of their maximum potential rates. These findings provide a theoretical justification for the approximation of steady-state microbial biomasses, which is frequently used in diagenetic modeling. In contrast, AOM rates show a strong seasonal evolution: AOM only becomes spontaneous in winter, when hydrogenotrophic sulfate reduction (hySR) sufficiently reduces the local H 2 concentration. The bioenergetic limitation of AOM is thus a critical factor modulating this process in seasonally-forced nearshore marine sediments. A global sensitivity analysis based on a 2-level factorial design reveals that AOM rates are most sensitive to the kinetic parameters describing hySR and acetotrophic methanogenesis (acME). The growth and substrate uptake kinetics of AOM are unimportant, whereas the threshold value of ATP energy conservation for AOM is the most sensitive thermodynamic parameter. These results confirm that anaerobic methane oxidizing microorganisms are metabolizing close to their thermodynamic limit, with the energetic balance being controlled by the relative rates of hySR and acME. The removal of Ac by acME primarily allows more sulfate (SO 4 2- ) to be utilized for H 2 oxidation, thereby promoting AOM.
Role of Health Literacy in Health-Related Information-Seeking Behavior Online: Cross-sectional Study

Background The internet has emerged as a main venue of health information delivery and health-related activities. However, few studies have examined how health literacy determines online health-related behavior. Objective The aim of this study was to investigate the current level of health-related information-seeking using the internet and how health literacy, access to technology, and sociodemographic characteristics impact health-related information-seeking behavior. Methods We conducted a cross-sectional study through a survey with Minnesotan adults (N=614) to examine their health literacy, access to technology, and health-related information-seeking internet use. We used multivariate regression analysis to assess the relationship between health-related information-seeking on the internet and health literacy and access to technology, controlling for sociodemographic characteristics. Results Better health literacy (β=.35, SE 0.12) and greater access to technological devices (eg, mobile phone and computer or tablet PC; β=.06, SE 0.19) were both associated with more health-related information-seeking behavior on the internet after adjusting for all other sociodemographic characteristics. Possession of a graduate degree (β=.28, SE 0.07), female gender (β=.15, SE 0.05), poor health (β=.22, SE 0.06), participation in social groups (β=.13, SE 0.05), and having an annual health exam (β=.35, SE 0.12) were all associated with online health-related information-seeking. Conclusions Our findings indicate that access to online health-related information is not uniformly distributed throughout the population, which may exacerbate disparities in health and health care. Research, policy, and practice attention are needed to address the disparities in access to health information as well as to ensure the quality of the information and improve health literacy.
Impact of Motivational Factors on Motivation of Police Force: A Case of Project of Punjab Police

a Police Communication Officer Punjab Safe Cities Authority, Lahore, Pakistan Email: masababbasi87@gmail.com b MS Project Management, Bahria University, Lahore Campus, Pakistan Email:aftabulhaq062@gmail.com c Assistant Professor, Management Studies Department, Bahria University, Islamabad Campus, Pakistan Email: siqbal.buic@bahria.edu. pk d MS Engineering Management, (CASE), UET Taxila, Pakistan Email:anumhussain61@gmail.com
The information content in contingent convertible bond prices

Kreditinstitutter benytter i stigende omfang Contingent Convertible Bonds (CoCo'er) til at opfylde en andel af deres kapitalkrav, hvilket kan gore markedet for CoCo'er interessant i forhold til at udlede information ominstitutternes robusthed. Denne artikel giver en grundig introduktion til CoCo'er - produktet, dets brug i reguleringen, markedet og de specifikke risici, som investorerne star overfor. Til at illustrere, hvilken information der potentielt kan udledes af CoCo'ernes prisniveau og -aendringer, benytter vi modeller, som inkorporerer de fleste af CoCo'ernes karakteristika og indbyggede risici. Modellerne illustrerer, hvordan kompleksiteten i produktet gor det svaert at bruge CoCo'er til at udlede information om udstederens finansielle tilstand, ligesom de mange CoCo-specifikke risici gor det usikkert, om prisen pa CoCo'er udgor en nedre graense for prisen pa egenkapital.
PHYSIOLOGICAL AND IMMUNOLOGICAL RESPONSES OF DUCKS (CAIRINA MOSCHATA DOMESTICA) TO SILYMARIN SUPPLEMENTATION

