Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective Effect of Spirulina against Aspartame Induced Oxidative Stress and Molecular Gene Brain

: Spirulina and alpha-lipoic acid have been considered as one of the most effective in antioxidative stress and anti-inflammatory activity. Aspartame (ASP) is one of the most widely used (artificial sweeteners) used in a variety of foods and feeds. This study was conducted to evaluate the possible protective effect of Spirulina and alpha-lipoic acid against aspartame induced oxidative stress and brain damage in rabbits. Forty two white male New-Zealand Rab bits were classified into seven equal groups. Group I: (Control group) received no drugs. Group II: rabbits administered with aspartame (250 mg/kg b. wt/day). Group III: rabbits received alpha- lipoic acid (100 mg/kg b. wt/day). Group IV: rabbits received Spirulina platensis (1500 mg/kg. b. wt/day). Group V: rabbits received aspartame (250 mg /kg b. wt) and treated with alpha- lipoic acid (100 mg/kg b. wt). Group VI: rabbits received aspartame (250 mg mg/kg b.wt) and treated with Spirulina platensis (1500 mg/kg b. wt). Group VII: rabbits received aspartame (250 mg mg/kg b.wt) and treated daily with alpha-lipoic acid (100 mg/kg b. wt) and Spirulina platensis (1500 mg/kg b. wt) for 8 weeks. At the end of experiment brain tissue was isolated and analyzed for determination of L-malondialdehyde (L-MDA), catalase (CAT) and reduced glutathione (GSH) in addition to anti-inflammatory cytokines: interleukin-10 (IL-10), Activator Protein-1 (AP-1), Bax gene expression and DNA damage. The obtained results showed a significant up-regulation of AP-1, Bax gene expression level and a significant down-regulation of IL-10 and marked increase in L-MDA and DNA damage that was indicated by an increase in tail length and tail DNA percent in brain tissue of aspartame treated rab bits. However, brain CAT activity and GSH concentration were significantly decreased when compared with control group. Co-administration of Spirulina and alpha-lipoic acid protected aspartame induced brain damage in rabbits via a significant improvement of all previous parameters and attenuate DNA changes. Conclusively, Spirulina platensis and alpha-lipoic acid exert a protective effect against DNA damage and oxidative stress in aspartame induced brain through free radical scavenging and anti-inflammatory activities as well as regenerating endogenous antioxidants defense sys tem mechanisms.
The energy saving potential of occupancy-based lighting control strategies in open-plan offices: The influence of occupancy patterns

Occupancy-based lighting control strategies have been proven to be effective in diminishing offices’ energy consumption. These strategies have typically worked by controlling lighting at the room level but, recently, lighting systems have begun to be equipped with sensors on a more fine-grained level, enabling lighting control at the desk level. For some office cases, however, the savings gained using this strategy may not outweigh the costs and design efforts compared to room control. This is because, in some offices, individual occupancy patterns are similar, hence the difference in savings between desk and room control would be minimal. This study examined the influence of occupancy pattern variance within an office space on the relative energy savings of control strategies with different control zone sizes. We applied stochastic modeling to estimate the occupancy patterns, as this method can account for uncertainty. To validate our model, simulation results were compared to earlier studies and real measurements, which demonstrated that our simulations provided realistic occupancy patterns. Next, office cases varying in both job-function type distribution and office policy were investigated on energy savings potential to determine the influence of occupancy pattern variance. The relative energy savings potential of the different control strategies differed minimally for the test cases, suggesting that variations in individual occupancy patterns negligibly influence energy savings. In all cases, lighting control at the desk level showed a significantly higher energy savings potential than strategies with lower control zone granularity, suggesting that it is useful to implement occupancy-based lighting at the desk level in all office cases. This strategy should, thus, receive more attention from both researchers and lighting designers.
On the improvement of the dynamic performance of dielectric elastomer actuators for active compression

