Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiwavelength membrane laser array using selective area growth on directly bonded InP on SiO2/Si

The cost and power consumption of optical transmitters are now hampering further increases in total transmission capacity within and between data centers. Photonic integrated circuits (PICs) based on silicon (Si) photonics with wavelength-division multiplexing (WDM) technologies are promising solutions. However, due to the inefficient light emission characteristics of Si, incorporating III-V compound semiconductor lasers into PICs via a heterogeneous integration scheme is desirable. In addition, optimizing the bandgap of the III-V material used for each laser in a WDM transmitter becomes important because of recent strict requirements for optical transmitters in terms of data speed and operating temperature. Given these circumstances, applying a direct-bonding scheme is very difficult because it requires multiple bonding steps to bond different-bandgap III-V materials that are individually grown on different wafers. Here, to achieve wideband WDM operation with a single wafer, we employ a selective area growth technique that allows us to control the bandgap of multi-quantum wells (MQWs) on a thin InP layer directly bonded to silicon (InP-on-insulator). The InP-on-insulator platform allows for epitaxial growth without the fundamental difficulties associated with lattice mismatch or antiphase boundaries. High crystal quality is achieved by keeping the total III-V layer thickness less than the critical thickness (430 nm) and compensating for the thermally induced strain in the MQWs. By carrying out one selective MQW growth, we successfully fabricated an eight-channel directly modulated membrane laser array with lasing wavelengths ranging from 1272.3 to 1310.5 nm. The fabricated lasers were directly modulated at 56-Gbit/s with pulse amplitude modulation with four-amplitude-level signal. This heterogeneous integration approach paves the way to establishing III-V/Si WDM-PICs for future data-center networks.
A single unit analysis of neural plasticity in adult cats : effects of monocular paralysis on the lateral geniculate nucleus

Loss of binocularity has been reported selectively in simple cortical cells following chronic monocular paralysis in adult cats. The nature of any analogous changes which may occur in the dorsal lateral geniculate nucleus (LGNd) may be predicted by the parallel processing model of geniculostriate connections. This model predicts that if simple cortical cells are selectively affected by chronic monocular paralysis, then the X-cell population of the LGNd should be affected selectively if any effect is seen. This experiment, therefore, examined the effects of chronic monocular paralysis in adult cats on the X- and Y-cell populations of the LGNd.
Global reconstruction of life‐history strategies: A case study using tunas

Abstract Measuring the demographic parameters of exploited populations is central to predicting their vulnerability and extinction risk. However, current rates of population decline and species loss greatly outpace our ability to empirically monitor all populations that are potentially threatened. The scale of this problem cannot be addressed through additional data collection alone, and therefore it is a common practice to conduct population assessments based on surrogate data collected from similar species. However, this approach introduces biases and imprecisions that are difficult to quantify. Recent developments in hierarchical modelling have enabled missing values to be reconstructed based on the correlations between available life‐history data, linking similar species based on phylogeny and environmental conditions. However, these methods cannot resolve life‐history variability among populations or species that are closely placed spatially or taxonomically. Here, theoretically motivated constraints that align with life‐history theory offer a new avenue for addressing this problem. We describe a Bayesian hierarchical approach that combines fragmented, multispecies and multi‐population data with established life‐history theory, in order to objectively determine similarity between populations based on trait correlations (life‐history trade‐offs) obtained from model fitting. We reconstruct 59 unobserved life‐history parameters for 23 populations of tuna that sustain some of the world's most valuable fisheries. Testing by cross‐validation across different scenarios indicated that life‐histories were accurately reconstructed when information was available for other populations of the same species. The reconstruction of several traits was also accurate for species represented by a single population, although credible intervals increased dramatically. Synthesis and applications. The described Bayesian hierarchical method provides access to life‐history traits that are difficult to measure directly and reconstructs missing life‐history information useful for assessing populations and species that are directly or indirectly affected by human exploitation of natural resources. The method is particularly useful for examining populations that are spatially or taxonomically similar, and the reconstructed life‐history strategies described for the principal market tunas have immediate application to the world‐wide management of these fisheries.
On the transposability of change management research results: a systematic scoping review of studies published in JOCM and JCM

