Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonal Papyrus Biomass Harvesting Patterns and its Implications on Productivity in Nyando Floodplain Wetland, Lake Victoria Basin, Kenya

Papyrus production not only maintains the structure and function of the wetland but also meets the needs of the surrounding communities who rely on them directly. Seasonal changes in rainfall patterns has influenced the productivity of Nyando wetland yet there is need to understand the influence of such changing conditions on the provisioning services. Although there have been studies done in these wetlands, there is inadequate understanding on the implication of biomass harvesting on the growth attributes of the papyrus plant in the face of changing seasons. This study focused on Nyando floodplain wetland located in the Eastern part of the shores of Lake Victoria which is a lifeline to many rural communities living around the lake. Papyrus biomass harvesting patterns were assessed in two study sites of Nyando wetland and at different seasons in order to determine its implication on papyrus productivity. Participatory tools, field survey, interviews, observation, field measurements and laboratory measurements were used. The results show the area harvested was different between sites and between seasons in Wasare (107.9 ± 2.7 m 2 ) dry and wet season (88.8 ± 3.1 m 2 ). Biomass and height were critical growth attributes that were affected by harvesting frequency and changes in rainfall patterns. Understanding harvesting patterns is important for planning and management of wetland ecosystem so as to continue providing materials while maintaining the structure and function of the wetland.
Do PCAOB Inspections of Foreign Auditors Improve Global Financial Reporting Comparability?

This study investigates whether Public Company Accounting Oversight Board (PCAOB) inspections of foreign auditors affect global financial reporting comparability. Foreign auditors may adjust audit methodologies to address PCAOB inspection findings, which could affect financial reporting of local clients. Exploiting both within- and across-country variation in PCAOB inspections, we find that non-US-listed foreign companies’ financial reporting becomes more comparable to their US and non-US industry peers after their auditors undergo an initial PCAOB inspection. Subsample tests suggest that results are driven by auditors that satisfactorily address deficiencies and auditors that do not publicly push back against deficiencies. The effects exist both within and across global audit networks and are dampened after local audit regulators begin inspection programs. Overall, our evidence suggests that the PCAOB international inspection program affects audit methodologies of inspected auditors in a consistent way, improving comparability across jurisdictions and auditors.
Traffic data reconstruction based on compressive sensing with neighbor regularization

The production and collection of the mass traffic data in the vehicle network will result in wasted bandwidth and data transmission delay. The mobile edge computing (MEC) technology is able to reduce the transmission cost and provide fast interactive response. However, the amount of data between roadside units (RSUs) and MEC servers has not decreased. Compressive sensing (CS) technology can reduce the sampling frequency and reconstruct the signal with even fewer samples than the sampling theorem requires. Therefore, in this article, we use CS technology to reduce the data in the “last mile” of traffic edge computing network. We propose two traffic data reconstruction models, which use different neighbor regularization methods in the objective function of CS reconstruction model. Different from the previous studies, we leverage the low‐rank nature and the neighbor relationship between detectors to improve the reconstruction accuracy of different missing scenes. To validate the improved reconstruction models, we have carried out extensive experiments based on the actual traffic flow data of the freeway system under different loss rates and loss patterns. The missing data are caused by reduced sampling frequency and accidental transmission loss so that it is closer to the real fact. The experimental results show that even if the traffic data from the RSUs to MEC servers are decreased by 50%, the complete data can be reconstructed accurately.
Childhood sleep disorders in premature infants that hospitalized in neonatal intensive care unit in neonatal period

Aim: Children requiring intensive care in the neonatal period have more fine motor injuries, learning difficulties, eating disorders and sleeping problems. Sleep disorder rate is about 10-30% in children who had no problem in newborn period. We aimed to investigate the rate of sleep disorder in children who were hospitalized in the neonatal intensive care unit during the neonatal period. Material and Methods: Fourty-six patients hospitalized in neonatal intensive care unit and still followed in outpatient policlinic at Çukurova University were enrolled in to the study. Children’s Sleep Habits Questionnaire was performed to evaluate sleep resistance, delay in fall into sleep, duration of sleep, sleep anxiety, parasomnia, midnight awakening and daily sleepiness. Results: Children were 6.64±1.18 years old. They were healthy and had no neurological sequela. None of the parents complained about sleep disorders. However, 20 of the 46 (43.47%) children had sleep disorder (Sleep disorder group). Twenty-six children had no sleep disorder (No sleep disorder group). There isn’t any statistically difference between the groups that terms of gestational age, birth weight, ventilator support, gender (p>0.05). Conclusion: Although there isn’t any significant difference between groups, sleep disorder rate is higher compared to normal population’s rates reported in the previous studies. Infants discharged from neonatal intensive care unit should be under evaluation also for sleep disorder.
Intention to quit tobacco and Perceptions About Enhanced Pictorial Warnings on Tobacco Products Among Male College Students in Puducherry- Mixed-Methods Study.

