Miracle-dz/UniFAR-FTUs huggingface dataset:
Trophic ecology of large herbivores in a reassembling African ecosystem

Megafauna assemblages have declined or disappeared throughout much of the world, and many efforts are underway to restore them. Understanding the trophic ecology of such reassembling systems is necessary for predicting recovery dynamics, guiding management, and testing general theory. Yet, there are few studies of recovering large‐mammal communities, and fewer still that have characterized food‐web structure with high taxonomic resolution. In Gorongosa National Park, large herbivores have rebounded from near‐extirpation following the Mozambican Civil War (1977–1992). However, contemporary community structure differs radically from the prewar baseline: medium‐sized ungulates now outnumber larger bodied species, and several apex carnivores remain locally extinct. We used DNA metabarcoding to quantify diet composition of Gorongosa’s 14 most abundant large‐mammal populations. We tested five hypotheses: (i) the most abundant populations exhibit greatest individual‐level dietary variability; (ii) these populations also have the greatest total niche width (dietary diversity); (iii) interspecific niche overlap is high, with the diets of less‐abundant species nested within those of more‐abundant species; (iv) partitioning of forage species is stronger in more structurally heterogeneous habitats; and (v) selectivity for plant taxa converges within guilds and digestive types, but diverges across them. Abundant (and narrow‐mouthed) populations exhibited higher among‐individual dietary variation, but not necessarily the greatest dietary diversity. Interspecific dietary overlap was high, especially among grazers and in structurally homogenous habitat, whereas niche separation was more pronounced among browsers and in heterogeneous habitat. Patterns of selectivity were similar for ruminants—grazers and browsers alike—but differed between ruminants and non‐ruminants. Synthesis. The structure of this recovering food web was consistent with several hypotheses predicated on competition, habitat complexity, and herbivore traits, but it differed from patterns observed in more intact assemblages. We propose that intraspecific competition in the fastest‐recovering populations has promoted individual variation and a more nested food web, wherein rare species use subsets of foods eaten by abundant species, and that this scenario is reinforced by weak predation pressure. Future work should test these conjectures and analyse how the taxonomic dietary niche axis studied here interacts with other mechanisms of diet partitioning to affect community reassembly following wildlife declines.
Evaluating of HPV–DNA ISH as an adjunct to p16 testing in oropharyngeal cancer

Aim: Current guidelines recommend p16 immunohistochemistry (IHC) for testing human papillomavirus (HPV) in oropharyngeal carcinoma (OPSCC). We evaluated the value of adding DNA in situ hybridization (ISH) to p16 IHC. Methods: Fifty patients with OPSCC were analyzed. Concordance between HPV–DNA ISH and p16 IHC was measured by Gwet's agreement coefficient. Results: p16 IHC was positive in 35/48 (72.9%), negative in 8/48 (16.7%) patients. Wide spectrum DNA–ISH was positive in 9/23 (39%) and negative in 14/23 (60.9%) patients. High-risk 16/18 (HR) HPV DNA–ISH was positive in 11/23 (47.8%) and negative in 12 (52.2%) patients. The agreement between HPV DNA–ISH and p16 IHC is fair (Gwet's AC1 = 0.318). Conclusion: The agreement between p16 IHC and HPV–DNA ISH was fair. However, ISH sensitivity was low. Our findings add to the current data that p16 IHC testing is reliable and may be enough as a stand-alone test for HPV detection in OPSCC.
Seroprevalence of Brucellosis in sheep in Maigana and Birnin Gwari agro-ecological zones of Kaduna State, Nigeria