The purpose of this study was to assess the transposability of study results published in the Journal of Organizational Change Management (JOCM) and the Journal of Change Management (JCM) between 2000 and 2019 for change-management practitioners and researchers. ,A systematic scoping review of a large sample of articles published in both journals was undertaken: 122 studies were considered for analysis and coded by two independent coders using an inductive grid. ,Findings show that few studies (1) describe the nature of changes undertaken by organizations; (2) explain the contextual elements that characterize the environment at the moment when these same transformations are deployed; or (3) nuance their observations according to the change operation. ,Information on the type of change undertaken by the organization and about how change has been implemented is useful when communicating new scientific knowledge to practitioners. Nevertheless, the way in which studies are sometimes described masks some important nuances to be considered when interpreting or replicating certain results. ,The relevance of these issues is enhanced by the fact that researchers or practitioners (as knowledge users) are likely to reproduce some of the actions carried out in previous studies in order to deepen research avenues or to facilitate the implementation of change initiatives in workplaces. ,This research is among the first to assess the transferability of change-management study results published in both journals over such a long period. Its relevance also speaks to the importance of contextualizing results to ease their transposability by researchers and practitioners.
Umami potential from crude extract of Bekkai lan (Albertisia papuana Becc.) leaves, an indegenous plant in east Kalimantan-Indonesia.

Umami-taste active compounds of Bekkai lan leaves crude extract (Albertisia papuana Becc.) were analyzed and their potential were evaluated by equivalent umami concentration (EUC) method. The EUC was found to be 48.31 g MSG/100 g in the crude extract, obtained at pH 8 for 3 minutes. The umami potential of the crude extract was moderate. The yield of the umami compound depend on pH and extraction time, therefore the lower the pH, the longer the time required for the extraction of umami compound.
Serological Evidence of Avian Mycoplasmosis and Salmonellosisin Different Poultry Birds at the Live Bird Market and Free RangeManagement System in Taraba State, Nigeria

Both avian mycoplasmosis due to Mycoplasma gallisepticum and Mycoplasma synoviae and salmonellosis due to Salmonella pullorum are responsible for economic losses to the poultry industry worldwide. This study was conducted between April to July, 2017, to determine the Seroprevalence of Mycoplasma gallisepticum (MG), Mycoplasma synoviae (MS) and Salmonella Pullorum (SP) in broiler chickens, layer chickens, indigenous chickens, guinea fowl, indigenous cross - breed chickens (Lacroilers) sampled at the Jalingo live bird market and indigenous chickens on free range. Out of the total of 792 serum samples tested, 60.22% were positive to MG. Also, out of the 275 sera samples tested for MS, 66.18% were positive for MS. Salmonella pullorum antibodies were detected in 53.9% of the 920 whole blood samples tested. Highest seropositive rates were detected in the indigenous chickens for both MG and MS with 71.93% and 90% seropositive rates, respectively. The highest antibody presence for SP were found in the layer chickens. The study found that all bird types had detectable antibodies for MG, MS and SP leading to the conclusion that MG, MS and SP antibodies are prevalent in chickens of different types as well as guinea fowl in the study area. The significance of these findings are discussed. are the species responsible for greater losses in the poultry industry. Infections are characterized by obstinate hacking cough, sneezing, tracheal rales, decreased feed efficacy, poor carcass quality, and suboptimal egg production in laying birds and reduced quality of day old chicks [3-6].
Hybrid Malware Classification Method Using Segmentation-Based Fractal Texture Analysis and Deep Convolution Neural Network Features

