Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Reviews and Meta-Analysis in Spine Surgery—How Good Are They in Methodological Quality? A Systematic Review

Study Design: Systematic review. Objectives: To assess the methodological quality of systematic reviews and meta-analyses in spine surgery over the past 2 decades. Materials and Methods: We conducted independent and in duplicate systematic review of the published systematic reviews and meta-analyses between 2000 and 2019 from PubMed Central and Cochrane Database pertaining to spine surgery involving surgical intervention. We searched bibliographies to identify additional relevant studies. Methodological quality was evaluated with AMSTAR score and graded with AMSTAR 2 criteria. Results: A total of 96 reviews met the eligibility criteria, with mean AMSTAR score of 7.51 (SD = 1.98). Based on AMSTAR 2 criteria, 13.5% (n = 13) and 18.7% (n = 18) of the studies had high and moderate level of confidence of results, respectively, without any critical flaws. A total of 29.1% (n = 28) of the studies had at least 1 critical flaw and 38.5% (n = 37) of the studies had more than 1 critical flaw, so that their results have low and critically low confidence, respectively. Failure to analyze the conflict of interest of authors of primary studies included in review and lack of list of excluded studies with justification were the most common critical flaw. Regression analysis demonstrated that studies with funding and studies published in recent years were significantly associated with higher methodological quality. Conclusion: Despite improvement in methodological quality of systematic reviews and meta-analyses in spine surgery in current decade, a substantial proportion continue to show critical flaws. With increasing number of review articles in spine surgery, stringent measures must be taken to adhere to methodological quality by following PRISMA and AMSTAR guidelines to attain higher standards of evidence in published literature.
Sampling probes affect bulk density and soil organic carbon measurements

Soil sampling equipment can be a major source of bias in soil organic carbon (SOC) stock estimations. The objective of this study was to evaluate the impact of sampling probes on soil bulk density (BD) and SOC stocks calculated using fixed depth (FD) and equivalent soil mass (ESM) methods. Soil samples were collected to 30 cm using three probes with different diameters and divided into 0–10‐, 10–20‐, and 20–30‐cm layers. The probe with smallest diameter measured higher BD at 0–10 cm in 42% of fields and was significantly different when averaged across fields, while no consistent differences were observed at lower depths. This study shows that sampling probes with different diameters may introduce biases in BD and SOC measurements at individual or combined soil layers when calculated using the FD approach. The ESM approach reduced the differences in mean SOC stocks calculated using different probes.
Assessing Digital Soil Inventories for Predicting Streamflow in the Headwaters of the Blue Nile

Comprehensive spatially referenced soil data are a crucial input in predicting biophysical and hydrological landscape processes. In most developing countries, these detailed soil data are not yet available. The objective of this study was, therefore, to evaluate the detail needed in soil resource inventories to predict the hydrologic response of watersheds. Using three distinctively different digital soil inventories, the widely used and tested soil and water assessment tool (SWAT) was selected to predict the discharge in two watersheds in the headwaters of the Blue Nile: the 1316 km2 Rib watershed and the nested 3.59 km2 Gomit watershed. The soil digital soil inventories employed were in increasing specificity: the global Food and Agricultural Organization (FAO), the Africa Soil Information Service (AfSIS) and the Amhara Design and Supervision Works Enterprise (ADSWE). Hydrologic simulations before model calibration were poor for all three soil inventories used as input. After model calibration, the streamflow predictions improved with monthly Nash–Sutcliffe efficiencies greater than 0.68. Predictions were statistically similar for the three soil databases justifying the use of the global FAO soil map in data-scarce regions for watershed discharge predictions.
Utilization of Nannochloropsis oceanica alga for biodiesel production and the de-lipidated biomass for improving Red tilapia aquaculture

1Lecturer, Marine resources department, Faculty of Natural Resources and environmental sciences, Omar Al-Mokhtar University, El-Beda, Libya. 2Associate professour in aquaculture division, National Institute of oceanography and fisheries, Qait Bay, Alexandria, Egypt. 3Head of Animal and Fish production department, Professour of fish husbandary faculty of Agriculture (El-Shatby), Alexandria University, egypt. 4Professour of Animal and fish Nutrition, department of Animal and Fish production, faculty of Agriculture (El-Shatby), Alexandria University, egypt. *Corresponding Author: hebasaad2222@yahoo.com
Is the Number of Tropical Cyclone Rapid Intensification Events in the Western North Pacific Increasing?