Background: Framework Convention on Tobacco Control (FCTC) recognized pictorial health warnings on tobacco products as a powerful public health intervention tool to communicate health risks and to bring about a behavioral change like quitting and reduction in tobacco consumption Objectives: To explore the perceptions on pictorial warnings on tobacco products and to find out the prevalence of ever and current tobacco product users, influencing factors and barriers in intention to quit tobacco among male college students. Material and Methods: An Exploratory Mixed-Method study [Two Focus Group Discussions (FGDs) among students followed by survey among 450 male college students] was carried out in an engineering college in Puducherry during December 2016February 2017. Results: As perceived by the students, the new pictorial warnings when compared to the old ones had better precision of pictures, convey the message better and elicit fear among the users. Out of 450 participating students, 57 (12.7%) students were ever users and 39 (8.7%) were current users of tobacco. Among current users, 30 (76.9%) has intention to quit the habit. Out of 450 students, 184 (41.1%) students have noticed the pictorial warnings and 111 (24.7%) of them stated that it will encourage users in quitting. Conclusion: Though the new pictorial warnings bring a sense of fear on initiators, it fails to create an impact on chronic users. Majority of the current users has intention to quit tobacco and would like to follow a healthy lifestyle.
Blockchain and Business Ethics

This paper provides, from a business ethics perspective, a basic clustering of the morally (a) favorable, (b) unfavorable, and (c) ambivalent dimensions of blockchain technology and its various emergent applications. Instead of proffering specific assessments on particular aspects of blockchain&#8208;based business models, we aim to offer an initial overview that charters the territory so that future research can bring about such moral assessments in an informed and orderly fashion. The main contribution of this paper lies in identifying several morally ambivalent dimensions of blockchain technology, which we finally link to two strands of business ethics research: ethical and legal aspects of legislation as well as a link to Habermasian corporate social responsibility theory arguing for transparent data production and consumption on the blockchain. We conclude that future research is necessary for moral assessment of the ambivalent cases, since their ethical evaluation changes depending on whether one analyzes them through the lenses of utilitarianism, contractarianism, deontology, and virtue ethics, respectively.
Identification of Biology Student’s Misconception in Makassar State University on Cell Biology by Applying Two-Tier MCQs Method

This study aims to know the level of understanding of UNM student’s experiencing misconceptions, understand the concept and do not understand the concept about cell biology using Two-Tier MCQs method. This research includes descriptive research. In this study, the Two-Tier MCQs method to identify student’s misconceptions. Population in this research is all student of study program of biology of UNM class 2015. Samples in this research as many as 20 people who tried randomly. Instruments used to test Two-Tier MCQs and interview methods to determine the causes of misconceptions. The result of data analysis shows that the highest misconception is in the mate rial structure and function of mitochondria and the lowest is in the cell cycle material.
Bias Correction of Airborne Thermal Infrared Observations Over Forests Using Melting Snow

Uncooled thermal infrared (TIR) imagers, commonly used on aircraft and small unmanned aircraft systems (UAS, “drones”), can provide high‐resolution surface temperature maps, but their accuracy is dependent on reliable calibration sources. A novel method for correcting surface temperature observations made by uncooled TIR imagers uses observations over melting snow, which provides a constant 0 °C reference temperature. This bias correction method is applied to remotely sensed surface temperature observations of forests and snow over two mountain study sites: Laret, Davos, Switzerland (27 March 2017) in the Alps, and Sagehen Creek, California, USA (21 April 2017) in the Sierra Nevada. Surface temperature retrieval errors that arise from temperature‐induced instrument bias, differences in image resolution, retrieval of mixed pixels, and variable view angles were evaluated for these forest snow scenes. Applying the melting snow‐based bias correction decreased the root‐mean‐square error by about 1 °C for retrieving snow, water, and forest canopy temperatures from airborne TIR observations. The influence of mixed pixels on surface temperature retrievals over forest snow scenes was found to depend on image resolution and the spatial distribution of forest stands. Airborne observations over the forests at Sagehen showed that near the edges of TIR images, at more than 20° from nadir, the snow surface within forest gaps smaller than 10 m was obscured by the surrounding trees. These off‐nadir views, with fewer mixed pixels, could allow more accurate airborne and satellite‐based observations of canopy surface temperatures.
Prediction of heart disease using data mining techniques: A Case study