As the number of internet users increases so does the number of malicious attacks using malware. The detection of malicious code is becoming critical, and the existing approaches need to be improved. Here, we propose a feature fusion method to combine the features extracted from pre-trained AlexNet and Inception-v3 deep neural networks with features attained using segmentation-based fractal texture analysis (SFTA) of images representing the malware code. In this work, we use distinctive pre-trained models (AlexNet and Inception-V3) for feature extraction. The purpose of deep convolutional neural network (CNN) feature extraction from two models is to improve the malware classifier accuracy, because both models have characteristics and qualities to extract different features. This technique produces a fusion of features to build a multimodal representation of malicious code that can be used to classify the grayscale images, separating the malware into 25 malware classes. The features that are extracted from malware images are then classified using different variants of support vector machine (SVM), k-nearest neighbor (KNN), decision tree (DT), and other classifiers. To improve the classification results, we also adopted data augmentation based on affine image transforms. The presented method is evaluated on a Malimg malware image dataset, achieving an accuracy of 99.3%, which makes it the best among the competing approaches.
Principals in Urban Schools Under Pressure: Relations With Parents in the Era of Test-Based Accountability

We conducted an inductive analysis of 166 interviews from a longitudinal study of 26 Chicago Public School principals. Test-based accountability pressures played a visible role in principals’ views of and relations with parents. Some principals reported banning parents from classrooms based on the need to protect instructional time to raise test scores; others thought more parental involvement would help their school reach its academic goals. Viewing principals in urban schools as street-level bureaucrats who have discretion in how they implement policy demands offers a way to understand variation in principals’ decisions about parent involvement.
Pharmacological therapy for COVID-19: Where are we now and where are we going?

Background: Up to the point of writing this review, there is no scientific evidence of any effective medical therapy for coronavirus disease 2019 (COVID-19). In this review, we attempted to discuss the current summary of evidence of some medication, currently in trial for the treatment of COVID-19. Material and Methods: We have done an electronic literature search using the following database: PubMed, Medline, Scopus and Google scholar. These databases were searched using the keywords COVID-19 and pharmacological therapy. Results: At present, there are no well randomized controlled studies which can give evidence for most of the therapy used for COVID-19. Several medications are in trials for COVID-19, among them: 1/ chloroquine and hydroxychloroquine; 2/anti-virals oseltamivir, remdesivir, lopinavir/ritonavir and other protease inhibitors; 3/antibiotics macrolide (Azithromycin); 4/cytokine therapy interferon; 5/ humanized monoclonal antibody tocilizumab; 6/adjunct therapies vitamins C, D, and herbal medicine; 7/ COVID-19 convalescent plasma; 8/systemic steroids; 9/expected COVID-19 vaccine. We have also included some of the herbal medicines that are commonly and widely used in the Middle East, Asia as well in Sudan, (black seeds, honey and Acacia Nilotica). It is worth mentioning that these herbal medicines have shown benefits in treating other diseases, but the evidence of their benefit in COVID-19 still needs to be established. Conclusion: Currently there is no pharmacological therapy for the COVID-19. More research and randomized clinical trials are needed to find effective therapy or vaccine against COVID-19. Keywords: COVID-19, Pharmacotherapy, herbal medicine, Sudan
Comparative secretome analysis of normal prostate and prostate cancer cell models