Dielectric elastomer actuators have been considered for an increasing number of applications due to their desirable characteristics of low weight, high strain outputs and favourable material costs. The present work describes the use of a dielectric elastomer actuator in conjunction with a belt mechanism to apply cyclic active compression. The belt mechanism helps convert the stress relaxation upon the voltage application to the dielectric elastomer actuator to a compressive force. Testing is conducted using multi-layered silicone–based dielectric elastomer actuators. A novel method of dynamically charging dielectric elastomer actuators through manipulating the input signal shape, termed the hold method, is introduced. Using this method, cyclic actuation strain output can be increased by 24% with insignificant change in actuation output curve shape. Furthermore, the effect of pre-stretch ratios on the output force amplitudes is characterized. The optimized hold time parameters obtained through cyclic dielectric elastomer force and strain are utilized for active compression physiological testing and a pressure gradient of 10 mmHg is achieved.
DocTer: documentation-guided fuzzing for testing deep learning API functions

Input constraints are useful for many software development tasks. For example, input constraints of a function enable the generation of valid inputs, i.e., inputs that follow these constraints, to test the function deeper. API functions of deep learning (DL) libraries have DL-specific input constraints, which are described informally in the free-form API documentation. Existing constraint-extraction techniques are ineffective for extracting DL-specific input constraints. To fill this gap, we design and implement a new technique—DocTer—to analyze API documentation to extract DL-specific input constraints for DL API functions. DocTer features a novel algorithm that automatically constructs rules to extract API parameter constraints from syntactic patterns in the form of dependency parse trees of API descriptions. These rules are then applied to a large volume of API documents in popular DL libraries to extract their input parameter constraints. To demonstrate the effectiveness of the extracted constraints, DocTer uses the constraints to enable the automatic generation of valid and invalid inputs to test DL API functions. Our evaluation on three popular DL libraries (TensorFlow, PyTorch, and MXNet) shows that DocTer’s precision in extracting input constraints is 85.4%. DocTer detects 94 bugs from 174 API functions, including one previously unknown security vulnerability that is now documented in the CVE database, while a baseline technique without input constraints detects only 59 bugs. Most (63) of the 94 bugs are previously unknown, 54 of which have been fixed or confirmed by developers after we report them. In addition, DocTer detects 43 inconsistencies in documents, 39 of which are fixed or confirmed.
Radio Scattering Horizons for Galactic and Extragalactic Transients

Radio wave scattering can cause severe reductions in detection sensitivity for surveys of Galactic and extragalactic fast (∼ms duration) transients. While Galactic sources like pulsars undergo scattering in the Milky Way interstellar medium (ISM), extragalactic fast radio bursts (FRBs) can also experience scattering in their host galaxies and other galaxies intervening in their lines of sight. We assess Galactic and extragalactic scattering horizons for fast radio transients using a combination of NE2001 to model the dispersion measure and scattering time (τ) contributed by the Galactic disk, and independently constructed electron density models for the Galactic halo and other galaxies’ ISMs and halos that account for different galaxy morphologies, masses, densities, and strengths of turbulence. For source redshifts 0.5 ≤ z s ≤ 1, an all-sky, isotropic FRB population has simulated values of τ (1 GHz) ranging from ∼1 μs to ∼2 ms (90% confidence, observer frame) that are dominated by host galaxies, although τ can be ≫2 ms at low Galactic latitudes. A population at z s = 5 has 0.01 ≲ τ ≲ 300 ms at 1 GHz (90% confidence), dominated by intervening galaxies. About 20% of these high-redshift FRBs are predicted to have τ > 5 ms at 1 GHz (observer frame), and ≳40% of FRBs between z s ∼ 0.5–5 have τ ≳ 1 ms for ν ≤ 800 MHz. Our scattering predictions may be conservative if scattering from circumsource environments is significant, which is possible under specific conditions. The percentage of FRBs selected against from scattering could also be substantially larger than we predict if circumgalactic turbulence causes more small-scale (≪1 au) density fluctuations than observed from nearby halos.
Out-of-hospital Cardiac Arrest Before and During the COVID-19 Pandemic in the South Bronx

