Miracle-dz/UniFAR-FTUs huggingface dataset:
Status quo and determinants on basic public health services of floating population

Objectives: To analyze the status and determinants on public health services of floating population and provide suggestions and strategies for promoting equality in basic public health services. Methods: Data from the2013 National Dynamic Floating Population Monitoring Survey and 2013 Floating Population Public Health,Family Planning,Basic Public Services Survey were used to analyse the utilization and determinants on public health services of floating population. Results: For the floating population,the utilization of basic public health services is relatively lower; the proportion of the population receiving a health exam each year only reached 33. 02%,while the proportion with a health record only reached 23. 84%. Only 5. 15% of the population knew the laws and regulations for occupational disease prevention,while 55. 00% of them had not received any training on occupational safety and health protection. The work of immunization and health management for 0-6 year-old children has progressed smoothly,but there existed a certain percentage of duplicate health cards and duplicate management. Lack of knowledge and lack of time were the main reasons for unused services. A multifactor analysis indicated that gender,age,education,work time every day,scope of migration and inflow time were the main determinants impacting the utilization of public health services for the floating population. Conclusion: The utilization of public health services is inadequate for the floating population; poor health awareness and poor service accessibility were the main determinants behind the utilization of public health services. Awareness of public health services among the floating population must be urgently improved to develop an appropriate public health service mechanism so as to enhance the utilization of public health services among the floating population.
Precessional Drivers of Late Miocene Mediterranean Sedimentary Sequences: African Summer Monsoon and Atlantic Winter Storm Tracks

Cyclic sedimentary patterns in the marine record of the Mediterranean Sea have been consistently correlated with orbitally‐driven shifts in climate. Freshwater input driven by the African summer monsoon is thought to be the main control of such hydrological changes, where the runoff signal is transferred from the eastern to the western Mediterranean. The geological record from the Atlantic margin also contains precession‐driven dilution cycles that have been correlated with the sedimentary sequences in the western and eastern Mediterranean despite the lack of a direct connection with the basin. In these regions, Atlantic winter storms have also been invoked to explain the wet phases. In the absence of seasonally‐resolved proxy data, climate simulations at high temporal resolution can be used to investigate the drivers of Mediterranean hydrologic changes both on precessional and seasonal timescales. Here, we use the results of 22 ocean‐atmosphere‐vegetation simulations through an entire late Miocene precession cycle. These show that the African summer monsoon drives the hydrologic budget in the Eastern Mediterranean during precession minima, while the western marginal basins are generally dominated by local net evaporative loss. During precession minima, the western Mediterranean and the Atlantic margin are also influenced by enhanced winter precipitation from the Atlantic storm tracks. We can, therefore, identify two different moisture sources affecting the circum‐Mediterranean area, characterized by the same phasing with respect to precession, but with opposite seasonality. This supports the interregional correlation of geological sections in these areas, as we show for the Messinian and speculate for other time periods.
Ecosystem physio-phenology revealed using circular statistics

Abstract. Quantifying how vegetation phenology responds to climate variability is a key prerequisite to predicting how ecosystem dynamics will shift with climate change. So far, many studies have focused on responses of classical phenological events (e.g., budburst or flowering) to climatic variability for individual species. Comparatively little is known on the dynamics of physio-phenological events such as the timing of maximum gross primary production (DOYGPPmax), i.e., quantities that are relevant for understanding terrestrial carbon cycle responses to climate variability and change. In this study, we aim to understand how DOYGPPmax depends on climate drivers across 52 eddy covariance (EC) sites in the FLUXNET network for different regions of the world. Most phenological studies rely on linear methods that cannot be generalized across both hemispheres and therefore do not allow for deriving general rules that can be applied for future predictions. One solution could be a new class of circular–linear (here called circular) regression approaches. Circular regression allows circular variables (in our case phenological events) to be related to linear predictor variables as climate conditions. As a proof of concept, we compare the performance of linear and circular regression to recover original coefficients of a predefined circular model for artificial data. We then quantify the sensitivity of DOYGPPmax across FLUXNET sites to air temperature, shortwave incoming radiation, precipitation, and vapor pressure deficit. Finally, we evaluate the predictive power of the circular regression model for different vegetation types. Our results show that the joint effects of radiation, temperature, and vapor pressure deficit are the most relevant controlling factor of DOYGPPmax across sites. Woody savannas are an exception, where the most important factor is precipitation. Although the sensitivity of the DOYGPPmax to climate drivers is site-specific, it is possible to generalize the circular regression models across specific vegetation types. From a methodological point of view, our results reveal that circular regression is a robust alternative to conventional phenological analytic frameworks. The analysis of phenological events at the global scale can benefit from the use of circular statistics. Such an approach yields substantially more robust results for analyzing phenological dynamics in regions characterized by two growing seasons per year or when the phenological event under scrutiny occurs between 2 years (i.e., DOYGPPmax in the Southern Hemisphere).
Process‐Guided Deep Learning Predictions of Lake Water Temperature