Brucellosis is an ancient and one of the world’s most widespread zoonotic diseases affecting public health and animal production. A cross-sectional study using simple random sampling was conducted between May and December, 2016 in Maigana and Birnin Gwari Agro-ecological zones of Kaduna State to determine the sero-prevalence of brucellosis in sheep. In addition the risk factors associated with sero-positivity in sheep were also assessed. A total of 400 sera samples comprised of 141 from males and 259 from females sheep were collected and screened for the presence of Brucella antibodies using Rose Bengal Plate test (RBPT) and competitive enzyme linked immunosorbent assay (cELISA). Sera analysis revealed that, 16.5% and 10.8% were seropositive to Brucella infection by RBPT and cELISA, respectively. There was statistically significant association between sex of the sheep and seropositivity to Brucella infection using RBPT (P < 0.05). Meanwhile, no statistically significant association between the age and breed of sheep and seropositivity to Brucella infection using RBPT and cELISA, respectively (P > 0.05). This study shows evidence of Brucella infection with high prevalence mainly among female sheep and the disease can be considered as a potential risk for both susceptible animals and humans in the study area. Therefore, creating awareness about brucellosis, interdisciplinary partnership and complementary effort between veterinary and public health professionals is very important to control the transmission of brucellosis.Keywords: Brucellosis, Kaduna State, Sheep, Sero-prevalence
Menstrual knowledge associated with adolescent’s attitude of intellectual disability on facing menstruation in Bantul, Indonesia

Background: Menstruation is an important event in puberty as a biological sign of sexual maturity for young women. Adolescent with intellectual disability has the same stage of biological development as normal adolescent. Menstruation often causes many problems such as menstrual pain, emotional changes and menstrual personal hygiene (such as: using sanitary napkins). It causes a lot of negative reactions and anxiety. The phenomenon that has often happened in community is feeling taboo to discuss menstrual problems, so that adolescents are not well informed. Objective of this study was to determine the association between menstrual knowledge with adolescent’s attitude of mental retardation (intellectual disability) on facing menstruation.Methods: This research is a descriptive analytic with a cross-sectional study. It was conducted at SLB Masudi Putra I and II Bantul, in August to October 2018 with intellectual disability adolescents who experienced menstruation, those were 39 respondents. Data collection is done by using a questionnaire. Bivariate analysis was done by the Spearman rank test.Results: The results of this research indicate that the percentages of adolescent’s knowledge of intellectual disability on facing menstruation were in medium category of 16 respondents (41.0%), and adolescent’s attitude of intellectual disability on facing menstruation mostly were negative of 24 respondents (61.5%) with p-value 0.001 (p<0.05 ) and the correlation coefficient (r) is positive at 0.495. It shows that there is an association between menstrual knowledge with adolescent’s attitude on facing menstruation with the closeness of the correlation in medium category.Conclusions: There were an association between menstrual knowledge with adolescent’s attitude of intellectual disability on facing menstruation at SLB Marsudi Putra Bantul with p-value 0.001 (p<0.05).
Skeletal muscle MRI differentiates SBMA and ALS and correlates with disease severity

Objective To investigate the use of muscle MRI for the differential diagnosis and as a disease progression biomarker for 2 major forms of motor neuron disorders: spinal bulbar muscular atrophy (SBMA) and amyotrophic lateral sclerosis (ALS). Methods We applied quantitative 3-point Dixon and semiquantitative T1-weighted and short tau inversion recovery (STIR) imaging to bulbar and lower limb muscles and performed clinical and functional assessments in ALS (n = 21) and SBMA (n = 21), alongside healthy controls (n = 16). Acquired images were analyzed for the presence of fat infiltration or edema as well as specific patterns of muscle involvement. Quantitative MRI measurements were correlated with clinical measures of disease severity in ALS and SBMA. Results Quantitative imaging revealed significant fat infiltration in bulbar (p < 0.001) and limb muscles in SBMA compared to controls (thigh: p < 0.001; calf: p = 0.001), identifying a characteristic pattern of muscle involvement. In ALS, semiquantitative STIR imaging detected marked hyperintensities in lower limb muscles, distinguishing ALS from SBMA and controls. Finally, MRI measurements correlated significantly with clinical scales of disease severity in both ALS and SBMA. Conclusions Our findings show that muscle MRI differentiates between SBMA and ALS and correlates with disease severity, supporting its use as a diagnostic tool and biomarker for disease progression. This highlights the clinical utility of muscle MRI in motor neuron disorders and contributes to establish objective outcome measures, which is crucial for the development of new drugs.
Pressure, temperature and processing time in enhancing Camelina sativa oil extraction by Instant Controlled Pressure-Drop (DIC) texturing pre-treatment