Background: Out-of-hospital cardiac arrest (OHCA) is a major health challenge; the impact of the COVID-19 pandemic on OHCA in the South Bronx is unknown. The aim of this study was to determine differences between return of spontaneous circulation(ROSC), witnessed arrest, bystander CPR and survival to discharge, prior to and during the COVID-19 pandemic to improve ROSC and survival. Methods: Single-center retrospective study of non-traumatic OHCA adult patients admitted to Lincoln Medical Center between 8/2019 to 6/2021, 3/2020 being the first established date of the COVID-19 pandemic in New York City. International Classification of Diseases (ICD) coding was used to identify cardiac arrests and collect information. Statistical analysis was performed using IBM-SPSS. Results: ROSC time pre COVID-19 was 26 minutes, during the COVID-19 pandemic it was 25 minutes 54 seconds. A significant difference in witnessed arrests in the pre COVID-19 period compared to the COVID-19 period (86% vs 55% p = 0.03). Bystander CPR occurred 36% of the time in the pre COVID-19 period contrasting to 19% during. Prior to the COVID-19 pandemic the overall survival to discharge in OHCA ROSC cases was 28.5% comparing to 29% during the pandemic. ROSC was 18 minutes among survivors during the pandemic, compared to 21 minutes in survivors prior to COVID (p = 0.2). Conclusion: There was a non-significant difference in ROSC, bystander CPR and survival to discharge in non-traumatic OHCA prior to and during the COVID-19 pandemic in the South Bronx. There was a significant difference in witnessed vs unwitnessed OHCA prior to and during the COVID-19 pandemic.
Estimating the Within-Person Change in Dental Service Access Measures during the COVID-19 Pandemic in the United States

Background: American adults delay dental care more than any other healthcare service. Unfortunately, the COVID-19 pandemic may have stalled efforts to address dental service delays. Early evidence has suggested substantial declines in dental service visits in the early phase of the pandemic, however our study is among the first to measure within-person changes from 2019 to 2020 and conduct subgroup analyses to examine if changing dental patterns were mediated by exposure to the pandemic, risk of adverse COVID-19 outcomes, or dental insurance. Methods: We analyzed a National Health Interview Survey panel of individuals initially surveyed in 2019, with subsequent follow up in 2020. The outcomes included dental service access measures and the interval of a most recent dental visit. By constructing a probability weighted linear regression model with fixed-effects, we estimated the average within-person change from 2019 to 2020. Robust standard errors were clustered within each respondent. Results: Overall, adults in 2020 were 4.6%-points less likely to visit the dentist compared to 2019 (p < 0.001). Significantly higher declines were found in Northeast/West regions compared to Midwest/South. We find no evidence that declining dental services in 2020 were associated with more chronic diseases, older age, or lack of dental insurance coverage. Adults did not report more financial or non-financial access barriers to dental care in 2020 compared to 2019. Conclusions: The long-term effects of the COVID-19 pandemic on delayed dental care warrants continued monitoring as policymakers aim to mitigate the pandemic's negative consequences on oral health equity.
Validity of Self-testing at Home With Rapid Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Detection by Lateral Flow Immunoassay