The current study was conducted to investigate the effect of Silymarin extract on productive performance and the immune-physiological status of growing (Cairina Moschata Domestica) ducklings. A total number of 200 day old ducklings were obtained from a commercial hatchery. Upon arrival they were brooded at 33 0 C for one week and then individually weighed and divided randomly into four treatments of 50 birds in five replicates 10 ducklings each. The first group was served as a control and fed the basal diet without any supplementation, while the second, third and fourth groups were fed the basal diet supplemented with silymarin extract at levels of 0.6, 0.9 or 1.4 g/ kg dietlevels, respectively. The duration of the experiment was 70 days. Results showed that silymarin at 0.6 g/kg diet level positively affected feed conversion ratio, live body weight and body weight gain compared with the control one. Moreover, silymarin recorded highly significant values of globulin fractions (α, β, and γ-globulin), immunoglobulins and thyroid hormone concentration. Additionally, silymarin had significantly improved liver functions markers (ALT, AST and ALP) and serum lipid profile and significantly decreased lipid fractions (cholesterol, low density lipoprotein and triglycerides). In a similar way, silymarin induced significant improvement in the antioxidant status including low malondialdehyde (MDA) concentration and higher total antioxidant capacity, glutathione peroxidase and superoxide dismutase enzymes activity. Additionally, pathogenic bacterial counts were significantly reducedgrowth compared with control group. Conclusion: silymarin extract at 0.6 g/kg diet, may be useful for improving growth performance, antioxidant status, liver functions. Notable linear decrease in the serum lipid profile concentration and pathogenic bacteria were observed in treated growing ducks.
Effect of Financial Leverage on the Value of Firms in Nigeria

The study investigated the effect of f inancial leverage on value of f irms in Nigeria in order to determine whether debt as a componen t of capital structure has posit ive or negative impact on value of f irms in Nigeria. The independent variables for the study are long term debts, medium term debts and short term debts while the dependent variable is the value of the firm. To guide the study three (3) hypotheses were formulated. The first hypothesis sought to find out whether significant relationships exist between long term debts of f irms and the overall value of the organization. The second is to test weather there is significant effect of medium term borrowing on the value of the selected firms and lastly, whether short term debts has effect on the value of Nigeria firms. The Pearson correlation coefficient and Ordinary Least Squares (OLS) regression analysis were used to test the hypoth eses. The study made use of secondary sources of information in carrying out the analysis. From the findings of the study, the results obtained showed that long term debt has a significant posit ive effect on the value of our sampled companies’ performance. Medium term debt and short term debts have significant posit ive influence on our sampled quoted companies’ value and were statist ically significant. This was confirmed by the results of the findings in this research. Posit ive impact implies that increases in the value of one variable tend to be associated with increases in the value of the selected firms. The researcher also found out that the use of leverage enhances the value of the firm. Therefore, it was recommended that f irms should go ahead and finan ce their operations with long term debt, medium term debts and short term debts when the need arises in order to ensure that value is enhanced.
ANTIMICROBIAL AND ANTIOXIDANT ACTIVITIES OF SOME PLANT EXTRACTS