The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling framework with a use‐case of predicting depth‐specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation of energy), and model pretraining to initialize the network with synthetic data (water temperature predictions from a process‐based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process‐based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root‐mean‐square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case‐study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.
The Fast Potential Evaluation Method of Enhanced Oil Recovery Based on Statistical Analysis

Based on a large number of empirical statistics of tertiary oil recovery technology in China, including polymer flooding, chemical flooding, gas flooding, in situ combustion, steam flooding, ect. , 22 key reservoir parameters were filterized. Five levels of quantitative screening criteria were developed for different tertiary oil recovery methods. The mean algorithm for the downward approximation and the grey correlation theory were used in this paper to quickly select the appropriate tertiary oil recovery method for the target blocks, which provides a preferred development method for subsequent potential evaluation. In the rapid analogy evaluation method of tertiary oil recovery potential, the total similarity ratio between the target block and the example block is determined. The target block is matched with the appropriate instance block according to the total similarity ratio value, using 80% as the boundary. The ratio of the geological reserves is used to predict the oil recovery interval, the actual annual injection data, and the economic profit, thus quickly predicting the economic potential of the tertiary oil recovery technology in the target block. Currently, our research team has integrated these two methods into the tertiary oil production potential evaluation software EORSYS3.0. The empirical analysis shows that this method is reasonable and the conclusion is reliable. In addition, the actual enhanced recovery value is within the effective range predicted by the method. The method and results of this paper will provide an important decision-making reference for the application and sustainable development of China Petroleum’s main tertiary oil recovery technology in the next 5–10 years.
HEALTH STATUS OF RURAL WOMEN AGRO-FOOD PROCESSORS IN ODOGBOLU LOCAL GOVERNMENT AREA OF OGUN STATE, NIGERIA

Health promotes efficiency in production since it has direct effect on the producers, hence poor health impairs agricultural system. Poor health could lead to decreased working days, workerâ€™s capacity, ability to explore diverse innovation and farming practices. This study was therefore carried out to assess the health status of rural women agro-food processors in Odogbolu Local Government Area, Ogun state, Nigeria. A survey research method was employed for the study and primary data were collected from one hundred and twenty respondents (120) through the use of a interview scheduled using multistage sampling techniques. Descriptive statistics and logit regression model were used for the study analysis. The results of the study revealed that most (83.5%) of the women were involved in more than one processing activities in the study area. A vast majority (91.67%) of the respondents experienced back pain while 87.5 percent reported headache as their common health problem. The result also revealed that self-medication was the highest mode of treatment due to distance to health facility centres. Findings from the logit regression analysis revealed that age (p<0.05), education (p<0.05), time spent (p<0.01), training (p<0.01) and wearing of protective garments (p<0.01) were the significant determinants of health status of the women processors in the study area. The study therefore concluded and recommended that women agro-food processors should be trained to become aware of the implication of processing activities on their health. There is need for government to make health care affordable and be within the reach of the farming community.
Current human resource challenges in the Caribbean hospitality industry

Provides an overview on the current human resource challenges facing the Caribbean hospitality industry, drawing on a presentation made at the second annual Caribbean roundtable discussion, held in Barbados during April 2004, attended by 33 participants and observers from industry and academia. The outcomes are reported here and in the second of two articles, “Future human resource challenges in the Caribbean hospitality industry”.
Unprecedented Northern Hemisphere Tropical Cyclone Genesis in 2018 Shaped by Subtropical Warming in the North Pacific and the North Atlantic

Northern Hemisphere tropical cyclone (TC) genesis (TCG) frequency in June‐September of 2018 reached a record high since 1965. This unprecedented TCG was mainly driven by the North Pacific (NP) and the subtropical North Atlantic (NA). TCs in the western North Pacific (WNP) predominately took a northward‐recurving track, resulting in the highest number of named storm days in the subtropical WNP on record. TCs in the eastern North Pacific propagated anomalously westward with three Category 4–5 hurricanes reaching the central North Pacific. The unprecedented TCG in the NP was caused by a persistent weakening of the NP subtropical high that was tightly coupled with the subtropical NP sea surface temperature (SST) warming. In the NA, enhanced TCG was mainly found in the subtropics owing to a favorable large‐scale environment forced by subtropical SST warming. The result here has important implications for understanding variability in TC activity on the hemisphere‐scale.
Variable‐discharge‐river macroforms in the Sunnyside Delta Interval of the Eocene Green River Formation, Uinta Basin, USA