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody lateral flow immunoassays (LFIA) can be carried out in the home and have been used as an affordable and practical approach to large-scale antibody prevalence studies. However, assay performance differs from that of high-throughput laboratory-based assays which can be highly sensitive. We explore LFIA performance under field conditions compared to laboratory-based ELISA and assess the potential of LFIAs to identify people who lack functional antibodies following infection or vaccination. Methods: Field evaluation of a self-administered LFIA test (Fortress, NI) among 3758 participants from the REal-time Assessment of Community Transmission-2 (REACT-2) study in England selected based on vaccination history and previous LFIA result to ensure a range of antibody titres. In July 2021, participants performed, at home, a self-administered LFIA on finger-prick blood, reported and submitted a photograph of the result, and provided a self-collected capillary blood sample (Tasso-SST) for serological assessment of IgG antibodies to the spike protein using the Roche Elecsys Anti-SARS-CoV-2 assay. We compared the self-administered and reported LFIA result to the quantitative Roche assay and checked the reading of the LFIA result with an automated image analysis (ALFA). In a subsample of 250 participants, we compared the results to live virus neutralisation. Results: Almost all participants (3593/3758, 95.6%) had been vaccinated or reported prior infection, with most having received one (862, 22.9%) or two (2430, 64.7%) COVID-19 vaccine doses. Overall, 2777/3758 (73.9%) were positive on self-reported LFIA, 2811/3457 (81.3%) positive by LFIA when ALFA-reported, and 3622/3758 (96.4%) positive on Roche anti-S (using the manufacturer reference standard threshold for positivity of 0.8 U ml-1). Live virus neutralisation was detected in 169 of 250 randomly selected samples (67.6%); 133/169 were positive with self-reported LFIA (sensitivity 78.7%; 95% CI 71.8, 84.6), 142/155 (91.6%; 86.1, 95.5) with ALFA, and 169 (100%; 97.8, 100.0) with Roche anti-S. There were 81 samples with no detectable virus neutralisation; 47/81 were negative with self-reported LFIA (specificity 58.0%; 95% CI 46.5, 68.9), 34/75 (45.3%; 33.8, 57.3) with ALFA, and 0/81 (0%; 0.0, 4.5) with Roche anti-S. All 250 samples remained positive with Roche anti-S when the threshold was increased to 1000U ml-1. Conclusions: Self-administered LFIA can provide insights into population patterns of infection and vaccine response, and sensitivity can be improved with automated reading of the result. The LFIA is less sensitive than a quantitative antibody test, but the positivity in LFIA correlates better than the quantitative ELISA with virus neutralisation.
Decentralized Representative Neighbourhood Construction for Machine Learning

This report presents the exploration of the construction of a diverse neighbourhood for each node individually and has the goal to see if a similar convergence speed as D-cliques can be reached. Three algorithms have been implemented and are presented, along with the skew they give: the random topology, the bipartite topology, and a topology created with the SRP matching algorithm. The lowest skew obtained with those topologies equals 0.12 and is given by the random neighbourhood improved by the Swapping technique which is also presented. To compare it to the previous results obtained on topologies using cliques [1], it is the algorithm Greedy swap with fully connected cliques that gives the lowest skew, 0.06. Hence until now, the resulting skew of the construction without cliques is then proven to be higher than the one of construction with cliques. By simulating with the machine learning model with the same parameters as the one used to get the fastest speed of convergence with the Greedy swap algorithm, the quality of results obtained depends on which dataset is used. For a dataset with simple classes, the speed of convergence and the accuracy obtained for topologies without cliques are similar as for topologies with cliques. On the other hand, using a more complicated dataset, results seem to be less good for topologies without cliques. Indeed, the speed of convergence stays quite high for the topology with cliques while the one for the topologies without cliques decreases considerably.
CONFLICT-INDUCED DEFORESTATION DETECTION IN AFRICAN CÔTE D’IVOIRE USING LANDSAT IMAGES AND RANDOM FOREST ALGORITHM: A CASE IN MOUNT PEKO NATIONAL PARK

African forests, especially in Côte d’Ivoire, have been lost during the past three decades. Worldwide, forests are being destroyed to make room for farmland. Deforestation depletes floral resources and fragments habitat. Cocoa growth threatens critical ecological zones, particularly in Côte d’Ivoire. The 2002–2007 conflict impacted Mount Peko National Park (PNMP). This issue has hastened the decline of endangered animal habitats (Colobus and Elephants). The classification approach based on Random Forest (RF) algorithm using the Mean Accuracy Decrease (MDA) has been applied for choosing a variable to select the best predictor variables in the model. A Spectral Index map and time series satellite images of the PNMP from 1985 to 2020 were used to identify land cover changes. RStudio and QGIS 3.4 software have been used to create training data. Among thirteen (13) variables studied, NIR ( Near Infrared), ShortWave Infrared 1 (SWIR 1) and SWIR bands had the increased importance of the variable for the performance of the classification prediction model. The NIR band was the greatest predictor. MDA predicted 75%. User accuracy (UA), Producer accuracy (PA), and Overall accuracy (OA) classifications were 98.75% ± 1.94, 99% ± 1.95, 97% ± 1.93. The park’s dense forest remained unchanged, but nonforest was reforested and 12.22% was turned to forest. During the study period, extensive cocoa plantations were established in formerly forested regions.
POLICY BRIEF POLICY ACTIONS TO SAFEGUARD THE OPERATIONS OF GVCS IN TIMES OF CRISIS AND BEYOND