Data mining is the process of rearranging through large datasets to identify patterns and establish relationships between them to solve problems through data analysis. Data mining tools allow enterprise to predict future trends. A pattern is useful, interesting and easily understood by human if it is valid for a given test and with some degree of certainty. Though the data amount generated in predicting heart disease is huge and complex advance data mining techniques can process the data. Heart disease is one the disease that causes the maximum causalities. This problem is identified long before but no proper actions been taken to combat this problem. This paper set out goal to finding which method would be best for predicting the diseases using data of four different dataset from four different places. Therefore, this article tries to finding which method would be best for predicting the diseases using data of four different datasets from four different places. This is a comparative study on the efficiency of different data mining techniques such as Decision Tree (DT), K-Nearest Neighbor (kNN), Naive Bayes, Logistic Regression in predicting heart diseases. The Data Mining techniques are analyzed and the accuracy of prediction is noted for each method used. The result showed that heart diseases can be predicted with accuracy of above 80%.
Inflation co-movement in the Asean countries

We conduct frequency domain analyses to document some empirical regularities on international inflation co-movement in the ASEAN countries. The estimated cohesion index, a measure of co-movement in frequency domain, shows that inflation co-movement is stronger in the long run than in the short run, which has not been examined in depth in the literature using time domain analysis. There is strong evidence that inflation co-movement within the ASEAN countries is weaker than inflation co-movement within the G7 countries. We also find that the inflation in an ASEAN country, on average, fluctuates more closely with the inflation in the G7 countries than with the inflations in other neighboring ASEAN countries, implying that geographical proximity is not important in inflation synchronization. These empirical findings suggest that the inflation in advanced countries is likely to be the main source of international inflation co-movement, which is more important than regional factor in explaining the fluctuations of inflation in the ASEAN countries.
Exchange rates and firm export performance in South Africa

This paper uses detailed firm transaction data on manufactured exports to analyse the dilution of the real exchange rate-export relationship in South Africa over the period 2010 to 2014.Our empirical results show that firms that are larger, have higher export shares in destination markets, and import are more likely to raise the domestic currency price of their exports in response to a depreciation, and consequently display weaker export quantity responses.The exchange rate responsiveness is also weaker for exporters of resource-based manufactured products and those that export outside Africa. South African manufactured exports are highly concentrated among a few large firms that rely heavily on imported intermediate inputs and predominantly export resource-based products.Consequently, these results provide an explanation for the low aggregate export response to the sustained depreciation over the period 2010 to 2014.
UAV Laser scanning technology: a potential cost-effective tool for micro-topography detection over wooded areas for archaeological prospection

ABSTRACT Airborne laser scanning (ALS) has recently been identified as a potential tool in topographic mapping for archaeological prospection. However, most existing applications in this field refers to manned ALS systems, for which the high operation and maintenance costs limits its application in small-scale archaeological investigation. In this paper, we conducted an exploratory study on the application of the unmanned aerial vehicle (UAV) laser scanning (ULS) system in ancient micro-topography detection over wooded areas. Compared with manned ALS technology, we analyzed the advantages and potentials of ULS technology for archaeological applications. Then we outlined existing mainstream survey-grade UAV-based laser scanners, data processing and visualization approaches. Furthermore, we performed case studies in three cultural heritage sites in Zhejiang Province, China using two representative mainstream survey-grade ULS systems. Results were then verified by an in-site investigation. Finally, the correct selection of ULS devices, the planning of data acquisition missions and the use of appropriate data processing methods specifically for archaeological prospection were discussed. This paper provides a cost-effective and flexible solution for micro-topography detection in wooded areas. ULS technology, as demonstrated here, can be an important supplement to existing archaeological investigation methods, particularly for small-scale areas, and has promising prospects in archaeological applications.
Indonesian community welfare levels clustering using the fuzzy subtractive clustering (FCM) method

Clustering is a technique used to classify objects or cases into groups based on their similarity, called clusters or groups. Objects in each group tend to resemble each other and differ greatly (not the same) with objects from other clusters. Public welfare is a condition of fulfilling the material, spiritual and social needs of citizens in order to be able to live properly. Fuzzy Subtractive Clustering (FSC) method is a clustering algorithm that can form the number and centroid of clusters in accordance with data conditions. This study aims to determine the FSC results in grouping the level of welfare of the Indonesian people in 2017. The testing results of the cluster validity index show 2 values of Partition Entropy and Classification Entropy forming into 2 clusters that have the best value, indicating that the provincial group has a high welfare level and the provincial group has a low welfare level.
Management of complex long bone nonunions using limb reconstruction system