111. Kulasingam, V. & Diamandis, E. P. Strategies for discovering novel cancer biomarkers through utilization of emerging technologies. Nature Clinical Practice Oncology 5, 588–599 (2008). URL http://www.nature. com/doifinder/ 10.1038/ncponc1187. 112. Saah, A. J. & Hoover, D. R. ”Sensitivity” and ”specificity” reconsidered: the meaning of these terms in analytical and diagnostic settings. Annals of internal medicine 126, 91–4 (1997). URL http://www.ncbi.nlm.nih.gov/ pubmed/8992938. 113. Rao, A. R. , Motiwala, H. G. & Karim, O. M. A. The discovery of prostatespecific antigen. BJU international 101, 5–10 (2008). URL http://www. ncbi.nlm.nih.gov/pubmed/17760888. 114. Kyung, Y. -S. , Lee, H. -C. & Kim, H. -J. Changes in serum prostatespecific antigen after treatment with antibiotics in patients with lower urinary tract symptoms/benign prostatic hyperplasia with prostatitis. International neurourology journal 14, 100–4 (2010). URL http://www.ncbi.nlm.nih.gov/pubmed/21120219http://www. pubmedcentral.nih.gov/articlerender.fcgi? artid=PMC2989471. 115. Serefoglu, E. C. et al. How reliable is 12-core prostate biopsy procedure in the detection of prostate cancer? Canadian Urological Association journal = Journal de l’Association des urologues du Canada 7, E293– 8 (2013). URL http://www.ncbi.nlm.nih.gov/pubmed/22398204http:// www.pubmedcentral.nih.gov/articlerender.fcgi? artid=PMC3668408. 116. Horgan, R. P., Kenny, L. C. , Mrcpi, M. & Phd, M. SAC review ’Omic’ technologies: genomics, transcriptomics, proteomics and metabolomics Clinical Research Fellow and Specialist Registrar in Obstetrics and Gynaecology. SAC Stellenbosch University https://scholar.sun.ac.za
The complete chloroplast genome of Rhamnus globosa (Rhamnaceae)

Abstract Rhamnus globosa Bunge is a small shrub that can be used in the treatment of swollen poison, because of the antimicrobial activity. Here, we constructed the complete chloroplast genome of the R. globosa using Illumina sequencing technology. The circular cp genome was 160,642 bp in size, and comprises a large single-copy (LSC) region of 88,889 bp, a small single-copy (SSC) region of 18,897 bp, and a pair of inverted repeats (IR) of 26,428 bp. The GC content was 37.14% overall, with 35.01%, 31.42%, and 42.75% for the LSC, SSC, and IR regions, respectively. The plastome comprised 129 unique genes including 81 protein-coding genes, 30 tRNAs, and 4 rRNAs. The ML phylogenetic analysis based on 44 chloroplast genomes in Rosales showed a strong sister relationship with Berchemia species.
NUTRITIVE VALUE OF MEAT FROM PHILIPPINE WHITE MALLARD (Anas boschas L.) AND PEKIN (Anas platyrynchos L.) DUCKS

Philippine White Mallard duck was compared with Pekin duck for its potential in meat production. A total of 50 ducklings were randomly assigned to 5 pens per treatment after 1 month of brooding. Each pen containing five ducks was con­sidered as a replicate. Ducks were raised until 12 weeks of age and dressed at the end of the growing period. Data were subjected to the Independent Sample t -test. Essential amino acid profiles of both duck breeds have no significant differences except for leucine and isoleucine in which higher levels were obtained in Pekin duck meat. Total non-essential amino acid of Pekin duck meat was also sig­nificantly higher than the meat from Philippine White Mallard although the individual amino acid did not differ between breeds. Fatty acid composition from the meat of both breeds of duck did not show any significant differences. However, Philippine White Mallard duck was noted to have significantly higher cholesterol content in both skin and lean compared with Pekin ducks. Results showed that nutrient content of meat from both duck breeds were comparable. On the health point of view, Pekin duck meat has an advantage over Philippine White Mallard due to lower cholesterol content.
Impact of COVID-19 on Performance of Pakistan Stock Exchange

The objective of this study is to determine the impact of COVID-19 on the performance of Pakistani Stock Market. This study uses the data of COVID-19 related positive cases, fatalities, recovers and the closing prices of PSX 100 index of the first half of 2020. The findings of the study suggest that only COVID-19 recoveries are influencing the performance of the index and the daily positive cases and fatalities are insignificantly related to the performance. Further studies can be performed by incorporating other variables such as economic growth, interest rate and inflation rate along with the COVID-19 related variables at a cross-country level.
Study of Supratentorial Tumours by Computed Tomography