COVID-19 has spurred calls for the renationalization of value chains to safeguard the supply of essential goods. In this policy brief, we argue that global value chains (GVCs) offer a solution to supply shortages and that the Group of Twenty (G20) must take the lead in safeguarding production in GVCs. Focusing on essential industries such as healthcare and food supply, we propose key policy actions to enhance the robustness of production systems by reducing trade costs and increasing multilateral cooperation.
Characteristics of Fermented Rice Straw with Several Types of Probiotics and Fermentation Time for Cow Feed

Rice straw has great potential as a feed ingredient for cattle, especially when it is difficult to get forage ingredients in the dry season. To get good quality feed from rice straw, it is necessary to use a fermentation process using probiotics. The purpose of this study was to compare the quality of straw fermented using several types of probiotics and the length of the fermentation process. The method that will be used in achieving these goals is the experimental design method. Completely Randomized Design (CRD) factorial pattern consisting of 2 factors, namely: factor I type of probiotic (P) consisting of EM4 (P1), Bio Bali Tani (P2 ), and Rumino bacillus (P3), and factor II the length of fermentation time (T), namely: 1 week (T1), 2 weeks (T2), 3 weeks (T3), and 4 weeks (T4), where each treatment combination was carried out repeated 3 times. The results showed that the type of probiotic had a significant effect (P<0.05) on the quality of fermented straw, where Bio Bali Tani (P2) showed the best results in crude protein content (CP), water content, and crude fiber. While the fermentation time at week 4 was significantly the best crude protein (CP) (P<0.05), but the 1-week fermentation time was significantly the lowest (P<0.05) the quality of fermented straw. The interaction between the types of probiotics and the length of time of fermentation only occurred at the highest crude fiber content at P2T2 (the interaction between the Bio Bali Tani probiotics with a fermentation time of 2 weeks), and the lowest at the interaction P1 with T4. From this research, it can be concluded that the type of probiotic and the longer the fermentation process affect the quality of fermented straw, where the probiotic Bio Bali Tani produces the best quality.
Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities

In this paper, we review and generalize results on the derivation of tractable non-negativity (necessary and su¢ cient) conditions for N -dimensional asymmetric MEM and GARCH/HEAVY models with spillovers. We show that the non-negativity constraints are translated into simple matrix inequalities, which are easily handled. In practice, these conditions may not be ful(cid:133)lled. To deal with these cases, we propose a constrained QML estimation. We also obtain new theoretical results about the second moment structure and the optimal forecasts of such multivariate processes. Four empirical examples are included to show the e⁄ectiveness of the proposed method.
CHEMICAL INVESTIGATION OF INDIAN LICHENS Part IV. Constitution of Montagnetol

THE isolation of a new phenolic component of Rocella montagnei named " Montagnetol " was described in Part III of this series. ' After further careful purification and analysis its composition was found to agree more closely with the formula, C12H1607. Though the substance did not give the homofluorescein reaction quickly as does orcinol, when the solution was allowed to stand for a few days the characteristic fluorescence developed. There was thus an indication that montagnetol is a derivative of orcinol. This was supported by the fact that 4: 7-dimethyl-5-hydroxy coumarin was formed, when it was treated with ethylacetoacetate under the conditions of Pechmann's reaction. The idea was followed up by subjecting the compound to the action of aqueous baryta and methyl alcoholic potash and analysing the products of decomposition. Decomposition with boiling aqueous baryta took place very readily yielding barium carbonate, orcinol and (meso) erythritol. With methyl alcoholic potash, however, the methyl ester of orsellinic acid was produced along with erythritol. Further by the action of concentrated sulphuric acid in the cold, pure samples of orsellinic acid and (meso) erythritol could be obtained. Dilute sulphuric acid in the cold had no action on the compound; but when the mixture was boiled, decomposition resulted, orcinol and erythritol being formed. From all these data it could be deduced that montagnetol is a compound of orsellinic acid and erythritol and since it is a neutral body it should be the erythrityl ester of orsellinic acid. That none of the phenolic hydroxyl groups are involved in any combination with erythritol was established as follows :—