Background: Management of complex nonunions is difficult due to the presence of infection, deformities, shortening and multiple surgeries in the past. Complex nonunions are traditionally managed by Ilizarov fixation. The disadvantages of Ilizarov are poor patient compliance, inconvenience of the frame and difficult frame construction. We conducted a study on 30 long bone complex nonunions treated by the limb reconstruction system (LRS). Materials and Methods: Between April 2009 and September 2012, we treated 30 cases of complex nonunion of long bone with the LRS. 28 were male and 2 females. Average shortening was 5.06 cm and 14 cases presented with infected implants. Initially we managed with implant removal, radical debridement followed by fixation with the LRS. In 16 cases, corticotomy and lengthening was done. The average duration of treatment was 9.68 months. We compressed the fracture site at the rate of 0.25 mm per day for 1-2 weeks and distracted the corticotomy at the rate of 1 mm/day till lengthening was achieved. Result: The union occurred in 89.28% cases and eradication of infection in 91.66% cases. Average lengthening done was 4.57 cm. We had 79% excellent, 11% good and 10% poor bony result and fnctional result was excellent in 40% cases, good in 50% and failure in 10% cases using ASAMI scoring system. Conclusion: LRS is an alternative to the Ilizarov fixation in their management of complex nonunion of long bones. It is less cumbersome to the patient and more surgeon and patient friendly.
Assessing the Teaching Quality of Economics Programme: Instructor Course Evaluations

Introduction. In recent years, measuring the efficiency and effectiveness of higher education has become a major issue. Most developed countries are using national surveys to measure teaching and assessment as key determinants of students’ approaches to learning which have direct effect on the quality of their learning outcomes. In less developed countries, there does not exist a national survey. This paper aims to propose an original questionnaire assessing the teaching quality. The specifics of this questionnaire, termed as the Instructor Course Evaluation Survey, is that it addresses three main dimensions, such as: Learning Resources, Teaching Effectiveness, and Student Support.Materials and Methods. The paper opted for an analytic study using 3,776 completed questionnaires. This is a case study applied to the students enrolled in economics program in a private university in Albania. The Instructor Course Evaluation Survey design was supported by the literature review, identifying the three main dimensions included in the questionnaire. The reliability was tested with Cronbach’s alpha and with Confirmatory Factor Analysis. The use of Confirmatory Factor Analysis helps in identifying issues of multi-dimensionality in scales.Results. The paper provides empirical insights into the assessing methodology and brings a new model of it. The finding suggests that Learning Resources, Teaching Effectiveness and Student Support increase the quality of teaching. Because of the chosen research target group, students from economics program, the research results may not be generalizable. Therefore, researchers are encouraged to test the proposed statements further.Discussion and Conclussion. This paper fulfills an identified need to propose an original and simple questionnaire to be used from different universities and programs to measure the quality of teaching.
Beyond Wealth and Health: The Social Environment as a Protective Factor for Cognitive Development of Children in Nicaragua

ABSTRACT We examine the contributions of the environmental context on cognitive development in a representative sample of children (24–59 month-olds) in Nicaragua. Multivariate regression models revealed that children who experienced high levels of structure in the home, encountered more social interaction, and were enrolled in early education programs, exhibited higher cognitive skills. These factors were related to, but better accounted for, variability in children’s skills than the socio-economic endowment of the home or maternal education levels – the two most commonly used proxies to quantify children’s early contexts. Results from this study provide validation of the relation between children’s proximal early social environment and cognitive outcomes in a novel context. The results also provide motivation for deeper empirical investigation in the specific aspects of the home environment that may be central to providing resilience to low wealth populations, and to reducing inequality in developmental skills.
Using conjoint constitution to understand responses to slow-moving environmental change: the case of mountain pine beetle in north-central Colorado

ABSTRACT A growing body of work exists on the social implications of forest insect disturbances. However, although increasingly explored, there remains a need to further understand social responses to large-scale forest insect disturbances over time. This requires longitudinal investigations into people’s conceptualizations of their changing local environments, associated risk perceptions, and forest management preferences in the context of forest insect disturbance-related changes to the landscape. Within the context of the mountain pine beetle outbreak that affected approximately 3.4 million acres of Colorado forests, this study is a ten-year follow-up to a 2006–2007 study that explored local responses to the outbreak. Using qualitative interviews with 54 informants from nine north-central Colorado communities affected by the outbreak, this paper incorporates a social construction approach known as ‘conjoint constitution’ to examine the interplay between slow-moving biophysical changes to the landscape as a result of the outbreak, communities’ understandings and risk perceptions of these changes, as well as shifts in locals’ thinking about forest management.