In this study, three plants; rosemary, ginger, and peppermint, were extracted using three solvents; ethanol, methanol and water. A comparison was held between different extracts concerning: chemical composition, efficiency of the extraction method, yield, antimicrobial and antioxidant potentials. Phenolic compounds profile were studied via High Performance Liquid Chromatography (HPLC). Antimicrobial activity of the extracts was examined against: Escherichia coli, Staphylococcus epidermidis, Staphylococcus aureus, Staphylococcus pyogenes, Candida albicans, Klebseilla pneumonia, Bacillus subtilis and Streptococcus. spp using agar well diffusion method. The inhibition zones diameter (IZD) were ranged between 1137 mm. The results showed that ethanol extraction had the highest yield of rosemary and peppermint (19.17 and 17.19%, respectively). While; the lowest was obtained from ginger methanol extracts (12.78%). Rosemary water extract had the highest total phenolic contents (271.66 ± 12.2 μg/mg, while ethanol extract of ginger and peppermint gave 201.31 ± 8.99 and 165 ± 4.74 mg gallic acid equivalent (GAE/g) respectively. Concerning the total flavonoid contents; rosemary methanol extract gained the highest content (123.9 ± 2.99 μg/mg), while in ethanol extracts of ginger and peppermint showed the best results (44.06 ± 0.55, 89.54 ± 2.63 μg/mg, respectively). Antioxidant activity was used as a parameter to evaluate the protective antioxidant ability of examined herbs represented in IC50 (inhibition concentration). Results showed that in rosemary water extract 24. 5μg/ml, while in ginger and peppermint ethanol extracts was 38.98 and 80 μg/ml, respectively. Depending on results stated above, it can be recommend using water for rosemary extraction and ethanol 70% for ginger and peppermint extractions for the best antioxidant and antimicrobial impact.
OXIDATION PROCESS OF Fe NANOPARTICLES

The natural oxidation process is studied in the case of 15 nm iron nanoparticles produced by the thermal decomposition of Fe(CO)5. X-ray diffraction spectra of the nanoparticles at different timescales after exposure to air revealed the instant oxidation of iron and the formation of wustite and magnetite. Wustite mainly occupies the interior of nanoparticles, as evidenced by microscopy, but is slowly transformed to a spinel structure. The shape, the dispersion and the role of surfactant were investigated by conventional microscopy and Fourier Transformed-Infrared (FT-IR) spectroscopy. Magnetic hysteresis loops confirmed the expected variation of magnetic properties till the steady state.
Tree trace reconstruction using subtraces

Abstract Tree trace reconstruction aims to learn the binary node labels of a tree, given independent samples of the tree passed through an appropriately defined deletion channel. In recent work, Davies, Rácz, and Rashtchian [10] used combinatorial methods to show that $\exp({\mathrm{O}} (k \log_{k} n))$ samples suffice to reconstruct a complete k-ary tree with n nodes with high probability. We provide an alternative proof of this result, which allows us to generalize it to a broader class of tree topologies and deletion models. In our proofs we introduce the notion of a subtrace, which enables us to connect with and generalize recent mean-based complex analytic algorithms for string trace reconstruction.
Information Energy Capacity Region for SWIPT Systems Over Rayleigh-Fading Channels

In this paper, we study the fundamental limits of simultaneous information and power transfer over a Rayleigh-fading channel, where the channel input is constrained to peak-power (PP) constraints that vary in each channel use by taking into account high-power amplifier (HPA) nonlinearities. In particular, a three-party communication system is considered, where a transmitter aims simultaneously conveying information to an information receiver and delivering energy to an energy harvesting receiver. For the special case of static PP constraints, we study the information-energy capacity region and the associated input distribution under: a) average-power and PP constraints at the transmitter, b) an HPA nonlinearity at the transmitter, and c) nonlinearity of the energy harvesting circuit at the energy receiver. By extending Smith’s mathematical framework, we show that the optimal input distribution under those constraints is discrete with a finite number of mass points. We show that HPA significantly reduces the information energy capacity region. In addition, we derive a closed-form expression of the capacity-achieving distribution for the low PP regime, where there is no trade-off between information and energy transfer. For the case with time-varying PP constraints, we characterize the optimal input distribution of this channel by using Shannon’s coding scheme. Specifically, we numerically study a particular scenario for the time-varing PP constraints, where the PP constraint probabilistically is either zero or equal to a non-zero constant.
Facial Manipulation Detection Based on the Color Distribution Analysis in Edge Region

In this work, we present a generalized and robust facial manipulation detection method based on color distribution analysis of the vertical region of edge in a manipulated image. Most of the contemporary facial manipulation method involves pixel correction procedures for reducing awkward-ness of pixel value differences along the facial boundary in a synthesized image. For this procedure, there are distinctive differences in the facial boundary between face manipulated image and unforged natural image. Also, in the forged image, there should be distinctive and unnatural features in the gap distribution between facial boundary and background edge region because it tends to damage the natural effect of lighting. We design the neural network for detecting face-manipulated image with these distinctive features in facial boundary and background edge. Our extensive experiments show that our method outperforms other existing face manipulation detection methods on detecting synthesized face image in various datasets regardless of whether it has participated in training.
Milky Way archaeology using RR Lyrae and type II Cepheids