Background: Brain neoplasms may be classified by the location of supratentorial, infratentorial and midline tumours. Of the supratentorial neoplasms, meningiomas are the most frequent extra-axial neoplasms. CT has become the most important diagnostic procedure in evaluating patients suspected of harboring an intracranial tumor. It is still considered the basic radiologic study since it gives specific information for the management of brain tumours and is minimally invasive. The purpose of this study was to assess the distribution, features, localization and extent of supratentorial neoplasms. Subjects and Methods: Fifty cases with symptoms of intracranial pathology and on CT found to have supratentorial tumours were studied. Results: The CT patterns of 50 supratentorial tumours were reviewed, out of which 30 cases i.e. 60%, were found to be intra- axial and 20 i.e. 40% extra-axial tumours. GBM formed the major group of the intra axial tumours i.e. 18 %, and meningiomas formed the major extra-axial tumours forming 26%. Conclusion: CT proves to be a valuable modality of imaging in evaluating the distribution, features, localizing and assessing the extent of various intra and extra-axial tumours in the supratentorial region.
Machine learning methods’ performance in radiative transfer model inversion to retrieve plant traits from Sentinel-2 data of a mixed mountain forest

ABSTRACT Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies. Here, we compared a radiative transfer model (RTM) inversion by merit function and five machine learning algorithms trained on an RTM simulated dataset predicting the three plant traits leaf chlorophyll content (LCC), canopy chlorophyll content (CCC), and leaf area index (LAI), in a mixed temperate forest. The accuracy of the retrieval methods in predicting these three plant traits with spectral data from Sentinel-2 acquired on 13 July 2017 over Bavarian Forest National Park, Germany, was evaluated using in situ measurements collected contemporaneously. The RTM inversion using merit function resulted in estimations of LCC (R 2 = 0.26, RMSE = 3.9 µg/cm2), CCC (R 2 = 0.65, RMSE = 0.33 g/m2), and LAI (R 2 = 0.47, RMSE = 0.73 m2/m2), comparable to the estimations based on the machine learning method Random forest regression of LCC (R 2 = 0.34, RMSE = 4.06 µg/cm2), CCC (R 2 = 0.65, RMSE = 0.34 g/m2), and LAI (R 2 = 0.47, RMSE = 0.75 m2/m2). Several of the machine learning algorithms also yielded accuracies and robustness similar to the RTM inversion using merit function. The performance of regression methods trained on synthetic datasets showed promise for fast and accurate mapping of plant traits accross different plant functional types from remote sensing data.
Dietary patterns of Chinese puerperal women and their association with postpartum weight retention: Results from the mother–infant cohort study

Abstract Dietary intake may affect maternal health, but it remains unclear about puerperal dietary intake and its association with maternal health. This study investigated the dietary patterns and their related factors and association with postpartum weight retention (PPWR) in Chinese puerperal women. Participants were from the mother–infant cohort study, in which both mothers and infants were followed up from childbirth to the next 2 years, in seven cities around China. Maternal puerperal dietary patterns were derived by a food frequency questionnaire and principal component analysis (PCA) within 1 month postpartum. PPWR was assessed by the difference of weight at 42 days and 6 months postpartum minus the pre‐pregnancy weight. Of 503 postpartum women, four dietary patterns were identified, including ‘plant food’ pattern (rice and vegetables as dominant foods), ‘diverse’ pattern (starchy roots, fruit, livestock meat and aquatic products), ‘traditional northern’ pattern (poultry, eggs and soup) and ‘marine‐flour’ pattern (flour, coarse food grains and marine fish). The diverse pattern was associated with professional puerperal family care and counselling service (p < .05). PPWRs at 42 days and 6 months postpartum were 6.37 and 4.70 kg averagely. The plant food dietary pattern tended to be associated with higher 42‐day PPWR (β = .105, p < .05), and diverse pattern was associated with lower 6‐months PPWR (β = −.137, p < .05). Conclusively, this study presented four dominant dietary patterns in Chinese postpartum women and showed a lower PPWR in adherence to diverse dietary pattern. The results would provide evidence to furtherly guide dietary practice and improve maternal health.