An outcrop dataset from the early Eocene Sunnyside Delta Interval of the Green River Formation in the Uinta Basin, Utah, USA, documents alluvial channel lithosomes. The abundance of Froude supercritical‐flow sedimentary structures, together with an abundance of high‐deposition‐rate sedimentary structures, in‐channel bioturbation and pedogenic modification, in‐channel muds and thick soft‐clast conglomerates, identify these lithosomes as deposits of variable‐discharge rivers. These recognition criteria are part of an emerging facies model for variable‐discharge rivers. This facies model, however, yet lacks robust recognition criteria for macro‐scale or bar‐scale stratal patterns of variable‐discharge rivers. This study presents a dataset that corroborates some known stratal patterns and provides examples of hitherto unknown bar‐scale stratal patterns of variable‐discharge rivers, including: (i) low‐angle downstream‐accretion sets that may form as washed‐out sheets in high sediment supply conditions or downstream of hydraulic jumps; (ii) high‐angle upstream‐accretion sets that imply deposition from systematically upstream‐migrating channel‐scale hydraulic jumps (cyclic steps); (iii) concave‐up, upward‐flattening high‐angle downstream‐accretion sets that are consistent with aggradation in channel‐scale hydraulic‐jump scours; (iv) upstream‐accretion and lateral‐accretion sets that may be linked to high‐magnitude flood reworking of point bars; and (v) aggradation or vertical‐accretion sets of ambiguous origin. These unconventional stratal patterns are compared to the established bar strata, such as those formed by point bars and braid bars and a discussion is provided on formative conditions for the here documented unconventional strata. This work highlights a need for further studies on the effect of discharge variability on bar formation and on the link between river morphology and bar types.
Minimasi Waste dengan Pendekatan Value Stream Mapping

The problem that occurs in the packaging bottle production process is the amount of waste in it. Therefore, this study aims to make improvements in reducing waste of production time and provide recommendations for managing the production process so that in the future can be used as a reference in the production process optimization. The method used in this study is descriptive analysis conducted by examining the work and activities of an object. The results of the study show that in the production process, there was still a form of waste which, when viewed from the seven waste concept in the lean manufacturing system, there are some of the most dominant wastes such as inventory, waiting, process, overproduction, and defect. After improvement of the current mapping, the waste that occurs such as inventory, process, overproduction, waiting, and defects that occur in the production line reduced from the total lead time of 2.1 days with seven operators to 0.9 days with ten operators. Furthermore, the cycle time value of the current value stream mapping was 120.9 seconds, while the cycle time value of the proposed value stream mapping was 72 seconds. This shows an increase in productivity.
Responses of ocean biogeochemistry to atmospheric supply of lithogenic and pyrogenic iron-containing aerosols

Abstract Atmospheric supply of iron (Fe) to the ocean has been suggested to regulate marine productivity in large parts of the world’s ocean. However, there are still large uncertainties regarding how the atmospheric inputs of dissolved Fe (DFe) influence the seawater DFe concentrations and thus net primary production (NPP). Here, we use an atmospheric chemistry model and two ocean biogeochemistry models with high (Model H) and low (Model L) sensitivities to atmospheric sources of DFe to explore the responses of ocean biogeochemistry to different types of atmospheric inputs of DFe: mineral dust and combustion aerosols. When both Fe content in mineral dust of 3.5% and Fe solubility of 2% are prescribed in sensitivity simulations, the ocean models overestimate DFe concentration in the surface ocean downwind from the North African and East Asian dust plumes. Considering different degrees of atmospheric Fe processing reduces the overestimates of DFe concentration in the North Atlantic and North Pacific. The two ocean biogeochemistry models show substantially different magnitudes of responses to the atmospheric input of DFe. The more detailed Model H shows a much higher sensitivity of NPP to the change in combustion aerosols than to mineral dust, regardless of relative inputs of the sedimentary sources. This finding suggests that pyrogenic Fe-containing aerosols are more important sources of atmospheric bioavailable Fe for marine productivity than would be expected from the small amount of DFe deposition, especially in the Pacific and Southern oceans.
Cloud Ice Processes Enhance Spatial Scales of Organization in Arctic Stratocumulus