Instant Controlled Pressure Drop (DIC) was evaluated as a texturing pre-treatment for the extraction of Camelina sativa (L.) oil. DIC was coupled to Accelerated Solvent Extraction (ASE), Pressing and Dynamic Maceration (DM). DIC optimization was performed by studying the effects of pressure, temperature and processing time on oil yield. DIC + ASE obtained seed-oil yields of 615.9±0.5 against 555.5±0.5 g oil/kg-ddb for untextured seeds (RM). Via pressing, oil yields were 490.9±0.5 and 444.7±0.5 g oil/kg-ddb for textured and untextured seeds, respectively. Through coupling DIC (P: 0.63 MPa and t: 105 s) to the pressing extraction (60 s) of seeds along with 2h of DM of meals, it was possible to reach 605.8 g oil/kg ddb of oil yield. The same results were not obtained for RM seeds, where after 24 h of DM extraction, the oil yield was 554.7 g oil/kg ddb. DIC allowed for an increase in Camelina oil yields, reduced extraction time and valorized pressing meals.
Design and validation of a diagnostic MOOC evaluation method combining AHP and text mining algorithms

ABSTRACT The proliferation of massive open online courses (MOOCs) highlights the necessity of developing accurate and diagnostic evaluation methods to assess the courses’ quality and effectiveness. Hence, this study proposes a diagnostic MOOC evaluation (DME) method that combines the Analytic Hierarchy Process algorithm and learner review mining to integrate expert opinions, standardized rubrics, and learner feedback into the evaluation process. For this purpose, 30 MOOCs from the Coursera website were purposively selected and evaluated using the DME method and the results compared with expert evaluation and learner rating scores. The preliminary findings, in general, support the feasibility, accuracy, and diagnostic utility of the DME method and its suitability as a low-cost, sophisticated, and accurate method for MOOC evaluation. Finally, the study discusses several limitations and technical issues of the DME method that should be addressed in future research and practice.
Predicting the Discovery Pattern of Publically Known Exploited Vulnerabilities

Vulnerabilities with publically known exploits typically form 2–7 percent of all vulnerabilities reported for a given software version. With a smaller number of known exploited vulnerabilities compared with the total number of vulnerabilities, it is more difficult to model and predict when a vulnerability with a known exploit will be reported. In this article, we introduce an approach for predicting the discovery pattern of publically known exploited vulnerabilities using all publically known vulnerabilities reported for a given software. Eight commonly used vulnerability discovery models (VDMs) and one neural network model (NNM) were utilized to evaluate the prediction capability of our approach. We compared their predictions results with the scenario when only exploited vulnerabilities were used for prediction. Our results show that, in terms of prediction accuracy, out of eight software we analyzed, our approach led to more accurate results in seven cases. Only in one case, the accuracy of our approach was worse by 1.6 percent.
Photosynthesis and growth kinetics of Chlorella vulgaris R-117 cultured in an internally LED‑illuminated photobioreactor

The aim of this work was to correlate changes of photosynthesis activity vs. growth in Chlorella vulgaris R-117 (CCALA 1107), fast-growing and robust microalga cultured in an internally illuminated 10-L photobioreactor (PBR). The cultures were grown at high output irradiance provided by four LED light sources submerged in the culture when the light path was short, between 25-30 mm. The culture of Chlorella R-117 grown under 2,500 µmol(photon) m-2 s-1 attained a doubling time of 3.5 d and biomass density of 3.5 g(DM) L-1 after about 10-d period. When grown under 3,500 µmol(photon) m-2 s-1, the culture reached a doubling time of 1.7 d, and biomass density of ~5.5 g L-1 before entering the stationary phase. Electron transport rate changes correlated well with the culture growth demonstrating the usefulness of chlorophyll fluorescence for photosynthesis monitoring. This can be crucial for potential scale-up to large indoor PBRs to optimise culture growth.
Digitization and urban governance: The city as a reflection of its data infrastructure