Japan Meteorological Agency (JMA) best track data indicate that the number of rapid intensification (RI) tropical cyclone events in the western North Pacific increased from 1987 to 2018. To clarify whether this increase is due to climatological changes or qualitative changes in the data, the long-term trend of RI events in JMA operational Dvorak data, which have been used as the first guess for best track analysis, was investigated. Because the JMA Dvorak analysis procedure has remained almost unchanged since 1987, the temporal homogeneity of the Dvorak data is expected to be much better than that of the best track data. The results showed no discernable trend in Dvorak-based RI events over the 32 years. Although the frequency distribution of 24-h intensity changes changed slightly in the Dvorak analysis, that of the best track data changed significantly; as a result, the frequency of best track-based RI events increased after 2006. JMA started using microwave satellite imagery for best track analysis in 2006. This change likely affected the temporal homogeneity of the best track data. These results suggest that the increase in best track-based RI events was due mainly to qualitative changes related to advances in observational techniques. (Citation: Shimada, U., M. Yamaguchi, and S. Nishimura, 2020: Is the number of tropical cyclone rapid intensification events in the western North Pacific increasing? SOLA, 16, 1−5, doi:10.2151/sola.2020-001.)
Techniques and Thresholds of Significance for Using WSR-88D Velocity Data to Anticipate Significant Tornadoes

Significant tornadoes (EF2+) make up a very small percentage of the total United States tornado events, but produce the overwhelming majority of tornado fatalities. Identifying significant tornado events in a shortfused warning environment has been a particular focus of the United States National Weather Service’s severe weather program in recent years, with the goal of reducing the loss of life from significant events to the greatest extent possible. This study aims to further this effort by identifying and quantifying the skill of key signals present in Weather Service Radar-1998 Doppler velocity data in the minutes prior to the onset of significant tornado damage. When separated by storm mode, several radar velocity signals are identified that show operationally useful skill in differentiating between significant and weak/nontornadic events in supercells—with lead time. The highest skill scores are achieved by combining maximum volumetric rotational speed and depth of the storm’s mesocyclone, as well as the overall change in rotational speed in the final minutes prior to the onset of significant damage. Very little, if any, predictive skill was found when only the lowest elevation scan was considered, including more frequent supplementary scans in between full volumetric scans. The same signals that showed noteworthy skill for supercells failed to discriminate between significant and weak/nontornadic events in quasi-linear convective Systems and bow echo/mesoscale convective vortex events.
The Influence of Organizational Culture on Organizational Performance (The Case of Debre Berhan University)

The objective of this study was to examine the influence of organizational culture on organizational performance in the case of Debre Berhan University. Organizational culture variables namely; Involvement, consistency, Adaptability, and Mission are taken as independent variables and organizational performance served as dependent variable. The study was adopted quantitative research approach and the nature of the study was descriptive and explanatory. The total sample of the study was 338 respondents with a response rate of 311 respondents. In this study both descriptive and inferential statistics were used. The data were collected using questionnaires in which the researcher used primary and secondary data. The data were analyzed through the device of Statistical Package for Social Science version 23. The finding of the study depicted that mission and consistency cultures were strong relationship and influence on organizational performance. Involvement and adaptability culture were moderate relationship with organizational performance. However, adaptability culture was insignificant influence on organizational performance. The finding of the study shows that mission culture was the dominant culture of Debre Berhan University. The level of organizational performance was moderate. The overall findings of the study suggest that organizational culture influence organizational performance. Keywords: Involvement, Consistency, Adaptability, Mission, Organizational performance DOI: 10.7176/IEL/10-1-03 Publication date: January 31st 2020
Push–Pull Gradient Methods for Distributed Optimization in Networks

In this article, we focus on solving a distributed convex optimization problem in a network, where each agent has its own convex cost function and the goal is to minimize the sum of the agents’ cost functions while obeying the network connectivity structure. In order to minimize the sum of the cost functions, we consider new distributed gradient-based methods where each node maintains two estimates, namely an estimate of the optimal decision variable and an estimate of the gradient for the average of the agents’ objective functions. From the viewpoint of an agent, the information about the gradients is pushed to the neighbors, whereas the information about the decision variable is pulled from the neighbors, hence giving the name “push–pull gradient methods. ” The methods utilize two different graphs for the information exchange among agents and, as such, unify the algorithms with different types of distributed architecture, including decentralized (peer to peer), centralized (master–slave), and semicentralized (leader–follower) architectures. We show that the proposed algorithms and their many variants converge linearly for strongly convex and smooth objective functions over a network (possibly with unidirectional data links) in both synchronous and asynchronous random-gossip settings. In particular, under the random-gossip setting, “push–pull” is the first class of algorithms for distributed optimization over directed graphs. Moreover, we numerically evaluate our proposed algorithms in both scenarios, and show that they outperform other existing linearly convergent schemes, especially for ill-conditioned problems and networks that are not well balanced.
Constructing an identity scale to analyze changes in One China identity: evidence from Taiwanese student delegations visiting Mainland China