Stratocumulus clouds around the globe tend to organize into cellular patterns, a phenomenon that has been primarily studied for the subtropical trade wind region. However, stratocumulus are also prevalent in high latitudes, where they often occur as mixed‐phase clouds. Yet little research has been conducted regarding mechanisms of cloud organization in the mixed‐phase regime. In cloud‐resolving model simulations we investigate the processes driving organization in open‐cell mixed‐phase stratocumuli. Similar to warm‐phase clouds, mixed‐phase clouds develop a subcloud circulation of evaporated/sublimated precipitation, cold pool formation, and consecutive updrafts driving new convective cells. For a larger ice to liquid water ratio, we find locally stronger precipitation and larger cloud cells. Hence, a higher concentration of ice nucleating particles can induce a breakup of the stratocumulus organization, with implications for the radiative balance at the surface. A decrease in cloud condensation nuclei concentration is also found to intensify precipitation and impact cloud organization.
Fruit quality in Hass avocado and its relationships with different growing areas under tropical zones

Submitted on March 19 , 2019 and accepted on September 09 , 2019. 1 This research was funded by “Sistema General de Regalias del Gobierno Colombiano and Secretaría de Agricultura de Antioquia” in project: “Desarrollo tecnologico, productivo y comercial del aguacate en el departamento de Antioquia”, with code No. 4600001078. 2 Corporación Colombiana de Investigación Agropecuaria, Agrosavia, La Selva, Ríonegro, Colombia. juanchenaorojas@gmail.com; jlopezh@agrosavia.co 3 Universidad Nacional de Colombia, Escuela de Biociencias, Facultad de Ciencias, Medellín, Colombia. nwosorio@unal.edu. co 4 Universidad Nacional de Colombia sede Bogotá, Facultad de Ciencias Agrarias ,Departamento de Agronomía, Bogotá, Colombia . jgramireg@unal.edu. co *Corresponding author : juanchenaorojas@gmail.com Fruit quality in Hass avocado and its relationships with different growing areas under tropical zones 1
Parametric study by means of 3D CFD to improve the airflow pattern and temperature distribution in data center rooms

The processing efficacy and energy efficiency of data centers (DC) is directly related with the cooling performance of the air-conditioning systems. The cooling effectiveness depends on airflow pattern and temperature distribution. This paper presents the parametric study of three-dimensional (3D) computational fluid dynamics (CFD) models to improve these technical characteristics. In this case study the most suitable thermal load, as deemed by the organization, of the heat flow boundary condition is simulated and studied for maximum and minimum airflow. The analysis of the numerical results provides a prediction of the thermal performance, i.e., the lower values and spatial gradients (hot spots) of air temperature and velocity while maintaining the computational processing requirements. These results allow the development of an optimized CFD model for setting up the operational parameters of CRAC systems for DC rooms. observed at the extremities of the lines of the racks and occur due to the improper airflow in these locations. Both case studies confirm this scenario. The poor air flow at the extremities of the lines of the racks occurs due to a deficient layout of the room. This study confirmed that the layout of the room is not ideal. A solution could be the removing at least a few racks from both lines’ extremities in order to enable a more adequate air flow in that location.
Modeling Travel Time Distributions of Preferential Subsurface Runoff, Deep Percolation and Transpiration at A Montane Forest Hillslope Site

Residence and travel times of water in headwater catchments, or their smaller spatial units, such as individual hillslopes, represent important descriptors of catchments’ hydrological regime. In this study, travel time distributions and residence times were evaluated for a montane forest hillslope site. A two-dimensional dual-continuum model, previously validated on water flow and oxygen-18 data, was used to simulate the seasonal soil water regime and selected major rainfall–runoff events observed at the hillslope site. The model was subsequently used to generate hillslope breakthrough curves of a fictitious conservative tracer applied at the hillslope surface in the form of the Dirac impulse. The simulated tracer breakthroughs allowed us to estimate the travel time distributions of soil water associated with the episodic subsurface stormflow, deep percolation and transpiration, thus yielding partial travel time distributions for the individual discharge processes. The travel time distributions determined for stormflow were dominated by the lateral component of preferential flow. The stormflow median travel times, calculated for nine selected rainfall–runoff events, varied considerably—ranging from 1 to 17 days. The estimated travel times were significantly affected by the temporal rainfall patterns and antecedent soil moisture distributions. The residence times of soil water, evaluated for three consecutive growing seasons, ranged from 29 to 37 days. The analysis reveals the interplay of soil water storage and discharge processes at the hillslope site of interest. The applied methodology can be used for the evaluation of runoff dynamics at the hillslope and catchment scales as well as for the quantification of biogeochemical transformations of dissolved chemicals.