This article introduces the ‘House Model’, an integrated framework consisting of four data governance modes, based on the urban and smart city vision, context, and big data technologies. The model stems from engaged scholarship, synthesizing and extending the academic debates and evidence from existing smart city initiatives. It provides a means for comparing cities in terms of their digitization efforts, helps the planning of more effective urban data infrastructures and guides future empirical research in this area. The article contributes to the literature examining the issue of big data and its governance in local government and smart cities. Points for practitioners Data is a vital part of smart city initiatives. Where the data comes from, who owns it and how it is used are all important questions. Data governance is therefore important and has consequences for the overall governance of the city. The House Model presented in this article provides a means for organizing data governance. It relates questions of data governance to the history and vision of smart city initiatives, and provides a typology organizing these initiatives.
Downside Risk in the Oil Market: Does It Affect Stock Returns in China?

ABSTRACT In this paper, we investigate the impact of downside risk in the oil market on the expected stock returns in China’s A-share market, and find that downside risk positively influences the expected stock returns. This positive influence remains after controlling for various control variables. It is also robust under different stock market conditions and the financial crisis, and with high-frequency data as an alternative measure of downside risk. In addition, the positive relation is consistent across industries regardless of whether they are directly related to natural resources or only indirectly related to oil. We also find evidence of nonlinearity in the relation between the oil and stock markets. The positive relation can be explained by the global risk aversion of investors who are averse to downside risk in the oil market and thus demand compensation in the form of higher expected returns for holding stocks.
Program Capacity for Redesign in Educational Leadership Preparation

Characteristics that contribute to successful redesign and launch of principal preparation programs may be understood collectively as the capacity of those programs. A model of capacity for redesign of principal preparation programs should strike a balance between the technical and professional aspects of teaching and leadership and the cultural and relational aspects of organizations. We surveyed a national sample of program directors and interviewed a purposive sample of those in the midst of redesigning their programs to arrive at a framework of the tools and raw materials programs need to meet the new demands of principal preparation.
INFLUENCE OF RANGING UNCERTAINTY OF TERRESTRIAL LASER SCANNING ON CHANGE DETECTION IN TOPOGRAPHIC 3D POINT CLOUDS

Abstract. Terrestrial laser scanners are commonly used for remotely sensing natural surfaces into 3D point clouds. Time series of such 3D point clouds can be analysed to gain information of surface changes that are induced by Earth surface shaping processes. The atomic unit in time series analysis is a bitemporal change detection and quantification. This should involve an estimation of the minimum quantifiable change, the Level of Detection, to separate signal from noise, e.g. stemming from the measurement. To enable such an estimation through error propagation, a model of the sensing instrument’s measurement uncertainty is required. In this work, we present an investigation on the ranging component of terrestrial laser scanning on this uncertainty and its influence on 3D distances between point clouds of two epochs. Specifically, we analyse the effects of incidence angle, intensity and range for different object materials, and make additional considerations with respect to waveform information returned by the sensor. We estimate a model for the rangefinder uncertainty of a terrestrial laser scanner and apply it on experimental data. The results show that using a sensor-specific model of ranging uncertainty allows an appropriate estimation of the Level of Detection. At a range of 60 m and a rotational displacement of 10°, this Level of Detection ranges between 0.1 mm to 1 mm for a white and a grey surface and up to 5 mm for a black surface. The completeness of the detection of significant change ranges from 60.2 % (black) to 89.8 % (grey) for the proposed method and from 65.5 % to 88.9 % for the baseline, when compared to tachymeter measurements. The similarity between the results is expected and suggests the validity of error propagation for the derivation of the Level of Detection.
Observing land-use/land-cover dynamics in semi-arid environment: Evidence from Damaturu Town and its surrounding lands, Yobe State, Nigeria