Abstract It is both academically and practically valuable to construct a multi-dimensional scale to assess the effectiveness of the Communist Party of China's (CPC) policy toward Taiwan. The author constructed a One China identity scale based on national identity theory and the CPC's political advocacy and actions toward Taiwan. Using panel data from 271 members of Taiwanese student delegations to Mainland China from 2016 to 2017, this study explored the changes in their sense of a One China identity. The results showed a significant increase (0.11, 5.19%) in the average ratings of the investigated students' One China identity. The regression equation constructed by the current study was able to explain 10.94% of the total variance of the One China identity scale, and all three hypotheses were supported. Following the exchange program, Taiwanese students appeared to have a greater sense of a One China identity. Their impression of Mainland China had improved, their acceptance of the CPC's regime had increased, and their preference for authoritarianism had increased.
Analisis Potensi Ekonomi Sektor Pertanian dan Sektor Pariwisata di Provinsi Bali Menggunakan Teknik Analisis Regional

Provinsi Bali mempunyai peran yang strategis dalam pembangunan Indonesia, khususnya sektor pariwisata dan masih mengandalkan sektor pertanian sebagai mata pencahariannya. Kedua sektor ini merupakan sektor yang diandalkan dalam sumber pendapatan Provinsi Bali. Analisis regional diperlukan sebagai upaya untuk mengidentifikasi dan menganalisis potensi unggulan setiap kabupaten di Provinsi Bali. Metode yang digunakan adalah Location Quotient, Shift Share, Indeks Spesialisasi Regional, dan Tipologi Klassen. Data yang digunakan berupa data Pendapatan Domestik Regional Bruto (PDRB) atas dasar harga konstan 2010 dan data PDRB per kapita tahun 2015-2017. Keberadaan dua sektor basis dan unggulan memperlihatkan bahwa sektor pariwisata yang ditopang oleh Badung, Buleleng, Denpasar, dan Gianyar memiliki peran yang tinggi terhadap pendapatan kabupaten/kota tersebut dan Provinsi Bali secara keseluruhan. Analisis Shift-Share menunjukkan kontribusi PDRB terbesar adalah sektor pariwisata dan tidak terspesialisasi di setiap daerah. Hasil analisis tipologi Klassen menunjukkan adanya kesenjangan antara kabupaten/kota yang menjadi basis pariwisata dengan kabupaten/kota yang bukan menjadi basis pariwisata. The Province of Bali has a strategic role in Indonesia’s development, particularly the tourism sector and still relies on the agricultural sector as its livelihood. Both of these sectors are sectors that are relied upon in the sources of income of the Province of Bali. Regional analysis is needed as an effort to identify and analyze the superior potential of each district in Bali Province. The methods used are Location Quotient, Shift Share, Regional Specialization Index, and Klassen Typology. The data used in the form of GRDP data based on constant 2010 prices and GRDP data per capita in 2015-2017. The existence of two basic and superior sectors shows that the tourism sector supported by Badung, Buleleng, Denpasar and Gianyar has a high role in the revenue of the regency / city and the Province of Bali as a whole. Shift-Share analysis shows that the biggest PDRB contribution is the tourism sector and is not specialized in each region. Klassen’s typology analysis results show a gap between the districts / cities that are the basis of tourism and the districts that are not the basis of tourism.
Evaluating graphical manipulations in automatically laid out LineSets

ABSTRACT This paper presents an empirical study to determine whether alterations to graphical features (colour and size) of automatically generated LineSets improve task performance. LineSets are used to visualise sets and networks. The increasingly common nature of such data suggests that having effective visualisations is important. Unlike many approaches to set and network visualisation, which often use concave or convex shapes to represent sets alongside graphs, LineSets use lines overlaid on a graph. LineSets have been shown to be advantageous over shape-based approaches. However, the graphical properties of LineSets have not been fully explored. Our results suggest that automatically drawn LineSets can be significantly improved for certain tasks through the considered use of colour alongside size variations applied to their graphical elements. In particular, we show that perceptually distinguishable colours, lines of varying width, and nodes of varying diameter lead to improved task performance in automatically laid-out LineSets.
Does institutional stability granger-cause foreign direct investment? evidence from Canada

Global FDIs have increased substantially since the 1990’s. This was seen as a favorable development among developing countries, however developed countries have had a mixed reaction. In this paper we look at the effects of FDI flows on institutional stability, to better understand what drives FDI. The focus country for this paper is Canada, as it is one of the few countries where the economy remained relatively stable compared to other economies during the global financial crisis. As such, the findings from this study can shed light on what allowed Canadian policy makers to maintain economic stability. The methodology applied is Auto-Regressive Distributive Lag (ARDL) to understand the relationship between FDI and institutional stability along with other controlled variables (GNP, inflation, and exports). This study is different from others in that it examines the Canadian economy, and similar papers have examined different countries (to my knowledge). Based on previous theoretical and empirical literature, most of the research points to FDI positively affecting institutional stability. However, there is some literature that makes the case for this relationship not always holding true. Our empirical findings tend to show that it is in fact institutional stability that positively impacts FDI in the long run. As such, the policy makers should consider implementing policies that ensure that the strength of institutions is enhanced, and this in turn will attract more investment.
Calibration of Machine Learning–Based Probabilistic Hail Predictions for Operational Forecasting