We present a chemo-dynamical study of the Orphan stellar stream using a catalog of RR Lyrae pulsating variable stars for which photometric, astrometric, and spectroscopic data are available. Employing low-resolution spectra from the Sloan Digital Sky Survey (SDSS), we determined line-of-sight velocities for individual exposures and derived the systemic velocities of the RR Lyrae stars. In combination with the stars’ spectroscopic metallicities and Gaia EDR3 astrometry, we investigated the northern part of the Orphan stream. In our probabilistic approach, we found 20 single mode RR Lyrae variables likely associated with the Orphan stream based on their positions, proper motions, and distances. The acquired sample permitted us to expand our search to nonvariable stars in the SDSS dataset, utilizing line-of-sight velocities determined by the SDSS. We found 54 additional nonvariable stars linked to the Orphan stream. The metallicity distribution for the identified red giant branch stars and blue horizontal branch stars is, on average, −2.13 ± 0.05 dex and −1.87 ± 0.14 dex, with dispersions of 0.23 and 0.43 dex, respectively. The metallicity distribution of the RR Lyrae variables peaks at −1.80 ± 0.06 dex and a dispersion of 0.25 dex. Using the collected stellar sample, we investigated a possible link between the ultra-faint dwarf galaxy Grus II and the Orphan stream. Based on their kinematics, we found that both the stream RR Lyrae and Grus II are on a prograde orbit with similar orbital properties, although the large uncertainties on the dynamical properties render an unambiguous claim of connection difficult. At the same time, the chemical analysis strongly weakens the connection between both. We argue that Grus II in combination with the Orphan stream would have to exhibit a strong inverse metallicity gradient, which to date has not been detected in any Local Group system.
Bit Error Tolerance Metrics for Binarized Neural Networks

To reduce the resource demand of neural network (NN) inference systems, it has been proposed to use approximate memory, in which the supply voltage and the timing parameters are tuned trading accuracy with energy consumption and performance. Tuning these parameters aggressively leads to bit errors, which can be tolerated by NNs when bit flips are injected during training. However, bit flip training, which is the state of the art for achieving bit error tolerance, does not scale well; it leads to massive overheads and cannot be applied for high bit error rates (BERs). Alternative methods to achieve bit error tolerance in NNs are needed, but the underlying principles behind the bit error tolerance of NNs have not been reported yet. With this lack of understanding, further progress in the research on NN bit error tolerance will be restrained. In this study, our objective is to investigate the internal changes in the NNs that bit flip training causes, with a focus on binarized NNs (BNNs). To this end, we quantify the properties of bit error tolerant BNNs with two metrics. First, we propose a neuron-level bit error tolerance metric, which calculates the margin between the pre-activation values and batch normalization thresholds. Secondly, to capture the effects of bit error tolerance on the interplay of neurons, we propose an inter-neuron bit error tolerance metric, which measures the importance of each neuron and computes the variance over all importance values. Our experimental results support that these two metrics are strongly related to bit error tolerance.
AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

With the rapid adoption of machine learning (ML), a number of domains now use the approach of fine-tuning models pre-trained on a large corpus of data. However, our experiments show that even fine-tuning on models like BERT can take many hours when using GPUs. While prior work proposes limiting the number of layers that are fine-tuned, e.g., freezing all layers but the last layer, we find that such static approaches lead to reduced accuracy. We propose, AutoFreeze, a system that uses an adaptive approach to choose which layers are trained and show how this can accelerate model fine-tuning while preserving accuracy. We also develop mechanisms to enable efficient caching of intermediate activations which can reduce the forward computation time when performing fine-tuning. Our evaluation on fourNLP tasks shows that AutoFreeze, with caching enabled, can improve fine-tuning performance by up to 2.55x.