The fragile Sudano-Sahelian ecological zone of Nigeria has been classified as a hotspot of land cover change (LCC) that has been suffering from serious anthropogenic and biophysical stresses. Damaturu, being the fastest growing town situated in the region happened to be a victim of this negative development. The purpose of this study is to remotely observe and assess the prevailing land-use/land-cover (LULC) dynamics of Damaturu town and its delicate surrounding lands from the year 1987-2017 study periods. To achieve this, a supervised image classification technique with Maximum Likelihood Classifier (MLC) algorithm was used in ERDAS Imagine version 15 software to classify the three epochs multi-temporal and multi-spectral Landsat imageries (TM 1987, ETM+7 2000 and OLI 2017). The classified LULC maps and their resulting statistics were then used to assess the spatio-temporal aspects of the observed changes by placing the results within the wider context of previous related literature and evidences. Findings revealed that the built-up area has been expanding since 1987 with an annual change rate of 4.5% between 1987-2000, and 5.3% during 2000-2017 respectively. The growth of the town is being accompanied by massive farmlands expansion and vegetal cover (trees and shrubs) lost making the surrounding arable lands seriously disturbed. Thus, if the observed trends continue, the entire studied region will be subjected to severe environmental hazard such as desertification. Overall, the study provides valuable information required for sustainable environmental management.
The Effects of Leadership Styles on Job Performance of Experts through the Mediating Role of Psychological Empowerment (The Case of Agricultural Jihad Organization of Kerman Province)

Job performance is considered one of the most important criteria for developing and measuring the performance of organizations such as the Agricultural Jihad Organization (AJO). The main purpose of the present study was to study the effects of leadership styles on job performance through the mediating role of psychological empowerment. The statistical population was composed of the experts of AJO in Kerman province (N=1418). The sample size was estimated to be 306 experts according to Krejcie and Morgan’s sampling table. The stratified random sampling method was used to select the samples. The research instrument was a questionnaire whose validity was confirmed by a panel of experts in the field of agricultural extension, education, and management. Cronbach's alpha coefficient was employed to examine the reliability of the constructs (0.76≤α≤0.93). The results revealed that the psychological empowerment and the transformational, transactional, and laissez-faire leadership styles had significant effects on job performance. The transformational and transactional leadership styles also had positive and significant effects on psychological empowerment. On the other hand, the laissez-faire leadership style had a negative and significant effect on psychological empowerment. In the end, it should be noted that the independent variables could account for 63 percent of the variance in job performance.
Determinant of Willingness to Pay Health Insurance Contribution to Informal Workers

The purpose of this study was to analyze the willingness to pay contributions of informal workers and the factors that affect the willingness to pay contribution of Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan for informal workers in Brebes Regency. Descriptive research with quantitative approach method is used in this study. Data analysis method uses logistic regression method. The results showed that 71 respondents were willing to pay contribution of Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan for the sustainability of the program and improve the quality of service facilities and 29 respondents said they were not willing to pay. Factors that have a significantly affect on willingness to pay for informal workers are income variable, number of family members, and history of catastrophic disease. Whereas the factors that have no significant on willingness to pay are the last education variable and knowledge. The policy implication for local governments is to increase productivity in the informal sector which aims to increase income of informal workers and re-record Pekerja Bukan Penerima Upah (PBPU) participants who are economically incapable to be transferred to Penerima Bantuan Iuran (PBI) participants. Increase knowledge related to the importance of paying contributions to Pekerja Bukan Penerima Upah (PBPU) participants by Badan Penyelenggara Jaminan Sosial ( BPJS) Kesehatan.