In this study, we use machine learning (ML) to improve hail prediction by postprocessing numerical weather prediction (NWP) data from the new High-Resolution Ensemble Forecast system, version 2 (HREFv2). Multiple operational models and ensembles currently predict hail, however ML models are more computationally efficient and do not require the physical assumptions associated with explicit predictions. Calibrating the ML-based predictions toward familiar forecaster output allows for a combination of higher skill associated with ML models and increased forecaster trust in the output. The observational dataset used to train and verify the random forest model is the Maximum Estimated Size of Hail (MESH), a Multi-Radar Multi-Sensor (MRMS) product. To build trust in the predictions, the ML-based hail predictions are calibrated using isotonic regression. The target datasets for isotonic regression include the local storm reports and Storm Prediction Center (SPC) practically perfect data. Verification of the ML predictions indicates that the probability magnitudes output from the calibrated models closely resemble the day-1 SPC outlook and practically perfect data. The ML model calibrated toward the local storm reports exhibited better or similar skill to the uncalibrated predictions, while decreasing model bias. Increases in reliability and skill after calibration may increase forecaster trust in the automated hail predictions.
Characteristics of a wing-like sandstone intrusion, Volund Field

Abstract Reservoirs in the Volund Field are all sandstone intrusions with wings on three sides forming the main reservoir volumes. The southern wing was the target of exploration and appraisal wells, which led to the field development. Identification of three smaller intrusions proves the southern wing to be a composite intrusion, similar to outcrop analogues. Identification from core and borehole logs shows that it comprises sandstone-, mudstone- and mudstone-rich intervals, including mudstone clast breccia. Mudstone clast breccia constitutes a significant missed pay candidate. Breccia is porous and has a sand-supported matrix, which gives it excellent reservoir quality. This may be missed pay using analysis of borehole logs. Well data, largely borehole logs, show consistently uniform sandstone porosity distribution within the intrusions, independent of depth. Significantly, at about 100 m from the depth at which the wing emanates from sills, porosity has a broader spread of values. The spread of values is attributable to mudstone clast breccia and thin-bedded sandstone and mudstone. Porosity derived from borehole logs does not differentiate breccia from siltstone, but inference is possible using calibration of logs with core.
Structural Characterization of ZnO and Al Doped ZnO Powders Synthesis in Aqueous Solutions

Undoped and Al-doped ZnO (AZO) powders have been synthesized by hydrolytic and hydrothermal synthesis from Zn(NO3)2 , AlCl3 using KOH 1M concentraction like hydrolisis agent. The structural properties of prepared powders were studied using XRD and FTIR spectroscopy. Presence of aluminium in the hydrothermal powders is correlated with the presence of Zn-Al hydrotalcite like structure.
Three‐year surveillance (2016–2018) of chigger mites vector for tsutsugamushi disease in the Hwaseong‐Si area of Gyeonggi‐Do, Republic of Korea

Owing to climate change, the global resurgence of vector‐borne infectious diseases has emerged as a critical public health issue. Orientia tsutsugamushi is the etiological agent of tsutsugamushi disease (scrub typhus) a mite‐borne acute febrile disease occurring in the Asia‐Pacific region. We investigated the prevalence of tsutsugamushi disease transmitted by chigger mite vectors living on rodents. Using sticky‐type chigger traps for three months during 2016–2018, 1,057 chigger mites were collected (chigger mite index, 1.31) from four locations in the Hwaseong‐si area of Gyeonggi‐do, Republic of Korea. Five species distributed among three genera were identified. In addition, 94 rodents were captured (collection rate: 7.83%) using Sherman live traps over the course of three months (April, October, and November) during 2016–2017. Three rodent species were captured and identified and the striped field mouse (Apodemus agrarius) was the dominant rodent host species in the surveyed area. A total of 10,469 ectoparasitic chigger mites were recovered from the 94 rodents, from which 13 species distributed among four genera were identified. Of the 5,250 chigger mites examined, Leptotrombidium pallidum was most abundant (n = 2,558), followed by L. orientale, L. scutellare, L. zetum, Euschoengastia koreaensis, L. subintermedium, and Neotrombicula tamiyai. Of the examined chigger mites, no groups recovered from rodent hosts tested positive for O. tsutsugamushi. This study provides fundamental regional information on vector‐borne disease data collection in the Hwaseong‐si area, Gyeonggi‐do, and will further contribute to formulating disease control and prevention strategies.